和AMSU-B微波资料估测黑龙江省降水
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摘要
本文利用FY-2静止红外卫星和NOAA极轨卫星的AMSU-B微波资料资进行定量降水估测,并对两种方法的估测效果进行检验,讨论和分析了其误差产生原因及改进方法。在此基础上,利用静止卫星资料结合微波资料对卫星云图反演降水方法进行改进,结果显示定量估测结果得到明显改善。
静止卫星资料估测降水采用的是云指数法,利用云顶亮温,采用逐步回归的方法估测降水。微波资料反演降水由于是对降水粒子的直接探测,物理意义明确。该方法首先建立积云模型,得到微波方程,再通过通道匹配法得到反演的降水数据。静止卫星资料结合微波资料估测方法是：先利用微波资料反演降水的方法,结合加密自动雨量站,检验该方法反演效果。如果反演效果较好,确定主要降水区和降水量级,然后再利用静止红外卫星估测降水的方法继续跟踪对流云团,确定降水区的移动方向和移动速度,并初步确定降水量强度的变化情况。
通过两种方法的估测降水工作的得到如下结果：
(1)静止卫星资料获取便捷,FY-2静止红外卫星云图作为该方法唯一基础性资料,相对于所有气象台都可以利用该方法快速估测降水,由于强对流云团产生的降水空间分布寸在较大的不均匀性,这加大了误差程度；利用微波资料定量降水估测由于空间分辨率高,物理意义明确所以得到的估测结果比较令人满意,但是由于微波资料获取的局限性,使得应用者无法得到一个时间上精细的降水估测结果。静止卫星资料结合微波资料对卫星云图反演降水方法可以同时满足高的时间和空间分辨率,做到定时、定点、定量估测。
(2)FY-2静止红外卫星估测降水对1mm以下或无降水区的估测准确率比较高,10-24.9mm/h的定量估测准确率达到65-70%,对大于25mm/h的估测准确率则非常低,仅为30%左右。利用微波资料反演降水的效果比较好,在降水落区和降水定量估测上效果都比较好,对降水量大于20mm估测准确率达到50%,基本准确率为75%。两种方法相结合估测降水基本可以达到微波资料估测降水的准确率又可以利用静止卫星资料方法估测做实时订正。
(3)FY-2静止红外卫星估测降水误差的主要原因在于：①即使同一像素内部不同地点的降水强度也会有很大差异,地面雨量站的雨量记录代表性本身就存在误差；②当云团处于生命期旺盛阶段至消散阶段初期时,估测的结果往往偏小,特别是对短时强降水很难估测；反之,当云团处于生命期初始阶段时,估测结果往往偏大。③当水汽条件比较好的时,产生的降水强度往往比较大,而云顶温度有时却难以表现出这种水汽状态,导致估测结果往往偏小；反之,当水汽条件比较差时,容易造成降水的估测结果往往偏大。
(4)由于这两种估测降水方法的优缺点各有不同,所以利用两种方法相结合的方式估测降水区和降水量得到了更好的效果。方法是：先利用微波资料反演降水方法初步判断降水区与降水量级,判断结果与实况结果吻合较好时,再利用FY-2静止红外卫星云图估测降水的方法更新降水区的移动和降水强度的变化,最后达到更加准确有效的利用卫星资料做定时、定点、定量降水估测的效果。
The quantificational rainfall is estimated by data from FY-2 satellite and AMSU-B microwave on NOAA with the two methods as well as testing, and discussing their error, and the improved method was giving in this dissertation. In order to quantitative estimation results obvious, microwave material satellite inversion precipitation method is modified combination the stationary satellite data on the base of above mentioned.
The method of Static satellite estimates of precipitation is cloud index method, which get the rainfall estimation by stepwise regression method with the cloud top brightness temperature. The method of Microwave material inversion rainfall precipitation is based on the directly detection for particles, which has clearly physical meaning. In this method, the cumulus clouds model must be established to get microwave equation at first, and the estimation of precipitation is inversed through channels matched. The method of Static satellite data combining microwave material estimates precipitation through the inversion of microwave material, and the encryption Automatic Rainfall Station data is used to verify the inversed results. If we get a better results and then, the main precipitation area and precipitation grades is confirmed. Thus, we can use the method of stationary infrared satellite rainfall estimation to trace the convective cloud cluster, determine the moving direction and speed of the precipitation area as well as the variation of rainfall intensity.
