地基微波辐射计大气环境遥感研究
|
摘要
大气环境作为无线电系统信息传输的途径,对信息系统的性能具有重要影响,大气参数剖面的遥感对评估无线电系统性能具有重要应用价值,同时,大气剖面的遥感还可用于气象预报,提高气象预报的准确度。本文系统论述了利用地基微波辐射计探测反演大气参数剖面的原理和反演技术。着重研究了双通道微波辐射计反演大气参数剖面、积分水气和云液态水含量的反演技术及反演算法,并对12通道微波辐射计反演大气参数剖面进行了仿真研究。本文的主要工作有:
(1)在传统线性回归算法的基础上提出了非线性回归算法,通过增加回归方程的非线性项因素来提高反演大气剖面的精度,并利用青岛和北京的历史探空数据得到了两地区的非线性回归算法模型。在青岛进行了微波辐射计反演和无线电探空剖面的对比实验,实验结果表明,反演剖面与探空剖面有较好的一致性,且非线性回归算法反演水汽剖面较线性回归算法具有更好的反演精度。
(2)由于神经网络算法在处理非线性问题方面具有强大的优势,本文给出了一种利用微波辐射测量反演大气参数剖面的BP神经网络算法,利用青岛地区历史探空数据仿真的大气辐射亮温对神经网络进行了训练,并对利用实测亮温反演的大气剖面与探空实测剖面进行了比较分析,分析结果表明利用微波辐射计反演的大气剖面与实测剖面间有很好的一致性,且较非线性回归算法有更好的反演精度。同时利用神经网络算法进行了12通道微波辐射计反演性能的仿真研究,并与双通道微波辐射计反演结果进行了对比分析,分析结果表明利用多通道微波辐射计可进一步提高大气剖面的反演精度。
(3)分析了利用双通道微波辐射计反演大气积分水汽和云中液态水含量的反演方法,并利用青岛历史探空数据得到了青岛地区积分水汽和云液态水反演的线性回归模型,实验表明反演结果与气象探空结果有很好的一致性。
(4)利用青岛站和北京站的历史探空数据仿真研究了线性回归算法,非线性回归算法和神经网络算法在不同月份的反演性能,研究表明,不同算法的反演精度随着气象条件的变化具有明显差异,针对不同季节,选用适当的反演算法,可有效提高微波辐射计的反演精度。
本文的研究结果可用于微波辐射计的大气环境遥感,对提高微波辐射计的大气环境遥感精度具有重要的参考价值。
Atmospheric environment, as the information transmitting path for radio system, has great effects on the performance of information systems, therefore remote sensing profiles of atmospheric parameters is very important for evaluating the performance of radio system. Moreover, atmospheric profiles can be applied to weather forecast, and improve its accuracy. The basic principle and retrieving techniques of remote sensing atmospheric profiles by ground-based microwave radiometer are reviewed in this thesis. Research focuses on the retrieving techniques and algorithms of dual-channel radiometer retrieving profiles of atmospheric parameters, integrated precipitable water vapor and integrated liquid water. The main works are:
(1) A non-linear regression algorithm based on conventional linear regression algorithm is presented, which improves the accuracy of retrieving profiles by adding non-linear terms. The non-linear regression models are developed based upon the radiosonde data of Qingdao and Beijing. The results of the experiment in Qingdao show that retrieving profiles are identical with radiosonde profiles, and non-linear regression algorithm has better accuracy in retrieving water vapor profile.
(2) Artificial neural network algorithm can easily adapt to non-linear problems, therefore a BP network used in radiometer to retrieve atmospheric profiles is introduced, and trained with the historical radiosonde data and its simulating brightness temperatures of Qingdao. The results show that retrieving profiles gained by BP network algorithm have good agreement with radiosonde data, which are also more accuracy than that gained by non-linear algorithm. Meanwhile, 12-channel radiometer retrieval simulation is made with neural network, and the comparison with the retrieving ones by dual-channel radiometer demonstrates that using multi-channel radiometer can improve the accuracy of profiling.
