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590.#.#.d: Los artículos enviados a la revista "Atmósfera", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Consejo Nacional de Ciencia y Tecnología (CONACyT); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Scientific Electronic Library Online (SciELO); SCOPUS, Web Of Science (WoS); SCImago Journal Rank (SJR)

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650.#.4.x: Físico Matemáticas y Ciencias de la Tierra

336.#.#.b: article

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336.#.#.a: Artículo

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270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

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270.#.#.d: MX

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883.#.#.a: Revistas UNAM

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883.#.#.q: Dirección General de Publicaciones y Fomento Editorial

850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/ATM.2015.28.01.05/40890

100.1.#.a: Gairola, R. M.; Prakash, Satya; Pal, P. K.

524.#.#.a: Gairola, R. M., et al. (2015). Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data. Atmósfera; Vol. 28 No. 1, 2015; 51-61. Recuperado de https://repositorio.unam.mx/contenidos/11180

245.1.0.a: Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM

264.#.0.c: 2015

264.#.1.c: 2015-01-13

653.#.#.a: Indian monsoon region; INSAT Multispectral Rainfall Algorithm; rain gauge; objective analysis

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC 4.0 Internacional, https://creativecommons.org/licenses/by-nc/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico editora@atmosfera.unam.mx

884.#.#.k: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/ATM.2015.28.01.05

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041.#.7.h: eng

520.3.#.a: In this paper, an attempt has been made to estimate rainfall over the Indian monsoon region by the synergistic use of the geostationary Kalpana-1 satellite-derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates and rain gauge data, using a successive correction method in order to further refine the operational IMSRA rainfall estimates. The successive correction method benefits from high spatial and temporal resolutions of the Kalpana-1 satellite and accurate rainfall estimates from rain gauges. A preliminary analysis is done for the southwest monsoon season of 2010 at a daily scale. The successive correction method is applied at a 1º latitude × 1º longitude resolution determined by the spatial autocorrelation analysis. Results are compared with four independent global multisatellite rainfall products, namely the Global Satellite Mapping of Precipitation, the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis near-real time and research version rainfall monitoring products, and the Global Precipitation Climatology Project rainfall product. The objectively analyzed rainfall estimates show noticeable improvement over the satellite-based rainfall estimates alone over southern India. Comparison with independent rain gauge observations shows a considerable improvement in terms of correlation, bias and root-mean-square error after objective analysis, especially over the regions where density of rain gauge is fairly good. Overall results reveal that the synergistic use of satellite and in situ observations has potential for more accurate rainfall estimations over the Indian monsoon region.

773.1.#.t: Atmósfera; Vol. 28 No. 1 (2015); 51-61

773.1.#.o: https://www.revistascca.unam.mx/atm/index.php/atm/index

046.#.#.j: 2021-10-20 00:00:00.000000

022.#.#.a: ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236

310.#.#.a: Trimestral

300.#.#.a: Páginas: 51-61

264.#.1.b: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM

doi: https://doi.org/10.20937/ATM.2015.28.01.05

handle: 01c5f3ff94c76184

harvesting_date: 2023-06-20 16:00:00.0

856.#.0.q: application/pdf

last_modified: 2023-06-20 16:00:00

license_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode.es

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Artículo

Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

Gairola, R. M.; Prakash, Satya; Pal, P. K.

Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM, publicado en Atmósfera, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Entidad o dependencia
Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
Revista
Repositorio
Contacto
Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

Cita

Gairola, R. M., et al. (2015). Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data. Atmósfera; Vol. 28 No. 1, 2015; 51-61. Recuperado de https://repositorio.unam.mx/contenidos/11180

Descripción del recurso

Autor(es)
Gairola, R. M.; Prakash, Satya; Pal, P. K.
Tipo
Artículo de Investigación
Área del conocimiento
Físico Matemáticas y Ciencias de la Tierra
Título
Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data
Fecha
2015-01-13
Resumen
In this paper, an attempt has been made to estimate rainfall over the Indian monsoon region by the synergistic use of the geostationary Kalpana-1 satellite-derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates and rain gauge data, using a successive correction method in order to further refine the operational IMSRA rainfall estimates. The successive correction method benefits from high spatial and temporal resolutions of the Kalpana-1 satellite and accurate rainfall estimates from rain gauges. A preliminary analysis is done for the southwest monsoon season of 2010 at a daily scale. The successive correction method is applied at a 1º latitude × 1º longitude resolution determined by the spatial autocorrelation analysis. Results are compared with four independent global multisatellite rainfall products, namely the Global Satellite Mapping of Precipitation, the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis near-real time and research version rainfall monitoring products, and the Global Precipitation Climatology Project rainfall product. The objectively analyzed rainfall estimates show noticeable improvement over the satellite-based rainfall estimates alone over southern India. Comparison with independent rain gauge observations shows a considerable improvement in terms of correlation, bias and root-mean-square error after objective analysis, especially over the regions where density of rain gauge is fairly good. Overall results reveal that the synergistic use of satellite and in situ observations has potential for more accurate rainfall estimations over the Indian monsoon region.
Tema
Indian monsoon region; INSAT Multispectral Rainfall Algorithm; rain gauge; objective analysis
Idioma
eng
ISSN
ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236

Enlaces