Multiregional Satellite Precipitation Products Evaluation over Complex Terrain

Autor: Yagmur Derin, Guy Delrieu, Che-Hao Chang, Yung Chia Hsu, Efthymios I. Nikolopoulos, Koray K. Yilmaz, Franco Salerno, Brice Boudevillain, Wouter Buytaert, Humberto Vergara, Dejene Sahlu, Bastian Manz, Emmanouil N. Anagnostou, Alexis Berne, Semu Ayalew Moges, Juan-Pablo Rodriguez-Sanchez, Waldo Lavado-Casimiro, Marco Borga, Yang Hong
Přispěvatelé: Ecole Polytechnique Fédérale de Lausanne (EPFL), Universita degli Studi di Padova, Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Department of Hydraulic Engineering, Tsinghua University [Beijing] (THU), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Tsinghua University [Beijing], Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Imperial College London, British Council (UK)
Rok vydání: 2016
Předmět:
Wet season
Atmospheric Science
010504 meteorology & atmospheric sciences
0208 environmental biotechnology
Weather forecasting
purl.org/pe-repo/ocde/ford#1.05.10 [https]
Terrain
02 engineering and technology
[SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology
computer.software_genre
01 natural sciences
Precipitación
Lluvia
[SDU.STU.PL]Sciences of the Universe [physics]/Earth Sciences/Planetology
Dry season
Satélite meteorológico
Meteorology & Atmospheric Sciences
Precipitation
Cartografía
Hidrometeorología
[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces
environment
ComputingMilieux_MISCELLANEOUS
0105 earth and related environmental sciences
Rain gauge
Tropics
15. Life on land
020801 environmental engineering
Climatología
[SDU]Sciences of the Universe [physics]
13. Climate action
Climatology
Environmental science
Control meteorológico
Satellite
0401 Atmospheric Sciences
Satélite
computer
Zdroj: Journal of Hydrometeorology
Journal of Hydrometeorology, American Meteorological Society, 2016, 17 (6), pp.1817-1836. ⟨10.1175/JHM-D-15-0197.1⟩
Repositorio U. El Bosque
Universidad El Bosque
instacron:Universidad El Bosque
Repositorio Institucional -SENAMHI
Servicio Nacional de Meteorología e Hidrología del Perú
SENAMHI-Institucional
instacron:SENAMHI
ISSN: 1525-7541
1525-755X
Popis: 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.
Databáze: OpenAIRE
Externí odkaz: