Articles | Volume 12, issue 9
https://doi.org/10.5194/gmd-12-3975-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-3975-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
09 Sep 2019
Model description paper |
| 09 Sep 2019
| 09 Sep 2019
Developing a monthly radiative kernel for surface albedo change from satellite climatologies of Earth's shortwave radiation budget: CACK v1.0
Department of Forests and Climate, Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research, Ås, Norway
Thomas L. O'Halloran
Department of Forestry and Environmental Conservation, Clemson
University, Clemson, South Carolina, USA
Baruch Institute of Coastal Ecology and Forest Science, Clemson
University, Georgetown, South Carolina, USA
Related authors
Ryan M. Bright and Marianne T. Lund
Atmos. Chem. Phys., 21, 9887–9907, https://doi.org/10.5194/acp-21-9887-2021, https://doi.org/10.5194/acp-21-9887-2021, 2021
Short summary
Short summary
Humans affect the reflective properties (albedo) of Earth's surface and the amount of solar energy that it absorbs, in turn affecting climate. In recent years, a variety of climate metrics have been applied to characterize albedo perturbations in terms of their
CO2-equivalenteffects, despite the lack of scientific consensus surrounding the methods behind them. We review these metrics, evaluate their (de)merits, provide guidance for future application, and suggest avenues for future research.
Titta Majasalmi and Ryan M. Bright
Geosci. Model Dev., 12, 3923–3938, https://doi.org/10.5194/gmd-12-3923-2019, https://doi.org/10.5194/gmd-12-3923-2019, 2019
Short summary
Short summary
Many land surface models rely on solutions derived from two-stream approximations utilizing leaf-level optical properties, many of which have not been formally reviewed or published. Using plant functional type groupings of the Community Land Model (CLM), we found large deviations between measured and CLM default near-infrared optical properties, implying that the modeled shortwave radiation budget including surface albedo may be expected to change after updating the biased parameters.
Titta Majasalmi, Stephanie Eisner, Rasmus Astrup, Jonas Fridman, and Ryan M. Bright
Biogeosciences, 15, 399–412, https://doi.org/10.5194/bg-15-399-2018, https://doi.org/10.5194/bg-15-399-2018, 2018
Short summary
Short summary
Forest management shapes forest structure and in turn surface–atmosphere interactions. We used Fennoscandian forest maps and inventory data to develop a classification system for forest structure. The classification was integrated with the ESA Climate Change Initiative land cover map to achieve complete surface representation. The result is an improved product for modeling surface–atmosphere exchanges in regions with intensively managed forests.
R. M. Bright, G. Myhre, R. Astrup, C. Antón-Fernández, and A. H. Strømman
Biogeosciences, 12, 2195–2205, https://doi.org/10.5194/bg-12-2195-2015, https://doi.org/10.5194/bg-12-2195-2015, 2015
R. M. Bright and M. M. Kvalevåg
Atmos. Chem. Phys., 13, 11169–11174, https://doi.org/10.5194/acp-13-11169-2013, https://doi.org/10.5194/acp-13-11169-2013, 2013
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Ryan M. Bright and Marianne T. Lund
Atmos. Chem. Phys., 21, 9887–9907, https://doi.org/10.5194/acp-21-9887-2021, https://doi.org/10.5194/acp-21-9887-2021, 2021
Short summary
Short summary
Humans affect the reflective properties (albedo) of Earth's surface and the amount of solar energy that it absorbs, in turn affecting climate. In recent years, a variety of climate metrics have been applied to characterize albedo perturbations in terms of their
CO2-equivalenteffects, despite the lack of scientific consensus surrounding the methods behind them. We review these metrics, evaluate their (de)merits, provide guidance for future application, and suggest avenues for future research.
Titta Majasalmi and Ryan M. Bright
Geosci. Model Dev., 12, 3923–3938, https://doi.org/10.5194/gmd-12-3923-2019, https://doi.org/10.5194/gmd-12-3923-2019, 2019
Short summary
Short summary
Many land surface models rely on solutions derived from two-stream approximations utilizing leaf-level optical properties, many of which have not been formally reviewed or published. Using plant functional type groupings of the Community Land Model (CLM), we found large deviations between measured and CLM default near-infrared optical properties, implying that the modeled shortwave radiation budget including surface albedo may be expected to change after updating the biased parameters.