Two method of estimation the rainfall were tested with several cases of rainstorm which occurred in HeilongJiang Province, The mainly results as follwing:
(1) The method of Static satellite estimation is a rapid method on estiamating rainfall for all meteorological offices due to the Static satellite data acquisition is convenient and FY-2 static infrared satellite images are the basic material. The extremely inhomogeneous spatial distribution of precipitation produced by strong convective clouds will increase the degree of error; The method of microwave material to estimate the quantitatively precipitation is satisfaction duing to high spatial resolution and clearly physical meaning, for users, it would not get a time fine precipitation estimation because of the limitation of getting microwave data. The method of combined the Static satellite data and microwave material to estimate precipitation not only meet high temporal and spatial resolution, but also estimate the quantitative precipitation at achieve timed and fixed point.
(2) The accuracy rate of estimation of precipitation using FY-2 static infrared satellite is higher for precipitation rate which below 1mm per hour and no precipitation area, which is about 65-70% for precipitation rate between 10 and 24.9mm per hour. When the precipitation rate reached 25mm per hour, the estimated accuracy rate is very low, about 30%. The method of microwave material inversion precipitation effect get a better results, the estimated accuracy rate can reach 50% for precipitation rate larger than 20mm per hour and 75% for basic accuracy rate. The combination of two methods can not only achieve the accuracy rate of microwave material for precipitation's estimation but also do real-time corrections on the variation of precipitation intensity by Static satellite data.
(3) The large estimation error of FY-2 infrared satellite estimated rainfall may be caused by the following factors:①The difference of precipitation is obvious in different locations even within the same pixel and the representation of ground rainfall stations record have itself errors;②The estimated results are often small for the blooming and disspating cloud cluster, especially for short-time heavy rainfall which are often larger for the initial period of the cloud cluster;③The temperature at cloud top could not show the water vapor characters of abundant moisture conditions which can caused the stronger precipitation intensity, the estimated results is smaller in this condition; The estimated precipitation intensity is stronger in the poor water vapor condition.
静止卫星资料估测降水采用的是云指数法,利用云顶亮温,采用逐步回归的方法估测降水。微波资料反演降水由于是对降水粒子的直接探测,物理意义明确。该方法首先建立积云模型,得到微波方程,再通过通道匹配法得到反演的降水数据。静止卫星资料结合微波资料估测方法是：先利用微波资料反演降水的方法,结合加密自动雨量站,检验该方法反演效果。如果反演效果较好,确定主要降水区和降水量级,然后再利用静止红外卫星估测降水的方法继续跟踪对流云团,确定降水区的移动方向和移动速度,并初步确定降水量强度的变化情况。
通过两种方法的估测降水工作的得到如下结果：
(1)静止卫星资料获取便捷,FY-2静止红外卫星云图作为该方法唯一基础性资料,相对于所有气象台都可以利用该方法快速估测降水,由于强对流云团产生的降水空间分布寸在较大的不均匀性,这加大了误差程度；利用微波资料定量降水估测由于空间分辨率高,物理意义明确所以得到的估测结果比较令人满意,但是由于微波资料获取的局限性,使得应用者无法得到一个时间上精细的降水估测结果。静止卫星资料结合微波资料对卫星云图反演降水方法可以同时满足高的时间和空间分辨率,做到定时、定点、定量估测。
(2)FY-2静止红外卫星估测降水对1mm以下或无降水区的估测准确率比较高,10-24.9mm/h的定量估测准确率达到65-70%,对大于25mm/h的估测准确率则非常低,仅为30%左右。利用微波资料反演降水的效果比较好,在降水落区和降水定量估测上效果都比较好,对降水量大于20mm估测准确率达到50%,基本准确率为75%。两种方法相结合估测降水基本可以达到微波资料估测降水的准确率又可以利用静止卫星资料方法估测做实时订正。
(3)FY-2静止红外卫星估测降水误差的主要原因在于：①即使同一像素内部不同地点的降水强度也会有很大差异,地面雨量站的雨量记录代表性本身就存在误差；②当云团处于生命期旺盛阶段至消散阶段初期时,估测的结果往往偏小,特别是对短时强降水很难估测；反之,当云团处于生命期初始阶段时,估测结果往往偏大。③当水汽条件比较好的时,产生的降水强度往往比较大,而云顶温度有时却难以表现出这种水汽状态,导致估测结果往往偏小；反之,当水汽条件比较差时,容易造成降水的估测结果往往偏大。
(4)由于这两种估测降水方法的优缺点各有不同,所以利用两种方法相结合的方式估测降水区和降水量得到了更好的效果。方法是：先利用微波资料反演降水方法初步判断降水区与降水量级,判断结果与实况结果吻合较好时,再利用FY-2静止红外卫星云图估测降水的方法更新降水区的移动和降水强度的变化,最后达到更加准确有效的利用卫星资料做定时、定点、定量降水估测的效果。
The quantificational rainfall is estimated by data from FY-2 satellite and AMSU-B microwave on NOAA with the two methods as well as testing, and discussing their error, and the improved method was giving in this dissertation. In order to quantitative estimation results obvious, microwave material satellite inversion precipitation method is modified combination the stationary satellite data on the base of above mentioned.
