Articles | Volume 15, issue 4
https://doi.org/10.5194/gmd-15-1789-2022
© Author(s) 2022. 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-15-1789-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
02 Mar 2022
Model evaluation paper |
| 02 Mar 2022
| 02 Mar 2022
CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
A. Anthony Bloom
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Shuang Ma
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Paul Levine
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Alexander Norton
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Nicholas C. Parazoo
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
John T. Reager
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
John Worden
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Gregory R. Quetin
Department of Earth System Science, Stanford University, Stanford, CA
94305, USA
T. Luke Smallman
School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF,
United Kingdom
National Centre for Earth Observation, University of Edinburgh,
Edinburgh, EH9 3FF, United Kingdom
Mathew Williams
School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF,
United Kingdom
National Centre for Earth Observation, University of Edinburgh,
Edinburgh, EH9 3FF, United Kingdom
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Sassan Saatchi
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
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Sarah E. Hancock, Daniel Jacob, Zichong Chen, Hannah Nesser, Aaron Davitt, Daniel J. Varon, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, James D. East, Elise Penn, Cynthia A. Randles, John Worden, Ilse Aben, Robert J. Parker, and Joannes D. Maasakkers
EGUsphere, https://doi.org/10.5194/egusphere-2024-1763, https://doi.org/10.5194/egusphere-2024-1763, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We quantify 2021 methane emissions in South America at up to 25 km × 25 km resolution using satellite methane observations. We find a 55 % upward correction to the national anthropogenic inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC) under the Paris Agreement. Our estimates match inventories for Brazil, Bolivia, and Paraguay but are much higher for other countries. Livestock emissions (65 % of anthropogenic emissions) show the largest discrepancies.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Alba Lorente, Zichong Chen, Xiao Lu, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Margaux Winter, Shuang Ma, A. Anthony Bloom, John R. Worden, Robert N. Stavins, and Cynthia A. Randles
Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, https://doi.org/10.5194/acp-24-5069-2024, 2024
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We quantify 2019 methane emissions in the contiguous US (CONUS) at a ≈ 25 km × 25 km resolution using satellite methane observations. We find a 13 % upward correction to the 2023 US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) for 2019, with large corrections to individual states, urban areas, and landfills. This may present a challenge for US climate policies and goals, many of which target significant reductions in methane emissions.
Russell Doughty, Yujie Wang, Jennifer Johnson, Nicholas Parazoo, Troy Magney, Zoe Pierrat, Xiangming Xiao, Luis Guanter, Philipp Köhler, Christian Frankenberg, Peter Somkuti, Shuang Ma, Yuanwei Qin, Sean Crowell, and Berrien Moore III
EGUsphere, https://doi.org/10.22541/essoar.168167172.20799710/v1, https://doi.org/10.22541/essoar.168167172.20799710/v1, 2024
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Here we present a novel model of global photosynthesis, ChloFluo, which uses spaceborne chlorophyll fluorescence to estimate the amount of photosynthetically active radiation absorbed by chlorophyll. Potential uses of our model are to advance our understanding of the timing and magnitude of photosynthesis, its effect on atmospheric carbon dioxide fluxes, and vegetation response to climate events and change.
Russell Doughty, Michael C. Wimberly, Dan Wanyama, Helene Peiro, Nicholas Parazoo, Sean Crowell, and Moses Azong Cho
EGUsphere, https://doi.org/10.5194/egusphere-2023-3022, https://doi.org/10.5194/egusphere-2023-3022, 2024
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We find West African SIF to increase during the dry season and peak prior to precipitation, similar to the Amazon. In Central Africa, we find a continental-scale bimodal seasonality in SIF, the minimum of which is synchronous with precipitation, but its maximum is likely less related to environmental drivers. We also find important differences in the seasonality of SIF and VIs, which indicates that VI-based estimates of photosynthesis could be inaccurate as they have been shown to be the Amazon.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-516, https://doi.org/10.5194/essd-2023-516, 2024
Revised manuscript under review for ESSD
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This study provides an overview of data availability from observation and inventory-based CH4 emissions estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more Parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan Berner, Amy Breen, Abhishek Chatterjee, Scott Davidson, Gerald Frost, Teresa Hollingsworth, Go Iwahana, Randi Jandt, Anja Kade, Tatiana Loboda, Matt Macander, Michelle Mack, Charles Miller, Eric Miller, Susan Natali, Martha Raynolds, Adrian Rocha, Shiro Tsuyuzaki, Craig Tweedie, Donald Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-222, https://doi.org/10.5194/essd-2023-222, 2023
Revised manuscript accepted for ESSD
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The Arctic tundra is experiencing widespread physical and biological changes largely in response to warming. Yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and study compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which pulls together field datasets and includes vegetation, active layer, and fire-related properties.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
David T. Milodowski, T. Luke Smallman, and Mathew Williams
Biogeosciences, 20, 3301–3327, https://doi.org/10.5194/bg-20-3301-2023, https://doi.org/10.5194/bg-20-3301-2023, 2023
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Model–data fusion (MDF) allows us to combine ecosystem models with Earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to improve ecological fidelity of the calibrated models.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Y. Liu, and Jingyun Fang
Earth Syst. Sci. Data, 15, 1577–1596, https://doi.org/10.5194/essd-15-1577-2023, https://doi.org/10.5194/essd-15-1577-2023, 2023
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We provide the first long-term (since 1992), high-resolution (8.9 km) satellite radar backscatter data set (LHScat) with a C-band (5.3 GHz) signal dynamic for global lands. LHScat was created by fusing signals from ERS (1992–2001; C-band), QSCAT (1999–2009; Ku-band), and ASCAT (since 2007; C-band). LHScat has been validated against independent ERS-2 signals. It could be used in a variety of studies, such as vegetation monitoring and hydrological modelling.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
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The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
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Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Helen M. Worden, Gene L. Francis, Susan S. Kulawik, Kevin W. Bowman, Karen Cady-Pereira, Dejian Fu, Jennifer D. Hegarty, Valentin Kantchev, Ming Luo, Vivienne H. Payne, John R. Worden, Róisín Commane, and Kathryn McKain
Atmos. Meas. Tech., 15, 5383–5398, https://doi.org/10.5194/amt-15-5383-2022, https://doi.org/10.5194/amt-15-5383-2022, 2022
