Articles | Volume 12, issue 8
Geosci. Model Dev., 12, 3481–3501, 2019
https://doi.org/10.5194/gmd-12-3481-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 12, 3481–3501, 2019
https://doi.org/10.5194/gmd-12-3481-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper 07 Aug 2019
Model evaluation paper | 07 Aug 2019
The road weather model RoadSurf (v6.60b) driven by the regional climate model HCLIM38: evaluation over Finland
Erika Toivonen et al.
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Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni-Pekka Pietikäinen, Ernesto Rodríguez-Camino, Patrick Samuelsson, Erik van Meijgaard, and Minchao Wu
Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, https://doi.org/10.5194/gmd-13-1311-2020, 2020
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A new regional climate modelling system, HCLIM38, is presented and shown to be applicable in different regions ranging from the tropics to the Arctic. The main focus is on climate simulations at horizontal resolutions between 1 and 4 km, the so-called convection-permitting scales, even though the model can also be used at coarser resolutions. The benefits of simulating climate at convection-permitting scales are shown and are particularly evident for climate extremes.
Ana A. Piedehierro, André Welti, Angela Buchholtz, Kimmo Korhonen, Iida Pullinen, Ilkka Summanen, Annele Virtanen, and Ari Laaksonen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-10, https://doi.org/10.5194/acp-2021-10, 2021
Preprint under review for ACP
Juha Tonttila, Ali Afzalifar, Harri Kokkola, Tomi Raatikainen, Hannele Korhonen, and Sami Romakkaniemi
Atmos. Chem. Phys., 21, 1035–1048, https://doi.org/10.5194/acp-21-1035-2021, https://doi.org/10.5194/acp-21-1035-2021, 2021
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The focus of this study is on rain enhancement by deliberate injection of small particles into clouds (
cloud seeding). The particles, usually released from an aircraft, are expected to enhance cloud droplet growth, but its practical feasibility is somewhat uncertain. To improve upon this, we simulate the seeding effects with a numerical model. The model reproduces the main features seen in field observations, with a strong sensitivity to the total mass of the injected particle material.
André Welti, Kimmo Korhonen, Pasi Miettinen, Ana A. Piedehierro, Yrjö Viisanen, Annele Virtanen, and Ari Laaksonen
Atmos. Meas. Tech., 13, 7059–7067, https://doi.org/10.5194/amt-13-7059-2020, https://doi.org/10.5194/amt-13-7059-2020, 2020
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We describe a modification of the SPectrometer for Ice Nuclei (SPIN) chamber to study ice nucleation at low temperatures, relevant for ice formation in cirrus clouds. Validation experiments of homogeneous freezing of aqueous ammonium sulfate droplets and heterogeneous ice nucleation on silver iodide particles are included to demonstrate the advantages of the modified SPIN chamber for the investigation of ice nucleation in the extended temperature range.
Twan van Noije, Tommi Bergman, Philippe Le Sager, Declan O'Donnell, Risto Makkonen, María Gonçalves-Ageitos, Ralf Döscher, Uwe Fladrich, Jost von Hardenberg, Jukka-Pekka Keskinen, Hannele Korhonen, Anton Laakso, Stelios Myriokefalitakis, Pirkka Ollinaho, Carlos Pérez García-Pando, Thomas Reerink, Roland Schrödner, Klaus Wyser, and Shuting Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-413, https://doi.org/10.5194/gmd-2020-413, 2020
Preprint under review for GMD
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This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). We describe the model in detail and provide information about the applied tuning and spin-up procedures. The model's performance is characterized using coupled simulations conducted for CMIP6. The model has an effective equilibrium climate sensitivity of 3.9 °C and a transient climate response of 2.1 °C.
Joonas Merikanto, Kalle Nordling, Petri Räisänen, Jouni Räisänen, Declan O'Donnell, Antti-Ilari Partanen, and Hannele Korhonen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1029, https://doi.org/10.5194/acp-2020-1029, 2020
Preprint under review for ACP
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Human-induced aerosols concentrate around their emission sources, yet their climate effects span far and wide. Here, we use two climate models to robustly explore the mechanisms how Asian aerosols impact temperatures across the globe. A total removal of Asian aerosols increases the global temperatures by 0.26 ± 0.04 °C in the models, with most of the uncertainty arising from modelled cloud responses.
Ari Laaksonen, Jussi Malila, and Athanasios Nenes
Atmos. Chem. Phys., 20, 13579–13589, https://doi.org/10.5194/acp-20-13579-2020, https://doi.org/10.5194/acp-20-13579-2020, 2020
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Aerosol particles containing black carbon are ubiquitous in the atmosphere and originate from combustion processes. We examine their capability to act as condensation centers for water vapor. We make use of published experimental data sets for different types of black carbon particles, ranging from very pure particles to particles that contain both black carbon and water soluble organic matter, and we show that a recently developed theory reproduces most of the experimental results.
Jaakko Ahola, Hannele Korhonen, Juha Tonttila, Sami Romakkaniemi, Harri Kokkola, and Tomi Raatikainen
Atmos. Chem. Phys., 20, 11639–11654, https://doi.org/10.5194/acp-20-11639-2020, https://doi.org/10.5194/acp-20-11639-2020, 2020
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In this study, we present an improved cloud model that reproduces the behaviour of mixed-phase clouds containing liquid droplets and ice crystals in more detail than before. This model is a convenient computational tool that enables the study of phenomena that cannot fit into a laboratory. These clouds have a significant role in climate, but they are not yet properly understood. Here, we show the advantages of the new model in a case study focusing on Arctic mixed-phase clouds.
Maria Filioglou, Elina Giannakaki, John Backman, Jutta Kesti, Anne Hirsikko, Ronny Engelmann, Ewan O'Connor, Jari T. T. Leskinen, Xiaoxia Shang, Hannele Korhonen, Heikki Lihavainen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 20, 8909–8922, https://doi.org/10.5194/acp-20-8909-2020, https://doi.org/10.5194/acp-20-8909-2020, 2020
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Dust optical properties are region-dependent. Saharan, Asian, and Arabian dusts do not pose similar optical properties in terms of lidar ratios; thus, a universal lidar ratio for dust particles will lead to biases. The present study analyses observations over the United Arab Emirates, quantifying the optical and geometrical extents of the aerosol layers in the area, providing at the same time the Arabian dust properties along with chemical analysis of dust samples collected in the region.
Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni-Pekka Pietikäinen, Ernesto Rodríguez-Camino, Patrick Samuelsson, Erik van Meijgaard, and Minchao Wu
Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, https://doi.org/10.5194/gmd-13-1311-2020, 2020
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A new regional climate modelling system, HCLIM38, is presented and shown to be applicable in different regions ranging from the tropics to the Arctic. The main focus is on climate simulations at horizontal resolutions between 1 and 4 km, the so-called convection-permitting scales, even though the model can also be used at coarser resolutions. The benefits of simulating climate at convection-permitting scales are shown and are particularly evident for climate extremes.
Giulia Saponaro, Moa K. Sporre, David Neubauer, Harri Kokkola, Pekka Kolmonen, Larisa Sogacheva, Antti Arola, Gerrit de Leeuw, Inger H. H. Karset, Ari Laaksonen, and Ulrike Lohmann
Atmos. Chem. Phys., 20, 1607–1626, https://doi.org/10.5194/acp-20-1607-2020, https://doi.org/10.5194/acp-20-1607-2020, 2020
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The understanding of cloud processes is based on the quality of the representation of cloud properties. We compared cloud parameters from three models with satellite observations. We report on the performance of each data source, highlighting strengths and deficiencies, which should be considered when deriving the effect of aerosols on cloud properties.
Kalle Nordling, Hannele Korhonen, Petri Räisänen, Muzaffer Ege Alper, Petteri Uotila, Declan O'Donnell, and Joonas Merikanto
Atmos. Chem. Phys., 19, 9969–9987, https://doi.org/10.5194/acp-19-9969-2019, https://doi.org/10.5194/acp-19-9969-2019, 2019
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We carry out long equilibrium climate simulations with two modern climate models and show that the climate model dynamic response contributes strongly to the anthropogenic aerosol response. We demonstrate that identical aerosol descriptions do not improve climate model skill to estimate regional anthropogenic aerosol impacts. Our experiment utilized two independent climate models (NorESM and ECHAM6) with an identical description for aerosols optical properties and indirect effect.
