dor_id: 11225

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.2018.31.03.06/46622

100.1.#.a: Ahmed, Kamal; Shahid, Shamsuddin; Ismail, Tarmizi; Nawaz, Nadeem; Wang, Xiao-jun

524.#.#.a: Ahmed, Kamal, et al. (2018). Absolute homogeneity assessment of precipitation time series in an arid region of Pakistan. Atmósfera; Vol. 31 No. 3, 2018; 301-316. Recuperado de https://repositorio.unam.mx/contenidos/11225

720.#.#.a: Dr. Shamsuddin Shahid, University Technology Malaysia

245.1.0.a: Absolute homogeneity assessment of precipitation time series in an arid region of Pakistan

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

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

264.#.0.c: 2018

264.#.1.c: 2018-06-29

653.#.#.a: Absolute homogeneity; precipitation; hypothesis test; arid region; Balochistan

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.2018.31.03.06

001.#.#.#: 022.oai:ojs.pkp.sfu.ca:article/52340

041.#.7.h: eng

520.3.#.a: Homogeneity evaluations are usually performed on the total annual precipitation data, which often fails to detect non-homogeneity in seasonal precipitation. Furthermore, it is required to assess homogeneity using multiple methods as the performance of homogeneity testing methods depend on the distribution of the data. This is particularly important for the arid region where distributions of seasonal and annual rainfall are often non-normal. The homogeneity of annual and monthly precipitation datasets of 14 meteorological stations located in the arid region of Pakistan was assessed in this study using the Pettitt’s test, the standard normal homogeneity test (SNHT), the cumulative deviation test, the von Neumann’s ratio test, the Bayesian test, the Worsley’s likelihood ratio test, and Student’s t-test at a 95% confidence level. The rainfall series were categorized into three classes, namely “useful”, “doubtful” and “suspect” based on the results of different homogeneity tests. Results suggest that rainfall time series for most of the months in all the stations are useful. The rainfall time series are found doubtful for the month of June at two stations, for April at one station, and suspect for November at only one station. On the other hand, the annual series were found useful at 12 stations and suspect at two stations. Comparison of different homogeneity tests revealed that SNHT and Worsley’s tests are the most sensitive, and cumulative deviation test is the least sensitive to changes in monthly precipitation data. In the case of annual series, the von Neumann’s test was found most sensitive compared to other tests.

773.1.#.t: Atmósfera; Vol. 31 No. 3 (2018); 301-316

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: 301-316

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

doi: https://doi.org/10.20937/ATM.2018.31.03.06

handle: 289d755880ebaf9a

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

license_type: by-nc

_deleted_conflicts: 2-8bbd1f2e61e03f5d7a7b9309c9d039ac

No entro en nada

No entro en nada 2