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Satellite observations of global carbon monoxide (CO) are essential for understanding atmospheric chemistry and pollution sources. This paper describes a new data product using radiance measurements from the Cross-track Infrared Sounder (CrIS) instrument on the Suomi National Polar-orbiting Partnership (SNPP) satellite that provides vertical profiles of CO from single-field-of-view observations. We show how these satellite CO profiles compare to aircraft observations and evaluate their biases.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
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This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Vivienne H. Payne, Susan S. Kulawik, Emily V. Fischer, Jared F. Brewer, L. Gregory Huey, Kazuyuki Miyazaki, John R. Worden, Kevin W. Bowman, Eric J. Hintsa, Fred Moore, James W. Elkins, and Julieta Juncosa Calahorrano
Atmos. Meas. Tech., 15, 3497–3511, https://doi.org/10.5194/amt-15-3497-2022, https://doi.org/10.5194/amt-15-3497-2022, 2022
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We compare new satellite measurements of peroxyacetyl nitrate (PAN) with reference aircraft measurements from two different instruments flown on the same platform. While there is a systematic difference between the two aircraft datasets, both show the same large-scale distribution of PAN and the discrepancy between aircraft datasets is small compared to the satellite uncertainties. The satellite measurements show skill in capturing large-scale variations in PAN.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
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This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
Biogeosciences, 19, 2245–2262, https://doi.org/10.5194/bg-19-2245-2022, https://doi.org/10.5194/bg-19-2245-2022, 2022
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The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
Russell Doughty, Thomas P. Kurosu, Nicholas Parazoo, Philipp Köhler, Yujie Wang, Ying Sun, and Christian Frankenberg
Earth Syst. Sci. Data, 14, 1513–1529, https://doi.org/10.5194/essd-14-1513-2022, https://doi.org/10.5194/essd-14-1513-2022, 2022
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We describe and compare solar-induced chlorophyll fluorescence data produced by NASA from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 platforms.
Elias C. Massoud, A. Anthony Bloom, Marcos Longo, John T. Reager, Paul A. Levine, and John R. Worden
Hydrol. Earth Syst. Sci., 26, 1407–1423, https://doi.org/10.5194/hess-26-1407-2022, https://doi.org/10.5194/hess-26-1407-2022, 2022
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The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step toward improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
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We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
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Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Jennifer D. Hegarty, Karen E. Cady-Pereira, Vivienne H. Payne, Susan S. Kulawik, John R. Worden, Valentin Kantchev, Helen M. Worden, Kathryn McKain, Jasna V. Pittman, Róisín Commane, Bruce C. Daube Jr., and Eric A. Kort
Atmos. Meas. Tech., 15, 205–223, https://doi.org/10.5194/amt-15-205-2022, https://doi.org/10.5194/amt-15-205-2022, 2022
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Carbon monoxide (CO) is produced by combustion of substances such as fossil fuels and plays an important role in atmospheric pollution and climate. We evaluated estimates of atmospheric CO derived from outgoing radiation measurements of the Atmospheric Infrared Sounder (AIRS) on a satellite orbiting the Earth against CO measurements from aircraft to show that these satellite measurements are reliable for continuous global monitoring of atmospheric CO concentrations.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
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Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
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A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754, https://doi.org/10.5194/bg-18-2727-2021, https://doi.org/10.5194/bg-18-2727-2021, 2021
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Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
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We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
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We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Jin Ma, Linda M. J. Kooijmans, Ara Cho, Stephen A. Montzka, Norbert Glatthor, John R. Worden, Le Kuai, Elliot L. Atlas, and Maarten C. Krol
Atmos. Chem. Phys., 21, 3507–3529, https://doi.org/10.5194/acp-21-3507-2021, https://doi.org/10.5194/acp-21-3507-2021, 2021
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Carbonyl sulfide is an important trace gas in the atmosphere and useful to estimating gross primary productivity in ecosystems, but its sources and sinks remain highly uncertain. Therefore, we applied inverse model system TM5-4DVAR to better constrain the global budget. Our finding is in line with earlier studies, pointing to missing sources in the tropics and more uptake in high latitudes. We also stress the necessity of more ground-based observations and satellite data assimilation in future.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Alka Singh, John Thomas Reager, and Ali Behrangi
Hydrol. Earth Syst. Sci., 25, 511–526, https://doi.org/10.5194/hess-25-511-2021, https://doi.org/10.5194/hess-25-511-2021, 2021
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The study demonstrates the utility of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomalies (TWSAs) for obtaining statistics of hydrological droughts, i.e., recovery periods and required precipitation in different precipitation scenarios. The findings of this study are that the GRACE-based drought index is valid for estimating the required precipitation for drought recovery, and the period of drought recovery depends on the intensity of the precipitation.
Xueying Yu, Dylan B. Millet, Kelley C. Wells, Daven K. Henze, Hansen Cao, Timothy J. Griffis, Eric A. Kort, Genevieve Plant, Malte J. Deventer, Randall K. Kolka, D. Tyler Roman, Kenneth J. Davis, Ankur R. Desai, Bianca C. Baier, Kathryn McKain, Alan C. Czarnetzki, and A. Anthony Bloom
Atmos. Chem. Phys., 21, 951–971, https://doi.org/10.5194/acp-21-951-2021, https://doi.org/10.5194/acp-21-951-2021, 2021
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Methane concentrations have doubled since 1750. The US Upper Midwest is a key region contributing to such trends, but sources are poorly understood. We collected and analyzed aircraft data to resolve spatial and timing biases in wetland and livestock emission estimates and uncover errors in inventory treatment of manure management. We highlight the importance of intensive agriculture for the regional and US methane budgets and the potential for methane mitigation through improved management.
Sudhanshu Pandey, Sander Houweling, Alba Lorente, Tobias Borsdorff, Maria Tsivlidou, A. Anthony Bloom, Benjamin Poulter, Zhen Zhang, and Ilse Aben
Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, https://doi.org/10.5194/bg-18-557-2021, 2021
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We use atmospheric methane observations from the novel TROPOspheric Monitoring Instrument (TROPOMI; Sentinel-5p) to estimate methane emissions from South Sudan's wetlands. Our emission estimates are an order of magnitude larger than the estimate of process-based wetland models. We find that this underestimation by the models is likely due to their misrepresentation of the wetlands' inundation extent and temperature dependences.
