Articles | Volume 25, issue 6
Research article 09 Jun 2021
Research article | 09 Jun 2021
Global component analysis of errors in three satellite-only global precipitation estimates
Hanqing Chen et al.
No articles found.
Chloé Radice, Hélène Brogniez, Pierre-Emmanuel Kirstetter, and Philippe Chambon
Atmos. Chem. Phys. Discuss.,
Preprint under review for ACPShort summary
A novel probabilistic approach is proposed to evaluate relative humidity (RH) profiles simulated by an atmospheric model with respect to satellite-based RH defined from probability distributions. It improves upon deterministic comparisons by enhancing the information content to enable a finer assessment of each model-observation discrepancies, highlighting significant departures within a deterministic confidence range. Geographical and vertical distributions of the model biases are discussed.
Zhi Li, Mengye Chen, Shang Gao, Jonathan J. Gourley, Tiantian Yang, Xinyi Shen, Randall Kolar, and Yang Hong
Earth Syst. Sci. Data, 13, 3755–3766,Short summary
This dataset is a compilation of multi-sourced flood records, retrieved from official reports, instruments, and crowdsourcing data since 1900. This study utilizes the flood database to analyze flood seasonality within major basins and socioeconomic impacts over time. It is anticipated that this dataset can support a variety of flood-related research, such as validation resources for hydrologic models, hydroclimatic studies, and flood vulnerability analysis across the United States.
Yingzhao Ma, Xun Sun, Haonan Chen, Yang Hong, and Yinsheng Zhang
Hydrol. Earth Syst. Sci., 25, 359–374,Short summary
A two-stage blending approach is proposed for the data fusion of multiple satellite precipitation estimates (SPEs), which firstly reduces the systematic errors of original SPEs based on a Bayesian correction model and then merges the bias-corrected SPEs with a Bayesian weighting model. The model is evaluated in the warm season of 2010–2014 in the northeastern Tibetan Plateau. Results show that the blended SPE is greatly improved compared with the original SPEs, even in heavy rainfall events.
Ziqiang Ma, Jintao Xu, Siyu Zhu, Jun Yang, Guoqiang Tang, Yuanjian Yang, Zhou Shi, and Yang Hong
Earth Syst. Sci. Data, 12, 1525–1544,Short summary
Focusing on the potential drawbacks in generating the state-of-the-art IMERG data in both the TRMM and GPM era, a new daily calibration algorithm on IMERG was proposed, as well as a new AIMERG precipitation dataset (0.1°/half-hourly, 2000–2015, Asia) with better quality than IMERG for Asian scientific research and applications. The proposed daily calibration algorithm for GPM is promising and applicable in generating the future IMERG in either an operational scheme or a retrospective manner.
Z. Hui, P. Cheng, L. Wang, Y. Xia, H. Hu, and X. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1021–1025,
Ke Zhang, Xianwu Xue, Yang Hong, Jonathan J. Gourley, Ning Lu, Zhanming Wan, Zhen Hong, and Rick Wooten
Hydrol. Earth Syst. Sci., 20, 5035–5048,Short summary
We developed a new approach to couple a distributed hydrological model, CREST, to a geotechnical landslide model, TRIGRS, to simulate both flood- and rainfall-triggered landslide hazards. By implementing more sophisticated and realistic representations of hydrological processes in the coupled model system, it shows better performance than the standalone landslide model in the case study. It highlights the important physical connection between rainfall, hydrological processes and slope stability.
Wen-Yu Yang, Guang-Heng Ni, You-Cun Qi, Yang Hong, and Ting Sun
Atmos. Meas. Tech. Discuss.,
Revised manuscript has not been submittedShort summary
Using a dataset consisting of one-year measurements by an X-band radar and distrometer, we found that error corrections greatly improve X-band-radar-based rainfall estimation. Specifically, the greatest improvement is realized by the beam integration. Derivation of localized Z-R relationships for specific rainfall systems is also of great importance. Moreover, wind drift correction improves quantitative estimates and temporal consistency.
