Evaluation of Satellite Precipitation Estimates over Australia
| Autor: | Yuriy Kuleshov, Zhi-Weng Chua, Andrew B. Watkins |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
rain gauge precipitation measurements
010504 meteorology & atmospheric sciences Rain gauge 0207 environmental engineering australia 02 engineering and technology Satellite precipitation satellite precipitation estimates 01 natural sciences satellite precipitation validation Australia Climatology General Earth and Planetary Sciences Satellite lcsh:Q Precipitation 020701 environmental engineering Scale (map) lcsh:Science Reference dataset 0105 earth and related environmental sciences |
| Zdroj: | Remote Sensing; Volume 12; Issue 4; Pages: 678 Remote Sensing, Vol 12, Iss 4, p 678 (2020) |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs12040678 |
| Popis: | This study evaluates the U.S. National Oceanographic and Atmospheric Administration’s (NOAA) Climate Prediction Center morphing technique (CMORPH) and the Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) satellite precipitation estimates over Australia across an 18 year period from 2001 to 2018. The evaluation was performed on a monthly time scale and used both point and gridded rain gauge data as the reference dataset. Overall statistics demonstrated that satellite precipitation estimates did exhibit skill over Australia and that gauge-blending yielded a notable increase in performance. Dependencies of performance on geography, season, and rainfall intensity were also investigated. The skill of satellite precipitation detection was reduced in areas of elevated topography and where cold frontal rainfall was the main precipitation source. Areas where rain gauge coverage was sparse also exhibited reduced skill. In terms of seasons, the performance was relatively similar across the year, with austral summer (DJF) exhibiting slightly better performance. The skill of the satellite precipitation estimates was highly dependent on rainfall intensity. The highest skill was obtained for moderate rainfall amounts (2−4 mm/day). There was an overestimation of low-end rainfall amounts and an underestimation in both the frequency and amount for high-end rainfall. Overall, CMORPH and GSMaP datasets were evaluated as useful sources of satellite precipitation estimates over Australia. |
| Databáze: | OpenAIRE |
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