[1]孙晨玥,戴 强*,纪端阳,等.基于多相态KE-I关系的降水动能计算方法[J].山地学报,2023,(5):771-784.[doi:10.16089/j.cnki.1008-2786.000786]
　SUN Chenyue,DAI Qiang*,JI Duanyang,et al.Calculation of Precipitation Kinetic Energy Based on Multi-Phase KE-I Relationship[J].Mountain Research,2023,(5):771-784.[doi:10.16089/j.cnki.1008-2786.000786]
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基于多相态KE-I关系的降水动能计算方法
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2023年第5期
页码:
771-784
栏目:
山区技术
出版日期:
2023-09-25

文章信息/Info

Title:
Calculation of Precipitation Kinetic Energy Based on Multi-Phase KE-I Relationship
文章编号:
1008-2786-(2023)5-771-14
作者:
孙晨玥1; 戴 强1*; 纪端阳1; 顾 于1; 刘超楠1; 李雁鹏2
(1.南京师范大学 地理科学学院,南京 210023; 2.中国气象局 公共气象服务中心,北京 100081)
Author(s):
SUN Chenyue1;  DAI Qiang1*;  JI Duanyang1;  GU Yu1;  LIU Chaonan1;  LI Yanpeng2
(1.School of Geography, Nanjing Normal University, Nanjing 210023, China; 2. Public Meteorological Service Center, China Meteorological Administration, Beijing 100081, China)
关键词:
降水动能;  雨滴谱;  KE-I;  降水强度;  相态分类;  偏差计算
Keywords:
precipitation kinetic energy;  raindrop spectrometer;  KE-I;  precipitation intensity;  phase classification;  deviation calculation
分类号:
P412.13
DOI:
10.16089/j.cnki.1008-2786.000786
文献标志码:
A
摘要:
降水动能描述了水凝物到达地表的动能大小,是计算土壤颗粒分离和土壤侵蚀等地表物理化学过程的重要参数之一。针对目前降水动能计算多考虑降雨特征,忽略其他相态降水的问题,本研究基于2018年全国25个雨滴谱仪站点的降水观测数据,结合速度(V)-直径(D)关系对水凝物进行相态划分,拟合了不同相态降水的降水动能-降水强度(KEV-I)经验公式,总结出适用于雨、雪、雹的动能计算关系模型,并对各相态降水动能进行偏差分析和校正。结果表明:(1)降雨动能计算适用KEV-I指数型关系公式,降雪和降雹动能计算适用幂函数型关系公式;(2)降水动能偏差与总降水中非液态占比呈正相关,仅以降雨KEV-I经验公式估算所有相态降水的动能会显著高估降雪动能和低估降雹动能,对降水整体估算偏差在-0.05到0.31之间;(3)通过建立各相态的KEV-I计算模型,降水整体估算误差得到有效降低,降雪偏差从7.08降至-0.05,降雹偏差从-0.29降至0.03。本文所提出的方法能够有效提高降水动能估算的准确度,为区域土壤水力侵蚀计算提供更好的支撑。
Abstract:
Precipitation kinetic energy, which describes the magnitude of the kinetic energy of hydrometeor reaching earth surface, is one of the important parameters for calculating surface physicochemical processes such as soil particle separation and soil erosion. Rainfall characteristics were often considered in the calculation of precipitation kinetic energy, but precipitation in other phases was ignored.
In this study, it started from a primitive phase classification of hydro-condensate, followed by an analysis of the correlation between kinetic energy per unit volume of precipitation(KEV)and precipitation intensity(I); based on meteorological observations at 25 raindrop spectrometer stations nationwide in 2018, it further classified hydrometeor into phases by examining velocity(V)-diameter(D)correlation of hydrometeor; after fitting empirical equations of KEV-I for precipitation in different phases, it introduced a series of precipitation kinetic energy estimation models applicable to rainfall, snowfall, and hailfall. The statistical significance of KEV-I fitting was carefully justified by field observations in terms of Relative Error(RE), Mean Absolute Error(MAE), and Root Mean Square Error(RMSE).