W. A. Gonçalves, L. A. T. Machado, and P.-E. Kirstetter
Atmos. Chem. Phys., 15, 6789–6800,
Related subject area
Subject: Global hydrology | Techniques and Approaches: Remote Sensing and GISThe accuracy of temporal upscaling of instantaneous evapotranspiration to daily values with seven upscaling methodsEstimation of hydrological drought recovery based on precipitation and Gravity Recovery and Climate Experiment (GRACE) water storage deficitIntercomparison of freshwater fluxes over ocean and investigations into water budget closureWidespread decline in terrestrial water storage and its link to teleconnections across Asia and eastern EuropeAssimilation of vegetation optical depth retrievals from passive microwave radiometryLong-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basinsGlobal partitioning of runoff generation mechanisms using remote sensing dataLand–atmosphere interactions in the tropics – a reviewGlobal-scale human pressure evolution imprints on sustainability of river systemsUsing GRACE in a streamflow recession to determine drainable water storage in the Mississippi River basinA new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean regionGlobal joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation responseUsing modelled discharge to develop satellite-based river gauging: a case study for the Amazon BasinGlobal downscaling of remotely sensed soil moisture using neural networksGlobal 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilationExploring the merging of the global land evaporation WACMOS-ET products based on local tower measurementsEstimating time-dependent vegetation biases in the SMAP soil moisture productDaily GRACE gravity field solutions track major flood events in the Ganges–Brahmaputra DeltaControls on surface soil drying rates observed by SMAP and simulated by the Noah land surface modelQuantification of surface water volume changes in the Mackenzie Delta using satellite multi-mission dataMicrowave implementation of two-source energy balance approach for estimating evapotranspirationA global approach to estimate irrigated areas – a comparison between different data and statisticsThe future of Earth observation in hydrologyValidation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observationsMSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis dataEvaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall dataEvaluating the strength of the land–atmosphere moisture feedback in Earth system models using satellite observationsCloud tolerance of remote-sensing technologies to measure land surface temperatureDynamic changes in terrestrial net primary production and their effects on evapotranspirationAssessing changes in urban flood vulnerability through mapping land use from historical informationSACRA – a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVIA global data set of the extent of irrigated land from 1900 to 2005Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factorsSpatial patterns in timing of the diurnal temperature cyclePotential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studiesGlobal multi-scale segmentation of continental and coastal waters from the watersheds to the continental marginsAutomated global water mapping based on wide-swath orbital synthetic-aperture radarAn algorithm for generating soil moisture and snow depth maps from microwave spaceborne radiometers: HydroAlgoReconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpassSpace-based passive microwave soil moisture retrievals and the correction for a dynamic open water fractionA global analysis of soil moisture derived from satellite observations and a land surface modelAssimilation of ASCAT near-surface soil moisture into the SIM hydrological model over FranceThe sensitivity of land emissivity estimates from AMSR-E at C and X bands to surface propertiesUse of ENVISAT ASAR Global Monitoring Mode to complement optical data in the mapping of rapid broad-scale flooding in PakistanThe impact of land surface temperature on soil moisture anomaly detection from passive microwave observationsDrainage basin morphometry: a global snapshot from the shuttle radar topography missionThe International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurementsCombining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain areaAerodynamic roughness length estimation from very high-resolution imaging LIDAR observations over the Heihe basin in ChinaInterannual variations of the terrestrial water storage in the Lower Ob' Basin from a multisatellite approach
Hydrol. Earth Syst. Sci., 25, 4417–4433,Short summary
Instantaneous evapotranspiration (ET), which is detected by the remote sensing technique, needs to be upscaled to daily values in order to practical applications. The accuracy of seven upscaling methods is evaluated by using global observations. The sine function and the evaporative fraction method using extraterrestrial solar irradiance are recommended. Although every upscaling scheme has high accuracy at most sites, it is less accurate at tropical rainforest and tropical monsoon sites.
Alka Singh, John Thomas Reager, and Ali Behrangi
Hydrol. Earth Syst. Sci., 25, 511–526,Short summary
The study demonstrates the utility of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomalies (TWSAs) for obtaining statistics of hydrological droughts, i.e., recovery periods and required precipitation in different precipitation scenarios. The findings of this study are that the GRACE-based drought index is valid for estimating the required precipitation for drought recovery, and the period of drought recovery depends on the intensity of the precipitation.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146,Short summary
The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent satellite-based climate data records and ERA5 reanalysis E−P data.
Xianfeng Liu, Xiaoming Feng, Philippe Ciais, and Bojie Fu
Hydrol. Earth Syst. Sci., 24, 3663–3676,Short summary
Freshwater availability is crucial for sustainable development across the Asian and eastern European regions. Our results indicate widespread decline in terrestrial water storage (TWS) over the region during 2002–2017, primarily due to the intensive over-extraction of groundwater and warmth-induced surface water loss. The findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is growing demand for food grains and water supplies.
Sujay V. Kumar, Thomas R. Holmes, Rajat Bindlish, Richard de Jeu, and Christa Peters-Lidard
Hydrol. Earth Syst. Sci., 24, 3431–3450,Short summary
Vegetation optical depth (VOD) is a byproduct of the soil moisture retrieval from passive microwave instruments. This study demonstrates that VOD information can be utilized for improving land surface water budget and carbon conditions through data assimilation.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055,Short summary
The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Joseph T. D. Lucey, John T. Reager, and Sonya R. Lopez
Hydrol. Earth Syst. Sci., 24, 1415–1427,Short summary
This work relates total water storage (TWS) and rainfall to surface water inundation (SWI) using NASA satellite data. We determine whether TWS and/or rainfall control global SWI developments. Regression methods and cross-correlations were used to relate the measurements and correct for time differences among peaks. Results show TWS and rainfall control most global SWI developments. To our knowledge, this is the first global study on SWI controls and validates previous findings.
