Model evaluation paper 19 Jun 2018
Model evaluation paper | 19 Jun 2018
The seasonal relationship between intraseasonal tropical variability and ENSO in CMIP5
Tatiana Matveeva et al.
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Marine Bretagnon, Aurélien Paulmier, Véronique Garçon, Boris Dewitte, Séréna Illig, Nathalie Leblond, Laurent Coppola, Fernando Campos, Federico Velazco, Christos Panagiotopoulos, Andreas Oschlies, J. Martin Hernandez-Ayon, Helmut Maske, Oscar Vergara, Ivonne Montes, Philippe Martinez, Edgardo Carrasco, Jacques Grelet, Olivier Desprez-De-Gesincourt, Christophe Maes, and Lionel Scouarnec
Biogeosciences, 15, 5093–5111, https://doi.org/10.5194/bg-15-5093-2018, https://doi.org/10.5194/bg-15-5093-2018, 2018
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In oxygen minimum zone, the fate of the organic matter is a key question as the low oxygen condition would preserve the OM and thus enhance the biological carbon pump while the high microbial activity would foster the remineralisation and the greenhouse gases emission. To investigate this paradigm, sediment traps were deployed off Peru. We pointed out the influence of the oxygenation as well as the organic matter quantity and quality on the carbon transfer efficiency in the oxygen minimum zone.
Michelle I. Graco, Sara Purca, Boris Dewitte, Carmen G. Castro, Octavio Morón, Jesús Ledesma, Georgina Flores, and Dimitri Gutiérrez
Biogeosciences, 14, 4601–4617, https://doi.org/10.5194/bg-14-4601-2017, https://doi.org/10.5194/bg-14-4601-2017, 2017
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The Peruvian coastal upwelling ecosystem is a natural laboratory to study climatic variability and climate change. We examined the variability in the OMZ in the last decades in connection with the equatorial Pacific strong 1997–1998 El Niño event and the influence of central Pacific El Niño events and enhanced equatorial Kelvin wave activity since 2000. The data reveal two contrasting regimes and a long-term trend corresponding to a deepening of the oxygen-deficient waters and warming.
Luis Bravo, Marcel Ramos, Orlando Astudillo, Boris Dewitte, and Katerina Goubanova
Ocean Sci., 12, 1049–1065, https://doi.org/10.5194/os-12-1049-2016, https://doi.org/10.5194/os-12-1049-2016, 2016
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We evaluated the seasonal variability in Ekman transport, pumping and their relative contribution to total upwelling along the central-northern Chile region (~30ºS) from a high-resolution atmospheric model simulation. The results showed that the relative contribution of Ekman transport and pumping to the vertical transport along the coast, considering the estimated wind drop-off length, indicated meridional alternation between both mechanisms, modulated by orography and the intricate coastline.
Oscar Vergara, Boris Dewitte, Ivonne Montes, Veronique Garçon, Marcel Ramos, Aurélien Paulmier, and Oscar Pizarro
Biogeosciences, 13, 4389–4410, https://doi.org/10.5194/bg-13-4389-2016, https://doi.org/10.5194/bg-13-4389-2016, 2016
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The Southeast Pacific hosts one of the most extensive oxygen minimum zone (OMZ), yet the dynamics behind it remain unveiled. We use a high-resolution coupled physical–biogeochemical model to document the seasonal cycle of dissolved oxygen within the OMZ in both the coastal zone and the offshore ocean. The OMZ seasonal variability is driven by the seasonal fluctuations of the dissolved oxygen eddy flux, with a peak in Austral winter (fall) at the northern (southern) boundary and near the coast.
A. Olchev, A. Ibrom, O. Panferov, D. Gushchina, H. Kreilein, V. Popov, P. Propastin, T. June, A. Rauf, G. Gravenhorst, and A. Knohl
Biogeosciences, 12, 6655–6667, https://doi.org/10.5194/bg-12-6655-2015, https://doi.org/10.5194/bg-12-6655-2015, 2015
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The time series analysis of the main meteorological parameters and components of CO2 and H2O fluxes showed a high evapotranspiration (ET) and gross primary production (GPP) sensitivity of the tropical rainforest to meteorological variations caused by El Niño-Southern Oscillation (ENSO) events. Incoming solar radiation is the main governing factor that is responsible for ET and GPP variability. Changes in precipitation due to moderate ENSO events did not have any notable effect on ET and GPP.