It found that(1)the KEV-I exponential type formula was applied to the calculation of rainfall kinetic energy, and the KEV-I power function type formula was applied to the calculation of snowfall and hailfall kinetic energy.(2)The deviation of calculating precipitation kinetic energy was positively correlated with non-liquid fraction of total precipitation. Supposing that the kinetic energy of all phases of precipitation were estimated entirely by the KEV-I fitting of rainfall, it would significantly overestimated snowfall kinetic energy but underestimated the hailfall kinetic energy, with a deviation of -0.05 to 0.31 in extent from an overall precipitation estimate.(3)By establishing separate KEV-I calculation model for respective phase of precipitation, the overall estimation error of precipitation was effectively reduced. The snowfall deviation was reduced from 7.08 to -0.05, and the hailfall deviation was reduced from -0.29 to 0.03.
The method proposed in this paper effectively improved the accuracy of precipitation kinetic energy estimation, providing better support for the calculation of regional soil hydraulic erosion.

参考文献/References:

[1] BERGHUIJS W R, WOODS R A, HRACHOWITZ M. A precipitation shift from snow towards rain leads to a decrease in streamflow [J]. Nature Climate Change, 2018, 4(7): 583-586. DOI: 10.1038/NCLIMATE2246
[2] FORNIS R L, VERMEULEN H R, NIEUWENHUIS J D. Kinetic energy-rainfall intensity relationship for Central Cebu, Philippines for soil erosion studies [J]. Journal of Hydrology, 2005, 300: 20-32. DOI: 10.1016/j.jhydrol.2004.04.027
[3] VAN DIJK A I J M, BRUIJNZEEL L A, ROSEWELL C J. Rainfall intensity-kinetic energy relationships: A critical literature appraisal [J]. Journal of Hydrology, 2002, 261(14): 1-23. DOI: 10.1016/S0022-1694(02)00020-3
[4] BROWN T M, POGORZELSKI W H, GIAMMANCO I M. Evaluating hail damage using property insurance claims data [J]. Weather, Climate and Society, 2015, 7(3): 197-210. DOI: 10.1175/WCAS-D-15-0011.1
[5] LOFTUS A M, COTTON W R, CARRIO G G. A triple-moment hail bulk microphysics scheme. Part I: Description and initial evaluation [J]. Atmospheric Research, 2014, 149: 35-37. DOI: 10.1016/j.atmosres.2014.05.013
[6] MINEO C, RIDOLFI E, BERTINI C, et al. Kinetic energy and rainfall intensity relationships: A review [G]// AIP Conference Proceedings. Proceedings of International Conference of Numerical Analysis and Applied Mathematics. Rhodes: AIP Publishing, 2019: 210005-1-210005-4. DOI: 10.1063/1.5114216
[7] ANGULO-MARTÍNEZ M, BEGUERÍA S, KYSELY' J. Use of disdrometer data to evaluate the relationship of rainfall kinetic energy and intensity(KE-I)[J]. Science of the Total Environment, 2016, 568: 83-94. DOI: 10.1016/j.scitotenv.2016.05.223
[8] JAYAWARDENA A W, REZAUR R B. Drop size distribution and kinetic energy load of rainstorms in Hong Kong [J]. Hydrological Processes, 2000, 14(6): 1069-1082. DOI: 10.1002/(SICI)1099-1085(20000430)14:6<1069::AID-HYP997>3.0.CO; 2-Q
[9] SALLES C, POESEN J, SEMPERE-TORRES D. Kinetic energy of rain and its functional relationship with intensity [J]. Journal of Hydrology, 2002, 257: 256-270. DOI: 10.1016/S0022-1694(01)00555-8
