Thermal Monitoring and Evaluation of Precipitation Data Applying TRMM and GPM Satellites (Case Study: Bandar Abbas City)

Precipitation plays a decisive role in meeting the water needs of various crops, dam reserves, feeding surface and groundwater resources, and the occurrence of floods and droughts. Lack of access to long-term daily rainfall data and the high cost of setting up ground meteorological stations necessitate the replacement of low-cost methods with high-precision, high-volume data such as satellite data. The aim of this study was to evaluate the accuracy of precipitation data predicted by TRMM and GPM satellites in Bandar Abbas metropolis during a 17-year period from 2000 to 2017. Hourly precipitation data of TRMM and GPM satellites were obtained from databases. After analyzing the data format in MATLAB environment, hourly precipitation information was extracted. The results showed that the accuracy of both TRMM and GPM models in precipitation forecasting was appropriate and close to each other; it was often overestimated so that 75% of TRMM model precipitation forecasts and all forecasts GPM models were overestimated. The results showed that the TRMM model was more accurate than the GPM model in accurately predicting the occurrence of rainfall events and had less error in predicting unrealistic rainfall and the highest accuracy of the TRMM and GPM models is on a monthly, annual and daily scale, respectively. The value of EF index in TRMM model varies from -284.52 to 0.71 and in GPM model from -25514 to -1.25. The value of the EF index in the TRMM model predictions was positive in 42% of events, while, in the GPM model, it was not positively predicted in any event. The general conclusion of the research is that TRMM satellite is a suitable tool for monitoring and forecasting precipitation.