Articles | Volume 6, issue 3
https://doi.org/10.5194/gmd-6-687-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-687-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
24 May 2013
Model evaluation paper |
| 24 May 2013
The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate
M. Bentsen
Uni Climate, Uni Research Ltd, P.O. Box 7810, 5020 Bergen, Norway
Bjerknes Centre for Climate Research, P.O. Box 7810, 5020 Bergen, Norway
I. Bethke
Uni Climate, Uni Research Ltd, P.O. Box 7810, 5020 Bergen, Norway
Bjerknes Centre for Climate Research, P.O. Box 7810, 5020 Bergen, Norway
J. B. Debernard
Norwegian Meteorological Institute, P.O. Box 43, Blindern, 0313 Oslo, Norway
T. Iversen
Norwegian Meteorological Institute, P.O. Box 43, Blindern, 0313 Oslo, Norway
Dept. of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0315 Oslo, Norway
now at: ECMWF, Shinfield Park, Reading, RG2 9AX, UK
A. Kirkevåg
Norwegian Meteorological Institute, P.O. Box 43, Blindern, 0313 Oslo, Norway
Ø. Seland
Norwegian Meteorological Institute, P.O. Box 43, Blindern, 0313 Oslo, Norway
H. Drange
Bjerknes Centre for Climate Research, P.O. Box 7810, 5020 Bergen, Norway
Geophysical Institute, University of Bergen, P.O. Box 7803, 5020 Bergen, Norway
C. Roelandt
Uni Climate, Uni Research Ltd, P.O. Box 7810, 5020 Bergen, Norway
Bjerknes Centre for Climate Research, P.O. Box 7810, 5020 Bergen, Norway
I. A. Seierstad
Norwegian Meteorological Institute, P.O. Box 43, Blindern, 0313 Oslo, Norway
Dept. of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0315 Oslo, Norway
now at: Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology, P.O. Box 3640, 76021 Karlsruhe, Germany
J. E. Kristjánsson
Dept. of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0315 Oslo, Norway
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Atmos. Chem. Phys., 23, 523–549, https://doi.org/10.5194/acp-23-523-2023, https://doi.org/10.5194/acp-23-523-2023, 2023
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Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
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A climate model is used to evaluate how the radiative forcing (RF) associated with black carbon (BC) emissions depends on the latitude, longitude, and seasonality of emissions. It is found that both the direct RF (BC absorption of solar radiation in air) and snow RF (BC absorption in snow/ice) depend strongly on the emission region and season. The results suggest that, for a given mass of BC emitted, climatic impacts are likely to be largest for high-latitude emissions due to the large snow RF.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Julia Bruckert, Gholam Ali Hoshyaripour, Ákos Horváth, Lukas O. Muser, Fred J. Prata, Corinna Hoose, and Bernhard Vogel
Atmos. Chem. Phys., 22, 3535–3552, https://doi.org/10.5194/acp-22-3535-2022, https://doi.org/10.5194/acp-22-3535-2022, 2022
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Volcanic emissions endanger aviation and public health and also influence weather and climate. Forecasting the volcanic-plume dispersion is therefore a critical yet sophisticated task. Here, we show that explicit treatment of volcanic-plume dynamics and eruption source parameters significantly improves volcanic-plume dispersion forecasts. We further demonstrate the lofting of the SO2 due to a heating of volcanic particles by sunlight with major implications for volcanic aerosol research.
Ingo Bethke, Yiguo Wang, François Counillon, Noel Keenlyside, Madlen Kimmritz, Filippa Fransner, Annette Samuelsen, Helene Langehaug, Lea Svendsen, Ping-Gin Chiu, Leilane Passos, Mats Bentsen, Chuncheng Guo, Alok Gupta, Jerry Tjiputra, Alf Kirkevåg, Dirk Olivié, Øyvind Seland, Julie Solsvik Vågane, Yuanchao Fan, and Tor Eldevik
Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, https://doi.org/10.5194/gmd-14-7073-2021, 2021
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The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It adds data assimilation capability to the Norwegian Earth System Model version 1 (NorESM1) and has contributed output to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). We describe the system and evaluate its baseline, reanalysis and prediction performance.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
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Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Anne L. Morée, Jörg Schwinger, Ulysses S. Ninnemann, Aurich Jeltsch-Thömmes, Ingo Bethke, and Christoph Heinze
Clim. Past, 17, 753–774, https://doi.org/10.5194/cp-17-753-2021, https://doi.org/10.5194/cp-17-753-2021, 2021
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This modeling study of the Last Glacial Maximum (LGM, ~ 21 000 years ago) ocean explores the biological and physical changes in the ocean needed to satisfy marine proxy records, with a focus on the carbon isotope 13C. We estimate that the LGM ocean may have been up to twice as efficient at sequestering carbon and nutrients at depth as compared to preindustrial times. Our work shows that both circulation and biogeochemical changes must have occurred between the LGM and preindustrial times.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
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Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, and Christoffer A. Elo
Nonlin. Processes Geophys., 28, 61–91, https://doi.org/10.5194/npg-28-61-2021, https://doi.org/10.5194/npg-28-61-2021, 2021
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An unprecedented amount of rainfall data is available nowadays, such as ensemble model output, weather radar estimates, and in situ observations from networks of both traditional and opportunistic sensors. Nevertheless, the exact amount of precipitation, to some extent, eludes our knowledge. The objective of our study is precipitation reconstruction through the combination of numerical model outputs with observations from multiple data sources.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
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Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, https://doi.org/10.5194/gmd-13-6165-2020, 2020
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The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
Camilla W. Stjern, Bjørn H. Samset, Olivier Boucher, Trond Iversen, Jean-François Lamarque, Gunnar Myhre, Drew Shindell, and Toshihiko Takemura
Atmos. Chem. Phys., 20, 13467–13480, https://doi.org/10.5194/acp-20-13467-2020, https://doi.org/10.5194/acp-20-13467-2020, 2020
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The span between the warmest and coldest temperatures over a day is a climate parameter that influences both agriculture and human health. Using data from 10 models, we show how individual climate drivers such as greenhouse gases and aerosols produce distinctly different responses in this parameter in high-emission regions. Given the high uncertainty in future aerosol emissions, this improved understanding of the temperature responses may ultimately help these regions prepare for future changes.
Augustin Mortier, Jonas Gliß, Michael Schulz, Wenche Aas, Elisabeth Andrews, Huisheng Bian, Mian Chin, Paul Ginoux, Jenny Hand, Brent Holben, Hua Zhang, Zak Kipling, Alf Kirkevåg, Paolo Laj, Thibault Lurton, Gunnar Myhre, David Neubauer, Dirk Olivié, Knut von Salzen, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 20, 13355–13378, https://doi.org/10.5194/acp-20-13355-2020, https://doi.org/10.5194/acp-20-13355-2020, 2020
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We present a multiparameter analysis of the aerosol trends over the last 2 decades in the different regions of the world. In most of the regions, ground-based observations show a decrease in aerosol content in both the total atmospheric column and at the surface. The use of climate models, assessed against these observations, reveals however an increase in the total aerosol load, which is not seen with the sole use of observation due to partial coverage in space and time.
Xiaoning Xie, Gunnar Myhre, Xiaodong Liu, Xinzhou Li, Zhengguo Shi, Hongli Wang, Alf Kirkevåg, Jean-Francois Lamarque, Drew Shindell, Toshihiko Takemura, and Yangang Liu
Atmos. Chem. Phys., 20, 11823–11839, https://doi.org/10.5194/acp-20-11823-2020, https://doi.org/10.5194/acp-20-11823-2020, 2020
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Black carbon (BC) and greenhouse gases (GHGs) enhance precipitation minus evaporation (P–E) of Asian summer monsoon (ASM). Further analysis reveals distinct mechanisms controlling BC- and GHG-induced ASM P–E increases. The change in ASM P–E by BC is dominated by the dynamic effect of enhanced large-scale monsoon circulation, the GHG-induced change by the thermodynamic effect of increasing atmospheric water vapor. This results from different atmospheric temperature feedbacks due to BC and GHGs.
María A. Burgos, Elisabeth Andrews, Gloria Titos, Angela Benedetti, Huisheng Bian, Virginie Buchard, Gabriele Curci, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Anton Laakso, Julie Letertre-Danczak, Marianne T. Lund, Hitoshi Matsui, Gunnar Myhre, Cynthia Randles, Michael Schulz, Twan van Noije, Kai Zhang, Lucas Alados-Arboledas, Urs Baltensperger, Anne Jefferson, James Sherman, Junying Sun, Ernest Weingartner, and Paul Zieger
Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, https://doi.org/10.5194/acp-20-10231-2020, 2020
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We investigate how well models represent the enhancement in scattering coefficients due to particle water uptake, and perform an evaluation of several implementation schemes used in ten Earth system models. Our results show the importance of the parameterization of hygroscopicity and model chemistry as drivers of some of the observed diversity amongst model estimates. The definition of dry conditions and the phenomena taking place in this relative humidity range also impact the model evaluation.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
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The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Christopher J. Smith, Ryan J. Kramer, Gunnar Myhre, Kari Alterskjær, William Collins, Adriana Sima, Olivier Boucher, Jean-Louis Dufresne, Pierre Nabat, Martine Michou, Seiji Yukimoto, Jason Cole, David Paynter, Hideo Shiogama, Fiona M. O'Connor, Eddy Robertson, Andy Wiltshire, Timothy Andrews, Cécile Hannay, Ron Miller, Larissa Nazarenko, Alf Kirkevåg, Dirk Olivié, Stephanie Fiedler, Anna Lewinschal, Chloe Mackallah, Martin Dix, Robert Pincus, and Piers M. Forster
Atmos. Chem. Phys., 20, 9591–9618, https://doi.org/10.5194/acp-20-9591-2020, https://doi.org/10.5194/acp-20-9591-2020, 2020
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The spread in effective radiative forcing for both CO2 and aerosols is narrower in the latest CMIP6 (Coupled Model Intercomparison Project) generation than in CMIP5. For the case of CO2 it is likely that model radiation parameterisations have improved. Tropospheric and stratospheric radiative adjustments to the forcing behave differently for different forcing agents, and there is still significant diversity in how clouds respond to forcings, particularly for total anthropogenic forcing.
Jerry F. Tjiputra, Jörg Schwinger, Mats Bentsen, Anne L. Morée, Shuang Gao, Ingo Bethke, Christoph Heinze, Nadine Goris, Alok Gupta, Yan-Chun He, Dirk Olivié, Øyvind Seland, and Michael Schulz
Geosci. Model Dev., 13, 2393–2431, https://doi.org/10.5194/gmd-13-2393-2020, https://doi.org/10.5194/gmd-13-2393-2020, 2020
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Ocean biogeochemistry plays an important role in determining the atmospheric carbon dioxide concentration. Earth system models, which are regularly used to study and project future climate change, generally include an ocean biogeochemistry component. Prior to their application, such models are rigorously validated against real-world observations. In this study, we evaluate the ability of the ocean biogeochemistry in the Norwegian Earth System Model version 2 to simulate various datasets.
Montserrat Costa-Surós, Odran Sourdeval, Claudia Acquistapace, Holger Baars, Cintia Carbajal Henken, Christa Genz, Jonas Hesemann, Cristofer Jimenez, Marcel König, Jan Kretzschmar, Nils Madenach, Catrin I. Meyer, Roland Schrödner, Patric Seifert, Fabian Senf, Matthias Brueck, Guido Cioni, Jan Frederik Engels, Kerstin Fieg, Ksenia Gorges, Rieke Heinze, Pavan Kumar Siligam, Ulrike Burkhardt, Susanne Crewell, Corinna Hoose, Axel Seifert, Ina Tegen, and Johannes Quaas
Atmos. Chem. Phys., 20, 5657–5678, https://doi.org/10.5194/acp-20-5657-2020, https://doi.org/10.5194/acp-20-5657-2020, 2020
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The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This study analyses large-domain simulations with a new high-resolution model to investigate the differences in clouds between 1985 and 2013 comparing multiple observational datasets. The differences in aerosol and in cloud droplet concentrations are clearly detectable. For other quantities, the detection and attribution proved difficult, despite a substantial impact on the Earth's energy budget.
Constanze Wellmann, Andrew I. Barrett, Jill S. Johnson, Michael Kunz, Bernhard Vogel, Ken S. Carslaw, and Corinna Hoose
Atmos. Chem. Phys., 20, 2201–2219, https://doi.org/10.5194/acp-20-2201-2020, https://doi.org/10.5194/acp-20-2201-2020, 2020
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Severe hailstorms may cause damage to buildings and crops. Thus, the forecast of numerical weather prediction (NWP) models should be as reliable as possible.
Using statistical emulation, we identify those model input parameters describing environmental conditions and cloud microphysics which lead to large uncertainties in the prediction of deep convection. We find that the impact of the input parameters on the uncertainty depends on the considered output variable.
Øivind Hodnebrog, Gunnar Myhre, Bjørn H. Samset, Kari Alterskjær, Timothy Andrews, Olivier Boucher, Gregory Faluvegi, Dagmar Fläschner, Piers M. Forster, Matthew Kasoar, Alf Kirkevåg, Jean-Francois Lamarque, Dirk Olivié, Thomas B. Richardson, Dilshad Shawki, Drew Shindell, Keith P. Shine, Philip Stier, Toshihiko Takemura, Apostolos Voulgarakis, and Duncan Watson-Parris
Atmos. Chem. Phys., 19, 12887–12899, https://doi.org/10.5194/acp-19-12887-2019, https://doi.org/10.5194/acp-19-12887-2019, 2019
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Different greenhouse gases (e.g. CO2) and aerosols (e.g. black carbon) impact the Earth’s water cycle differently. Here we investigate how various gases and particles impact atmospheric water vapour and its lifetime, i.e., the average number of days that water vapour stays in the atmosphere after evaporation and before precipitation. We find that this lifetime could increase substantially by the end of this century, indicating that important changes in precipitation patterns are excepted.
Linda Schneider, Christian Barthlott, Corinna Hoose, and Andrew I. Barrett
Atmos. Chem. Phys., 19, 12343–12359, https://doi.org/10.5194/acp-19-12343-2019, https://doi.org/10.5194/acp-19-12343-2019, 2019
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This study addresses the relative impact of orography, soil moisture, and aerosols on precipitation over Germany in different weather regimes. We find that the impact of these perturbations is higher for weak than for strong large-scale forcing. Furthermore, aerosols and soil moisture are both of similar importance for precipitation forecasting, which indicates that their inclusion in operational ensemble forecasting should be assessed in the future.
Lise S. Graff, Trond Iversen, Ingo Bethke, Jens B. Debernard, Øyvind Seland, Mats Bentsen, Alf Kirkevåg, Camille Li, and Dirk J. L. Olivié
Earth Syst. Dynam., 10, 569–598, https://doi.org/10.5194/esd-10-569-2019, https://doi.org/10.5194/esd-10-569-2019, 2019
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Differences between a 1.5 and a 2.0 °C warmer global climate than 1850 conditions are discussed based on a suite of global atmosphere-only, fully coupled, and slab-ocean runs with the Norwegian Earth System Model. Responses, such as the Arctic amplification of global warming, are stronger with the fully coupled and slab-ocean configurations. While ice-free Arctic summers are rare under 1.5 °C warming in the slab-ocean runs, they are estimated to occur 18 % of the time under 2.0 °C warming.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
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Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Chuncheng Guo, Kerim H. Nisancioglu, Mats Bentsen, Ingo Bethke, and Zhongshi Zhang
Clim. Past, 15, 1133–1151, https://doi.org/10.5194/cp-15-1133-2019, https://doi.org/10.5194/cp-15-1133-2019, 2019
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We present an equilibrium simulation of the climate of Marine Isotope Stage 3, with an IPCC-class model with a relatively high model resolution and a long integration. The simulated climate resembles a warm interstadial state, as indicated by reconstructions of Greenland temperature, sea ice extent, and AMOC. Sensitivity experiments to changes in atmospheric CO2 levels and ice sheet size show that the model is in a relatively stable climate state without multiple equilibria.
Maiken Vassel, Luisa Ickes, Marion Maturilli, and Corinna Hoose
Atmos. Chem. Phys., 19, 5111–5126, https://doi.org/10.5194/acp-19-5111-2019, https://doi.org/10.5194/acp-19-5111-2019, 2019
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Multilayer clouds are coexisting clouds at different heights. We evaluate measurements and find that Arctic multilayer clouds occur in 29 % of the investigated days at Ny-Ålesund, Svalbard. Multilayer clouds can interact by ice crystals falling from the upper cloud into the lower cloud. This is possible in 23 % of the investigated days, and in 9 % it is not possible. Weather models are still error-prone in the Arctic and we suggest that multilayer clouds should be included more in future work.
Michael Boy, Erik S. Thomson, Juan-C. Acosta Navarro, Olafur Arnalds, Ekaterina Batchvarova, Jaana Bäck, Frank Berninger, Merete Bilde, Zoé Brasseur, Pavla Dagsson-Waldhauserova, Dimitri Castarède, Maryam Dalirian, Gerrit de Leeuw, Monika Dragosics, Ella-Maria Duplissy, Jonathan Duplissy, Annica M. L. Ekman, Keyan Fang, Jean-Charles Gallet, Marianne Glasius, Sven-Erik Gryning, Henrik Grythe, Hans-Christen Hansson, Margareta Hansson, Elisabeth Isaksson, Trond Iversen, Ingibjorg Jonsdottir, Ville Kasurinen, Alf Kirkevåg, Atte Korhola, Radovan Krejci, Jon Egill Kristjansson, Hanna K. Lappalainen, Antti Lauri, Matti Leppäranta, Heikki Lihavainen, Risto Makkonen, Andreas Massling, Outi Meinander, E. Douglas Nilsson, Haraldur Olafsson, Jan B. C. Pettersson, Nønne L. Prisle, Ilona Riipinen, Pontus Roldin, Meri Ruppel, Matthew Salter, Maria Sand, Øyvind Seland, Heikki Seppä, Henrik Skov, Joana Soares, Andreas Stohl, Johan Ström, Jonas Svensson, Erik Swietlicki, Ksenia Tabakova, Throstur Thorsteinsson, Aki Virkkula, Gesa A. Weyhenmeyer, Yusheng Wu, Paul Zieger, and Markku Kulmala
Atmos. Chem. Phys., 19, 2015–2061, https://doi.org/10.5194/acp-19-2015-2019, https://doi.org/10.5194/acp-19-2015-2019, 2019
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The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date and aimed to strengthen research and innovation regarding climate change issues in the Nordic region. The paper presents an overview of the main scientific topics investigated and provides a state-of-the-art comprehensive summary of what has been achieved in CRAICC.
Chuncheng Guo, Mats Bentsen, Ingo Bethke, Mehmet Ilicak, Jerry Tjiputra, Thomas Toniazzo, Jörg Schwinger, and Odd Helge Otterå
Geosci. Model Dev., 12, 343–362, https://doi.org/10.5194/gmd-12-343-2019, https://doi.org/10.5194/gmd-12-343-2019, 2019
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In this paper, we describe and evaluate a new variant of the Norwegian Earth System Model (NorESM). It is a computationally efficient model that is designed for experiments such as paleoclimate, carbon cycle, and large ensemble simulations. The model, with various recent code updates, shows improved climate performance compared to the CMIP5 version of NorESM, while the model resolution remains similar.
Michael Weger, Bernd Heinold, Christa Engler, Ulrich Schumann, Axel Seifert, Romy Fößig, Christiane Voigt, Holger Baars, Ulrich Blahak, Stephan Borrmann, Corinna Hoose, Stefan Kaufmann, Martina Krämer, Patric Seifert, Fabian Senf, Johannes Schneider, and Ina Tegen
Atmos. Chem. Phys., 18, 17545–17572, https://doi.org/10.5194/acp-18-17545-2018, https://doi.org/10.5194/acp-18-17545-2018, 2018
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The impact of desert dust on cloud formation is investigated for a major Saharan dust event over Europe by interactive regional dust modeling. Dust particles are very efficient ice-nucleating particles promoting the formation of ice crystals in clouds. The simulations show that the observed extensive cirrus development was likely related to the above-average dust load. The interactive dust–cloud feedback in the model significantly improves the agreement with aircraft and satellite observations.
Sylvia C. Sullivan, Christian Barthlott, Jonathan Crosier, Ilya Zhukov, Athanasios Nenes, and Corinna Hoose
Atmos. Chem. Phys., 18, 16461–16480, https://doi.org/10.5194/acp-18-16461-2018, https://doi.org/10.5194/acp-18-16461-2018, 2018
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Ice crystal formation in clouds can occur via thermodynamic nucleation, but also via mechanical collisions between pre-existing crystals or co-existing droplets. When descriptions of this mechanical ice generation are implemented into the COSMO weather model, we find that the contributions to crystal number from thermodynamic and mechanical processes are of the same order. Mechanical ice generation also intensifies differences in precipitation intensity between dynamic and quiescent regions.
Matthias Hummel, Corinna Hoose, Bernhard Pummer, Caroline Schaupp, Janine Fröhlich-Nowoisky, and Ottmar Möhler
Atmos. Chem. Phys., 18, 15437–15450, https://doi.org/10.5194/acp-18-15437-2018, https://doi.org/10.5194/acp-18-15437-2018, 2018
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How important for clouds is the ability of biological particles to glaciate droplets at little supercooling? In a case study, the regional atmospheric model COSMO–ART is used. Perturbed and control runs are compared.
The number of ice particles that are nucleated by biological particles is highest at around −10 °C. No significant influence on the average state of the cloud ice phase was found. However, the number of ice crystals is slightly enhanced in the absence of other ice nucleators.
Alf Kirkevåg, Alf Grini, Dirk Olivié, Øyvind Seland, Kari Alterskjær, Matthias Hummel, Inger H. H. Karset, Anna Lewinschal, Xiaohong Liu, Risto Makkonen, Ingo Bethke, Jan Griesfeller, Michael Schulz, and Trond Iversen
Geosci. Model Dev., 11, 3945–3982, https://doi.org/10.5194/gmd-11-3945-2018, https://doi.org/10.5194/gmd-11-3945-2018, 2018
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A new aerosol treatment is described and tested in a global climate model. With updated emissions, aerosol chemistry, and microphysics compared to its predecessor, black carbon (BC) mass concentrations aloft better fit observations, surface concentrations of BC and sea salt are less biased, and sulfate and mineral dust slightly more, while the results for organics are inconclusive. Man-made aerosols now yield a stronger cooling effect on climate that is strong compared to results from IPCC.
