Articles | Volume 15, issue 5
https://doi.org/10.5194/esd-15-1277-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-15-1277-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Sep 2024
Research article |
| 30 Sep 2024
| 30 Sep 2024
An enhanced Standardized Precipitation–Evapotranspiration Index (SPEI) drought-monitoring method integrating land surface characteristics
Department of Geography, The University of Hong Kong, Hong Kong SAR, China
Institute for Climate and Carbon Neutrality, The University of Hong Kong, Hong Kong SAR, China
Justin Sheffield
School of Geography and Environmental Science, University of Southampton, Southampton, UK
Zhongwang Wei
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
Michael Ek
Joint Numerical Testbed, Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Eric F. Wood
Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
deceased
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Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-292, https://doi.org/10.5194/hess-2024-292, 2024
Preprint under review for HESS
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We developed the first high-resolution, integrated surface water-groundwater hydrologic model of the entire continental China using ParFlow. The model shows good performance of streamflow and water table depth when compared to global data products and observations. It is essential for water resources management and decision making in China within a consistent framework in the changing world. It also has significant implications for similar modeling in other places in the world.
Gaosong Shi, Wenye Sun, Wei Shangguan, Zhongwang Wei, Hua Yuan, Ye Zhang, Hongbin Liang, Lu Li, Xiaolin Sun, Danxi Li, Feini Huang, Qingliang Li, and Yongjiu Dai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-299, https://doi.org/10.5194/essd-2024-299, 2024
Preprint under review for ESSD
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In this study, we developed the second version of China's high-resolution soil information grid using legacy soil samples and advanced machine learning. This version predicts over 20 soil properties at six depths, providing accurate soil variation maps across China. It outperforms previous versions and global products, offering valuable data for hydrological, ecological analyses, and earth system modeling, enhancing understanding of soil roles in environmental processes.
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Jiahao Shi, Hua Yuan, Wanyi Lin, Wenzong Dong, Hongbin Liang, Zhuo Liu, Jianxin Zeng, Haolin Zhang, Nan Wei, Zhongwang Wei, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-77, https://doi.org/10.5194/essd-2024-77, 2024
Revised manuscript accepted for ESSD
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Flux tower data are widely recognized as benchmarking data for land surface models, but insufficient emphasis on and deficiency in site attribute data limits their true value. We collect site-observed vegetation, soil, and topography data from various sources. The final dataset encompasses 90 sites globally with relatively complete site attribute data and high-quality flux validation data. This work has provided more reliable site attribute data, benefiting land surface model development.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
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Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Dominikus Heinzeller, Ligia Bernardet, Grant Firl, Man Zhang, Xia Sun, and Michael Ek
Geosci. Model Dev., 16, 2235–2259, https://doi.org/10.5194/gmd-16-2235-2023, https://doi.org/10.5194/gmd-16-2235-2023, 2023
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The Common Community Physics Package is a collection of physical atmospheric parameterizations for use in Earth system models and a framework that couples the physics to a host model’s dynamical core. A primary goal for this effort is to facilitate research and development of physical parameterizations and physics–dynamics coupling methods while offering capabilities for numerical weather prediction operations, for example in the upcoming implementation of the Global Forecast System (GFS) v17.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 4147–4167, https://doi.org/10.5194/hess-26-4147-2022, https://doi.org/10.5194/hess-26-4147-2022, 2022
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Tracer-aided hydrological models are useful tool to reduce uncertainty of hydrological modeling in cold basins, but there is little guidance on the sampling strategy for isotope analysis, which is important for large mountainous basins. This study evaluated the reliance of the tracer-aided modeling performance on the availability of isotope data in the Yarlung Tsangpo river basin, and provides implications for collecting water isotope data for running tracer-aided hydrological models.
M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1045–1052, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, 2022
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
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Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
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Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Colby K. Fisher, Ming Pan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 24, 293–305, https://doi.org/10.5194/hess-24-293-2020, https://doi.org/10.5194/hess-24-293-2020, 2020
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Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage. In this paper we present a method to derive continuous records of streamflow from a set of in situ gauges. Applying this method to the Ohio River basin, we found that we could reliably generate estimates of streamflow throughout the basin using only a small set of streamflow gauges, which can be useful for global river basins where we do not have good observations.
