利用高分辨率中尺度模式和地基GPS资料构造高时空分辨率的大气湿度廓线
|
摘要
预报强对流天气潜势的关键问题之一是了解大气的垂直稳定度和垂直风切变。目前预报员获取有关大气垂直稳定度和垂直风切变信息的主要方法是检验探空曲线。但现有的探空站网其时空密度无法提供足够详细的大气信息以指示发生强对流天气的潜势,而中尺度数值模式则可以输出高时空分辨率的各种模式变量,提供高时空分辨率的大气温湿风垂直廓线。主要问题是模式的温湿风廓线是否可靠。
利用北京2004年6月、7月和8月的加密探测资料,考察北京气象局3km分辨率的中尺度数值模式MM5对北京地区夏季对流发生的诊断分析能力,进行预报检验分析,估计模式温湿风垂直廓线和根据它们计算的对流诊断参数的可靠性。结果表明:模式模拟的各种大气廓线中,风廓线和温度廓线都具有一定的参考价值,但在廓线出现转折的地方,如:逆温层和风向转折时,模式预报较差。露点(湿度)廓线的预报误差较大,不能反映出真实水汽场的分布。模式预报的深层(地面～500hPa)垂直风切变与探空具有较好的一致性,而模式给出的对流有效位能CAPE由于温度和露点预报结果不理想,其值与实际偏差较大。因此模式输出的对流有效位能CAPE必须经过适当订正才能用于诊断强对流天气发生的可能性。
为订正大气模式预报的湿度廓线和对流参数CAPE值,本文利用探空的水汽总量和GPS层析的水汽资料对模式大气湿度廓线和CAPE值进行了订正。分别直接利用探空水汽总量、迭代法利用探空水汽总量、利用GPS层析水汽资料做了三种订正试验。结果表明,三种方法的效果成依次递增。直接利用探空水汽总量对模式预报的水汽廓线进行订正,模式水汽廓线订正后效果反而变差,由于模式预报的水汽分布不够合理,单纯对模式的水汽总量进行量值调整,而不改变模式水汽分布,会使水汽比实际偏大,从而导致CAPE值异常偏大。采取迭代法进行探空水汽总量订正后,采取逐层订正,并以模式预报的饱和比湿加以限制,湿度信息不再异常增大,订正后的CAPE值比直接订正的效果好,而且CAPE值的量值变化和这段时间大气实际观测的CAPE变化趋势相同,但是在CAPE值的预报数值还是不够准确。直接采用GPS层析技术得出的水汽密度廓线对模式预报进行订正,比湿廓线水汽变化趋势更接近实况,由此订正出来的CAPE值量值也更为接近,CAPE值的订正效果比前两种方法都好。
To forecast the strong convection weather, one of the key problems is to find out theatmospheric vertical stability and wind shear. Now for forecasters, checking the radiosondeobservation is the usual way to obtain information about the atmospheric vertical stability andwind shear. But the spatial and time resolution of the present radiosonde network cannotprovide sufficiently detailed information to indicate the possible appearance of the strongconvective weather. On the other hand, the Mesoscale Numerical Model is able to output allkinds of model variables with high resolution, and furthermore, provide the atmospherictemperature and humidity vertical profiles with high spatial and time resolution. The keyproblem is whether or these profiles are reliable .
Using the high resolution radiosonde data of Beijing in June , July, and August , 2004, themesoscale numerical model MM5 with a resolution of 3km of Beijing meteorological bureau ischecked to show its diagnosis ability for the possible occurrence of the convective weather insummer of Beijing, the reliability of the atmospheric temperature and humidity vertical profilesobtained from the numerical model as well as the convection diagnosis parameters which arecalculated from these profiles are estimated. Results show: in all kinds of atmospheric profilesobtained from the numerical model, the wind shear and temperature profiles both are valuableto some extent,while at the location where the profiles show a transition such as an temperatureinversion or a wind direction transition the simulation results are much poorer. The dew pointprofile show large error which cannot reflect the real distribution of the humidity field. Thevertical wind shear of the forecasting deep layer (from ground to 500hpa) shows a relative goodconsistence with the radiosonde observation, while the calculated CAPE value have largedifference with the real value because of the imperfect forecasting results of the temperature andhumidity . The CAPE value must be properly revised in order to diagnose the potential forecastof the strong convection weather.
