dor_id: 4119661

506.#.#.a: Público

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)

561.#.#.u: https://www.atmosfera.unam.mx/

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

351.#.#.b: Atmósfera

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

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

590.#.#.c: Open Journal Systems (OJS)

270.#.#.d: MX

270.1.#.d: México

590.#.#.b: Concentrador

883.#.#.u: https://revistas.unam.mx/catalogo/

883.#.#.a: Revistas UNAM

590.#.#.a: Coordinación de Difusión Cultural

883.#.#.1: https://www.publicaciones.unam.mx/

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.52499/46668

100.1.#.a: Das, Prabir Kumar; Das, Dilip Kumar; Midya, Subrata Kumar; Bandyopadhyay, Soumya; Raj, Uday

524.#.#.a: Das, Prabir Kumar, et al. (2020). Spatial analysis of wet spell probability over India (1971-. Atmósfera; Vol. 33 No. 1, 2020; 19-31. Recuperado de https://repositorio.unam.mx/contenidos/4119661

245.1.0.a: Spatial analysis of wet spell probability over India (1971-

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

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

264.#.0.c: 2020

264.#.1.c: 2019-12-13

653.#.#.a: Markov chain; wet spell probability; probable wet week; Indian summer monsoon; rainfall

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.52499

001.#.#.#: 022.oai:ojs.pkp.sfu.ca:article/52499

041.#.7.h: eng

520.3.#.a: The spatial analysis of the wet spell probability over the Indian region has been carried out using daily gridded (0.5º × 0.5º) rainfall data of 1971-2005 during the summer monsoon period, i.e. June-September. A threshold was applied to the weekly cumulative rainfall to convert the rainfall data into wet spell information. A Markov chain model was employed to estimate the initial and conditional probabilities of the wet spell for each grid and the spatio-temporal distribution of the wet spells probabilities was analyzed. The probability maps were able to capture the summer monsoon scenario over the Indian region, representing the onset, progression and withdrawal of monsoon rainfall. Higher wet spell probability was observed over the west coast and northeastern parts of India, i.e., the initial probability was maximum over these regions. However, lower probability values were observed in West Rajasthan, Gujarat and southern India. A threshold of 80% of the maximum initial probability was used to standardize the spatially-variable probability information, and a week with more than the threshold values was considered as a probable wet week. The duration of the longest probable wet spell was highest along the west coast and in northeastern India, whereas it was lowest in western and southern India. The start and duration of the longest spell of the probable wet week can be used for rainfed-agricultural planning, i.e., the start of sowing/planting, selection of crops and varieties based on their length of growing period, optimum harvesting period to avoid wet spell, etc.

773.1.#.t: Atmósfera; Vol. 33 No. 1 (2020); 19-31

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: 19-31

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

doi: https://doi.org/10.20937/ATM.52499

handle: 00c2cd5861b4a998

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

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file_creation_date: 2019-12-13 15:04:09.0

file_modification_date: 2019-12-13 15:04:40.0

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

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license_type: by-nc

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Artículo

Spatial analysis of wet spell probability over India (1971-

Das, Prabir Kumar; Das, Dilip Kumar; Midya, Subrata Kumar; Bandyopadhyay, Soumya; Raj, Uday

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

Das, Prabir Kumar, et al. (2020). Spatial analysis of wet spell probability over India (1971-. Atmósfera; Vol. 33 No. 1, 2020; 19-31. Recuperado de https://repositorio.unam.mx/contenidos/4119661

Descripción del recurso

Autor(es)
Das, Prabir Kumar; Das, Dilip Kumar; Midya, Subrata Kumar; Bandyopadhyay, Soumya; Raj, Uday
Tipo
Artículo de Investigación
Área del conocimiento
Físico Matemáticas y Ciencias de la Tierra
Título
Spatial analysis of wet spell probability over India (1971-
Fecha
2019-12-13
Resumen
The spatial analysis of the wet spell probability over the Indian region has been carried out using daily gridded (0.5º × 0.5º) rainfall data of 1971-2005 during the summer monsoon period, i.e. June-September. A threshold was applied to the weekly cumulative rainfall to convert the rainfall data into wet spell information. A Markov chain model was employed to estimate the initial and conditional probabilities of the wet spell for each grid and the spatio-temporal distribution of the wet spells probabilities was analyzed. The probability maps were able to capture the summer monsoon scenario over the Indian region, representing the onset, progression and withdrawal of monsoon rainfall. Higher wet spell probability was observed over the west coast and northeastern parts of India, i.e., the initial probability was maximum over these regions. However, lower probability values were observed in West Rajasthan, Gujarat and southern India. A threshold of 80% of the maximum initial probability was used to standardize the spatially-variable probability information, and a week with more than the threshold values was considered as a probable wet week. The duration of the longest probable wet spell was highest along the west coast and in northeastern India, whereas it was lowest in western and southern India. The start and duration of the longest spell of the probable wet week can be used for rainfed-agricultural planning, i.e., the start of sowing/planting, selection of crops and varieties based on their length of growing period, optimum harvesting period to avoid wet spell, etc.
Tema
Markov chain; wet spell probability; probable wet week; Indian summer monsoon; rainfall
Idioma
eng
ISSN
ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236

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