Titta Majasalmi, Stephanie Eisner, Rasmus Astrup, Jonas Fridman, and Ryan M. Bright
Biogeosciences, 15, 399–412, https://doi.org/10.5194/bg-15-399-2018, https://doi.org/10.5194/bg-15-399-2018, 2018
Short summary
Short summary
Forest management shapes forest structure and in turn surface–atmosphere interactions. We used Fennoscandian forest maps and inventory data to develop a classification system for forest structure. The classification was integrated with the ESA Climate Change Initiative land cover map to achieve complete surface representation. The result is an improved product for modeling surface–atmosphere exchanges in regions with intensively managed forests.
R. M. Bright, G. Myhre, R. Astrup, C. Antón-Fernández, and A. H. Strømman
Biogeosciences, 12, 2195–2205, https://doi.org/10.5194/bg-12-2195-2015, https://doi.org/10.5194/bg-12-2195-2015, 2015
R. M. Bright and M. M. Kvalevåg
Atmos. Chem. Phys., 13, 11169–11174, https://doi.org/10.5194/acp-13-11169-2013, https://doi.org/10.5194/acp-13-11169-2013, 2013
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Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20–30%. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases accessibility of training and working with the model.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-73, https://doi.org/10.5194/gmd-2024-73, 2024
Revised manuscript accepted for GMD
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Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
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Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-70, https://doi.org/10.5194/gmd-2024-70, 2024
Revised manuscript accepted for GMD
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Hurricanes may worsen the water quality in the lower Mississippi River Basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate-nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni G. Seijo-Ellis, Donata Giglio, Gustavo M. Marques, and Frank O. Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1378, https://doi.org/10.5194/egusphere-2024-1378, 2024
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A CESM/MOM6 regional configuration of the Caribbean Sea was developed as a response to the rising need of high-resolution models for climate impact studies. The configuration is validated for the period of 2000–2020 and improves significant errors in a low resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon river are well captured and the mean flows across the multiple passages in the Caribbean Sea agree with observations.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Catherine Guiavarc'h, Dave Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene T. Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
EGUsphere, https://doi.org/10.5194/egusphere-2024-805, https://doi.org/10.5194/egusphere-2024-805, 2024
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GOSI9 is the new UK’s hierarchy of global ocean and sea ice models. Developed as part of a collaboration between several UK research institutes it will be used for various applications such as weather forecast and climate prediction. The models, based on NEMO, are available at three resolutions 1°, ¼° and 1/12°. GOSI9 improves upon previous version by reducing global temperature and salinity biases and enhancing the representation of the Arctic sea ice and of the Antarctic Circumpolar Current.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Cited articles
Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P.,
Jones, C., Jung, M., Myneni, R., and Zhu, Z.: Evaluating the Land and Ocean
Components of the Global Carbon Cycle in the CMIP5 Earth System Models,
J. Climate, 26, 6801–6843, 2013.
Atwood, A. R., Wu, E., Frierson, D. M. W., Battisti, D. S., and Sachs, J.
P.: Quantifying Climate Forcings and Feedbacks over the Last Millennium in
the CMIP5–PMIP3 Models, J. Climate, 29, 1161–1178, 2016.
Block, K. and Mauritsen, T.: Forcing and feedback in the MPI-ESM-LR coupled
model under abruptly quadrupled CO2, J. Adv. Model. Earth
Sy., 5, 676–691, 2014.
Block, K. and Mauritsen, T.: ECHAM6 CTRL kernel, available at: https://swiftbrowser.dkrz.de/public/dkrz_0c07783a-0bdc-4d5e-9f3b-c1b86fac060d/Radiative_kernels/ (last access: 2 September 2019), 2015.
Bonan, G. B., Pollard, D., and Thompson, S. L.: Effects of Boreal Forest
Vegetation on Global Climate, Nature, 359, 716–718, 1992.