This paper make use of the integrated precipitation water vapor of radiosonde andtomography vapor data of GPS to modify the humidity vertical profile and CAPE valueobtained from the model. Using the integrated precipitation water (PW) of radiosonde, theiterative PW data of radiosonde, and tomography vapor data of GPS respectively, we carry onthree numerical tests. Results show: The efficiency of these three methods is ascending in turn.
For the method directly using the radiosonde PW, the efficiency of the forecasting CAPE iseven worse after being modified, which is because that the forecasting atmospheric humiditydistribution is imperfect so that only by modifying the model's PW but not changing thehumidity distribution, the vapor may be larger than the real value and furthermore, and makethe CAPE value larger exceptionally. For the method using the iterative way to carry out thePW modification, due to carry on the modification layer by layer and make a limit for saturationspecific humidity (qs) by the forecasting results so that the humidity cannot increaseexceptionally, the CAPE value becomes much better than the direct method, while its variabletrend is consistence with the observation value and the error decreases a lot, but the forecastingnumerical CAPE value still does not has sufficient accuracy. Finally, directly using thetomography vapor density data of GPS to modify the model, the modified humidity profilebecomes further closer to the observation and the modified CAPE value becomes closer to theobservation either, which indicate that the effect of the modification for the CAPE value isbetter than the previous two methods.
利用北京2004年6月、7月和8月的加密探测资料,考察北京气象局3km分辨率的中尺度数值模式MM5对北京地区夏季对流发生的诊断分析能力,进行预报检验分析,估计模式温湿风垂直廓线和根据它们计算的对流诊断参数的可靠性。结果表明:模式模拟的各种大气廓线中,风廓线和温度廓线都具有一定的参考价值,但在廓线出现转折的地方,如:逆温层和风向转折时,模式预报较差。露点(湿度)廓线的预报误差较大,不能反映出真实水汽场的分布。模式预报的深层(地面～500hPa)垂直风切变与探空具有较好的一致性,而模式给出的对流有效位能CAPE由于温度和露点预报结果不理想,其值与实际偏差较大。因此模式输出的对流有效位能CAPE必须经过适当订正才能用于诊断强对流天气发生的可能性。
为订正大气模式预报的湿度廓线和对流参数CAPE值,本文利用探空的水汽总量和GPS层析的水汽资料对模式大气湿度廓线和CAPE值进行了订正。分别直接利用探空水汽总量、迭代法利用探空水汽总量、利用GPS层析水汽资料做了三种订正试验。结果表明,三种方法的效果成依次递增。直接利用探空水汽总量对模式预报的水汽廓线进行订正,模式水汽廓线订正后效果反而变差,由于模式预报的水汽分布不够合理,单纯对模式的水汽总量进行量值调整,而不改变模式水汽分布,会使水汽比实际偏大,从而导致CAPE值异常偏大。采取迭代法进行探空水汽总量订正后,采取逐层订正,并以模式预报的饱和比湿加以限制,湿度信息不再异常增大,订正后的CAPE值比直接订正的效果好,而且CAPE值的量值变化和这段时间大气实际观测的CAPE变化趋势相同,但是在CAPE值的预报数值还是不够准确。直接采用GPS层析技术得出的水汽密度廓线对模式预报进行订正,比湿廓线水汽变化趋势更接近实况,由此订正出来的CAPE值量值也更为接近,CAPE值的订正效果比前两种方法都好。
To forecast the strong convection weather, one of the key problems is to find out theatmospheric vertical stability and wind shear. Now for forecasters, checking the radiosondeobservation is the usual way to obtain information about the atmospheric vertical stability andwind shear. But the spatial and time resolution of the present radiosonde network cannotprovide sufficiently detailed information to indicate the possible appearance of the strongconvective weather. On the other hand, the Mesoscale Numerical Model is able to output allkinds of model variables with high resolution, and furthermore, provide the atmospherictemperature and humidity vertical profiles with high spatial and time resolution. The keyproblem is whether or these profiles are reliable .