The method of Static satellite estimates of precipitation is cloud index method, which get the rainfall estimation by stepwise regression method with the cloud top brightness temperature. The method of Microwave material inversion rainfall precipitation is based on the directly detection for particles, which has clearly physical meaning. In this method, the cumulus clouds model must be established to get microwave equation at first, and the estimation of precipitation is inversed through channels matched. The method of Static satellite data combining microwave material estimates precipitation through the inversion of microwave material, and the encryption Automatic Rainfall Station data is used to verify the inversed results. If we get a better results and then, the main precipitation area and precipitation grades is confirmed. Thus, we can use the method of stationary infrared satellite rainfall estimation to trace the convective cloud cluster, determine the moving direction and speed of the precipitation area as well as the variation of rainfall intensity.
Two method of estimation the rainfall were tested with several cases of rainstorm which occurred in HeilongJiang Province, The mainly results as follwing:
(1) The method of Static satellite estimation is a rapid method on estiamating rainfall for all meteorological offices due to the Static satellite data acquisition is convenient and FY-2 static infrared satellite images are the basic material. The extremely inhomogeneous spatial distribution of precipitation produced by strong convective clouds will increase the degree of error; The method of microwave material to estimate the quantitatively precipitation is satisfaction duing to high spatial resolution and clearly physical meaning, for users, it would not get a time fine precipitation estimation because of the limitation of getting microwave data. The method of combined the Static satellite data and microwave material to estimate precipitation not only meet high temporal and spatial resolution, but also estimate the quantitative precipitation at achieve timed and fixed point.
(2) The accuracy rate of estimation of precipitation using FY-2 static infrared satellite is higher for precipitation rate which below 1mm per hour and no precipitation area, which is about 65-70% for precipitation rate between 10 and 24.9mm per hour. When the precipitation rate reached 25mm per hour, the estimated accuracy rate is very low, about 30%. The method of microwave material inversion precipitation effect get a better results, the estimated accuracy rate can reach 50% for precipitation rate larger than 20mm per hour and 75% for basic accuracy rate. The combination of two methods can not only achieve the accuracy rate of microwave material for precipitation's estimation but also do real-time corrections on the variation of precipitation intensity by Static satellite data.
(3) The large estimation error of FY-2 infrared satellite estimated rainfall may be caused by the following factors:①The difference of precipitation is obvious in different locations even within the same pixel and the representation of ground rainfall stations record have itself errors;②The estimated results are often small for the blooming and disspating cloud cluster, especially for short-time heavy rainfall which are often larger for the initial period of the cloud cluster;③The temperature at cloud top could not show the water vapor characters of abundant moisture conditions which can caused the stronger precipitation intensity, the estimated results is smaller in this condition; The estimated precipitation intensity is stronger in the poor water vapor condition.
