GPM/DPR雷达与CINRAD雷达降水探测对比
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摘要
通过对比星载DPR雷达与地基CINRAD雷达的降雨测量值,评估星地雷达联合应用的潜力。为了提高对比的准确性,在尽可能高的时空分辨率下,以几何匹配与格点匹配相结合的方式,提取星地雷达降水样本数据。2015年6月30日降水过程的对比分析结果表明:泰州、常州CINRAD雷达反射率因子在两站中分剖面的平均值偏差0.94 dB,地基雷达之间有很好的一致性;在DPR雷达与常州、泰州CINRAD雷达同时覆盖的降雨区域,星地之间雷达反射率因子的平均值偏差分别为-1. 2 dB和-1. 6 dB,显示星地雷达也有较好的一致性;现有DPR雷达陆上衰减订正算法在缩小星地雷达偏差方面起到一定作用,平均订正量0.4 dB,只要回波覆盖充分,匹配样本的高度以及其到地基雷达的距离对对比结果没有明显影响,而衰减订正和匹配样本区回波覆盖率是影响星地雷达对比结果的重要因素。
It is necessary to find out the difference between space-borne and ground-based radar data for evaluating the possibility of combined use of them. 2 neighboring ground-based radars at Taizhou and Changzhou are first checked for data consistence in full resolution and then compared with the DPR radar respectively.Results from the precipitation case on 30 June 2015 show that 2 radars have 0. 94 dB bias of mean reflectivity factor on the profile where distances to both radars are equal.To get high temporal and spatial resolution comparisons between DPR and CINRAD, the geometrymatching algorithm is used in vertical where 1-14 DPR range gates could be included in one sample pairs according to the distance to CINRAD radar site. The further away it's from the radar site, the more DPR gates can be included. The grid-matching algorithm is used in horizontal where total 5×5 grids in 1 km resolution are matched with one single DPR range gate. The DPR and CINRAD volume-averaged values are calculated for all such intersecting DPR range gates and 5×5 CINRAD grids. Statistic results on sample pairs show that the mean reflectivity factor biases of DPR radar are-1. 2 dB and-1.6 dB for CINRAD Taizhou and Changzhou radars, respectively, and the mean rain rate converted from Z-R relationship are 0. 10 mm · h~(-1) and 0. 13 mm · h~(-1) lower than CINRAD radars',over the same area where the three radars scanned successively within 6 min. When the distance to CINRAD gets longer, the bias between DPR and CINRAD is larger near the top of echo. And the bias in the bright band area is 122 dB larger than the mean bias as well. But the bias has no obvious relevance with distance and height in the other area if beam filling is enough.Attenuation correction and echo coverage over sample cell are among important factors which affect comparison results. Though there is no suitable surface reference, the attenuation correction algorithm for DPR radar over land works and decreases 0. 4 dB in mean bias between DPR and CINRAD Taizhou. The maximum correction is only 1. 36 dB due to moderate intensity of radar reflectivity factor.The equivalent radar reflectivity factor must be modified for the application of comparing DPR radar to other wavelength radar when the equivalent radar reflectivity factor is greater than 37 dBZ. For the application of combined multi-wavelength(such as DPR and CINRAD), data quality control and clutter identification and elimination are all among direct acting factors.
It is necessary to find out the difference between space-borne and ground-based radar data for evaluating the possibility of combined use of them. 2 neighboring ground-based radars at Taizhou and Changzhou are first checked for data consistence in full resolution and then compared with the DPR radar respectively.Results from the precipitation case on 30 June 2015 show that 2 radars have 0. 94 dB bias of mean reflectivity factor on the profile where distances to both radars are equal.To get high temporal and spatial resolution comparisons between DPR and CINRAD, the geometrymatching algorithm is used in vertical where 1-14 DPR range gates could be included in one sample pairs according to the distance to CINRAD radar site. The further away it's from the radar site, the more DPR gates can be included. The grid-matching algorithm is used in horizontal where total 5×5 grids in 1 km resolution are matched with one single DPR range gate. The DPR and CINRAD volume-averaged values are calculated for all such intersecting DPR range gates and 5×5 CINRAD grids. Statistic results on sample pairs show that the mean reflectivity factor biases of DPR radar are-1. 2 dB and-1.6 dB for CINRAD Taizhou and Changzhou radars, respectively, and the mean rain rate converted from Z-R relationship are 0. 10 mm · h~(-1) and 0. 13 mm · h~(-1) lower than CINRAD radars',over the same area where the three radars scanned successively within 6 min. When the distance to CINRAD gets longer, the bias between DPR and CINRAD is larger near the top of echo. And the bias in the bright band area is 122 dB larger than the mean bias as well. But the bias has no obvious relevance with distance and height in the other area if beam filling is enough.Attenuation correction and echo coverage over sample cell are among important factors which affect comparison results. Though there is no suitable surface reference, the attenuation correction algorithm for DPR radar over land works and decreases 0. 4 dB in mean bias between DPR and CINRAD Taizhou. The maximum correction is only 1. 36 dB due to moderate intensity of radar reflectivity factor.The equivalent radar reflectivity factor must be modified for the application of comparing DPR radar to other wavelength radar when the equivalent radar reflectivity factor is greater than 37 dBZ. For the application of combined multi-wavelength(such as DPR and CINRAD), data quality control and clutter identification and elimination are all among direct acting factors.