(3) Methods to retrieve the integrated precipitable water vapor(V) and integrated liquid water(L) based on dual-channel radiometer are analyzed, and the linear regression models are developed with the simulation results by historical radiosonde data of Qingdao. Experiment demonstrates that these models can be used with good accuracies.
(4) The inversion performances of linear regression algorithm, non-linear regression algorithm and neural network algorithm in different months in an average annual year are simulated by utilizing the historical radiosonde data of Qingdao and Beijing, and the simulation results show that the performances of different inversion methods present discrepancies apparently with the variety of weather condition. Therefore the proper selection of the inversion methods in different seasons may improve the retrieval accuracy.
The models proposed in this thesis can be applied to remote sensing atmospheric environment by radiometer, which have important reference value for improving the accuracy of remote sensing atmospheric by radiometer.
(1)在传统线性回归算法的基础上提出了非线性回归算法,通过增加回归方程的非线性项因素来提高反演大气剖面的精度,并利用青岛和北京的历史探空数据得到了两地区的非线性回归算法模型。在青岛进行了微波辐射计反演和无线电探空剖面的对比实验,实验结果表明,反演剖面与探空剖面有较好的一致性,且非线性回归算法反演水汽剖面较线性回归算法具有更好的反演精度。
(2)由于神经网络算法在处理非线性问题方面具有强大的优势,本文给出了一种利用微波辐射测量反演大气参数剖面的BP神经网络算法,利用青岛地区历史探空数据仿真的大气辐射亮温对神经网络进行了训练,并对利用实测亮温反演的大气剖面与探空实测剖面进行了比较分析,分析结果表明利用微波辐射计反演的大气剖面与实测剖面间有很好的一致性,且较非线性回归算法有更好的反演精度。同时利用神经网络算法进行了12通道微波辐射计反演性能的仿真研究,并与双通道微波辐射计反演结果进行了对比分析,分析结果表明利用多通道微波辐射计可进一步提高大气剖面的反演精度。
(3)分析了利用双通道微波辐射计反演大气积分水汽和云中液态水含量的反演方法,并利用青岛历史探空数据得到了青岛地区积分水汽和云液态水反演的线性回归模型,实验表明反演结果与气象探空结果有很好的一致性。
(4)利用青岛站和北京站的历史探空数据仿真研究了线性回归算法,非线性回归算法和神经网络算法在不同月份的反演性能,研究表明,不同算法的反演精度随着气象条件的变化具有明显差异,针对不同季节,选用适当的反演算法,可有效提高微波辐射计的反演精度。
本文的研究结果可用于微波辐射计的大气环境遥感,对提高微波辐射计的大气环境遥感精度具有重要的参考价值。
Atmospheric environment, as the information transmitting path for radio system, has great effects on the performance of information systems, therefore remote sensing profiles of atmospheric parameters is very important for evaluating the performance of radio system. Moreover, atmospheric profiles can be applied to weather forecast, and improve its accuracy. The basic principle and retrieving techniques of remote sensing atmospheric profiles by ground-based microwave radiometer are reviewed in this thesis. Research focuses on the retrieving techniques and algorithms of dual-channel radiometer retrieving profiles of atmospheric parameters, integrated precipitable water vapor and integrated liquid water. The main works are:
(1) A non-linear regression algorithm based on conventional linear regression algorithm is presented, which improves the accuracy of retrieving profiles by adding non-linear terms. The non-linear regression models are developed based upon the radiosonde data of Qingdao and Beijing. The results of the experiment in Qingdao show that retrieving profiles are identical with radiosonde profiles, and non-linear regression algorithm has better accuracy in retrieving water vapor profile.
(2) Artificial neural network algorithm can easily adapt to non-linear problems, therefore a BP network used in radiometer to retrieve atmospheric profiles is introduced, and trained with the historical radiosonde data and its simulating brightness temperatures of Qingdao. The results show that retrieving profiles gained by BP network algorithm have good agreement with radiosonde data, which are also more accuracy than that gained by non-linear algorithm. Meanwhile, 12-channel radiometer retrieval simulation is made with neural network, and the comparison with the retrieving ones by dual-channel radiometer demonstrates that using multi-channel radiometer can improve the accuracy of profiling.
