Articles | Volume 12, issue 3
https://doi.org/10.5194/essd-12-2209-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-2209-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Sep 2020
Data description paper |
| 15 Sep 2020
| 15 Sep 2020
DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution
Dalei Hao
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
State Key Laboratory of Remote Sensing Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Ghassem R. Asrar
Universities Space Research Association, Columbia, MD 21046, USA
Yelu Zeng
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
Qing Zhu
Earth Science Division, Lawrence Berkeley National Lab, Berkeley, CA 94720, USA
Jianguang Wen
State Key Laboratory of Remote Sensing Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Qing Xiao
State Key Laboratory of Remote Sensing Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
Related authors
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
Short summary
Short summary
We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Lingcheng Li, Gautam Bisht, Dalei Hao, and L. Ruby Leung
Earth Syst. Sci. Data, 16, 2007–2032, https://doi.org/10.5194/essd-16-2007-2024, https://doi.org/10.5194/essd-16-2007-2024, 2024
Short summary
Short summary
This study fills a gap to meet the emerging needs of kilometer-scale Earth system modeling by developing global 1 km land surface parameters for land use, vegetation, soil, and topography. Our demonstration simulations highlight the substantial impacts of these parameters on spatial variability and information loss in water and energy simulations. Using advanced explainable machine learning methods, we identified influential factors driving spatial variability and information loss.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
Short summary
Short summary
We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Dalei Hao, Gautam Bisht, Karl Rittger, Timbo Stillinger, Edward Bair, Yu Gu, and L. Ruby Leung
The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, https://doi.org/10.5194/tc-17-673-2023, 2023
Short summary
Short summary
We comprehensively evaluated the snow simulations in E3SM land model over the western United States in terms of spatial patterns, temporal correlations, interannual variabilities, elevation gradients, and change with forest cover of snow properties and snow phenology. Our study underscores the need for diagnosing model biases and improving the model representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Han Qiu, Dalei Hao, Yelu Zeng, Xuesong Zhang, and Min Chen
Earth Syst. Dynam., 14, 1–16, https://doi.org/10.5194/esd-14-1-2023, https://doi.org/10.5194/esd-14-1-2023, 2023
Short summary
Short summary
The carbon cycling in terrestrial ecosystems is complex. In our analyses, we found that both the global and the northern-high-latitude (NHL) ecosystems will continue to have positive net ecosystem production (NEP) in the next few decades under four global change scenarios but with large uncertainties. NHL ecosystems will experience faster climate warming but steadily contribute a small fraction of the global NEP. However, the relative uncertainty of NHL NEP is much larger than the global values.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
Short summary
Short summary
Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Meng Huang, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung
Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, https://doi.org/10.5194/gmd-15-6371-2022, 2022
Short summary
Short summary
The land surface in one grid cell may be diverse in character. This study uses an explicit way to account for that subgrid diversity in a state-of-the-art Earth system model (ESM) and explores its implications for the overlying atmosphere. We find that the shallow clouds are increased significantly with the land surface diversity. Our work highlights the importance of accurately representing the land surface and its interaction with the atmosphere in next-generation ESMs.
