Articles | Volume 25, issue 3
https://doi.org/10.5194/hess-25-1617-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-1617-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data
Ewan Pinnington
CORRESPONDING AUTHOR
National Centre for Earth Observation, Department of Meteorology, University of Reading, Reading, UK
Javier Amezcua
National Centre for Earth Observation, Department of Meteorology, University of Reading, Reading, UK
Elizabeth Cooper
UK Centre for Ecology and Hydrology, Wallingford, UK
Simon Dadson
UK Centre for Ecology and Hydrology, Wallingford, UK
School of Geography and the Environment, University of Oxford, Oxford, UK
Rich Ellis
UK Centre for Ecology and Hydrology, Wallingford, UK
Jian Peng
Department of Remote Sensing, Helmholtz Centre for Environmental Research – UFZ, Permoserstraße 15, 04318 Leipzig, Germany
Remote Sensing Centre for Earth System Research, Leipzig University, 04103 Leipzig, Germany
Emma Robinson
UK Centre for Ecology and Hydrology, Wallingford, UK
Ross Morrison
UK Centre for Ecology and Hydrology, Wallingford, UK
Simon Osborne
Met Office Field Site, Cardington Airfield, Shortstown, Bedford, UK
Tristan Quaife
National Centre for Earth Observation, Department of Meteorology, University of Reading, Reading, UK
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Elizabeth Cooper, Eleanor Blyth, Hollie Cooper, Rich Ellis, Ewan Pinnington, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 2445–2458, https://doi.org/10.5194/hess-25-2445-2021, https://doi.org/10.5194/hess-25-2445-2021, 2021
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Soil moisture estimates from land surface models are important for forecasting floods, droughts, weather, and climate trends. We show that by combining model estimates of soil moisture with measurements from field-scale, ground-based sensors, we can improve the performance of the land surface model in predicting soil moisture values.
Ewan Pinnington, Tristan Quaife, Amos Lawless, Karina Williams, Tim Arkebauer, and Dave Scoby
Geosci. Model Dev., 13, 55–69, https://doi.org/10.5194/gmd-13-55-2020, https://doi.org/10.5194/gmd-13-55-2020, 2020
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We present LAVENDAR, a mathematical method for combining observations with models of the terrestrial environment. Here we use it to improve estimates of crop growth in the UK Met Office land surface model. However, the method is model agnostic, requires no modification to the underlying code and can be applied to any part of the model. In the example application we improve estimates of maize yield by 74 % by assimilating observations of leaf area, crop height and photosynthesis.
Ewan Pinnington, Tristan Quaife, and Emily Black
Hydrol. Earth Syst. Sci., 22, 2575–2588, https://doi.org/10.5194/hess-22-2575-2018, https://doi.org/10.5194/hess-22-2575-2018, 2018
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This paper combines satellite observations of precipitation and soil moisture to understand what key information they offer to improve land surface model estimates of soil moisture over Ghana. When both observations are combined with the chosen land surface model we reduce the unbiased root-mean-squared error in a 5-year model hindcast by 27 %; this bodes well for the production of improved soil moisture estimates over sub-Saharan Africa where subsistence farming remains prevalent.
Francisco José Cuesta-Valero, Hugo Beltrami, Almudena García-García, Gerhard Krinner, Moritz Langer, Andrew H. MacDougall, Jan Nitzbon, Jian Peng, Karina von Schuckmann, Sonia I. Seneviratne, Wim Thiery, Inne Vanderkelen, and Tonghua Wu
Earth Syst. Dynam., 14, 609–627, https://doi.org/10.5194/esd-14-609-2023, https://doi.org/10.5194/esd-14-609-2023, 2023
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Climate change is caused by the accumulated heat in the Earth system, with the land storing the second largest amount of this extra heat. Here, new estimates of continental heat storage are obtained, including changes in inland-water heat storage and permafrost heat storage in addition to changes in ground heat storage. We also argue that heat gains in all three components should be monitored independently of their magnitude due to heat-dependent processes affecting society and ecosystems.
Samantha Petch, Bo Dong, Tristan Quaife, Robert P. King, and Keith Haines
Hydrol. Earth Syst. Sci., 27, 1723–1744, https://doi.org/10.5194/hess-27-1723-2023, https://doi.org/10.5194/hess-27-1723-2023, 2023
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Gravitational measurements of water storage from GRACE (Gravity Recovery and Climate Experiment) can improve understanding of the water budget. We produce flux estimates over large river catchments based on observations that close the monthly water budget and ensure consistency with GRACE on short and long timescales. We use energy data to provide additional constraints and balance the long-term energy budget. These flux estimates are important for evaluating climate models.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-430, https://doi.org/10.5194/essd-2022-430, 2023
Preprint under review for ESSD
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CHESS-SCAPE is a suite of high-resolution climate projections for the United Kingdom to 2080, derived from UKCP18 and designed to support climate impacts modelling. It contains four realisations each of four different scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), provided with and without bias-correction to historical data. The variables are available at 1 km resolution and daily timestep, with monthly, seasonal and annual means, plus twenty-year mean-monthly timeslices.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jeremy Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
EGUsphere, https://doi.org/10.5194/egusphere-2022-1483, https://doi.org/10.5194/egusphere-2022-1483, 2023
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We investigated the flux of carbon from the atmosphere into the land surface and the ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same amount of change in the global mean near surface temperature. Using this method, we show that the choice of scenario can have a big impact. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
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A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
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.
Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551, https://doi.org/10.5194/bg-19-5521-2022, https://doi.org/10.5194/bg-19-5521-2022, 2022
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Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair Sellar, and Chris Jones
EGUsphere, https://doi.org/10.5194/egusphere-2022-1196, https://doi.org/10.5194/egusphere-2022-1196, 2022
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and setup for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Inter-comparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impacts models and multiple sectors.
Emma L. Robinson, Matthew J. Brown, Alison L. Kay, Rosanna A. Lane, Rhian Chapman, Victoria A. Bell, and Eleanor M. Blyth
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-288, https://doi.org/10.5194/essd-2022-288, 2022
Revised manuscript under review for ESSD
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This work presents two new Penman-Monteith potential evaporation datasets for the UK, calculated with the same methodology applied to historical climate data (Hydro-PE HadUK-Grid) and an ensemble of future climate projections (Hydro-PE UKCP18 RCM). Both include an optional correction for evaporation of rain that lands on the surface of vegetation. The historical data are consistent with existing PE datasets and the future projections include effects of rising atmospheric CO2 on vegetation.
Joshua Chun Kwang Lee, Javier Amezcua, and Ross Noel Bannister
Geosci. Model Dev., 15, 6197–6219, https://doi.org/10.5194/gmd-15-6197-2022, https://doi.org/10.5194/gmd-15-6197-2022, 2022
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In this article, we implement a novel data assimilation method for the ABC–DA system which combines traditional data assimilation approaches in a hybrid approach. We document the technical development and test the hybrid approach in idealised experiments within a tropical framework of the ABC–DA system. Our findings indicate that the hybrid approach outperforms individual traditional approaches. Its potential benefits have been highlighted and should be explored further within this framework.
Shijie Li, Guojie Wang, Chenxia Zhu, Jiao Lu, Waheed Ullah, Daniel Fiifi Tawia Hagan, Giri Kattel, and Jian Peng
Hydrol. Earth Syst. Sci., 26, 3691–3707, https://doi.org/10.5194/hess-26-3691-2022, https://doi.org/10.5194/hess-26-3691-2022, 2022
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We found that the precipitation variability dominantly controls global evapotranspiration (ET) in dry climates, while the net radiation has substantial control over ET in the tropical regions, and vapor pressure deficit (VPD) impacts ET trends in boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the carbon–water–energy cycle.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Chandan Sarangi, TC Chakraborty, Sachchidanand Tripathi, Mithun Krishnan, Ross Morrison, Jonathan Evans, and Lina M. Mercado
Atmos. Chem. Phys., 22, 3615–3629, https://doi.org/10.5194/acp-22-3615-2022, https://doi.org/10.5194/acp-22-3615-2022, 2022
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Transpiration fluxes by vegetation are reduced under heat stress to conserve water. However, in situ observations over northern India show that the strength of the inverse association between transpiration and atmospheric vapor pressure deficit is weakening in the presence of heavy aerosol loading. This finding not only implicates the significant role of aerosols in modifying the evaporative fraction (EF) but also warrants an in-depth analysis of the aerosol–plant–temperature–EF continuum.