Michael Schäfer, Katharina Loewe, André Ehrlich, Corinna Hoose, and Manfred Wendisch
Atmos. Chem. Phys., 18, 13115–13133, https://doi.org/10.5194/acp-18-13115-2018, https://doi.org/10.5194/acp-18-13115-2018, 2018
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Airborne observed horizontal fields of cloud optical thickness are compared with semi-idealized large eddy simulations of Arctic stratus. The comparison focuses on horizontal cloud inhomogeneities and directional features of the small-scale cloud structures. Using inhomogeneity parameters and autocorrelation analysis it is investigated, if the observed small-scale cloud inhomogeneities can be represented by the model. Forcings for cloud inhomogeneities are investigated in a sensitivity study.
Robin G. Stevens, Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, Adrian A. Hill, Benjamin J. Shipway, Jonathan Wilkinson, Sami Romakkaniemi, Juha Tonttila, Ari Laaksonen, Hannele Korhonen, Paul Connolly, Ulrike Lohmann, Corinna Hoose, Annica M. L. Ekman, Ken S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, https://doi.org/10.5194/acp-18-11041-2018, 2018
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We perform a model intercomparison of summertime high Arctic clouds. Observed concentrations of aerosol particles necessary for cloud formation fell to extremely low values, coincident with a transition from cloudy to nearly cloud-free conditions. Previous analyses have suggested that at these low concentrations, the radiative properties of the clouds are determined primarily by these particle concentrations. The model results strongly support this hypothesis.
Fahad Saeed, Ingo Bethke, Stefan Lange, Ludwig Lierhammer, Hideo Shiogama, Dáithí A. Stone, Tim Trautmann, and Carl-Friedrich Schleussner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-107, https://doi.org/10.5194/gmd-2018-107, 2018
Revised manuscript has not been submitted
Tao Tang, Drew Shindell, Bjørn H. Samset, Oliviér Boucher, Piers M. Forster, Øivind Hodnebrog, Gunnar Myhre, Jana Sillmann, Apostolos Voulgarakis, Timothy Andrews, Gregory Faluvegi, Dagmar Fläschner, Trond Iversen, Matthew Kasoar, Viatcheslav Kharin, Alf Kirkevåg, Jean-Francois Lamarque, Dirk Olivié, Thomas Richardson, Camilla W. Stjern, and Toshihiko Takemura
Atmos. Chem. Phys., 18, 8439–8452, https://doi.org/10.5194/acp-18-8439-2018, https://doi.org/10.5194/acp-18-8439-2018, 2018
Inger Helene Hafsahl Karset, Terje Koren Berntsen, Trude Storelvmo, Kari Alterskjær, Alf Grini, Dirk Olivié, Alf Kirkevåg, Øyvind Seland, Trond Iversen, and Michael Schulz
Atmos. Chem. Phys., 18, 7669–7690, https://doi.org/10.5194/acp-18-7669-2018, https://doi.org/10.5194/acp-18-7669-2018, 2018
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This study highlights the role of oxidants in modeling of the preindustrial-to-present-day aerosol indirect effects. We argue that the aerosol precursor gases should be exposed to oxidants of its era to get a more correct representation of secondary aerosol formation. Our global model simulations show that the total aerosol indirect effect changes from −1.32 to −1.07 W m−2 when the precursor gases in the preindustrial simulation are exposed to preindustrial instead of present-day oxidants.
Camille Li, Clio Michel, Lise Seland Graff, Ingo Bethke, Giuseppe Zappa, Thomas J. Bracegirdle, Erich Fischer, Ben J. Harvey, Trond Iversen, Martin P. King, Harinarayan Krishnan, Ludwig Lierhammer, Daniel Mitchell, John Scinocca, Hideo Shiogama, Dáithí A. Stone, and Justin J. Wettstein
Earth Syst. Dynam., 9, 359–382, https://doi.org/10.5194/esd-9-359-2018, https://doi.org/10.5194/esd-9-359-2018, 2018
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This study investigates the midlatitude atmospheric circulation response to 1.5°C and 2.0°C of warming using modelling experiments run for the HAPPI project (Half a degree Additional warming, Prognosis & Projected Impacts). While the chaotic nature of the atmospheric flow dominates in these low-end warming scenarios, some local changes emerge. Case studies explore precipitation impacts both for regions that dry (Mediterranean) and regions that get wetter (Europe, North American west coast).
Sylvia C. Sullivan, Corinna Hoose, Alexei Kiselev, Thomas Leisner, and Athanasios Nenes
Atmos. Chem. Phys., 18, 1593–1610, https://doi.org/10.5194/acp-18-1593-2018, https://doi.org/10.5194/acp-18-1593-2018, 2018
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Ice multiplication (IM) processes can have a profound impact on cloud and precipitation development but are poorly understood. Here we study whether a lower limit of ice nuclei exists to initiate IM. The lower limit is found to be extremely low (0.01 per liter or less). A counterintuitive but profound conclusion thus emerges: IM requires cloud formation around a thermodynamic
sweet spotand is sensitive to fluctuations in cloud condensation nuclei concentration alone.
Petri Räisänen, Risto Makkonen, Alf Kirkevåg, and Jens B. Debernard
The Cryosphere, 11, 2919–2942, https://doi.org/10.5194/tc-11-2919-2017, https://doi.org/10.5194/tc-11-2919-2017, 2017
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While snow grains are non-spherical, spheres are often assumed in radiation calculations. Here, we replace spherical snow grains with non-spherical snow grains in a climate model. This leads to a somewhat higher snow albedo (by 0.02–0.03), increased snow and sea ice cover, and a distinctly colder climate (by over 1 K in the global mean). It also impacts the radiative effects of aerosols in snow. Overall, this work highlights the important role of snow albedo parameterization for climate models.
Luke B. Hande and Corinna Hoose
Atmos. Chem. Phys., 17, 14105–14118, https://doi.org/10.5194/acp-17-14105-2017, https://doi.org/10.5194/acp-17-14105-2017, 2017
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In this study, the relative contributions of different primary ice nucleation modes (i.e. processes leading to the formation of ice crystals with or without the help of certain aerosol particles, in this case mineral dust) are quantified in model simulations for different cloud types.
Lars Ahlm, Andy Jones, Camilla W. Stjern, Helene Muri, Ben Kravitz, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 17, 13071–13087, https://doi.org/10.5194/acp-17-13071-2017, https://doi.org/10.5194/acp-17-13071-2017, 2017
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We present results from coordinated simulations with three Earth system models focusing on the response of Earth’s radiation balance to the injection of sea salt particles. We find that in most regions the effective radiative forcing by the injected particles is equally large in cloudy and clear-sky conditions, suggesting a more important role of the aerosol direct effect in sea spray climate engineering than previously thought.
Maria Sand, Bjørn H. Samset, Yves Balkanski, Susanne Bauer, Nicolas Bellouin, Terje K. Berntsen, Huisheng Bian, Mian Chin, Thomas Diehl, Richard Easter, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Jean-François Lamarque, Guangxing Lin, Xiaohong Liu, Gan Luo, Gunnar Myhre, Twan van Noije, Joyce E. Penner, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Fangqun Yu, Kai Zhang, and Hua Zhang
Atmos. Chem. Phys., 17, 12197–12218, https://doi.org/10.5194/acp-17-12197-2017, https://doi.org/10.5194/acp-17-12197-2017, 2017
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The role of aerosols in the changing polar climate is not well understood and the aerosols are poorly constrained in the models. In this study we have compared output from 16 different aerosol models with available observations at both poles. We show that the model median is representative of the observations, but the model spread is large. The Arctic direct aerosol radiative effect over the industrial area is positive during spring due to black carbon and negative during summer due to sulfate.
Jörg Schwinger, Jerry Tjiputra, Nadine Goris, Katharina D. Six, Alf Kirkevåg, Øyvind Seland, Christoph Heinze, and Tatiana Ilyina
Biogeosciences, 14, 3633–3648, https://doi.org/10.5194/bg-14-3633-2017, https://doi.org/10.5194/bg-14-3633-2017, 2017
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Transient global warming under the high emission scenario RCP8.5 is amplified by up to 6 % if a pH dependency of marine DMS production is assumed. Importantly, this additional warming is not spatially homogeneous but shows a pronounced north–south gradient. Over the Antarctic continent, the additional warming is almost twice the global average. In the Southern Ocean we find a small DMS–climate feedback that counteracts the original reduction of DMS production due to ocean acidification.
Katharina Loewe, Annica M. L. Ekman, Marco Paukert, Joseph Sedlar, Michael Tjernström, and Corinna Hoose
Atmos. Chem. Phys., 17, 6693–6704, https://doi.org/10.5194/acp-17-6693-2017, https://doi.org/10.5194/acp-17-6693-2017, 2017
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Processes that affect Arctic mixed-phase cloud life cycle are extremely important for the surface energy budget. Three different sensitivity experiments mimic changes in the advection of air masses with different thermodynamic profiles and aerosol properties to find the potential mechanisms leading to the dissipation of the cloud. We found that the reduction of the cloud droplet number concentration was likely the primary contributor to the dissipation of the observed Arctic mixed-phase cloud.
Daniel Mitchell, Krishna AchutaRao, Myles Allen, Ingo Bethke, Urs Beyerle, Andrew Ciavarella, Piers M. Forster, Jan Fuglestvedt, Nathan Gillett, Karsten Haustein, William Ingram, Trond Iversen, Viatcheslav Kharin, Nicholas Klingaman, Neil Massey, Erich Fischer, Carl-Friedrich Schleussner, John Scinocca, Øyvind Seland, Hideo Shiogama, Emily Shuckburgh, Sarah Sparrow, Dáithí Stone, Peter Uhe, David Wallom, Michael Wehner, and Rashyd Zaaboul
Geosci. Model Dev., 10, 571–583, https://doi.org/10.5194/gmd-10-571-2017, https://doi.org/10.5194/gmd-10-571-2017, 2017
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This paper provides an experimental design to assess impacts of a world that is 1.5 °C warmer than at pre-industrial levels. The design is a new way to approach impacts from the climate community, and aims to answer questions related to the recent Paris Agreement. In particular the paper provides a method for studying extreme events under relatively high mitigation scenarios.
Massimo Cassiani, Andreas Stohl, Dirk Olivié, Øyvind Seland, Ingo Bethke, Ignacio Pisso, and Trond Iversen
Geosci. Model Dev., 9, 4029–4048, https://doi.org/10.5194/gmd-9-4029-2016, https://doi.org/10.5194/gmd-9-4029-2016, 2016
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FLEXPART is a community model used by many scientists. Here, an alternative FLEXPART model version has been developed, tailored to use with the output data generated by the Norwegian Earth System Model (NorESM1-M). The model provides an advanced tool to analyse and diagnose atmospheric transport properties of the climate model NorESM. To validate the model, several tests were performed that offered the possibility to investigate some aspects of offline global dispersion modelling.