Susan S. Kulawik, John R. Worden, Vivienne H. Payne, Dejian Fu, Steven C. Wofsy, Kathryn McKain, Colm Sweeney, Bruce C. Daube Jr., Alan Lipton, Igor Polonsky, Yuguang He, Karen E. Cady-Pereira, Edward J. Dlugokencky, Daniel J. Jacob, and Yi Yin
Atmos. Meas. Tech., 14, 335–354, https://doi.org/10.5194/amt-14-335-2021, https://doi.org/10.5194/amt-14-335-2021, 2021
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This paper shows comparisons of a new single-footprint methane product from the AIRS satellite to aircraft-based observations. We show that this AIRS methane product provides useful information to study seasonal and global methane trends of this important greenhouse gas.
Yuming Jin, Ralph F. Keeling, Eric J. Morgan, Eric Ray, Nicholas C. Parazoo, and Britton B. Stephens
Atmos. Chem. Phys., 21, 217–238, https://doi.org/10.5194/acp-21-217-2021, https://doi.org/10.5194/acp-21-217-2021, 2021
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We propose a new atmospheric coordinate (Mθe) based on equivalent potential temperature (θe) but with mass as the unit. This coordinate is useful in studying the spatial and temporal distribution of long-lived chemical tracers (CO2, CH4, O2 / N2, etc.) from sparse data, like airborne observation. Using this coordinate and sparse airborne observation (HIPPO and ATom), we resolve the Northern Hemisphere mass-weighted average CO2 seasonal cycle with high accuracy.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
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We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Robert J. Parker, Chris Wilson, A. Anthony Bloom, Edward Comyn-Platt, Garry Hayman, Joe McNorton, Hartmut Boesch, and Martyn P. Chipperfield
Biogeosciences, 17, 5669–5691, https://doi.org/10.5194/bg-17-5669-2020, https://doi.org/10.5194/bg-17-5669-2020, 2020
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Wetlands contribute the largest uncertainty to the atmospheric methane budget. WetCHARTs is a simple, data-driven model that estimates wetland emissions using observations of precipitation and temperature. We perform the first detailed evaluation of WetCHARTs against satellite data and find it performs well in reproducing the observed wetland methane seasonal cycle for the majority of wetland regions. In regions where it performs poorly, we highlight incorrect wetland extent as a key reason.
Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
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Satellite measurements of solar-induced chlorophyll fluorescence (SIF) provide a global measure of photosynthetic change. This enables scientists to better track carbon cycle responses to environmental change and tune biochemical processes in vegetation models for an improved simulation of future change. We use tower-instrumented SIF measurements and controlled model experiments to assess the state of the art in terrestrial biosphere SIF modeling and find a wide range of sensitivities to light.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
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Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
Alireza Farahmand, E. Natasha Stavros, John T. Reager, Ali Behrangi, James T. Randerson, and Brad Quayle
Nat. Hazards Earth Syst. Sci., 20, 1097–1106, https://doi.org/10.5194/nhess-20-1097-2020, https://doi.org/10.5194/nhess-20-1097-2020, 2020
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Wildfires result in billions of dollars of losses each year. Most wildfire predictions have a 10 d lead-time. This study introduces a framework for a 1-month lead-time prediction of wildfires based on vapor pressure deficit and surface soil moisture in the US. The results show that the model can successfully predict burned area with relatively small margins of error. This is especially important for operational wildfire management such as national resource allocation.
Robert L. Herman, John Worden, David Noone, Dean Henze, Kevin Bowman, Karen Cady-Pereira, Vivienne H. Payne, Susan S. Kulawik, and Dejian Fu
Atmos. Meas. Tech., 13, 1825–1834, https://doi.org/10.5194/amt-13-1825-2020, https://doi.org/10.5194/amt-13-1825-2020, 2020
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This study is the first assessment and validation of AIRS HDO / H2O retrieved by optimal estimation. Initial comparisons with in situ measurements from NASA ORACLES are promising: the small bias and consistent rms of AIRS suggest that AIRS has well-characterized HDO / H2O. This analysis opens the possibility of a new 17-year long-term data record of global tropospheric HDO / H2O measured from space.
Joseph T. D. Lucey, John T. Reager, and Sonya R. Lopez
Hydrol. Earth Syst. Sci., 24, 1415–1427, https://doi.org/10.5194/hess-24-1415-2020, https://doi.org/10.5194/hess-24-1415-2020, 2020
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This work relates total water storage (TWS) and rainfall to surface water inundation (SWI) using NASA satellite data. We determine whether TWS and/or rainfall control global SWI developments. Regression methods and cross-correlations were used to relate the measurements and correct for time differences among peaks. Results show TWS and rainfall control most global SWI developments. To our knowledge, this is the first global study on SWI controls and validates previous findings.
Tia R. Scarpelli, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Kelly Rose, Lucy Romeo, John R. Worden, and Greet Janssens-Maenhout
Earth Syst. Sci. Data, 12, 563–575, https://doi.org/10.5194/essd-12-563-2020, https://doi.org/10.5194/essd-12-563-2020, 2020
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Methane, a potent greenhouse gas, is emitted through the exploitation of oil, gas, and coal resources, and many efforts to reduce emissions have targeted these sources. We have created a global inventory of oil, gas, and coal methane emissions based on country reporting to the United Nations. The inventory can be used along with satellite observations of methane to better understand the contribution of these sources to global emissions and to identify potential biases in emissions reporting.
Corey R. Lawrence, Jeffrey Beem-Miller, Alison M. Hoyt, Grey Monroe, Carlos A. Sierra, Shane Stoner, Katherine Heckman, Joseph C. Blankinship, Susan E. Crow, Gavin McNicol, Susan Trumbore, Paul A. Levine, Olga Vindušková, Katherine Todd-Brown, Craig Rasmussen, Caitlin E. Hicks Pries, Christina Schädel, Karis McFarlane, Sebastian Doetterl, Christine Hatté, Yujie He, Claire Treat, Jennifer W. Harden, Margaret S. Torn, Cristian Estop-Aragonés, Asmeret Asefaw Berhe, Marco Keiluweit, Ágatha Della Rosa Kuhnen, Erika Marin-Spiotta, Alain F. Plante, Aaron Thompson, Zheng Shi, Joshua P. Schimel, Lydia J. S. Vaughn, Sophie F. von Fromm, and Rota Wagai
Earth Syst. Sci. Data, 12, 61–76, https://doi.org/10.5194/essd-12-61-2020, https://doi.org/10.5194/essd-12-61-2020, 2020
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The International Soil Radiocarbon Database (ISRaD) is an an open-source archive of soil data focused on datasets including radiocarbon measurements. ISRaD includes data from bulk or
whole soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil surface.