Bozzi, E., Genesio, L., Toscano, P., Pieri, M., and Miglietta, F.: Mimicking
biochar-albedo feedback in complex Mediterranean agricultural landscapes,
Environ. Res. Lett., 10, 084014, https://doi.org/10.1088/1748-9326/10/8/084014, 2015.
Breipohl, A. M.: Probabilistic systems analysis: an introduction to
probabilistic models, decisions, and applications of random processes,
Wiley, New York, USA, 1970.
Bretherton, C. S., Uttal, T., Fairall, C. W., Yuter, S. E., Weller, R. A.,
Baumgardner, D., Comstock, K., Wood, R., and Raga, G. B.: The Epic 2001
Stratocumulus Study, B. Am. Meteorol. Soc., 85,
967–978, 2004.
Bright, R. M.: Metrics for Biogeophysical Climate Forcings from Land Use and
Land Cover Changes and Their Inclusion in Life Cycle Assessment: A Critical
Review, Environ. Sci. Technol., 49, 3291–3303, 2015.
Bright, R. M. and Kvalevåg, M. M.: Technical Note: Evaluating a simple parameterization of radiative shortwave forcing from surface albedo change, Atmos. Chem. Phys., 13, 11169–11174, https://doi.org/10.5194/acp-13-11169-2013, 2013.
Bright, R. M. and O'Halloran, T. L.: A monthly shortwave radiative forcing kernel for surface albedo change using CERES satellite data, Environmental Data Initiative,
https://doi.org/10.6073/pasta/d77b84b11be99ed4d5376d77fe0043d8, 2019.
Caiazzo, F., Malina, R., Staples, M. D., Wolfe, P., J., Yim, S. H. L., and
Barrett, S. R. H.: Quantifying the climate impacts of albedo changes due to
biofuel production: a comparison with biogeochemical effects, Environ. Res. Lett., 9, 024015, https://doi.org/10.1088/1748-9326/9/2/024015, 2014.
Carrer, D., Pique, G., Ferlicoq, M., Ceamanos, X., and Ceschia, E.: What is
the potential of cropland albedo management in the fight against global
warming? A case study based on the use of cover crops, Environ. Res. Lett., 13, 044030, https://doi.org/10.1088/1748-9326/aab650, 2018.
CERES Science Team: CERES EBAF-Surface Edition 4.0. NASA Atmospheric Science
and Data Center (ASDC), https://doi.org/10.5067/TERRA+AQUA/CERES/EBAF-SURFACE_L3B004.0, 2018a.
CERES Science Team: CERES EBAF-TOA Edition 4.0. NASA Atmospheric Science and
Data Center (ASDC), https://doi.org/10.5067/TERRA+AQUA/CERES/EBAF-TOA_L3B004.0, 2018b.
Cherubini, F., Bright, R. M., and Strømman, A. H.: Site-specific global
warming potentials of biogenic CO2 for bioenergy: contributions from carbon
fluxes and albedo dynamics, Environ. Res. Lett., 7, 045902, https://doi.org/10.1088/1748-9326/7/4/045902, 2012.
Clifford, A. A.: Multivariate error analysis: A handbook of error
propagation and calculation in many-parameter systems, Applied Science
Publishers, London, UK, 1973.
Collins, W. D., Rasch, P. J., Boville, B. A., Hack, J. J., McCaa, J. R.,
Williamson, D. L., Briegleb, B. P., Bitz, C. M., Lin, S.-J., and Zhang, M.:
The Formulation and Atmospheric Simulation of the Community Atmosphere Model
Version 3 (CAM3), J. Climate, 19, 2144–2161, 2006.
Dickinson, R. E. and Henderson-Sellers, A.: Modelling tropical
deforestation: A study of GCM land-surface parametrizations, Q.
J. Roy. Meteor. Soc., 114, 439–462, 1988.
Dolinar, E. K., Dong, X., Xi, B., Jiang, J. H., and Su, H.: Evaluation of
CMIP5 simulated clouds and TOA radiation budgets using NASA satellite
observations, Clim. Dynam., 44, 2229–2247, 2015.