(3) Methods to retrieve the integrated precipitable water vapor(V) and integrated liquid water(L) based on dual-channel radiometer are analyzed, and the linear regression models are developed with the simulation results by historical radiosonde data of Qingdao. Experiment demonstrates that these models can be used with good accuracies.
(4) The inversion performances of linear regression algorithm, non-linear regression algorithm and neural network algorithm in different months in an average annual year are simulated by utilizing the historical radiosonde data of Qingdao and Beijing, and the simulation results show that the performances of different inversion methods present discrepancies apparently with the variety of weather condition. Therefore the proper selection of the inversion methods in different seasons may improve the retrieval accuracy.
The models proposed in this thesis can be applied to remote sensing atmospheric environment by radiometer, which have important reference value for improving the accuracy of remote sensing atmospheric by radiometer.
引文
[1]. E.N. Kadygrov. Integrated Profiling Systems and Other Upper-air Measurement Techniques, CIMO/OPAG-UPPER-AIR/ET-RSUAT&T-1/Doc, 2005, 6.2(1), p. 2
[2]. Thomas Kuhn. Atmospheric Absorption Models for the Millimeter Wave Range[Paper]. Universit¨at Bremen Bremen,2003
[3]. E.N. Kadygrov. Integrated Profiling Systems And Other Upper-Air Measurement Techniques[Report].CIMO/OPAG-UPPER-AIR/ET-RSUAT&T-1/Doc, 2005, 6.2(1), p. 2.
[4]. QIU Jinhuan,and CHEN Hongbin. Recent Progresses inAtmospheric Remote Sensing Research in China[R], Advances In Atmospheric Sciences, 2004, Vol. 21, No. 3, 475–484
[5]. www.radiometer-physics.com
[6]. Westwater, E. R., and M. T. Decker. Application of Statistical Inversion to Ground-Based Microwave Remote Sensing of Temperature and Water Vapor Profiles[M]. in Inversion Methods in Atmospheric Remote Sounding (A. Decker, ed.), Academic Press, New York, 1977,pp:395-428.
[7]. Press F. Earth models obtained by Monte-Carlo inversion[J]. J. Geophys. Res., 1968,73(16), pp:5223-5234.
[8]. Press F. An introduction to Earth structure and seismotectonics[M]. Procedings of the International Sxhool of Physics Enrico Fermi, Course L, Mantle and Core in Planetary Physics, Coulomb, J. and Caputo M.(editors), Academic Press,1971.
[9]. Smith W. L. Iterative solution of the radiative transfer equation for the temperature and absorbing gas profile of an atmosphere[J]. Applied Optics, 1970,9,pp:1993-1999.
[10]. Conrath B. J. Vertical resolution temperature files obtained from remote radiation measurement[J]. Journal of the Atmospheric Science, 1972,29,pp:1262-1271.
[11]. Rodgers,C.D. Retrieval of Atmospheric Temperature and Composition from Remote Measurement of Thermal Radiation[J]. Rev. Geophys and Space Phys.,1976,14,pp:609-624.
[12]. Ledsham, W. H., and D. H. Staelin. An Extended Kalman-Bucy Filter for Atmospheric Temperature Profile Retrieval with a Passive Microwave Sounder[J]. J. Appl. Meteorol., 1978,17,pp:1023-1033.
[13]. Patrizia Basili, Piero Ciotti, and Domenico Solimini. Inversion of ground-based radiometric data by Kalman filtering[J], Radio Science,1980, Vol 16, No 1, pp.83-91.
[14]. Basili, P., P. Ciotti, and D. Solimini. Inversion of Ground-based Radiometric Data By Kalman Filtering[J]. Radio Sci, 1981,16,pp:83-91.
[15]. Miguel Vélez-Reyes. Atmospheric Retrievals using Regularization Methods[J]. IEEE, 1998, pp:1403-1407.