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197,Short summary
Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Serena Ceola, Francesco Laio, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 3933–3944,Short summary
A simple and effective index for the quantitative estimation of the evolution of human pressure on rivers at global scale is proposed. This index, based on nightlights and river discharge data, shows a significant increase from 1992 to 2013 worldwide. The most notable changes are found in river basins across Africa and Asia, where human pressure on rivers is growing markedly. This index identifies priority areas that can be targeted for the implementation of mitigation strategies and plans.
Heloisa Ehalt Macedo, Ralph Edward Beighley, Cédric H. David, and John T. Reager
Hydrol. Earth Syst. Sci., 23, 3269–3277,Short summary
The water stored under the surface is very important for defining the amount of water available for human and environmental applications; however, it is still a challenge to obtain such measurements. NASA's GRACE satellites provide information on total terrestrial water storage based on observations of gravity changes. Here, we relate GRACE data to streamflow measurements, providing estimations of the fraction of baseflow and total drainable storage for the Mississippi River basin.
Linlin Li, Andrew Skidmore, Anton Vrieling, and Tiejun Wang
Hydrol. Earth Syst. Sci., 23, 3037–3056,Short summary
We derived an 8 d, 500 m resolution surface water fraction product over the Mediterranean region for 2000–2017 based on MODIS data. This dataset complements existing surface water/wetland datasets by adding more temporal detail. It allows for the seasonal, inter-annual, and long-term dynamics of the surface water extent to be monitored, inclusive of small-sized and highly dynamic water bodies; it can also contribute to biodiversity and climate change assessment.
Siyuan Tian, Luigi J. Renzullo, Albert I. J. M. van Dijk, Paul Tregoning, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 1067–1081,
Jiawei Hou, Albert I. J. M. van Dijk, Luigi J. Renzullo, and Robert A. Vertessy
Hydrol. Earth Syst. Sci., 22, 6435–6448,Short summary
Satellite-based river gauging can be constructed based on remote-sensing-derived surface water extent and modelled discharge, and used to estimate river discharges with satellite observations only. This provides opportunities for monitoring river discharge in the absence of a real-time hydrological model or gauging stations.
Seyed Hamed Alemohammad, Jana Kolassa, Catherine Prigent, Filipe Aires, and Pierre Gentine
Hydrol. Earth Syst. Sci., 22, 5341–5356,Short summary
A new machine learning algorithm is developed to downscale satellite-based soil moisture estimates from their native spatial scale of 9 km to 2.25 km.
Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980,Short summary
Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533,Short summary
Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Simon Zwieback, Andreas Colliander, Michael H. Cosh, José Martínez-Fernández, Heather McNairn, Patrick J. Starks, Marc Thibeault, and Aaron Berg
Hydrol. Earth Syst. Sci., 22, 4473–4489,Short summary
Satellite soil moisture products can provide critical information on incipient droughts and the interplay between vegetation and water availability. However, time-variant systematic errors in the soil moisture products may impede their usefulness. Using a novel statistical approach, we detect such errors (associated with changing vegetation) in the SMAP soil moisture product. The vegetation-associated biases impede drought detection and the quantification of vegetation–water interactions.
Ben T. Gouweleeuw, Andreas Kvas, Christian Gruber, Animesh K. Gain, Thorsten Mayer-Gürr, Frank Flechtner, and Andreas Güntner
Hydrol. Earth Syst. Sci., 22, 2867–2880,Short summary
Daily GRACE gravity field solutions have been evaluated against daily river runoff data for major flood events in the Ganges–Brahmaputra Delta in 2004 and 2007. Compared to the monthly gravity field solutions, the trends over periods of a few days in the daily gravity field solutions are able to reflect temporal variations in river runoff during major flood events. This implies that daily gravity field solutions released in near-real time may support flood monitoring for large events.
Peter J. Shellito, Eric E. Small, and Ben Livneh
Hydrol. Earth Syst. Sci., 22, 1649–1663,Short summary
After soil gets wet, much of the surface moisture evaporates directly back into the air. Recent satellite data show that this process is enhanced when there is more water in the soil, less humidity in the air, and less vegetation covering the ground. A widely used model shows similar effects of soil water and humidity, but it largely misses the role of vegetation and assigns outsized importance to soil type. These results are encouraging evidence that the satellite can be used to improve models.