Luke B. Hande, Christa Engler, Corinna Hoose, and Ina Tegen
Atmos. Chem. Phys., 16, 12059–12079, https://doi.org/10.5194/acp-16-12059-2016, https://doi.org/10.5194/acp-16-12059-2016, 2016
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An aerosol model was used to simulate the concentration of natural and anthropogenic aerosols over Germany. Using a detailed parameterization of CCN activation, which includes information of aerosol chemical and physical properties, CCN concentrations were calculated. Using these results, a series of best fit functions were used to define a new parameterization, which is a simple function of vertical velocity and pressure. The new parameterization is easy to implement in models.
Jörg Schwinger, Nadine Goris, Jerry F. Tjiputra, Iris Kriest, Mats Bentsen, Ingo Bethke, Mehmet Ilicak, Karen M. Assmann, and Christoph Heinze
Geosci. Model Dev., 9, 2589–2622, https://doi.org/10.5194/gmd-9-2589-2016, https://doi.org/10.5194/gmd-9-2589-2016, 2016
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We present an evaluation of the ocean carbon cycle stand-alone configuration of the Norwegian Earth System Model. A re-tuning of the ecosystem parameterisation improves surface tracer fields between versions 1 and 1.2 of the model. Focus is placed on the evaluation of newly implemented parameterisations of the biological carbon pump (i.e. the sinking of particular organic carbon). We find that the model previously underestimated the carbon transport into the deep ocean below 2000 m depth.
Zak Kipling, Philip Stier, Colin E. Johnson, Graham W. Mann, Nicolas Bellouin, Susanne E. Bauer, Tommi Bergman, Mian Chin, Thomas Diehl, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Harri Kokkola, Xiaohong Liu, Gan Luo, Twan van Noije, Kirsty J. Pringle, Knut von Salzen, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Toshihiko Takemura, Kostas Tsigaridis, and Kai Zhang
Atmos. Chem. Phys., 16, 2221–2241, https://doi.org/10.5194/acp-16-2221-2016, https://doi.org/10.5194/acp-16-2221-2016, 2016
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The vertical distribution of atmospheric aerosol is an important factor in its effects on climate. In this study we use a sophisticated model of the many interacting processes affecting aerosol in the atmosphere to show that the vertical distribution is typically dominated by only a few of these processes. Constraining these physical processes may help to reduce the large differences between models. However, the important processes are not always the same for different types of aerosol.
C. Barthlott and C. Hoose
Atmos. Chem. Phys., 15, 12361–12384, https://doi.org/10.5194/acp-15-12361-2015, https://doi.org/10.5194/acp-15-12361-2015, 2015
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This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling model for 7 cases of 2013. By means of a series of grid-refinement resolution tests, the variability of clouds and precipitation and how this variability changes with model resolution are investigated. The performance of the model at these resolutions is of general relevance to the research community as well as to operational forecasters
M. E. Salter, P. Zieger, J. C. Acosta Navarro, H. Grythe, A. Kirkevåg, B. Rosati, I. Riipinen, and E. D. Nilsson
Atmos. Chem. Phys., 15, 11047–11066, https://doi.org/10.5194/acp-15-11047-2015, https://doi.org/10.5194/acp-15-11047-2015, 2015
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We have developed an inorganic sea spray source function that is based upon state-of-the-art measurements of sea spray aerosol production using a temperature-controlled plunging jet sea spray aerosol chamber. The sea spray source function was implemented in a Lagrangian particle dispersion model and showed good skill in predicting measurements of Na+ concentration at a number of field sites, underlining its validity.
A. Stohl, B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. Olivié, J. Quaas, B. Quennehen, J.-C. Raut, S. T. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu
Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, https://doi.org/10.5194/acp-15-10529-2015, 2015
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This paper presents a summary of the findings of the ECLIPSE EU project. The project has investigated the climate and air quality impacts of short-lived climate pollutants (especially methane, ozone, aerosols) and has designed a global mitigation strategy that maximizes co-benefits between air quality and climate policy. Transient climate model simulations allowed quantifying the impacts on temperature (e.g., reduction in global warming by 0.22K for the decade 2041-2050) and precipitation.
M. Hummel, C. Hoose, M. Gallagher, D. A. Healy, J. A. Huffman, D. O'Connor, U. Pöschl, C. Pöhlker, N. H. Robinson, M. Schnaiter, J. R. Sodeau, M. Stengel, E. Toprak, and H. Vogel
Atmos. Chem. Phys., 15, 6127–6146, https://doi.org/10.5194/acp-15-6127-2015, https://doi.org/10.5194/acp-15-6127-2015, 2015
L. B. Hande, C. Engler, C. Hoose, and I. Tegen
Atmos. Chem. Phys., 15, 4389–4397, https://doi.org/10.5194/acp-15-4389-2015, https://doi.org/10.5194/acp-15-4389-2015, 2015
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Dust is a significant aerosol on seasonal timescales. There are large differences in dust and INP concentrations between seasons. The INP concentrations have a different vertical distribution than other common parameterisations suggest. We provide a new formulation to estimate the INP particles formed on dust aerosols, for use in process studies and regional simulations over Europe. The new formulation captures a much more realistic seasonal variability and vertical profile.
I. Steinke, C. Hoose, O. Möhler, P. Connolly, and T. Leisner
Atmos. Chem. Phys., 15, 3703–3717, https://doi.org/10.5194/acp-15-3703-2015, https://doi.org/10.5194/acp-15-3703-2015, 2015
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Ice nucleation in clouds has a significant influence on the global radiative budget and the hydrological cycle. Several studies have investigated the ice formation in droplets and parameterizations have been developed in order to include immersion freezing in climate models. In contrast, there are fewer studies regarding the conversion of water vapor into ice (so-called deposition nucleation) which is the topic of this paper which investigates deposition nucleation by Arizona Test dust in detail
N. Hiranuma, M. Paukert, I. Steinke, K. Zhang, G. Kulkarni, C. Hoose, M. Schnaiter, H. Saathoff, and O. Möhler
Atmos. Chem. Phys., 14, 13145–13158, https://doi.org/10.5194/acp-14-13145-2014, https://doi.org/10.5194/acp-14-13145-2014, 2014
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A new heterogeneous ice nucleation parameterization is developed and implemented in cloud models. The results of our simulations suggest stronger influence of dust particles lifted to the upper troposphere on heterogeneous nucleation and more ice nucleation at temperature and humidity conditions relevant to both mixed-phase and cirrus clouds when compared to the existing parametrical frameworks.
B. H. Samset, G. Myhre, A. Herber, Y. Kondo, S.-M. Li, N. Moteki, M. Koike, N. Oshima, J. P. Schwarz, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, M. Chin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, M. Schulz, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 14, 12465–12477, https://doi.org/10.5194/acp-14-12465-2014, https://doi.org/10.5194/acp-14-12465-2014, 2014
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Far from black carbon (BC) emission sources, present climate models are unable to reproduce flight measurements. By comparing recent models with data, we find that the atmospheric lifetime of BC may be overestimated in models. By adjusting modeled BC concentrations to measurements in remote regions - over oceans and at high altitudes - we arrive at a reduced estimate for BC radiative forcing over the industrial era.
D. Neubauer, U. Lohmann, C. Hoose, and M. G. Frontoso
Atmos. Chem. Phys., 14, 11997–12022, https://doi.org/10.5194/acp-14-11997-2014, https://doi.org/10.5194/acp-14-11997-2014, 2014
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Several biases in the representation of clouds in the stratocumulus regime in the ECHAM6-HAM2 global climate model were found by evaluating the model in the stratocumulus cloud regime. Simulations with changes in model resolution and physics to better represent clouds and aerosol in the stratocumulus regime show that the human influence on clouds and thus climate by emission of aerosol particles is sensitive to the representation of (stratocumulus) clouds.
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
Y. Wang, X. Liu, C. Hoose, and B. Wang
Atmos. Chem. Phys., 14, 10411–10430, https://doi.org/10.5194/acp-14-10411-2014, https://doi.org/10.5194/acp-14-10411-2014, 2014
M. Joly, P. Amato, L. Deguillaume, M. Monier, C. Hoose, and A.-M. Delort
Atmos. Chem. Phys., 14, 8185–8195, https://doi.org/10.5194/acp-14-8185-2014, https://doi.org/10.5194/acp-14-8185-2014, 2014
R. Makkonen, Ø. Seland, A. Kirkevåg, T. Iversen, and J. E. Kristjánsson
Atmos. Chem. Phys., 14, 5127–5152, https://doi.org/10.5194/acp-14-5127-2014, https://doi.org/10.5194/acp-14-5127-2014, 2014
C. Jiao, M. G. Flanner, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, K. S. Carslaw, M. Chin, N. De Luca, T. Diehl, S. J. Ghan, T. Iversen, A. Kirkevåg, D. Koch, X. Liu, G. W. Mann, J. E. Penner, G. Pitari, M. Schulz, Ø. Seland, R. B. Skeie, S. D. Steenrod, P. Stier, T. Takemura, K. Tsigaridis, T. van Noije, Y. Yun, and K. Zhang
Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, https://doi.org/10.5194/acp-14-2399-2014, 2014
T. Iversen, M. Bentsen, I. Bethke, J. B. Debernard, A. Kirkevåg, Ø. Seland, H. Drange, J. E. Kristjansson, I. Medhaug, M. Sand, and I. A. Seierstad
Geosci. Model Dev., 6, 389–415, https://doi.org/10.5194/gmd-6-389-2013, https://doi.org/10.5194/gmd-6-389-2013, 2013
J. F. Tjiputra, C. Roelandt, M. Bentsen, D. M. Lawrence, T. Lorentzen, J. Schwinger, Ø. Seland, and C. Heinze
Geosci. Model Dev., 6, 301–325, https://doi.org/10.5194/gmd-6-301-2013, https://doi.org/10.5194/gmd-6-301-2013, 2013
B. H. Samset, G. Myhre, M. Schulz, Y. Balkanski, S. Bauer, T. K. Berntsen, H. Bian, N. Bellouin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, S. Kinne, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 13, 2423–2434, https://doi.org/10.5194/acp-13-2423-2013, https://doi.org/10.5194/acp-13-2423-2013, 2013
A. Kirkevåg, T. Iversen, Ø. Seland, C. Hoose, J. E. Kristjánsson, H. Struthers, A. M. L. Ekman, S. Ghan, J. Griesfeller, E. D. Nilsson, and M. Schulz
Geosci. Model Dev., 6, 207–244, https://doi.org/10.5194/gmd-6-207-2013, https://doi.org/10.5194/gmd-6-207-2013, 2013
M. Sand, T. K. Berntsen, J. E. Kay, J. F. Lamarque, Ø. Seland, and A. Kirkevåg
Atmos. Chem. Phys., 13, 211–224, https://doi.org/10.5194/acp-13-211-2013, https://doi.org/10.5194/acp-13-211-2013, 2013
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Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
CropSuite – A comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – The ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
A non-intrusive, multi-scale, and flexible coupling interface in WRF
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
The very-high resolution configuration of the EC-Earth global model for HighResMIP
ZEMBA v1.0: An energy and moisture balance climate model to investigate Quaternary climate
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
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CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used for climate impact assessments, adaptation and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++ and Python) and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
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This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged between WRF and any other model (e.g. an ocean model) using the coupling library Ocean-Atmosphere-Sea-Ice-Soil – Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-119, https://doi.org/10.5194/gmd-2024-119, 2024
Revised manuscript accepted for GMD
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10-15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100-km and a 25-km grid. The three models are compared with observations to study the improvements thanks to the increased in the resolution.