Donohoe, A. and Battisti, D. S.: Atmospheric and Surface Contributions to
Planetary Albedo, J. Climate, 24, 4402–4418, 2011.
Durieux, L., Machado, L. A. T., and Laurent, H.: The impact of deforestation
on cloud cover over the Amazon arc of deforestation, Remote Sens.
Environ., 86, 132–140, 2003.
Free, M. and Sun, B.: Trends in U.S. Total Cloud Cover from a
Homogeneity-Adjusted Dataset, J. Climate, 27, 4959–4969, 2014.
Gao, F., He, T., Wang, Z., Ghimire, B., Shuai, Y., Masek, J., Schaaf, C.,
and Williams, C.: Multi-scale climatological albedo look-up maps derived
from MODIS BRDF/albedo products, J. Appl. Remote Sens., 8, 083532, https://doi.org/10.1117/1.JRS.8.083532, 2014.
Ghimire, B., Williams, C. A., Masek, J., Gao, F., Wang, Z., Schaaf, C., and
He, T.: Global albedo change and radiative cooling from anthropogenic land
cover change, 1700 to 2005 based on MODIS, land use harmonization, radiative
kernels, and reanalysis, Geophys. Res. Lett., 41, 9087–9096, 2014.
Green, P., Gardiner, T., Medland, D., and Cimini, D.: WP2: Guide to
uncertainty in measurement and its nomenclature, Version 4.0., UK, National Physical Laboratory (NPL), Centre for Carbon Measurement, Teddington, UK, 212 pp., 2017.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner,
P. J., Lamarque, J. F., Large, W. G., Lawrence, D., Lindsay, K., Lipscomb,
W. H., Long, M. C., Mahowald, N., Marsh, D. R., Neale, R. B., Rasch, P., Vavrus, S., Vertenstein, M., Bader, D., Collins, W. D., Hack, J.
J., Kiehl, J., and Marshall, S.: The Community Earth System Model: A
Framework for Collaborative Research, B. Am. Meteorol. Soc., 94, 1339–1360, 2013.
Iqbal, M.: An introduction to solar radiation, Academic Press Canada,
Ontario, CA, Canada, 1983.
Jones, A. D., Calvin, K. V., Collins, W. D., and Edmonds, J.: Accounting for
radiative forcing from albedo change in future global land-use scenarios,
Climatic Change, 131, 691–703, 2015.
Kashimura, H., Abe, M., Watanabe, S., Sekiya, T., Ji, D., Moore, J. C., Cole, J. N. S., and Kravitz, B.: Shortwave radiative forcing, rapid adjustment, and feedback to the surface by sulfate geoengineering: analysis of the Geoengineering Model Intercomparison Project G4 scenario, Atmos. Chem. Phys., 17, 3339–3356, https://doi.org/10.5194/acp-17-3339-2017, 2017.
Kato, S., Loeb, N. G., Rose, F. G., Doelling, D. R., Rutan, D. A., Caldwell,
T. E., Yu, L., and Weller, R. A.: Surface Irradiances Consistent with
CERES-Derived Top-of-Atmosphere Shortwave and Longwave Irradiances, J. Climate, 26, 2719–2740, 2012.
Kato, S., Loeb, N. G., Rose, F. G., Doelling, D. R., Rutan, D. A., Caldwell,
T. E., Yu, L., and Weller, R. A.: Surface irradiances consistent with
CERES-derived top-of-atmosphere shortwave and longwave irradiances, J. Climate, 26, 2719–2740, 2013.
Kato, S., Rose, F. G., Rutan, D. A., Thorsen, T. J., Loeb, N. G., Doelling,
D. R., Huang, X., Smith, W. L., Su, W., and Ham, S.-H.: Surface Irradiances
of Edition 4.0 Clouds and the Earth's Radiant Energy System (CERES) Energy
Balanced and Filled (EBAF) Data Product, J. Climate, 31, 4501–4527,
2018.
Lacis, A. A. and Hansen, J. E.: A parameterization for the absorption of
solar radiation in the earth's atmosphere, J. Atmos. Sci.,
31, 118–133, 1974.
