A Step towards Integrating CMORPH Precipitation Estimation with Rain Gauge Measurements
| Autor: | Claudio dos Santos Amaral, Augusto José Pereira Filho, Guilherme Vemado, Oswaldo Augusto Filho, Eymar Silva Sampaio Lopes, Rodrigo Irineu Cerri, Marcelo Fischer Gramani, Leandro Eugenio da Silva Cerri, Cláudia Cristina dos Santos, Fernando Mazo D'Affonseca, Fábio Augusto Gomes Vieira Reis, Felipe Vemado, Agostinho Tadashi Ogura, Lucilia do Carmo Giordano, José Eduardo Zaine |
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| Přispěvatelé: | Universidade de São Paulo (USP), Universidade Estadual Paulista (Unesp), Inst Nacl Pesquisas Espaciais, Inst Pesquisas Tecnol, Eberhard Karls Univ Tubingen, Petrobras Res & Dev Ctr |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Atmospheric Science
Watershed Article Subject 010504 meteorology & atmospheric sciences Rain gauge 0208 environmental biotechnology 02 engineering and technology Structural basin lcsh:QC851-999 01 natural sciences Pollution Standard deviation 020801 environmental engineering Water resources CHUVA Geophysics Hydrology (agriculture) Climatology Environmental science Hydrometeorology lcsh:Meteorology. Climatology Precipitation 0105 earth and related environmental sciences |
| Zdroj: | Advances in Meteorology, Vol 2018 (2018) Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP Web of Science Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| ISSN: | 1687-9317 1687-9309 |
| Popis: | Made available in DSpace on 2019-10-06T02:14:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01 Petrobras Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Accurate daily rainfall estimation is required in several applications such as in hydrology, hydrometeorology, water resources management, geomorphology, civil protection, and agriculture, among others. CMORPH daily rainfall estimations were integrated with rain gauge measurements in Brazil between 2000 and 2015, in order to reduce daily rainfall estimation errors by means of the statistical objective analysis scheme (SOAS). Early comparisons indicated high discrepancies between daily rain gauge rainfall measurements and respective CMORPH areal rainfall accumulation estimates that tended to be reduced with accumulation time span (e.g., yearly accumulation). Current results show CMORPH systematically underestimates daily rainfall accumulation along the coastal areas. The normalized error variance (NEXERVA) is higher in sparsely gauged areas at Brazilian North and Central-West regions. Monthly areal rainfall averages and standard deviation were obtained for eleven Brazilian watersheds. While an overall negative tendency (3mmh(-1)) was estimated, the Amazon watershed presented a long-term positive tendency. Monthly areal mean precipitation and respective spatial standard deviation closely follow a power-law relationship for data-rich watersheds, i.e., with denser rain gauge networks. Daily SOAS rainfall accumulation was also used to calculate the spatial distribution of frequencies of 3-day rainfall episodes greater than 100mm. Frequencies greater than 3% were identified downwind of the Peruvian Andes, the Bolivian Amazon Basin, and the La Plata Basin, as well as along the Brazilian coast, where landslides are recurrently triggered by precipitation. Univ Sao Paulo, Inst Astron Geofis & Ciencias Atmosfer, Dept Ciencias Atmosfer, Sao Paulo, Brazil Univ Estadual Paulista, Inst Geociencias & Ciencias Exatas, Sao Paulo, Brazil Inst Nacl Pesquisas Espaciais, Sao Paulo, Brazil Inst Pesquisas Tecnol, Sao Paulo, Brazil Univ Sao Paulo, Escola Engn Sao Carlos, Sao Paulo, Brazil Eberhard Karls Univ Tubingen, Tubingen, Germany Petrobras Res & Dev Ctr, Rio De Janeiro, Brazil Univ Estadual Paulista, Inst Geociencias & Ciencias Exatas, Sao Paulo, Brazil Petrobras: 2014/00438-9 CNPq: 302349/2017-6 |
| Databáze: | OpenAIRE |
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