I. Hernández-Carrasco, J. Sudre, V. Garçon, H. Yahia, C. Garbe, A. Paulmier, B. Dewitte, S. Illig, I. Dadou, M. González-Dávila, and J. M. Santana-Casiano
Biogeosciences, 12, 5229–5245, https://doi.org/10.5194/bg-12-5229-2015, https://doi.org/10.5194/bg-12-5229-2015, 2015
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We have reconstructed maps of air-sea CO2 fluxes at high resolution (4 km) in the offshore Benguela region using sea surface temperature and ocean colour data and CarbonTracker CO2 fluxes data at low resolution (110 km).
The inferred representation of pCO2 improves the description provided by CarbonTracker, enhancing small-scale variability.
We find that the resolution, as well as the inferred pCO2 data itself, is closer to in situ measurements of pCO2.
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Sonia Jerez, Laura Palacios-Peña, Claudia Gutiérrez, Pedro Jiménez-Guerrero, Jose María López-Romero, Enrique Pravia-Sarabia, and Juan Pedro Montávez
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Yaqiong Lu and Xianyu Yang
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Crop growth in land surface models normally requires high-temporal-resolution climate data, but such high-temporal-resolution climate data are not provided by many climate model simulations due to expensive storage, which limits modeling choices if there is an interest in a particular climate simulation that only saved monthly outputs. Our work provides an alternative way to use the monthly climate for crop yield projections. Such an approach could be easily adopted by other crop models.
Rumi Ohgaito, Akitomo Yamamoto, Tomohiro Hajima, Ryouta O'ishi, Manabu Abe, Hiroaki Tatebe, Ayako Abe-Ouchi, and Michio Kawamiya
Geosci. Model Dev., 14, 1195–1217, https://doi.org/10.5194/gmd-14-1195-2021, https://doi.org/10.5194/gmd-14-1195-2021, 2021
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Using the MIROC-ES2L Earth system model, selected time periods of the past were simulated. The ability to simulate the past is also an evaluation of the performance of the model in projecting global warming. Simulations for 21 000, 6000, and 127 000 years ago, and a simulation for 1000 years starting in 850 CE were simulated. The results showed that the model can generally describe past climate change.
Qiong Zhang, Ellen Berntell, Josefine Axelsson, Jie Chen, Zixuan Han, Wesley de Nooijer, Zhengyao Lu, Qiang Li, Qiang Zhang, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 1147–1169, https://doi.org/10.5194/gmd-14-1147-2021, https://doi.org/10.5194/gmd-14-1147-2021, 2021
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Paleoclimate modelling has long been regarded as a strong out-of-sample test bed of the climate models that are used for the projection of future climate changes. Here, we document the model experimental setups for the three past warm periods with EC-Earth3-LR and present the results on the large-scale features. The simulations demonstrate good performance of the model in capturing the climate response under different climate forcings.
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.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-393, https://doi.org/10.5194/gmd-2020-393, 2020
Revised manuscript accepted for GMD
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth System Models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling representation of the more detailed physics and chemistry at reduced computational cost while still retaining physical information.
Qun Liu, Matthew Collins, Penelope Maher, Stephen I. Thomson, and Geoffrey K. Vallis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-402, https://doi.org/10.5194/gmd-2020-402, 2020
Revised manuscript accepted for GMD
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Clouds play an vital role in Earth's energy budget and even a small change in cloud fields can have a large impact on climate system. They also bring lots of uncertainties to climate models. Here we implement a simple diagnostic cloud scheme in order to reproduce the general radiative properties of clouds. The scheme can capture some key features of the cloud fraction and cloud radiative properties, thus providing a useful tool to explore the unsolved problems about clouds.
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.
