Abstract
Using rain-gauge-observation daily precipitation data from the Global Historical Climatology Network (V3.25) and the Chinese Surface Daily Climate Dataset (V3.0), this study investigates the fidelity of the AHPRODITE dataset in representing extreme precipitation, in terms of the extreme precipitation threshold value, occurrence number, probability of detection, and extremal dependence index during the cool (October to April) and warm (May to September) seasons in Central Asia during 1961–90. The distribution of extreme precipitation is characterized by large extreme precipitation threshold values and high occurrence numbers over the mountainous areas. The APHRODITE dataset is highly correlated with the gauge-observation precipitation data and can reproduce the spatial distributions of the extreme precipitation threshold value and total occurrence number. However, APHRODITE generally underestimates the extreme precipitation threshold values, while it overestimates the total numbers of extreme precipitation events, particularly over the mountainous areas. These biases can be attributed to the overestimation of light rainfall and the underestimation of heavy rainfall induced by the rainfall distribution-based interpolation. Such deficits are more evident for the warm season than the cool season, and thus the biases are more pronounced in the warm season than in the cool season. The probability of detection and extremal dependence index reveal that APHRODITE has a good capability of detecting extreme precipitation, particularly in the cool season.
摘要
本文基于极端降水阈值、频次、事件检出率和独立于极端概率指数等评估指标, 考察了1961-1990年APHRODITE格点降水资料在中亚地区冷季(10月至次年4月)和暖季(5月至9月)极端降水研究中的适用性。结果表明: 中亚地区极端阈值和频次的高值区主要位于山脉地区, APHRODITE与站点资料存在很好的相关性, 能较好的重现中亚地区极端降水阈值和频次的空间分布特征。但APHRODITE弱降水的频次偏多以及对于强降水强度的低估, 共同导致APHRODITE低估了极端降水阈值的大小, 而高估了极端降水事件的总频次, 这种偏差在山区更为明显, 并且暖季的偏差大于冷季。事件检出率和独立于极端概率指数均表明APHRODITE资料能较好的检出和重现中亚地区极端降水特征。
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Acknowledgements
The authors are grateful to the two anonymous reviewers for their valuable comments and suggestions. This research was funded by the National Key Research and Development Program of China (Grant No. 2018YFC1507101), the National Natural Science Foundation of China (Grant Nos. 41861144014, 41875078 and 41630424) and the National Key Research and Development Program of China (Grant No. 2016YFA0601501). We acknowledge Hirosaki University for providing the APHRODITE precipitation data (http://aphoodtte.st.hirosaki-u.ac.jp/download/). We thank the China Meteorological Data Service Center for providing the Chinese Surface Daily Climate Dataset (V3.0) (https://data.cma.cn/en/?r=data/detail&data-Code=SURF_CLI_CHN_MUL_DAY_CES_V3.0) and the National Oceanic and Atmospheric Administration, National Centers for Environmental Information, for providing the GHCN-D dataset (V3.25) (Menne et al., 2012). We convey our gratitude to the contributors of the SciPy ecosystem (Virtanen et al., 2020), which was used for data analysis and visualization.
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Article Highlights
• APHRODITE can reproduce the spatial distributions of the extreme precipitation threshold value and total occurrence number.
• APHRODITE underestimates the extreme precipitation threshold values and overestimates the total numbers of the extreme precipitation.
• The warm season features a stronger shift of the precipitation distribution “spectrum” to smaller amplitudes, resulting in higher biases than in the cool season.
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Lai, S., Xie, Z., Bueh, C. et al. Fidelity of the APHRODITE Dataset in Representing Extreme Precipitation over Central Asia. Adv. Atmos. Sci. 37, 1405–1416 (2020). https://doi.org/10.1007/s00376-020-0098-3
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DOI: https://doi.org/10.1007/s00376-020-0098-3