Articles | Volume 24, issue 8
Research article 27 Aug 2020
Research article | 27 Aug 2020
Data-driven estimates of evapotranspiration and its controls in the Congo Basin
Michael W. Burnett et al.
No articles found.
Yanlan Liu, Nataniel M. Holtzman, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 25, 2399–2417,Short summary
The flow of water through plants varies with species-specific traits. To determine how they vary across the world, we mapped the traits that best allowed a model to match microwave satellite data. We also defined average values across a few clusters of trait behavior. These form a tractable solution for use in large-scale models. Transpiration estimates using these clusters were more accurate than if using plant functional types. We expect our maps to improve transpiration forecasts.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754,Short summary
Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Andrew F. Feldman, Daniel J. Short Gianotti, Alexandra G. Konings, Pierre Gentine, and Dara Entekhabi
Biogeosciences, 18, 831–847,Short summary
We quantify global plant water uptake durations after rainfall using satellite-based plant water content measurements. In wetter regions, plant water uptake occurs within a day due to rapid coupling between soil and plant water content. Drylands show multi-day plant water uptake after rain pulses, providing widespread evidence for slow rehydration responses and pulse-driven growth responses. Our results suggest that drylands are sensitive to projected shifts in rainfall intensity and frequency.
Nataniel M. Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, and Alexandra G. Konings
Biogeosciences, 18, 739–753,Short summary
Microwave radiation coming from Earth's land surface is affected by both soil moisture and the water in plants that cover the soil. We measured such radiation with a sensor elevated above a forest canopy while repeatedly measuring the amount of water stored in trees at the same location. Changes in the microwave signal over time were closely related to tree water storage changes. Satellites with similar sensors could thus be used to monitor how trees in an entire region respond to drought.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422,Short summary
We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Alexandra G. Konings, A. Anthony Bloom, Junjie Liu, Nicholas C. Parazoo, David S. Schimel, and Kevin W. Bowman
Biogeosciences, 16, 2269–2284,Short summary
We estimate heterotrophic respiration (Rh) – the respiration from microbes in the soil – using satellite estimates of the net carbon flux and other quantities. Rh is an important carbon flux but is rarely studied by itself. Our method is the first to estimate how Rh varies in both space and time. The resulting new estimate of Rh is compared to the best currently available alternative, which is based on interpolating field measurements globally. The two estimates disagree and are both uncertain.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124,Short summary
Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Remote Sensing and GISVariations in surface roughness of heterogeneous surfaces in the Nagqu area of the Tibetan PlateauEvapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate modelsThe benefit of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysisEvaluation of the dual-polarization weather radar quantitative precipitation estimation using long-term datasetsValidation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the NetherlandsComprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over ChinaSuitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West AfricaAbility of an Australian reanalysis dataset to characterise sub-daily precipitationA daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture productsEvaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towersStatistical characteristics of raindrop size distribution during rainy seasons in the Beijing urban area and implications for radar rainfall estimationAn evaluation of daily precipitation from a regional atmospheric reanalysis over AustraliaPerformance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basinThe El Niño event of 2015–2016: climate anomalies and their impact on groundwater resources in East and Southern AfricaConsistency of satellite-based precipitation products in space and over time compared with gauge observations and snow- hydrological modelling in the Lake Titicaca regionUsing phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: a case study in LuxembourgIntegrating multiple satellite observations into a coherent dataset to monitor the full water cycle – application to the Mediterranean regionAn improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution “all weather” productTemporal- and spatial-scale and positional effects on rain erosivity derived from point-scale and contiguous rain dataThe PERSIANN family of global satellite precipitation data: a review and evaluation of productsExploring seasonal and regional relationships between the Evaporative Stress Index and surface weather and soil moisture anomalies across the United StatesDevelopment of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United StatesEvaluation of multiple climate data sources for managing environmental resources in East AfricaPrecipitation downscaling using a probability-matching approach and geostationary infrared data: an evaluation over six climate regionsRegional co-variability of spatial and temporal soil moisture–precipitation coupling in North Africa: an observational perspectiveRegional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous USRegional frequency analysis of extreme rainfall in Belgium based on radar estimatesAn assessment of the performance of global rainfall estimates without ground-based observationsWater–food–energy nexus with changing agricultural scenarios in India during recent decadesIntensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern MediterraneanThe effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over FranceReservoir storage and hydrologic responses to droughts in the Paraná River basin, south-eastern BrazilRemote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixelsComparison of satellite-based evapotranspiration estimates over the Tibetan PlateauEvaluation of soil moisture downscaling using a simple thermal-based proxy – the REMEDHUS network (Spain) exampleThe SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheatEvaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002–2012)Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in EthiopiaDownscaling of seasonal soil moisture forecasts using satellite dataLong term soil moisture mapping over the Tibetan plateau using Special Sensor Microwave/ImagerIntercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climateIntegrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over FranceExperiences in using the TMPA-3B42R satellite data to complement rain gauge measurements in the Ecuadorian coastal foothillsA statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS dataEstimation of evapotranspiration from MODIS TOA radiances in the Poyang Lake basin, ChinaEvaluation of high-resolution satellite precipitation products using rain gauge observations over the Tibetan PlateauValidation of a Meteosat Second Generation solar radiation dataset over the northeastern Iberian PeninsulaJoint statistical correction of clutters, spokes and beam height for a radar derived precipitation climatology in southern GermanyEstimation of forest structure metrics relevant to hydrologic modelling using coordinate transformation of airborne laser scanning data
Maoshan Li, Xiaoran Liu, Lei Shu, Shucheng Yin, Lingzhi Wang, Wei Fu, Yaoming Ma, Yaoxian Yang, and Fanglin Sun
Hydrol. Earth Syst. Sci., 25, 2915–2930,Short summary
In this study, using MODIS satellite data and site atmospheric turbulence observation data in the Nagqu area of the northern Tibetan Plateau, with the Massman-retrieved model and a single height observation to determine aerodynamic surface roughness, temporal and spatial variation characteristics of the surface roughness were analyzed. The result is feasible, and it can be applied to improve the model parameters of the land surface model and the accuracy of model simulation in future work.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300,Short summary
Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586,Short summary
The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
Tanel Voormansik, Roberto Cremonini, Piia Post, and Dmitri Moisseev
Hydrol. Earth Syst. Sci., 25, 1245–1258,Short summary
A long set of operational polarimetric weather radar rainfall accumulations from Estonia and Italy are generated and investigated. Results show that the combined product of specific differential phase and horizontal reflectivity yields the best results when compared to rain gauge measurements. The specific differential-phase-based product overestimates weak precipitation, and the horizontal-reflectivity-based product underestimates heavy rainfall in all analysed accumulation periods.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495,Short summary
NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, and Jian Peng
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
Soil moisture plays a critical role in the water and energy cycles of the earth system, for which a long-term soil moisture product with high quality is urgently needed. In-situ observations are generally treated as the true value to systematically evaluate five soil moisture products including one remote sensing product and four reanalysis datasets during 1981–2013. This long-term inter-comparison study provides clues for SM product enhancement and further hydrological applications.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406,Short summary
This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 24, 2951–2962,Short summary
BARRA is a high-resolution reanalysis dataset over the Oceania region. This study evaluates the performance of sub-daily BARRA precipitation at point and spatial scales over Australia. We find that the dataset reproduces some of the sub-daily characteristics of precipitation well, although it exhibits some spatial displacement errors, and it performs better in temperate than in tropical regions. The product is well suited to complement other estimates derived from remote sensing and rain gauges.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710,Short summary
Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
Floyd Vukosi Khosa, Mohau Jacob Mateyisi, Martina Reynita van der Merwe, Gregor Timothy Feig, Francois Alwyn Engelbrecht, and Michael John Savage
Hydrol. Earth Syst. Sci., 24, 1587–1609,Short summary
The paper evaluates soil moisture outputs from three structurally distinct models against in situ data. Our goal is to find how representative the model outputs are for site and region. This is a question of interest as some of the models have a specific regional focus on their inceptions. Much focus is placed on how the models capture the soil moisture signal. We find that there is agreement on seasonal patterns between the models and observations with a tolerable level of model uncertainty.
