Malawi, like many other countries, faces growing challenges from climate variability and water scarcity. Despite advancements in remote sensing and meteorological data collection, comprehensive mapping and analysis of climatic water deficit remain limited. This study addresses this gap by investigating the spatial-temporal dynamics of meteorological water deficit in Malawi, utilising Moderate Resolution Imaging Spectroradiometer (MODIS) and gridded datasets. Through the application of Google Earth Engine and cartographic scripting, the research offers a detailed analysis of interrelated variables such as Land Surface Temperature (LST), air temperature, precipitation, and evapotranspiration, revealing regional disparities, and temporal trends in water availability. The results highlight significant spatial-temporal variations in temperature, with notable increases in LST during the dry season. Although general precipitation increases across the country during the study period, water deficit conditions persist. Furthermore, the study identifies substantial differences in actual evapotranspiration between northern and southern regions, reflecting varying water deficit impacts on LST. Future research priorities include developing national climate adaptation strategies using machine learning techniques to enhance resilience against climate variability.