全球降水计划IMERG和GSMaP反演降水在四川地区的精度评估
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摘要
IMERG和GSMaP是全球降水计划(GPM)时代最主要的高分辨率降水产品。为研究其在中国四川地区的适用性,以中国气象局提供的自动气象站融合降水数据为参考基准,采用6种统计指数分析了IMERG(IMERG_Uncal, IMERG_Cal)和GSMaP(GSMaP_MVK,GSMaP_Gauge)系列产品在四川的误差特征。结果表明:①在日和小时尺度上,GSMaP系列产品均高估地面降水观测,GSMaP_MVK高估最显著,校正产品GSMaP_Gauge的相关系数(CC)、相对偏差(BIAS)和均方根误差(RMSE)较GSMaP_MVK均有较大提高,尤其对川西高原降水的高估现象改善明显,而IMERG_Uncal存在低估川西高原降水、轻微高估四川盆地降水的问题,校正产品IMERG_Cal一定程度上降低了对川西高原降水的低估现象,但整体精度(CC, RMSE)提高不明显。②IMERG系列产品对降水事件的探测准确性更好,GSMaP_Gauge虽然在四川表现出较高的命中率(POD),但存在较多的误报降水,在盆地和四川南部各产品均表现出较高的POD和关键成功指数(CSI)以及低误报率(FAR),而四川西北部表现最差,尤其是在无自动站分布地区。③4套降水产品中,IMERG_Cal表现出最好的探测强降水和弱降水的能力,具有一定的监测极端降水的潜力。总体上,IMERG和GSMaP在盆地的反演精度优于高原山区,校正产品精度优于纯卫星产品,不同地形地区精度差异明显,表明对卫星降水产品进行不同地形误差订正仍是未来降水反演工作的重点和难点。
The Integrated Multi-satellitE Retrievals for GPM(IMERG) and Global Satellite Mapping of Precipitation(GSMaP) are two high precisely multi-satellite precipitation estimates in the GPM era. In order to evaluate the applicability of both IMERG and GSMaP series products(IMERG_Uncal and IMERG_Cal, GSMaP_MVK and GSMaP_Gauge) over the Sichuan region in China, six statistical indices are used to systematically analyze the error characteristics of these products, benchmarked by a set of ground-based dataset from China Meterological Administration(CMA). Results show that:(1) All products show the dramatic regional difference over Sichuan at both daily and hourly scales. The GSMaP series products overestimate precipitation and the most overestimations occur over the high altitude areas located in the Western Sichuan. GSMaP_Gauge shows relatively higher correlation coefficient and lower relative bias and root mean square error due to the employment of gauge-based adjustments. On the contrary, IMERG_Uncal shows underestimation over the mountainous areas, while the relatively slight overestimation appears in the basin area with lower elevation at both daily and hourly time scales, suggesting that gauge-calibrated dataset IMERG_Cal has effectively improved the relative bias in the mountainous areas but not in the flat basin area.(2)By synthesizing the three classified statistical indices, IMERG series products exhibit better potentials in detecting precipitation events. Although GSMaP_Gauge shows a higher hit rate of precipitation, it has more false alarm ratios of precipitation. All products show better hit rate and lower false alarm rate over basin area and southern Sichuan. Furthermore, it is found that the ground-based dataset has some errors in those areas without meteorological stations, which leads to the apparent uncertainty in assessing the accuracy of satellite precipitation products over the Northwest Sichuan Plateau.(3) IMERG_Cal performs better in capturing the rainfall amounts and events compared with other products, especially for the lowest and highest rainfall intensity ranges, demonstrating its application potential for monitoring the extreme weather events. Overall, both IMERG and GSMa P estimates have relatively high uncertainties over the mountainous areas than ones over the flat basin areas. Additionally, the gauge-calibrated products obviously outperform the uncalibrated datasets. On the basis of the findings, future efforts focus on reducing and correcting the errors and biases of satellite precipitation estimates by considering both spatio-temporal characteristics and the topographical information.