Jiao Lu, Guojie Wang, Tiexi Chen, Shijie Li, Daniel Fiifi Tawia Hagan, Giri Kattel, Jian Peng, Tong Jiang, and Buda Su
Earth Syst. Sci. Data, 13, 5879–5898, https://doi.org/10.5194/essd-13-5879-2021, https://doi.org/10.5194/essd-13-5879-2021, 2021
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This study has combined three existing land evaporation (ET) products to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25° to define the global proxy ET with lower uncertainties. The merged product is the best at capturing dynamics over different locations and times among all data sets. The merged product performed well over a range of vegetation cover scenarios and also captured the trend of land evaporation over different areas well.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, Bo Qiu, Jun Ge, Kai Qin, Yong Xue, and Jian Peng
Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, https://doi.org/10.5194/hess-25-4209-2021, 2021
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Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for which a long-term SM product with high quality is urgently needed. In situ observations are generally treated as the true value to systematically evaluate five SM products, including one remote sensing product and four reanalysis data sets during 1981–2013. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
Elizabeth Cooper, Eleanor Blyth, Hollie Cooper, Rich Ellis, Ewan Pinnington, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 2445–2458, https://doi.org/10.5194/hess-25-2445-2021, https://doi.org/10.5194/hess-25-2445-2021, 2021
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Soil moisture estimates from land surface models are important for forecasting floods, droughts, weather, and climate trends. We show that by combining model estimates of soil moisture with measurements from field-scale, ground-based sensors, we can improve the performance of the land surface model in predicting soil moisture values.
Hollie M. Cooper, Emma Bennett, James Blake, Eleanor Blyth, David Boorman, Elizabeth Cooper, Jonathan Evans, Matthew Fry, Alan Jenkins, Ross Morrison, Daniel Rylett, Simon Stanley, Magdalena Szczykulska, Emily Trill, Vasileios Antoniou, Anne Askquith-Ellis, Lucy Ball, Milo Brooks, Michael A. Clarke, Nicholas Cowan, Alexander Cumming, Philip Farrand, Olivia Hitt, William Lord, Peter Scarlett, Oliver Swain, Jenna Thornton, Alan Warwick, and Ben Winterbourn
Earth Syst. Sci. Data, 13, 1737–1757, https://doi.org/10.5194/essd-13-1737-2021, https://doi.org/10.5194/essd-13-1737-2021, 2021
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COSMOS-UK is a UK network of environmental monitoring sites, with a focus on measuring field-scale soil moisture. Each site includes soil and hydrometeorological sensors providing data including air temperature, humidity, net radiation, neutron counts, snow water equivalent, and potential evaporation. These data can provide information for science, industry, and agriculture by improving existing understanding and data products in fields such as water resources, space sciences, and biodiversity.
Simon J. Dadson, Eleanor Blyth, Douglas Clark, Helen Davies, Richard Ellis, Huw Lewis, Toby Marthews, and Ponnambalan Rameshwaran
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-60, https://doi.org/10.5194/hess-2021-60, 2021
Manuscript not accepted for further review
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Flood prediction helps national and regional planning and real-time flood response. In this study we apply and test a new way to make wide area predictions of flooding which can be combined with weather forecasting and climate models to give faster predictions of flooded areas. By simplifying the detailed floodplain topography we can keep track of the fraction of land flooded for hazard mapping purposes. When tested this approach accurately reproduces benchmark datasets for England.
Gemma Coxon, Nans Addor, John P. Bloomfield, Jim Freer, Matt Fry, Jamie Hannaford, Nicholas J. K. Howden, Rosanna Lane, Melinda Lewis, Emma L. Robinson, Thorsten Wagener, and Ross Woods
Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, https://doi.org/10.5194/essd-12-2459-2020, 2020
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We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
Emma L. Robinson and Douglas B. Clark
Hydrol. Earth Syst. Sci., 24, 1763–1779, https://doi.org/10.5194/hess-24-1763-2020, https://doi.org/10.5194/hess-24-1763-2020, 2020
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This study used a water balance approach based on GRACE total water storage to infer the amount of cold-season precipitation in four Arctic river basins. This was used to evaluate four gridded meteorological data sets, which were used as inputs to a land surface model. We found that the cold-season precipitation in these data sets needed to be increased by up to 55 %. Using these higher precipitation inputs improved the model representation of Arctic hydrology, particularly lying snow.
Jian Peng, Simon Dadson, Feyera Hirpa, Ellen Dyer, Thomas Lees, Diego G. Miralles, Sergio M. Vicente-Serrano, and Chris Funk
Earth Syst. Sci. Data, 12, 753–769, https://doi.org/10.5194/essd-12-753-2020, https://doi.org/10.5194/essd-12-753-2020, 2020
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Africa has been severely influenced by intense drought events, which has led to crop failure, food shortages, famine, epidemics and even mass migration. The current study developed a high spatial resolution drought dataset entirely from satellite-based products. The dataset has been comprehensively inter-compared with other drought indicators and may contribute to an improved characterization of drought risk and vulnerability and minimize drought's impact on water and food security in Africa.
Ewan Pinnington, Tristan Quaife, Amos Lawless, Karina Williams, Tim Arkebauer, and Dave Scoby
Geosci. Model Dev., 13, 55–69, https://doi.org/10.5194/gmd-13-55-2020, https://doi.org/10.5194/gmd-13-55-2020, 2020
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We present LAVENDAR, a mathematical method for combining observations with models of the terrestrial environment. Here we use it to improve estimates of crop growth in the UK Met Office land surface model. However, the method is model agnostic, requires no modification to the underlying code and can be applied to any part of the model. In the example application we improve estimates of maize yield by 74 % by assimilating observations of leaf area, crop height and photosynthesis.
Elizabeth S. Cooper, Sarah L. Dance, Javier García-Pintado, Nancy K. Nichols, and Polly J. Smith
Hydrol. Earth Syst. Sci., 23, 2541–2559, https://doi.org/10.5194/hess-23-2541-2019, https://doi.org/10.5194/hess-23-2541-2019, 2019
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Flooding from rivers is a huge and costly problem worldwide. Computer simulations can help to warn people if and when they are likely to be affected by river floodwater, but such predictions are not always accurate or reliable. Information about flood extent from satellites can help to keep these forecasts on track. Here we investigate different ways of using information from satellite images and look at the effect on computer predictions. This will help to develop flood warning systems.
Dagmawi Asfaw, Emily Black, Matthew Brown, Kathryn Jane Nicklin, Frederick Otu-Larbi, Ewan Pinnington, Andrew Challinor, Ross Maidment, and Tristan Quaife
Geosci. Model Dev., 11, 2353–2371, https://doi.org/10.5194/gmd-11-2353-2018, https://doi.org/10.5194/gmd-11-2353-2018, 2018
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TAMSAT-ALERT is a framework for combining observational and forecast information into continually updated assessments of the likelihood of user-defined adverse events like low cumulative rainfall or lower than average crop yield. It is easy to use and flexible to accommodate any impact model that uses meteorological data. The results show that it can be used to monitor the meteorological impact on yield within a growing season and to test the value of routinely issued seasonal forecasts.
Ewan Pinnington, Tristan Quaife, and Emily Black
Hydrol. Earth Syst. Sci., 22, 2575–2588, https://doi.org/10.5194/hess-22-2575-2018, https://doi.org/10.5194/hess-22-2575-2018, 2018
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This paper combines satellite observations of precipitation and soil moisture to understand what key information they offer to improve land surface model estimates of soil moisture over Ghana. When both observations are combined with the chosen land surface model we reduce the unbiased root-mean-squared error in a 5-year model hindcast by 27 %; this bodes well for the production of improved soil moisture estimates over sub-Saharan Africa where subsistence farming remains prevalent.
Eleanor M. Blyth, Alberto Martinez-de la Torre, and Emma L. Robinson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-153, https://doi.org/10.5194/hess-2018-153, 2018
Manuscript not accepted for further review
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In a warming climate, the water budget of the land is subject to varying forces such as increasing evaporative demand, mainly through the increased temperature, and changes to the precipitation, which might go up or down. Using a verified, physically based model over with 55 years, an analysis of the water budget demonstrates that Great Britain is getting warmer and wetter. We demonstrated that amount of water captured on the trees has an impact on the overall trend.
Robin J. Hogan, Tristan Quaife, and Renato Braghiere
Geosci. Model Dev., 11, 339–350, https://doi.org/10.5194/gmd-11-339-2018, https://doi.org/10.5194/gmd-11-339-2018, 2018
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This paper describes a fast new method for calculating how much sunlight is absorbed and reflected by forests and other types of vegetation, rigorously taking account of the complex 3-D structure. Careful evaluation shows it to perform well even in difficult scenes with snow on the ground. The method is suitable for use within the computer models used to make weather and climate forecasts, where it has the potential to improve predictions of near-surface temperature and photosynthesis rates.
Karina Williams, Jemma Gornall, Anna Harper, Andy Wiltshire, Debbie Hemming, Tristan Quaife, Tim Arkebauer, and David Scoby
Geosci. Model Dev., 10, 1291–1320, https://doi.org/10.5194/gmd-10-1291-2017, https://doi.org/10.5194/gmd-10-1291-2017, 2017
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This study looks in detail at how well the crop model within the Joint UK Land Environment Simulator (JULES), a community land-surface model, is able to simulate irrigated maize in Nebraska. We use the results to point to future priorities for model development and describe how our methodology can be adapted to set up model runs for other sites and crop varieties.