Cassandra Normandin, Frédéric Frappart, Bertrand Lubac, Simon Bélanger, Vincent Marieu, Fabien Blarel, Arthur Robinet, and Léa Guiastrennec-Faugas
Hydrol. Earth Syst. Sci., 22, 1543–1561,
Thomas R. H. Holmes, Christopher R. Hain, Wade T. Crow, Martha C. Anderson, and William P. Kustas
Hydrol. Earth Syst. Sci., 22, 1351–1369,Short summary
In an effort to apply cloud-tolerant microwave data to satellite-based monitoring of evapotranspiration (ET), this study reports on an experiment where microwave-based land surface temperature is used as the key diagnostic input to a two-source energy balance method for the estimation of ET. Comparisons of this microwave ET with the conventional thermal infrared estimates show widespread agreement in spatial and temporal patterns from seasonal to inter-annual timescales over Africa and Europe.
Jonas Meier, Florian Zabel, and Wolfram Mauser
Hydrol. Earth Syst. Sci., 22, 1119–1133,Short summary
The following study extends existing irrigation maps based on official reports. The main idea was to extend the reported irrigated areas using agricultural suitability data and compare them with remote sensing information about plant conditions. The analysis indicates an increase in irrigated land by 18 % compared to the reported statistics. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914,Short summary
We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Liangjing Zhang, Henryk Dobslaw, Tobias Stacke, Andreas Güntner, Robert Dill, and Maik Thomas
Hydrol. Earth Syst. Sci., 21, 821–837,Short summary
Global numerical models perform differently, as has been found in some model intercomparison studies, which mainly focused on components like evapotranspiration, soil moisture or runoff. We have applied terrestrial water storage that is estimated from a GRACE-based state-of-art post-processing method to validate four global numerical models and try to identify the advantages and deﬁciencies of a certain model. GRACE-based TWS demonstrates its additional benefits to improve the models in future.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615,Short summary
MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
Oliver López, Rasmus Houborg, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 21, 323–343,Short summary
The study evaluated the spatial and temporal consistency of satellite-based hydrological products based on the water budget equation, including three global evaporation products. The products were spatially matched using spherical harmonics analysis. The results highlighted the difficulty in obtaining agreement between independent satellite products, even over regions with simple water budgets. However, imposing a time lag on water storage data improved results considerably.
Paul A. Levine, James T. Randerson, Sean C. Swenson, and David M. Lawrence
Hydrol. Earth Syst. Sci., 20, 4837–4856,Short summary
We demonstrate a new approach to assess the strength of feedbacks resulting from land–atmosphere coupling on decadal timescales. Our approach was tailored to enable evaluation of Earth system models (ESMs) using data from Earth observation satellites that measure terrestrial water storage anomalies and relevant atmospheric variables. Our results are consistent with previous work demonstrating that ESMs may be overestimating the strength of land surface feedbacks compared with observations.
Thomas R. H. Holmes, Christopher R. Hain, Martha C. Anderson, and Wade T. Crow
Hydrol. Earth Syst. Sci., 20, 3263–3275,Short summary
We test the cloud tolerance of two technologies to estimate land surface temperature (LST) from space: microwave (MW) and thermal infrared (TIR). Although TIR has slightly lower errors than MW with ground data under clear-sky conditions, it suffers increasing negative bias as cloud cover increases. In contrast, we find no direct impact of clouds on the accuracy and bias of MW-LST. MW-LST can therefore be used to improve TIR cloud screening and increase sampling in clouded regions.
Zhi Li, Yaning Chen, Yang Wang, and Gonghuan Fang
Hydrol. Earth Syst. Sci., 20, 2169–2178,Short summary
Global net primary production (NPP) slightly increased in 2000–2014. More than 64 % of vegetated land in the Northern Hemisphere (NH) showed increased NPP, while 60.3 % in Southern Hemisphere (SH) showed a decreasing trend. Vegetation greening and climate change promote rises of global evapotranspiration (ET). The increased rate of ET in the NH is faster than that in the SH. Meanwhile, global warming and vegetation greening accelerate evaporation in soil moisture. Continuation of these trends will likely exacerbate the risk of ecological drought.
M. Boudou, B. Danière, and M. Lang
Hydrol. Earth Syst. Sci., 20, 161–173,Short summary
This paper presents an appraisal of flood vulnerability of two French cities, Besançon and Moissac, which have been largely impacted by two ancient major floods (resp. in January 1910 and March 1930). An analysis of historical sources allows the mapping of land use and occupation within the flood extent of the two historical floods, both in past and present contexts. It gives an insight into the complexity of flood risk evolution, at a local scale.