Using the high resolution radiosonde data of Beijing in June , July, and August , 2004, themesoscale numerical model MM5 with a resolution of 3km of Beijing meteorological bureau ischecked to show its diagnosis ability for the possible occurrence of the convective weather insummer of Beijing, the reliability of the atmospheric temperature and humidity vertical profilesobtained from the numerical model as well as the convection diagnosis parameters which arecalculated from these profiles are estimated. Results show: in all kinds of atmospheric profilesobtained from the numerical model, the wind shear and temperature profiles both are valuableto some extent,while at the location where the profiles show a transition such as an temperatureinversion or a wind direction transition the simulation results are much poorer. The dew pointprofile show large error which cannot reflect the real distribution of the humidity field. Thevertical wind shear of the forecasting deep layer (from ground to 500hpa) shows a relative goodconsistence with the radiosonde observation, while the calculated CAPE value have largedifference with the real value because of the imperfect forecasting results of the temperature andhumidity . The CAPE value must be properly revised in order to diagnose the potential forecastof the strong convection weather.
This paper make use of the integrated precipitation water vapor of radiosonde andtomography vapor data of GPS to modify the humidity vertical profile and CAPE valueobtained from the model. Using the integrated precipitation water (PW) of radiosonde, theiterative PW data of radiosonde, and tomography vapor data of GPS respectively, we carry onthree numerical tests. Results show: The efficiency of these three methods is ascending in turn.
For the method directly using the radiosonde PW, the efficiency of the forecasting CAPE iseven worse after being modified, which is because that the forecasting atmospheric humiditydistribution is imperfect so that only by modifying the model's PW but not changing thehumidity distribution, the vapor may be larger than the real value and furthermore, and makethe CAPE value larger exceptionally. For the method using the iterative way to carry out thePW modification, due to carry on the modification layer by layer and make a limit for saturationspecific humidity (qs) by the forecasting results so that the humidity cannot increaseexceptionally, the CAPE value becomes much better than the direct method, while its variabletrend is consistence with the observation value and the error decreases a lot, but the forecastingnumerical CAPE value still does not has sufficient accuracy. Finally, directly using thetomography vapor density data of GPS to modify the model, the modified humidity profilebecomes further closer to the observation and the modified CAPE value becomes closer to theobservation either, which indicate that the effect of the modification for the CAPE value isbetter than the previous two methods.
引文
1. Obsty .F .P. Operations of national Severe Storms Forecast Center .Wea forecasting,1992,17 :546～562.
2. Mills G A. Colquhoun J R. Objective prediction of sever thunderstorm environments: preliminary results linking a decision tree with an operational regional NWP model,Wea forecasting,1998,13:1078～1092.
3. Wilson J W. Crook N A, Mueller C K. Nowcasting Thunderstorm :a status Report. .Bull. Amer. Meteor. Soc,1998,79:2079～2099
4. 王笑芳.丁一汇. 北京地区强对流天气短时预报方法的研究. 大气科学,1994,18(2):173～183
5 王改利. 刘黎平. 多普勒雷达资料在暴雨临近预报中的应用. 气象,2005,31(10):12～15
6. 廖玉芳. 潘志祥. 李德华等. 基于单多普勒天气雷达产品的短时预报预警业务工作平台. 广西气象, 2005,26(增刊一):97～99
7. 杜秉玉.姚祖庆. 上海地区强对流天气短时预报系统. 南京气象学院学报,2000,23(2):242～250
8. Sherwood S C. On moist instability.Mon Wea Rev , 2000,128:4139～4142
9. Gao shouting. Lei ting. Zhou Yushu. Moist potential vorticity anomaly with heat and mass forcings in torrential rain systems. Chin Phys Lettt,2002:878～880
10. Schultz D M. Schum macher P N. Doswell C A. The intricacies of instabilities .Mon Wea Rev,2000,128:4143～4148
11. Hart. Robert E. Forbes Gregory S. Grumm Richard H. The use of hourly odel-generated soundings to forecast mesoscale phenomena. Part I: Initial assessment in forecasting warm-season phenomena. Wea.forecasting,1998,13(4):1165-1185.
