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Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
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IF5.240
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5.768
5.768
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Abstracted/indexedShort summary
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.
Data assimilation combines observations with numerical models to get an improved estimate of the...
GMD | Articles | Volume 13, issue 9
Geosci. Model Dev., 13, 4305–4321, 2020
https://doi.org/10.5194/gmd-13-4305-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 13, 4305–4321, 2020
https://doi.org/10.5194/gmd-13-4305-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper 16 Sep 2020
Development and technical paper | 16 Sep 2020
Efficient ensemble data assimilation for coupled models with the Parallel Data Assimilation Framework: example of AWI-CM (AWI-CM-PDAF 1.0)
Lars Nerger et al.
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The Cryosphere, 10, 761–774, https://doi.org/10.5194/tc-10-761-2016, https://doi.org/10.5194/tc-10-761-2016, 2016
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We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
Xuewei Li, Qinghua Yang, Lejiang Yu, Paul R. Holland, Chao Min, Longjiang Mu, and Dake Chen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-359, https://doi.org/10.5194/tc-2020-359, 2021
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The Arctic sea ice thickness record minimum is confirmed occurring in autumn 2011. The dynamic and thermodynamic processes leading to the minimum thickness is analyzed based on a daily sea ice thickness reanalysis data covering the melting season. The results demonstrate that the dynamic transport of multiyear ice and the subsequent surface energy budget response is a critical mechanism actively contributing to the evolution of Arctic sea ice thickness in 2011.
Chao Min, Qinghua Yang, Longjiang Mu, Frank Kauker, and Robert Ricker
The Cryosphere, 15, 169–181, https://doi.org/10.5194/tc-15-169-2021, https://doi.org/10.5194/tc-15-169-2021, 2021
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An ensemble of four estimates of the sea-ice volume (SIV) variations in Baffin Bay from 2011 to 2016 is generated from the locally merged satellite observations, three modeled sea ice thickness sources (CMST, NAOSIM, and PIOMAS) and NSIDC ice drift data (V4). Results show that the net increase of the ensemble mean SIV occurs from October to April with the largest SIV increase in December, and the reduction occurs from May to September with the largest SIV decline in July.
Qian Shi, Qinghua Yang, Longjiang Mu, Jinfei Wang, François Massonnet, and Matthew R. Mazloff
The Cryosphere, 15, 31–47, https://doi.org/10.5194/tc-15-31-2021, https://doi.org/10.5194/tc-15-31-2021, 2021
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The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019, https://doi.org/10.5194/tc-13-3209-2019, 2019
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Sea ice volume export through the Fram Strait has been studied using varied methods, however, mostly in winter months. Here we report sea ice volume estimates that extend over summer seasons. A recent developed sea ice thickness dataset, in which CryoSat-2 and SMOS sea ice thickness together with SSMI/SSMIS sea ice concentration are assimilated, is used and evaluated in the paper. Results show our estimate is more reasonable than that calculated by satellite data only.
Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, Lars Nerger, and Thomas Lavergne
The Cryosphere, 10, 761–774, https://doi.org/10.5194/tc-10-761-2016, https://doi.org/10.5194/tc-10-761-2016, 2016
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We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
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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).
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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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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.
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.
Gill M. Martin, Richard C. Levine, José M. Rodriguez, and Michael Vellinga
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-268, https://doi.org/10.5194/gmd-2020-268, 2020
Revised manuscript accepted for GMD
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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 parameterizations and/or model resolution.
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.
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.
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.
Qiong Zhang, Qiang Li, Qiang Zhang, Ellen Berntell, Josefine Axelsson, Jie Chen, Zixuan Han, Wesley de Nooijer, Zhengyao Lu, Klaus Wyser, and Shuting Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-208, https://doi.org/10.5194/gmd-2020-208, 2020
Revised manuscript accepted for GMD
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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 experiments setup for the three past warm periods with EC-Earth3-LR and present the results on the large-scale features from the completed production simulations. The simulations demonstrate the good performance of the model to capture the climate response under different climate forcings.