Lawrence, D. and Vandecar, K.: Effects of tropical deforestation on climate
and agriculture, Nat. Clim. Change, 5, 27–36, doi:10.1038/nclimate2430, 2014.
Lenton, T. M. and Vaughan, N. E.: The radiative forcing potential of different climate geoengineering options, Atmos. Chem. Phys., 9, 5539–5561, https://doi.org/10.5194/acp-9-5539-2009, 2009.
Li, J. L. F., Waliser, D. E., Stephens, G., Lee, S., L'Ecuyer, T., Kato, S.,
Loeb, N., and Ma, H.-Y.: Characterizing and understanding radiation budget
biases in CMIP3/CMIP5 GCMs, contemporary GCM, and reanalysis, J.
Geophys. Res.-Atmos., 118, 8166–8184, 2013.
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward optimal closure of the
Earth's top-of-atmosphere radiation budget, J. Climate, 22, 748–766,
2009.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G.,
Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth's
Radiant Energy System (CERES) Energy Balanced and Filled (EBAF)
Top-of-Atmosphere (TOA) Edition-4.0 Data Product, J. Climate, 31,
895–918, 2017.
Lutz, D. A. and Howarth, R. B.: The price of snow: albedo valuation and a
case study for forest management, Environ. Res. Lett., 10,
064013, doi:10.1088/1748-9326/10/6/064013, 2015.
Lutz, D. A., Burakowski, E. A., Murphy, M. B., Borsuk, M. E., Niemiec, R.
M., and Howarth, R. B.: Tradeoffs between three forest ecosystem services
across the state of New Hampshire, USA: timber, carbon, and albedo,
Ecol. Appl., 26, 146–161, 2015.
Mahadevan, S. and Sarkar, S.: Uncertainty analysis methods, U.S. Department
of Energy, Washington, D.C., USA, 32 pp., 2009.
Muñoz, I., Campra, P., and Fernández-Alba, A. R.: Including
CO2-emission equivalence of changes in land surface albedo in life cycle
assessment. Methodology and case study on greenhouse agriculture,
Int. J. Life Cycle Ass., 15, 672–681, 2010.
O'Halloran, T. L., Law, B. E., Goulden, M. L., Wang, Z., Barr, J. G.,
Schaaf, C., Brown, M., Fuentes, J. D., Göckede, M., Black, A., and
Engel, V.: Radiative forcing of natural forest disturbances, Glob. Change
Biol., 18, 555–565, 2012.
Pendergrass, A. G.: CAM5 Radiative Kernels, available at: https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.cam5-kernels.html (last access: 2 September 2019), 2017.
Pendergrass, A. G., Conley, A., and Vitt, F. M.: Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5, Earth Syst. Sci. Data, 10, 317–324, https://doi.org/10.5194/essd-10-317-2018, 2018.
Qu, X. and Hall, A.: Assessing Snow Albedo Feedback in Simulated Climate
Change, J. Climate, 19, 2617–2630, 2006.
Randerson, J. T., Liu, H., Flanner, M. G., Chambers, S. D., Jin, Y., Hess,
P. G., Pfister, G., Mack, M. C., Treseder, K. K., Welp, L. R., Chapin, F.
S., Harden, J. W., Goulden, M. L., Lyons, E., Neff, J. C., Schuur, E. A. G.,
and Zender, C. S.: The Impact of Boreal Forest Fire on Climate Warming,
Science, 314, 1130–1132, 2006.
Rasool, S. I. and Schneider, S. H.: Atmospheric Carbon Dioxide and Aerosols:
Effects of Large Increases on Global Climate, Science, 173, 138–141, 1971.
Richter, I.: Climate model biases in the eastern tropical oceans: causes,
impacts and ways forward, WIRES Clim. Change,
6, 345–358, 2015.
Schmidt, M. and Lipson, H.: Distilling free-form natural laws from
experimental data, Science, 324, 81–85, 2009.