Laura Rontu, Joni-Pekka Pietikäinen, and Daniel Martin Perez
Adv. Sci. Res., 16, 129–136, https://doi.org/10.5194/asr-16-129-2019, https://doi.org/10.5194/asr-16-129-2019, 2019
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Radiative transfer calculations in numerical weather prediction (NWP)
and climate models require reliable information about aerosol
concentration in the atmosphere, combined with data on aerosol optical
properties. Data from the Copernicus atmosphere monitoring service
(CAMS) and European Centre for Medium-Range Weather Forecasts (ECMWF)
were implemented to the limited area, short-range HARMONIE-AROME NWP
model.
Tuomo Nieminen, Veli-Matti Kerminen, Tuukka Petäjä, Pasi P. Aalto, Mikhail Arshinov, Eija Asmi, Urs Baltensperger, David C. S. Beddows, Johan Paul Beukes, Don Collins, Aijun Ding, Roy M. Harrison, Bas Henzing, Rakesh Hooda, Min Hu, Urmas Hõrrak, Niku Kivekäs, Kaupo Komsaare, Radovan Krejci, Adam Kristensson, Lauri Laakso, Ari Laaksonen, W. Richard Leaitch, Heikki Lihavainen, Nikolaos Mihalopoulos, Zoltán Németh, Wei Nie, Colin O'Dowd, Imre Salma, Karine Sellegri, Birgitta Svenningsson, Erik Swietlicki, Peter Tunved, Vidmantas Ulevicius, Ville Vakkari, Marko Vana, Alfred Wiedensohler, Zhijun Wu, Annele Virtanen, and Markku Kulmala
Atmos. Chem. Phys., 18, 14737–14756, https://doi.org/10.5194/acp-18-14737-2018, https://doi.org/10.5194/acp-18-14737-2018, 2018
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Atmospheric aerosols have diverse effects on air quality, human health, and global climate. One important source of aerosols is their formation via nucleation and growth in the atmosphere. We have analyzed long-term observations of regional new particle formation events around the globe and provide a comprehensive view on the characteristics of this phenomenon in diverse environments. The results are useful in developing more realistic representation of atmospheric aerosols in global models.
Harri Kokkola, Thomas Kühn, Anton Laakso, Tommi Bergman, Kari E. J. Lehtinen, Tero Mielonen, Antti Arola, Scarlet Stadtler, Hannele Korhonen, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Ina Tegen, Colombe Siegenthaler-Le Drian, Martin G. Schultz, Isabelle Bey, Philip Stier, Nikos Daskalakis, Colette L. Heald, and Sami Romakkaniemi
Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, https://doi.org/10.5194/gmd-11-3833-2018, 2018
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In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.
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.
Jorma Joutsensaari, Matthew Ozon, Tuomo Nieminen, Santtu Mikkonen, Timo Lähivaara, Stefano Decesari, M. Cristina Facchini, Ari Laaksonen, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 18, 9597–9615, https://doi.org/10.5194/acp-18-9597-2018, https://doi.org/10.5194/acp-18-9597-2018, 2018
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New particle formation (NPF) in the atmosphere is globally an important source of aerosol particles. NPF events are typically identified and analyzed manually by researchers from particle size distribution data day by day, which is time consuming and might be inconsistent. We have developed an automatic analysis method based on deep learning for NPF event identification. The developed method can be easily utilized to analyze any long-term datasets more accurately and consistently.
Joni-Pekka Pietikäinen, Tiina Markkanen, Kevin Sieck, Daniela Jacob, Johanna Korhonen, Petri Räisänen, Yao Gao, Jaakko Ahola, Hannele Korhonen, Ari Laaksonen, and Jussi Kaurola
Geosci. Model Dev., 11, 1321–1342, https://doi.org/10.5194/gmd-11-1321-2018, https://doi.org/10.5194/gmd-11-1321-2018, 2018
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The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation and that the model can reproduce surface water temperature, ice depth and ice season length with reasonably high accuracy.
Andreas Kürten, Chenxi Li, Federico Bianchi, Joachim Curtius, António Dias, Neil M. Donahue, Jonathan Duplissy, Richard C. Flagan, Jani Hakala, Tuija Jokinen, Jasper Kirkby, Markku Kulmala, Ari Laaksonen, Katrianne Lehtipalo, Vladimir Makhmutov, Antti Onnela, Matti P. Rissanen, Mario Simon, Mikko Sipilä, Yuri Stozhkov, Jasmin Tröstl, Penglin Ye, and Peter H. McMurry
Atmos. Chem. Phys., 18, 845–863, https://doi.org/10.5194/acp-18-845-2018, https://doi.org/10.5194/acp-18-845-2018, 2018
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A recent laboratory study (CLOUD) showed that new particles nucleate efficiently from sulfuric acid and dimethylamine (DMA). The reanalysis of previously published data reveals that the nucleation rates are even faster than previously assumed, i.e., nucleation can proceed at rates that are compatible with collision-controlled new particle formation for atmospheric conditions. This indicates that sulfuric acid–DMA nucleation is likely an important source of particles in the boundary layer.
Felix N. Matt, John F. Burkhart, and Joni-Pekka Pietikäinen
Hydrol. Earth Syst. Sci., 22, 179–201, https://doi.org/10.5194/hess-22-179-2018, https://doi.org/10.5194/hess-22-179-2018, 2018
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Certain particles that have the ability to absorb sunlight deposit onto mountain snow via atmospheric transport mechanisms and then lower the snow's ability to reflect sunlight, which increases snowmelt. Herein we present a model aiming to simulate this effect and model the impacts on the streamflow of a southern Norwegian river. We find a significant difference in streamflow between simulations with and without the effect of light absorbing particles applied, in particular during spring melt.
Elham Baranizadeh, Tuomo Nieminen, Taina Yli-Juuti, Markku Kulmala, Tuukka Petäjä, Ari Leskinen, Mika Komppula, Ari Laaksonen, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 17, 13361–13371, https://doi.org/10.5194/acp-17-13361-2017, https://doi.org/10.5194/acp-17-13361-2017, 2017
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Extrapolation of the particle formation rates from one measured larger size (e.g., 7 nm) to smaller sizes (e.g., 3 nm) based on simplified growth-scavenging dynamics works fairly well to estimate mean daily formation rates, but it fails to predict the time evolution of the particle population. This points to the challenges in predicting atmospheric nucleation rates for locations where the particle growth and loss rates are size- and time-dependent.
Anton Laakso, Hannele Korhonen, Sami Romakkaniemi, and Harri Kokkola
Atmos. Chem. Phys., 17, 6957–6974, https://doi.org/10.5194/acp-17-6957-2017, https://doi.org/10.5194/acp-17-6957-2017, 2017
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Based on simulations, equatorial stratospheric sulfur injections have shown to be an efficient strategy to counteract ongoing global warming. However, equatorial injections would result in relatively larger cooling in low latitudes than in high latitudes. This together with greenhouse-gas-induced warming would lead to cooling in the Equator and warming in the high latitudes. Results of this study show that a more optimal cooling effect is achieved by varying the injection area seasonally.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Elham Baranizadeh, Benjamin N. Murphy, Jan Julin, Saeed Falahat, Carly L. Reddington, Antti Arola, Lars Ahlm, Santtu Mikkonen, Christos Fountoukis, David Patoulias, Andreas Minikin, Thomas Hamburger, Ari Laaksonen, Spyros N. Pandis, Hanna Vehkamäki, Kari E. J. Lehtinen, and Ilona Riipinen
Geosci. Model Dev., 9, 2741–2754, https://doi.org/10.5194/gmd-9-2741-2016, https://doi.org/10.5194/gmd-9-2741-2016, 2016
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The molecular mechanisms through which new ultrafine (< 100 nm) aerosol particles are formed in the atmosphere have puzzled the scientific community for decades. In the past few years, however, significant progress has been made in unraveling these processes through laboratory studies and computational efforts. In this work we have implemented these new developments to an air quality model and study the implications of anthropogenically driven particle formation for European air quality.
Tero Mielonen, Anca Hienola, Thomas Kühn, Joonas Merikanto, Antti Lipponen, Tommi Bergman, Hannele Korhonen, Pekka Kolmonen, Larisa Sogacheva, Darren Ghent, Antti Arola, Gerrit de Leeuw, and Harri Kokkola
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-625, https://doi.org/10.5194/acp-2016-625, 2016
Revised manuscript not accepted
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We studied the temperature dependence of AOD and its radiative effects over the southeastern US. We used spaceborne observations of AOD, LST and tropospheric NO2 with simulations of ECHAM-HAMMOZ. The level of AOD in this region is governed by anthropogenic emissions but the temperature dependency is most likely caused by BVOC emissions. According to the observations and simulations, the regional clear-sky DRE for biogenic aerosols is −0.43 ± 0.88 W/m2/K and −0.86 ± 0.06 W/m2/K, respectively.