The Integrated Multi-satellitE Retrievals for GPM(IMERG) and Global Satellite Mapping of Precipitation(GSMaP) are two high precisely multi-satellite precipitation estimates in the GPM era. In order to evaluate the applicability of both IMERG and GSMaP series products(IMERG_Uncal and IMERG_Cal, GSMaP_MVK and GSMaP_Gauge) over the Sichuan region in China, six statistical indices are used to systematically analyze the error characteristics of these products, benchmarked by a set of ground-based dataset from China Meterological Administration(CMA). Results show that:(1) All products show the dramatic regional difference over Sichuan at both daily and hourly scales. The GSMaP series products overestimate precipitation and the most overestimations occur over the high altitude areas located in the Western Sichuan. GSMaP_Gauge shows relatively higher correlation coefficient and lower relative bias and root mean square error due to the employment of gauge-based adjustments. On the contrary, IMERG_Uncal shows underestimation over the mountainous areas, while the relatively slight overestimation appears in the basin area with lower elevation at both daily and hourly time scales, suggesting that gauge-calibrated dataset IMERG_Cal has effectively improved the relative bias in the mountainous areas but not in the flat basin area.(2)By synthesizing the three classified statistical indices, IMERG series products exhibit better potentials in detecting precipitation events. Although GSMaP_Gauge shows a higher hit rate of precipitation, it has more false alarm ratios of precipitation. All products show better hit rate and lower false alarm rate over basin area and southern Sichuan. Furthermore, it is found that the ground-based dataset has some errors in those areas without meteorological stations, which leads to the apparent uncertainty in assessing the accuracy of satellite precipitation products over the Northwest Sichuan Plateau.(3) IMERG_Cal performs better in capturing the rainfall amounts and events compared with other products, especially for the lowest and highest rainfall intensity ranges, demonstrating its application potential for monitoring the extreme weather events. Overall, both IMERG and GSMa P estimates have relatively high uncertainties over the mountainous areas than ones over the flat basin areas. Additionally, the gauge-calibrated products obviously outperform the uncalibrated datasets. On the basis of the findings, future efforts focus on reducing and correcting the errors and biases of satellite precipitation estimates by considering both spatio-temporal characteristics and the topographical information.
引文
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[5] Pombo S, Oliveira Rodrigo Proen?a De. Evaluation of extreme precipitation estimates from TRMM in Angola. Journal of Hydrology, 2015, 523:663-679.
[6] Jiang Shanhu, Ren Liliang, Yong Bin, et al. Hydrological evaluation of the TRMM multi-satellite precipitation estimates over the Mishui basin. Advances in Water Science, 2014, 25(5):641-649.[江善虎,任立良,雍斌,等. TRMM卫星降水数据在洣水流域径流模拟中的应用.水科学进展, 2014, 25(5):641-649.]
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[16] Jin Xiaolong, Shao Hua, Zhang Chi, et al. The applicability evaluation of three satellite products in Tianshan Mountains.Journal of Natural Resources, 2016, 31(12):2074-2085.[金晓龙,邵华,张弛,等. GPM卫星降水数据在天山山区的适用性分析.自然资源学报, 2016, 31(12):2074-2085.]
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[19] Shao Yuankun, Shen Tongli, You Yong, et al. Precipitation features of Sichuan basin in the recent 40 decades. Journal of Southwest Agricultural University(Natural Science), 2005(6):749-752.[邵远坤,沈桐立,游泳,等.四川盆地近40年来的降水特征分析.西南农业大学学报(自然科学版), 2005(6):749-752.]
[20] Yang Yunchuan, Cheng Genwei, Fan Jihui, et al. Accuracy validation of TRMM 3B42 data in Sichuan basin and the surrounding areas. Journal of the Meteorological Sciences, 2013, 33(5):526-535.[杨云川,程根伟,范继辉,等.四川盆地及周边地区TRMM 3B42数据精度检验.气象科学, 2013, 33(5):526-535.]
[21] Ji Tao, Yang Hua, Liu Rui, et al. Applicability analysis of the TRMM precipitation data in the Sichuan-Chongqing region. Progress in Geography, 2014, 33(10):1375-1386.[嵇涛,杨华,刘睿,等. TRMM卫星降水数据在川渝地区的适用性分析.地理科学进展, 2014, 33(10):1375-1386.]
[22] Sun Chen, Cheng Zhigang, Mao Xiaoliang, et al. Extreme climatic change trend and features in Sichuan for latest 44years. Journal of Lanzhou University(Natural Science), 2017(1):119-126.[孙晨,程志刚,毛晓亮,等.近44a四川地区极端气候变化趋势及特征分析.兰州大学学报(自然科学版), 2017(1):119-126.]