Dalei Hao, Gautam Bisht, Yu Gu, Wei-Liang Lee, Kuo-Nan Liou, and L. Ruby Leung
Geosci. Model Dev., 14, 6273–6289, https://doi.org/10.5194/gmd-14-6273-2021, https://doi.org/10.5194/gmd-14-6273-2021, 2021
Short summary
Short summary
Topography exerts significant influence on the incoming solar radiation at the land surface. This study incorporated a well-validated sub-grid topographic parameterization in E3SM land model (ELM) version 1.0. The results demonstrate that sub-grid topography has non-negligible effects on surface energy budget, snow cover, and surface temperature over the Tibetan Plateau and that the ELM simulations are sensitive to season, elevation, and spatial scale.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Ashley Brereton, Zelalem Mekonnen, Bhavna Arora, William Riley, Kunxiaojia Yuan, Yi Xu, Yu Zhang, Qing Zhu, Tyler Anthony, and Adina Paytan
EGUsphere, https://doi.org/10.5194/egusphere-2025-361, https://doi.org/10.5194/egusphere-2025-361, 2025
Short summary
Short summary
Wetlands absorb carbon dioxide (CO2), helping slow climate change, but they also release methane, a potent warming gas. We developed a collection of AI-based models to estimate magnitudes of CO2 and methane exchanged between the land and the atmosphere, for wetlands on a regional scale. This approach helps to inform land-use planning, restoration, and greenhouse gas accounting, while also creating a foundation for future advancements in prediction accuracy.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
Short summary
Short summary
We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
Short summary
Short summary
This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
Short summary
Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Lingcheng Li, Gautam Bisht, Dalei Hao, and L. Ruby Leung
Earth Syst. Sci. Data, 16, 2007–2032, https://doi.org/10.5194/essd-16-2007-2024, https://doi.org/10.5194/essd-16-2007-2024, 2024
Short summary
Short summary
This study fills a gap to meet the emerging needs of kilometer-scale Earth system modeling by developing global 1 km land surface parameters for land use, vegetation, soil, and topography. Our demonstration simulations highlight the substantial impacts of these parameters on spatial variability and information loss in water and energy simulations. Using advanced explainable machine learning methods, we identified influential factors driving spatial variability and information loss.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
Short summary
Short summary
We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Zhiqiang Liu, Ning Zeng, Yun Liu, Eugenia Kalnay, Ghassem Asrar, Qixiang Cai, and Pengfei Han
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-15, https://doi.org/10.5194/gmd-2023-15, 2023
Revised manuscript not accepted
Short summary
Short summary
We introduced a novel algorithm that assimilates a better a priori knowledge to improve the estimation of global surface carbon flux. The algorithm aims at separating the first-order systematic biases in the a priori "bottom-up" flux estimations out of the inversion framework from a comprehensive data assimilation perspective.
Dalei Hao, Gautam Bisht, Karl Rittger, Timbo Stillinger, Edward Bair, Yu Gu, and L. Ruby Leung
The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, https://doi.org/10.5194/tc-17-673-2023, 2023
Short summary
Short summary
We comprehensively evaluated the snow simulations in E3SM land model over the western United States in terms of spatial patterns, temporal correlations, interannual variabilities, elevation gradients, and change with forest cover of snow properties and snow phenology. Our study underscores the need for diagnosing model biases and improving the model representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
Short summary
Short summary
We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Han Qiu, Dalei Hao, Yelu Zeng, Xuesong Zhang, and Min Chen
Earth Syst. Dynam., 14, 1–16, https://doi.org/10.5194/esd-14-1-2023, https://doi.org/10.5194/esd-14-1-2023, 2023
Short summary
Short summary
The carbon cycling in terrestrial ecosystems is complex. In our analyses, we found that both the global and the northern-high-latitude (NHL) ecosystems will continue to have positive net ecosystem production (NEP) in the next few decades under four global change scenarios but with large uncertainties. NHL ecosystems will experience faster climate warming but steadily contribute a small fraction of the global NEP. However, the relative uncertainty of NHL NEP is much larger than the global values.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
Short summary
Short summary
Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Rongqi Tang, Xiaodan Wu, Jingping Wang, Dujuan Ma, Qicheng Zeng, Jianguang Wen, and Qing Xiao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-282, https://doi.org/10.5194/amt-2022-282, 2022
Publication in AMT not foreseen
Short summary
Short summary
The vertical distribution characteristics of ozone in China have not been fully understood. This study first identified the vertical sensitivity of AIRS in detecting trends and verified the sensitivity in the near ground using in-situ measurements. Then a consistent ozone datasets dating back to the 1970s was constructed. we found that the spatiotemporal variation of ozone in the stratosphere shows a strong dependence on altitudes, and opposite results can be found at different altitudes.
Meng Huang, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung
Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, https://doi.org/10.5194/gmd-15-6371-2022, 2022
Short summary
Short summary
The land surface in one grid cell may be diverse in character. This study uses an explicit way to account for that subgrid diversity in a state-of-the-art Earth system model (ESM) and explores its implications for the overlying atmosphere. We find that the shallow clouds are increased significantly with the land surface diversity. Our work highlights the importance of accurately representing the land surface and its interaction with the atmosphere in next-generation ESMs.