Markku Kangas, Laura Rontu, Carl Fortelius, Mika Aurela, and Antti Poikonen
Geosci. Instrum. Method. Data Syst., 5, 75–84, https://doi.org/10.5194/gi-5-75-2016, https://doi.org/10.5194/gi-5-75-2016, 2016
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Sodankylä, in the heart of the Arctic Research Centre of the Finnish Meteorological Institute in northern Finland with temperatures ranging from −50 to +30 °C, provides a challenging location for numerical weather forecasting (NWP) models. In this article, the use of measurements performed in Sodankylä for near-real time online verification of NWP models is described. A more specific case study of three different radiation schemes, applicable in NWP model HARMONIE-AROME, is also presented.
Jenni Kontkanen, Emma Järvinen, Hanna E. Manninen, Katrianne Lehtipalo, Juha Kangasluoma, Stefano Decesari, Gian Paolo Gobbi, Ari Laaksonen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 16, 1919–1935, https://doi.org/10.5194/acp-16-1919-2016, https://doi.org/10.5194/acp-16-1919-2016, 2016
J. Kim, L. Ahlm, T. Yli-Juuti, M. Lawler, H. Keskinen, J. Tröstl, S. Schobesberger, J. Duplissy, A. Amorim, F. Bianchi, N. M. Donahue, R. C. Flagan, J. Hakala, M. Heinritzi, T. Jokinen, A. Kürten, A. Laaksonen, K. Lehtipalo, P. Miettinen, T. Petäjä, M. P. Rissanen, L. Rondo, K. Sengupta, M. Simon, A. Tomé, C. Williamson, D. Wimmer, P. M. Winkler, S. Ehrhart, P. Ye, J. Kirkby, J. Curtius, U. Baltensperger, M. Kulmala, K. E. J. Lehtinen, J. N. Smith, I. Riipinen, and A. Virtanen
Atmos. Chem. Phys., 16, 293–304, https://doi.org/10.5194/acp-16-293-2016, https://doi.org/10.5194/acp-16-293-2016, 2016
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The hygroscopicity of nucleated nanoparticles was measured in the presence of sulfuric acid, sulfuric acid-dimethylamine, and sulfuric acid-organics derived from α-pinene oxidation during CLOUD7 at CERN in 2012. The hygroscopicity parameter κ decreased with increasing particle size, indicating decreasing acidity of particles.
A. Laakso, H. Kokkola, A.-I. Partanen, U. Niemeier, C. Timmreck, K. E. J. Lehtinen, H. Hakkarainen, and H. Korhonen
Atmos. Chem. Phys., 16, 305–323, https://doi.org/10.5194/acp-16-305-2016, https://doi.org/10.5194/acp-16-305-2016, 2016
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We have studied the impacts of a volcanic eruption during solar radiation management (SRM) using an aerosol-climate model ECHAM5-HAM-SALSA and an Earth system model MPI-ESM. A volcanic eruption during stratospheric sulfur geoengineering would lead to larger particles and smaller amount of new particles than if an volcano erupts in normal atmospheric conditions. Thus, volcanic eruption during SRM would lead to only a small additional cooling which would last for a significantly shorter period.
A. Laaksonen and J. Malila
Atmos. Chem. Phys., 16, 135–143, https://doi.org/10.5194/acp-16-135-2016, https://doi.org/10.5194/acp-16-135-2016, 2016
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Heterogeneous nucleation is a phenomenon that starts the condensation of supersaturated vapours on solid surfaces. An example is the formation of cirrus clouds in the atmosphere: their formation is often triggered at relative humidities clearly above 100%. We derive a new theory that can be used to calculate the threshold supersaturation of heterogeneous nucleation of water vapour on nanoparticles and show that it performs significantly better than older theories when compared to lab experiment.
J. Joutsensaari, P. Yli-Pirilä, H. Korhonen, A. Arola, J. D. Blande, J. Heijari, M. Kivimäenpää, S. Mikkonen, L. Hao, P. Miettinen, P. Lyytikäinen-Saarenmaa, C. L. Faiola, A. Laaksonen, and J. K. Holopainen
Atmos. Chem. Phys., 15, 12139–12157, https://doi.org/10.5194/acp-15-12139-2015, https://doi.org/10.5194/acp-15-12139-2015, 2015
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Global warming will induce large-scale insect outbreaks in boreal forests. Our results from field and laboratory experiments, satellite observations and global-scale modelling suggest that more frequent insect outbreaks, in addition to temperature-dependent increases in VOC emissions, could result in substantial increases in biogenic SOA formation and therefore affect both aerosol direct and indirect forcing of climate at regional scales. This should be considered in future climate predictions.
J.-P. Pietikäinen, K. Kupiainen, Z. Klimont, R. Makkonen, H. Korhonen, R. Karinkanta, A.-P. Hyvärinen, N. Karvosenoja, A. Laaksonen, H. Lihavainen, and V.-M. Kerminen
Atmos. Chem. Phys., 15, 5501–5519, https://doi.org/10.5194/acp-15-5501-2015, https://doi.org/10.5194/acp-15-5501-2015, 2015
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The global aerosol--climate model ECHAM-HAMMOZ is used to study the aerosol burden and forcing changes in the coming decades. We show that aerosol burdens overall can have a decreasing trend leading to reductions in the direct aerosol effect being globally 0.06--0.4W/m2 by 2030, whereas the aerosol indirect radiative effect could decline 0.25--0.82W/m2. We also show that the targeted emission reduction measures can be a much better choice for the climate than overall high reductions globally.
M. Dalirian, H. Keskinen, L. Ahlm, A. Ylisirniö, S. Romakkaniemi, A. Laaksonen, A. Virtanen, and I. Riipinen
Atmos. Chem. Phys., 15, 3815–3829, https://doi.org/10.5194/acp-15-3815-2015, https://doi.org/10.5194/acp-15-3815-2015, 2015
C. Andersson, R. Bergström, C. Bennet, L. Robertson, M. Thomas, H. Korhonen, K. E. J. Lehtinen, and H. Kokkola
Geosci. Model Dev., 8, 171–189, https://doi.org/10.5194/gmd-8-171-2015, https://doi.org/10.5194/gmd-8-171-2015, 2015
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We have integrated the sectional aerosol dynamics model SALSA into the European scale chemistry-transport model MATCH. The combined model reproduces observed higher particle number concentration (PNCs) in central Europe and lower concentrations in remote regions; however, the total PNC is underestimated. The low nucleation rate coefficient used in this study is an important reason for the underestimation.
S. Schobesberger, A. Franchin, F. Bianchi, L. Rondo, J. Duplissy, A. Kürten, I. K. Ortega, A. Metzger, R. Schnitzhofer, J. Almeida, A. Amorim, J. Dommen, E. M. Dunne, M. Ehn, S. Gagné, L. Ickes, H. Junninen, A. Hansel, V.-M. Kerminen, J. Kirkby, A. Kupc, A. Laaksonen, K. Lehtipalo, S. Mathot, A. Onnela, T. Petäjä, F. Riccobono, F. D. Santos, M. Sipilä, A. Tomé, G. Tsagkogeorgas, Y. Viisanen, P. E. Wagner, D. Wimmer, J. Curtius, N. M. Donahue, U. Baltensperger, M. Kulmala, and D. R. Worsnop
Atmos. Chem. Phys., 15, 55–78, https://doi.org/10.5194/acp-15-55-2015, https://doi.org/10.5194/acp-15-55-2015, 2015
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We used an ion mass spectrometer at CERN's CLOUD chamber to investigate the detailed composition of ammonia--sulfuric acid ion clusters (of both polarities) as they initially form and then grow into aerosol particles, at atmospherically relevant conditions. We found that these clusters’ composition is mainly determined by the ratio of the precursor vapors and ranges from ammonia-free clusters to clusters containing > 1 ammonia per sulfuric acid. Acid--base bindings are a key formation mechanism.
E. M. Dunne, S. Mikkonen, H. Kokkola, and H. Korhonen
Atmos. Chem. Phys., 14, 13631–13642, https://doi.org/10.5194/acp-14-13631-2014, https://doi.org/10.5194/acp-14-13631-2014, 2014
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Marine clouds have a strong effect on the Earth's radiative balance. One proposed climate feedback is that, in a warming climate, marine aerosol emissions will change due to changing wind speeds. We have examined the processes that affect aerosol emissions and removal over 15 years, and high-temporal-resolution output over 2 months. We conclude that wind trends are unlikely to cause a strong feedback in marine regions, but changes in removal processes or transport from continental regions may.