Emma L. Robinson, Eleanor M. Blyth, Douglas B. Clark, Jon Finch, and Alison C. Rudd
Hydrol. Earth Syst. Sci., 21, 1189–1224, https://doi.org/10.5194/hess-21-1189-2017, https://doi.org/10.5194/hess-21-1189-2017, 2017
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We present a dataset of daily meteorological variables at 1 km resolution over Great Britain (1961–2012), calculated by spatially downscaling coarser resolution datasets, adjusting for local topography, along with derived potential evapotranspiration (PET). A positive trend in PET was identified and attributed to trends in the meteorology. The trend in PET is particularly driven by decreasing relative humidity and increasing shortwave radiation in the spring.
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).
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
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The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
Alexander Loew, Jian Peng, and Michael Borsche
Geosci. Model Dev., 9, 2499–2532, https://doi.org/10.5194/gmd-9-2499-2016, https://doi.org/10.5194/gmd-9-2499-2016, 2016
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Surface water and energy fluxes are essential components of the Earth system. The present paper introduces a new framework for the estimation of surface energy and water fluxes at the land surface, which allows for temporally and spatially high resolved flux estimates at the global scale. The framework maximizes the usage of existing long-term satellite data records. Overall the results indicate very good agreement with in situ observations when compared against 49 FLUXNET stations worldwide.
J. Peng, J. Niesel, and A. Loew
Hydrol. Earth Syst. Sci., 19, 4765–4782, https://doi.org/10.5194/hess-19-4765-2015, https://doi.org/10.5194/hess-19-4765-2015, 2015
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This paper gives a comprehensive evaluation of a simple newly developed downscaling scheme using in situ measurements from REMEDHUS network, a first cross-comparison of the performance of the downscaled soil moisture from MODIS and MSG SEVIRI, an evaluation of the performance of the downscaled soil moisture at different spatial resolutions, and an exploration of the influence of LST, vegetation index, terrain, clouds, and land cover heterogeneity on the performance of VTCI.
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
A. Loew, P. M. van Bodegom, J.-L. Widlowski, J. Otto, T. Quaife, B. Pinty, and T. Raddatz
Biogeosciences, 11, 1873–1897, https://doi.org/10.5194/bg-11-1873-2014, https://doi.org/10.5194/bg-11-1873-2014, 2014
J. Peng, M. Borsche, Y. Liu, and A. Loew
Hydrol. Earth Syst. Sci., 17, 3913–3919, https://doi.org/10.5194/hess-17-3913-2013, https://doi.org/10.5194/hess-17-3913-2013, 2013
R. Morrison, A. M. J. Cumming, H. E. Taft, J. Kaduk, S. E. Page, D. L. Jones, R. J. Harding, and H. Balzter
Biogeosciences Discuss., https://doi.org/10.5194/bgd-10-4193-2013, https://doi.org/10.5194/bgd-10-4193-2013, 2013
Preprint withdrawn
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US
Hybrid forecasting: blending climate predictions with AI models
Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin
Local moisture recycling across the globe
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
Spatial distribution of oceanic moisture contributions to precipitation over the Tibetan Plateau
Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France
Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia
Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 °C warmer worlds – how anthropogenic aerosols change the story
Pan evaporation is increased by submerged macrophytes
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
Characterizing basin-scale precipitation gradients in the Third Pole region using a high-resolution atmospheric simulation-based dataset
A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change
A principal component based strategy for regionalisation of precipitation intensity-duration-frequency (IDF) statistics
Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing
Hydrological concept formation inside long short-term memory (LSTM) networks
A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China
Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations
On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe
Regional, multi-decadal analysis on the Loire River basin reveals that stream temperature increases faster than air temperature
Investigating the response of leaf area index to droughts in southern African vegetation using observations and model simulations
Recent decrease in summer precipitation over the Iberian Peninsula closely links to reduction in local moisture recycling
Exploring the possible role of satellite-based rainfall data in estimating inter- and intra-annual global rainfall erosivity
Critical transitions in the hydrological system: early-warning signals and network analysis
Testing a maximum evaporation theory over saturated land: implications for potential evaporation estimation
The role of morphology in the spatial distribution of short-duration rainfall extremes in Italy
Impact of correcting sub-daily climate model biases for hydrological studies
The Mesoamerican mid-summer drought: the impact of its definition on occurrences and recent changes
Reconstructing climate trends adds skills to seasonal reference crop evapotranspiration forecasting
Influence of initial soil moisture in a regional climate model study over West Africa – Part 1: Impact on the climate mean
Influence of initial soil moisture in a regional climate model study over West Africa – Part 2: Impact on the climate extremes
Compound flood impact forecasting: integrating fluvial and flash flood impact assessments into a unified system
Ensemble streamflow forecasting over a cascade reservoir catchment with integrated hydrometeorological modeling and machine learning
Machine-learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany
Extreme precipitation events in the Mediterranean area: contrasting two different models for moisture source identification
Flexible and consistent quantile estimation for intensity–duration–frequency curves
Evaluation of Asian summer precipitation in different configurations of a high-resolution general circulation model in a range of decision-relevant spatial scales
Rainfall-induced shallow landslides and soil wetness: comparison of physically based and probabilistic predictions
Land use and climate change effects on water yield from East African forested water towers
Easy-to-use spatial random-forest-based downscaling-calibration method for producing precipitation data with high resolution and high accuracy
Improved parameterization of snow albedo in Noah coupled with Weather Research and Forecasting: applicability to snow estimates for the Tibetan Plateau
A 10 km North American precipitation and land-surface reanalysis based on the GEM atmospheric model
Contribution of moisture sources to precipitation changes in the Three Gorges Reservoir Region
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
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Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Urmin Vegad and Vimal Mishra
Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, https://doi.org/10.5194/hess-26-6361-2022, 2022
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Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We developed a hydrologic modelling-based streamflow prediction considering the influence of reservoirs in India.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
EGUsphere, https://doi.org/10.5194/egusphere-2022-1279, https://doi.org/10.5194/egusphere-2022-1279, 2022
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For the rainfall-runoff simulation from a certain area hydrological models are used, which require precipitation and temperature data as input. Since these are often not available as observations, we tested simulation results from atmospheric models. Two products were tested (ERA5-Land & COSMO-REA6) for Slovenian catchments, both lead to good simulations results. Their usage enables the of rainfall-runoff simulation in unobserved catchments as a requisite for e.g. flood protection measures.
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022, https://doi.org/10.5194/hess-26-6055-2022, 2022
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The interest of this study is to demonstrate that we identify two zones in our study area whose hydroclimatic behaviours are uneven. By investigating relationships between the hydroclimatic conditions in both clusters for past observations with the overall atmospheric functioning, we show that the inequalities are mainly driven by a different control of the atmospheric teleconnection patterns over the area.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
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We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
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Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022, https://doi.org/10.5194/hess-26-4741-2022, 2022
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Due to climate change, it is extremely important to determine evaporation as accurately as possible. In nature, there are sediments and macrophytes in the open waters; thus, one of the aims was to investigate their effect on evaporation. The second aim of this paper was to estimate daily evaporation by using different models, which, according to results, have high priority in the evaporation prediction. Water management can obtain useful information from the results of the current research.
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022, https://doi.org/10.5194/hess-26-4603-2022, 2022
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There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
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Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
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High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-233, https://doi.org/10.5194/hess-2022-233, 2022
Revised manuscript accepted for HESS
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Intensity-Duration-Frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, e.g., for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, Thomas Grünwald, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 26, 3177–3239, https://doi.org/10.5194/hess-26-3177-2022, https://doi.org/10.5194/hess-26-3177-2022, 2022
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In the study we analysed the uncertainties of the meteorological data and model parameterization for evaporation modelling. We have taken a physically based lumped BROOK90 model and applied it in three different frameworks using global, regional and local datasets. Validating the simulations with eddy-covariance data from five stations in Germany, we found that the accuracy model parameterization plays a bigger role than the quality of the meteorological forcing.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
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Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Huajin Lei, Hongyu Zhao, and Tianqi Ao
Hydrol. Earth Syst. Sci., 26, 2969–2995, https://doi.org/10.5194/hess-26-2969-2022, https://doi.org/10.5194/hess-26-2969-2022, 2022
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How to combine multi-source precipitation data effectively is one of the hot topics in hydrometeorological research. This study presents a two-step merging strategy based on machine learning for multi-source precipitation merging over China. The results demonstrate that the proposed method effectively distinguishes the occurrence of precipitation events and reduces the error in precipitation estimation. This method is robust and may be successfully applied to other areas even with scarce data.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 26, 2697–2714, https://doi.org/10.5194/hess-26-2697-2022, https://doi.org/10.5194/hess-26-2697-2022, 2022
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The hydrometeorological skills of two new nowcasting systems for forecasting Mediterranean intense rainfall events and floods are investigated. The results reveal that up to 75 or 90 min of forecast the performance of the nowcasting system blending numerical weather prediction and extrapolation of radar estimation is higher than the numerical weather model. For lead times up to 3 h the skills are equivalent in general. Using these nowcasting systems for flash flood forecasting is also promising.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669, https://doi.org/10.5194/hess-26-2649-2022, https://doi.org/10.5194/hess-26-2649-2022, 2022
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River discharge is strongly influenced by the temporal structure of precipitation. Here, we show how extreme precipitation events that occur a few days or weeks after a previous event have a larger effect on river discharge than events occurring in isolation. Windows of 2 weeks or less between events have the most impact. Similarly, periods of persistent high discharge tend to be associated with the occurrence of several extreme precipitation events in close succession.