Hylke E. Beck, Ming Pan, Tirthankar Roy, Graham P. Weedon, Florian Pappenberger, Albert I. J. M. van Dijk, George J. Huffman, Robert F. Adler, and Eric F. Wood
Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, https://doi.org/10.5194/hess-23-207-2019, 2019
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We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the Stage-IV gauge-radar dataset as a reference. The best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for reporting times. Our findings can be used as a guide to choose the most suitable precipitation dataset for a particular application.
Sara Sadri, Eric F. Wood, and Ming Pan
Hydrol. Earth Syst. Sci., 22, 6611–6626, https://doi.org/10.5194/hess-22-6611-2018, https://doi.org/10.5194/hess-22-6611-2018, 2018
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Of particular interest to NASA's SMAP-based agricultural applications is a monitoring product that assesses near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for the meaningful assessment of its indices. This study presents initial insights about using SMAP Level 3 and Level 4 for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS).
Stephen Blenkinsop, Hayley J. Fowler, Renaud Barbero, Steven C. Chan, Selma B. Guerreiro, Elizabeth Kendon, Geert Lenderink, Elizabeth Lewis, Xiao-Feng Li, Seth Westra, Lisa Alexander, Richard P. Allan, Peter Berg, Robert J. H. Dunn, Marie Ekström, Jason P. Evans, Greg Holland, Richard Jones, Erik Kjellström, Albert Klein-Tank, Dennis Lettenmaier, Vimal Mishra, Andreas F. Prein, Justin Sheffield, and Mari R. Tye
Adv. Sci. Res., 15, 117–126, https://doi.org/10.5194/asr-15-117-2018, https://doi.org/10.5194/asr-15-117-2018, 2018
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Measurements of sub-daily (e.g. hourly) rainfall totals are essential if we are to understand short, intense bursts of rainfall that cause flash floods. We might expect the intensity of such events to increase in a warming climate but these are poorly realised in projections of future climate change. The INTENSE project is collating a global dataset of hourly rainfall measurements and linking with new developments in climate models to understand the characteristics and causes of these events.
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
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Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
John Musau, Sopan Patil, Justin Sheffield, and Michael Marshall
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-123, https://doi.org/10.5194/esd-2017-123, 2018
Manuscript not accepted for further review
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Three decades LAI data indicates diverse and often non-stationary vegetation changes in East Africa. Significant increase in vegetation variance is indicated in most of the region which is positively correlated to the variance of climate anomalies. The vegetation resistance to short-term drought and its memory effect are mainly positive and significant with noteworthy variations across landcover types. Further analysis is required to separated human-induced and climate-caused vegetation changes.
Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood
Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, https://doi.org/10.5194/hess-22-241-2018, 2018
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A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
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This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Di Tian, Eric F. Wood, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 1477–1490, https://doi.org/10.5194/hess-21-1477-2017, https://doi.org/10.5194/hess-21-1477-2017, 2017
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This study evaluated dynamic climate model sub-seasonal forecasts for important precipitation and temperature indices over the contiguous United States. The presence of active Madden-Julian Oscillation (MJO) events improved weekly mean precipitation forecast skill over most regions. Sub-seasonal forecast indices calculated from the daily forecast showed higher skill than temporally downscaled forecasts, suggesting the usefulness of the daily forecast for sub-seasonal hydrological forecasting.
Michael Marshall, Michael Norton-Griffiths, Harvey Herr, Richard Lamprey, Justin Sheffield, Tor Vagen, and Joseph Okotto-Okotto
Earth Syst. Dynam., 8, 55–73, https://doi.org/10.5194/esd-8-55-2017, https://doi.org/10.5194/esd-8-55-2017, 2017
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The transition of land from one cover type to another can adversely affect the Earth system. A growing body of research aims to map these transitions in space and time to better understand the impacts. Here we develop a statistical model that is parameterized by socio-ecological geospatial data and extensive aerial/ground surveys to visualize and interpret these transitions on an annual basis for 30 years in Kenya. Future work will use this method to project land suitability across Africa.