Yu Ma, Guangheng Ni, Chandrasekar V. Chandra, Fuqiang Tian, and Haonan Chen
Hydrol. Earth Syst. Sci., 23, 4153–4170,Short summary
Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation. This study extensively investigates the DSD characteristics during rainy seasons in the Beijing urban area using 5-year DSD observations from a Parsivel2 disdrometer. The statistical distributions of DSD parameters are examined and the polarimetric radar rainfall algorithms are derived to support the ongoing development of an X-band radar network.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 23, 3387–3403,Short summary
BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to characterize a rich spatial variation in daily precipitation behaviour. In addition, its ability to represent large rainfalls is valuable for the analysis of extremes. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Webster Gumindoga, Tom H. M. Rientjes, Alemseged Tamiru Haile, Hodson Makurira, and Paolo Reggiani
Hydrol. Earth Syst. Sci., 23, 2915–2938,Short summary
We evaluate the influence of elevation and distance from large-scale open water bodies on bias for CMORPH satellite rainfall in the Zambezi basin. Effects of distance > 10 km from water bodies are minimal, whereas the effects at shorter distances are indicated but are not conclusive for lack of rain gauges. Taylor diagrams show station elevation influencing CMORPH performance. The
spatio-temporaland newly developed
elevation zonebias schemes proved more effective in removing CMORPH bias.
Seshagiri Rao Kolusu, Mohammad Shamsudduha, Martin C. Todd, Richard G. Taylor, David Seddon, Japhet J. Kashaigili, Girma Y. Ebrahim, Mark O. Cuthbert, James P. R. Sorensen, Karen G. Villholth, Alan M. MacDonald, and Dave A. MacLeod
Hydrol. Earth Syst. Sci., 23, 1751–1762,
Frédéric Satgé, Denis Ruelland, Marie-Paule Bonnet, Jorge Molina, and Ramiro Pillco
Hydrol. Earth Syst. Sci., 23, 595–619,Short summary
This paper assesses the potential of satellite precipitation estimates (SPEs) for precipitation measurement and hydrological and snow modelling. A total of 12 SPEs is considered to provide a global overview of available SPE accuracy for users interested in such datasets. Results show that, over poorly monitored regions, SPEs represent a very efficient alternative to traditional precipitation gauges to follow precipitation in time and space and for hydrological and snow modelling.
Maik Renner, Claire Brenner, Kaniska Mallick, Hans-Dieter Wizemann, Luigi Conte, Ivonne Trebs, Jianhui Wei, Volker Wulfmeyer, Karsten Schulz, and Axel Kleidon
Hydrol. Earth Syst. Sci., 23, 515–535,Short summary
We estimate the phase lag of surface states and heat fluxes to incoming solar radiation at the sub-daily timescale. While evapotranspiration reveals a minor phase lag, the vapor pressure deficit used as input by Penman–Monteith approaches shows a large phase lag. The surface-to-air temperature gradient used by energy balance residual approaches shows a small phase shift in agreement with the sensible heat flux and thus explains the better correlation of these models at the sub-daily timescale.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491,Short summary
This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Samiro Khodayar, Amparo Coll, and Ernesto Lopez-Baeza
Hydrol. Earth Syst. Sci., 23, 255–275,
Franziska K. Fischer, Tanja Winterrath, and Karl Auerswald
Hydrol. Earth Syst. Sci., 22, 6505–6518,Short summary
The potential of rain to cause soil erosion by runoff is called rain erosivity. Rain erosivity is highly variable in space and time even over distances of less than 1 km. Contiguously measured radar rain data depict for the first time this spatio-temporal variation, but scaling factors are required to account for differences in spatial and temporal resolution compared to rain gauge data. These scaling factors were obtained from more than 2 million erosive events.