Zhiqiang Liu, Ning Zeng, Yun Liu, Eugenia Kalnay, Ghassem Asrar, Bo Wu, Qixiang Cai, Di Liu, and Pengfei Han
Geosci. Model Dev., 15, 5511–5528, https://doi.org/10.5194/gmd-15-5511-2022, https://doi.org/10.5194/gmd-15-5511-2022, 2022
Short summary
Short summary
We described the application of a constrained ensemble Kalman filter (CEnKF) in a joint CO2 and surface carbon fluxes estimation study. By assimilating the pseudo-surface and OCO-2 observations, the annual global flux estimation is significantly biased without mass conservation. With the additional CEnKF process, the CO2 mass is strictly constrained, and the estimation of annual fluxes is significantly improved.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
Short summary
Short summary
Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
Short summary
Short summary
We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
Tao Zhang, Yuyu Zhou, Zhengyuan Zhu, Xiaoma Li, and Ghassem R. Asrar
Earth Syst. Sci. Data, 14, 651–664, https://doi.org/10.5194/essd-14-651-2022, https://doi.org/10.5194/essd-14-651-2022, 2022
Short summary
Short summary
We generated a global seamless 1 km daily (mid-daytime and mid-nighttime) land surface temperature (LST) dataset (2003–2020) using MODIS LST products by proposing a spatiotemporal gap-filling framework. The average root mean squared errors of the gap-filled LST are 1.88°C and 1.33°C, respectively, in mid-daytime and mid-nighttime. The global seamless LST dataset is unique and of great use in studies on urban systems, climate research and modeling, and terrestrial ecosystem studies.
Nirasindhu Desinayak, Anup K. Prasad, Hesham El-Askary, Menas Kafatos, and Ghassem R. Asrar
Ann. Geophys., 40, 67–82, https://doi.org/10.5194/angeo-40-67-2022, https://doi.org/10.5194/angeo-40-67-2022, 2022
Short summary
Short summary
The study presents long-term altitudinal changes and variability (spatial and temporal; during 2000–2017) in the coverage of snow and glaciers in one of the world’s largest mountainous regions, i.e., the Hindu Kush Himalayan (HKH) region. The western zone and high-altitude regions (above 6000 m) show no significant decline in snow cover, whereas the lower-altitude regions (< 6000 m) show a variable but statistically significant decline in snow cover in the central and eastern zones (5 %–15 %).
Jing Tao, Qing Zhu, William J. Riley, and Rebecca B. Neumann
The Cryosphere, 15, 5281–5307, https://doi.org/10.5194/tc-15-5281-2021, https://doi.org/10.5194/tc-15-5281-2021, 2021
Short summary
Short summary
We improved the DOE's E3SM land model (ELMv1-ECA) simulations of soil temperature, zero-curtain period durations, cold-season CH4, and CO2 emissions at several Alaskan Arctic tundra sites. We demonstrated that simulated CH4 emissions during zero-curtain periods accounted for more than 50 % of total emissions throughout the entire cold season (Sep to May). We also found that cold-season CO2 emissions largely offset warm-season net uptake currently and showed increasing trends from 1950 to 2017.
Dalei Hao, Gautam Bisht, Yu Gu, Wei-Liang Lee, Kuo-Nan Liou, and L. Ruby Leung
Geosci. Model Dev., 14, 6273–6289, https://doi.org/10.5194/gmd-14-6273-2021, https://doi.org/10.5194/gmd-14-6273-2021, 2021
Short summary
Short summary
Topography exerts significant influence on the incoming solar radiation at the land surface. This study incorporated a well-validated sub-grid topographic parameterization in E3SM land model (ELM) version 1.0. The results demonstrate that sub-grid topography has non-negligible effects on surface energy budget, snow cover, and surface temperature over the Tibetan Plateau and that the ELM simulations are sensitive to season, elevation, and spatial scale.