Sophie Flack-Prain, Patrick Meir, Yadvinder Malhi, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 16, 4463–4484, https://doi.org/10.5194/bg-16-4463-2019, https://doi.org/10.5194/bg-16-4463-2019, 2019
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Across the Amazon rainforest, trees take in carbon through photosynthesis. However, photosynthesis across the basin is threatened by predicted shifts in rainfall patterns. To unpick how changes in rainfall affect photosynthesis, we use a model which combines climate data with our knowledge of photosynthesis and other plant processes. We find that stomatal constraints are less important, and instead shifts in leaf surface area and leaf properties drive changes in photosynthesis with rainfall.
Helen M. Worden, A. Anthony Bloom, John R. Worden, Zhe Jiang, Eloise A. Marais, Trissevgeni Stavrakou, Benjamin Gaubert, and Forrest Lacey
Atmos. Chem. Phys., 19, 13569–13579, https://doi.org/10.5194/acp-19-13569-2019, https://doi.org/10.5194/acp-19-13569-2019, 2019
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Biogenic non-methane volatile organic compounds (NMVOCs) emitted from vegetation play a significant role in air quality and climate. However, there are large uncertainties in their role for climate. We present a Bayesian approach to estimate carbon monoxide fluxes that are chemically produced from biogenic sources. This provides independent constraints on models that predict biogenic emissions in order improve their capability for predicting air quality and future climate scenarios.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences, 16, 3069–3093, https://doi.org/10.5194/bg-16-3069-2019, https://doi.org/10.5194/bg-16-3069-2019, 2019
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This study presents an estimate of global terrestrial photosynthesis. We make use of satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and estimate photosynthetic carbon uptake. This new framework incorporates nonlinear, process-based understanding of the link between fluorescence and photosynthesis, an advance on past approaches. This will aid in the utility of fluorescence to quantify terrestrial carbon cycle feedbacks.
Heloisa Ehalt Macedo, Ralph Edward Beighley, Cédric H. David, and John T. Reager
Hydrol. Earth Syst. Sci., 23, 3269–3277, https://doi.org/10.5194/hess-23-3269-2019, https://doi.org/10.5194/hess-23-3269-2019, 2019
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The water stored under the surface is very important for defining the amount of water available for human and environmental applications; however, it is still a challenge to obtain such measurements. NASA's GRACE satellites provide information on total terrestrial water storage based on observations of gravity changes. Here, we relate GRACE data to streamflow measurements, providing estimations of the fraction of baseflow and total drainable storage for the Mississippi River basin.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jian-Xiong Sheng, Yuzhong Zhang, Monica Hersher, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, Greet Janssens-Maenhout, and Robert J. Parker
Atmos. Chem. Phys., 19, 7859–7881, https://doi.org/10.5194/acp-19-7859-2019, https://doi.org/10.5194/acp-19-7859-2019, 2019
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We use 2010–2015 satellite observations of atmospheric methane to improve estimates of methane emissions and their trends, as well as the concentration and trend of tropospheric OH (hydroxyl radical, methane's main sink). We find overestimates of Chinese coal and Middle East oil/gas emissions in the prior estimate. The 2010–2015 growth in methane is attributed to an increase in emissions from India, China, and areas with large tropical wetlands. The contribution from OH is small in comparison.
Thomas Luke Smallman and Mathew Williams
Geosci. Model Dev., 12, 2227–2253, https://doi.org/10.5194/gmd-12-2227-2019, https://doi.org/10.5194/gmd-12-2227-2019, 2019
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Photosynthesis and evapotranspiration are processes with global significance for climate, carbon and water cycling. Process-orientated simulation of these processes and their interactions have till now come at high computational cost. Here we present a new coupled model of intermediate complexity operating at orders of magnitude greater speed. Independent evaluation at FLUXNET sites for a single, global parameterization shows good agreement, with a typical R2 value of ~ 0.60.
Alexandra G. Konings, A. Anthony Bloom, Junjie Liu, Nicholas C. Parazoo, David S. Schimel, and Kevin W. Bowman
Biogeosciences, 16, 2269–2284, https://doi.org/10.5194/bg-16-2269-2019, https://doi.org/10.5194/bg-16-2269-2019, 2019
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We estimate heterotrophic respiration (Rh) – the respiration from microbes in the soil – using satellite estimates of the net carbon flux and other quantities. Rh is an important carbon flux but is rarely studied by itself. Our method is the first to estimate how Rh varies in both space and time. The resulting new estimate of Rh is compared to the best currently available alternative, which is based on interpolating field measurements globally. The two estimates disagree and are both uncertain.
Efrén López-Blanco, Jean-François Exbrayat, Magnus Lund, Torben R. Christensen, Mikkel P. Tamstorf, Darren Slevin, Gustaf Hugelius, Anthony A. Bloom, and Mathew Williams
Earth Syst. Dynam., 10, 233–255, https://doi.org/10.5194/esd-10-233-2019, https://doi.org/10.5194/esd-10-233-2019, 2019
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The terrestrial CO2 exchange in Arctic ecosystems plays an important role in the global carbon cycle and is particularly sensitive to the ongoing warming experienced in recent years. To improve our understanding of the atmosphere–biosphere interplay, we evaluated the state of the terrestrial pan-Arctic carbon cycling using a promising data assimilation system in the first 15 years of the 21st century. This is crucial when it comes to making predictions about the future state of the carbon cycle.