Daniel Francis James Gunning, Kerim Hestnes Nisancioglu, Emilie Capron, and Roderik van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2024-1384, https://doi.org/10.5194/egusphere-2024-1384, 2024
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth’s orbit. We demonstrate ZEMBA reproduces many features of the Earth’s climate for both the pre-industrial period and the Earth’s most recent cold extreme- the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
K. Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
EGUsphere, https://doi.org/10.5194/egusphere-2024-1431, https://doi.org/10.5194/egusphere-2024-1431, 2024
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The study aimed to improve the representation of spring wheat and rice in the CLM5. The modified CLM5 model performed significantly better than the default model in simulating crop phenology, yield, carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific parameters for accurately simulating vegetation processes and land surface processes.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 2. Multiple aerosol types, J. Geophys. Res., 105, 6837–6844, https://doi.org/10.1029/1999JD901161, 2000.
Adcroft, A., Hallberg, R., and Harrison, M.: A finite volume discretization of the pressure gradient force using analytic integration, Ocean Model., 22, 106–113, https://doi.org/10.1016/j.ocemod.2008.02.001, 2008.
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–1167, 2003.
Alterskjær, K., Kristjánsson, J. E., and Hoose, C.: Do anthropogenic aerosols enhance or suppress the surface cloud forcing in the Arctic?, J. Geophys. Res., 115, D22204, https://doi.org/10.1029/2010JD014015, 2010.
Ammann, C. M., Meehl, G. A., Washington, W. M., and Zender, C. S.: A monthly and latitudinally varying volcanic forcing dataset in simulations of 20th century climate, Geophys. Res. Lett., 30, 12, https://doi.org/10.1029/2003GL016875, 2003.
Annamalai, H. and Slingo, J. M.: Active/break cycles: diagnosis of the intraseasonal variability of the Asian summer monsoon, Clim. Dynam., 18, 85–102, https://doi.org/10.1007/s003820100161, 2001.
Antonov, J. I., Seidov, D., Boyer, T. P., Locarnini, R. A., Mishonov, A. V., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World Ocean Atlas 2009, Volume 2: Salinity, in: NOAA Atlas NESDIS 69, edited by: Levitus, S., U.S. Government Printing Office, Washington, DC, 184 pp., 2010.
Årthun, M., Eldevik, T., Smedsrud, L. H., Skagseth, Ø., and Ingvaldsen, R. B.: Quantifying the influence of Atlantic heat on Barents sea ice variability and retreat, J. Climate, 25, 4736–4743, https://doi.org/10.1175/JCLI-D-11-00466.1, 2012.
Assmann, K. M., Bentsen, M., Segschneider, J., and Heinze, C.: An isopycnic ocean carbon cycle model, Geosci. Model Dev., 3, 143–167, https://doi.org/10.5194/gmd-3-143-2010, 2010.
Bengtsson, L., Semenov, V. A., and Johannessen, O. M.: The early twentieth-century warming in the Arctic – a possible mechanism, J. Climate, 17, 4045–4057, 2004.
Bentsen, M., Drange, H., Furevik, T., and Zhou, T.: Simulated variability of the Atlantic meridional overturning circulation, Clim. Dynam., 22, 701–720, https://doi.org/10.1007/s00382-004-0397-x, 2004.
Bleck, R. and Smith, L. T.: A wind-driven isopycnic coordinate model of the North and Equatorial Atlantic Ocean, 1. Model development and supporting experiments, J. Geophys. Res., 95, 3273–3285, 1990.
Bleck, R., Rooth, C., Hu, D., and Smith, L. T.: Salinity-driven thermocline transients in a wind- and thermohaline-forced isopycnic coordinate model of the North Atlantic, J. Phys. Oceanogr., 22, 1486–1505, 1992.
Boé, J., Hall, A., and Qu, X.: September sea-ice cover in the Arctic Ocean projected to vanish by 2100, Nat. Geosci., 2, 341–343, https://doi.org/10.1038/ngeo467, 2009.
Boer, G. J. and Yu, B.: Climate sensitivity and response, Clim. Dynam., 20, 415–429, https://doi.org/10.1007/s00382-002-0283-3, 2003.
Booth, B. B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., and Bellouin, N.: Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 484, 228–232, https://doi.org/10.1038/nature10946, 2012.
Branstator, G. and Selten, F.: "Modes of variability" and climate change, J. Climate, 22, 2639–2658, https://doi.org/10.1175/2008JCLI2517.1, 2009.
Bretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M., and Bladé, I.: The effective number of spatial degrees of freedom of a time-varying field, J. Climate, 12, 1990–2009, 1999.
Briegleb, B. P. and Light, B.: A Delta-Eddington Mutiple Scattering Parameterization for Solar Radiation in the Sea Ice Component of the Community Climate System Model, Tech. Rep. NCAR/TN-472+STR, National Center for Atmospheric Research, Boulder, Colorado, USA, 2007.
Bromwich, D. H., Fogt, R. L., Hodges, K. I., and Walsh, J. E.: A tropospheric assessment of the ERA-40, NCEP, and JRA-25 global reanalyses in the polar regions, J. Geophys. Res., 112, D10111, https://doi.org/10.1029/2006JD007859, 2007.
Cassou, C.: Intraseasonal interaction between the Madden–Julian oscillation and the North Atlantic oscillation, Nature, 455, 523–527, https://doi.org/10.1038/nature07286, 2008.
Charlton-Perez, A. J., Baldwin, M. P., Birner, T., Black, R. X., Butler, A. H., Calvo, N., Davis, N. A., Gerber, E. P., Gillett, N., Hardiman, S., Kim, J., Kr{ü}ger, K., Lee, Y.-Y., Manzini, E., McDaniel, B. A., Polvani, L., Reichler, T., Shaw, T. A., Sigmond, M., Son, S.-W., Toohey, M., Wilcox, L., Yoden, S., Christiansen, B., Lott, F., Shindell, D., Yukimoto, S., and Watanabe, S.: On the lack of stratospheric dynamical variability in low-top versions of the CMIP5 models, J. Geophys. Res., 118, 2494–2505, 10.1002/jgrd.50125, 2013.
Chylek, P., Folland, C. K., Dijkstra, H. A., Lesins, G., and Dubey, M. K.: Ice-core data evidence for a prominent near 20 year time-scale of the Atlantic Multidecadal Oscillation, Geophys. Res. Lett., 38, L13704, 10.1029/2011GL047501, 2011.
Collins, W. D., Rasch, P. J., Boville, B. A., Hack, J. J., McCaa, J. R., Williamson, D. L., and Briegleb, B. P.: The formulation and atmospheric simulation of the community atmosphere model version, J. Climate, 19, 2144–2161, 2006.
Comiso, J.: Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I, (1979–2010), digital media, National Snow and Ice Data Center, Boulder, Colorado, USA, 1999, available at: http://nsidc.org/data/nsidc-0079.html (last access: August 2012), updated 2012.
Cook, K. H., Meehl, G. A., and Arblaster, J. M.: Monsoon regimes and processes in CCSM4, Part II: African and American monsoon systems, J. Climate, 25, 2609–2621, https://doi.org/10.1175/JCLI-D-11-00185.1, 2012.
Craig, A. P., Vertenstein, M., and Jacob, R.: A new flexible coupler for earth system modeling developed for CCSM4 and CESM1, Int. J. High Perform. Comput. Appl., 26, 31–42, https://doi.org/10.1177/1094342011428141, 2012.
Delworth, T. L. and Knutson, T. R.: Simulation of early 20th century global warming, Science, 287, 2246–2250, 2000.
Delworth, T. L. and Mann, M. E.: Observed and simulated multidecadal variability in the Northern Hemisphere, Clim. Dynam., 16, 661–676, 2000.
Deser, C., Phillips, A. S., Tomas, R. A., Okumura, Y. M., Alexander, M. A., Capotondi, A., Scott, J. D., Kwon, Y. O., and Ohba, M.: ENSO and Pacific decadal variability in the community climate system model version, J. Climate, 4, 2622–2651, https://doi.org/10.1175/JCLI-D-11-00301.1, 2012.
Döös, K. and Webb, D. J.: The Deacon cell and the other meridional cells of the Southern Ocean, J. Phys. Oceanogr., 24, 429–442, 1994.
Drange, H., Dokken, T., Furevik, T., Gerdes, R., Berger, W., Nesje, A., Orvik, K. A., Skagseth, Ø., Skjelvan, I., and Østerhus, S.: The Nordic seas: an overview, in: The Nordic Seas: An Integrated Perspective, edited by: Drange, H., Dokken, T., Furevik, T., Gerdes, R., and Berger, W., AGU Monograph 158, American Geophysical Union, Washington DC, 1–10, 2005a.
Drange, H., Gerdes, R., Gao, Y., Karcher, M., Kauker, F., and Bentsen, M.: Ocean general circulation modelling of the Nordic Seas, in: The Nordic Seas: An Integrated Perspective, edited by: Drange, H., Dokken, T., Furevik, T., Gerdes, R., and Berger, W., AGU Monograph 158, American Geophysical Union, Washington DC, 199–200, 2005b.
Dukowicz, J. K. and Baumgardner, J. R.: Incremental remapping as a transport/advection algorithm, J. Comput. Phys., 160, 318–335, 2000.
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W., Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J., Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J., Sentman, L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A. T., and Zadeh, N.: GFDL's ESM2 global coupled climate-carbon Earth System Models, Part I: Physical formulation and baseline simulation characteristics, J. Climate, 25, 6646–6665, https://doi.org/10.1175/JCLI-D-11-00560.1, 2012.
Eden, C. and Greatbatch, R. J.: Towards a mesoscale eddy closure, Ocean Model., 20, 223–239, https://doi.org/10.1016/j.ocemod.2007.09.002, 2008.
Eden, C., Jochum, M., and Danabasoglu, G.: Effects of different closures for thickness diffusivity, Ocean Model., 26, 47–59, https://doi.org/10.1016/j.ocemod.2008.08.004, 2009.
Escudier, R., Mignot, J., and Swingedouw, D.: A 20-year coupled ocean-sea ice-atmosphere variability mode in the North Atlantic in an AOGCM, Clim. Dynam., 40, 619–636, https://doi.org/10.1007/s00382-012-1402-4, 2013.
EUMETSAT: Global sea ice concentration reprocessing dataset 1978–2009 (v1.1, 2011), digital media, EUMETSAT Ocean and Sea Ice Satelitte Application Facility, Norwegian and Danish Meteorological Institutes, available at: http://osisaf.met.no (last access: August 2012), 2011.
Fasullo, J. T. and Trenberth, K. E.: The annual cycle of the energy budget, Part II: Meridional structures and poleward transports, J. Climate, 21, 2313–2325, https://doi.org/10.1175/2007JCLI1936.1, 2008.
Fetterer, F., Knowles, K., Meier, W., and Savoie, M.: Sea Ice Index, digital media, National Snow and Ice Data Center, Boulder, Colorado, USA, available at: http://nsidc.org/data/g02135.html (last access: August 2012), 2009.
Flanner, M. G. and Zender, C. S.: Linking snowpack microphysics and albedo evolution, J. Geophys. Res., 111, D12208, https://doi.org/10.1029/2005JD006834, 2006.
Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D., Haywood, J., Lean, J., Lowe, D. C., Myhre, G., Nganga, J., Prinn, R., Raga, G., Schulz, M., and Dorland, R. V.: Changes in atmospheric constituents and in radiative forcing, in: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., chap. 2, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 129–234, 2007.
Fox-Kemper, B., Ferrari, R., and Hallberg, R.: Parameterization of mixed layer eddies, Part I: Theory and diagnosis, J. Phys. Oceanogr., 38, 1145–1165, 2008.
Frankcombe, L. M. and Dijkstra, H. A.: Coherent multidecadal variability in North Atlantic sea level, Geophys. Res. Lett., 36, L15604, https://doi.org/10.1029/2009GL039455, 2009.
Frankcombe, L. M., von der Heydt, A., and Dijkstra, H. A.: North Atlantic multidecadal climate variability: An investigation of dominant time scales and processes, J. Climate, 23, 3626–3638, 10.1175/2010JCLI3471.1, 2010.
Furevik, T., Bentsen, M., Drange, H., Kindem, I. K. T., Kvamstø, N. G., and Sorteberg, A.: Description and evaluation of the bergen climate model: ARPEGE coupled with MICOM, Clim. Dynam., 21, 27–51, 2003.
Gaspar, P.: Modeling the seasonal cycle of the upper ocean, J. Phys. Oceanogr., 18, 161–180, 1988.
Gent, P. R., Yeager, S. G., Neale, R. B., Levis, S., and Bailey, D. A.: Improvements in a half degree atmosphere/land version of the CCSM, Clim. Dynam., 34, 819–833, https://doi.org/10.1007/s00382-009-0614-8, 2010.
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P. H., Yang, Z.-L., and Zhang, M.: The Community Climate System Model Version 4, J. Climate, 24, 4973–4991, https://doi.org/10.1175/2011JCLI4083.1, 2011.
Ghil, M., Allen, M. R., Dettinger, M. D., Ide, K., Kondrashov, D., Mann, M. E., Robertson, A. W., Saunders, A., Tian, Y., Varadi, F., and Yiou, P.: Advanced spectral methods for climatic time series, Rev. Geophys., 40, 1003, https://doi.org/10.1029/2000RG000092, 2002.
Greenwald, T. J.: A 2 year comparison of AMSR-E and MODIS cloud liquid water path observations, Geophys. Res. Lett., 36, L20805, https://doi.org/10.1029/2009GL040394, 2009.
Gregg, M. C., Sanford, T. B., and Winkel, D. P.: Reduced mixing from the breaking of internal waves in equatorial waters, Nature, 422, 513–515, https://doi.org/10.1038/nature01507, 2003.
Häkkinen, S. and Rhines, P. B.: Decline of subpolar North Atlantic circulation during the 1990s, Science, 304, 555–559, https://doi.org/10.1126/science.1094917, 2004.
Hallberg, R.: Time integration of diapycnal diffusion and richardson number-dependent mixing in isopycnal coordinate ocean models, Mon. Weather Rev., 128, 1402–1419, 2000.
Harrison, E. F., Minnis, P., Barkstrom, B. R., Ramanathan, V., Cess, R. D., and Gibson, G. G.: Seasonal variation of cloud radiative forcing derived from the earth radiation budget experiment, J. Geophys. Res., 95, 18687–18703, 1990.
Hátún, H., Sandø, A. B., Drange, H., Hansen, B., and Valdimarsson, H.: Influence of the Atlantic subpolar gyre on the thermohaline circulation, Science, 309, 1841–1844, https://doi.org/10.1126/science.1114777, 2005.
Hendon, H. H., Wheeler, M. C., and Zhang, C.: Seasonal Dependence of the MJO–ENSO Relationship, J. Climate, 20, 531–543, https://doi.org/10.1175/JCLI4003.1, 2007.
Holland, M. M., Bailey, D. A., Briegleb, B. P., Light, B., and Hunke, E.: Improved sea ice shortwave radiation physics in CCSM4: the impact of melt ponds and aerosols on arctic sea ice, J. Climate, 25, 1413–1430, https://doi.org/10.1175/JCLI-D-11-00078.1, 2012.
Hoose, C., Kristjánsson, J. E., Iversen, T., Kirkevåg, A., Seland, Ø., and Gettelman, A.: Constraining cloud droplet number concentration in GCMs suppresses the aerosol indirect effect, Geophys. Res. Lett., 36, L12807, https://doi.org/10.1029/2009GL038568, 2009.
Hoose, C., Kristjánsson, J. E., Chen, J. P., and Hazra, A.: A classical-theory-based parameterization of heterogeneous ice nucleation by mineral dust, soot, and biological particles in a global climate model, J. Atmos. Sci., 67, 2483–2503, https://doi.org/10.1175/2010JAS3425.1, 2010.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., and Wolff, D. B.: The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales, J. Hydrometeorol., 8, 38–55, https://doi.org/10.1175/JHM560.1, 2007.
Huffman, G. J., Adler, R. F., Bolvin, D. T., and Gu, G.: Improving the global precipitation record: GPCP Version 2.1, Geophys. Res. Lett., 36, L17808, https://doi.org/10.1029/2009GL040000, 2009.
Hunke, E. C. and Lipscomb, W. H.: CICE: the Los Alamos Sea Ice Model, documentation and software, version 4.0, Tech. Rep. LA-CC-06-012, Los Alamos National Laboratory, Los Alamos, New Mexico, USA, 2008.
Hurrell, J. W., Hack, J. J., Phillips, A. S., Caron, J., and Yin, J.: The dynamical simulation of the community atmosphere model version, J. Climate, 19, 2162–2183, https://doi.org/10.1175/JCLI3762.1, 2006.
Iversen, T.: Preface to special issue on RegClim, Tellus A, 60, 395–397, https://doi.org/10.1111/j.1600-0870.2008.00319.x, 2008.
Iversen, T., Bentsen, M., Bethke, I., Debernard, J. B., Kirkevåg, A., Seland, Ø., Drange, H., Kristjansson, J. E., Medhaug, I., Sand, M., and Seierstad, I. A.: The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections, Geosci. Model Dev., 6, 389–415, https://doi.org/10.5194/gmd-6-389-2013, 2013.
Jayne, S. R.: The impact of abyssal mixing parameterizations in an ocean general circulation model, J. Phys. Oceanogr., 39, 1756–1775, https://doi.org/10.1175/2009JPO4085.1, 2009.
Jiang, J. H., Su, H., Zhai, C., Perun, V. S., Genio, A. D., Nazarenko, L. S., Donner, L. J., Horowitz, L., Seman, C., Cole, J., Gettelman, A., Ringer, M. A., Rotstayn, L., Jeffrey, S., Wu, T., Brient, F., Dufresne, J.-L., Kawai, H., Koshiro, T., Watanabe, M., L'Ecuyer, T. S., Volodin, E. M., Iversen, T., Drange, H., Mesquita, M. D. S., Read, W. G., Waters, J. W., Tian, B., Teixeira, J., and Stephens, G. L.: Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA "A-Train" satellite observations, J. Geophys. Res., 117, D14105, https://doi.org/10.1029/2011JD017237, 2012.
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D., Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D., Gobron, N., Kiely, G., Kutsch, W., Lasslop, G., Law, B. E., Lindroth, A., Merbold, L., Montagnani, L., Moors, E. J., Papale, D., Sottocornola, M., Vaccari, F., and Williams, C.: Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations, J. Geophys. Res., 116, G00J07, https://doi.org/10.1029/2010JG001566, 2011.
Jungclaus, J. H. and Koenigk, T.: Low-frequency variability of the arctic climate: the role of oceanic and atmospheric heat transport variations, Clim. Dynam., 34, 265–279, https://doi.org/10.1007/s00382-009-0569-9, 2010.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, Bull. Amer. Meteor. Soc., 77, 437–471, 1996.
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S. K., Hnilo, J. J., Fiorino, M., and Potter, G. L.: NCEP-DOE AMIP-II reanalysis (R-2), Bull. Amer. Meteor. Soc., 83, 1631–1643, https://doi.org/10.1175/BAMS-83-11-1631, 2002.
Kiehl, J. T. and Trenberth, K. E.: Earth's annual global mean energy budget, Bull. Amer. Meteor. Soc., 78, 197–208, 1997.
Kirkevåg, A., Iversen, T., Kristjánsson, J. E., Seland, Ø., and Debernard, J. B.: On the additivity of climate response to anthropogenic aerosols and CO2, and the enhancement of future global warming by carbonaceous aerosols, Tellus A, 60, 513–527, https://doi.org/10.1111/j.1600-0870.2008.00308.x, 2008a.
Kirkevåg, A., Iversen, T., Seland, Ø., Debernard, J. B., Storelvmo, T., and Kristjánsson, J. E.: Aerosol-cloud-climate interactions in the climate model CAM-Oslo, Tellus A, 60, 492–512, https://doi.org/10.1111/j.1600-0870.2008.00313.x, 2008b.
Kirkevåg, A., Iversen, T., Seland, Ø., Hoose, C., Kristjánsson, J. E., Struthers, H., Ekman, A. M. L., Ghan, S., Griesfeller, J., Nilsson, E. D., and Schulz, M.: Aerosol-climate interactions in the Norwegian Earth System Model – NorESM1-M, Geosci. Model Dev., 6, 207–244, https://doi.org/10.5194/gmd-6-207-2013, 2013.
Kraus, E. B. and Turner, J. S.: A one-dimensional model of the seasonal thermocline –II. The general theory and its consequences, Tellus, 19, 98–105, 1967.
Kristjánsson, J. E.: Studies of the aerosol indirect effect from sulfate and black carbon aerosols, J. Geophys. Res., 107, D15, https://doi.org/10.1029/2001JD000887, 2002.
Kristjánsson, J. E., Iversen, T., Kirkevåg, A., Seland, Ø, and Debernard, J.: Response of the climate system to aerosol direct and indirect forcing: role of cloud feedbacks, J. Geophys. Res., 110, D24206, https://doi.org/10.1029/2005JD006299, 2005.
Kwok, R. and Cunningham, G. F.: ICESat over Arctic sea ice: estimation of snow depth and ice thickness, J. Geophys. Res., 113, C08010, https://doi.org/10.1029/2008JC004753, 2008.
Kwok, R. and Rothrock, D. A.: Decline in Arctic sea ice thickness from submarine and ICESat records: 1958–2008, Geophys. Res. Lett., 36, L15501, https://doi.org/10.1029/2009GL039035, 2009.
Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., Shindell, D., Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M., Mahowald, N., McConnell, J. R., Naik, V., Riahi, K., and van Vuuren, D. P.: Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application, Atmos. Chem. Phys., 10, 7017–7039, https://doi.org/10.5194/acp-10-7017-2010, 2010.
Large, W. G. and Yeager, S.: Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies, Tech. Rep. NCAR/TN-460+STR, National Center for Atmospheric Research, Boulder, Colorado, USA, 2004.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air-sea flux data set, Clim. Dynam., 33, 341–364, https://doi.org/10.1007/s00382-008-0441-3, 2008.
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, 1994.
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson, S. C., Lawrence, P. J., Zeng, X., Yang, Z.-L., Levis, S., Sakaguchi, K., Bonan, G. B., and Slater, A. G.: Parameterization improvements and functional and structural advances in version 4 of the community land model, J. Adv. Model. Earth Syst., 3, M03001, https://doi.org/10.1029/2011MS000045, 2011.