S. Kotsuki and K. Tanaka
Hydrol. Earth Syst. Sci., 19, 4441–4461,Short summary
This study aims to develop a new global data set of a satellite-derived crop calendar (SACRA) and to reveal its advantages and disadvantages compared to other global products. The cultivation period of SACRA is identified from the time series of NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (< 62 days) in most areas.
S. Siebert, M. Kummu, M. Porkka, P. Döll, N. Ramankutty, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 19, 1521–1545,Short summary
We developed the historical irrigation data set (HID) depicting the spatio-temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5arcmin resolution. The HID reflects very well the spatial patterns of irrigated land as shown on two historical maps for 1910 and 1960. Global AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. Mean aridity on irrigated land increased and mean natural river discharge decreased from 1900 to 1950.
B. Revilla-Romero, J. Thielen, P. Salamon, T. De Groeve, and G. R. Brakenridge
Hydrol. Earth Syst. Sci., 18, 4467–4484,Short summary
One of the main challenges in global hydrological modelling is the limited availability of observational data for calibration and model verification. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System (GFDS) for converting the flood detection signal into river discharge values. This work also provides a first analysis of the local factors influencing the accuracy of discharge measurement as provided by this system.
T. R. H. Holmes, W. T. Crow, and C. Hain
Hydrol. Earth Syst. Sci., 17, 3695–3706,
A. Loew, T. Stacke, W. Dorigo, R. de Jeu, and S. Hagemann
Hydrol. Earth Syst. Sci., 17, 3523–3542,
G. G. Laruelle, H. H. Dürr, R. Lauerwald, J. Hartmann, C. P. Slomp, N. Goossens, and P. A. G. Regnier
Hydrol. Earth Syst. Sci., 17, 2029–2051,
R. S. Westerhoff, M. P. H. Kleuskens, H. C. Winsemius, H. J. Huizinga, G. R. Brakenridge, and C. Bishop
Hydrol. Earth Syst. Sci., 17, 651–663,
E. Santi, S. Pettinato, S. Paloscia, P. Pampaloni, G. Macelloni, and M. Brogioni
Hydrol. Earth Syst. Sci., 16, 3659–3676,
E. Delogu, G. Boulet, A. Olioso, B. Coudert, J. Chirouze, E. Ceschia, V. Le Dantec, O. Marloie, G. Chehbouni, and J.-P. Lagouarde
Hydrol. Earth Syst. Sci., 16, 2995–3010,
B. T. Gouweleeuw, A. I. J. M. van Dijk, J. P. Guerschman, P. Dyce, and M. Owe
Hydrol. Earth Syst. Sci., 16, 1635–1645,
K. T. Rebel, R. A. M. de Jeu, P. Ciais, N. Viovy, S. L. Piao, G. Kiely, and A. J. Dolman
Hydrol. Earth Syst. Sci., 16, 833–847,
C. Draper, J.-F. Mahfouf, J.-C. Calvet, E. Martin, and W. Wagner
Hydrol. Earth Syst. Sci., 15, 3829–3841,
H. Norouzi, M. Temimi, W. B. Rossow, C. Pearl, M. Azarderakhsh, and R. Khanbilvardi
Hydrol. Earth Syst. Sci., 15, 3577–3589,
D. O'Grady, M. Leblanc, and D. Gillieson
Hydrol. Earth Syst. Sci., 15, 3475–3494,
R. M. Parinussa, T. R. H. Holmes, M. T. Yilmaz, and W. T. Crow
Hydrol. Earth Syst. Sci., 15, 3135–3151,
P. L. Guth
Hydrol. Earth Syst. Sci., 15, 2091–2099,
W. A. Dorigo, W. Wagner, R. Hohensinn, S. Hahn, C. Paulik, A. Xaver, A. Gruber, M. Drusch, S. Mecklenburg, P. van Oevelen, A. Robock, and T. Jackson
Hydrol. Earth Syst. Sci., 15, 1675–1698,
J. Cristóbal, R. Poyatos, M. Ninyerola, P. Llorens, and X. Pons
Hydrol. Earth Syst. Sci., 15, 1563–1575,
J. Colin and R. Faivre
Hydrol. Earth Syst. Sci., 14, 2661–2669,
F. Frappart, F. Papa, A. Güntner, S. Werth, G. Ramillien, C. Prigent, W. B. Rossow, and M.-P. Bonnet
Hydrol. Earth Syst. Sci., 14, 2443–2453,
AghaKouchak, A., Behrangi, A., Sorooshian, S., Hsu, K., and Amitai, E.: Evaluation of satellite retrieved extreme precipitation rates across the central United States, J. Geophys., Res.-Atmos., 116, D02115, https://doi.org/10.1029/2010JD014741, 2011.