Vasileios Myrgiotis, Mathew Williams, Robert M. Rees, and Cairistiona F. E. Topp
Biogeosciences, 16, 1641–1655, https://doi.org/10.5194/bg-16-1641-2019, https://doi.org/10.5194/bg-16-1641-2019, 2019
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This study focuses on a northwestern European cropland region and shows that the type of crop growing on a soil has notable effects on the emission of nitrous oxide (N2O – a greenhouse gas) from that soil. It was found that N2O emissions from soils under oilseed cultivation are significantly higher than soils under cereal cultivation. This variation is mostly explained by the fact that oilseeds require more nitrogen (fertiliser) than cereals, especially at early crop growth stages.
John R. Worden, Susan S. Kulawik, Dejian Fu, Vivienne H. Payne, Alan E. Lipton, Igor Polonsky, Yuguang He, Karen Cady-Pereira, Jean-Luc Moncet, Robert L. Herman, Fredrick W. Irion, and Kevin W. Bowman
Atmos. Meas. Tech., 12, 2331–2339, https://doi.org/10.5194/amt-12-2331-2019, https://doi.org/10.5194/amt-12-2331-2019, 2019
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In this paper we take the first steps towards generating a multi-decadal record of the deuterium content of water vapor, useful for evaluating the moisture sources and processes affecting water vapor, by estimating the deuterium content from thermal IR radiances from the AIRS instrument. We find the AIRS-based measurements are sensitive to the deuterium content of water vapor in the middle and lower troposphere with a single measurement uncertainty of ~ 3 % and an accuracy of ~ 0.7 %.
Anne Sofie Lansø, Thomas Luke Smallman, Jesper Heile Christensen, Mathew Williams, Kim Pilegaard, Lise-Lotte Sørensen, and Camilla Geels
Biogeosciences, 16, 1505–1524, https://doi.org/10.5194/bg-16-1505-2019, https://doi.org/10.5194/bg-16-1505-2019, 2019
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Although coastal regions only amount to 7 % of the global oceans, their contribution to the global oceanic surface exchange of CO2 is much greater. In this study, we gain detailed insight into how these coastal marine fluxes compare to CO2 exchange from coastal land regions. Annually, the coastal marine exchanges are smaller than the total uptake of CO2 from the land surfaces within the study area but comparable in size to terrestrial fluxes from individual land cover classes of the region.
Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
Atmos. Chem. Phys., 19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019, https://doi.org/10.5194/acp-19-4345-2019, 2019
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Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
Yuanyuan Huang, Mark Stacy, Jiang Jiang, Nilutpal Sundi, Shuang Ma, Volodymyr Saruta, Chang Gyo Jung, Zheng Shi, Jianyang Xia, Paul J. Hanson, Daniel Ricciuto, and Yiqi Luo
Geosci. Model Dev., 12, 1119–1137, https://doi.org/10.5194/gmd-12-1119-2019, https://doi.org/10.5194/gmd-12-1119-2019, 2019
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Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD) into models. EcoPAD also has the potential to become an interactive tool for resource management, stimulate citizen science in ecology, and transform environmental education.
Yuzhong Zhang, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Ritesh Gautam, and John Worden
Atmos. Chem. Phys., 18, 15959–15973, https://doi.org/10.5194/acp-18-15959-2018, https://doi.org/10.5194/acp-18-15959-2018, 2018
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We assess the potential of using satellite observations of atmospheric methane to monitor global mean tropospheric OH concentration, a key parameter for the oxidizing power of the atmosphere.
Dejian Fu, Susan S. Kulawik, Kazuyuki Miyazaki, Kevin W. Bowman, John R. Worden, Annmarie Eldering, Nathaniel J. Livesey, Joao Teixeira, Fredrick W. Irion, Robert L. Herman, Gregory B. Osterman, Xiong Liu, Pieternel F. Levelt, Anne M. Thompson, and Ming Luo
Atmos. Meas. Tech., 11, 5587–5605, https://doi.org/10.5194/amt-11-5587-2018, https://doi.org/10.5194/amt-11-5587-2018, 2018
Yilong Wang, Philippe Ciais, Daniel Goll, Yuanyuan Huang, Yiqi Luo, Ying-Ping Wang, A. Anthony Bloom, Grégoire Broquet, Jens Hartmann, Shushi Peng, Josep Penuelas, Shilong Piao, Jordi Sardans, Benjamin D. Stocker, Rong Wang, Sönke Zaehle, and Sophie Zechmeister-Boltenstern
Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, https://doi.org/10.5194/gmd-11-3903-2018, 2018
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We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Joshua Benmergui, A. Anthony Bloom, Claudia Arndt, Ritesh Gautam, Daniel Zavala-Araiza, Hartmut Boesch, and Robert J. Parker
Atmos. Chem. Phys., 18, 12257–12267, https://doi.org/10.5194/acp-18-12257-2018, https://doi.org/10.5194/acp-18-12257-2018, 2018
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Analysis of 7 years (2010–2016) of GOSAT methane trends over Canada, the contiguous US, and Mexico suggests that US methane emissions increased by 2.5 ± 1.4 % a−1 over the 7-year period, with contributions from both oil–gas systems and livestock in the Midwest. Mexican emissions show a decrease that can be attributed to a decreasing cattle population. Canadian emissions show year-to-year variability driven by wetland emissions and correlated with wetland areal extent.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-270, https://doi.org/10.5194/bg-2018-270, 2018
Revised manuscript has not been submitted
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This study presents a global estimate of land carbon uptake through photosynthesis. We make use satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and then use the optimized model to estimate photosynthetic carbon uptake. This provides a new tool that can combine measurements and observations in a systematic way and maximise the use of chlorophyll fluorescence to improve our understanding of the land carbon cycle.
Victoria Meyer, Sassan Saatchi, David B. Clark, Michael Keller, Grégoire Vincent, António Ferraz, Fernando Espírito-Santo, Marcus V. N. d'Oliveira, Dahlia Kaki, and Jérôme Chave
Biogeosciences, 15, 3377–3390, https://doi.org/10.5194/bg-15-3377-2018, https://doi.org/10.5194/bg-15-3377-2018, 2018
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This study shows how a simple lidar-derived metric measuring the area covered by large trees (> 27 m) can explain biomass variations across the Neotropics. The importance of this metric is in its relevance to the structural and ecological characteristics of large trees and their unique contribution in determining the biomass of forests. Our results point toward simplified ground data collection and potential algorithms for future space missions focusing on biomass estimation.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Melissa P. Sulprizio, A. Anthony Bloom, Arlyn E. Andrews, and Debra Wunch
Atmos. Chem. Phys., 18, 6483–6491, https://doi.org/10.5194/acp-18-6483-2018, https://doi.org/10.5194/acp-18-6483-2018, 2018
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We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US to estimate methane emissions in that region. Our results suggest that the EPA inventory is regionally unbiased but there are large local biases, suggesting variable emission factors. Our results also suggest that the choice of landcover map is the dominant source of error for wetland emission estimates.
