Measuring Precipitation from Space - a Satellite View on the Tibetan Plateau
Precipitation is an essential variable in the global climate system. The processing of reliable high resolution global precipitation data remains an issue, as all available data sets have their own weaknesses. This applies in particular to remote regions with complex terrain such as the Tibetan Plat...
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| Format: | Doctoral Thesis |
| Language: | English |
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Philipps-Universität Marburg
2025
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| Online Access: | PDF Full Text |
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| Summary: | Precipitation is an essential variable in the global climate system. The processing of reliable high resolution global precipitation data remains an issue, as all available data sets have their own weaknesses. This applies in particular to remote regions with complex terrain such as the Tibetan Plateau (TiP). Satellite based data sets from the NASA and ESA are commonly used for analyses and the retrieval of climate variables. Satellite based data sets that have not yet been scientifically exploited, or only to a limited extent, are Elektro-L2 and Insat-3D. The Global Precipitation Measurement Mission (GPM) provides precipitation from space using a combination of low earth orbiting satellites and enhances the retrieval of precipitation and snowfall using improved instruments. Based on the potential inherent in the data sets, they were used in the following two studies to develop an algorithm to retrieve precipitation for the TiP. Training models on a smaller temporal segmentation made a significant difference in the results of precipitation areadelineation. Undersampling was used for precipitation rates retrieval. Comparing the results of both the classification of the precipitation areas and the retrieval of precipitation rates we found that the new approach outperforms the Infrared (IR) only precipitation product from the Integrated Multi-satellitE Retrievals for GPM (IMERG). The results of the precipitation retrieval agree with the daily rain gauge measurements from the Chinese Ministry of Water Resources.
Snow plays a crucial role on the TiP and snowfall precipitation is not well explored. The third study draws an intercomparison of the variables total precipitation (TP) and snowfall precipitation (SF) of the GPM dual precipitation frequency radar (DPR) Level 2 product together with GPM DPR snowfall flags and six model based data sets: ERA5, ERA5 land, ERA Interim, MERRA 2, JRA 55 and HAR V2. The intercomparison of model based data with the snowfall flags performs poorly for both TP and SF. Since it is known that mismatches between remote sensing data and modeled data exist, we increased the time lag of the reanalysis data and included GPM neighbor pixels to improve the results. The intercomparison with the GPM DPR snowfall flags using the temporal adjustment improved the results significantly, whereas the spatial adjustment did not show strong improvements. The intercomparison of the GPM DPR TP and SF with the modeled data was improved by both temporal and spatial adjustment. Retrieving precipitation and snowfall from space offers great potential. It remains a challenge and needs further research. |
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| DOI: | 10.17192/z2025.0212 |