Wei-Liang Lee, Yi-Chi Wang, Chein-Jung Shiu, I-chun Tsai, Chia-Ying Tu, Yung-Yao Lan, Jen-Ping Chen, Hua-Lu Pan, and Huang-Hsiung Hsu
Geosci. Model Dev., 13, 3887–3904, https://doi.org/10.5194/gmd-13-3887-2020, https://doi.org/10.5194/gmd-13-3887-2020, 2020
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The Taiwan Earth System Model (TaiESM) is a new climate model developed in Taiwan. It includes several new features, and therefore it can better simulate the occurrence of convective rainfall, solar energy received by mountainous surfaces, and more detail chemical processes in aerosols. TaiESM can capture the trend of global warming after 1950 well, and its overall performance in most meteorological quantities is better than the average of global models used in IPCC AR5.
John T. Fasullo
Geosci. Model Dev., 13, 3627–3642, https://doi.org/10.5194/gmd-13-3627-2020, https://doi.org/10.5194/gmd-13-3627-2020, 2020
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The fidelity of climate model simulations included in the WCRP Coupled Model Intercomparison Project Versions 3 through 6 is evaluated using best estimates of fields considered by the community to be critical for climate change projections. The analysis benchmarks patterns of the mean state and variability (seasonal/interannual) both within and across model generations, highlighting progress and quantifying persisting biases across models.
Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet
Geosci. Model Dev., 13, 3607–3625, https://doi.org/10.5194/gmd-13-3607-2020, https://doi.org/10.5194/gmd-13-3607-2020, 2020
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This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.
Malte Meinshausen, Zebedee R. J. Nicholls, Jared Lewis, Matthew J. Gidden, Elisabeth Vogel, Mandy Freund, Urs Beyerle, Claudia Gessner, Alexander Nauels, Nico Bauer, Josep G. Canadell, John S. Daniel, Andrew John, Paul B. Krummel, Gunnar Luderer, Nicolai Meinshausen, Stephen A. Montzka, Peter J. Rayner, Stefan Reimann, Steven J. Smith, Marten van den Berg, Guus J. M. Velders, Martin K. Vollmer, and Ray H. J. Wang
Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, https://doi.org/10.5194/gmd-13-3571-2020, 2020
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This study provides the future greenhouse gas (GHG) concentrations under the new set of so-called SSP scenarios (the successors of the IPCC SRES and previous representative concentration pathway (RCP) scenarios). The projected CO2 concentrations range from 350 ppm for low-emission scenarios by 2150 to more than 2000 ppm under the high-emission scenarios. We also provide concentrations, latitudinal gradients, and seasonality for most of the other 42 considered GHGs.
David N. Bresch and Gabriela Aznar-Siguan
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-151, https://doi.org/10.5194/gmd-2020-151, 2020
Revised manuscript accepted for GMD
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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.
Rein Haarsma, Mario Acosta, Rena Bakhshi, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Susanna Corti, Paolo Davini, Eleftheria Exarchou, Federico Fabiano, Uwe Fladrich, Ramon Fuentes Franco, Javier García-Serrano, Jost von Hardenberg, Torben Koenigk, Xavier Levine, Virna Loana Meccia, Twan van Noije, Gijs van den Oord, Froila M. Palmeiro, Mario Rodrigo, Yohan Ruprich-Robert, Philippe Le Sager, Etienne Tourigny, Shiyu Wang, Michiel van Weele, and Klaus Wyser
Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, https://doi.org/10.5194/gmd-13-3507-2020, 2020
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HighResMIP is an international coordinated CMIP6 effort to investigate the improvement in climate modeling caused by an increase in horizontal resolution. This paper describes EC-Earth3P-(HR), which has been developed for HighResMIP. First analyses reveal that increasing resolution does improve certain aspects of the simulated climate but that many other biases still continue, possibly related to phenomena that are still not yet resolved and need to be parameterized.