12. Hart. Robert E. Forbes Gregory S.The use of hourly model-generated soundings to forecast mesoscale phenomena Part II: initial assessment in forecasting nonconvective strong wind gusts. Wea.forecasting,1999,14(3):461-469.
13. Hart R. E. R.S Forbes. R.G. Soo. Forecasting studies using hourly model-generated soundings to forecast convective in the mid-Atlantic region. 16th Conf. on WAF(AMS),1997,Preprints 1997 :164-166.
14. Maddox R A. Doswell C A. An examination of jet stream configuration 500 mb vorticity advection and low-level thermal Advection patterns during extended periods of intense convection.Report. Mon Wea Rev,1985,110:184～197
15. John R H. Doswell C A. severe local storms forecasting. Wea.forecasting, 1992, 7: 588-612
16. Moncrieserf M W. Miller M J. the dynamics and simulation of tropical cumulonimbus and Squall lines. Quart J Roy Meteor Soc,1977,6, 102:373~394
17. Huntriesff H. Schiesser H H. Schmid W A. Comparison of Traditional and newly developed Thunderstorm in indicies for Switzerland. Wea.forecasting, 1997,12:108-125
18. Desautels G. Verret R. Canadian Meteorological Centre summer severe weather package In: Preprints, .18th conf . on Severe Local Storms. Amer Meteor Soc,1996:689~692
19. 李耀东.刘键文.刘玉玲等.爱玛图的微机制作和对流有效位能计算.气象,1998,24(1):21～23
20. D.O.B lanchard. 对流有效位能垂直分布作用的评估.(彭治班)气象科技,2000,2:34～40
21. 李耀东.刘键文.动力和能量参数在强对流天气预报中的应用研究.气象学报,2004,62(4):401～409
22. 李耀东.高守亭.刘键文.对流能量计算及强对流天气落区预报技术研究.应用气象学报,2004,15(1):10～20
23. 李吉顺.田生春.北京地区强对流环境风垂直分布的一些统计特征.强对流天气文集.北京:气象出版社,1981,149～152
24. 俞小鼎.姚秀萍.熊廷南等.多普勒天气雷达原理与业务应用.北京:气象出版社,2006,90～97
25. 俞小鼎.王迎春.陈明轩等.新一代天气雷达与强对流天气预警.高原气象,2005,24:410-416
26. 彭治班. 刘键文. 郭虎. 国外强对流天气的应用研究.北京:气象出版社,2000,89～140
27. 王叶红.崔春光.赵玉春.雷达降水资料一维变分同化研究-湿度廓线调整.科学通报, 2005,50(20):2271～2277
28. FedorMesinger. 周丽.对降水资料的四维变分同化.气象科技,1997,03:410-416
29. 王华荣. 郁凡. 用一维变分方法同化 GMS-5 反演湿度场及其在降水预报中的应用分析.南京大学学报(自然科学版) ,2006,01:410-416
30. 王超. 万丰. 张凤英等.数值预报/卫星反演/数据同化循环试验.气象学报,1997,06:410-416
31. Flores A. Ruffini.G. Rius A. 4D tropospheric tomography using GPS slant wet delays. Annales Geophysicae, 2000,18: 223～234
32. Lubomir P. Per JarLemark. Ground-Based GPS Tomography of water vapor:analysis of simulated and real data. Special issue of the Journal of the Meteorological Society of Japan, 2004,82(1):551～560
33. Ha S Y. Guo Y R. Roken C. Comparison of GPS Slant Wet Delay Measurements with Model Simulations during the Passage of a Squall Line. Geophys Res Lett, 2002,29(23):2113～2113
34. 宋淑丽.朱文耀.丁金才等.上海 GPS 综合应用网对 2002 年长江三角洲地区入梅过程的监测. 天文学进展, 2003,21(2):180～184.
35. 袁招洪.丁金才.陈永林.中尺度数值预报模式预报水汽与GPS观测的比较研究. 大气科学,2004,28(3):433-440.
