Citation

BibTex format

@article{Derin:2016:10.1175/JHM-D-15-0197.1,
author = {Derin, Y and Anagnostou, E and Berne, A and Borga, M and Boudevillain, B and Buytaert, W and Chang, CH and Delrieu, G and Hong, Y and Hsu, YC and Lavado-Casimiro, W and Manz, B and Moges, S and Nikolopoulos, EI and Sahlu, D and Salerno, F and Rodríguez-Sánchez, JP and Vergara, HJ and Yilmaz, KK},
doi = {10.1175/JHM-D-15-0197.1},
journal = {Journal of Hydrometeorology},
pages = {1817--1836},
title = {Multiregional Satellite Precipitation Products Evaluation over Complex Terrain},
url = {http://dx.doi.org/10.1175/JHM-D-15-0197.1},
volume = {17},
year = {2016}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network.
AU - Derin,Y
AU - Anagnostou,E
AU - Berne,A
AU - Borga,M
AU - Boudevillain,B
AU - Buytaert,W
AU - Chang,CH
AU - Delrieu,G
AU - Hong,Y
AU - Hsu,YC
AU - Lavado-Casimiro,W
AU - Manz,B
AU - Moges,S
AU - Nikolopoulos,EI
AU - Sahlu,D
AU - Salerno,F
AU - Rodríguez-Sánchez,JP
AU - Vergara,HJ
AU - Yilmaz,KK
DO - 10.1175/JHM-D-15-0197.1
EP - 1836
PY - 2016///
SN - 1525-755X
SP - 1817
TI - Multiregional Satellite Precipitation Products Evaluation over Complex Terrain
T2 - Journal of Hydrometeorology
UR - http://dx.doi.org/10.1175/JHM-D-15-0197.1
UR - http://hdl.handle.net/10044/1/37600
VL - 17
ER -