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022, https://doi.org/10.5194/hess-26-2583-2022, 2022
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Stream temperature appears to be increasing globally, but its rate remains poorly constrained due to a paucity of long-term data. Using a thermal model, this study provides a large-scale understanding of the evolution of stream temperature over a long period (1963–2019). This research highlights that air temperature and streamflow can exert joint influence on stream temperature trends, and riparian shading in small mountainous streams may mitigate warming in stream temperatures.
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
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To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
Yubo Liu, Monica Garcia, Chi Zhang, and Qiuhong Tang
Hydrol. Earth Syst. Sci., 26, 1925–1936, https://doi.org/10.5194/hess-26-1925-2022, https://doi.org/10.5194/hess-26-1925-2022, 2022
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Our findings indicate that the reduction in contribution to the Iberian Peninsula (IP) summer precipitation is mainly concentrated in the IP and its neighboring grids. Compared with 1980–1997, both local recycling and external moisture were reduced during 1998–2019. The reduction in local recycling in the IP closely links to the disappearance of the wet years and the decreasing contribution in the dry years.
Nejc Bezak, Pasquale Borrelli, and Panos Panagos
Hydrol. Earth Syst. Sci., 26, 1907–1924, https://doi.org/10.5194/hess-26-1907-2022, https://doi.org/10.5194/hess-26-1907-2022, 2022
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Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of rainfall erosivity was constructed using data with a 30 min time interval. It was shown that the satellite-based precipitation products are an interesting option for estimating rainfall erosivity, especially in regions with limited ground data. However, ground-based high-frequency precipitation measurements are (still) essential for accurate estimates of rainfall erosivity.
Xueli Yang, Zhi-Hua Wang, and Chenghao Wang
Hydrol. Earth Syst. Sci., 26, 1845–1856, https://doi.org/10.5194/hess-26-1845-2022, https://doi.org/10.5194/hess-26-1845-2022, 2022
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In this study, we investigated potentially catastrophic transitions in hydrological processes by identifying the early-warning signals which manifest as a
critical slowing downin complex dynamic systems. We then analyzed the precipitation network of cities in the contiguous United States and found that key network parameters, such as the nodal density and the clustering coefficient, exhibit similar dynamic behaviour, which can serve as novel early-warning signals for the hydrological system.
Zhuoyi Tu, Yuting Yang, and Michael L. Roderick
Hydrol. Earth Syst. Sci., 26, 1745–1754, https://doi.org/10.5194/hess-26-1745-2022, https://doi.org/10.5194/hess-26-1745-2022, 2022
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Here we test a maximum evaporation theory that acknowledges the interdependence between radiation, surface temperature, and evaporation over saturated land. We show that the maximum evaporation approach recovers observed evaporation and surface temperature under non-water-limited conditions across a broad range of bio-climates. The implication is that the maximum evaporation concept can be used to predict potential evaporation that has long been a major difficulty for the hydrological community.
Paola Mazzoglio, Ilaria Butera, Massimiliano Alvioli, and Pierluigi Claps
Hydrol. Earth Syst. Sci., 26, 1659–1672, https://doi.org/10.5194/hess-26-1659-2022, https://doi.org/10.5194/hess-26-1659-2022, 2022
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We have analyzed the spatial dependence of rainfall extremes upon elevation and morphology in Italy. Regression analyses show that previous rainfall–elevation relations at national scale can be substantially improved with new data, both using topography attributes and constraining the analysis within areas stemming from geomorphological zonation. Short-duration mean rainfall depths can then be estimated, all over Italy, using different parameters in each area of the geomorphological subdivision.
Mina Faghih, François Brissette, and Parham Sabeti
Hydrol. Earth Syst. Sci., 26, 1545–1563, https://doi.org/10.5194/hess-26-1545-2022, https://doi.org/10.5194/hess-26-1545-2022, 2022
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The diurnal cycles of precipitation and temperature generated by climate models are biased. This work investigates whether or not impact modellers should correct the diurnal cycle biases prior to conducting hydrological impact studies at the sub-daily scale. The results show that more accurate streamflows are obtained when the diurnal cycles biases are corrected. This is noticeable for smaller catchments, which have a quicker reaction time to changes in precipitation and temperature.
Edwin P. Maurer, Iris T. Stewart, Kenneth Joseph, and Hugo G. Hidalgo
Hydrol. Earth Syst. Sci., 26, 1425–1437, https://doi.org/10.5194/hess-26-1425-2022, https://doi.org/10.5194/hess-26-1425-2022, 2022
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The mid-summer drought (MSD) is common in Mesoamerica. It is a short (weeks-long) period of reduced rainfall near the middle of the rainy season. When it occurs, how long it lasts, and how dry it is all have important implications for smallholder farmers. Studies of changes in MSD characteristics rely on defining characteristics of an MSD. Different definitions affect whether an area would be considered to experience an MSD as well as the changes that have happened in the last 40 years.
Qichun Yang, Quan J. Wang, Andrew W. Western, Wenyan Wu, Yawen Shao, and Kirsti Hakala
Hydrol. Earth Syst. Sci., 26, 941–954, https://doi.org/10.5194/hess-26-941-2022, https://doi.org/10.5194/hess-26-941-2022, 2022
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Forecasts of evaporative water loss in the future are highly valuable for water resource management. These forecasts are often produced using the outputs of climate models. We developed an innovative method to correct errors in these forecasts, particularly the errors caused by deficiencies of climate models in modeling the changing climate. We apply this method to seasonal forecasts of evaporative water loss across Australia and achieve significant improvements in the forecast quality.
Brahima Koné, Arona Diedhiou, Adama Diawara, Sandrine Anquetin, N'datchoh Evelyne Touré, Adama Bamba, and Arsene Toka Kobea
Hydrol. Earth Syst. Sci., 26, 711–730, https://doi.org/10.5194/hess-26-711-2022, https://doi.org/10.5194/hess-26-711-2022, 2022
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The impact of initial soil moisture anomalies can persist for up to 3–4 months and is greater on temperature than on precipitation over West Africa. The strongest homogeneous impact on temperature is located over the Central Sahel, with a peak change of −1.5 and 0.5 °C in the wet and dry experiments, respectively. The strongest impact on precipitation in the wet and dry experiments is found over the West and Central Sahel, with a peak change of about 40 % and −8 %, respectively.
Brahima Koné, Arona Diedhiou, Adama Diawara, Sandrine Anquetin, N'datchoh Evelyne Touré, Adama Bamba, and Arsene Toka Kobea
Hydrol. Earth Syst. Sci., 26, 731–754, https://doi.org/10.5194/hess-26-731-2022, https://doi.org/10.5194/hess-26-731-2022, 2022
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The impact of initial soil moisture is more significant on temperature extremes than on precipitation extremes. A stronger impact is found on maximum temperature than on minimum temperature. The impact on extreme precipitation indices is homogeneous, especially over the Central Sahel, and dry (wet) experiments tend to decrease (increase) the number of precipitation extreme events but not their intensity.
Josias Láng-Ritter, Marc Berenguer, Francesco Dottori, Milan Kalas, and Daniel Sempere-Torres
Hydrol. Earth Syst. Sci., 26, 689–709, https://doi.org/10.5194/hess-26-689-2022, https://doi.org/10.5194/hess-26-689-2022, 2022
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During flood events, emergency managers such as civil protection authorities rely on flood forecasts to make informed decisions. In the current practice, they monitor several separate forecasts, each one of them covering a different type of flooding. This can be time-consuming and confusing, ultimately compromising the effectiveness of the emergency response. This work illustrates how the automatic combination of flood type-specific impact forecasts can improve decision support systems.
Junjiang Liu, Xing Yuan, Junhan Zeng, Yang Jiao, Yong Li, Lihua Zhong, and Ling Yao
Hydrol. Earth Syst. Sci., 26, 265–278, https://doi.org/10.5194/hess-26-265-2022, https://doi.org/10.5194/hess-26-265-2022, 2022
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Hourly streamflow ensemble forecasts with the CSSPv2 land surface model and ECMWF meteorological forecasts reduce both the probabilistic and deterministic forecast error compared with the ensemble streamflow prediction approach during the first week. The deterministic forecast error can be further reduced in the first 72 h when combined with the long short-term memory (LSTM) deep learning method. The forecast skill for LSTM using only historical observations drops sharply after the first 24 h.
Michael Peichl, Stephan Thober, Luis Samaniego, Bernd Hansjürgens, and Andreas Marx
Hydrol. Earth Syst. Sci., 25, 6523–6545, https://doi.org/10.5194/hess-25-6523-2021, https://doi.org/10.5194/hess-25-6523-2021, 2021
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Using a statistical model that can also take complex systems into account, the most important factors affecting wheat yield in Germany are determined. Different spatial damage potentials are taken into account. In many parts of Germany, yield losses are caused by too much soil water in spring. Negative heat effects as well as damaging soil drought are identified especially for north-eastern Germany. The model is able to explain years with exceptionally high yields (2014) and losses (2003, 2018).