Emily V. Fischer, Liye Zhu, Vivienne H. Payne, John R. Worden, Zhe Jiang, Susan S. Kulawik, Steven Brey, Arsineh Hecobian, Daniel Gombos, Karen Cady-Pereira, and Frank Flocke
Atmos. Chem. Phys., 18, 5639–5653, https://doi.org/10.5194/acp-18-5639-2018, https://doi.org/10.5194/acp-18-5639-2018, 2018
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PAN is an atmospheric reservoir for nitrogen oxide radicals, and it plays a lead role in their redistribution in the troposphere. We analyze new Tropospheric Emission Spectrometer (TES) PAN observations over North America during July 2006 to 2009. We identify smoke-impacted TES PAN retrievals by co-location with NOAA Hazard Mapping System (HMS) smoke plumes. Depending on the year, 15–32 % of cases where elevated PAN is identified in TES observations overlap with smoke plumes.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, and Marko Scholze
Geosci. Model Dev., 11, 1517–1536, https://doi.org/10.5194/gmd-11-1517-2018, https://doi.org/10.5194/gmd-11-1517-2018, 2018
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It is difficult to estimate how much CO2 plants absorb via photosynthesis and even more difficult to model this for the whole globe. Here, we present a framework to combine a new satellite measurement "solar-induced chlorophyll fluorescence" with a global photosynthesis model. We then quantify how this new measurement constrains model uncertainties and find highly effective constraint. These results pave a novel pathway for improving estimates and modelling abilities of photosynthesis globally.
Jean-François Exbrayat, A. Anthony Bloom, Pete Falloon, Akihiko Ito, T. Luke Smallman, and Mathew Williams
Earth Syst. Dynam., 9, 153–165, https://doi.org/10.5194/esd-9-153-2018, https://doi.org/10.5194/esd-9-153-2018, 2018
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We use global observations of current terrestrial net primary productivity (NPP) to constrain the uncertainty in large ensemble 21st century projections of NPP under a "business as usual" scenario using a skill-based multi-model averaging technique. Our results show that this procedure helps greatly reduce the uncertainty in global projections of NPP. We also identify regions where uncertainties in models and observations remain too large to confidently conclude a sign of the change of NPP.
Nicholas C. Parazoo, Charles D. Koven, David M. Lawrence, Vladimir Romanovsky, and Charles E. Miller
The Cryosphere, 12, 123–144, https://doi.org/10.5194/tc-12-123-2018, https://doi.org/10.5194/tc-12-123-2018, 2018
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Carbon models suggest the permafrost carbon feedback (soil carbon emissions from permafrost thaw) acts as a slow, unobservable leak. We investigate if permafrost temperature provides an observable signal to detect feedbacks. We find a slow carbon feedback in warm sub-Arctic permafrost soils, but potentially rapid feedback in cold Arctic permafrost. This is surprising since the cold permafrost region is dominated by tundra and underlain by deep, cold permafrost thought impervious to such changes.
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
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We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gabriel Abramowitz, Martin G. De Kauwe, Bradley Evans, Vanessa Haverd, Longhui Li, Caitlin Moore, Youngryel Ryu, Simon Scheiter, Stanislaus J. Schymanski, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, https://doi.org/10.5194/bg-14-4711-2017, 2017
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This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Efrén López-Blanco, Magnus Lund, Mathew Williams, Mikkel P. Tamstorf, Andreas Westergaard-Nielsen, Jean-François Exbrayat, Birger U. Hansen, and Torben R. Christensen
Biogeosciences, 14, 4467–4483, https://doi.org/10.5194/bg-14-4467-2017, https://doi.org/10.5194/bg-14-4467-2017, 2017
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An improvement in our process-based understanding of CO2 exchanges in the Arctic and their climate sensitivity is critical. With continued warming temperatures and longer growing seasons, tundra systems will likely increase rates of C cycling, although shifts in sink strength could take place, challenging the forecast of upcoming C states. In this context, we investigated the functional responses of C exchange to environmental characteristics across 8 consecutive years in West Greenland.
Darren Slevin, Simon F. B. Tett, Jean-François Exbrayat, A. Anthony Bloom, and Mathew Williams
Geosci. Model Dev., 10, 2651–2670, https://doi.org/10.5194/gmd-10-2651-2017, https://doi.org/10.5194/gmd-10-2651-2017, 2017
A. Anthony Bloom, Kevin W. Bowman, Meemong Lee, Alexander J. Turner, Ronny Schroeder, John R. Worden, Richard Weidner, Kyle C. McDonald, and Daniel J. Jacob
Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, https://doi.org/10.5194/gmd-10-2141-2017, 2017
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Wetland emissions are a principal source of uncertainty in the global atmospheric methane budget due to poor knowledge of wetland processes. We construct a wetland methane emission and uncertainty dataset for use in global atmospheric methane models. Our wetland model ensemble is based on static wetland maps, satellite-derived inundation and carbon cycle models. The ensemble performs favourably against regional flux estimates and atmospheric methane measurements relative to previous studies.
Zhe Jiang, Helen Worden, John R. Worden, Daven K. Henze, Dylan B. A. Jones, Avelino F. Arellano, Emily V. Fischer, Liye Zhu, Kazuyuki Miyazaki, K. Folkert Boersma, and Vivienne H. Payne
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-382, https://doi.org/10.5194/acp-2017-382, 2017
Preprint withdrawn
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We investigated the variation of US tropospheric NO2 in the past decade. We demonstrated significant divergence between the time variation in tropospheric NO2 columns from OMI retrievals and surface measurements. Our analysis suggests limited contributions from local effects such as fossil fuel emissions, lightning, or instrument artifacts, and indicates possible important contributions from long-range transport of Asian emissions that are modulated by ENSO.