[16]. Fredrick Solheim, John R.Godwin…Radiometric Profiling of Temperature, Water Vapor and Cloud Liquid Water using Various Inversion Methods[J]. Radio Science, 1998, Vol.33 No.2 Mar-Apr
[17].林黎虹,张健,石耀霖.利用遗传算法反演大气的垂直温度结构[J],中国科学院研究生院学报,1997,14(1).pp.43-50.
[18]. Churnside, J.H., T.A. Stermitz, and J.A. Schroeder. Temperature Profiling with Neural Network Inversion of Microwave Radiometer Date[J]. J. Atmos Oceanic Technol, 1994,11,105-109
[19]. F. Del Firate and G. Schiavon. A Neural Network Algorithm for the Retrieval of Atmospheric Profiles from Radiometric Data. IEEE,1997,pp.2097-2098.
[20]. Vanessa C. de Viterbo, Jo?ao P. Braga1, E′lcio H. Shiguemori…, Atmospheric Temperature Retrieval using Non-linear Hopfield Neural Network. Brazil, 2004.
[21].élcio H. Shiguemori, Haroldo F. de Campos Velho…Neural Network based Models in the Inversion of Temperature Vertical Profiles from Radiation Data. Brazil, 2004
[22]. YAO Zhigang, CHEN Hongbin, and LIN Longfu. Retrieving Atmospheric Temperature Profiles from AMSU-A Data with Neural Networks. Advances In Atmospheric Sciences, 2005, Vol. 22, No. 4, pp.606–616.
[23]. Rosangela Saher Cintra,JoséDemisio Sim?es Silva. Artificial Neural Network To Estimate Integrated Water Vapor Using Satellite Data From Hsb Sensor. Brazil, 2006, April 24-28, p. 11-15.
[24]. Th. Rose, H. Czekala. Accurate Atmospheric Profiling with the RPG-HATPRO Humidity– and Temperature Profiler. Operating Manual .RPG, Meckenheim / Germany, 2005,10.7.
[25]. Th. Rose, H. Czekala. RPG-HATPRO, RPG-TEMPRO, RPG-HUMPRO Humidity and Temperature Profilers.Operating Manual., 2006, July.
[26]. Randolph Ware, Fredrick Solheim, Richard Carpenter. Radiometric profiling of tropospheric temperature, humidity and cloud liquid[J]. Radio Science, 2001, Nov.
[27]. ITU. HandBook on RadioMeteorology. 1996.
[28]. Fawwaz T. Ulaby, Richard K. Moore, Adrian k.Fung. Microwave Remote Sensing, 1986, Vol 3.
[29].张培昌,王振会.大气微波遥感基础[M].北京:气象出版社,1995,pp346-384
[30]. Fawwaz T. Ulaby, Richard K. Moore, drian k. Fung. Microwave Remote Sensing, 1981, Vol 1.
[31]. ITU-R P.676-6. Attenuation by atmospheric gases[R].2005.
[32]. Erwan Motte. Retrieval Characterization of a Double Sidebdand Radiometer for Simultaneous Observation of Ozone and Carbon Monoxide[Paper].Department of Radio and Space Science, Chalmers University of Technology. G?teborg, Sweden 2004
[33]. Thomas Rose, Harald Czekala. Filterbank Radiometers for Atmospheric Profiling[Report]. AOGS 1-st Annual Meeting– Singapore, 2004,6. 7
[34]. Meeks M. L., V. E. Lilley. The Microwave Spectrum of Oxygen in the Earth’s Atmosphere[J]. Journal of Geophysical Research, 1963, 68, 1683-1703.
[35]. Barrett A. H., V. K. Chung. A Method for the Determination of High Altitude Water Vapor Abundance from Ground-based Microwave Observation[J]. Journal of Geophysical Research, 1962, 67, 4259-4266.
[36].赵柏林,张霭琛.大气探测原理。北京:气象出版社,1987
[37]. Guiraud, F.O., J. Howard, and D.C. Hogg. A Dual-Channel Microwave Radiometer for Measurement of Precipitable Water Vapor and Liquid[J]. IEEE Trans. Geosci. Electron, 1979, GE-17:129-136.
[38]. Fabio Del Frate and Giovanni Schiavon. A combined natural orthogonal functions/neural network technique for the radiometric estimation of atmospheric profiles[J]. Radio Science, 1998, 33(2): 405-410.
[39].黄彦彬,德力格尔,王振会.利用地基双通道微波辐射计遥感青藏高原大气云水特征[J].南京气象学院学报, 2001, 24(3):391～397.
[40].周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京:清华大学出版社, 2005
[41]. Rumelhart, D. E., G. E. Hinton, and R. J. Williams. Learning internal representation by error propagation. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Foundation, 1986, Vol. 1, Cambridge, MIT Press, 318–362.
[42].阎平凡,张长水.人工神经网络与模拟进化计算[M].北京:清华大学出版社,2002.
[43]. Randolph Ware, Richard Carpenter,...A multi-channel radiometric profiler of temperature, humidity, and cloud liquid[J].Radio Science,2003, Vol. 38, No. 4
[44]. ED R. WESTWATER.Ground-Based Determination of low Altitude Temperature Profiles by Microwaves[J].UDC, 1972,Vol. 100, No. 1, January.
[45]. G. E. PECKHAM and M. GRIPPA.Improved retrieval of tropospheric temperatures from remote measurements of thermal radiation using the adiabatic lapse rate as a constraint[J]. Q. J. R. Meteorol. Soc. 2000, 126, pp. 749-760
[46]. G. E. PECKHAM and M. GRIPPA.Improved retrieval of tropospheric temperatures from remote measurements of thermal radiation using the adiabatic lapse rate as a constraint[J]. Q. J. R. Meteorol. Soc. 2000, 126, pp. 749-760
[47]. GJB/Z 87-97,雷达电波传播折射与衰减手册[S],北京.国防科工委军标出版发行部出版,1997.10
[48].熊皓,等编.无线电波传播[M].北京:电子工业出社,2000.
[49]. Hogg D C, Decker M T, Guiraud F O, etal. An automatic profiler of the temperature, wind and humidity in the troposphere[J].J Appl Meteorol,1983,22(5):807~831.
[50].赵从龙,蔡化庆,宋玉东.对流层水汽和液态水的地基微波遥感探测[J].应用气象学报,1991,2(2):200~207
[51].朱元竞,胡成达.微波辐射计在人工影响天气中的应用[C].中国气象局“八五”期间大气科学基金研究论文汇编.北京:气象出版社,1997.249~255.
[52].段英,吴志会.利用地基遥感方法检测大气中汽态、液态水含量分布特征[J].应用气象学报,1999,10(1):34~40
[53]. Hogg D C, Decker M T, Guiraud F O, etal. An automatic profiler of the temperature, wind and humidity in the troposphere[J].J Appl Meteorol,1983,22(5):807~831.
[54]. James C. Liljegren, Eugene E. Clothiaux... A new retrieval for cloud liquid water path using a ground-based microwave radiometer and measurements of cloud temperature[J]. Journal of Geophysical Research,2001, Vol,106,NO.D13,pp14485-14500,July 16.
[55]. Ed R. Westwater and Yong Han. Analysis of integrated cloud liquid and precipitable water vapor retrievals from microwave radiometers during the Surface Heat Budget of the Arctic Ocean project[J]. Journal Of Geophysical Research,2001, Vol. 106, No. D23, pp:32019–32030, December 16.
[56]. Ulrich Lo¨Hnert, Susanne Crewell, and Clemens Simmer. An Integrated Approach toward Retrieving Physically Consistent Profiles of Temperature, Humidity, and Cloud Liquid Water[J]. Journal of Applied Meteorology,2004, Vol,43,pp:1295-1307,September.
[57]. Cory Davis, Claudia Emde, and Robert Harwood. A 3-D Polarized Reversed Monte Carlo Radiative Transfer Model for Millimeter and Sub-millimeter Passive Remote Sensing in Cloudy Atmospheres[J].IEEE Transactions On Geo-science And Remote Sensing, May 2005, Vol. 43, No. 5,pp:1096-1101.