Lean, J., Rottman, G., Harder, J., and Kopp, G.: SORCE contributions to new understanding of global change and solar variability, Solar Phys., 230, 27–53, https://doi.org/10.1007/s11207-005-1527-2, 2005.
L'Ecuyer, T. S., Wood, N. B., Haladay, T., Stephens, G. L., and Stackhouse Jr., P. W.: Impact of clouds on atmospheric heating based on the R04 CloudSat fluxes and heating rates data set, J. Geophys. Res., 113, D00A15, https://doi.org/10.1029/2008JD009951, 2008.
Legates, D. R. and Willmott, C. J.: Mean seasonal and spatial variability in gauge-corrected, global precipitation, Int. J. Climatol., 10, 111–127, 1990.
Legg, S., Hallberg, R. W., and Girton, J. B.: Comparison of entrainment in overflows simulated by z-coordinate, isopycnal and non-hydrostatic models, Ocean Model., 11, 69–97, https://doi.org/10.1016/j.ocemod.2004.11.006, 2006.
Liebmann, B., Hendon, H. H., and Glick, J. D.: The relationship between tropical cyclones of the Western Pacific and Indian Oceans and the Madden–Julian oscillation, J. Meteor. Soc. Japan, 72, 401–412, 1994.
Lin, J. L.: The double-ITCZ problem in IPCC AR4 coupled GCMs: ocean-atmosphere feedback analysis, J. Climate, 20, 4497–4525, https://doi.org/10.1175/JCLI4272.1, 2007.
Lin, J. L., Kiladis, G. N., Mapes, B. E., Weickmann, K. M., Sperber, K. R., Lin, W., Wheeler, M. C., Schubert, S. D., Genio, A. D., Donner, L. J., Emori, S., Gueremy, J. F., Hourdin, F., Rasch, P. J., Roeckner, E., and Scinocca, J. F.: Tropical intraseasonal variability in 14 IPCC AR4 climate models, Part I: convective signals, J. Climate, 19, 2665–2690, https://doi.org/10.1175/JCLI3735.1, 2006.
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World Ocean Atlas 2009, Volume 1: Temperature, in: NOAA Atlas NESDIS 68, edited by: Levitus, S., US Government Printing Office, Washington, D.C., 184 pp., 2010.
Loeb, N. G., Kato, S., Loukachine, K., and Manalo-Smith, N.: Angular distribution models for top-of-atmosphere radiative flux estimation from the clouds and the earths radiant energy system instrument on the Terra satellite, Part I: Methodology, J. Atmos. Ocean. Tech., 22, 338–351, https://doi.org/10.1175/JTECH1712.1, 2005.
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F., Kato, S., Manalo-Smith, N., and Wong, T.: Toward optimal closure of the earth's top-of-atmosphere radiation budget, J. Climate, 22, 748–766, https://doi.org/10.1175/2008JCLI2637.1, 2009.
Loeb, N. G., Lyman, J. M., Johnson, G. C., Allan, R. P., Doelling, D. R., Wong, T., Soden, B. J., and Stephens, G. L.: Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty, Nat. Geosci., 5, 110–113, https://doi.org/10.1038/ngeo1375, 2012.
Lohmann, K., Drange, H., and Bentsen, M.: A possible mechanism for the strong weakening of the North Atlantic subpolar gyre in the mid-1990s, Geophys. Res. Lett., 36, L15602, https://doi.org/10.1029/2009GL039166, 2009.
Madden, R. A. and Julian, P. R.: Detection of a 40–50 day oscillation in the zonal wind in the Tropical Pacific, J. Atmos. Sci., 28, 702–708, 1971.
Maier-Reimer, E.: Geochemical cycles in an ocean general circulation model. Preindustrial tracer distributions, Glob. Biogeochem. Cy., 7, 645–677, https://doi.org/10.1029/93GB01355, 1993.
Maier-Reimer, E., Kriest, I., Segschneider, J., and Wetzel, P.: The HAMburg Ocean Carbon Cycle model HAMOCC 5.1 - Technical description release 1.1, Reports on Earth System Science 14, Max Planck Institute for Meteorology, Hamburg, Germany, 2005.
Marks, K. and Smith, W.: An evaluation of publicly available global bathymetry grids, Mar. Geophys. Res., 27, 19–34, https://doi.org/10.1007/s11001-005-2095-4, 2006.
Maximenko, N., Niiler, P., Rio, M. H., Melnichenko, O., Centurioni, L., Chambers, D., Zlotnicki, V., and Galperin, B.: Mean dynamic topography of the ocean derived from satellite and drifting buoy data using three different techniques, J. Atmos. Ocean. Tech., 26, 1910–1919, https://doi.org/10.1175/2009JTECHO672.1, 2009.
McDougall, T. J. and Jackett, D. R.: An assessment of orthobaric density in the global ocean, J. Phys. Oceanogr., 35, 2054–2075, https://doi.org/10.1175/JPO2796.1, 2005.
Medhaug, I. and Furevik, T.: North Atlantic 20th century multidecadal variability in coupled climate models: sea surface temperature and ocean overturning circulation, Ocean Sci., 7, 389–404, https://doi.org/10.5194/os-7-389-2011, 2011.
Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. T., Gregory, J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., Raper, S. C. B., Watterson, I. G., Weaver, A. J., and Zhao, Z.-C.: Global climate projections, in: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., chap. 10, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 747–845, 2007.
Megann, A. P., New, A. L., Blaker, A. T., and Sinha, B.: The sensitivity of a coupled climate model to its ocean component, J. Climate, 23, 5126–5150, https://doi.org/10.1175/2010JCLI3394.1, 2010.
Mitchell, T. D. and Jones, P. D.: An improved method of constructing a database of monthly climate observations and associated high-resolution grids, Int. J. Climatol., 25, 693–712, https://doi.org/10.1002/joc.1181, 2005.
Morel, Y., Baraille, R., and Pichon, A.: Time splitting and linear stability of the slow part of the barotropic component, Ocean Model., 23, 73–81, https://doi.org/10.1016/j.ocemod.2008.04.001, 2008.
Morice, C. P., Kennedy, J. J., Rayner, N. A., and Jones, P. D.: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: the HadCRUT4 data set, J. Geophys. Res., 117, D08101, https://doi.org/10.1029/2011JD017187, 2012.
Morrison, H. and Gettelman, A.: A new two-moment bulk stratiform cloud microphysics scheme in the community atmosphere model, version 3 (CAM3). Part I: Description and numerical tests, J. Climate, 21, 3642–3659, https://doi.org/10.1175/2008JCLI2105.1, 2008.
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next generation of scenarios for climate change research and assessment, Nature, 463, 747–756, https://doi.org/10.1038/nature08823, 2010.
Munk, W. H.: Abyssal recipes, Deep-Sea Res., 13, 707–730, 1966.
Neale, R. B., Richter, J. H., and Jochum, M.: The impact of convection on ENSO: from a delayed oscillator to a series of events, J. Climate, 21, 5904–5924, https://doi.org/10.1175/2008JCLI2244.1, 2008.
Neale, R. B., Richter, J. H., Conley, A. J., Park, S., Lauritzen, P. H., Gettelman, A., Williamson, D. L., Rasch, P. J., Vavrus, S. J., Taylor, M. A., Collins, W. D., Zhang, M., and Lin, S.-J.: Description of the NCAR Community Atmosphere Model (CAM 4.0), Tech. Rep. NCAR/TN-485+STR, National Center for Atmospheric Research, Boulder, Colorado, USA, 2010.
Neale, R. B., Richter, J., Park, S., Lauritzen, P. H., Vavrus, S. J., Rasch, P. J., and Zhang, M.: The mean climate of the Community Atmosphere Model (CAM4) in forced SST and fully coupled experiments, J. Climate, https://doi.org/10.1175/JCLI-D-12-00236.1, in press, 2013.
Oberhuber, J. M.: Simulation of the Atlantic circulation with a coupled sea ice-mixed layer-isopycnal general circulation model, Part I: Model description, J. Phys. Oceanogr., 23, 808–829, 1993.
O'Dell, C. W., Wentz, F. J., and Bennartz, R.: Cloud liquid water path from satellite-based passive microwave observations: a new climatology over the global oceans, J. Climate, 21, 1721–1739, https://doi.org/10.1175/2007JCLI1958.1, 2008.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E., Lawrence, P. J., Levis, S., Swenson, S. C., Thornton, P. E., Dai, A., Decker, M., Dickinson, R., Feddema, J., Heald, C. L., Hoffman, F., Lamarque, J.-F., Mahowald, N., Niu, G.-Y., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stöckli, R., Wang, A., Yang, Z.-L., Zeng, X., and Zeng, X.: Technical Description of version 4.0 of the Community Land Model (CLM), Tech. Rep. NCAR/TN-478+STR, National Center for Atmospheric Research, Boulder, Colorado, USA, 2010.
Onogi, K., Tsutsui, J., Koide, H., Sakamoto, M., Kobayashi, S., Hatsushika, H., Matsumoto, T., Yamazaki, N., Kamahori, H., Takahashi, K., Kadokura, S., Wada, K., Kato, K., Oyama, R., Ose, T., Mannoji, N., and Taira, R.: The JRA-25 reanalysis, J. Meteor. Soc. Jpn., 85, 369–432, 2007.
Orre, S., Smith, J. N., Alfimov, V., and Bentsen, M.: Simulating transport of 129I and idealized tracers in the Northern North Atlantic Ocean, Environ. Fluid Mech., 10, 213–233, https://doi.org/10.1007/s10652-009-9138-3, 2010.
Osborn, T. J.: Simulating the winter North Atlantic oscillation: the roles of internal variability and greenhouse gas forcing, Clim. Dynam., 22, 605–623, https://doi.org/10.1007/s00382-004-0405-1, 2004.
Otterå, O. H., Bentsen, M., Bethke, I., and Kvamstø, N. G.: Simulated pre-industrial climate in Bergen Climate Model (version 2): model description and large-scale circulation features, Geosci. Model Dev., 2, 197–212, https://doi.org/10.5194/gmd-2-197-2009, 2009.
Otterå, O. H., Bentsen, M., Drange, H., and Suo, L.: External forcing as a metronome for Atlantic multidecadal variability, Nat. Geosci., 3, 688–694, https://doi.org/10.1038/ngeo955, 2010.
Palmer, T. N.: A nonlinear dynamical perspective on climate prediction, J. Climate, 12, 575–591, 1999.
Quenouille, M. H.: Associated Measurements, Butterworths Scientific, London, 242 pp., 1952.
Räisänen, J.: CO2-induced climate change in CMIP2 experiments: quantification of agreement and role of internal variability, J. Climate, 14, 2088–2104, 2001.
Rasch, P. J. and Kristjánsson, J. E.: A comparison of the CCM3 model climate using diagnosed and predicted condensate parameterizations, J. Climate, 11, 1587–1614, 1998.
Rasch, P. J., Coleman, D. B., Mahowald, N., Williamson, D. L., Lin, S. J., Boville, B. A., and Hess, P.: Characteristics of atmospheric transport using three numerical formulations for atmospheric dynamics in a single GCM framework, J. Climate, 19, 2243–2266, https://doi.org/10.1175/JCLI3763.1, 2006.
