{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T13:12:08Z","timestamp":1775740328299,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2009,9,11]],"date-time":"2009-09-11T00:00:00Z","timestamp":1252627200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recent advances in the field of remote sensing have led to an increase in available rainfall data on a regional and global scale. Several NASA sponsored satellite missions provide valuable precipitation data. However, the advantages of the data are limited by complications related to the indirect nature of satellite estimates. This study intends to develop a stochastic model for uncertainty analysis of satellite rainfall fields through simulating error fields and imposing them over satellite estimates. In order to examine reliability and performance of the presented model, ensembles of satellite estimates are simulated for a large area across the North and South Carolina. The generated ensembles are then compared with original satellite estimates with respect to statistical properties and spatial dependencies. The results show that the model can be used to describe the uncertainties associated to TRMM multi-satellite precipitation estimates. The presented model is validated using random sub-samples of the observations based on the bootstrap technique. The results indicate that the model performs reasonably well with different numbers of available rain gauges.<\/jats:p>","DOI":"10.3390\/rs1030606","type":"journal-article","created":{"date-parts":[[2009,9,11]],"date-time":"2009-09-11T10:45:00Z","timestamp":1252665900000},"page":"606-619","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":80,"title":["Accounting for Uncertainties of the TRMM Satellite Estimates"],"prefix":"10.3390","volume":"1","author":[{"given":"Amir","family":"AghaKouchak","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, University of Louisiana at Lafayette, PO Box 42291, Lafayette, LA 70504, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nasrin","family":"Nasrollahi","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, University of Louisiana at Lafayette, PO Box 42291, Lafayette, LA 70504, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emad","family":"Habib","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, University of Louisiana at Lafayette, PO Box 42291, Lafayette, LA 70504, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2009,9,11]]},"reference":[{"key":"ref_1","unstructured":"Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, J., and Hanson, C.E. (2007). Climate Change 2007: Impacts, Adaptation, and Vulnerability, Cambridge University Press. Exit EPA Disclaimer Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change."},{"key":"ref_2","unstructured":"Ruddiman, W. (2005). Plows, Plagues and Petroleum: How Humans Took Control of Climate, Princeton University Press."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Miller, C., and Edwards, P. (2001). Changing the Atmosphere: Expert Knowledge and Environmental Governance, MIT Press.","DOI":"10.7551\/mitpress\/1789.001.0001"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/S0022-1694(96)80007-2","article-title":"Modeling the effects of spatial variability in rainfall on catchment response. 2. Experiments with distributed and lumped models","volume":"175","author":"Shah","year":"1996","journal-title":"J. Hydrol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/0022-1694(95)02703-R","article-title":"Measurement and analysis of small-scale convective storm rainfall variability","volume":"173","author":"Goodrich","year":"1995","journal-title":"J. Hydrol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/0022-1694(95)02704-S","article-title":"Impact of small-scale spatial rainfall variability on runoff modeling","volume":"173","author":"Faures","year":"1995","journal-title":"J. Hydrol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/0022-1694(94)90263-1","article-title":"The sensitivity of hydrological models to spatial rainfall patterns: an evaluation using observed data","volume":"159","author":"Obled","year":"1994","journal-title":"J. Hydrol."},{"key":"ref_8","unstructured":"Seliga, T., Aron, G., Aydin, K., and White, E. (,  1992). Simulation using radar rainfall rates and a unit hydrograph model (SYN-HYD) applied to GREVE watershed. Am. Meteor. Soc., 25th Int. Conf. on Radar Hydrology, Paris, France."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/0022-1694(85)90165-9","article-title":"Effect of spatial variability of effective rainfall on direct runoff by geomorphoIogic approach","volume":"81","author":"Corradini","year":"1985","journal-title":"J. Hydrol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/0022-1694(83)90211-1","article-title":"The significance of rainfall in the study of hydrological processes at basin scale","volume":"65","author":"Hamlin","year":"1983","journal-title":"J. Hydrol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1029\/WR019i003p00791","article-title":"Runoff prediction errors and bias in parameter estimation induced by spatial variability of precipitation","volume":"19","author":"Troutman","year":"1983","journal-title":"Water Resour. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"958","DOI":"10.1029\/WR005i005p00958","article-title":"Effect of rainfall variability on strearnflow simulation","volume":"5","author":"Dawdy","year":"1969","journal-title":"Water Resour. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2035","DOI":"10.1175\/1520-0477(2000)081<2035:EOPSSE>2.3.CO;2","article-title":"Evolution of the PERSIANN system satellite-based estimates of tropical rainfall","volume":"81","author":"Sorooshian","year":"2000","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_14","first-page":"1120","article-title":"GOES multispectral rainfall algorithm (GMSRA)","volume":"29","author":"Ba","year":"2001","journal-title":"J. Appl. Meteorol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1175\/1525-7541(2001)002<0036:GPAODD>2.0.CO;2","article-title":"Global precipitation at one-degree daily resolution from multisatellite observations","volume":"2","author":"Huffman","year":"2001","journal-title":"J. Hydrometeorol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1175\/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2","article-title":"The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979\u2013present)","volume":"4","author":"Adler","year":"2003","journal-title":"J. Hydrometeorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","article-title":"CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution","volume":"5","author":"Joyce","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1834","DOI":"10.1175\/JAM2173.1","article-title":"Precipitation estimation from remotely sensed imagery using Artificial Neural Network-Cloud Classification System","volume":"43","author":"Hong","year":"2004","journal-title":"J. Appl. Meteorol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"W08421","DOI":"10.1029\/2005WR004398","article-title":"Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response","volume":"42","author":"Hong","year":"2006","journal-title":"Water Resour. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1175\/2007JHM846.1","article-title":"Satellite rainfall uncertainty estimation using an artificial neural network","volume":"8","author":"Bellerby","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1029\/2005GL023122","article-title":"Using a multi-dimensional satellite rainfall error model to characterize uncertainty in soil moisture fields simulated by an offline land surface model","volume":"32","author":"Hossain","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1175\/JHM454.1","article-title":"Probabilistic and ensemble representations of the uncertainty in an IR\/microwave satellite precipitation product","volume":"6","author":"Bellerby","year":"2005","journal-title":"J. Hydrometeorol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3759","DOI":"10.1175\/1520-0442(2003)016<3759:COTMFE>2.0.CO;2","article-title":"Comparison of two methods for estimating the sampling-related uncertainty of satellite rainfall averages based on a large radar dataset","volume":"16","author":"Steiner","year":"2003","journal-title":"J. Climate"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1111\/j.0033-0124.2000.t01-1-.x","article-title":"Validation and uncertainty analysis of satellite rainfall algorithms","volume":"52","author":"Greene","year":"2000","journal-title":"Prof. Geogr."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1016\/j.cageo.2005.10.006","article-title":"On Latin Hypercube sampling for efficient uncertainty estimation of satellite rainfall observations in flood prediction","volume":"32","author":"Hossain","year":"2006","journal-title":"Comput. Geosci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"19569","DOI":"10.1029\/98JD00309","article-title":"Uncertainty analysis of satellite rainfall algorithms over the tropical Pacific","volume":"103","author":"Morrissey","year":"1998","journal-title":"J. Geophys. Res.-Atmosph."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/S0273-1177(97)00056-2","article-title":"Uncertainty in satellite rainfall estimates: Time series comparison","volume":"19","author":"Chang","year":"1997","journal-title":"Adv. Space Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1016\/j.atmosres.2009.02.004","article-title":"Estimating actual rainfall from satellite rainfall products","volume":"92","author":"Yan","year":"2009","journal-title":"Atmosph. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2195","DOI":"10.1029\/JD095iD03p02195","article-title":"Sampling errors for satellite-derived tropical rainfallMonte Carlo study using a spacetime stochastic model","volume":"95","author":"Bell","year":"1990","journal-title":"J. Geophys. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"677","DOI":"10.5194\/hess-11-677-2007","article-title":"Effect of spatial distribution of daily rainfall on interior catchment response of a distributed hydrological model","volume":"11","author":"Schuurmans","year":"2007","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"29","DOI":"10.5194\/hess-9-29-2005","article-title":"Significance of spatial variability in precipitation for process-oriented modelling: results from two nested catchments using radar and ground station data","volume":"9","author":"Tetzlaff","year":"2005","journal-title":"Hydrolo. Earth Syst. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0022-1694(02)00311-6","article-title":"Spatial characteristics of thunderstorm rainfall fields and their relation to runoff","volume":"271","author":"Syed","year":"2003","journal-title":"J. Hydrol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/S0022-1694(01)00611-4","article-title":"Influence of rainfall spatial variability on flood prediction","volume":"260","author":"Arnaud","year":"2002","journal-title":"J. Hydrol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"653","DOI":"10.5194\/hess-4-653-2000","article-title":"The sensitivity of catchment runoff models to rainfall data at different spatial scales","volume":"4","author":"Bell","year":"2000","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.1175\/2007JHM859.1","article-title":"Multitemporal analysis of TRMM-based satellite precipitation products for land data assimilation applications","volume":"8","author":"Tian","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_36","first-page":"487","article-title":"Assessment of current passive-microwave- and infrared-based satellite rainfall remote sensing for flood prediction","volume":"5","author":"Hossain","year":"2004","journal-title":"J. Geophys. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"L05402","DOI":"10.1029\/2006GL029147","article-title":"Evaluation of the research-version TMPA threehourly 0.25\u00b00.25\u00b0 rainfall estimates over Oklahoma","volume":"34","author":"Villarini","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"AghaKouchak, A., Habib, E., and B\u00e1rdossy, A. (2009). A. Modeling radar rainfall estimation uncertainties: A random error model. J. Hydrol. Eng., in press.","DOI":"10.1061\/(ASCE)HE.1943-5584.0000185"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Villarini, G., Krajewski, W., Ciach, G., and Zimmerman, D. (2009). Product-Error-Driven generator of probable rainfall conditioned on WSR-88D precipitation estimates. Water Resour. Res., 45.","DOI":"10.1029\/2008WR006946"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1175\/2007JHM814.1","article-title":"Product-error-driven uncertainty model for probabilistic quantitative precipitation estimation with NEXRAD data","volume":"8","author":"Ciach","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_41","unstructured":"Germann, U., Berenguer, M., Sempere-Torres, D., and Salvade, G. (2006, January September). Ensemble radar precipitation estimation - a new topic on the radar horizon. Proc. 4th European Conference on Radar in Meteorology and Hydrology ERAD 2006, Barcelon, Spain."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Clark, M., Gangopadhyay, S., Brandon, D., Werner, K., Hay, L., Rajagopalan, B., and Yates, D. (2004). A resampling procedure for generating conditioned daily weather sequences. Water Resour. Res., 40.","DOI":"10.1029\/2003WR002747"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1175\/1525-7541(2004)005<0243:TSSAMF>2.0.CO;2","article-title":"Schaake shuffle: A method for econstructing space-time variability in forecasted precipitation and temperature fields","volume":"5","author":"Clark","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"175","DOI":"10.5194\/hess-5-175-2001","article-title":"Downscaling rainfields in space and time using the String of Beads model in time series mode","volume":"5","author":"Pegram","year":"2001","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_45","first-page":"31623","article-title":"A space and time model for design storm rainfall","volume":"104","author":"Seed","year":"2001","journal-title":"J. Geophys. Res."},{"key":"ref_46","first-page":"1191","article-title":"Estimates of root-mean-square random error for finite samples of estimated precipitation","volume":"36","author":"Huffman","year":"1997","journal-title":"J. Hydrometeorol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1029\/WR021i005p00764","article-title":"Synthesis of radar rainfall data","volume":"21","author":"Krajewski","year":"1985","journal-title":"Water Resour. Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM Multi-satellite Precipitation Analysis: Quasi-global, multiyear, combined-sensor precipitation estimates at fine scale","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Habib, E., Henschke, A., and Adler, R. (2009). Evaluation of TMPA satellite-based research and real-time rainfall estimates during six tropical-related heavy rainfall events over Louisiana, USA. Atmosph. Res.","DOI":"10.1016\/j.atmosres.2009.06.015"},{"key":"ref_50","unstructured":"Spearman, C.E. Available on line at: http:\/\/www.archive.org\/stream\/proofmeasurement00speauoft#page\/n33\/mode\/2up."},{"key":"ref_51","unstructured":"Hollander, M., and Wolfe, D. (1973). Nonparametric Statistical Methods, Wiley."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/1\/3\/606\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T22:11:09Z","timestamp":1760220669000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/1\/3\/606"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,9,11]]},"references-count":51,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2009,9]]}},"alternative-id":["rs1030606"],"URL":"https:\/\/doi.org\/10.3390\/rs1030606","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,9,11]]}}}