引文
[1] Hou A Y,and Coauthors. The global precipitation measurement mission. Bull Amer Meteor Soc,2014,95:701-722.
[2] Toshio I,Toshiaki K, Robert M,et al. Rain profiling algorithm for the TRMM precipitation radar. J Appl Meteor,1997,39(12):2038-2052.
[3] Schwaller M R,Morris K R. A ground validation network for the global precipitation measurement mission. J Atmos Ocean Technol,2011,28(3):301-319.
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[9]陈廷娣,王连仲,窦贤康.TRMM卫星与机载雷达在降雨反演中的数据对比个例研究.应用气象学报.2008,19(4):454-462.
[10]李嘉睿,卢乃锰,谷松岩.青藏高原地区TRMM PR地面降雨率的修正.应用气象学报,2015,26(5):636-640.
[11]唐英杰,马舒庆,杨玲,等.云底高度的地基毫米波云雷达观测及其对比.应用气象学报,2015,26(6):680-687.
[12]何平,朱小燕,阮征,等.风廓线雷达探测降水过程的初步研究.应用气象学报,2009,20(4):465-470.
[13]高郁东,万齐林,薛纪善,等.同化雷达估算降水率对暴雨预报的影响.应用气象学报,2015,26(1):45-56.
[14]东高红,刘黎平.雷达与雨量计联合估测降水的相关性分析.应用气象学报,2012,23(1):30-39.
[15]史锐,程明虎,崔哲虎,等.用反射率因子垂直廓线联合雨量计校准估测夏季区域强降水.应用气象学报,2005,16(6):737-745.
[16]楚志刚,许丹,王振会,等.基于TRMM/PR的长江下游地基雷达一致性订正.应用气象学报,2018,29(3):296-306.
[17] Toshio I,and Coauthors. GPM/DPR Level-2 Algorithm Theoretical Basis Document. https://pmm. nasa. gov/sites/default/files/document_files/ATBD_GPM_DPR_n3_dec15.pdf.[2017-12-03].
[18]王强.综合气象观测.北京:气象出版社,2012.
[19]寇蕾蕾,楚志刚,李南,等.TRMM星载测雨雷达和地基雷达反射率因子数据的三维融合.气象学报,2016,74(2):285-297.
[20] Haynes JM,Marchand RT,LuoZ,etal.Amulti-purpose radar simulation package:QuickBeam. Bull Amer Meteor Soc,2007,88:1723-1727.
[21]张培昌,杜秉玉,戴铁丕.雷达气象学.北京:气象出版社,2001:122-123;183.
[22] Meneghini R,Jones J,Iguchi T,et al. A hybrid surface reference technique and its application to the TRMM precipitation radar. J Atmos Oceanic Technol,2004,21(11):1645-1658.
[23] Bolen S M,Chandrasekar V. Methodology for aligning and comparing space borne Radar and ground-based radar observations. J Atmos Oceanic Technol, 2003, 20:647-659.
[24] Tagawa T,Hanado H.Okamoto K,et al. Suppression of surface clutter interference with precipitation measurements byspace borne precipitation radar. IEEE Trans Geosci Remote Sens,2007,45:1324-1331.
[25] Takuji K,Toshio I,Masahiro K,et al. A statistical method for reducing sidelobe clutter for the Ku-band precipitation radar on board the GPM core observatory. J Atmos Ocean Technol,2016,33:1413-1428.