引文
1.张文建、许建民,暴雨系统的卫星遥感理论和方法[M].北京：气象出版社,2004.P177-204
2.陈渭民等.卫星气象学[M].北京：气象出版社,2003.390-411
3. Allision,L J,E B Rodgers, T T Wilheit and R W Fett.1974. Tropical cyclone rainfall as measured by the Nimbus 5 Electrically Scanning Microwave Radiometer. Rull.Amer.Meteor.Soc.,55:: 1074-1089
4. Arkin P A,R Joyce and JE Janowiak.1994. IR techniques:GOES precipitation index. Rem.Sens.Rev. Buettner K.1963. Regenortung vom Wettersatelliten mit Hllfe con Zentimeerwellen. Die Naturwissenschaftler.50:591-592
5. Kummerow C and J A Weinman.1988. Determining microwave brightness temperatures from horizontally finite and vertically structured clouds.J.Geophys.93:3720-3728
6. Mugnai A and E A Smith.1988. Radiative transfer to space through a precipitation cloud at multiple microwave frequencies Part I:Model description.J.Appl.Meteor.,27:1055-1073
7.Simpson J, C Kummerow, W K Tao et. al.1996. On the tropical rainfall measuring misson(TRMM).Meteorogy and Atmospheric Physics,60:19-36
8. Smith E A and G Jtripoli.1993. Foundation for statistical-physical precipitation retrieval from passive microwave satellite measurements; Part I:emission source and generalized weighting function properties of a time-dependent cloud-radiation model. J.Appl,Meteor.,32:17-39
9. Smith E A and A Mugnai.1988. Radiation transfer to space through a Foundation precipitation cloud at multiple microwave frequencies.Part II:Results and analysis.J.Appl.Meteor.,27: 1074-1091
lO.Ulaby F,R Moore and A Fung.1981. Microwave remote sensing active and passive. Vol. Ⅰ:Microwave remote sensing fundamentals and radiometry. Addidon-Wesley
11.Weiman J A and P J Guetter.1977. Determination of rainfall distributions from microwave radiation measured by the Nimbus-6 ESMR.J.Appl.Meteeor.16:437-442
12.方宗义.风云二号经哈子气象卫星的作用和效益[J].气象2000(9),55-56
13.王新、方祥、邱红等,应用AMSU-B微波资料分析0509号Matsa台风水汽场分布特征[J],气象,2009(12),3-36
14.Wu. R., and J. A. Weinman,1984:Microwave radiances from precipitating clouds containing atmspherical ice, combined phase, and liquid hydrometeors, J. Geophys. Res.,89,7170-7178.
2.陈渭民等.卫星气象学[M].北京：气象出版社,2003.390-411
3. Allision,L J,E B Rodgers, T T Wilheit and R W Fett.1974. Tropical cyclone rainfall as measured by the Nimbus 5 Electrically Scanning Microwave Radiometer. Rull.Amer.Meteor.Soc.,55:: 1074-1089
4. Arkin P A,R Joyce and JE Janowiak.1994. IR techniques:GOES precipitation index. Rem.Sens.Rev. Buettner K.1963. Regenortung vom Wettersatelliten mit Hllfe con Zentimeerwellen. Die Naturwissenschaftler.50:591-592
5. Kummerow C and J A Weinman.1988. Determining microwave brightness temperatures from horizontally finite and vertically structured clouds.J.Geophys.93:3720-3728
6. Mugnai A and E A Smith.1988. Radiative transfer to space through a precipitation cloud at multiple microwave frequencies Part I:Model description.J.Appl.Meteor.,27:1055-1073
7.Simpson J, C Kummerow, W K Tao et. al.1996. On the tropical rainfall measuring misson(TRMM).Meteorogy and Atmospheric Physics,60:19-36
8. Smith E A and G Jtripoli.1993. Foundation for statistical-physical precipitation retrieval from passive microwave satellite measurements; Part I:emission source and generalized weighting function properties of a time-dependent cloud-radiation model. J.Appl,Meteor.,32:17-39
9. Smith E A and A Mugnai.1988. Radiation transfer to space through a Foundation precipitation cloud at multiple microwave frequencies.Part II:Results and analysis.J.Appl.Meteor.,27: 1074-1091
lO.Ulaby F,R Moore and A Fung.1981. Microwave remote sensing active and passive. Vol. Ⅰ:Microwave remote sensing fundamentals and radiometry. Addidon-Wesley
11.Weiman J A and P J Guetter.1977. Determination of rainfall distributions from microwave radiation measured by the Nimbus-6 ESMR.J.Appl.Meteeor.16:437-442
12.方宗义.风云二号经哈子气象卫星的作用和效益[J].气象2000(9),55-56
13.王新、方祥、邱红等,应用AMSU-B微波资料分析0509号Matsa台风水汽场分布特征[J],气象,2009(12),3-36
14.Wu. R., and J. A. Weinman,1984:Microwave radiances from precipitating clouds containing atmspherical ice, combined phase, and liquid hydrometeors, J. Geophys. Res.,89,7170-7178.