Assessment of satellite products for filling rainfall data gaps in the Amazon region

Rainfall data series with adequate quality and length are often incomplete or nonexistent. Thus, filling in rainfall gaps becomes necessary to complete databases. This article proposes the use of satellite products (TRMM—Tropical Measuring Mission, CHIRPS—Climate Hazards Group InfraRed Precipitation Stations CMORPH—CPC Morphing Technique) fill historical series. The simple regression method, using estimates, was tested missing from 164 gauge stations Amazon region. Large dispersions were observed between data, R2 ranging 0.383 0.844, best results found areas less rainfall. As well, greatest performance verified dry period, r d higher than 0.899 0.950, respectively. product representation region CHIRPS, which had lowest monthly values mean absolute error (0.979 mm) root square (3.656 mm). confirm that estimates satisfactorily represent seasonal variation region, despite presenting cases overestimation underestimation data. CHIRPS can be explained by spatial resolution (0.05°), allowing for more accurate weather forecasts. In fact, has CHPclim model, adds other factors good performance. These characteristics justify better daily favoring each state analyzed. Recommendations Resource Managers Satellite have been increasingly used estimating regions a low number installed stations. assessment selection these needs elaborated decision making water resource managers. important recognize occurrence patterns prediction climatic behavior Sectors such as agriculture disaster prevention (droughts, floods, erosion watersheds, river silting) need knowledge planning, management, mitigation. Knowledge is very this case, season temperatures increasing due global climate change. changes establish conditions intense fires, increases deforestation