Pengfei Wang, Jinrong Jiang, Pengfei Lin, Mengrong Ding, Junlin Wei, Feng Zhang, Lian Zhao, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yongqiang Yu, Xuebin Chi, and Hailong Liu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-323, https://doi.org/10.5194/gmd-2020-323, 2020
Revised manuscript accepted for GMD
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The global ocean general circulation models are a fundamental tool for oceanography research, ocean forecast, and climate change research. The increasing resolution will greatly improve the simulation of the model, but it also demands much more computing resources. In this study, we have ported an ocean general circulation model to a heterogeneous computing system and have developed a 3–5 km model version. A 14-year integration has been conducted and the preliminary results have been evaluated.
Steven R. Brus, Phillip J. Wolfram, Luke P. Van Roekel, and Jessica D. Meixner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-351, https://doi.org/10.5194/gmd-2020-351, 2020
Revised manuscript accepted for GMD
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Wind generated waves are an important process in the global climate system. They mediate many interactions between the ocean, atmosphere, and sea ice. Models which describe these waves are computationally expensive and have often been excluded from coupled Earth system models. To address this, we have developed a capability for the WAVEWATCHIII model which allows model resolution to be varied globally across the coastal the open ocean. This allows for improved accuracy at reduced computing time.
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.
Meng-Zhuo Zhang, Zhongfeng Xu, Ying Han, and Weidong Guo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-310, https://doi.org/10.5194/gmd-2020-310, 2020
Revised manuscript accepted for GMD
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Overall model performance evaluation in simulating multiple fields is crucial for geoscientific model development, inter-comparison, and application with increasing models available recently. We make key improvements for the Multivariable Integrated Evaluation (MVIE) method and develop a simple-to-use and straightforward tool, Multivariable Integrated Evaluation Tool (MVIETool) based on the improved MVIE, which will assist researchers to efficiently evaluate multivariable model performance.
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.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-390, https://doi.org/10.5194/gmd-2020-390, 2020
Revised manuscript accepted for GMD
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This paper presents an update of the FaIR simple climate model, used for estimating the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used not only in academic or corporate research, but also in education.
Olivier Marti, Sébastien Nguyen, Pascale Braconnot, Sophie Valcke, Florian Lemarié, and Eric Blayo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-307, https://doi.org/10.5194/gmd-2020-307, 2020
Revised manuscript accepted for GMD
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State-of-the-art Earth System models, like the ones used in the CMIP6 intercomparison project, suffer from temporal inconsistencies at the ocean-atmosphere interface. In this study, a mathematically consistent iterative Schwarz method is used as a reference. It's tremendous computational cost make it unusable for production runs. But it allow us to evaluate the error made when using legacy coupling schemes. The impact on the climate at longer time scale, from days to decades, is not evaluated.
Jun'ya Takakura, Shinichiro Fujimori, Kiyoshi Takahashi, Naota Hanasaki, Tomoko Hasegawa, Yukiko Hirabayashi, Yasushi Honda, Toshichika Iizumi, Chan Park, Makoto Tamura, and Yasuaki Hijioka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-349, https://doi.org/10.5194/gmd-2020-349, 2020
Revised manuscript accepted for GMD
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To simplify calculating economic impacts of climate change, Statistical methods called emulators are developed and evaluated. There are trade-offs between model complexity and emulation performance. Aggregated economic impacts can be approximated by relatively simple emulators, but complex emulators are necessary to accommodate finer-scale economic impacts.
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.
Martina Messmer, Santos J. González-Rojí, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-347, https://doi.org/10.5194/gmd-2020-347, 2020
Revised manuscript accepted for GMD
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Sensitivity experiments with the WRF model are run to find an optimal parameterization setup for precipitation around Mount Kenya at a scale that resolves convection (1 km). Precipitation is compared against many weather stations and gridded observational data sets. Both the temporal correlation of monthly precipitation sums and pattern correlations show that fewer nests lead to a more constrained simulation with higher correlation. The Grell-Freitas cumulus scheme obtains most accurate results.
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.
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Short summary
Predicting El Niño both in current condition and for the next century is a key societal need. Intraseasonal atmosphere variability (ITV) plays an important role in triggering of El Niño; the El Niño/ITV relationship may change in future climate. The purpose of this study is to select the models that are most skilful in simulation of the ITV/El Niño relationship and thus promising for investigation of the El Niño mechanism under global climate change. Five models of CMIP5 project were selected.
Predicting El Niño both in current condition and for the next century is a key societal need....