36. 宋淑丽.朱文耀.丁金才等.上海 GPS 网层析水汽三纬分布改善数值预报湿度场.科学通报,2005,50(20):2271～2277
37. 王小亚.朱文耀.严豪健等.地面 GPS 探测大气可降水量的初步结果. 大气科学, 1999,23(5):605-612.
38. 梁丰.李成才.王迎春等.应用区域地区全球定位系统观测分析北京地区大气总水汽量.大气科学,2003,27(2):236～244.
39. 李延兴.徐宝祥.胡新康. 用地基 GPS 观测站遥测大气含水量和可降雨量的理论基础与试验结果.中国科学(A 辑),2000,30(增刊):107-110.
40. 丁金才.黄炎.叶其欣.2002年台风Ramasun影响华东沿海期间可降水量的GPS观测和分析. 大气科学,2004,128(14):613-624
41. 袁招洪.丁金才.陈敏. GPS 观测资料应用于中尺度数值预报模式的初步研究. 气象学报.2005,62(2):200-212.
42. 严豪健.朱文耀.黄王成.上海天文台 GPS 气象学的研究现状.中国科学院上海天文台年刊,2000,21:24-34.
43. 宋淑丽.朱文耀.程宗颐等.GPS 信号斜路径方向水汽含量的计算方法.天文学报, 2004,45(3):338～346
44. Ying-Hua kuo. Yong-Run Guo. ED R. Westwater. Assimilation of Precipitable Water Measurements into a Mesoscale Numerical model . Mon Wea Rev,1993,121:1215～1238
45. 盛裴轩.毛节泰.李建国. 大气物理学,北京大学出版社,2003,478-482
46. 陈创买.郭英琼.气象常用参数和物理量查算表.气象出版社,1983.
47. 谢璞.张朝林.王迎春等.北京地区单双频地基 GPS 大气水汽遥测试验与研究进展.奥运气象保障技术研究 2004 年度论文汇编. 北京:气象出版社,2004:165-171
48. Smith W.Note on the relationship between total precipitable water and surface dew point. J. Appl. Meteor.,1966,5:726～727.
49. Won T.The simulation of hourly global radiation from hourly reported meteorological parameters-Canadian Prairie Area.Conference 3rd,1977,Canadian Solar Energy Society Inc.Edmonton,Alberta.
50. Cole R. J. Direct solar radiation data as input into mathematical models describing the thermal performance of buildings, Part Ⅱ: Development of relationships, Build . Environ.,1976, 11: 181～186.
51.“北京地区地基 GPS 遥感水汽应用研究”课题组,北京地区地基 GPS 遥感大气水汽应用研究课题结题材料.北京城市气象工程技术研究中心,北京,2005.
52. 郑良杰.中尺度天气系统的诊断分析和数值模拟,北京:气象出版社,1989,94～123
53. 刘键文.郭虎.李耀东等.天气分析预报物理量计算基础.北京:气象出版社,2005.
55. Tammy M.Weckwerth. James W.Wilson. Roger M.Wakimoto. Thermodynamic Variability within the Convective Boundary Layer Due to Horizontal Convective Rolls. Monthly Weather Review,1996,124:769-784.
56.中国气象局北京城市气象研究所. 中国气象学会北京城市气象学委员会.美国国家大气研究中心(NCAR).中美强对流天气临近预报技术国际研讨会文集.北京:气象出版社,2004.
2. Mills G A. Colquhoun J R. Objective prediction of sever thunderstorm environments: preliminary results linking a decision tree with an operational regional NWP model,Wea forecasting,1998,13:1078～1092.