Sara Cloux, Daniel Garaboa-Paz, Damián Insua-Costa, Gonzalo Miguez-Macho, and Vicente Pérez-Muñuzuri
Hydrol. Earth Syst. Sci., 25, 6465–6477, https://doi.org/10.5194/hess-25-6465-2021, https://doi.org/10.5194/hess-25-6465-2021, 2021
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We examine the performance of a widely used Lagrangian method for moisture tracking by comparing it with a highly accurate Eulerian tool, both operating on the same WRF atmospheric model fields. Although the Lagrangian approach is very useful for a qualitative analysis of moisture sources, it has important limitations in quantifying the contribution of individual sources to precipitation. These drawbacks should be considered by other authors in the future so as to not draw erroneous conclusions.
Felix S. Fauer, Jana Ulrich, Oscar E. Jurado, and Henning W. Rust
Hydrol. Earth Syst. Sci., 25, 6479–6494, https://doi.org/10.5194/hess-25-6479-2021, https://doi.org/10.5194/hess-25-6479-2021, 2021
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Extreme rainfall events are modeled in this study for different timescales. A new parameterization of the dependence between extreme values and their timescale enables our model to estimate extremes on very short (1 min) and long (5 d) timescales simultaneously. We compare different approaches of modeling this dependence and find that our new model improves performance for timescales between 2 h and 2 d without affecting model performance on other timescales.
Mark R. Muetzelfeldt, Reinhard Schiemann, Andrew G. Turner, Nicholas P. Klingaman, Pier Luigi Vidale, and Malcolm J. Roberts
Hydrol. Earth Syst. Sci., 25, 6381–6405, https://doi.org/10.5194/hess-25-6381-2021, https://doi.org/10.5194/hess-25-6381-2021, 2021
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Simulating East Asian Summer Monsoon (EASM) rainfall poses many challenges because of its multi-scale nature. We evaluate three setups of a 14 km global climate model against observations to see if they improve simulated rainfall. We do this over catchment basins of different sizes to estimate how model performance depends on spatial scale. Using explicit convection improves rainfall diurnal cycle, yet more model tuning is needed to improve mean and intensity biases in simulated summer rainfall.
Elena Leonarduzzi, Brian W. McArdell, and Peter Molnar
Hydrol. Earth Syst. Sci., 25, 5937–5950, https://doi.org/10.5194/hess-25-5937-2021, https://doi.org/10.5194/hess-25-5937-2021, 2021
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Landslides are a dangerous natural hazard affecting alpine regions, calling for effective warning systems. Here we consider different approaches for the prediction of rainfall-induced shallow landslides at the regional scale, based on open-access datasets and operational hydrological forecasting systems. We find antecedent wetness useful to improve upon the classical rainfall thresholds and the resolution of the hydrological model used for its estimate to be a critical aspect.
Charles Nduhiu Wamucii, Pieter R. van Oel, Arend Ligtenberg, John Mwangi Gathenya, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 25, 5641–5665, https://doi.org/10.5194/hess-25-5641-2021, https://doi.org/10.5194/hess-25-5641-2021, 2021
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East African water towers (WTs) are under pressure from human influences within and without, but the water yield (WY) is more sensitive to climate changes from within. Land use changes have greater impacts on WY in the surrounding lowlands. The WTs have seen a strong shift towards wetter conditions while, at the same time, the potential evapotranspiration is gradually increasing. The WTs were identified as non-resilient, and future WY may experience more extreme variations.
Chuanfa Chen, Baojian Hu, and Yanyan Li
Hydrol. Earth Syst. Sci., 25, 5667–5682, https://doi.org/10.5194/hess-25-5667-2021, https://doi.org/10.5194/hess-25-5667-2021, 2021
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This study proposes an easy-to-use downscaling-calibration method based on a spatial random forest with the incorporation of high-resolution variables. The proposed method is general, robust, accurate and easy to use as it shows more accurate results than the classical methods in the study area with heterogeneous terrain morphology and precipitation. It can be easily applied to other regions where precipitation data with high resolution and high accuracy are urgently required.
Lian Liu, Yaoming Ma, Massimo Menenti, Rongmingzhu Su, Nan Yao, and Weiqiang Ma
Hydrol. Earth Syst. Sci., 25, 4967–4981, https://doi.org/10.5194/hess-25-4967-2021, https://doi.org/10.5194/hess-25-4967-2021, 2021
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Albedo is a key factor in land surface energy balance, which is difficult to successfully reproduce by models. Here, we select eight snow events on the Tibetan Plateau to evaluate the universal improvements of our improved albedo scheme. The RMSE relative reductions for temperature, albedo, sensible heat flux and snow depth reach 27%, 32%, 13% and 21%, respectively, with remarkable increases in the correlation coefficients. This presents a strong potential of our scheme for modeling snow events.
Nicolas Gasset, Vincent Fortin, Milena Dimitrijevic, Marco Carrera, Bernard Bilodeau, Ryan Muncaster, Étienne Gaborit, Guy Roy, Nedka Pentcheva, Maxim Bulat, Xihong Wang, Radenko Pavlovic, Franck Lespinas, Dikra Khedhaouiria, and Juliane Mai
Hydrol. Earth Syst. Sci., 25, 4917–4945, https://doi.org/10.5194/hess-25-4917-2021, https://doi.org/10.5194/hess-25-4917-2021, 2021
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In this paper, we highlight the importance of including land-data assimilation as well as offline precipitation analysis components in a regional reanalysis system. We also document the performance of the first multidecadal 10 km reanalysis performed with the GEM atmospheric model that can be used for seamless land-surface and hydrological modelling in North America. It is of particular interest for transboundary basins, as existing datasets often show discontinuities at the border.
Ying Li, Chenghao Wang, Hui Peng, Shangbin Xiao, and Denghua Yan
Hydrol. Earth Syst. Sci., 25, 4759–4772, https://doi.org/10.5194/hess-25-4759-2021, https://doi.org/10.5194/hess-25-4759-2021, 2021
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Precipitation change in the Three Gorges Reservoir Region (TGRR) plays a critical role in the operation and regulation of the Three Gorges Dam and the protection of residents and properties. We investigated the long-term contribution of moisture sources to precipitation changes in this region with an atmospheric moisture tracking model. We found that southwestern source regions (especially the southeastern tip of the Tibetan Plateau) are the key regions that control TGRR precipitation changes.
Cited articles
Abbaszadeh, P., Gavahi, K., and Moradkhani, H.: Multivariate remotely sensed
and in-situ data assimilation for enhancing community WRF-Hydro model
forecasting, Adv. Water Resour., 145, 103721,
https://doi.org/10.1016/j.advwatres.2020.103721, 2020. a
Anderson, J. L. and Anderson, S. L.: A Monte Carlo Implementation of the
Nonlinear Filtering Problem to Produce Ensemble Assimilations and Forecasts,
Mon. Weather Rev., 127, 2741–2758,
https://doi.org/10.1175/1520-0493(1999)127<2741:AMCIOT>2.0.CO;2, 1999. a
Asfaw, D., Black, E., Brown, M., Nicklin, K. J., Otu-Larbi, F., Pinnington, E., Challinor, A., Maidment, R., and Quaife, T.: TAMSAT-ALERT v1: a new framework for agricultural decision support, Geosci. Model Dev., 11, 2353–2371, https://doi.org/10.5194/gmd-11-2353-2018, 2018. a
Baatz, R., Bogena, H., Hendricks Franssen, H.-J., Huisman, J., Qu, W.,
Montzka, C., and Vereecken, H.: Calibration of a catchment scale cosmic-ray
probe network: A comparison of three parameterization methods, J.