[23] Bai Yingying, Zhang Yi, Gao Yanghua, et al. Spatial differences of precipitation over Sichuan Basin. Scientia Geographica Sinica, 2011, 31(4):478-484.[白莹莹,张焱,高阳华,等.四川盆地降水变化的区域差异.地理科学,2011, 31(4):478-484.]
[24] Xie P P, Xiong A Y. A conceptual model for constructing high-resolution gauge-satellite merged precipitation analyses.Journal of Geophysical Research Atmospheres, 2011, 116(D21):21106.
[25] Shen Y, Zhao P, Pan Y, et al. A high spatiotemporal gauge-satellite merged precipitation analysis over China. Journal of Geophysical Research Atmospheres, 2014, 119(6):3063-3075.
[26] Shen Yan, Pan Yang, Yu Jingjing, et al. Quality assessment of hourly merged precipitation product over China.Transactions of Atmospheric Sciences, 2013, 36(1):37-46.[沈艳,潘旸,宇婧婧,等.中国区域小时降水量融合产品的质量评估.大气科学学报, 2013, 36(1):37-46.]
[27] Huffman G, Bolvin D, Nelkin E, et al. Improving user access to the Integrated Multi-Satellite Retrievals for GPM(IMERG)products. Egu General Assembly Conference. EGU General Assembly Conference Abstracts, 2016.
[28] Kachi M, Kubota T, Aonashi K, et al. Recent improvements in the global satellite mapping of precipitation(GSMaP).Geoscience&Remote Sensing Symposium, IEEE, 2014:3762-3765.
[29] Yong B, Ren L L, Hong Y, et al. First evaluation of the climatological calibration algorithm in the real-time TMPA precipitation estimates over two basins at high and low latitudes. Water Resources Research, 2013, 49(5):2461-2472.
[30] Li Qilun, Zhang Wanchang, Yi Lu, et al. Accuracy evaluation and comparison of GPM and TRMM precipitation product over Mainland China. Advances in Water Science, 2018, 29(3):303-313.[李麒崙,张万昌,易路,等. GPM与TRMM降水数据在中国大陆的精度评估与对比.水科学进展, 2018, 29(3):303-313.]
[31] Hu Qingfang, Yang Dawen, Wang Yintang, et al. Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang river basin. Scientia Sinica Technologica, 2013, 56(4):853-865.[胡庆芳,杨大文,王银堂,等.赣江流域高分辨率卫星降水数据的精度特征与时空变化规律.中国科学:技术科学, 2013, 56(4):447-459.]
[32] Tian Y D, Peters-Lidard C D, Eylander J B, et al. Component analysis of errors in satellite-based precipitation estimates.Journal of Geophysical Research, 2009, 114(D24):D24101.
[33] Zhou Changyan, Cen Sixian, Li Yueqing, et al. Precipitation variation and its impacts in Sichuan in the last 50 years.Acta Geographica Sinica, 2011, 66(5):619-630.[周长艳,岑思弦,李跃清,等.四川省近50年降水的变化特征及影响.地理学报, 2011, 66(5):619-630.]
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[35] Kim K, Park J, Baik J, et al. Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42over Far-East Asia. Atmospheric Research, 2017, 187:95-105.
[36] Ran X, Tian F Q, Long Y, et al. Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over southern Tibetan Plateau based on a high-density rain-gauge network:Validation of GPM and TRMM over TP. Journal of Geophysical Research Atmospheres, 2017, 122(2):910-924.
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[38] Prakash S, Mitra A K, Rajagopal E N, et al. Assessment of TRMM-based TMPA and GSMaP precipitation products over India for the peak southwest monsoon season. International Journal of Climatology, 2016, 36(4):1614-1631.
[2] Tong K, Su F G, Yang D Q, et al. Evaluation of satellite precipitation retrievals and their potential utilities in hydrologic modeling over the Tibetan Plateau. Journal of Hydrology, 2014, 519:423-437.
[3] Guo Ruifang, Liu Yuanbo. Multi-satellite retrieval of high resolution precipitation:An overview. Advances in Earth Science, 2015, 30(8):891-903.[郭瑞芳,刘元波.多传感器联合反演高分辨率降水方法综述.地球科学进展, 2015, 30(8):891-903.]