Vivienne H. Payne, Emily V. Fischer, John R. Worden, Zhe Jiang, Liye Zhu, Thomas P. Kurosu, and Susan S. Kulawik
Atmos. Chem. Phys., 17, 6341–6351, https://doi.org/10.5194/acp-17-6341-2017, https://doi.org/10.5194/acp-17-6341-2017, 2017
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Peroxyacetyl nitrate (PAN) plays a key role in atmospheric chemistry and long-range transport of pollution. In this paper, we present measurements of PAN from the Tropospheric Emission Spectrometer, an instrument on board the NASA Aura satellite since 2004. We focus on measurements of PAN in tropical regions, where data from ground-based and aircraft campaigns are particularly sparse. We observe temporal changes in PAN associated with changes in fires, convection and emissions.
Zhe Jiang, John R. Worden, Helen Worden, Merritt Deeter, Dylan B. A. Jones, Avelino F. Arellano, and Daven K. Henze
Atmos. Chem. Phys., 17, 4565–4583, https://doi.org/10.5194/acp-17-4565-2017, https://doi.org/10.5194/acp-17-4565-2017, 2017
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We constrain the long-term variation in global CO emissions for 2001–2015. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, unchanged anthropogenic CO emissions from Europe since 2008, and likely a positive trend from India and southeast Asia.
Paul A. Levine, James T. Randerson, Sean C. Swenson, and David M. Lawrence
Hydrol. Earth Syst. Sci., 20, 4837–4856, https://doi.org/10.5194/hess-20-4837-2016, https://doi.org/10.5194/hess-20-4837-2016, 2016
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We demonstrate a new approach to assess the strength of feedbacks resulting from land–atmosphere coupling on decadal timescales. Our approach was tailored to enable evaluation of Earth system models (ESMs) using data from Earth observation satellites that measure terrestrial water storage anomalies and relevant atmospheric variables. Our results are consistent with previous work demonstrating that ESMs may be overestimating the strength of land surface feedbacks compared with observations.
A. Anthony Bloom, Thomas Lauvaux, John Worden, Vineet Yadav, Riley Duren, Stanley P. Sander, and David S. Schimel
Atmos. Chem. Phys., 16, 15199–15218, https://doi.org/10.5194/acp-16-15199-2016, https://doi.org/10.5194/acp-16-15199-2016, 2016
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Understanding terrestrial carbon processes is a major challenge in climate science. We define the satellite system required to understand greenhouse gas biogeochemistry: our study is focused on Amazon wetland CH4 emissions. We find that future geostationary satellites will provide the CH4 measurements required to understand wetland CH4 processes. Low-earth orbit satellites will be unable to resolve wetland CH4 processes due to a low number of cloud-free CH4 measurements over the Amazon basin.
Hilke Oetjen, Vivienne H. Payne, Jessica L. Neu, Susan S. Kulawik, David P. Edwards, Annmarie Eldering, Helen M. Worden, and John R. Worden
Atmos. Chem. Phys., 16, 10229–10239, https://doi.org/10.5194/acp-16-10229-2016, https://doi.org/10.5194/acp-16-10229-2016, 2016
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We developed and tested a strategy for combining TES and IASI free-tropospheric ozone data. A time series of the merged ozone data is presented for regional monthly means over the western US, Europe, and eastern Asia. We show that free-tropospheric ozone over Europe and the western US has remained relatively constant over the past decade but that, contrary to expectations, ozone over Asia in recent years does not continue the rapid rate of increase observed from 2004–2010.
Le Kuai, John R. Worden, King-Fai Li, Glynn C. Hulley, Francesca M. Hopkins, Charles E. Miller, Simon J. Hook, Riley M. Duren, and Andrew D. Aubrey
Atmos. Meas. Tech., 9, 3165–3173, https://doi.org/10.5194/amt-9-3165-2016, https://doi.org/10.5194/amt-9-3165-2016, 2016
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This paper describes the retrieval algorithm to estimate the lower tropospheric methane concentrations using Hyperspectral Thermal Emission Spectrometer (HyTES) airborne measurements. This project aims to map and detect methane plumes from the oil leaking or dairy emission. Our results demonstrate an example of the quantitative retrievals, imaged a big methane plume from storage tanks near Kern River Oil Field. The methane enhancement is well above the uncertainties of the estimates.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
K. E. Clark, A. J. West, R. G. Hilton, G. P. Asner, C. A. Quesada, M. R. Silman, S. S. Saatchi, W. Farfan-Rios, R. E. Martin, A. B. Horwath, K. Halladay, M. New, and Y. Malhi
Earth Surf. Dynam., 4, 47–70, https://doi.org/10.5194/esurf-4-47-2016, https://doi.org/10.5194/esurf-4-47-2016, 2016
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The key findings of this paper are that landslides in the eastern Andes of Peru in the Kosñipata Valley rapidly turn over the landscape in ~1320 years, with a rate of 0.076% yr-1. Additionally, landslides were concentrated at lower elevations, due to an intense storm in 2010 accounting for ~1/4 of the total landslide area over the 25-year remote sensing study. Valley-wide carbon stocks were determined, and we estimate that 26 tC km-2 yr-1 of soil and biomass are stripped by landslides.
E. A. Sproles, S. G. Leibowitz, J. T. Reager, P. J. Wigington Jr, J. S. Famiglietti, and S. D. Patil
Hydrol. Earth Syst. Sci., 19, 3253–3272, https://doi.org/10.5194/hess-19-3253-2015, https://doi.org/10.5194/hess-19-3253-2015, 2015
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The paper demonstrates how data from the Gravity Recovery and Climate Experiment (GRACE) can be used to describe the relationship between water stored at the regional scale and stream flow. Additionally, we employ GRACE as a regional-scale indicator to successfully predict stream flow later in the water year. Our work focuses on the Columbia River Basin (North America), but is widely applicable across the globe, and could prove to be particularly useful in regions with limited hydrological data.
C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton
Geosci. Model Dev., 8, 1899–1918, https://doi.org/10.5194/gmd-8-1899-2015, https://doi.org/10.5194/gmd-8-1899-2015, 2015
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In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient
simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.