Maksim Iakunin, Victor Stepanenko, Rui Salgado, Miguel Potes, Alexandra Penha, Maria Helena Novais, and Gonçalo Rodrigues
Geosci. Model Dev., 13, 3475–3488, https://doi.org/10.5194/gmd-13-3475-2020, https://doi.org/10.5194/gmd-13-3475-2020, 2020
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The Alqueva reservoir, located in the southeast of Portugal, is the largest artificial reservoir in western Europe. It was established in 2002 to provide water and electrical resources to meet regional needs. Complex research of this reservoir is an essential scientific task in the scope of meteorology, hydrology, biology, and ecology. Two numerical models (namely, LAKE 2.0 and FLake) were used to assess the thermodynamic and biogeochemical regimes of the reservoir over 2 years of observations.
Klaus Wyser, Twan van Noije, Shuting Yang, Jost von Hardenberg, Declan O'Donnell, and Ralf Döscher
Geosci. Model Dev., 13, 3465–3474, https://doi.org/10.5194/gmd-13-3465-2020, https://doi.org/10.5194/gmd-13-3465-2020, 2020
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The EC-Earth model used for CMIP6 is found to have a higher equilibrium climate sensitivity (ECS) than its predecessor used for CMIP5. In a series of sensitivity experiments, we investigate which model updates since CMIP5 have contributed to the increase in ECS. The main reason for the higher sensitivity in the EC-Earth model is the improved representation of the aerosol–radiation and aerosol–cloud interactions.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Peter Burek, Yusuke Satoh, Taher Kahil, Ting Tang, Peter Greve, Mikhail Smilovic, Luca Guillaumot, Fang Zhao, and Yoshihide Wada
Geosci. Model Dev., 13, 3267–3298, https://doi.org/10.5194/gmd-13-3267-2020, https://doi.org/10.5194/gmd-13-3267-2020, 2020
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We present the new global hydrological model "Community Water Model" (CWatM), which can be used globally and regionally. The model is open source and written with the Python programming language. It uses global, freely available data in a smart and state-of-the-art format. It includes the major hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demand from the agriculture, domestic, and industrial sectors.
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020, https://doi.org/10.5194/gmd-13-3241-2020, 2020
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Online coupling of meteorology and chemistry models often presents maintenance issues with hard-wired coding. We present WRF-GC, an one-way online coupling of the WRF meteorological model and GEOS-Chem atmospheric chemistry model for regional atmospheric chemistry and air quality modeling. Our coupling structure allows future versions of either parent model to be immediately integrated into WRF-GC. The WRF-GC model was able to well reproduce regional PM2.5 with greater computational efficiency.
Jon Sáenz, Sheila Carreno-Madinabeitia, Ganix Esnaola, Santos J. González-Rojí, Gabriel Ibarra-Berastegi, and Alain Ulazia
Geosci. Model Dev., 13, 3221–3240, https://doi.org/10.5194/gmd-13-3221-2020, https://doi.org/10.5194/gmd-13-3221-2020, 2020
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A new diagram for the verification of vector variables (wind, current, etc.) generated by multiple models against a set of observations is presented in this package. It has been designed as a generalization of the Taylor diagram for two-dimensional quantities. It is based on the analysis of the two-dimensional structure of the mean squared error matrix between model and observations, and it allows for an easy assessment of both bias and directional errors as well.
Lei Ma, George C. Hurtt, Louise P. Chini, Ritvik Sahajpal, Julia Pongratz, Steve Frolking, Elke Stehfest, Kees Klein Goldewijk, Donal O'Leary, and Jonathan C. Doelman
Geosci. Model Dev., 13, 3203–3220, https://doi.org/10.5194/gmd-13-3203-2020, https://doi.org/10.5194/gmd-13-3203-2020, 2020
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Earth system models require information on historical land cover change. We present transition rules to generate land cover change from newly developed land use dataset (Land-use Harmonization, LUH2). The resulting forest cover, vegetation carbon, and emissions from land use and land cover change are simulated and evaluated against remote sensing data and other studies. The rules can guide the incorporation of land-cover information within earth system models for CMIP6.
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Short summary
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.
Data assimilation combines observations with numerical models to get an improved estimate of the...
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