Min Chen and Ken Caldeira
Earth Syst. Dynam., 11, 875–883, https://doi.org/10.5194/esd-11-875-2020, https://doi.org/10.5194/esd-11-875-2020, 2020
Short summary
Short summary
We examine the implications of future motivation for humans to migrate by analyzing today’s relationships between climatic factors and population density, with all other factors held constant. Such analyses are unlikely to make accurate predictions but can still be useful for informing discussions about the broad range of incentives that might influence migration decisions. Areas with the highest projected population growth rates tend to be the areas most adversely affected by climate change.
Cited articles
Augustine, J. A., DeLuisi, J. J., and Long, C. N.: SURFRAD – A national
surface radiation budget network for atmospheric research, B. Am. Meteorol. Soc., 81, 2341–2358, 2000.
Boland, J., David, M., and Lauret, P.: Short term solar radiation
forecasting: Island versus continental sites, Energy, 113, 186–192, 2016.
Burt, J. and Smith, B.: Deep space climate observatory: The DSCOVR mission,
2012 IEEE Aerospace Conference, Big Sky, MT, USA, 3–10 March 2012, 1–13, 2012.
Chen, M. and Zhuang, Q.: Evaluating aerosol direct radiative effects on
global terrestrial ecosystem carbon dynamics from 2003 to 2010, Tellus B, 66, 21808, 2014.
Damm, A., Elbers, J., Erler, A., Gioli, B., Hamdi, K., Hutjes, R.,
Kosvancova, M., Meroni, M., Miglietta, F., and Moersch, A.: Remote sensing
of sun-induced fluorescence to improve modeling of diurnal courses of gross
primary production (GPP), Glob. Change Biol., 16, 171–186, 2010.
Driemel, A., Augustine, J., Behrens, K., Colle, S., Cox, C., Cuevas-Agulló, E., Denn, F. M., Duprat, T., Fukuda, M., Grobe, H., Haeffelin, M., Hodges, G., Hyett, N., Ijima, O., Kallis, A., Knap, W., Kustov, V., Long, C. N., Longenecker, D., Lupi, A., Maturilli, M., Mimouni, M., Ntsangwane, L., Ogihara, H., Olano, X., Olefs, M., Omori, M., Passamani, L., Pereira, E. B., Schmithüsen, H., Schumacher, S., Sieger, R., Tamlyn, J., Vogt, R., Vuilleumier, L., Xia, X., Ohmura, A., and König-Langlo, G.: Baseline Surface Radiation Network (BSRN): structure and data description (1992–2017), Earth Syst. Sci. Data, 10, 1491–1501, https://doi.org/10.5194/essd-10-1491-2018, 2018.
Farquhar, G. D. and Roderick, M. L.: Pinatubo, diffuse light, and the
carbon cycle, Science, 299, 1997–1998, 2003.
Feng, F. and Wang, K.: Merging satellite retrievals and reanalyses to
produce global long-term and consistent surface incident solar radiation
datasets, Remote Sensing, 10, 115, https://doi.org/10.3390/rs10010115, 2018.
García, R. D., Cuevas, E., Ramos, R., Cachorro, V. E., Redondas, A., and Moreno-Ruiz, J. A.: Description of the Baseline Surface Radiation Network (BSRN) station at the Izaña Observatory (2009–2017): measurements and quality control/assurance procedures, Geosci. Instrum. Method. Data Syst., 8, 77–96, https://doi.org/10.5194/gi-8-77-2019, 2019.
Gu, L., Baldocchi, D., Verma, S. B., Black, T., Vesala, T., Falge, E. M.,
and Dowty, P. R.: Advantages of diffuse radiation for terrestrial ecosystem
productivity, J. Geophys. Res.-Atmos., 107, ACL 2-1–ACL
2-23, 2002.
Hao, D., Wen, J., Xiao, Q., Wu, S., Lin, X., Dou, B., You, D., and Tang, Y.:
Simulation and analysis of the topographic effects on snow-free albedo over
rugged terrain, Remote Sensing, 10, 278, https://doi.org/10.3390/rs10020278, 2018a.
Hao, D., Wen, J., Xiao, Q., Wu, S., Lin, X., You, D., and Tang, Y.: Impacts
of DEM Geolocation Bias on Downward Surface Shortwave Radiation Estimation
Over Clear-Sky Rugged Terrain: A Case Study in Dayekou Basin, China, IEEE
Geosci. Remote Sens. Lett., 16, 10–14, 2018b.