[4] Liu Z, Ostrenga D, Teng W, et al. Tropical Rainfall Measuring Mission(TRMM)precipitation data and services for research and applications. Bulletin of the American Meteorological Society, 2012, 93(9):1317.
[5] Pombo S, Oliveira Rodrigo Proen?a De. Evaluation of extreme precipitation estimates from TRMM in Angola. Journal of Hydrology, 2015, 523:663-679.
[6] Jiang Shanhu, Ren Liliang, Yong Bin, et al. Hydrological evaluation of the TRMM multi-satellite precipitation estimates over the Mishui basin. Advances in Water Science, 2014, 25(5):641-649.[江善虎,任立良,雍斌,等. TRMM卫星降水数据在洣水流域径流模拟中的应用.水科学进展, 2014, 25(5):641-649.]
[7] Hou A Y, Kakar R K, Neeck S, et al. The global precipitation measurement mission. Bulletin of the American Meteorological Society, 2014, 95(5):701-722.
[8] Draper D W, Newell D A, Wentz F J, et al. The Global Precipitation Measurement(GPM)Microwave Imager(GMI):Instrument overview and early on-orbit performance. IEEE Journal of Selected Topics in Applied Earth Observations&Remote Sensing, 2015, 8(7):3452-3462.
[9] Tang Guoqiang, Wan Wei, Zeng Ziyue, et al. An overview of the Global Precipitation Measurement(GPM)mission and its latest development. Remote Sensing Technology and Application, 2015, 30(4):607-615.[唐国强,万玮,曾子悦,等.全球降水测量(GPM)计划及其最新进展综述.遥感技术与应用, 2015, 30(4):607-615.]
[10] Shige S, Yamamoto T, Tsukiyama T, et al. The GSMaP precipitation retrieval algorithm for microwave sounders:Overocean algorithm. IEEE Transactions on Geoscience&Remote Sensing, 2009, 47(9):3084-3097.
[11] Tan M, Duan Z. Assessment of GPM and TRMM precipitation products over Singapore. Remote Sensing, 2017, 9(7):720.
[12] Sharifi E, Steinacker R, Saghafian B. Assessment of GPM-IMERG and other precipitation products against gauge data under different topographic and climatic conditions in Iran:Preliminary results. Remote Sensing, 2016, 8(2):135.
[13] Tian Y D, Peters-Lidard C D, Adler R F, et al. Evaluation of GSMaP precipitation estimates over the contiguous United States. Journal of Hydrometeorology, 2010, 11(2):566-574.
[14] Tang G Q, Ma Y Z, Long D, et al. Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over Mainland China at multiple spatiotemporal scales. Journal of Hydrology, 2016, 533:152-167.
[15] Chen Xiaohong, Zhong Ruida, Wang Zhaoli, et al. Accuracy and hydrological utility evaluation of new generation GPM IMERG remote sensing precipitation data in southern China. Journal of Hydraulic Engineering, 2017, 48(10):1147-1156.[陈晓宏,钟睿达,王兆礼,等.新一代GPM IMERG卫星遥感降水数据在中国南方地区的精度及水文效用评估.水利学报, 2017, 48(10):1147-1156.]
[16] Jin Xiaolong, Shao Hua, Zhang Chi, et al. The applicability evaluation of three satellite products in Tianshan Mountains.Journal of Natural Resources, 2016, 31(12):2074-2085.[金晓龙,邵华,张弛,等. GPM卫星降水数据在天山山区的适用性分析.自然资源学报, 2016, 31(12):2074-2085.]
[17] Lu D K, Yong B. Evaluation and hydrological utility of the latest GPM IMERG V5 and GSMaP V7 precipitation products over the Tibetan Plateau. Remote Sensing, 2018, 10(12):2022.
[18] Zhang S J, Wang D H, Qin Z K, et al. Assessment of the GPM and TRMM precipitation products using the rain gauge network over the Tibetan Plateau. Journal of Meteorological Research, 2018, 32(2):324-336.
[19] Shao Yuankun, Shen Tongli, You Yong, et al. Precipitation features of Sichuan basin in the recent 40 decades. Journal of Southwest Agricultural University(Natural Science), 2005(6):749-752.[邵远坤,沈桐立,游泳,等.四川盆地近40年来的降水特征分析.西南农业大学学报(自然科学版), 2005(6):749-752.]