L. Q. Hao, A. Kortelainen, S. Romakkaniemi, H. Portin, A. Jaatinen, A. Leskinen, M. Komppula, P. Miettinen, D. Sueper, A. Pajunoja, J. N. Smith, K. E. J. Lehtinen, D. R. Worsnop, A. Laaksonen, and A. Virtanen
Atmos. Chem. Phys., 14, 13483–13495, https://doi.org/10.5194/acp-14-13483-2014, https://doi.org/10.5194/acp-14-13483-2014, 2014
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Positive matrix factorization (PMF) was applied to the unified high-resolution mass spectra organic species with NO+ and NO2+ ions from the measurement in a mixed region between the boreal forestland and the urban area. The PMF analysis succeeded in separating the mixed spectra into three distinct organic factors and one inorganic factor. The particulate organic nitrate was distinguished by PMF for the first time, with a contribution of one-third of the total nitrate mass.
P. Räisänen, A. Luomaranta, H. Järvinen, M. Takala, K. Jylhä, O. N. Bulygina, K. Luojus, A. Riihelä, A. Laaksonen, J. Koskinen, and J. Pulliainen
Geosci. Model Dev., 7, 3037–3057, https://doi.org/10.5194/gmd-7-3037-2014, https://doi.org/10.5194/gmd-7-3037-2014, 2014
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Snowmelt influences greatly the climatic conditions in spring. This study evaluates the timing of springtime end of snowmelt in the ECHAM5 model. A key finding is that, in much of northern Eurasia, snow disappears too early in ECHAM5, in spite of a slight cold bias in spring. This points to the need for a more comprehensive treatment of the surface energy budget. In particular, the surface temperature for the snow-covered and snow-free parts of a climate model grid cell should be separated.
Y. Gao, T. Markkanen, L. Backman, H. M. Henttonen, J.-P. Pietikäinen, H. M. Mäkelä, and A. Laaksonen
Biogeosciences, 11, 7251–7267, https://doi.org/10.5194/bg-11-7251-2014, https://doi.org/10.5194/bg-11-7251-2014, 2014
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This work studies the biogeophysical impacts of peatland forestation on regional climate conditions in Finland by a regional climate model with two land cover maps produced from Finnish national forest inventories. A warming in spring and a slight cooling in the growing season are found in peatland forestation area, which are mainly induced by the decreased surface albedo and increased ET, respectively. The snow clearance days are advanced. The results are also compared with observational data.
J.-P. Pietikäinen, S. Mikkonen, A. Hamed, A. I. Hienola, W. Birmili, M. Kulmala, and A. Laaksonen
Atmos. Chem. Phys., 14, 11711–11729, https://doi.org/10.5194/acp-14-11711-2014, https://doi.org/10.5194/acp-14-11711-2014, 2014
A.-I. Partanen, E. M. Dunne, T. Bergman, A. Laakso, H. Kokkola, J. Ovadnevaite, L. Sogacheva, D. Baisnée, J. Sciare, A. Manders, C. O'Dowd, G. de Leeuw, and H. Korhonen
Atmos. Chem. Phys., 14, 11731–11752, https://doi.org/10.5194/acp-14-11731-2014, https://doi.org/10.5194/acp-14-11731-2014, 2014
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New parameterizations for the sea spray aerosol source flux and its organic fraction were incorporated into a global aerosol-climate model. The emissions of sea salt were considerably less than previous estimates. This study demonstrates that sea spray aerosol may actually decrease the number of cloud droplets, which has a warming effect on climate. Overall, sea spray aerosol was predicted to have a global cooling effect due to the scattering of solar radiation from sea spray aerosol particles.
S. V. Henriksson, J.-P. Pietikäinen, A.-P. Hyvärinen, P. Räisänen, K. Kupiainen, J. Tonttila, R. Hooda, H. Lihavainen, D. O'Donnell, L. Backman, Z. Klimont, and A. Laaksonen
Atmos. Chem. Phys., 14, 10177–10192, https://doi.org/10.5194/acp-14-10177-2014, https://doi.org/10.5194/acp-14-10177-2014, 2014
H. Portin, A. Leskinen, L. Hao, A. Kortelainen, P. Miettinen, A. Jaatinen, A. Laaksonen, K. E. J. Lehtinen, S. Romakkaniemi, and M. Komppula
Atmos. Chem. Phys., 14, 6021–6034, https://doi.org/10.5194/acp-14-6021-2014, https://doi.org/10.5194/acp-14-6021-2014, 2014
H. Kokkola, P. Yli-Pirilä, M. Vesterinen, H. Korhonen, H. Keskinen, S. Romakkaniemi, L. Hao, A. Kortelainen, J. Joutsensaari, D. R. Worsnop, A. Virtanen, and K. E. J. Lehtinen
Atmos. Chem. Phys., 14, 1689–1700, https://doi.org/10.5194/acp-14-1689-2014, https://doi.org/10.5194/acp-14-1689-2014, 2014
J. Bialek, M. Dall Osto, P. Vaattovaara, S. Decesari, J. Ovadnevaite, A. Laaksonen, and C. O'Dowd
Atmos. Chem. Phys., 14, 1557–1570, https://doi.org/10.5194/acp-14-1557-2014, https://doi.org/10.5194/acp-14-1557-2014, 2014
T. Korhola, H. Kokkola, H. Korhonen, A.-I. Partanen, A. Laaksonen, K. E. J. Lehtinen, and S. Romakkaniemi
Geosci. Model Dev., 7, 161–174, https://doi.org/10.5194/gmd-7-161-2014, https://doi.org/10.5194/gmd-7-161-2014, 2014
A. I. Partanen, A. Laakso, A. Schmidt, H. Kokkola, T. Kuokkanen, J.-P. Pietikäinen, V.-M. Kerminen, K. E. J. Lehtinen, L. Laakso, and H. Korhonen
Atmos. Chem. Phys., 13, 12059–12071, https://doi.org/10.5194/acp-13-12059-2013, https://doi.org/10.5194/acp-13-12059-2013, 2013
G. S. Stuart, R. G. Stevens, A.-I. Partanen, A. K. L. Jenkins, H. Korhonen, P. M. Forster, D. V. Spracklen, and J. R. Pierce
Atmos. Chem. Phys., 13, 10385–10396, https://doi.org/10.5194/acp-13-10385-2013, https://doi.org/10.5194/acp-13-10385-2013, 2013
H. Keskinen, A. Virtanen, J. Joutsensaari, G. Tsagkogeorgas, J. Duplissy, S. Schobesberger, M. Gysel, F. Riccobono, J. G. Slowik, F. Bianchi, T. Yli-Juuti, K. Lehtipalo, L. Rondo, M. Breitenlechner, A. Kupc, J. Almeida, A. Amorim, E. M. Dunne, A. J. Downard, S. Ehrhart, A. Franchin, M.K. Kajos, J. Kirkby, A. Kürten, T. Nieminen, V. Makhmutov, S. Mathot, P. Miettinen, A. Onnela, T. Petäjä, A. Praplan, F. D. Santos, S. Schallhart, M. Sipilä, Y. Stozhkov, A. Tomé, P. Vaattovaara, D. Wimmer, A. Prevot, J. Dommen, N. M. Donahue, R.C. Flagan, E. Weingartner, Y. Viisanen, I. Riipinen, A. Hansel, J. Curtius, M. Kulmala, D. R. Worsnop, U. Baltensperger, H. Wex, F. Stratmann, and A. Laaksonen
Atmos. Chem. Phys., 13, 5587–5600, https://doi.org/10.5194/acp-13-5587-2013, https://doi.org/10.5194/acp-13-5587-2013, 2013
A. I. Hienola, J.-P. Pietikäinen, D. Jacob, R. Pozdun, T. Petäjä, A.-P. Hyvärinen, L. Sogacheva, V.-M. Kerminen, M. Kulmala, and A. Laaksonen
Atmos. Chem. Phys., 13, 4033–4055, https://doi.org/10.5194/acp-13-4033-2013, https://doi.org/10.5194/acp-13-4033-2013, 2013
V.-M. Kerminen, M. Paramonov, T. Anttila, I. Riipinen, C. Fountoukis, H. Korhonen, E. Asmi, L. Laakso, H. Lihavainen, E. Swietlicki, B. Svenningsson, A. Asmi, S. N. Pandis, M. Kulmala, and T. Petäjä
Atmos. Chem. Phys., 12, 12037–12059, https://doi.org/10.5194/acp-12-12037-2012, https://doi.org/10.5194/acp-12-12037-2012, 2012
Related subject area
Climate and Earth system modeling
Understanding the development of systematic errors in the Asian summer monsoon
ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model
Evaluation of polar stratospheric clouds in the global chemistry–climate model SOCOLv3.1 by comparison with CALIPSO spaceborne lidar measurements
Lossy compression of Earth system model data based on a hierarchical tensor with Adaptive-HGFDR (v1.0)
Methane chemistry in a nutshell – the new submodels CH4 (v1.0) and TRSYNC (v1.0) in MESSy (v2.54.0)
Coordinating an operational data distribution network for CMIP6 data
Implementation of sequential cropping into JULESvn5.2 land-surface model
Development of four-dimensional variational assimilation system based on the GRAPES–CUACE adjoint model (GRAPES–CUACE-4D-Var V1.0) and its application in emission inversion
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses
CLIMADA v1.4.1: towards a globally consistent adaptation options appraisal tool
FORTE 2.0: a fast, parallel and flexible coupled climate model
Optimization of the sulfate aerosol hygroscopicity parameter in WRF-Chem
Updated European hydraulic pedotransfer functions with communicated uncertainties in the predicted variables (euptfv2)
Spin-up characteristics with three types of initial fields and the restart effects on forecast accuracy in the GRAPES global forecast system
GTS v1.0: a macrophysics scheme for climate models based on a probability density function
Calibration of temperature-dependent ocean microbial processes in the cGENIE.muffin (v0.9.13) Earth system model
Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations
DiRong1.0: a distributed implementation for improving routing network generation in model coupling
Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations
Geospatial input data for the PALM model system 6.0: model requirements, data sources and processing