[58]. T.R. Sreerekha, S. Buehler, C. Emde. A simple new radiative transfer model for simulating the effect of cirrus clouds in the microwave spectral region[J]. Journal of Quantitative Spectroscopy & Radiative Transfer,2002, 75:611–624.
[59]. Wu, S-C. Optimum Frequencies of a Passive Mircrowave Radiometer for Tropospheric Path-Length Correction[J]. IEEE Trans Antennas Propag,1979,Ap-27,pp:233-239
[60]. R. Ware, D. Cimini, P. Herzegh,.. Ground-Based Radiometric Profiling during Dynamic Weather Conditions[J], Journal of Applied Meteorology, 2004.
[61]. Susanne Crewell,Harald Czekala,…,Microwave Radiometer for Cloud Carthography: A 22-channel ground-based microwave radiometer for atmosphere research. Radio Science, 2001, Vol36, PP:621-638
[2]. Thomas Kuhn. Atmospheric Absorption Models for the Millimeter Wave Range[Paper]. Universit¨at Bremen Bremen,2003
[3]. E.N. Kadygrov. Integrated Profiling Systems And Other Upper-Air Measurement Techniques[Report].CIMO/OPAG-UPPER-AIR/ET-RSUAT&T-1/Doc, 2005, 6.2(1), p. 2.
[4]. QIU Jinhuan,and CHEN Hongbin. Recent Progresses inAtmospheric Remote Sensing Research in China[R], Advances In Atmospheric Sciences, 2004, Vol. 21, No. 3, 475–484
[5]. www.radiometer-physics.com
[6]. Westwater, E. R., and M. T. Decker. Application of Statistical Inversion to Ground-Based Microwave Remote Sensing of Temperature and Water Vapor Profiles[M]. in Inversion Methods in Atmospheric Remote Sounding (A. Decker, ed.), Academic Press, New York, 1977,pp:395-428.
[7]. Press F. Earth models obtained by Monte-Carlo inversion[J]. J. Geophys. Res., 1968,73(16), pp:5223-5234.
[8]. Press F. An introduction to Earth structure and seismotectonics[M]. Procedings of the International Sxhool of Physics Enrico Fermi, Course L, Mantle and Core in Planetary Physics, Coulomb, J. and Caputo M.(editors), Academic Press,1971.
[9]. Smith W. L. Iterative solution of the radiative transfer equation for the temperature and absorbing gas profile of an atmosphere[J]. Applied Optics, 1970,9,pp:1993-1999.
[10]. Conrath B. J. Vertical resolution temperature files obtained from remote radiation measurement[J]. Journal of the Atmospheric Science, 1972,29,pp:1262-1271.
[11]. Rodgers,C.D. Retrieval of Atmospheric Temperature and Composition from Remote Measurement of Thermal Radiation[J]. Rev. Geophys and Space Phys.,1976,14,pp:609-624.
[12]. Ledsham, W. H., and D. H. Staelin. An Extended Kalman-Bucy Filter for Atmospheric Temperature Profile Retrieval with a Passive Microwave Sounder[J]. J. Appl. Meteorol., 1978,17,pp:1023-1033.
[13]. Patrizia Basili, Piero Ciotti, and Domenico Solimini. Inversion of ground-based radiometric data by Kalman filtering[J], Radio Science,1980, Vol 16, No 1, pp.83-91.
[14]. Basili, P., P. Ciotti, and D. Solimini. Inversion of Ground-based Radiometric Data By Kalman Filtering[J]. Radio Sci, 1981,16,pp:83-91.
[15]. Miguel Vélez-Reyes. Atmospheric Retrievals using Regularization Methods[J]. IEEE, 1998, pp:1403-1407.