[10] LIM Y S, KIM J K, KIM J W, et al. Analysis of the relationship between the kinetic energy and intensity of rainfall in Daejeon, Korea [J]. Quaternary International, 2015, 384: 107-117. DOI: 10.1016/j.quaint.2015.03.021
[11] USÓN A, RAMOS M C. An improved rainfall erosivity index obtained from experimental interrill soil losses in soils with a Mediterranean climate [J]. Catena, 2001, 43(4): 293-305. DOI: 10.1016/S0341-8162(00)00150-8
[12] PETAN S, RUSJAN S, VIDMAR A, et al. The rainfall kinetic energy-intensity relationship for rainfall erosivity estimation in the mediterranean part of Slovenia [J]. Journal of Hydrology, 2010, 391(3-4): 314-321. DOI: 10.1016/j.jhydrol.2010.07.031
[13] NEARING M A, YIN S Q, BORRELLI P, et al. Rainfall erosivity: An historical review [J]. Catena, 2017, 157: 357-362. DOI: 10.1016/j.catena.2017.06.004
[14] 陈洁, 刘玉洁, 潘韬, 等. 1961—2010年中国降水时空变化特征及对地表干湿状况影响[J]. 自然资源学报, 2019, 34(11): 2440-2453. [CHEN Jie, LIU Yujie, PAN Tao, et al. Spatiotemporal variation of precipitation in China and its impact on surface dry-wet conditions during 1961-2010 [J]. Journal of Natural Resources, 2019, 34(11): 2440-2453] DOI: 10.31497/zrzyxb.20191115
[15] 李林, 孙赫敏, 仰美霖, 等. 基于速度和数量阈值的雨滴谱质量控制方法[J]. 气象, 2022, 48(7): 891-898. [LI Lin, SUN Hemin, YANG Meilin, et al. Disdrometer's data quality control method based on speed and quantity threshold [J]. Meteorological Monthly, 2022, 48(7): 891-898] DOI: 10.7519/j.issn.1000-0526.2022.041201
[16] GOU Yabin, CHEN Haonan, ZHU Hong, et al. Microphysical processes of super typhoon Lekima(2019)and their impacts on polarimetric radar remote sensing of precipitation [J]. Atmospheric Chemistry and Physics, 2023, 23(4): 2439-2463. DOI: 10.5194/acp-23-2439-2023
[17] LÖFFLER-MANG M, JOSS J. An optical disdrometer for measuring size and velocity of hydrometeors [J]. Journal of Atmospheric and Oceanic Technology, 2000, 17(2): 130-139. DOI: 10.1175/1520-0426(2000)017<0130:AODFMS>2.0.CO; 2
[18] ATLAS D, SRIVASTAVA R C, SEKHON R S. Doppler radar characteristics of precipitation at vertical incidence [J]. Reviews of Geophysics and Space Physics, 1973, 11(1): 1-35. DOI: 10.1029/RG011i001p00001
[19] FRIEDRICH K, KALINA E A, MASTERS F J, et al. Drop-size distributions in thunderstorms measured by optical disdrometers during VORTEX2 [J]. Monthly Weather Review, 2013, 141(4): 1182-1203. DOI: 10.1175/MWR-D-12-00116.1
[20] 陶然亭. 基于二维视频雨滴谱仪和双偏振雷达研究中国东部地区降雪微物理特征与降雪估计[D]. 南京: 南京大学, 2020: 1-73. [TAO Ranting. Snow microphysical characteristics and snow fall estimation in East China based on a 2D video disdrometer and dual polarization radar [D]. Nanjing: Nanjing University, 2020: 1-73] DOI: 10.27235/d.cnki.gnjiu.2020.002509
[21] GRIESER J, HILL M. How to express hail intensity—modeling the hailstone size distribution [J]. Journal of Applied Meteorology and Climatology, 2019, 58(10): 2329-2345. DOI: 10.1175/JAMC-D-18-0334.1
[22] DAI Qiang, ZHU Jingxuan, ZHANG Shuliang, et al. Estimation of rainfall erosivity based on WRF-derived raindrop size distributions [J]. Hydrology and Earth System Sciences, 2020, 24(11): 5407-5422. DOI: 10.5194/hess-24-5407-2020
