Ground validation of TRMM 3B43 V7 precipitation estimates over Colombia. Part I: Monthly and seasonal timescales - Sara M. Vallejo‐Bernal; Viviana Urrea; Juan M. Bedoya‐Soto; Daniela Posada; Alejandro Olarte; Yadira Cárdenas‐Posso; Franklyn Ruiz‐Murcia; María T. Martínez; Walter A. Petersen; George J. Huffman; Germán Poveda (International Journal of Climatology, 2021)
In this study, we validate precipitation estimates remotely sensed by the Tropical Rainfall Measuring Mission (TRMM) at monthly and seasonal timescales, during the period 1998–2015, by calculating and analyzing diverse error metrics between the 3B43 V7 product and in situ measurements from 1,180 rain gauges over Colombia, of which at least 987 are fully independent of TRMM. We explore the existence of spatiotemporal patterns to assess the performance of 3B43 V7 over the five major natural regions of Colombia: Caribbean, Pacific, Andes, Orinoco and Amazon. The results show that 3B43 V7 product is able to capture the phase of the annual cycle of monthly mean precipitation, but the performance is not good for the amplitude, in particular over the Andes and Pacific regions owing to complex climatic and topographic conditions. In general, 3B43 V7 exhibits good performance in the low‐lying and plain Amazon, Orinoco and Caribbean regions. Over the Andes region, characterized by complex topography, overestimation errors are identified [root mean squared error (RMSE) ≥83.59 mm·month −1 and relative bias (BIAS) ≥4.69%], whereas the extremely wet rainfall regime of the Pacific region is largely underestimated (RMSE ≥253.52 mm ·month −1 and BIAS ≤−11.75%). These errors are greater during the wet seasons when the metrics reach worse scores than those reported in similar studies worldwide. Occurrence analyses showed that 3B43 V7 misses very frequent light rainfall events and less frequent but very heavy storms, which contribute to the overall underestimation (overestimation) observed over the Pacific (Andes) region. The error characteristics identified and quantified in this study confirm the well‐documented limitations of remote precipitation sensing and constitute a warning about major challenges that complex climatic and physiographic features can impose on satellite rainfall missions.