Hao, D., Asrar, G. R., Zeng, Y., Zhu, Q., Wen, J., Xiao, Q., and Chen, M.:
Estimating hourly land surface downward shortwave and photosynthetically
active radiation from DSCOVR/EPIC observations, Remote Sens. Environ., 232, 111320, https://doi.org/10.1016/j.rse.2019.111320, 2019.
Hao, D., Chen, M., Asrar, G. R., Zeng, Y., Zhu, Q., Wen, J., and Xiao, Q: A
global DSCOVR/EPIC-based hourly/daily shortwave radiation/PAR dataset,
DataHub for Pacific Northwest National Laboratory,
https://doi.org/10.25584/1595069, 2020.
Herman, J., Huang, L., McPeters, R., Ziemke, J., Cede, A., and Blank, K.: Synoptic ozone, cloud reflectivity, and erythemal irradiance from sunrise to sunset for the whole earth as viewed by the DSCOVR spacecraft from the earth–sun Lagrange 1 orbit, Atmos. Meas. Tech., 11, 177–194, https://doi.org/10.5194/amt-11-177-2018, 2018.
Huang, G., Li, Z., Li, X., Liang, S., Yang, K., Wang, D., and Zhang, Y.:
Estimating surface solar irradiance from satellites: Past, present, and
future perspectives, Remote Sens. Environ., 233, 111371, https://doi.org/10.1016/j.rse.2019.111371, 2019.
Kato, S., Rose, F. G., Rutan, D. A., Thorsen, T. J., Loeb, N. G., Doelling,
D. R., Huang, X., Smith, W. L., Su, W., and Ham, S.-H.: Surface irradiances
of edition 4.0 clouds and the earth's radiant energy system (CERES) energy
balanced and filled (EBAF) data product, J. Climate, 31, 4501–4527,
2018.
Khahro, S. F., Tabbassum, K., Talpur, S., Alvi, M. B., Liao, X., and Dong,
L.: Evaluation of solar energy resources by establishing empirical models
for diffuse solar radiation on tilted surface and analysis for optimum tilt
angle for a prospective location in southern region of Sindh, Pakistan,
Int. J. Elec. Power, 64,
1073–1080, 2015.
Khlopenkov, K., Duda, D., Thieman, M., Minnis, P., Su, W., and Bedka, K.:
Development of multi-sensor global cloud and radiance composites for earth
radiation budget monitoring from DSCOVR, Proc. SPIE 10424, Remote Sensing of Clouds and the Atmosphere XXII, 104240K, https://doi.org/10.1117/12.2278645, 2017.
Korany, M., Boraiy, M., Eissa, Y., Aoun, Y., Abdel Wahab, M. M., Alfaro, S. C., Blanc, P., El-Metwally, M., Ghedira, H., Hungershoefer, K., and Wald, L.: A database of multi-year (2004–2010) quality-assured surface solar hourly irradiation measurements for the Egyptian territory, Earth Syst. Sci. Data, 8, 105–113, https://doi.org/10.5194/essd-8-105-2016, 2016.
Letu, H., Yang, K., Nakajima, T. Y., Ishimoto, H., Nagao, T. M., Riedi, J.,
Baran, A. J., Ma, R., Wang, T., and Shang, H.: High-resolution retrieval of
cloud microphysical properties and surface solar radiation using
Himawari-8/AHI next-generation geostationary satellite, Remote Sens. Environ., 239, 111583, https://doi.org/10.1016/j.rse.2019.111583, 2020.
Li, X., Al-Yaari, A., Schwank, M., Fan, L., Frappart, F., Swenson, J., and
Wigneron, J.-P.: Compared performances of SMOS-IC soil moisture and
vegetation optical depth retrievals based on Tau-Omega and Two-Stream
microwave emission models, Remote Sens. Environ., 236, 111502, https://doi.org/10.1016/j.rse.2019.111502, 2020.
Liang, S., Wang, K., Zhang, X., and Wild, M.: Review on estimation of land
surface radiation and energy budgets from ground measurement, remote sensing
and model simulations, IEEE J. Sel. Top. Appl., 3, 225–240, 2010.