Exploring the parameter space of the COSMO-CLM v5.0 regional climate model for the Central Asia CORDEX domain
The benefits of increasing resolution in global and regional climate simulations for European climate extremes
European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)
Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6
A computationally efficient method for probabilistic local warming projections constrained by history matching and pattern scaling, demonstrated by WASP–LGRTC-1.0
R2D2 v2.0: accounting for temporal dependences in multivariate bias correction via analogue rank resampling
Extending the Modular Earth Submodel System (MESSy v2.54) model hierarchy: the ECHAM/MESSy IdeaLized (EMIL) model setup
Boreal summer intraseasonal oscillation in a superparameterized general circulation model: effects of air–sea coupling and ocean mean state
Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response
Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5
A new bias-correction method for precipitation over complex terrain suitable for different climate states: a case study using WRF (version 3.8.1)
A process-based evaluation of the Intermediate Complexity Atmospheric Research Model (ICAR) 1.0.1
ISSM-SLPS: geodetically compliant Sea-Level Projection System for the Ice-sheet and Sea-level System Model v4.17
Newly developed aircraft routing options for air traffic simulation in the chemistry–climate model EMAC 2.53: AirTraf 2.0
Quantifying CanESM5 and EAMv1 sensitivities to Mt. Pinatubo volcanic forcing for the CMIP6 historical experiment
Optimizing high-resolution Community Earth System Model on a heterogeneous many-core supercomputing platform
MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change
Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 2: Sensitivity analysis and model calibration
Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 1: Implementation and model behaviour
Effects of Coupling a Stochastic Convective Parameterization with Zhang-McFarlane Scheme on Precipitation Simulation in the DOE E3SMv1 Atmosphere Model
The E3SM version 1 single-column model
RadNet 1.0: exploring deep learning architectures for longwave radiative transfer
Efficient ensemble data assimilation for coupled models with the Parallel Data Assimilation Framework: example of AWI-CM (AWI-CM-PDAF 1.0)
Modelling mineral dust emissions and atmospheric dispersion with MADE3 in EMAC v2.54
Evaluation of the University of Victoria Earth System Climate Model version 2.10 (UVic ESCM 2.10)
Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for emergent constraints and future projections from Earth system models in CMIP
Evaluating the land-surface energy partitioning in ERA5
Robust Ecosystem Demography (RED version 1.0): a parsimonious approach to modelling vegetation dynamics in Earth system models
The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)
Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia
Gill M. Martin, Richard C. Levine, José M. Rodriguez, and Michael Vellinga
Geosci. Model Dev., 14, 1007–1035, https://doi.org/10.5194/gmd-14-1007-2021, https://doi.org/10.5194/gmd-14-1007-2021, 2021
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Our study highlights a number of different techniques that can be employed to investigate the sources of model error. We demonstrate how this methodology can be used to identify the regions and model components responsible for the development of long-standing errors in the Asian summer monsoon. Once these are known, further work can be done to explore the local processes contributing to this behaviour and their sensitivity to changes in physical parameterisations and/or model resolution.
Trang Van Pham, Christian Steger, Burkhardt Rockel, Klaus Keuler, Ingo Kirchner, Mariano Mertens, Daniel Rieger, Günther Zängl, and Barbara Früh
Geosci. Model Dev., 14, 985–1005, https://doi.org/10.5194/gmd-14-985-2021, https://doi.org/10.5194/gmd-14-985-2021, 2021
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A new regional climate model was prepared based on a weather forecast model. Slow processes of the climate system such as ocean state development and greenhouse gas emissions were implemented. A model infrastructure and evaluation tools were also prepared to facilitate long-term simulations and model evalution. The first ICON-CLM results were close to observations and comparable to those from COSMO-CLM, the recommended model being used at the Deutscher Wetterdienst and CLM Community.
Michael Steiner, Beiping Luo, Thomas Peter, Michael C. Pitts, and Andrea Stenke
Geosci. Model Dev., 14, 935–959, https://doi.org/10.5194/gmd-14-935-2021, https://doi.org/10.5194/gmd-14-935-2021, 2021
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We evaluate polar stratospheric clouds (PSCs) as simulated by the chemistry–climate model (CCM) SOCOLv3.1 in comparison with measurements by the CALIPSO satellite. A cold bias results in an overestimated PSC area and mountain-wave ice is underestimated, but we find overall good temporal and spatial agreement of PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes may also achieve good approximations of the fundamental properties of PSCs.
Zhaoyuan Yu, Dongshuang Li, Zhengfang Zhang, Wen Luo, Yuan Liu, Zengjie Wang, and Linwang Yuan
Geosci. Model Dev., 14, 875–887, https://doi.org/10.5194/gmd-14-875-2021, https://doi.org/10.5194/gmd-14-875-2021, 2021
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Few lossy compression methods consider both the global and local multidimensional coupling correlations, which could lead to information loss in data compression. Here we develop an adaptive lossy compression method, Adaptive-HGFDR, to capture both the global and local variation of multidimensional coupling correlations and improve approximation accuracy. The method can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity.
Franziska Winterstein and Patrick Jöckel
Geosci. Model Dev., 14, 661–674, https://doi.org/10.5194/gmd-14-661-2021, https://doi.org/10.5194/gmd-14-661-2021, 2021
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Atmospheric methane is currently a hot topic in climate research. This is partly due to its chemically active nature. We introduce a simplified approach to simulate methane in climate models to enable large sensitivity studies by reducing computational cost but including the crucial feedback of methane on stratospheric water vapour. We further provide options to simulate the isotopic content of methane and to generate output for an inverse optimization technique for emission estimation.
Ruth Petrie, Sébastien Denvil, Sasha Ames, Guillaume Levavasseur, Sandro Fiore, Chris Allen, Fabrizio Antonio, Katharina Berger, Pierre-Antoine Bretonnière, Luca Cinquini, Eli Dart, Prashanth Dwarakanath, Kelsey Druken, Ben Evans, Laurent Franchistéguy, Sébastien Gardoll, Eric Gerbier, Mark Greenslade, David Hassell, Alan Iwi, Martin Juckes, Stephan Kindermann, Lukasz Lacinski, Maria Mirto, Atef Ben Nasser, Paola Nassisi, Eric Nienhouse, Sergey Nikonov, Alessandra Nuzzo, Clare Richards, Syazwan Ridzwan, Michel Rixen, Kim Serradell, Kate Snow, Ag Stephens, Martina Stockhause, Hans Vahlenkamp, and Rick Wagner
Geosci. Model Dev., 14, 629–644, https://doi.org/10.5194/gmd-14-629-2021, https://doi.org/10.5194/gmd-14-629-2021, 2021
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This paper describes the infrastructure that is used to distribute Coupled Model Intercomparison Project Phase 6 (CMIP6) data around the world for analysis by the climate research community. It is expected that there will be ~20 PB (petabytes) of data available for analysis. The operations team performed a series of preparation "data challenges" to ensure all components of the infrastructure were operational for when the data became available for timely data distribution and subsequent analysis.
Camilla Mathison, Andrew J. Challinor, Chetan Deva, Pete Falloon, Sébastien Garrigues, Sophie Moulin, Karina Williams, and Andy Wiltshire
Geosci. Model Dev., 14, 437–471, https://doi.org/10.5194/gmd-14-437-2021, https://doi.org/10.5194/gmd-14-437-2021, 2021
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Sequential cropping (also known as multiple or double cropping) is a common cropping system, particularly in tropical regions. Typically, land surface models only simulate a single crop per year. To understand how sequential crops influence surface fluxes, we implement sequential cropping in JULES to simulate all the crops grown within a year at a given location in a seamless way. We demonstrate the method using a site in Avignon, four locations in India and a regional run for two Indian states.
