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Introducing satellite data bases of precipitation in Iran | ||
| علوم و فناوری اطلاعات کشاورزی | ||
| Volume 8, Issue 1 - Serial Number 15, March 2025, Pages 27-36 PDF (371.08 K) | ||
| Document Type: Extension | ||
| DOI: 10.22092/jaist.2024.367213.1123 | ||
| Authors | ||
| Seyed Masoud Soleimanpour* 1; Parsa Haghighi2 | ||
| 1Associate Professor, Soil Conservation and Watershed Management Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran | ||
| 2Masters, Soil Conservation and Watershed Management Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran | ||
| Abstract | ||
| In this research, at first, the methods of estimating precipitation by meteorological satellites have been interpreted, and then the satellite precipitation databases have been introduced and a comparison has been made between the accuracy of satellite output and precipitation measurement algorithms. The investigation of the present research showed that in the use of satellite rainfall data, time, geographical location and the amount of rainfall should be taken into consideration, and the accuracy and precision of the forecasted rainfall values can be increased from satellite data integration methods. The relationship between the rainfall intensity of each region and the rainfall recorded by the satellite is also important, and in addition to the logical relationship between the satellite rainfall values and the local station, the relationship between the rainfall intensity of each region and the rainfall recorded by the satellites can also be investigated. The output of satellite models at least on the daily time scale for precipitation data indicates moderate to poor accuracy; Therefore, in order to reduce the uncertainty of satellite precipitation products, it is necessary to use exponential microscale methods at the station level and reduce the error. | ||
| Keywords | ||
| precipitation estimation; uncertainty; meteorological satellites; remote sensing | ||
| References | ||
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