[23] KIM J, HAN H, KIM B, et al. Use of a high-resolution-satellite-based precipitation product in mapping continental-scale rainfall erosivity: A case study of the United States [J]. Catena, 2020, 193: 104602. DOI: 10.1016/j.catena.2020.104602
[24] MONTERO-MARTÍNEZ G, GARCÍA-GARCÍA F, ARENAL-CASAS S. The change of rainfall kinetic energy content with altitude [J]. Journal of Hydrology, 2020, 584: 124685. DOI: 10.1016/j.jhydrol.2020.124685
[25] CHEN Hao, ZHANG Xiaoping, ABLA M, et al. Effects of vegetation and rainfall types on surface runoff and soil erosion on steep slopes on the Loess Plateau, China [J]. Catena, 2018, 170: 141-149. DOI: 10.1016/j.catena.2018.06.006
[26] ZHU Jingxuan, ZHANG Shuliang, YANG Qiqi, et al. Comparison of rainfall microphysics characteristics derived by numerical weather prediction modelling and dual-frequency precipitation radar [J]. Meteorological Applications, 2021, 28(3): e2000. DOI: 10.1002/met.2000
[27] WILLMOTT C J, MATSUURA K. Advantages of the mean absolute error(MAE)over the root mean square error(RMSE)in assessing average model performance [J]. Climate Research, 2005, 30(1): 79-82. DOI: 10.3354/cr030079
[28] 于水燕, 毕力格, 苏立娟, 等. 内蒙古巴彦淖尔市冰雹云移动路径及其特征[J]. 干旱区研究, 2022, 39(4): 1047-1055. [YU Shuiyan, BI Lige, SU Lijuan, et al. Movement paths and characteristics of hail clouds in Bayannur, Inner Mongolia [J]. Arid Zone Research, 2022, 39(4): 1047-1055] DOI: 10.13866/j.azr.2022.04.06
[29] 韩经纬, 王海梅, 乌兰, 等. 内蒙古雷暴、冰雹灾害的评估分析与防御对策研究[J]. 干旱区资源与环境, 2009, 23(7): 31-38. [HAN Jingwei, WANG Haimei, WU Lan, et al. The analysis and assessment on thunderstorm and hail disasters and the countermeasures in Inner Mongolia [J]. Journal of Arid Land Resources and Environment, 2009, 23(7): 31-38] DOI: 10.13448/j.cnki.jalre.2009.07.008
[30] 冯晓莉, 马占良, 管琴, 等. 1980—2018年青海高原冰雹分布特征及其关键影响因素分析 [J]. 气象, 2021, 47(6): 717-726. [FENG Xiaoli, MA Zhanliang, GUAN Qin, et al. Spatio-temporal characteristics of hail and its influence factors in Qinghai Plateau during 1980-2018 [J]. Meteorological Monthly, 2021, 47(6): 717-726] DOI: 10.7519/j.issn.1000-0526.2021.06.007
[31] 黄艳, 裴江文. 新疆喀什地区冰雹气候特征及大气环境背景分析[J]. 干旱区研究, 2015, 32(3): 526-532. [HUANG Yan, PEI Jiangwen. Hail climate characteristics and atmospheric environment background in Kashi region, Xinjiang [J]. Arid Zone Research, 2015, 32(3): 526-532] DOI: 10.13866/j.azr.2015.03.17
[32] 王昀, 卢品睿, 王旭. 天山南侧喀什地区冰雹潜势预报及预警指标的研究[J]. 干旱区地理, 2018, 41(5): 937-944. [WANG Yun, LU Pinrui, WANG Xu. Nowcasting indicators of radar of hail cloud in southern Tianshan Mountains [J]. Arid Land Geography, 2018, 41(5): 937-944] DOI: 10.12118/j.issn.1000-6060.2018.05.05

备注/Memo

备注/Memo:
收稿日期(Received date): 2023-04-08; 改回日期(Accepted date):2023-10-13
基金项目(Foundation item): 国家自然科学基金(42371409,41871299)。[National Natural Science Foundation of China(42371409, 41871299)]
作者简介(Biography): 孙晨玥(2001-),女,天津人,本科生,主要研究方向:降水观测与模拟。[SUN Chenyue( 2001-), female, born in Tianjin, B.S. candidate, research on precipitation observation and simulation] E-mail: 10200123@njnu.edu.cn
*通讯作者(Corresponding author): 戴强(1987-),男,江苏扬中人,博士,教授,主要研究方向:水文遥感与地理建模。[DAI Qiang(1987-), male, born in Yangzhong, Jiangsu province, Ph.D., professor, research on hydrological remote sensing and geographic modeling] E-mail: q.dai@njnu.edu.cn
更新日期/Last Update: 2023-09-30