Liou, K. N., Gu, Y., Leung, L. R., Lee, W. L., and Fovell, R. G.: A WRF simulation of the impact of 3-D radiative transfer on surface hydrology over the Rocky Mountains and Sierra Nevada, Atmos. Chem. Phys., 13, 11709–11721, https://doi.org/10.5194/acp-13-11709-2013, 2013.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G.,
Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the earth's
radiant energy system (CERES) energy balanced and filled (EBAF)
top-of-atmosphere (TOA) edition-4.0 data product, J. Climate, 31,
895–918, 2018.
Marshak, A., Herman, J., Adam, S., Karin, B., Carn, S., Cede, A.,
Geogdzhayev, I., Huang, D., Huang, L.-K., and Knyazikhin, Y.: Earth
observations from DSCOVR EPIC instrument, B. Am. Meteorol. Soc., 99, 1829–1850, 2018.
Mercado, L. M., Bellouin, N., Sitch, S., Boucher, O., Huntingford, C., Wild,
M., and Cox, P. M.: Impact of changes in diffuse radiation on the global
land carbon sink, Nature, 458, 1014–1017, 2009.
Molina García, V., Sasi, S., Efremenko, D. S., and Loyola, D.:
Improvement of EPIC/DSCOVR Image Registration by Means of Automatic
Coastline Detection, Remote Sensing, 11, 1747, https://doi.org/10.3390/rs11151747, 2019.
Ohmura, A., Dutton, E. G., Forgan, B., Fröhlich, C., Gilgen, H., Hegner,
H., Heimo, A., König-Langlo, G., McArthur, B., and Müller, G.:
Baseline Surface Radiation Network (BSRN/WCRP): New precision radiometry for
climate research, B. Am. Meteorol. Soc., 79,
2115–2136, 1998.
Pinker, R., Zhang, B., and Dutton, E.: Do satellites detect trends in
surface solar radiation?, Science, 308, 850–854, 2005.
Raptis, P., Kazadzis, S., Psiloglou, B., Kouremeti, N., Kosmopoulos, P., and
Kazantzidis, A.: Measurements and model simulations of solar radiation at
tilted planes, towards the maximization of energy capture, Energy, 130,
570–580, 2017.
Roderick, M. L. and Farquhar, G. D.: The cause of decreased pan evaporation
over the past 50 years, Science, 298, 1410–1411, 2002.
Rutan, D., Rose, F., Smith, N., and Charlock, T.: Validation data set for
CERES surface and atmospheric radiation budget (SARB), WCRP/GEWEX
Newsletter, 11, 11–12, 2001.
Rutan, D. A., Kato, S., Doelling, D. R., Rose, F. G., Nguyen, L. T.,
Caldwell, T. E., and Loeb, N. G.: CERES synoptic product: Methodology and
validation of surface radiant flux, J. Atmos. Ocean.
Tech., 32, 1121–1143, 2015.
Ryu, Y., Jiang, C., Kobayashi, H., and Detto, M.: MODIS-derived global land
products of shortwave radiation and diffuse and total photosynthetically
active radiation at 5 km resolution from 2000, Remote Sens. Environ., 204, 812–825, 2018.
Sweerts, B., Pfenninger, S., Yang, S., Folini, D., Van der Zwaan, B., and
Wild, M.: Estimation of losses in solar energy production from air pollution
in China since 1960 using surface radiation data, Nat. Energ., 4, 657–663,
2019.
Urraca, R., Huld, T., Gracia-Amillo, A., Martinez-de-Pison, F. J., Kaspar,
F., and Sanz-Garcia, A.: Evaluation of global horizontal irradiance
estimates from ERA5 and COSMO-REA6 reanalyses using ground and
satellite-based data, Sol. Energ., 164, 339–354, 2018.
Van Heerwaarden, C. C., Vilà-Guerau de Arellano, J., Gounou, A.,
Guichard, F., and Couvreux, F.: Understanding the daily cycle of
evapotranspiration: A method to quantify the influence of forcings and
feedbacks, J. Hydrometeorol., 11, 1405–1422, 2010.
