Satellite precipitation product: Applicability and accuracy evaluation in diverse region

Satellite precipitation products, e.g., Tropical Rainfall Measuring Mission version-07 (hereafter TRMM) and its successor Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (hereafter IMERG) are being used at a global scale for rainfall estimation. Recently, SM2RAIN-ASCAT (hereafter SM2RAIN) is a novel addition to satellite-based precipitation products which gives the rainfall estimates from the knowledge of soil moisture state and is based on 'bottom to top' approach. A comparative assessment of any newly developed product or a new version of the product is quite vital for algorithm developers and users. Hence, this research work was carried out to evaluate the accuracy and applicability of SM2RAIN, in comparison to in-situ data, TRMM, and IMERG in diverse regions of Pakistan. The comparative analysis was performed on a temporal scale (daily and monthly) and seasonal scale (spring, autumn, summer, and winter) using five performance metrics namely, root mean square error (RMSE), correlation coefficient (CC), false alarm ratio (FAR), the probability of detection (POD), and critical success index (CSI). The results showed that: (1) SM2RAIN is a better rainfall estimation product in the dry region (having avg. CC>0.35), however, less effective in hilly and mountainous terrain having high rainfall intensity; (2) SM2RAIN provides more satisfactory estimates in winter and autumn seasons, while relative poor in the summer season; (3) SM2RAIN performs better in terms of rainfall detection with an average POD of 0.61; (4) the overall performance of SM2RAIN is very convincing and it was concluded that SM2RAIN can be a feasible satellite product for most of the areas of Pakistan. It is noteworthy here to mention that this could be the preliminary assessment of SM2RAIN in diverse climatic zones of Pakistan.