Hydrol., 516, 231–244,
https://doi.org/10.1016/j.jhydrol.2014.02.026, 2014. a, b
Baatz, R., Hendricks Franssen, H.-J., Han, X., Hoar, T., Bogena, H. R., and Vereecken, H.: Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction, Hydrol. Earth Syst. Sci., 21, 2509–2530, https://doi.org/10.5194/hess-21-2509-2017, 2017. a
Bateni, S. M. and Entekhabi, D.: Relative efficiency of land surface energy
balance components, Water Resour. Res., 48, W04510, https://doi.org/10.1029/2011WR011357, 2012. a
Beljaars, A. C. M., Viterbo, P., Miller, M. J., and Betts, A. K.: The Anomalous
Rainfall over the United States during July 1993: Sensitivity to Land Surface
Parameterization and Soil Moisture Anomalies, Mon. Weather Rev., 124,
362–383, https://doi.org/10.1175/1520-0493(1996)124<0362:TAROTU>2.0.CO;2, 1996. a
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a
Beven, K.: How far can we go in distributed hydrological modelling?, Hydrol. Earth Syst. Sci., 5, 1–12, https://doi.org/10.5194/hess-5-1-2001, 2001. a
Beven, K. and Binley, A.: The future of distributed models: Model calibration
and uncertainty prediction, Hydrol. Process., 6, 279–298,
https://doi.org/10.1002/hyp.3360060305, 1992. a
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects, Mon. Weather Rev., 129, 420–436, https://doi.org/10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2, 2001. a
Bocquet, M. and Sakov, P.: Joint state and parameter estimation with an iterative ensemble Kalman smoother, Nonlin. Processes Geophys., 20, 803–818, https://doi.org/10.5194/npg-20-803-2013, 2013. a
Bogena, H. R., Huisman, J. A., Güntner, A., Hübner, C., Kusche, J., Jonard,
F., Vey, S., and Vereecken, H.: Emerging methods for noninvasive sensing of
soil moisture dynamics from field to catchment scale: a review, WIREs Water,
2, 635–647, https://doi.org/10.1002/wat2.1097, 2015. a
Bormann, N., Bonavita, M., Dragani, R., Eresmaa, R., Matricardi, M., and
McNally, A.: Enhancing the impact of IASI observations through an updated
observation error covariance matrix, ECMWF Technical Memorandum Number 756, ECMWF, https://doi.org/10.21957/gq8j2gjp7, 2015. a
Botto, A., Belluco, E., and Camporese, M.: Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope, Hydrol. Earth Syst. Sci., 22, 4251–4266, https://doi.org/10.5194/hess-22-4251-2018, 2018. a
Chen, F., Crow, W. T., Bindlish, R., Colliander, A., Burgin, M. S., Asanuma,
J., and Aida, K.: Global-scale evaluation of SMAP, SMOS and ASCAT soil
moisture products using triple collocation, Remote Sens. Environ.,
214, 1–13, https://doi.org/10.1016/j.rse.2018.05.008, 2018. a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011. a, b
Clark, P., Roberts, N., Lean, H., Ballard, S. P., and Charlton-Perez, C.:
Convection-permitting models: a step-change in rainfall forecasting,
Meteorol. Appl., 23, 165–181, https://doi.org/10.1002/met.1538, 2016. a
Colliander, A., Jackson, T., Bindlish, R., Chan, S., Das, N., Kim, S., Cosh,
M., Dunbar, R., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A.,
Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D., al
Jassar, H., Lopez-Baeza, E., Martínez-Fernàndez, J.,
Gonzàlez-Zamora, A., Livingston, S., McNairn, H., Pacheco, A., Moghaddam,
M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J.,
Pulliainen, J., Rautiainen, K., Ramos, J., Seyfried, M., Starks, P., Su, Z.,
Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M.,
Walker, J., Wu, X., Monerris, A., O'Neill, P., Entekhabi, D., Njoku, E., and
Yueh, S.: Validation of SMAP surface soil moisture products with core
validation sites, Remote Sens. Environ., 191, 215–231,
https://doi.org/10.1016/j.rse.2017.01.021, 2017. a, b, c
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A Statistical
Exploration of the Relationships of Soil Moisture Characteristics to the
Physical Properties of Soils, Water Resour. Res., 20, 682–690,
https://doi.org/10.1029/WR020i006p00682, 1984. a, b
Courtier, P., Thépaut, J.-N., and Hollingsworth, A.: A strategy for
operational implementation of 4D-Var, using an incremental approach,
Q. J. Roy. Meteor. Soc., 120, 1367–1387,
https://doi.org/10.1002/qj.49712051912, 1994. a
De Lannoy, G. J. M. and Reichle, R. H.: Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model, Hydrol. Earth Syst. Sci., 20, 4895–4911, https://doi.org/10.5194/hess-20-4895-2016, 2016. a
Desilets, D. and Zreda, M.: Footprint diameter for a cosmic-ray soil moisture
probe: Theory and Monte Carlo simulations, Water Resour. Res., 49,
3566–3575, https://doi.org/10.1002/wrcr.20187, 2013. a
Draper, C. S., Reichle, R. H., De Lannoy, G. J. M., and Liu, Q.: Assimilation
of passive and active microwave soil moisture retrievals, Geophys. Res. Lett., 39, L04401, https://doi.org/10.1029/2011GL050655, 2012. a
Duygu, M. B. and Akyürek, Z.: Using Cosmic-Ray Neutron Probes in Validating
Satellite Soil Moisture Products and Land Surface Models, Water, 11, 1362,
https://doi.org/10.3390/w11071362, 2019. a
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow,
W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson,
T. J., Johnson, J., Kimball, J., Piepmeier, J. R., Koster, R. D.,
Martin, N., McDonald, K. C., Moghaddam, M., Moran, S., Reichle, R.,
Shi, J. C., Spencer, M. W., Thurman, S. W., Tsang, L., and Van Zyl,
J.: The Soil Moisture Active Passive (SMAP) Mission, P. IEEE,
98, 704–716, 2010. a, b, c
Evensen, G.: The Ensemble Kalman Filter: theoretical formulation and practical
implementation, Ocean Dynam., 53, 343–367,
https://doi.org/10.1007/s10236-003-0036-9, 2003. a, b
Evensen, G.: Analysis of iterative ensemble smoothers for solving inverse
problems, Computat. Geosci., 22, 885–908,
https://doi.org/10.1007/s10596-018-9731-y, 2018. a
Evans, J. G., Ward, H. C., Blake, J. R., Hewitt, E. J., Morrison, R., Fry, M.,
Ball, L. A., Doughty, L. C., Libre, J. W., Hitt, O. E., Rylett, D., Ellis,
R. J., Warwick, A. C., Brooks, M., Parkes, M. A., Wright, G. M. H., Singer,
A. C., Boorman, D. B., and Jenkins, A.: Soil water content in southern
England derived from a cosmic-ray soil moisture observing system –
COSMOS-UK, Hydrol. Process., 30, 4987–4999, https://doi.org/10.1002/hyp.10929,
2016. a
Fischer, G., Nachtergaele, F., Prieler, S., Van Velthuizen, H., Verelst, L.,
and Wiberg, D.: Global agro-ecological zones assessment for agriculture
(GAEZ 2008), IIASA, Laxenburg, and FAO, Rome, Italy, available at:
http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/
(last access: 28 April 2020), 2008. a, b, c, d, e
Fowler, A. M., Dance, S. L., and Waller, J. A.: On the interaction of
observation and prior error correlations in data assimilation, Q.
J. Roy. Meteor. Soc., 144, 48–62,
https://doi.org/10.1002/qj.3183, 2018. a
Fratini, G. and Mauder, M.: Towards a consistent eddy-covariance processing: an intercomparison of EddyPro and TK3, Atmos. Meas. Tech., 7, 2273–2281, https://doi.org/10.5194/amt-7-2273-2014, 2014. a
Han, X., Franssen, H.-J. H., Montzka, C., and Vereecken, H.: Soil moisture and
soil properties estimation in the Community Land Model with synthetic
brightness temperature observations, Water Resour. Res., 50,
6081–6105, https://doi.org/10.1002/2013WR014586, 2014. a, b, c, d
Hauser, M., Orth, R., and Seneviratne, S. I.: Investigating soil moisture–climate interactions with prescribed soil moisture experiments: an assessment with the Community Earth System Model (version 1.2), Geosci. Model Dev., 10, 1665–1677, https://doi.org/10.5194/gmd-10-1665-2017, 2017. a
Hilton, F., Collard, A., Guidard, V., Randriamampianina, R., and Schwaerz, M.: Assimilation of IASI radiances at European NWP centres, available at:
https://www.ecmwf.int/node/15331 (last access: 29 March 2021), 2009. a
Houtekamer, P. L. and Mitchell, H. L.: Data Assimilation Using an Ensemble
Kalman Filter Technique, Mon. Weather Rev., 126, 796–811,
https://doi.org/10.1175/1520-0493(1998)126<0796:DAUAEK>2.0.CO;2, 1998. a
Howes, K. E., Fowler, A. M., and Lawless, A. S.: Accounting for model error in
strong-constraint 4D-Var data assimilation, Q. J.
Meteor. Soc., 143, 1227–1240, https://doi.org/10.1002/qj.2996, 2017. a
Hunt, B. R., Kostelich, E. J., and Szunyogh, I.: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter, Physica D, 230, 112–126, 2007. a
Kawanishi, T., Sezai, T., Ito, Y., Imaoka, K., Takeshima, T.,
Ishido, Y., Shibata, A., Miura, M., Inahata, H., and Spencer,
R. W.: The Advanced Microwave Scanning Radiometer for the Earth Observing
System (AMSR-E), NASDA's contribution to the EOS for global energy and water
cycle studies, IEEE T. Geosci. Remote, 41,
184–194, https://doi.org/10.1109/TGRS.2002.808331, 2003. a
Köhli, M., Schrön, M., Zreda, M., Schmidt, U., Dietrich, P., and
Zacharias, S.: Footprint characteristics revised for field-scale soil
moisture monitoring with cosmic-ray neutrons, Water Resour. Res., 51,
5772–5790, https://doi.org/10.1002/2015WR017169, 2015. a, b, c
Kolassa, J., Reichle, R., and Draper, C.: Merging active and passive microwave
observations in soil moisture data assimilation, Remote Sens.