Chao Wang, Xingqin An, Qing Hou, Zhaobin Sun, Yanjun Li, and Jiangtao Li
Geosci. Model Dev., 14, 337–350, https://doi.org/10.5194/gmd-14-337-2021, https://doi.org/10.5194/gmd-14-337-2021, 2021
Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 365–375, https://doi.org/10.5194/gmd-14-365-2021, https://doi.org/10.5194/gmd-14-365-2021, 2021
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Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
David N. Bresch and Gabriela Aznar-Siguan
Geosci. Model Dev., 14, 351–363, https://doi.org/10.5194/gmd-14-351-2021, https://doi.org/10.5194/gmd-14-351-2021, 2021
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Climate change is a fact and adaptation a necessity. The Economics of Climate Adaptation methodology provides a framework to integrate risk and reward perspectives of different stakeholders, underpinned by the CLIMADA impact modelling platform. This extended version of CLIMADA enables risk assessment and options appraisal in a modular form and occasionally bespoke fashion yet with high reusability of functionalities to foster usage in interdisciplinary studies and international collaboration.
Adam T. Blaker, Manoj Joshi, Bablu Sinha, David P. Stevens, Robin S. Smith, and Joël J.-M. Hirschi
Geosci. Model Dev., 14, 275–293, https://doi.org/10.5194/gmd-14-275-2021, https://doi.org/10.5194/gmd-14-275-2021, 2021
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FORTE 2.0 is a flexible coupled atmosphere–ocean general circulation model that can be run on modest hardware. We present two 2000-year simulations which show that FORTE 2.0 is capable of producing a stable climate. Earlier versions of FORTE were used for a wide range of studies, ranging from aquaplanet configurations to investigating the cold European winters of 2009–2010. This paper introduces the updated model for which the code and configuration are now publicly available.
Ah-Hyun Kim, Seong Soo Yum, Dong Yeong Chang, and Minsu Park
Geosci. Model Dev., 14, 259–273, https://doi.org/10.5194/gmd-14-259-2021, https://doi.org/10.5194/gmd-14-259-2021, 2021
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A new method to estimate the sulfate aerosol hygroscopicity parameter (κSO4) is suggested that can consider κSO4 for two different sulfate species instead of prescribing a single κSO4 value, as in most previous studies. The new method simulates more realistic cloud droplet concentrations and, thus, a more realistic cloud albedo effect than the original method. The new method is simple and readily applicable to modeling studies investigating sulfate aerosols’ effect in aerosol–cloud interactions.
Brigitta Szabó, Melanie Weynants, and Tobias K. D. Weber
Geosci. Model Dev., 14, 151–175, https://doi.org/10.5194/gmd-14-151-2021, https://doi.org/10.5194/gmd-14-151-2021, 2021
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This paper presents updated European prediction algorithms (euptf2) to compute soil hydraulic parameters from easily available soil properties. The new algorithms lead to significantly better predictions and provide a built-in prediction uncertainty computation. The influence of predictor variables on predicted soil hydraulic properties is explored and practical guidance on how to use the derived PTFs is provided. A website and an R package facilitate easy application of the updated predictions.
Zhanshan Ma, Chuanfeng Zhao, Jiandong Gong, Jin Zhang, Zhe Li, Jian Sun, Yongzhu Liu, Jiong Chen, and Qingu Jiang
Geosci. Model Dev., 14, 205–221, https://doi.org/10.5194/gmd-14-205-2021, https://doi.org/10.5194/gmd-14-205-2021, 2021
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The spin-up in GRAPES_GFS, under different initial fields, goes through a dramatic adjustment in the first half-hour of integration and slow dynamic and thermal adjustments afterwards. It lasts for at least 6 h, with model adjustment gradually completed from lower to upper layers in the model. Thus, the forecast results, at least in the first 6 h, should be avoided when used. In addition, the spin-up process should repeat when the model simulation is interrupted.
Chein-Jung Shiu, Yi-Chi Wang, Huang-Hsiung Hsu, Wei-Ting Chen, Hua-Lu Pan, Ruiyu Sun, Yi-Hsuan Chen, and Cheng-An Chen
Geosci. Model Dev., 14, 177–204, https://doi.org/10.5194/gmd-14-177-2021, https://doi.org/10.5194/gmd-14-177-2021, 2021
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A cloud macrophysics scheme utilizing grid-mean hydrometeor information is developed and evaluated for climate models. The GFS–TaiESM–Sundqvist (GTS) scheme can simulate variations of cloud fraction associated with relative humidity (RH) in a more consistent way than the default scheme of CAM5.3. Through better cloud–RH distributions, the GTS scheme helps to better represent cloud fraction, cloud radiative forcing, and thermodynamic-related climatic fields in climate simulations.
Katherine A. Crichton, Jamie D. Wilson, Andy Ridgwell, and Paul N. Pearson
Geosci. Model Dev., 14, 125–149, https://doi.org/10.5194/gmd-14-125-2021, https://doi.org/10.5194/gmd-14-125-2021, 2021
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Temperature is a controller of metabolic processes and therefore also a controller of the ocean's biological carbon pump (BCP). We calibrate a temperature-dependent version of the BCP in the cGENIE Earth system model. Since the pre-industrial period, warming has intensified near-surface nutrient recycling, supporting production and largely offsetting stratification-induced surface nutrient limitation. But at the same time less carbon that sinks out of the surface then reaches the deep ocean.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Hao Yu, Li Liu, Chao Sun, Ruizhe Li, Xinzhu Yu, Cheng Zhang, Zhiyuan Zhang, and Bin Wang
Geosci. Model Dev., 13, 6253–6263, https://doi.org/10.5194/gmd-13-6253-2020, https://doi.org/10.5194/gmd-13-6253-2020, 2020
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Routing network generation is a major step for initializing the data transfer functionality for model coupling. The distributed implementation for routing network generation (DiRong1.0) proposed in this paper can significantly improve the global implementation of routing network generation used in some existing coupling software, because it does not introduce any gather–broadcast communications and achieves much lower complexity in terms of time, memory, and communication.
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.
Wieke Heldens, Cornelia Burmeister, Farah Kanani-Sühring, Björn Maronga, Dirk Pavlik, Matthias Sühring, Julian Zeidler, and Thomas Esch
Geosci. Model Dev., 13, 5833–5873, https://doi.org/10.5194/gmd-13-5833-2020, https://doi.org/10.5194/gmd-13-5833-2020, 2020
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For realistic microclimate simulations in urban areas with PALM 6.0, detailed description of surface types, buildings and vegetation is required. This paper shows how such input data sets can be derived with the example of three German cities. Various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. The collection and preparation of input data sets is tedious. Future research aims therefore at semi-automated tools to support users.
Emmanuele Russo, Silje Lund Sørland, Ingo Kirchner, Martijn Schaap, Christoph C. Raible, and Ulrich Cubasch
Geosci. Model Dev., 13, 5779–5797, https://doi.org/10.5194/gmd-13-5779-2020, https://doi.org/10.5194/gmd-13-5779-2020, 2020
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The parameter space of the COSMO-CLM RCM is investigated for the Central Asia CORDEX domain using a perturbed physics ensemble (PPE) with different parameter values. Results show that only a subset of model parameters presents relevant changes in model performance and these changes depend on the considered region and variable: objective calibration methods are highly necessary in this case. Additionally, the results suggest the need for calibrating an RCM when targeting different domains.
Carley E. Iles, Robert Vautard, Jane Strachan, Sylvie Joussaume, Bernd R. Eggen, and Chris D. Hewitt
Geosci. Model Dev., 13, 5583–5607, https://doi.org/10.5194/gmd-13-5583-2020, https://doi.org/10.5194/gmd-13-5583-2020, 2020
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We investigate how increased resolution affects the simulation of European climate extremes for global and regional climate models to inform modelling strategies. Precipitation extremes become heavier with higher resolution, especially over mountains, wind extremes become somewhat stronger, and for temperature extremes warm biases are reduced over mountains. Differences with resolution for the global model appear to come from downscaling effects rather than improved large-scale circulation.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
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Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
George C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed O. Kaplan, Jennifer Kennedy, Tamás Krisztin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. van Vuuren, and Xin Zhang
Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, https://doi.org/10.5194/gmd-13-5425-2020, 2020
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To estimate the effects of human land use activities on the carbon–climate system, a new set of global gridded land use forcing datasets was developed to link historical land use data to eight future scenarios in a standard format required by climate models. This new generation of land use harmonization (LUH2) includes updated inputs, higher spatial resolution, more detailed land use transitions, and the addition of important agricultural management layers; it will be used for CMIP6 simulations.