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003.
Reichler, T. and Kim, J.: How well do coupled models simulate today's climate?, Bull. Amer. Meteor. Soc., 89, 303–311, https://doi.org/10.1175/BAMS-89-3-303, 2008.
Richter, J. H. and Rasch, P. J.: Effects of convective momentum transport on the atmospheric circulation in the community atmosphere model, version 3, J. Climate, 21, 1487–1499, https://doi.org/10.1175/2007JCLI1789.1, 2008.
Rossow, W. B. and Dueñas, E. N.: The International Satellite Cloud Climatology Project (ISCCP) web site: an online resource for research, Bull. Amer. Meteor. Soc., 85, 167–172, https://doi.org/10.1175/BAMS-85-2-167, 2004.
Rossow, W. B. and Schiffer, R. A.: Advances in understanding clouds from ISCCP, Bull. Amer. Meteor. Soc., 80, 2261–2287, 1999.
Rothrock, D. A., Percival, D. B., and Wensnahan, M.: The decline in arctic sea-ice thickness: separating the spatial, annual, and interannual variability in a quarter century of submarine data, J. Geophys. Res., 113, C05003, https://doi.org/10.1029/2007JC004252, 2008.
Rotstayn, L. D. and Lohmann, U.: Tropical rainfall trends and the indirect aerosol effect, J. Climate, 15, 2103–2116, 2002.
Sadourny, R.: The dynamics of finite-difference models of the shallow-water equations, J. Atmos. Sci., 32, 680–689, 1975.
Seager, R., Battisti, D. S., Yin, J., Gordon, N., Naik, N., Clement, A. C., and Cane, M. A.: Is the Gulf Stream responsible for Europes mild winters?, Q. J. Roy. Meteorol. Soc., 128, 2563–2586, 2002.
Seethala, C. and Horváth, \'A.: Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds, J. Geophys. Res., 115, D13202, https://doi.org/10.1029/2009JD012662, 2010.
Seland, Ø, Iversen, T., Kirkevåg, A., and Storelvmo, T.: Aerosol-climate interactions in the CAM-Oslo atmospheric GCM and investigation of associated basic shortcomings, Tellus A, 60, 459–491, https://doi.org/10.1111/j.1600-0870.2008.00318.x, 2008.
Shaffrey, L. and Sutton, R.: Bjerknes compensation and the decadal variability of the energy transports in a coupled climate model, J. Climate, 19, 1167–1181, https://doi.org/10.1175/JCLI3652.1, 2006.
Simmons, H. L., Jayne, S. R., St. Laurent, L. C., and Weaver, A. J.: Tidally driven mixing in a numerical model of the ocean general circulation, Ocean Model., 6, 245–263, https://doi.org/10.1016/S1463-5003(03)00011-8, 2004.
Sorteberg, A., Furevik, T., Drange, H., and Kvamstø, N. G.: Effects of simulated natural variability on Arctic temperature projections, Geophys. Res. Lett., 32, L18708, https://doi.org/10.1029/2005GL023404, 2005.
Spencer, R. W.: Global oceanic precipitation from the MSU during 1979–91 and comparisons to other climatologies, J. Climate, 6, 1301–1326, 1993.
Srokosz, M., Baringer, M., Bryden, H., Cunningham, S., Delworth, T., Lozier, S., Marotzke, J., and Sutton, R.: Past, present, and future changes in the Atlantic meridional overturning circulation, Bull. Amer. Meteor. Soc., 93, 1663–1676, https://doi.org/10.1175/BAMS-D-11-00151.1, 2012.
Steele, M., Morley, R., and Ermold, W.: PHC: A global ocean hydrography with a high-quality Arctic Ocean, J. Climate, 14, 2079–2087, 2001.
Storelvmo, T., Kristjánsson, J. E., Ghan, S. J., Kirkevåg, A., Seland, Ø., and Iversen, T.: Predicting cloud droplet number concentration in Community Atmosphere Model (CAM)-Oslo, J. Geophys. Res., 111, D24208, https://doi.org/10.1029/2005JD006300, 2006.
Stroeve, J. C., Serreze, M. C., Holland, M. M., Kay, J. E., Malanik, J., and Barrett, A. P.: The Arctic's rapidly shrinking sea ice cover: a research synthesis, Clim. Change, 110, 1005–1027, https://doi.org/10.1007/s10584-011-0101-1, 2012.
Struthers, H., Ekman, A. M. L., Glantz, P., Iversen, T., Kirkevåg, A., Mårtensson, E. M., Seland, Ø., and Nilsson, E. D.: The effect of sea ice loss on sea salt aerosol concentrations and the radiative balance in the Arctic, Atmos. Chem. Phys., 11, 3459–3477, https://doi.org/10.5194/acp-11-3459-2011, 2011.
Subramanian, A. C., Jochum, M., Miller, A. J., Murtugudde, R., Neale, R. B., and Waliser, D. E.: The Madden–Julian oscillation in CCSM4, J. Climate, 24, 6261–6282, https://doi.org/10.1175/JCLI-D-11-00031.1, 2011.
Sun, S., Bleck, R., Rooth, C., Dukowicz, J., Chassignet, E., and Killworth, P.: Inclusion of thermobaricity in isopycnic-coordinate ocean models, J. Phys. Oceanogr., 29, 2719–2729, 1999.
Sutton, R. T. and Hodson, D. L. R.: Atlantic ocean forcing of North American and European summer climate, Science, 309, 115–118, https://doi.org/10.1126/science.1109496, 2005.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the experiment design, Bull. Amer. Meteor. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Thompson, D. W. J. and Wallace, J. M.: Annular modes in the extratropical circulation, Part I: month-to-month variability, J. Climate, 13, 1000–1016, 2000.
Thornton, P. E., Lamarque, J.-F., Rosenbloom, N. A., and Mahowald, N. M.: Influence of carbon-nitrogen cycle coupling on land model response to CO2 fertilization and climate variability, Global Biogeochem. Cy., 21, GB4018, https://doi.org/10.1029/2006GB002868, 2007.
Ting, M., Kushnir, Y., Seager, R., and Li, C.: Robust features of Atlantic multi-decadal variability and its climate impacts, Geophys. Res. Lett., 38, L17705, https://doi.org/10.1029/2011GL048712, 2011.
Tjiputra, J. F., Assmann, K., Bentsen, M., Bethke, I., Otterå, O. H., Sturm, C., and Heinze, C.: Bergen Earth system model (BCM-C): model description and regional climate-carbon cycle feedbacks assessment, Geosci. Model Dev., 3, 123–141, https://doi.org/10.5194/gmd-3-123-2010, 2010.
Tjiputra, J. F., Roelandt, C., Bentsen, M., Lawrence, D. M., Lorentzen, T., Schwinger, J., Seland, Ø., and Heinze, C.: Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM), Geosci. Model Dev., 6, 301–325, https://doi.org/10.5194/gmd-6-301-2013, 2013.
Trenberth, K. E. and Shea, D. J.: Atlantic hurricanes and natural variability in 2005, Geophys. Res. Lett., 33, L12704, https://doi.org/10.1029/2006GL026894, 2006.
Trenberth, K. E., Branstator, G. W., Karoly, D., Kumar, A., Lau, N. C., and Ropelewski, C.: Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures, J. Geophys. Res., 103, 14291–14324, https://doi.org/10.1029/97JC01444, 1998.
Trenberth, K. E., Smith, L., Qian, T., Dai, A., and Fasullo, J.: Estimates of the global water budget and its annual cycle using observational and model data, J. Hydrometeorol., 8, 758–769, https://doi.org/10.1175/JHM600.1, 2007.
Trenberth, K. E., Fasullo, J. T., and Mackaro, J.: Atmospheric moisture transports from ocean to land and global energy flows in reanalyses, J. Climate, 24, 4907–4924, https://doi.org/10.1175/2011JCLI4171.1, 2011.
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J. F., Morcrette, J. J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40 re-analysis, Quart. J. Roy. Meteorol. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176, 2005.
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J. F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The representative concentration pathways: an overview, Climate Change, 109, 5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011.
Vertenstein, M., Craig, T., Middleton, A., Feddema, D., and Fischer, C.: CCSM4.0 User's Guide, available at: http://www.cesm.ucar.edu/models/ccsm4.0/ccsm_doc/book1.htm (last access: August 2012), 2010.
Waliser, D., Sperber, K., Hendon, H., Kim, D., Wheeler, M., Weickmann, K., Zhang, C., Donner, L., Gottschalck, J., Higgins, W., Kang, I. S., Legler, D., Moncrieff, M., Vitart, F., Wang, B., Wang, W., Woolnough, S., Maloney, E., Schubert, S., and Stern, W.: MJO simulation diagnostics, J. Climate, 22, 3006–3030, https://doi.org/10.1175/2008JCLI2731.1, 2009.
Wallace, J. M., Zhang, Y., and Bajuk, L.: Interpretation of interdecadal trends in Northern Hemisphere surface air temperature, J. Climate, 9, 249–259, 1996.
Wallace, J. M., Rasmusson, E. M., Mitchell, T. P., Kousky, V. E., Sarachik, E. S., and von Storch, H.: On the structure and evolution of ENSO-related climate variability in the tropical Pacific: lessons from TOGA, J. Geophys. Res., 103, 14241–14259, https://doi.org/10.1029/97JC02905, 1998.
Wang, Y. M., Lean, J. L., and Sheeley Jr., N. R.: Modeling the sun's magnetic field and irradiance since 1713, Astrophys. J., 625, 522–538, https://doi.org/10.1086/429689, 2005.
Wentz, F. J.: A well-calibrated ocean algorithm for special sensor microwave/imager, J. Geophys. Res., 102, 8703–8718, https://doi.org/10.1029/96JC01751, 1997.
Worby, A. P., Geiger, C. A., Paget, M. J., Woert, M. L. V., Ackley, S. F., and DeLiberty, T. L.: Thickness distribution of Antarctic sea ice, J. Geophys. Res., 113, C05S92, https://doi.org/10.1029/2007JC004254, 2008.
Yu L. and Weller, R. A.: Objectively analyzed air-sea heat fluxes for the global ice-free oceans (1981–2005), Bull. Amer. Meteor. Soc., 88, 527–539, https://doi.org/10.1175/BAMS-88-4-527, 2007.
Yu, L., Jin, X., and Weller, R. A.: Multidecade Global Flux Datasets from the Objectively Analyzed Air-sea Fluxes (OAFlux) Project: Latent and sensible heat fluxes, ocean evaporation, and related surface meteorological variables, Tech. Rep. OA-2008-01, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA, 2008.
Zhang, C.: Madden–Julian oscillation, Rev. Geophys., 43, RG2003, https://doi.org/10.1029/2004RG000158, 2005.
Zhang, G. J. and McFarlane, N. A.: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model, Atmos. Ocean, 33, 407–446, 1995.
Zhang, Z. S., Nisancioglu, K., Bentsen, M., Tjiputra, J., Bethke, I., Yan, Q., Risebrobakken, B., Andersson, C., and Jansen, E.: Pre-industrial and mid-Pliocene simulations with NorESM-L, Geosci. Model Dev., 5, 523–533, https://doi.org/10.5194/gmd-5-523-2012, 2012.