AghaKouchak, A., Mehran, A., Norouzi, H., and Behrangi, A.: Systematic and random error components in satellite precipitation data sets, Geophys. Res. Lett., 39, L09406, https://doi.org/10.1029/2012GL051592, 2012.
Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Beck, H. E., McNamara, I., Ribbe, L., Nauditt, A., Birkel, C., Verbist, K., Giraldo-Osorio, J. D., and Thinh, N. X.: RF-MEP: A novel random forest method for merging gridded precipitation products and ground-based measurements, Remote Sens. Environ., 239, 111606, https://doi.org/10.1016/j.rse.2019.111606, 2020.
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017.
Beck, H. E., Pan, M., Roy, T., Weedon, G. P., Pappenberger, F., van Dijk, A. I. J. M., Huffman, G. J., Adler, R. F., and Wood, E. F.: Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS, Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, 2019.
Bhuiyan, M. A. E., Nikolopoulos, E. I., Anagnostou, E. N., Quintana-Seguí, P., and Barella-Ortiz, A.: A nonparametric statistical technique for combining global precipitation datasets: development and hydrological evaluation over the Iberian Peninsula, Hydrol. Earth Syst. Sci., 22, 1371–1389, https://doi.org/10.5194/hess-22-1371-2018, 2018.
Chen, H., Lu, D., Zhou, Z., Zhu, Z., Ren, Y., and Yong, B.: An overview of the evaluation of satellite precipitation Products for Global Precipitation Measurement (GPM) (in Chinese), Water Resour. Prot., 35, 27–34, 2019a.
Chen, H., Yong, B., Gourly, J. J., Liu, J., Ren, L., Wang, W., Hong, Y., and Zhang, J.: Impact of the Crucial Geographical and Climatic Factors on the Input Source Errors of GPM-based Global Satellite Precipitation Estimates, J. Hydrol., 575, 1–16, 2019b.
Chen, H., Yong, B., Qi, W., Wu, H., Ren, L., and Hong, Y.: Investigating the Evaluation Uncertainty for Satellite Precipitation Estimates Based on Two Different Ground Precipitation Observation Products, J. Hydrometeorol., 21, 2595–2606, 2020a.
Chen, H., Yong, B., Shen, Y., Liu, J., Hong, Y., and Zhang, J.: Comparison analysis of six purely satellite-derived global precipitation estimates, J. Hydrol., 581, 124376, https://doi.org/10.1016/j.jhydrol.2019.124376, 2020b.
Chen, M., Shi, W., Xie, P., Silva, V. B., Kousky, V. E., Wayne Higgins, R., and Janowiak, J. E.: Assessing objective techniques for gauge-based analyses of global daily precipitation, J. Geophys. Res.-Atmos., 113, D04110, https://doi.org/10.1029/2007JD009132, 2008.
Chen, S., Hong, Y., Cao, Q., Gourley, J. J., Kirstetter, P. E., Yong, B., Tian, Y., Zhang, Z. X., Shen, Y., Hu, J. J., and Hardy, J.: Similarity and difference of the two successive V6 and V7 TRMM multisatellite precipitation analysis performance over China, J. Geophys. Res.-Atmos., 118, 13060–13074, 2013.
Choubin, B., Khalighisigaroodi, S., Mishra, A. K., Goodarzi, M., Shamshirband, S., Ghaljaee, E., and Zhang, F.: A novel bias correction framework of TMPA 3B42 daily precipitation data using similarity matrix/homogeneous conditions, Sci. Total Environ., 694, 133680, https://doi.org/10.1016/j.scitotenv.2019.133680, 2019.
Gebregiorgis, A. S., Kirstetter, P.-E., Hong, Y. E., Gourley, J. J., Huffman, G. J., Petersen, W. A., Xue, X., and Schwaller, M. R.: To what extent is the day 1 GPM IMERG satellite precipitation estimate improved as compared to TRMM TMPA-RT?, J. Geophys. Res.-Atmos., 123, 1694–1707, 2018.
Guo, H., Bao, A., Ndayisaba, F., Liu, T., Kurban, A., and De Maeyer, P.: Systematical Evaluation of Satellite Precipitation Estimates Over Central Asia Using an Improved Error-Component Procedure, J. Geophys. Res.-Atmos., 122, 10906–10927, 2017.
Hashemi, H., Nordin, M., Lakshmi, V., Huffman, G. J., and Knight, R.: Bias Correction of Long-Term Satellite Monthly Precipitation Product (TRMM 3B43) over the Conterminous United States, J. Hydrometeorol., 18, 2491–2509, 2017.
Hong, Y., Hsu, K. L., Sorooshian, S., and Gao, X.: Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system, J. Appl. Meteorol., 43, 1834–1853, 2004.
