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Evaluation of high resolution global satellite precipitation mapping during meteorological drought over Iran
Theoretical and Applied Climatology ( IF 3.4 ) Pub Date : 2021-07-07 , DOI: 10.1007/s00704-021-03708-8
Mohammad Darand 1, 2 , Hassan Fathi 1
Affiliation  

This study evaluated the performance of three versions of Global Satellite Mapping of Precipitation (GSMaP) products at 0.1° spatial resolution for monitoring meteorological drought over Iran. The investigated GSMaP products included the gauge-corrected product (GSMaP-Gauge), the standard MW-IR combined product (GSMaP-MVK), and the near-real-time product (GSMaP-NRT), examined during the period from 1 March 2014 to 31 December 2018. For reference, we used high-quality ground-observed precipitation data from 344 synoptic stations. The standard precipitation index (SPI) on different timescales from 1 to 12 months was used for the quantification of drought events. The statistical metrics employed for the assessment of the performance of the three GSMaP products included Pearson’s correlation coefficient (R) and root mean square error (RMSE). In addition to the evaluations based on spatial and temporal scales, the capability of the GSMaP products of identifying drought events was considered. The results indicated that GSMaP-Gauge was superior to the other two GSMaP products in the monitoring of drought patterns over Iran, with a much higher R and a much lower RMSE, particularly on long timescales. In spatial terms, all the three GSMaP products exhibited high performance in Western Iran, where precipitation is high. Generally, the study revealed the potential capability of GSMaP products for monitoring meteorological drought over Iran, particularly for data-poor or ungauged basins.



中文翻译:

伊朗气象干旱期间高分辨率全球卫星降水测绘评估

本研究评估了三个版本的全球降水卫星测绘 (GSMaP) 产品在 0.1° 空间分辨率下监测伊朗气象干旱的性能。被调查的GSMaP产品包括量规校正产品(GSMaP-Gauge)、标准MW-IR组合产品(GSMaP-MVK)和近实时产品(GSMaP-NRT),自3月1日起检测2014年至2018年12月31日。作为参考,我们使用了来自344个天气站的高质量地面观测降水数据。1 至 12 个月不同时间尺度的标准降水指数 (SPI) 用于量化干旱事件。用于评估三种 GSMaP 产品性能的统计指标包括 Pearson 相关系数 (R) 和均方根误差 (RMSE)。除了基于空间和时间尺度的评估外,还考虑了 GSMaP 产品识别干旱事件的能力。结果表明,GSMaP-Gauge 在监测伊朗干旱模式方面优于其他两种 GSMaP 产品,具有更高的 R 和更低的 RMSE,尤其是在长时间尺度上。在空间方面,所有三个 GSMaP 产品在伊朗西部都表现出很高的性能,那里的降水量很大。总的来说,该研究揭示了 GSMaP 产品在监测伊朗气象干旱方面的潜在能力,特别是对于数据贫乏或未经测量的盆地。结果表明,GSMaP-Gauge 在监测伊朗干旱模式方面优于其他两种 GSMaP 产品,具有更高的 R 和更低的 RMSE,尤其是在长时间尺度上。在空间方面,所有三个 GSMaP 产品在伊朗西部都表现出很高的性能,那里的降水量很大。总的来说,该研究揭示了 GSMaP 产品在监测伊朗气象干旱方面的潜在能力,特别是对于数据贫乏或未经测量的盆地。结果表明,GSMaP-Gauge 在监测伊朗干旱模式方面优于其他两种 GSMaP 产品,具有更高的 R 和更低的 RMSE,尤其是在长时间尺度上。在空间方面,所有三个 GSMaP 产品在伊朗西部都表现出很高的性能,那里的降水量很大。总的来说,该研究揭示了 GSMaP 产品在监测伊朗气象干旱方面的潜在能力,特别是对于数据贫乏或未经测量的盆地。

更新日期:2021-07-07
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