Philip Goodwin, Martin Leduc, Antti-Ilari Partanen, H. Damon Matthews, and Alex Rogers
Geosci. Model Dev., 13, 5389–5399, https://doi.org/10.5194/gmd-13-5389-2020, https://doi.org/10.5194/gmd-13-5389-2020, 2020
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Numerical climate models are used to make projections of future surface warming for different pathways of future greenhouse gas emissions, where future surface warming will vary from place to place. However, it is so expensive to run complex models using supercomputers that future projections can only be produced for a small number of possible future emissions pathways. This study presents an efficient climate model to make projections of local surface warming using a desktop computer.
Mathieu Vrac and Soulivanh Thao
Geosci. Model Dev., 13, 5367–5387, https://doi.org/10.5194/gmd-13-5367-2020, https://doi.org/10.5194/gmd-13-5367-2020, 2020
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We propose a multivariate bias correction (MBC) method to adjust the spatial and/or inter-variable properties of climate simulations, while also accounting for their temporal dependences (e.g., autocorrelations).
It consists on a method reordering the ranks of the time series according to their multivariate distance to a reference time series.
Results show that temporal correlations are improved while spatial and inter-variable correlations are still satisfactorily corrected.
Hella Garny, Roland Walz, Matthias Nützel, and Thomas Birner
Geosci. Model Dev., 13, 5229–5257, https://doi.org/10.5194/gmd-13-5229-2020, https://doi.org/10.5194/gmd-13-5229-2020, 2020
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Numerical models of Earth's climate system have been gaining more and more complexity over the last decades. Therefore, it is important to establish simplified models to improve process understanding. In our study, we present and document the development of a new simplified model setup within the framework of a complex climate model system that uses the same routines to calculate atmospheric dynamics as the complex model but is simplified in the representation of clouds and radiation.
Yingxia Gao, Nicholas P. Klingaman, Charlotte A. DeMott, and Pang-Chi Hsu
Geosci. Model Dev., 13, 5191–5209, https://doi.org/10.5194/gmd-13-5191-2020, https://doi.org/10.5194/gmd-13-5191-2020, 2020
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Both the air–sea coupling and ocean mean state affect the fidelity of simulated boreal summer intraseasonal oscillation (BSISO). To elucidate their relative effects on the simulated BSISO, a set of experiments was conducted using a superparameterized AGCM and its coupled version. Both air–sea coupling and cold ocean mean state improve the BSISO amplitude due to the suppression of the overestimated variance, while the former (latter) could further upgrade (degrade) the BSISO propagation.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
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Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Jaeyoung Song, Gretchen R. Miller, Anthony T. Cahill, Luiza Maria T. Aparecido, and Georgianne W. Moore
Geosci. Model Dev., 13, 5147–5173, https://doi.org/10.5194/gmd-13-5147-2020, https://doi.org/10.5194/gmd-13-5147-2020, 2020
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The performance of a land surface model (CLM4.5 and 5.0) was examined against a suite of measurements from a tropical montane rainforest in Costa Rica. Both versions failed to capture the effects of frequent rainfall events and mountainous terrain on temperature, leaf wetness, photosynthesis, and transpiration. While the new model version eliminated some errors, it still cannot precisely simulate a number of processes. This suggests that two key components of the model need modification.
Patricio Velasquez, Martina Messmer, and Christoph C. Raible
Geosci. Model Dev., 13, 5007–5027, https://doi.org/10.5194/gmd-13-5007-2020, https://doi.org/10.5194/gmd-13-5007-2020, 2020
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This work presents a new bias-correction method for precipitation that considers orographic characteristics, which can be used in studies where the latter strongly changes. The three-step correction method consists of a separation into orographic features, correction of low-intensity precipitation, and application of empirical quantile mapping. Seasonal bias induced by the global climate model is fully corrected. Rigorous cross-validations illustrate the method's applicability and robustness.
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-317, https://doi.org/10.5194/gmd-2020-317, 2020
Revised manuscript accepted for GMD
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The presented process based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Eric Larour, Lambert Caron, Mathieu Morlighem, Surendra Adhikari, Thomas Frederikse, Nicole-Jeanne Schlegel, Erik Ivins, Benjamin Hamlington, Robert Kopp, and Sophie Nowicki
Geosci. Model Dev., 13, 4925–4941, https://doi.org/10.5194/gmd-13-4925-2020, https://doi.org/10.5194/gmd-13-4925-2020, 2020
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ISSM-SLPS is a new projection system for future sea level that increases the resolution and accuracy of current projection systems and improves the way uncertainty is treated in such projections. This will pave the way for better inclusion of state-of-the-art results from existing intercomparison efforts carried out by the scientific community, such as GlacierMIP2 or ISMIP6, into sea-level projections.
Hiroshi Yamashita, Feijia Yin, Volker Grewe, Patrick Jöckel, Sigrun Matthes, Bastian Kern, Katrin Dahlmann, and Christine Frömming
Geosci. Model Dev., 13, 4869–4890, https://doi.org/10.5194/gmd-13-4869-2020, https://doi.org/10.5194/gmd-13-4869-2020, 2020
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This paper describes the updated submodel AirTraf 2.0 which simulates global air traffic in the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. Nine aircraft routing options have been integrated, including contrail avoidance, minimum economic costs, and minimum climate impact. Example simulations reveal characteristics of different routing options on air traffic performances. The consistency of the AirTraf simulations is verified with literature data.
Landon A. Rieger, Jason N. S. Cole, John C. Fyfe, Stephen Po-Chedley, Philip J. Cameron-Smith, Paul J. Durack, Nathan P. Gillett, and Qi Tang
Geosci. Model Dev., 13, 4831–4843, https://doi.org/10.5194/gmd-13-4831-2020, https://doi.org/10.5194/gmd-13-4831-2020, 2020
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Recently, the stratospheric aerosol forcing dataset used as an input to the Coupled Model Intercomparison Project phase 6 was updated. This work explores the impact of those changes on the modelled historical climates in the CanESM5 and EAMv1 models. Temperature differences in the stratosphere shortly after the Pinatubo eruption are found to be significant, but surface temperatures and precipitation do not show a significant change.
Shaoqing Zhang, Haohuan Fu, Lixin Wu, Yuxuan Li, Hong Wang, Yunhui Zeng, Xiaohui Duan, Wubing Wan, Li Wang, Yuan Zhuang, Hongsong Meng, Kai Xu, Ping Xu, Lin Gan, Zhao Liu, Sihai Wu, Yuhu Chen, Haining Yu, Shupeng Shi, Lanning Wang, Shiming Xu, Wei Xue, Weiguo Liu, Qiang Guo, Jie Zhang, Guanghui Zhu, Yang Tu, Jim Edwards, Allison Baker, Jianlin Yong, Man Yuan, Yangyang Yu, Qiuying Zhang, Zedong Liu, Mingkui Li, Dongning Jia, Guangwen Yang, Zhiqiang Wei, Jingshan Pan, Ping Chang, Gokhan Danabasoglu, Stephen Yeager, Nan Rosenbloom, and Ying Guo
Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, https://doi.org/10.5194/gmd-13-4809-2020, 2020
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Science advancement and societal needs require Earth system modelling with higher resolutions that demand tremendous computing power. We successfully scale the 10 km ocean and 25 km atmosphere high-resolution Earth system model to a new leading-edge heterogeneous supercomputer using state-of-the-art optimizing methods, promising the solution of high spatial resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modelling and HPC design communities.
Tokuta Yokohata, Tsuguki Kinoshita, Gen Sakurai, Yadu Pokhrel, Akihiko Ito, Masashi Okada, Yusuke Satoh, Etsushi Kato, Tomoko Nitta, Shinichiro Fujimori, Farshid Felfelani, Yoshimitsu Masaki, Toshichika Iizumi, Motoki Nishimori, Naota Hanasaki, Kiyoshi Takahashi, Yoshiki Yamagata, and Seita Emori
Geosci. Model Dev., 13, 4713–4747, https://doi.org/10.5194/gmd-13-4713-2020, https://doi.org/10.5194/gmd-13-4713-2020, 2020
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The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balances, human water management, and crop growth incorporates a land-use decision-making model based on economic activities. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand.
