Spatiotemporal analyses of temperature and equivalent temperature and their relationship with crop health across Pakistan’s cropland

Spatiotemporal variations in temperature (T) and equivalent temperature (Te) significantly impact agricultural production across Pakistan, highlighting the need for enhanced weather and climate modeling. This study utilized four reanalysis datasets spanning a 38-year period (1981–2018): the fifth-generation European Center for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5), Interim ECMWF reanalysis (ERA-Interim), Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), and the Japanese 55-year reanalysis (JRA55). We employed National Oceanic and Atmospheric Administration/Advanced Very High-Resolution Radiometer (NOAA/AVHRR) Normalized Difference Vegetation Index (NDVI) data, a proxy for crop health, to assess the relationship between T, Te, and NDVI. This relationship is examined via regression and correlation analyses, and significance is assessed using the Mann–Kendall test and t-test. Our results show that near-surface T significantly contributes to the magnitude of Te (> 90%), whereas specific humidity (SH) has a smaller impact (< 10%). Both T and Te increase significantly across the entire tropospheric column, at 0.15 – 0.31 and 0.38 – 0.77 °C/decade, respectively. Notably, the mid-tropospheric level exhibits less warming than the upper and lower tropospheric levels. Correlation analyses of T and Te with NDVI reveal that Te exhibits a significantly stronger relationship with NDVI compared to T on both seasonal and annual timescales. The highest correlation occurs in the warm and humid summer monsoon (June – August), with Te showing a correlation of 0.50 and T correlating at 0.22 with NDVI. This study suggests that Te can serve as an additional metric for analysing near-surface heating trends in relation to crop health.