L. Rowland, A. Harper, B. O. Christoffersen, D. R. Galbraith, H. M. A. Imbuzeiro, T. L. Powell, C. Doughty, N. M. Levine, Y. Malhi, S. R. Saleska, P. R. Moorcroft, P. Meir, and M. Williams
Geosci. Model Dev., 8, 1097–1110, https://doi.org/10.5194/gmd-8-1097-2015, https://doi.org/10.5194/gmd-8-1097-2015, 2015
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This study evaluates the capability of five vegetation models to simulate the response of forest productivity to changes in temperature and drought, using data collected from an Amazonian forest. This study concludes that model consistencies in the responses of net canopy carbon production to temperature and precipitation change were the result of inconsistently modelled leaf-scale process responses and substantial variation in modelled leaf area responses.
A. A. Bloom and M. Williams
Biogeosciences, 12, 1299–1315, https://doi.org/10.5194/bg-12-1299-2015, https://doi.org/10.5194/bg-12-1299-2015, 2015
D. Slevin, S. F. B. Tett, and M. Williams
Geosci. Model Dev., 8, 295–316, https://doi.org/10.5194/gmd-8-295-2015, https://doi.org/10.5194/gmd-8-295-2015, 2015
M. Réjou-Méchain, H. C. Muller-Landau, M. Detto, S. C. Thomas, T. Le Toan, S. S. Saatchi, J. S. Barreto-Silva, N. A. Bourg, S. Bunyavejchewin, N. Butt, W. Y. Brockelman, M. Cao, D. Cárdenas, J.-M. Chiang, G. B. Chuyong, K. Clay, R. Condit, H. S. Dattaraja, S. J. Davies, A. Duque, S. Esufali, C. Ewango, R. H. S. Fernando, C. D. Fletcher, I. A. U. N. Gunatilleke, Z. Hao, K. E. Harms, T. B. Hart, B. Hérault, R. W. Howe, S. P. Hubbell, D. J. Johnson, D. Kenfack, A. J. Larson, L. Lin, Y. Lin, J. A. Lutz, J.-R. Makana, Y. Malhi, T. R. Marthews, R. W. McEwan, S. M. McMahon, W. J. McShea, R. Muscarella, A. Nathalang, N. S. M. Noor, C. J. Nytch, A. A. Oliveira, R. P. Phillips, N. Pongpattananurak, R. Punchi-Manage, R. Salim, J. Schurman, R. Sukumar, H. S. Suresh, U. Suwanvecho, D. W. Thomas, J. Thompson, M. Uríarte, R. Valencia, A. Vicentini, A. T. Wolf, S. Yap, Z. Yuan, C. E. Zartman, J. K. Zimmerman, and J. Chave
Biogeosciences, 11, 6827–6840, https://doi.org/10.5194/bg-11-6827-2014, https://doi.org/10.5194/bg-11-6827-2014, 2014
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Forest carbon mapping may greatly reduce uncertainties in the global carbon budget. Accuracy of such maps depends however on the quality of field measurements. Using 30 large forest plots, we found large local spatial variability in biomass. When field calibration plots are smaller than the remote sensing pixels, this high local spatial variability results in an underestimation of the variance in biomass.
M. Van Oijen, J. Balkovi, C. Beer, D. R. Cameron, P. Ciais, W. Cramer, T. Kato, M. Kuhnert, R. Martin, R. Myneni, A. Rammig, S. Rolinski, J.-F. Soussana, K. Thonicke, M. Van der Velde, and L. Xu
Biogeosciences, 11, 6357–6375, https://doi.org/10.5194/bg-11-6357-2014, https://doi.org/10.5194/bg-11-6357-2014, 2014
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We use a new risk analysis method, and six vegetation models, to analyse how climate change may alter drought risks in European ecosystems. The conclusions are (1) drought will pose increasing risks to productivity in the Mediterranean area; (2) this is because severe droughts will become more frequent, not because ecosystems will become more vulnerable; (3) future C sequestration will be at risk because carbon gain in primary productivity will be more affected than carbon loss in respiration.
G. B. Bonan, M. Williams, R. A. Fisher, and K. W. Oleson
Geosci. Model Dev., 7, 2193–2222, https://doi.org/10.5194/gmd-7-2193-2014, https://doi.org/10.5194/gmd-7-2193-2014, 2014
R. Q. Thomas and M. Williams
Geosci. Model Dev., 7, 2015–2037, https://doi.org/10.5194/gmd-7-2015-2014, https://doi.org/10.5194/gmd-7-2015-2014, 2014
G. Xenakis and M. Williams
Geosci. Model Dev., 7, 1519–1533, https://doi.org/10.5194/gmd-7-1519-2014, https://doi.org/10.5194/gmd-7-1519-2014, 2014
T. L. Smallman, M. Williams, and J. B. Moncrieff
Biogeosciences, 11, 735–747, https://doi.org/10.5194/bg-11-735-2014, https://doi.org/10.5194/bg-11-735-2014, 2014
D. Wunch, P. O. Wennberg, J. Messerschmidt, N. C. Parazoo, G. C. Toon, N. M. Deutscher, G. Keppel-Aleks, C. M. Roehl, J. T. Randerson, T. Warneke, and J. Notholt
Atmos. Chem. Phys., 13, 9447–9459, https://doi.org/10.5194/acp-13-9447-2013, https://doi.org/10.5194/acp-13-9447-2013, 2013
V. Meyer, S. S. Saatchi, J. Chave, J. W. Dalling, S. Bohlman, G. A. Fricker, C. Robinson, M. Neumann, and S. Hubbell
Biogeosciences, 10, 5421–5438, https://doi.org/10.5194/bg-10-5421-2013, https://doi.org/10.5194/bg-10-5421-2013, 2013
T. L. Smallman, J. B. Moncrieff, and M. Williams
Geosci. Model Dev., 6, 1079–1093, https://doi.org/10.5194/gmd-6-1079-2013, https://doi.org/10.5194/gmd-6-1079-2013, 2013
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Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
Dynamic MJO forecasts using an ensemble subseasonal-to-seasonal forecast system of IAP-CAS model
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
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.
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.
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”.
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.
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.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
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This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
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Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. 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 testbed for climate attribution studies.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
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Short summary
Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Global carbon and water have large uncertainties that are hard to quantify in current regional...