[20] Yang Yunchuan, Cheng Genwei, Fan Jihui, et al. Accuracy validation of TRMM 3B42 data in Sichuan basin and the surrounding areas. Journal of the Meteorological Sciences, 2013, 33(5):526-535.[杨云川,程根伟,范继辉,等.四川盆地及周边地区TRMM 3B42数据精度检验.气象科学, 2013, 33(5):526-535.]
[21] Ji Tao, Yang Hua, Liu Rui, et al. Applicability analysis of the TRMM precipitation data in the Sichuan-Chongqing region. Progress in Geography, 2014, 33(10):1375-1386.[嵇涛,杨华,刘睿,等. TRMM卫星降水数据在川渝地区的适用性分析.地理科学进展, 2014, 33(10):1375-1386.]
[22] Sun Chen, Cheng Zhigang, Mao Xiaoliang, et al. Extreme climatic change trend and features in Sichuan for latest 44years. Journal of Lanzhou University(Natural Science), 2017(1):119-126.[孙晨,程志刚,毛晓亮,等.近44a四川地区极端气候变化趋势及特征分析.兰州大学学报(自然科学版), 2017(1):119-126.]
[23] Bai Yingying, Zhang Yi, Gao Yanghua, et al. Spatial differences of precipitation over Sichuan Basin. Scientia Geographica Sinica, 2011, 31(4):478-484.[白莹莹,张焱,高阳华,等.四川盆地降水变化的区域差异.地理科学,2011, 31(4):478-484.]
[24] Xie P P, Xiong A Y. A conceptual model for constructing high-resolution gauge-satellite merged precipitation analyses.Journal of Geophysical Research Atmospheres, 2011, 116(D21):21106.
[25] Shen Y, Zhao P, Pan Y, et al. A high spatiotemporal gauge-satellite merged precipitation analysis over China. Journal of Geophysical Research Atmospheres, 2014, 119(6):3063-3075.
[26] Shen Yan, Pan Yang, Yu Jingjing, et al. Quality assessment of hourly merged precipitation product over China.Transactions of Atmospheric Sciences, 2013, 36(1):37-46.[沈艳,潘旸,宇婧婧,等.中国区域小时降水量融合产品的质量评估.大气科学学报, 2013, 36(1):37-46.]
[27] Huffman G, Bolvin D, Nelkin E, et al. Improving user access to the Integrated Multi-Satellite Retrievals for GPM(IMERG)products. Egu General Assembly Conference. EGU General Assembly Conference Abstracts, 2016.
[28] Kachi M, Kubota T, Aonashi K, et al. Recent improvements in the global satellite mapping of precipitation(GSMaP).Geoscience&Remote Sensing Symposium, IEEE, 2014:3762-3765.
[29] Yong B, Ren L L, Hong Y, et al. First evaluation of the climatological calibration algorithm in the real-time TMPA precipitation estimates over two basins at high and low latitudes. Water Resources Research, 2013, 49(5):2461-2472.
[30] Li Qilun, Zhang Wanchang, Yi Lu, et al. Accuracy evaluation and comparison of GPM and TRMM precipitation product over Mainland China. Advances in Water Science, 2018, 29(3):303-313.[李麒崙,张万昌,易路,等. GPM与TRMM降水数据在中国大陆的精度评估与对比.水科学进展, 2018, 29(3):303-313.]
[31] Hu Qingfang, Yang Dawen, Wang Yintang, et al. Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang river basin. Scientia Sinica Technologica, 2013, 56(4):853-865.[胡庆芳,杨大文,王银堂,等.赣江流域高分辨率卫星降水数据的精度特征与时空变化规律.中国科学:技术科学, 2013, 56(4):447-459.]
[32] Tian Y D, Peters-Lidard C D, Eylander J B, et al. Component analysis of errors in satellite-based precipitation estimates.Journal of Geophysical Research, 2009, 114(D24):D24101.
[33] Zhou Changyan, Cen Sixian, Li Yueqing, et al. Precipitation variation and its impacts in Sichuan in the last 50 years.Acta Geographica Sinica, 2011, 66(5):619-630.[周长艳,岑思弦,李跃清,等.四川省近50年降水的变化特征及影响.地理学报, 2011, 66(5):619-630.]
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