Phu Nguyen, Mohammed Ombadi, Soroosh Sorooshian, Kuolin Hsu, Amir AghaKouchak, Dan Braithwaite, Hamed Ashouri, and Andrea Rose Thorstensen
Hydrol. Earth Syst. Sci., 22, 5801–5816,Short summary
The goal of this article is to first provide an overview of the available PERSIANN precipitation retrieval algorithms and their differences. We evaluate the products over CONUS at different spatial and temporal scales using CPC data. Daily scale is the finest temporal scale used for the evaluation over CONUS. We provide a comparison of the available products at a quasi-global scale. We highlight the strengths and limitations of the PERSIANN products.
Jason A. Otkin, Yafang Zhong, David Lorenz, Martha C. Anderson, and Christopher Hain
Hydrol. Earth Syst. Sci., 22, 5373–5386,Short summary
Correlation analyses were used to explore relationships between the Evaporative Stress Index (ESI) – which depicts anomalies in evapotranspiration (ET) – and various land and atmospheric variables that impact ET. The results revealed that the ESI is more strongly correlated to anomalies in soil moisture and near-surface vapor pressure deficit than to precipitation and temperature anomalies. Large regional and seasonal dependencies in the strengths of the correlations were also observed.
Vikalp Mishra, James F. Cruise, Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 22, 4935–4957,Short summary
Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.
Solomon Hailu Gebrechorkos, Stephan Hülsmann, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 22, 4547–4564,Short summary
In Africa field-based meteorological data are scarce; therefore global data sources based on remote sensing and climate models are often used as alternatives. To assess their suitability for a large and topographically complex area in East Africa, we evaluated multiple climate data products with available ground station data at multiple timescales over 21 regions. The comprehensive evaluation resulted in identification of preferential data sources to be used for climate and hydrological studies.
Ruifang Guo, Yuanbo Liu, Han Zhou, and Yaqiao Zhu
Hydrol. Earth Syst. Sci., 22, 3685–3699,Short summary
Existing satellite products are often insufficient for use in small-scale (< 10 km) hydrological and meteorological studies. We propose a new approach based on the cumulative distribution of frequency to downscale satellite precipitation products with geostationary (GEO) data. This paper uses CMORPH and FY2-E GEO data to examine the approach in six different climate regions. The downscaled precipitation performed better for convective systems.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294,Short summary
In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Nishan Bhattarai, Kaniska Mallick, Nathaniel A. Brunsell, Ge Sun, and Meha Jain
Hydrol. Earth Syst. Sci., 22, 2311–2341,Short summary
We report the first ever regional-scale implementation of the Surface Temperature Initiated Closure (STIC1.2) model for mapping evapotranspiration (ET) using MODIS land surface and gridded climate datasets to overcome the existing uncertainties in aerodynamic temperature and conductance estimation in global ET models. Validation and intercomparison with SEBS and MOD16 products across an aridity gradient in the US manifested better ET mapping potential of STIC1.2 in different climates and biomes.
Edouard Goudenhoofdt, Laurent Delobbe, and Patrick Willems
Hydrol. Earth Syst. Sci., 21, 5385–5399,Short summary
Knowing the characteristics of extreme precipitation is useful for flood management applications like sewer system design. The potential of a 12-year high-quality weather radar precipitation dataset is investigated by comparison with rain gauges. Despite known limitations, a good agreement is found between the radar and the rain gauges. Using the radar data allow us to reduce the uncertainty of the extreme value analysis, especially for short duration extremes related to thunderstorms.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361,Short summary
The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Beas Barik, Subimal Ghosh, A. Saheer Sahana, Amey Pathak, and Muddu Sekhar
Hydrol. Earth Syst. Sci., 21, 3041–3060,Short summary
The article summarises changing patterns of the water-food-energy nexus in India during recent decades. The work first analyses satellite data of water storage with a validation using the observed well data. Northern India shows a declining trend of water storage and western-central India shows an increasing trend of the same. Major droughts result in a drop in water storage which is not recovered due to uncontrolled ground water irrigation for agricultural activities even in good monsoon years.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404,Short summary
Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033,Short summary
This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Davi de C. D. Melo, Bridget R. Scanlon, Zizhan Zhang, Edson Wendland, and Lei Yin
Hydrol. Earth Syst. Sci., 20, 4673–4688,Short summary
Drought propagation from rainfall deficits to reservoir depletion was studied based on remote sensing, monitoring and modelling data. Regional droughts were shown by widespread depletion in total water storage that reduced soil moisture storage and runoff, greatly reducing reservoir storage. The multidisciplinary approach to drought assessment shows the linkages between meteorological and hydrological droughts that are essential for managing water resources subjected to climate extremes.