Schmidt, M. and Lipson, H.: Symbolic regression of implicit equations, in:
Genetic Programming Theory and Practice VII, Springer, doi:10.1007/978-1-4419-1626-6, 2010.
Shell, K. M.: CAM3 radiative kernels, available at: http://people.oregonstate.edu/~shellk/kernel.html (last access: 2 September 2019), 2008.
Shell, K. M., Kiehl, J. T., and Shields, C. A.: Using the Radiative Kernel
Technique to Calculate Climate Feedbacks in NCAR's Community Atmospheric
Model, J. Climate, 21, 2269–2282, 2008.
Smits, G. F. and Kotanchek, M.: Pareto-front exploitation in symbolic
regression, in: Genetic programming theory and practice II, Springer, Boston, USA, 2005.
Soden, B. J., Held, I. M., Colman, R., Shell, K. M., Kiehl, J. T., and
Shields, C. A.: Quantifying Climate Feedbacks Using Radiative Kernels,
J. Climate, 21, 3504–3520, 2008.
Srivastava, R.: Trends in aerosol optical properties over South Asia,
Int. J. Climatol., 37, 371–380, 2017.
Stephens, G. L., O'Brien, D., Webster, P. J., Pilewski, P., Kato, S., and
Li, J.-l.: The albedo of Earth, Rev. Geophys., 53, 141–163, 2015.
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S.,
Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I.,
Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and
Roeckner, E.: Atmospheric component of the MPI-M Earth System Model: ECHAM6,
J. Adv. Model. Earth Sy., 5, 146–172, 2013.
Taylor, K. E., Crucifix, M., Braconnot, P., Hewitt, C. D., Doutriaux, C.,
Broccoli, A. J., Mitchell, J. F. B., and Webb, M. J.: Estimating Shortwave
Radiative Forcing and Response in Climate Models, J. Climate, 20,
2530–2543, 2007.
The GFDL Global Atmospheric Model Development Team: The New GFDL Global
Atmosphere and Land Model AM2–LM2: Evaluation with Prescribed SST
Simulations, J. Climate, 17, 4641–4673, 2004.
Vanderhoof, M., Williams, C. A., Ghimire, B., and Rogan, J.: Impact of
mountain pine beetle outbreaks on forest albedo and radiative forcing, as
derived from Moderate Resolution Imaging Spectroradiometer, Rocky Mountains,
USA, J. Geophys. Res.-Biogeo., 118, 1461–1471, 2013.
Wang, H. and Su, W.: Evaluating and understanding top of the atmosphere
cloud radiative effects in Intergovernmental Panel on Climate Change (IPCC)
Fifth Assessment Report (AR5) Coupled Model Intercomparison Project Phase 5
(CMIP5) models using satellite observations, J. Geophys.
Res.-Atmos., 118, 683–699, 2013.
Winton, M.: Simple optical models for diagnosing surface-atmosphere
shortwave interactions, J. Climate, 18, 3796–3806, 2005.
Winton, M.: Surface Albedo Feedback Estimates for the AR4 Climate Models,
J. Climate, 19, 359–365, 2006.
Wright, J. S., Fu, R., Worden, J. R., Chakraborty, S., Clinton, N. E., Risi,
C., Sun, Y., and Yin, L.: Rainforest-initiated wet season onset over the
southern Amazon, P. Natl. Acad. Sci. USA, 114, 8481–8486, https://doi.org/10.1073/pnas.1621516114, 2017.
Zhao, D., Xin, J., Gong, C., Wang, X., Ma, Y., and Ma, Y.: Trends of Aerosol
Optical Properties over the Heavy Industrial Zone of Northeastern Asia in
the Past Decade (2004–15), J. Atmos. Sci., 75,
1741–1754, 2018.
Short summary
To determine the effects of land cover change on climate, researchers must be able to quantify the net change in energy (radiation) at the top of the atmosphere caused by changes in surface reflectance (albedo). Historically, this was done with sophisticated models that require detailed input datasets only available to specialists. Here we combine existing remotely sensed datasets and a new formulation to create a new model that is accurate, transparent, and easy to use.
To determine the effects of land cover change on climate, researchers must be able to quantify...