[16]. Fredrick Solheim, John R.Godwin…Radiometric Profiling of Temperature, Water Vapor and Cloud Liquid Water using Various Inversion Methods[J]. Radio Science, 1998, Vol.33 No.2 Mar-Apr
[17].林黎虹,张健,石耀霖.利用遗传算法反演大气的垂直温度结构[J],中国科学院研究生院学报,1997,14(1).pp.43-50.
[18]. Churnside, J.H., T.A. Stermitz, and J.A. Schroeder. Temperature Profiling with Neural Network Inversion of Microwave Radiometer Date[J]. J. Atmos Oceanic Technol, 1994,11,105-109
[19]. F. Del Firate and G. Schiavon. A Neural Network Algorithm for the Retrieval of Atmospheric Profiles from Radiometric Data. IEEE,1997,pp.2097-2098.
[20]. Vanessa C. de Viterbo, Jo?ao P. Braga1, E′lcio H. Shiguemori…, Atmospheric Temperature Retrieval using Non-linear Hopfield Neural Network. Brazil, 2004.
[21].élcio H. Shiguemori, Haroldo F. de Campos Velho…Neural Network based Models in the Inversion of Temperature Vertical Profiles from Radiation Data. Brazil, 2004
[22]. YAO Zhigang, CHEN Hongbin, and LIN Longfu. Retrieving Atmospheric Temperature Profiles from AMSU-A Data with Neural Networks. Advances In Atmospheric Sciences, 2005, Vol. 22, No. 4, pp.606–616.
[23]. Rosangela Saher Cintra,JoséDemisio Sim?es Silva. Artificial Neural Network To Estimate Integrated Water Vapor Using Satellite Data From Hsb Sensor. Brazil, 2006, April 24-28, p. 11-15.
[24]. Th. Rose, H. Czekala. Accurate Atmospheric Profiling with the RPG-HATPRO Humidity– and Temperature Profiler. Operating Manual .RPG, Meckenheim / Germany, 2005,10.7.
[25]. Th. Rose, H. Czekala. RPG-HATPRO, RPG-TEMPRO, RPG-HUMPRO Humidity and Temperature Profilers.Operating Manual., 2006, July.
[26]. Randolph Ware, Fredrick Solheim, Richard Carpenter. Radiometric profiling of tropospheric temperature, humidity and cloud liquid[J]. Radio Science, 2001, Nov.
[27]. ITU. HandBook on RadioMeteorology. 1996.
[28]. Fawwaz T. Ulaby, Richard K. Moore, Adrian k.Fung. Microwave Remote Sensing, 1986, Vol 3.
[29].张培昌,王振会.大气微波遥感基础[M].北京:气象出版社,1995,pp346-384
[30]. Fawwaz T. Ulaby, Richard K. Moore, drian k. Fung. Microwave Remote Sensing, 1981, Vol 1.
[31]. ITU-R P.676-6. Attenuation by atmospheric gases[R].2005.
[32]. Erwan Motte. Retrieval Characterization of a Double Sidebdand Radiometer for Simultaneous Observation of Ozone and Carbon Monoxide[Paper].Department of Radio and Space Science, Chalmers University of Technology. G?teborg, Sweden 2004
[33]. Thomas Rose, Harald Czekala. Filterbank Radiometers for Atmospheric Profiling[Report]. AOGS 1-st Annual Meeting– Singapore, 2004,6. 7
[34]. Meeks M. L., V. E. Lilley. The Microwave Spectrum of Oxygen in the Earth’s Atmosphere[J]. Journal of Geophysical Research, 1963, 68, 1683-1703.
[35]. Barrett A. H., V. K. Chung. A Method for the Determination of High Altitude Water Vapor Abundance from Ground-based Microwave Observation[J]. Journal of Geophysical Research, 1962, 67, 4259-4266.
[36].赵柏林,张霭琛.大气探测原理。北京:气象出版社,1987
[37]. Guiraud, F.O., J. Howard, and D.C. Hogg. A Dual-Channel Microwave Radiometer for Measurement of Precipitable Water Vapor and Liquid[J]. IEEE Trans. Geosci. Electron, 1979, GE-17:129-136.