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., and Lguchi, T.: The global precipitation measurement mission, B. Am. Meteorol. Soc., 95, 701–722, 2014.
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., and Tan, J.: Integrated Multi-satellitE Retrievals for GPM (IMERG) Technical Documentation, NASA/GSFC, 1, 2019.
Kidd, C. and Huffman, G. J.: Global precipitation measurement, Meteorol. Appl., 18, 334–353, 2011.
Kidd, C. and Levizzani, V.: Status of satellite precipitation retrievals, Hydrol. Earth Syst. Sci., 15, 1109–1116, https://doi.org/10.5194/hess-15-1109-2011, 2011.
Kidd, C., Becker, A., Huffman, G. J., Muller, C. L., Joe, P., Skofronick-Jackson, G., and Kirschbaum, D. B.: So, how much of the Earth's surface is covered by rain gauges?, B. Am. Meteorol. Soc., 98, 69–78, 2017.
Kirstetter, P. E., Hong, Y., Gourley, J. J., Schwaller, M., Petersen, W., and Zhang, J.: Comparison of TRMM 2A25 products, version 6 and version 7, with NOAA/NSSL ground radar-based National Mosaic QPE, J. Hydrometeorol., 14, 661–669, 2013.
Kirstetter, P. E., Karbalaee, N., Hsu, K., and Hong, Y.: Probabilistic precipitation rate estimates with space-based infrared sensors, Q. J. Roy. Meteor. Soc., 144, 191–205, 2018.
Le, H. M., Sutton, J. R., Du Bui, D., Bolten, J. D., and Lakshmi, V.: Comparison and Bias Correction of TMPA Precipitation Products over the Lower Part of Red-Thai Binh River Basin of Vietnam, Remote Sens., 10, 1582, https://doi.org/10.3390/rs10101582, 2018.
Liu, Z.: Comparison of ntegrated Multi-satellite Retrievals for GPM (IMERG) and TRMM Multi-satellite Precipitation Analysis (TMPA) monthly precipitation products: initial results, J. Hydrometeorol., 17, 777–790, 2016.
Maggioni, V., Meyers, P. C., and Robinson, M. D.: A review of merged high-resolution satellite precipitation product accuracy during the Tropical Rainfall Measuring Mission (TRMM) era, J. Hydrometeorol., 17, 1101–1117, 2016a.
Maggioni, V., Sapiano, M. R., and Adler, R. F.: Estimating Uncertainties in High-Resolution Satellite Precipitation Products: Systematic or Random Error?, J. Hydrometeorol., 17, 1119–1129, 2016b.
NASA: Precipitation Data Directory, available at: https://pmm.nasa.gov/data-access/downloads/gpm, last access: 20 February 2021.
Prakash, S., Mitra, A. K., AghaKouchak, A., Liu, Z., Norouzi, H., and Pai, D. S.: A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region, J. Hydrol., 556, 865–876, 2018.
Shen, G., Chen, N., Wang, W., and Chen, Z.: WHU-SGCC: a novel approach for blending daily satellite (CHIRP) and precipitation observations over the Jinsha River basin, Earth Syst. Sci. Data, 11, 1711–1744, https://doi.org/10.5194/essd-11-1711-2019, 2019.
Shen, Y. and Xiong, A.: Validation and comparison of a new gauge-based precipitation analysis over mainland China, Int. J. Climatol., 36, 252–265, 2016.
Shen, Y., Zhao, P., Pan, Y., and Yu, J.: A high spatiotemporal gauge-satellite merged precipitation analysis over China, J. Geophys. Res.-Atmos., 119, 3063–3075, 2014.
Skofronick-Jackson, G., Petersen, W. A., Berg, W., Kidd, C., Stocker, E. F., Kirschbaum, D. B., Kakar, R., Braun, S. A., Huffman, G. J., Lguchi, T., Kirstetter, P. E., Kummerow, C., Meneghini, R., Oki, R., Olson, W. S., Takayabu, Y. N., Furukawa, K., and Wilheit, T.: The Global Precipitation Measurement (GPM) mission for science and society, B. Am. Meteorol. Soc., 98, 1679–1695, 2017.
Sorooshian, S., Hsu, K. L., Gao, X., Gupta, H. V., Imam, B., and Braithwaite, D.: Evaluation of PERSIANN system satellite-based estimates of tropical rainfall, B. Am. Meteorol. Soc., 81, 2035–2046, 2000.
Su, J., Lü, H., Zhu, Y., Wang, X., and Wei, G.: Component analysis of errors in four GPM-based precipitation estimations over Mainland China, Remote Sens., 10, 1420, 2018.
Sungmin, O. and Kirstetter, P. E.: Evaluation of diurnal variation of GPM IMERG-derived summer precipitation over the contiguous US using MRMS data, Q. J. Roy. Meteorol. Soc., 144, 270–281, 2018.
