dor_id: 4120130

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

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://www.revistascca.unam.mx/atm/index.php/atm/index

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351.#.#.a: Artículos

harvesting_group: RevistasUNAM

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

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270.#.#.d: MX

270.1.#.d: México

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883.#.#.a: Revistas UNAM

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

856.4.0.u: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/8561/8031

100.1.#.a: Luque, A.; Gómez, I.; Manso, M.

524.#.#.a: Luque, A., et al. (2006). Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices. Atmósfera; Vol. 19 No. 3, 2006. Recuperado de https://repositorio.unam.mx/contenidos/4120130

245.1.0.a: Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices

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

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

264.#.0.c: 2006

264.#.1.c: 2009-10-05

653.#.#.a: CRR; rainsat; meteosat; convective rainfall rate; satellite estimated rainfall; radar; calibration matrices; satellite rainfall algorithm; CRR; RAINSAT; METEOSAT; CONVECTIVE RAINFALL RATE; SATELLITE ESTIMATED RAINFALL; RADAR; CALIBRATION MATRICES; SATELLITE RAINFALL ALGORITHM

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

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041.#.7.h: eng

520.3.#.a: The CRR (Convective Rainfall Rate) algorithm was developed to detect intense mesoscale convective cells and to screen the most probable precipitation associated. It estimates rainfall intensity using the three bands of the Meteosat-7 and matrices calibrated with earth-based radars. Calibration matrices were performed following an accurate version of the Rainsat techniques but combining the infrared bands to detect convective clouds. Matrices were developed, up for the North of Europe, over the Baltic countries, with data from the radar of the Baltex Project provided by the SMHI (Swedish Meteorological and Hydrological Institute) and for the South of Europe, over the Iberian Peninsula, with radar data as provided by the INM (Spanish Meteorological Institute). In the present research, the CRR calibration methodology is validated, an analysis of calibration matrices differences in both areas over Europe is detailed and CRR resulting images are verified in a qualitative manner using rainfall radar images as ground true.

773.1.#.t: Atmósfera; Vol. 19 No. 3 (2006)

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

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

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

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245.1.0.b: Convective rainfall rate melti-chanel algorithm for meteosat-7 and radar derived calibration matrices

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Artículo

Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices

Luque, A.; Gómez, I.; Manso, M.

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

Luque, A., et al. (2006). Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices. Atmósfera; Vol. 19 No. 3, 2006. Recuperado de https://repositorio.unam.mx/contenidos/4120130

Descripción del recurso

Autor(es)
Luque, A.; Gómez, I.; Manso, M.
Tipo
Artículo de Investigación
Área del conocimiento
Físico Matemáticas y Ciencias de la Tierra
Título
Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices
Fecha
2009-10-05
Resumen
The CRR (Convective Rainfall Rate) algorithm was developed to detect intense mesoscale convective cells and to screen the most probable precipitation associated. It estimates rainfall intensity using the three bands of the Meteosat-7 and matrices calibrated with earth-based radars. Calibration matrices were performed following an accurate version of the Rainsat techniques but combining the infrared bands to detect convective clouds. Matrices were developed, up for the North of Europe, over the Baltic countries, with data from the radar of the Baltex Project provided by the SMHI (Swedish Meteorological and Hydrological Institute) and for the South of Europe, over the Iberian Peninsula, with radar data as provided by the INM (Spanish Meteorological Institute). In the present research, the CRR calibration methodology is validated, an analysis of calibration matrices differences in both areas over Europe is detailed and CRR resulting images are verified in a qualitative manner using rainfall radar images as ground true.
Tema
CRR; rainsat; meteosat; convective rainfall rate; satellite estimated rainfall; radar; calibration matrices; satellite rainfall algorithm; CRR; RAINSAT; METEOSAT; CONVECTIVE RAINFALL RATE; SATELLITE ESTIMATED RAINFALL; RADAR; CALIBRATION MATRICES; SATELLITE RAINFALL ALGORITHM
Idioma
eng
ISSN
ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236

Enlaces