Zhi Qing Peng, Xiaozhou Xin, Jin Jun Jiao, Ti Zhou, and Qinhuo Liu
Hydrol. Earth Syst. Sci., 20, 4409–4438,Short summary
A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182,Short summary
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).
J. Peng, J. Niesel, and A. Loew
Hydrol. Earth Syst. Sci., 19, 4765–4782,Short summary
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.
G. Boulet, B. Mougenot, J.-P. Lhomme, P. Fanise, Z. Lili-Chabaane, A. Olioso, M. Bahir, V. Rivalland, L. Jarlan, O. Merlin, B. Coudert, S. Er-Raki, and J.-P. Lagouarde
Hydrol. Earth Syst. Sci., 19, 4653–4672,Short summary
The paper presents a new model (SPARSE) to estimate total evapotranspiration as well as its components (evaporation and transpiration) from remote-sensing data in the thermal infra-red domain. The limits of computing two unknowns (evaporation and transpiration) out of one piece of information (one surface temperature) are assessed theoretically. The model performance in retrieving the components as well as the water stress is assessed for two wheat crops (one irrigated and one rainfed).
O. P. Prat and B. R. Nelson
Hydrol. Earth Syst. Sci., 19, 2037–2056,
Y. Duan, A. M. Wilson, and A. P. Barros
Hydrol. Earth Syst. Sci., 19, 1501–1520,Short summary
A diagnostic analysis of the space-time structure of error in quantitative precipitation estimates (QPEs) from the precipitation radar on the Tropical Rainfall Measurement Mission satellite is presented here in preparation for the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014. A high-density raingauge network over the southern Appalachians allows for direct comparison between ground-based measurements and satellite-based QPE (PR 2A25 Version 7 with 5 years of data 2008-2013).
A. W. Worqlul, B. Maathuis, A. A. Adem, S. S. Demissie, S. Langan, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 18, 4871–4881,
S. Schneider, A. Jann, and T. Schellander-Gorgas
Hydrol. Earth Syst. Sci., 18, 2899–2905,
R. van der Velde, M. S. Salama, T. Pellarin, M. Ofwono, Y. Ma, and Z. Su
Hydrol. Earth Syst. Sci., 18, 1323–1337,
J. Chirouze, G. Boulet, L. Jarlan, R. Fieuzal, J. C. Rodriguez, J. Ezzahar, S. Er-Raki, G. Bigeard, O. Merlin, J. Garatuza-Payan, C. Watts, and G. Chehbouni
Hydrol. Earth Syst. Sci., 18, 1165–1188,
A. L. Barbu, J.-C. Calvet, J.-F. Mahfouf, and S. Lafont
Hydrol. Earth Syst. Sci., 18, 173–192,
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Water that evaporates from Africa's tropical forests provides rainfall throughout the continent. However, there are few sources of meteorological data in central Africa, so we use observations from satellites to estimate evaporation from the Congo Basin at different times of the year. We find that existing evaporation estimates in tropical Africa do not accurately capture seasonal variations in evaporation and that fluctuations in soil moisture and solar radiation drive evaporation rates.
Water that evaporates from Africa's tropical forests provides rainfall throughout the continent....