John Musau, Sopan Patil, Justin Sheffield, and Michael Marshall
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-502, https://doi.org/10.5194/hess-2016-502, 2016
Manuscript not accepted for further review
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An assessment of vegetation-climate relations over East Africa is presented. LAI trends in Southern Ethiopia through Central Kenya into Central Tanzania show persistent decrease. Precipitation exerts widespread positive forcing on vegetation. North Uganda shows high LAI increase. Positive vegetation feedback on precipitation is dominant while a stronger negative forcing on Tmin is shown. Vegetation-climate interactions show strong spatial dependence. Land cover types influence the interractions.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
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In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
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This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Wolfgang Buermann, Claudie Beaulieu, Bikash Parida, David Medvigy, George J. Collatz, Justin Sheffield, and Jorge L. Sarmiento
Biogeosciences, 13, 1597–1607, https://doi.org/10.5194/bg-13-1597-2016, https://doi.org/10.5194/bg-13-1597-2016, 2016
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Recent analyses of the global carbon budget found a substantial increase in the land sink in the late 1980s whose origin remains unknown. Consistent with this shift, we find that plant growth increased in the late 1980s especially in Eurasia and northern Africa. There, climatic constraints on plant growth have eased possibly due to linked climate modes in the North Atlantic. Better understanding of North Atlantic climate may be essential for more credible projections of the land carbon sink.
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
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The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
S. Sadri, J. Kam, and J. Sheffield
Hydrol. Earth Syst. Sci., 20, 633–649, https://doi.org/10.5194/hess-20-633-2016, https://doi.org/10.5194/hess-20-633-2016, 2016
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Low flows are a critical part of the river flow regime but little is known about how they are changing in response to human influences and climate. We analyzed low flow records across the eastern US and identified sites that were minimally influenced by human activities. We found a general increasing trend in low flows across the northeast and decreasing trend across the southeast that are likely driven by changes in climate. The results have implications for how we manage our water resources.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
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In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
W. Zhan, M. Pan, N. Wanders, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 4275–4291, https://doi.org/10.5194/hess-19-4275-2015, https://doi.org/10.5194/hess-19-4275-2015, 2015
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
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Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
J. Elliott, C. Müller, D. Deryng, J. Chryssanthacopoulos, K. J. Boote, M. Büchner, I. Foster, M. Glotter, J. Heinke, T. Iizumi, R. C. Izaurralde, N. D. Mueller, D. K. Ray, C. Rosenzweig, A. C. Ruane, and J. Sheffield
Geosci. Model Dev., 8, 261–277, https://doi.org/10.5194/gmd-8-261-2015, https://doi.org/10.5194/gmd-8-261-2015, 2015
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We present and describe the Global Gridded Crop Model Intercomparison (GGCMI) project, an ongoing international effort to 1) validate global models of crop productivity, 2) improve models through detailed analysis of processes, and 3) assess the impacts of climate change on agriculture and food security. We present analysis of data inputs for the project, detailed protocols for conducting and evaluating simulation outputs, and example results.
K. Guan, S. P. Good, K. K. Caylor, H. Sato, E. F. Wood, and H. Li
Biogeosciences, 11, 6939–6954, https://doi.org/10.5194/bg-11-6939-2014, https://doi.org/10.5194/bg-11-6939-2014, 2014
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Climate change is expected to modify the way that rainfall arrives, namely the frequency and intensity of rainfall events and rainy season length. Yet, the quantification of the impact of these possible rainfall changes across large biomes is lacking. Our study fills this gap by developing a new modeling framework, applying it to continental Africa. We show that African ecosystems are highly sensitive to these rainfall variabilities, with esp. large sensitivity to changes in rainy season length.
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
S. Manfreda, L. Brocca, T. Moramarco, F. Melone, and J. Sheffield
Hydrol. Earth Syst. Sci., 18, 1199–1212, https://doi.org/10.5194/hess-18-1199-2014, https://doi.org/10.5194/hess-18-1199-2014, 2014
M. Pan and E. F. Wood
Hydrol. Earth Syst. Sci., 17, 4577–4588, https://doi.org/10.5194/hess-17-4577-2013, https://doi.org/10.5194/hess-17-4577-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
S. Shukla, J. Sheffield, E. F. Wood, and D. P. Lettenmaier
Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, https://doi.org/10.5194/hess-17-2781-2013, 2013
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Short summary
Integrating evaporative demand into drought indicators is effective, but the choice of method and the effectiveness of surface features remain undocumented. We evaluate various methods and surface features for predicting soil moisture dynamics. Using minimal ancillary information alongside meteorological and vegetation data, we develop a simple land-cover-based method that improves soil moisture drought predictions, especially in forests, showing promise for better real-time drought forecasting.
Integrating evaporative demand into drought indicators is effective, but the choice of method...
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