Wang, D., Liang, S., Zhang, Y., Gao, X., Brown, M. G., and Jia, A.: A New
Set of MODIS Land Products (MCD18): Downward Shortwave Radiation and
Photosynthetically Active Radiation, Remote Sensing, 12, 168, https://doi.org/10.3390/rs12010168, 2020.
Wang, H. and Pinker, R.: Shortwave radiative fluxes from MODIS: Model
development and implementation, J. Geophys. Res.-Atmos., 114, D20201, https://doi.org/10.1029/2008JD010442, 2009.
Wang, W., Yin, G., Zhao, W., Wen, F., and Yu, D.: Spatial Downscaling of MSG
Downward Shortwave Radiation Product Under Clear-Sky Condition, IEEE T. Geosci. Remote, 3264–3272, https://doi.org/10.1109/TGRS.2019.2951699, 2019.
Wang, X., Wu, J., Chen, M., Xu, X., Wang, Z., Wang, B., Wang, C., Piao, S.,
Lin, W., and Miao, G.: Field evidences for the positive effects of aerosols
on tree growth, Glob. Change Biol., 24, 4983–4992, 2018.
Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee III, R. B., Smith,
G. L., and Cooper, J. E.: Clouds and the Earth's Radiant Energy System
(CERES): An earth observing system experiment, B. Am. Meteorol. Soc., 77, 853–868, 1996.
Wild, M., Gilgen, H., Roesch, A., Ohmura, A., Long, C. N., Dutton, E. G.,
Forgan, B., Kallis, A., Russak, V., and Tsvetkov, A.: From dimming to
brightening: Decadal changes in solar radiation at Earth's surface, Science,
308, 847–850, 2005.
Wyser, K., O'Hirok, W., and Gautier, C.: A simple method for removing 3-D
radiative effects in satellite retrievals of surface irradiance, Remote Sens. Environ., 94, 335–342, 2005.
Xu, X., Wang, J., Wang, Y., Zeng, J., Torres, O., Yang, Y., Marshak, A.,
Reid, J., and Miller, S.: Passive remote sensing of altitude and optical
depth of dust plumes using the oxygen A and B bands: First results from
EPIC/DSCOVR at Lagrange-1 point, Geophys. Res. Lett., 44,
7544–7554, 2017.
Yang, B., Knyazikhin, Y., Mõttus, M., Rautiainen, M., Stenberg, P., Yan,
L., Chen, C., Yan, K., Choi, S., and Park, T.: Estimation of leaf area index
and its sunlit portion from DSCOVR EPIC data: Theoretical basis, Remote Sens. Environ., 198, 69–84, 2017.
Yang, Y., Meyer, K., Wind, G., Zhou, Y., Marshak, A., Platnick, S., Min, Q., Davis, A. B., Joiner, J., Vasilkov, A., Duda, D., and Su, W.: Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation, Atmos. Meas. Tech., 12, 2019–2031, https://doi.org/10.5194/amt-12-2019-2019, 2019.
Zhang, S., Li, X., She, J., and Peng, X.: Assimilating remote sensing data
into GIS-based all sky solar radiation modeling for mountain terrain, Remote Sens. Environ., 231, 111239, https://doi.org/10.1016/j.rse.2019.111239, 2019.
Zhang, X., Liang, S., Zhou, G., Wu, H., and Zhao, X.: Generating Global LAnd
Surface Satellite incident shortwave radiation and photosynthetically active
radiation products from multiple satellite data, Remote Sens. Environ., 152, 318–332, 2014.
Zhao, L., Lee, X., and Liu, S.: Correcting surface solar radiation of two
data assimilation systems against FLUXNET observations in North America,
J. Geophys. Res.-Atmos., 118, 9552–9564, 2013.
Short summary
We adopted machine-learning models to generate the first global land products of SW–PAR based on DSCOVR/EPIC data. Our products are consistent with ground-based observations, capture the spatiotemporal patterns well and accurately track substantial diurnal, monthly and seasonal variations in SW–PAR. Our products provide a valuable alternative for solar photovoltaic applications and can be used to improve our understanding of the diurnal cycles of terrestrial water, carbon and energy fluxes.
We adopted machine-learning models to generate the first global land products of SW–PAR based on...
Altmetrics
Final-revised paper
Preprint