Takido, K., Valeriano, O. C. S., Ryo, M., Tanuma, K., Ushio, T., and Kubota, T.: Spatiotemporal evaluation of the gauge-adjusted global satellite mapping of precipitation at the basin scale, J. Meteorol. Soc. Jpn., 94, 185–195, 2016.
Tan, J., Petersen, W. A., Kirstetter, P. E., and Tian, Y.: Performance of IMERG as a function of spatiotemporal scale, J. Hydrometeorol., 18, 307–319, 2017.
Tapiador, F. J., Turk, F. J., Petersen, W., Hou, A. Y., García-Ortega, E., Machado, L. A. T., Angelis, C. F., Salio, P., Kidd, C., Huffman, G. J., and de Castro, M.: Global precipitation measurement: methods, datasets and applications, Atmos. Res., 105, 70–97, 2012.
Tian, Y. and Peters-Lidard, C. D.: A global map of uncertainties in satellite-based precipitation measurements, Geophys. Res. Lett., 37, L24407, https://doi.org/10.1029/2010GL046008, 2010.
Tian, Y., Peters-Lidard, C. D., Eylander, J. B., Joyce, R. J., Huffman, G. J., Adler, R. F., Hsu, K. L., Turk, F. J., Garcia, M., and Zeng, J.: Component analysis of errors in satellite-based precipitation estimates, J. Geophys. Res.-Atmos., 114, D24101, https://doi.org/10.1029/2009JD011949, 2009.
Tian, Y., Peters-Lidard, C. D., and Eylander, J. B.: Real-Time Bias Reduction for Satellite-Based Precipitation Estimates, J. Hydrometeorol., 11, 1275–1285, 2010.
Ushio, T., Sasashige, K., Kubota, T., Shige, S., Okamoto, K. I., Aonashi, K., Inoue, T., Takahashi, N., Iguchi, T., Kachi, M., Oki, R., Morimoto, T., and Kawasaki, Z. I.: A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive microwave and infrared radiometric data, J. Meteorol. Soc. Jpn. Ser. II, 87, 137–151, 2009.
Willmott, J.: On the validation of model, Phys. Geogr., 2, 184–194, 1981.
Xie, P., Chen, M., Yang, S., Yatagai, A., Hayasaka, T., Fukushima, Y., and Liu, C.: A gauge-based analysis of daily precipitation over East Asia, J. Hydrometeorol., 8, 607–626, 2007.
Xu, R., Tian, F., Yang, L., Hu, H., Lu, H., and Hou, A.: Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over southern Tibetan Plateau based on a high-density rain gauge network, J. Geophys. Res.-Atmos, 122, 910–924, 2017.
Xu, S., Shen, Y., and Du, Z.: Tracing the source of the errors in hourly IMERG using a decomposition evaluation scheme, Atmosphere, 7, 161, https://doi.org/10.3390/atmos7120161, 2016.
Yamamoto, M. K. and Shige, S.: Implementation of an orographic/nonorographic rainfall classification scheme in the GSMaP algorithm for microwave radiometers, Atmos. Res., 163, 36–47, 2015.
Yong, B., Ren, L., Hong, Y., Wang, J. H., Gourley, J. J., Jiang, S., Chen, X., and Wang, W.: Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: A case study in Laohahe basin, China, Water Resour. Res., 46, W07542, https://doi.org/10.1029/2009WR008965, 2010.
Yong, B., Ren, L., Hong, Y., Gourley, J. J., Tian, Y., Huffman, G. J., Chen X., Wang W. G., and Wen, Y. X.: First evaluation of the climatological calibration algorithm in the real-time TMPA precipitation estimates over two basins at high and low latitudes, Water Resour. Res., 49, 2461–2472, 2013.
Yong, B., Liu, D., Gourley, J. J., Tian, Y., Huffman, G. J., Ren, L., and Hong, Y.: Global view of real-time TRMM multisatellite precipitation analysis: Implications for its successor global precipitation measurement mission, B. Am. Meteorol. Soc., 96, 283–296, 2015.
Yong, B., Chen, B., Tian, Y., Yu, Z., and Hong, Y.: Error-component analysis of TRMM-based multi-satellite precipitation estimates over mainland China, Remote Sens., 8, 440, https://doi.org/10.3390/rs8050440, 2016.
Zhang, J., Howard, K., Langston, C., Kaney, B., Qi, Y., Tang, L., Grams, H., Wang, D., Cocks, S., Martinaitis, S., Arthur, A., Cooper, K., Brogden, J., and Kitzmiller, D.: Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation: Initial operating capabilities, B. Am. Meteorol. Soc., 97, 621–638, 2016.