3. Wilson J W. Crook N A, Mueller C K. Nowcasting Thunderstorm :a status Report. .Bull. Amer. Meteor. Soc,1998,79:2079～2099
4. 王笑芳.丁一汇. 北京地区强对流天气短时预报方法的研究. 大气科学,1994,18(2):173～183
5 王改利. 刘黎平. 多普勒雷达资料在暴雨临近预报中的应用. 气象,2005,31(10):12～15
6. 廖玉芳. 潘志祥. 李德华等. 基于单多普勒天气雷达产品的短时预报预警业务工作平台. 广西气象, 2005,26(增刊一):97～99
7. 杜秉玉.姚祖庆. 上海地区强对流天气短时预报系统. 南京气象学院学报,2000,23(2):242～250
8. Sherwood S C. On moist instability.Mon Wea Rev , 2000,128:4139～4142
9. Gao shouting. Lei ting. Zhou Yushu. Moist potential vorticity anomaly with heat and mass forcings in torrential rain systems. Chin Phys Lettt,2002:878～880
10. Schultz D M. Schum macher P N. Doswell C A. The intricacies of instabilities .Mon Wea Rev,2000,128:4143～4148
11. Hart. Robert E. Forbes Gregory S. Grumm Richard H. The use of hourly odel-generated soundings to forecast mesoscale phenomena. Part I: Initial assessment in forecasting warm-season phenomena. Wea.forecasting,1998,13(4):1165-1185.
12. Hart. Robert E. Forbes Gregory S.The use of hourly model-generated soundings to forecast mesoscale phenomena Part II: initial assessment in forecasting nonconvective strong wind gusts. Wea.forecasting,1999,14(3):461-469.
13. Hart R. E. R.S Forbes. R.G. Soo. Forecasting studies using hourly model-generated soundings to forecast convective in the mid-Atlantic region. 16th Conf. on WAF(AMS),1997,Preprints 1997 :164-166.
14. Maddox R A. Doswell C A. An examination of jet stream configuration 500 mb vorticity advection and low-level thermal Advection patterns during extended periods of intense convection.Report. Mon Wea Rev,1985,110:184～197
15. John R H. Doswell C A. severe local storms forecasting. Wea.forecasting, 1992, 7: 588-612
16. Moncrieserf M W. Miller M J. the dynamics and simulation of tropical cumulonimbus and Squall lines. Quart J Roy Meteor Soc,1977,6, 102:373~394
17. Huntriesff H. Schiesser H H. Schmid W A. Comparison of Traditional and newly developed Thunderstorm in indicies for Switzerland. Wea.forecasting, 1997,12:108-125
18. Desautels G. Verret R. Canadian Meteorological Centre summer severe weather package In: Preprints, .18th conf . on Severe Local Storms. Amer Meteor Soc,1996:689~692
19. 李耀东.刘键文.刘玉玲等.爱玛图的微机制作和对流有效位能计算.气象,1998,24(1):21～23
20. D.O.B lanchard. 对流有效位能垂直分布作用的评估.(彭治班)气象科技,2000,2:34～40
21. 李耀东.刘键文.动力和能量参数在强对流天气预报中的应用研究.气象学报,2004,62(4):401～409
22. 李耀东.高守亭.刘键文.对流能量计算及强对流天气落区预报技术研究.应用气象学报,2004,15(1):10～20
23. 李吉顺.田生春.北京地区强对流环境风垂直分布的一些统计特征.强对流天气文集.北京:气象出版社,1981,149～152
24. 俞小鼎.姚秀萍.熊廷南等.多普勒天气雷达原理与业务应用.北京:气象出版社,2006,90～97
25. 俞小鼎.王迎春.陈明轩等.新一代天气雷达与强对流天气预警.高原气象,2005,24:410-416
26. 彭治班. 刘键文. 郭虎. 国外强对流天气的应用研究.北京:气象出版社,2000,89～140
27. 王叶红.崔春光.赵玉春.雷达降水资料一维变分同化研究-湿度廓线调整.科学通报, 2005,50(20):2271～2277
28. FedorMesinger. 周丽.对降水资料的四维变分同化.气象科技,1997,03:410-416
29. 王华荣. 郁凡. 用一维变分方法同化 GMS-5 反演湿度场及其在降水预报中的应用分析.南京大学学报(自然科学版) ,2006,01:410-416
30. 王超. 万丰. 张凤英等.数值预报/卫星反演/数据同化循环试验.气象学报,1997,06:410-416
31. Flores A. Ruffini.G. Rius A. 4D tropospheric tomography using GPS slant wet delays. Annales Geophysicae, 2000,18: 223～234
32. Lubomir P. Per JarLemark. Ground-Based GPS Tomography of water vapor:analysis of simulated and real data. Special issue of the Journal of the Meteorological Society of Japan, 2004,82(1):551～560
33. Ha S Y. Guo Y R. Roken C. Comparison of GPS Slant Wet Delay Measurements with Model Simulations during the Passage of a Squall Line. Geophys Res Lett, 2002,29(23):2113～2113
34. 宋淑丽.朱文耀.丁金才等.上海 GPS 综合应用网对 2002 年长江三角洲地区入梅过程的监测. 天文学进展, 2003,21(2):180～184.