[26] Liao L,Robert M. Validation of TRMM precipitation radar through comparison of its multiyear measurements with ground-based radar. J Applied Meteorology and Climatology,2009,48:804-817.
[2] Toshio I,Toshiaki K, Robert M,et al. Rain profiling algorithm for the TRMM precipitation radar. J Appl Meteor,1997,39(12):2038-2052.
[3] Schwaller M R,Morris K R. A ground validation network for the global precipitation measurement mission. J Atmos Ocean Technol,2011,28(3):301-319.
[4] Bolen S M, Chandrasekar V. Quantitative cross validation of space-based and ground-based radar observations. J Appl Meteor,2000,39(12):2071-2079.
[5] Zhong Lingzhi,Yang Rongfang,Wen Yixin,et al. Cross-evaluation of reflectivity from the space-borne precipitation radar and multi-type ground-based weather radar network in China. Atmos Res,2017,196:200-210.
[6]商建,范学花.杨汝良.TRMM卫星测雨雷达与地基雷达的数据匹配问题研究.遥感技术与应用,2009,24(2):164-166.
[7]王成刚,葛文忠,魏鸣.TRMM PR雷达与阜阳雷达降水资料的对比研究.遥感学报,2003,7(4):332-336.
[8]王振会,李圣殷,戴建华,等.星载雷达与地基雷达数据的个例对比分析.高原气象,2015,34(3):804-814.
[9]陈廷娣,王连仲,窦贤康.TRMM卫星与机载雷达在降雨反演中的数据对比个例研究.应用气象学报.2008,19(4):454-462.
[10]李嘉睿,卢乃锰,谷松岩.青藏高原地区TRMM PR地面降雨率的修正.应用气象学报,2015,26(5):636-640.
[11]唐英杰,马舒庆,杨玲,等.云底高度的地基毫米波云雷达观测及其对比.应用气象学报,2015,26(6):680-687.
[12]何平,朱小燕,阮征,等.风廓线雷达探测降水过程的初步研究.应用气象学报,2009,20(4):465-470.
[13]高郁东,万齐林,薛纪善,等.同化雷达估算降水率对暴雨预报的影响.应用气象学报,2015,26(1):45-56.
[14]东高红,刘黎平.雷达与雨量计联合估测降水的相关性分析.应用气象学报,2012,23(1):30-39.
[15]史锐,程明虎,崔哲虎,等.用反射率因子垂直廓线联合雨量计校准估测夏季区域强降水.应用气象学报,2005,16(6):737-745.
[16]楚志刚,许丹,王振会,等.基于TRMM/PR的长江下游地基雷达一致性订正.应用气象学报,2018,29(3):296-306.
[17] Toshio I,and Coauthors. GPM/DPR Level-2 Algorithm Theoretical Basis Document. https://pmm. nasa. gov/sites/default/files/document_files/ATBD_GPM_DPR_n3_dec15.pdf.[2017-12-03].
[18]王强.综合气象观测.北京:气象出版社,2012.
[19]寇蕾蕾,楚志刚,李南,等.TRMM星载测雨雷达和地基雷达反射率因子数据的三维融合.气象学报,2016,74(2):285-297.
[20] Haynes JM,Marchand RT,LuoZ,etal.Amulti-purpose radar simulation package:QuickBeam. Bull Amer Meteor Soc,2007,88:1723-1727.
[21]张培昌,杜秉玉,戴铁丕.雷达气象学.北京:气象出版社,2001:122-123;183.
[22] Meneghini R,Jones J,Iguchi T,et al. A hybrid surface reference technique and its application to the TRMM precipitation radar. J Atmos Oceanic Technol,2004,21(11):1645-1658.
[23] Bolen S M,Chandrasekar V. Methodology for aligning and comparing space borne Radar and ground-based radar observations. J Atmos Oceanic Technol, 2003, 20:647-659.
[24] Tagawa T,Hanado H.Okamoto K,et al. Suppression of surface clutter interference with precipitation measurements byspace borne precipitation radar. IEEE Trans Geosci Remote Sens,2007,45:1324-1331.
[25] Takuji K,Toshio I,Masahiro K,et al. A statistical method for reducing sidelobe clutter for the Ku-band precipitation radar on board the GPM core observatory. J Atmos Ocean Technol,2016,33:1413-1428.
[26] Liao L,Robert M. Validation of TRMM precipitation radar through comparison of its multiyear measurements with ground-based radar. J Applied Meteorology and Climatology,2009,48:804-817.