Articles | Volume 18, issue 12
https://doi.org/10.5194/hess-18-5077-2014
https://doi.org/10.5194/hess-18-5077-2014
Research article
 | 
11 Dec 2014
Research article |  | 11 Dec 2014

Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications

H. Seyyedi, E. N. Anagnostou, E. Beighley, and J. McCollum

Related authors

Brief communication: Storm Daniel flood impact in Greece in 2023: mapping crop and livestock exposure from synthetic-aperture radar (SAR)
Kang He, Qing Yang, Xinyi Shen, Elias Dimitriou, Angeliki Mentzafou, Christina Papadaki, Maria Stoumboudi, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 24, 2375–2382, https://doi.org/10.5194/nhess-24-2375-2024,https://doi.org/10.5194/nhess-24-2375-2024, 2024
Short summary
A global forest burn severity dataset from Landsat imagery (2003–2016)
Kang He, Xinyi Shen, and Emmanouil N. Anagnostou
Earth Syst. Sci. Data, 16, 3061–3081, https://doi.org/10.5194/essd-16-3061-2024,https://doi.org/10.5194/essd-16-3061-2024, 2024
Short summary
To What Extent Do Extreme Storm Events Change Future Flood Hazards?
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
EGUsphere, https://doi.org/10.5194/egusphere-2023-1969,https://doi.org/10.5194/egusphere-2023-1969, 2023
Short summary
Predictive Understanding of Socioeconomic Flood Impact in Data-Scarce Regions Based on Channel Properties and Storm Characteristics: Application in High Mountain Asia (HMA)
Mariam Khanam, Giulia Sofia, Wilmalis Rodriguez, Efthymios I. Nikolopoulos, Binghao Lu, Dongjin Song, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-120,https://doi.org/10.5194/nhess-2023-120, 2023
Revised manuscript under review for NHESS
Short summary
Improving fire severity prediction in south-eastern Australia using vegetation specific information
Kang He, Xinyi Shen, Cory Merow, Efthymios Nikolopoulos, Rachael V. Gallagher, Feifei Yang, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-69,https://doi.org/10.5194/nhess-2023-69, 2023
Revised manuscript accepted for NHESS
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Stochastic approaches
Assessing downscaling techniques for frequency analysis, total precipitation and rainy day estimation in CMIP6 simulations over hydrological years
David A. Jimenez, Andrea Menapace, Ariele Zanfei, Eber José de Andrade Pinto, and Bruno Brentan
Hydrol. Earth Syst. Sci., 28, 1981–1997, https://doi.org/10.5194/hess-28-1981-2024,https://doi.org/10.5194/hess-28-1981-2024, 2024
Short summary
Simulating sub-hourly rainfall data for current and future periods using two statistical disaggregation models: case studies from Germany and South Korea
Ivan Vorobevskii, Jeongha Park, Dongkyun Kim, Klemens Barfus, and Rico Kronenberg
Hydrol. Earth Syst. Sci., 28, 391–416, https://doi.org/10.5194/hess-28-391-2024,https://doi.org/10.5194/hess-28-391-2024, 2024
Short summary
Synoptic weather patterns conducive to compound extreme rainfall–wave events in the NW Mediterranean
Marc Sanuy, Juan C. Peña, Sotiris Assimenidis, and José A. Jiménez
Hydrol. Earth Syst. Sci., 28, 283–302, https://doi.org/10.5194/hess-28-283-2024,https://doi.org/10.5194/hess-28-283-2024, 2024
Short summary
Exploring the joint probability of precipitation and soil moisture over Europe using copulas
Carmelo Cammalleri, Carlo De Michele, and Andrea Toreti
Hydrol. Earth Syst. Sci., 28, 103–115, https://doi.org/10.5194/hess-28-103-2024,https://doi.org/10.5194/hess-28-103-2024, 2024
Short summary
Water cycle changes in Czechia: a multi-source water budget perspective
Mijael Rodrigo Vargas Godoy, Yannis Markonis, Oldrich Rakovec, Michal Jenicek, Riya Dutta, Rajani Kumar Pradhan, Zuzana Bešťáková, Jan Kyselý, Roman Juras, Simon Michael Papalexiou, and Martin Hanel
Hydrol. Earth Syst. Sci., 28, 1–19, https://doi.org/10.5194/hess-28-1-2024,https://doi.org/10.5194/hess-28-1-2024, 2024
Short summary

Cited articles

Adler, R. F., Kidd, C., Petty, G., Morissey, M., and Goodman, H. M.: Intercomparison of Global Precipitation Products: The Third Precipitation Intercomparison Project (PIP–3), B. Am. Meteorol. Soc., 82, 1377–1396, https://doi.org/10.1175/1520-0477(2001)082<1377:IOGPPT>2.3.CO;2, 2001.
AghaKouchak, A., Nasrollahi, N., and Habib, E.: Accounting for Uncertainties of the TRMM Satellite Estimates, Remote Sens., 1, 606–619, 2009.
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.
Bastola, S. and Misra, V.: Evaluation of dynamically downscaled reanalysis precipitation data for hydrological application, Hydrol. Process., 28, 1989–2002, https://doi.org/10.1002/hyp.9734, 2014.
Behrangi, A., Khakbaz, B., Jaw, T. C., AghaKouchak, A., Hsu, K., and Sorooshian, S.: Hydrologic evaluation of satellite precipitation products over a mid-size basin, J. Hydrol., 397, 225–237, https://doi.org/10.1016/j.jhydrol.2010.11.043, 2011.
Download
Short summary
The paper presents a methodology for using global precipitation products from satellite remote sensing to error-correct and downscale global atmospheric reanalysis precipitation data sets. It is shown that streamflow simulations from the satellite-adjusted precipitation reanalysis give similar statistics to the ones derived by high-resolution ground-based radar rainfall data sets. This approach can be applied globally to derive improved flood frequency maps over data-poor areas.