Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought

Drought is probably the most multifaceted environmental disaster that results from a precipitation deficiency. It perhaps has directly and indirectly potential effects on people's lives, economy, other resources worldwide. However, for reducing negative impacts of drought, understanding information about seasonal drought frequency persistence are crucial early warning mitigations policies. Therefore, current research examines selected stations' meteorological persistence. For this purpose, ordinal outcomes modelled under set cumulative Logit Models (CLM). The estimation CLM made logit link function. Further, Brant Test (BT) used to check parallel line assumptions. BT substantiates odds ratios same across several classes. Thereby POM ubiquitous choice analysis. Proportional Odds Model (POM) utilized compute Probability Persistence (PDP) in varying seasons (March, April, May (Spring); June, July, August (Summer); September, October, November (Autumn); December, January, February (Winter). Standardized Precipitation Index (SPI) certain time scale (i.e. three-month SPI-3) mainly POM. Amid SPI various seasons, relationship found significant at 5% significance level stations, including Murree, Rawalpindi, Sialkot, Sargodha, Faisalabad, Bahawalnagar, Bahawalpur, Mianwali, Jhelum Multan, Khanpur, Lahore. substantiated by twelve stations province Punjab, Pakistan. provide direction dynamically identify spatial interseasonal propagation drought. Moreover, obtained can be helpful making useful policies system, risk assessment, management, formulating drought-reducing plans.