35. 袁招洪.丁金才.陈永林.中尺度数值预报模式预报水汽与GPS观测的比较研究. 大气科学,2004,28(3):433-440.
36. 宋淑丽.朱文耀.丁金才等.上海 GPS 网层析水汽三纬分布改善数值预报湿度场.科学通报,2005,50(20):2271～2277
37. 王小亚.朱文耀.严豪健等.地面 GPS 探测大气可降水量的初步结果. 大气科学, 1999,23(5):605-612.
38. 梁丰.李成才.王迎春等.应用区域地区全球定位系统观测分析北京地区大气总水汽量.大气科学,2003,27(2):236～244.
39. 李延兴.徐宝祥.胡新康. 用地基 GPS 观测站遥测大气含水量和可降雨量的理论基础与试验结果.中国科学(A 辑),2000,30(增刊):107-110.
40. 丁金才.黄炎.叶其欣.2002年台风Ramasun影响华东沿海期间可降水量的GPS观测和分析. 大气科学,2004,128(14):613-624
41. 袁招洪.丁金才.陈敏. GPS 观测资料应用于中尺度数值预报模式的初步研究. 气象学报.2005,62(2):200-212.
42. 严豪健.朱文耀.黄王成.上海天文台 GPS 气象学的研究现状.中国科学院上海天文台年刊,2000,21:24-34.
43. 宋淑丽.朱文耀.程宗颐等.GPS 信号斜路径方向水汽含量的计算方法.天文学报, 2004,45(3):338～346
44. Ying-Hua kuo. Yong-Run Guo. ED R. Westwater. Assimilation of Precipitable Water Measurements into a Mesoscale Numerical model . Mon Wea Rev,1993,121:1215～1238
45. 盛裴轩.毛节泰.李建国. 大气物理学,北京大学出版社,2003,478-482
46. 陈创买.郭英琼.气象常用参数和物理量查算表.气象出版社,1983.
47. 谢璞.张朝林.王迎春等.北京地区单双频地基 GPS 大气水汽遥测试验与研究进展.奥运气象保障技术研究 2004 年度论文汇编. 北京:气象出版社,2004:165-171
48. Smith W.Note on the relationship between total precipitable water and surface dew point. J. Appl. Meteor.,1966,5:726～727.
49. Won T.The simulation of hourly global radiation from hourly reported meteorological parameters-Canadian Prairie Area.Conference 3rd,1977,Canadian Solar Energy Society Inc.Edmonton,Alberta.
50. Cole R. J. Direct solar radiation data as input into mathematical models describing the thermal performance of buildings, Part Ⅱ: Development of relationships, Build . Environ.,1976, 11: 181～186.
51.“北京地区地基 GPS 遥感水汽应用研究”课题组,北京地区地基 GPS 遥感大气水汽应用研究课题结题材料.北京城市气象工程技术研究中心,北京,2005.
52. 郑良杰.中尺度天气系统的诊断分析和数值模拟,北京:气象出版社,1989,94～123
53. 刘键文.郭虎.李耀东等.天气分析预报物理量计算基础.北京:气象出版社,2005.
55. Tammy M.Weckwerth. James W.Wilson. Roger M.Wakimoto. Thermodynamic Variability within the Convective Boundary Layer Due to Horizontal Convective Rolls. Monthly Weather Review,1996,124:769-784.
56.中国气象局北京城市气象研究所. 中国气象学会北京城市气象学委员会.美国国家大气研究中心(NCAR).中美强对流天气临近预报技术国际研讨会文集.北京:气象出版社,2004.