Phenology forcing model to estimate phenology shifting ability of extreme environmental events - Ahmad, Aqeel; Liu, Yujie (Frontiers in Plant Science, 2022)
The current study considered the climate extreme index (CEI) values originated from extreme environmental events (EEEs) by following the NOAA- the National Oceanic and Atmospheric Administration 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 (Psi). Finally, the CEIs, and the Psi were undergone the development of the phenology forcing (PF) model. The developed model showed a high sensitivity at the CEI value of as low as ≥1.0. Furthermore, the uncertainty index varied between 0.03-0.07, 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).