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Phenology forcing model to estimate phenology shifting ability of extreme environmental events

The current study considered the climate extreme index (CEI) values originated from extreme environmental events (EEEs) by following the National Oceanic and Atmospheric Administration (NOAA) guidelines. The EEEs were fractionated into six sub-categories (i.e., high temperature, low temperature, hig...

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Detalles Bibliográficos
Autores principales: Ahmad, Aqeel, Liu, Yujie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9493310/
https://www.ncbi.nlm.nih.gov/pubmed/36160991
http://dx.doi.org/10.3389/fpls.2022.961335
Descripción
Sumario:The current study considered the climate extreme index (CEI) values originated from extreme environmental events (EEEs) by following the National Oceanic and Atmospheric Administration (NOAA) guidelines. The EEEs were fractionated into six sub-categories (i.e., high temperature, low temperature, high precipitation, low precipitation, drought, and wind), and the combined impact of CEIs was utilized to develop an algorithm for the estimation of the phenology sensitivity index (P(Si)). Finally, the CEIs, and the P(Si) were undergone the development of the phenology forcing (P(F)) model. The developed model showed a high sensitivity at the CEI value of as low as ≥1.0. Furthermore, the uncertainty index varied between 0.03 and 0.07, making a parabolic curvature at increasing CEIs (1.0–15.0). The current study precisely estimates the tendency of EEEs for phenology change. It will assist in policy-making and planning crop cultivation plans for achieving sustainable development goal 2 (SDG2) of the Food and Agriculture Organization (FAO).