With the occurrence of underestimation of the CMORPH estimates in the summer Further analysesĬonducted at the monthly scale for Europe revealed seasonal misalignments, GloREDa rainfall erosivity maps was observed in Europe, while the worst agreement was detected in Africa and South America. At theĬontinental level, the best agreement between annual CMORPH and interpolated Were observed in areas with the highest rainfall erosivity values.
Overall, results indicated that the CMORPHĮstimates have a marked tendency to underestimate rainfall erosivity whenĬompared to the GloREDa estimates. Validated against the pluviograph data included in the Global Rainfall Erosivity Database (GloREDa). The obtained global estimates of rainfall erosivity were Alternatively, theĮrosivity density (ED) concept was also used to estimate global rainfallĮrosivity. Such high spatial and temporal (30 min) resolution data have not yet been used for theĮstimation of rainfall erosivity on a global scale. Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) Climate Prediction Center MORPHing (CMORPH) technique. Resolution global precipitation estimates obtained with the National For this purpose, we used the high spatial and temporal Global rainfall erosivity using satellite-based rainfall data was explored
Since the 1980s, the suitability of alternative approaches to estimate Increase in future decades since the monitoring networks have been declining As theĪvailability of high temporal resolution rainfall data will most likely not Resolution rainfall data needed to estimate rainfall erosivity. In this regard, the mainĬhallenge is still represented by the limited availability of high temporal More dynamic inter- and intra-annual assessments. Despite recent developments in modeling global soil erosion by water, to date, no substantial progress has been made towards
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