Chia-Te Chien, Markus Pahlow, Markus Schartau, and Andreas Oschlies
Geosci. Model Dev., 13, 4691–4712, https://doi.org/10.5194/gmd-13-4691-2020, https://doi.org/10.5194/gmd-13-4691-2020, 2020
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We demonstrate sensitivities of tracers to parameters of a new optimality-based plankton–ecosystem model (OPEM) in the UVic-ESCM. We find that changes in phytoplankton subsistence nitrogen quota strongly impact the nitrogen inventory, nitrogen fixation, and elemental stoichiometry of ordinary phytoplankton and diazotrophs. We introduce a new likelihood-based metric for model calibration, and it shows the capability of constraining globally averaged oxygen, nitrate, and DIC concentrations.
Markus Pahlow, Chia-Te Chien, Lionel A. Arteaga, and Andreas Oschlies
Geosci. Model Dev., 13, 4663–4690, https://doi.org/10.5194/gmd-13-4663-2020, https://doi.org/10.5194/gmd-13-4663-2020, 2020
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The stoichiometry of marine biotic processes is important for the regulation of atmospheric CO2 and hence the global climate. We replace a simplistic, fixed-stoichiometry plankton module in an Earth system model with an optimal-regulation model with variable stoichiometry. Our model compares better to the observed carbon transfer from the surface to depth and surface nutrient distributions. This work could aid our ability to describe and project the role of marine ecosystems in the Earth system.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-249, https://doi.org/10.5194/gmd-2020-249, 2020
Revised manuscript accepted for GMD
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A stochastic deep convection parameterization is implemented into the U.S. Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in deep convective parameterization.
Peter A. Bogenschutz, Shuaiqi Tang, Peter M. Caldwell, Shaocheng Xie, Wuyin Lin, and Yao-Sheng Chen
Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, https://doi.org/10.5194/gmd-13-4443-2020, 2020
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This paper documents a tool that has been developed that can be used to accelerate the development and understanding of climate models. This version of the model, known as a the single-column model, is much faster to run than the full climate model, and we demonstrate that this tool can be used to quickly exploit model biases that arise due to physical processes. We show examples of how this single-column model can directly benefit the field.
Ying Liu, Rodrigo Caballero, and Joy Merwin Monteiro
Geosci. Model Dev., 13, 4399–4412, https://doi.org/10.5194/gmd-13-4399-2020, https://doi.org/10.5194/gmd-13-4399-2020, 2020
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The calculation of atmospheric radiative transfer is the most computationally expensive part of climate models. Reducing this computational burden could potentially improve our ability to simulate the earth's climate at finer scales. We propose using a statistical model – a deep neural network – to compute approximate radiative transfer in the earth's atmosphere. We demonstrate a significant reduction in computational burden as compared to a traditional scheme, especially when using GPUs.
Lars Nerger, Qi Tang, and Longjiang Mu
Geosci. Model Dev., 13, 4305–4321, https://doi.org/10.5194/gmd-13-4305-2020, https://doi.org/10.5194/gmd-13-4305-2020, 2020
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Data assimilation combines observations with numerical models to get an improved estimate of the model state. This work discusses the technical aspects of how a coupled model that simulates the ocean and the atmosphere can be augmented by data assimilation functionality provided in generic form by the open-source software PDAF (Parallel Data Assimilation Framework). A very efficient program is obtained that can be executed on high-performance computers.
Christof G. Beer, Johannes Hendricks, Mattia Righi, Bernd Heinold, Ina Tegen, Silke Groß, Daniel Sauer, Adrian Walser, and Bernadett Weinzierl
Geosci. Model Dev., 13, 4287–4303, https://doi.org/10.5194/gmd-13-4287-2020, https://doi.org/10.5194/gmd-13-4287-2020, 2020
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Mineral dust aerosol plays an important role in the climate system. Previously, dust emissions have often been represented in global models by prescribed monthly-mean emission fields representative of a specific year. We now apply an online calculation of wind-driven dust emissions. This results in an improved agreement with observations, due to a better representation of the highly variable dust emissions. Increasing the model resolution led to an additional performance gain.
Nadine Mengis, David P. Keller, Andrew H. MacDougall, Michael Eby, Nesha Wright, Katrin J. Meissner, Andreas Oschlies, Andreas Schmittner, Alexander J. MacIsaac, H. Damon Matthews, and Kirsten Zickfeld
Geosci. Model Dev., 13, 4183–4204, https://doi.org/10.5194/gmd-13-4183-2020, https://doi.org/10.5194/gmd-13-4183-2020, 2020
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In this paper, we evaluate the newest version of the University of Victoria Earth System Climate Model (UVic ESCM 2.10). Combining recent model developments as a joint effort, this version is to be used in the next phase of model intercomparison and climate change studies. The UVic ESCM 2.10 is capable of reproducing changes in historical temperature and carbon fluxes well. Additionally, the model is able to reproduce the three-dimensional distribution of many ocean tracers.
Axel Lauer, Veronika Eyring, Omar Bellprat, Lisa Bock, Bettina K. Gier, Alasdair Hunter, Ruth Lorenz, Núria Pérez-Zanón, Mattia Righi, Manuel Schlund, Daniel Senftleben, Katja Weigel, and Sabrina Zechlau
Geosci. Model Dev., 13, 4205–4228, https://doi.org/10.5194/gmd-13-4205-2020, https://doi.org/10.5194/gmd-13-4205-2020, 2020
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The Earth System Model Evaluation Tool is a community software tool designed for evaluation and analysis of climate models. New features of version 2.0 include analysis scripts for important large-scale features in climate models, diagnostics for extreme events, regional model and impact evaluation. In this paper, newly implemented climate metrics, emergent constraints for climate-relevant feedbacks and diagnostics for future model projections are described and illustrated with examples.
Brecht Martens, Dominik L. Schumacher, Hendrik Wouters, Joaquín Muñoz-Sabater, Niko E. C. Verhoest, and Diego G. Miralles
Geosci. Model Dev., 13, 4159–4181, https://doi.org/10.5194/gmd-13-4159-2020, https://doi.org/10.5194/gmd-13-4159-2020, 2020
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Climate reanalyses are widely used in different fields and an in-depth evaluation of the different variables provided by reanalyses is a necessary means to provide feedback on the quality to their users and the operational centres producing these data sets. In this study, we show the improvements of ECMWF's latest climate reanalysis (ERA5) upon its predecessor (ERA-Interim) in partitioning the available energy at the land surface.
Arthur P. K. Argles, Jonathan R. Moore, Chris Huntingford, Andrew J. Wiltshire, Anna B. Harper, Chris D. Jones, and Peter M. Cox
Geosci. Model Dev., 13, 4067–4089, https://doi.org/10.5194/gmd-13-4067-2020, https://doi.org/10.5194/gmd-13-4067-2020, 2020
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The Robust Ecosystem Demography (RED) model simulates cohorts of vegetation through mass classes. RED establishes a framework for representing demographic changes through competition, growth, and mortality across the size distribution of a forest. The steady state of the model can be solved analytically, enabling initialization. When driven by mean growth rates from a land-surface model, RED is able to fit the observed global vegetation map, giving a map of implicit mortality rates.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Abigail Snyder, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Karina Williams, Ziwei Wang, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 3995–4018, https://doi.org/10.5194/gmd-13-3995-2020, https://doi.org/10.5194/gmd-13-3995-2020, 2020
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Improving our understanding of the impacts of climate change on crop yields will be critical for global food security in the next century. The models often used to study the how climate change may impact agriculture are complex and costly to run. In this work, we describe a set of global crop model emulators (simplified models) developed under the Agricultural Model Intercomparison Project. Crop model emulators make agricultural simulations more accessible to policy or decision makers.
Miguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F. Trigo, Sofia L. Ermida, João P. A. Martins, and Emanuel Dutra
Geosci. Model Dev., 13, 3975–3993, https://doi.org/10.5194/gmd-13-3975-2020, https://doi.org/10.5194/gmd-13-3975-2020, 2020
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We used earth observations to evaluate and improve the representation of land surface temperature (LST) and vegetation coverage over Iberia in CHTESSEL and SURFEX land surface models. We demonstrate the added value of updating the vegetation types and fractions together with the representation of vegetation coverage seasonality. Results show a large reduction in daily maximum LST systematic error during warm months, with neutral impacts in other seasons.
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Short summary
We evaluated the skill of the road weather model RoadSurf to reproduce present-day road weather conditions in Finland when driven by a high-resolution regional climate model. Simulated road surface temperatures and conditions were compared to observations between 2002 and 2014 at 25 Finnish road weather stations. RoadSurf accurately captured the main characteristics of road weather conditions. Thus, this model can be used to study the future scenarios of road weather in the study area.
We evaluated the skill of the road weather model RoadSurf to reproduce present-day road weather...