Environ., 191, 117–130, 2017. a
Li, C., Lu, H., Yang, K., Han, M., Wright, J., Chen, Y., Yu, L., Xu, S., Huang,
X., and Gong, W.: The Evaluation of SMAP Enhanced Soil Moisture Products
Using High-Resolution Model Simulations and In-Situ Observations on the
Tibetan Plateau, Remote Sens., 10, 535, https://doi.org/10.3390/rs10040535, 2018. a
Lievens, H., Reichle, R. H., Liu, Q., De Lannoy, G. J. M., Dunbar, R. S., Kim,
S. B., Das, N. N., Cosh, M., Walker, J. P., and Wagner, W.: Joint Sentinel-1
and SMAP data assimilation to improve soil moisture estimates, Geophys.
Res. Lett., 44, 6145–6153, https://doi.org/10.1002/2017GL073904, 2017. a
Liu, Q., Reichle, R. H., Bindlish, R., Cosh, M. H., Crow, W. T., de Jeu, R.,
De Lannoy, G. J. M., Huffman, G. J., and Jackson, T. J.: The Contributions of
Precipitation and Soil Moisture Observations to the Skill of Soil Moisture
Estimates in a Land Data Assimilation System, J. Hydrometeorol., 12, 750–765, https://doi.org/10.1175/JHM-D-10-05000.1, 2011. a
Lorenc, A. C. and Rawlins, F.: Why does 4D-Var beat 3D-Var?, Q. J.
Roy. Meteor. Soc., 131, 3247–3257, https://doi.org/10.1256/qj.05.85,
2005. a
Marthews, T. R., Quesada, C. A., Galbraith, D. R., Malhi, Y., Mullins, C. E., Hodnett, M. G., and Dharssi, I.: High-resolution hydraulic parameter maps for surface soils in tropical South America, Geosci. Model Dev., 7, 711–723, https://doi.org/10.5194/gmd-7-711-2014, 2014. a
Martinez-de la Torre, A., Blyth, E., and Robinson, E.: Water, carbon and energy fluxes simulation for Great Britain using the JULES Land Surface Model and the Climate Hydrology and Ecology research Support System, meteorology dataset (1961–2015) [CHESS-land],
https://doi.org/10.5285/c76096d6-45d4-4a69-a310-4c67f8dcf096, 2018. a
Martínez-de la Torre, A., Blyth, E. M., and Weedon, G. P.: Using observed river flow data to improve the hydrological functioning of the JULES land surface model (vn4.3) used for regional coupled modelling in Great Britain (UKC2), Geosci. Model Dev., 12, 765–784, https://doi.org/10.5194/gmd-12-765-2019, 2019. a
Maurer, E. P. and Lettenmaier, D. P.: Potential Effects of Long-Lead Hydrologic Predictability on Missouri River Main-Stem Reservoirs, J. Climate, 17, 174–186, https://doi.org/10.1175/1520-0442(2004)017<0174:PEOLHP>2.0.CO;2, 2004. a
Minamide, M. and Zhang, F.: Adaptive Observation Error Inflation for
Assimilating All-Sky Satellite Radiance, Mon. Weather Rev., 145,
1063–1081, https://doi.org/10.1175/MWR-D-16-0257.1, 2017. a
Mizukami, N., Clark, M. P., Newman, A. J., Wood, A. W., Gutmann, E. D.,
Nijssen, B., Rakovec, O., and Samaniego, L.: Towards seamless large-domain
parameter estimation for hydrologic models, Water Resour. Res., 53,
8020–8040, https://doi.org/10.1002/2017WR020401, 2017. a
Montzka, C., Moradkhani, H., Weihermüller, L., Franssen, H.-J. H., Canty,
M., and Vereecken, H.: Hydraulic parameter estimation by remotely-sensed top
soil moisture observations with the particle filter, J. Hydrol.,
399, 410–421, https://doi.org/10.1016/j.jhydrol.2011.01.020, 2011. a
Montzka, C., Bogena, H. R., Zreda, M., Monerris, A., Morrison, R., Muddu, S.,
and Vereecken, H.: Validation of Spaceborne and Modelled Surface Soil
Moisture Products with Cosmic-Ray Neutron Probes, Remote Sens., 9, 103,
https://doi.org/10.3390/rs9020103, 2017. a
Moradkhani, H., Sorooshian, S., Gupta, H. V., and Houser, P. R.: Dual
state-parameter estimation of hydrological models using ensemble Kalman
filter, Adv. Water Resour., 28, 135–147,
https://doi.org/10.1016/j.advwatres.2004.09.002, 2005. a, b
Morrison, R., Cooper, H., Cumming, A., Evans, C., Thornton, J., Winterbourn,
J., Rylett, D., and Jones, D.: Eddy covariance measurements of carbon
dioxide, energy and water fluxes at a cropland and a grassland on lowland
peat soils, East Anglia, UK, 2016–2019, UK Centre for Ecology and Hydrology data set,
https://doi.org/10.5285/2fe84b80-117a-4b19-a1f5-71bbd1dba9c9, 2020. a
Nearing, G. S., Moran, M. S., Thorp, K. R., Collins, C. D. H., and Slack,
D. C.: Likelihood parameter estimation for calibrating a soil moisture model
using radar bakscatter, Remote Sens. Environ., 114, 2564–2574,
https://doi.org/10.1016/j.rse.2010.05.031, 2010. a, b
Osborne, S. R. and Weedon, G. P.: Observations and Modeling of
Evapotranspiration and Dewfall during the 2018 Meteorological Drought in
Southern England, J. Hydrometeorol., 22, 279–295, https://doi.org/10.1175/JHM-D-20-0148.1, 2021. a
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch, W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.: Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation, Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006. a
Peng, J., Pinnington, E., Robinson, E., Evans, J., Quaife, T., Harris, P., and Blyth, E.: A high-resolution soil moisture dataset from merged model and Earth observation data in Great Britain, Remote Sens. Environ., in review, 2021. a
Pinnington, E.: pyearthsci/lavendar: First release of LaVEnDAR software (Version v1.0.0), Zenodo, https://doi.org/10.5281/zenodo.2654853, 2019. a
Pinnington, E.: LAVENDAR Rose-suite repository, Met-Office trac system, availalbe at: https://code.metoffice.gov.uk/trac/roses-u/browser/b/q/3/5/7/trunk (last access: 29 March 2021), 2020. a
Pinnington, E., Quaife, T., and Black, E.: Impact of remotely sensed soil moisture and precipitation on soil moisture prediction in a data assimilation system with the JULES land surface model, Hydrol. Earth Syst. Sci., 22, 2575–2588, https://doi.org/10.5194/hess-22-2575-2018, 2018. a, b, c
Pinnington, E., Quaife, T., Lawless, A., Williams, K., Arkebauer, T., and Scoby, D.: The Land Variational Ensemble Data Assimilation Framework: LAVENDAR v1.0.0, Geosci. Model Dev., 13, 55–69, https://doi.org/10.5194/gmd-13-55-2020, 2020. a, b, c
Pinnington, E. M., Casella, E., Dance, S. L., Lawless, A. S., Morison, J. I.,
Nichols, N. K., Wilkinson, M., and Quaife, T. L.: Investigating the role of
prior and observation error correlations in improving a model forecast of
forest carbon balance using Four-dimensional Variational data assimilation,
Agr. Forest Meteorol., 228/229, 299–314,
https://doi.org/10.1016/j.agrformet.2016.07.006, 2016. a
Pitman, A. J., Henderson-Sellers, A., Desborough, C. E., Yang, Z. L.,
Abramopoulos, F., Boone, A., Dickinson, R. E., Gedney, N., Koster, R.,
Kowalczyk, E., Lettenmaier, D., Liang, X., Mahfouf, J. F., Noilhan, J.,
Polcher, J., Qu, W., Robock, A., Rosenzweig, C., Schlosser, C. A., Shmakin,
A. B., Smith, J., Suarez, M., Verseghy, D., Wetzel, P., Wood, E., and Xue,
Y.: Key results and implications from phase 1(c) of the Project for
Intercomparison of Land-surface Parametrization Schemes, Clim. Dynam.,
15, 673–684, https://doi.org/10.1007/s003820050309, 1999. a
Reichle, R. H., De Lannoy, G. J. M., Liu, Q., Ardizzone, J. V., Colliander, A., Conaty, A., Crow, W., Jackson, T. J., Jones, L. A., Kimball, J. S., Koster, R. D., Mahanama, S. P., Smith, E. B., Berg, A., Bircher, S., Bosch, D., Caldwell, T. G., Cosh, M., Gonzàlez-Zamora, A., Holifield Collins, C. D., Jensen, K. H., Livingston, S., Lopez-Baeza, E., Martínez-Fernàndez, J., McNairn, H., Moghaddam, M., Pacheco, A., Pellarin, T., Prueger, J., Rowlandson, T., Seyfried, M., Starks, P., Su, Z., Thibeault, M., van der Velde, R., Walker, J., Wu, X., and Zeng, Y.: Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using In Situ Measurements, J. Hydrometeorol., 18, 2621–2645, https://doi.org/10.1175/JHM-D-17-0063.1, 2017. a
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier,
P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grünwald, T.,
Havránková, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila,
A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-M.,
Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G.,
Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of
net ecosystem exchange into assimilation and ecosystem respiration: review
and improved algorithm, Glob. Change Biol., 11, 1424–1439,
https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005. a, b
Reichstein, M., Moffat, A., Wutzler, T., and Sickel, K.: REddyProc: Data
processing and plotting utilities of (half-) hourly eddy-covariance
measurements, R package version 0.6-0/r9, available at: https://cran.r-project.org/web/packages/REddyProc/index.html (last access: 29 March 2021), 2014. a
Ridler, M.-E., Zhang, D., Madsen, H., Kidmose, J., Refsgaard, J. C., and
Jensen, K. H.: Bias-aware data assimilation in integrated hydrological
modelling, Hydrol. Res., 49, 989–1004, https://doi.org/10.2166/nh.2017.117,
2017. a
Robinson, E., Blyth, E., Clark, D., Comyn-Platt, E., Finch, J., and Rudd, A.:
Climate hydrology and ecology research support system meteorology dataset for
Great Britain (1961–2015) [CHESS-met] v1.2,
https://doi.org/10.5285/b745e7b1-626c-4ccc-ac27-56582e77b900, 2017. a
Rosolem, R., Hoar, T., Arellano, A., Anderson, J. L., Shuttleworth, W. J., Zeng, X., and Franz, T. E.: Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale, Hydrol. Earth Syst. Sci., 18, 4363–4379, https://doi.org/10.5194/hess-18-4363-2014, 2014. a
Samaniego, L., Kumar, R., and Attinger, S.: Multiscale parameter
regionalization of a grid-based hydrologic model at the mesoscale, Water
Resour. Res., 46, W05523, https://doi.org/10.1029/2008WR007327, 2010. a
Sawada, Y. and Koike, T.: Simultaneous estimation of both hydrological and
ecological parameters in an ecohydrological model by assimilating microwave
signal, J. Geophys. Res.-Atmos., 119, 8839–8857,
https://doi.org/10.1002/2014JD021536, 2014. a, b
Schaap, M. G., Nemes, A., and van Genuchten, M. T.: Comparison of Models for
Indirect Estimation of Water Retention and Available Water in Surface Soils,
Vadose Zone J., 3, 1455–1463, https://doi.org/10.2136/vzj2004.1455, 2004. a
Shuttleworth, J., Rosolem, R., Zreda, M., and Franz, T.: The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation, Hydrol. Earth Syst. Sci., 17, 3205–3217, https://doi.org/10.5194/hess-17-3205-2013, 2013. a
Stanley, S., Antoniou, V., Ball, L., Bennett, E., Blake, J., Boorman, D.,
Brooks, M., Clarke, M., Cooper, H., Cowan, N., Evans, J., Farrand, P., Fry,
M., Hitt, O., Jenkins, A., Kral, F., Lord, W., Morrison, R., Nash, G.,
Rylett, D., Scarlett, P., Swain, O., Thornton, J., Trill, E., Warwick, A.,
and Winterbourn, J.: Daily and sub-daily hydrometeorological and soil data
(2013–2017) [COSMOS-UK], https://doi.org/10.5285/a6012796-291c-4fd6-a7ef-6f6ed0a6cfa5, 2019. a, b
Stewart, L. M., Dance, S. L., Nichols, N. K., Eyre, J. R., and Cameron, J.:
Estimating interchannel observation-error correlations for IASI radiance data
in the Met Office system†, Q. J. Roy. Meteor.
Soc., 140, 1236–1244, https://doi.org/10.1002/qj.2211, 2014. a
Tapley, B. D., Bettadpur, S., Ries, J. C., Thompson, P. F., and Watkins, M. M.:
GRACE Measurements of Mass Variability in the Earth System, Science, 305,
503–505, https://doi.org/10.1126/science.1099192, 2004. a
Thiemann, M., Trosset, M., Gupta, H., and Sorooshian, S.: Bayesian recursive
parameter estimation for hydrologic models, Water Resour. Res., 37,
2521–2535, https://doi.org/10.1029/2000WR900405, 2001. a
Tifafi, M., Guenet, B., and Hatté, C.: Large Differences in Global and
Regional Total Soil Carbon Stock Estimates Based on SoilGrids, HWSD, and
NCSCD: Intercomparison and Evaluation Based on Field Data From USA, England,
Wales, and France, Global Biogeochem. Cy., 32, 42–56,
https://doi.org/10.1002/2017GB005678, 2018. a
Van Looy, K., Bouma, J., Herbst, M., Koestel, J., Minasny, B., Mishra, U.,
Montzka, C., Nemes, A., Pachepsky, Y. A., Padarian, J., Schaap, M. G., Tóth,
B., Verhoef, A., Vanderborght, J., van der Ploeg, M. J., Weihermüller, L.,
Zacharias, S., Zhang, Y., and Vereecken, H.: Pedotransfer Functions in Earth
System Science: Challenges and Perspectives, Rev. Geophys., 55,
1199–1256, https://doi.org/10.1002/2017RG000581, 2017. a
Vrugt, J. A., Gupta, H. V., Bouten, W., and Sorooshian, S.: A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters, Water Resour. Res., 39, 1201,
https://doi.org/10.1029/2002WR001642, 2003. a
Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S.,
Figa-Saldaña, J., de Rosnay, P., Jann, A., Schneider, S., Komma, J.,
Kubu, G., Brugger, K., Aubrecht, C., Züger, J., Gangkofner, U.,
Kienberger, S., Brocca, L., Wang, Y., Blöschl, G., Eitzinger, J.,
Steinnocher, K., Zeil, P., and Rubel, F.: The ASCAT Soil Moisture Product:
A Review of its Specifications, Validation Results, and Emerging
Applications, Meteorol. Z., 22, 5–33,
https://doi.org/10.1127/0941-2948/2013/0399, 2013. a
Walker, J. P., Willgoose, G. R., and Kalma, J. D.: In situ measurement of soil
moisture: a comparison of techniques, J. Hydrol., 293, 85–99,
https://doi.org/10.1016/j.jhydrol.2004.01.008, 2004. a
Wang, P., Li, J., Li, Z., Lim, A. H. N., Li, J., and Goldberg, M. D.: Impacts
of Observation Errors on Hurricane Forecasts When Assimilating Hyperspectral
Infrared Sounder Radiances in Partially Cloudy Skies, J. Geophys.
Res.-Atmos., 124, 10802–10813, https://doi.org/10.1029/2019JD031029,
2019.
a
Wang, X., Bishop, C. H., and Julier, S. J.: Which Is Better, an Ensemble of Positive–Negative Pairs or a Centered Spherical Simplex Ensemble?, Mon. Weather Rev., 132, 1590–1605, https://doi.org/10.1175/1520-0493(2004)132<1590:WIBAEO>2.0.CO;2, 2004. a
Wösten, J., Lilly, A., Nemes, A., and Le Bas, C.: Development and use of a
database of hydraulic properties of European soils, Geoderma, 90, 169–185, https://doi.org/10.1016/S0016-7061(98)00132-3, 1999. a, b
Yang, K., Zhu, L., Chen, Y., Zhao, L., Qin, J., Lu, H., Tang, W., Han, M.,
Ding, B., and Fang, N.: Land surface model calibration through microwave data
assimilation for improving soil moisture simulations, J. Hydrol.,
533, 266–276, https://doi.org/10.1016/j.jhydrol.2015.12.018, 2016. a, b, c, d
Zhang, R., Kim, S., and Sharma, A.: A comprehensive validation of the SMAP
Enhanced Level-3 Soil Moisture product using ground measurements over varied
climates and landscapes, Remote Sens. Environ., 223, 82–94,
https://doi.org/10.1016/j.rse.2019.01.015, 2019. a, b, c, d
Zheng, D., Li, X., Wang, X., Wang, Z., Wen, J., van der Velde, R., Schwank,
M., and Su, Z.: Sampling depth of L-band radiometer measurements of soil
moisture and freeze-thaw dynamics on the Tibetan Plateau, Remote Sens.
Environ., 226, 16–25, https://doi.org/10.1016/j.rse.2019.03.029,
2019. a
Zreda, M., Desilets, D., Ferré, T. P. A., and Scott, R. L.: Measuring soil
moisture content non-invasively at intermediate spatial scale using
cosmic-ray neutrons, Geophys. Res. Lett., 35, L21402,
https://doi.org/10.1029/2008GL035655, 2008. a, b
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System, Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012. a
Short summary
Land surface models are important tools for translating meteorological forecasts and reanalyses into real-world impacts at the Earth's surface. We show that the hydrological predictions, in particular soil moisture, of these models can be improved by combining them with satellite observations from the NASA SMAP mission to update uncertain parameters. We find a 22 % reduction in error at a network of in situ soil moisture sensors after combining model predictions with satellite observations.
Land surface models are important tools for translating meteorological forecasts and reanalyses...