[38]. Fabio Del Frate and Giovanni Schiavon. A combined natural orthogonal functions/neural network technique for the radiometric estimation of atmospheric profiles[J]. Radio Science, 1998, 33(2): 405-410.
[39].黄彦彬,德力格尔,王振会.利用地基双通道微波辐射计遥感青藏高原大气云水特征[J].南京气象学院学报, 2001, 24(3):391～397.
[40].周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京:清华大学出版社, 2005
[41]. Rumelhart, D. E., G. E. Hinton, and R. J. Williams. Learning internal representation by error propagation. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Foundation, 1986, Vol. 1, Cambridge, MIT Press, 318–362.
[42].阎平凡,张长水.人工神经网络与模拟进化计算[M].北京:清华大学出版社,2002.
[43]. Randolph Ware, Richard Carpenter,...A multi-channel radiometric profiler of temperature, humidity, and cloud liquid[J].Radio Science,2003, Vol. 38, No. 4
[44]. ED R. WESTWATER.Ground-Based Determination of low Altitude Temperature Profiles by Microwaves[J].UDC, 1972,Vol. 100, No. 1, January.
[45]. G. E. PECKHAM and M. GRIPPA.Improved retrieval of tropospheric temperatures from remote measurements of thermal radiation using the adiabatic lapse rate as a constraint[J]. Q. J. R. Meteorol. Soc. 2000, 126, pp. 749-760
[46]. G. E. PECKHAM and M. GRIPPA.Improved retrieval of tropospheric temperatures from remote measurements of thermal radiation using the adiabatic lapse rate as a constraint[J]. Q. J. R. Meteorol. Soc. 2000, 126, pp. 749-760
[47]. GJB/Z 87-97,雷达电波传播折射与衰减手册[S],北京.国防科工委军标出版发行部出版,1997.10
[48].熊皓,等编.无线电波传播[M].北京:电子工业出社,2000.
[49]. Hogg D C, Decker M T, Guiraud F O, etal. An automatic profiler of the temperature, wind and humidity in the troposphere[J].J Appl Meteorol,1983,22(5):807~831.
[50].赵从龙,蔡化庆,宋玉东.对流层水汽和液态水的地基微波遥感探测[J].应用气象学报,1991,2(2):200~207
[51].朱元竞,胡成达.微波辐射计在人工影响天气中的应用[C].中国气象局“八五”期间大气科学基金研究论文汇编.北京:气象出版社,1997.249~255.
[52].段英,吴志会.利用地基遥感方法检测大气中汽态、液态水含量分布特征[J].应用气象学报,1999,10(1):34~40
[53]. Hogg D C, Decker M T, Guiraud F O, etal. An automatic profiler of the temperature, wind and humidity in the troposphere[J].J Appl Meteorol,1983,22(5):807~831.
[54]. James C. Liljegren, Eugene E. Clothiaux... A new retrieval for cloud liquid water path using a ground-based microwave radiometer and measurements of cloud temperature[J]. Journal of Geophysical Research,2001, Vol,106,NO.D13,pp14485-14500,July 16.
[55]. Ed R. Westwater and Yong Han. Analysis of integrated cloud liquid and precipitable water vapor retrievals from microwave radiometers during the Surface Heat Budget of the Arctic Ocean project[J]. Journal Of Geophysical Research,2001, Vol. 106, No. D23, pp:32019–32030, December 16.
[56]. Ulrich Lo¨Hnert, Susanne Crewell, and Clemens Simmer. An Integrated Approach toward Retrieving Physically Consistent Profiles of Temperature, Humidity, and Cloud Liquid Water[J]. Journal of Applied Meteorology,2004, Vol,43,pp:1295-1307,September.
[57]. Cory Davis, Claudia Emde, and Robert Harwood. A 3-D Polarized Reversed Monte Carlo Radiative Transfer Model for Millimeter and Sub-millimeter Passive Remote Sensing in Cloudy Atmospheres[J].IEEE Transactions On Geo-science And Remote Sensing, May 2005, Vol. 43, No. 5,pp:1096-1101.
[58]. T.R. Sreerekha, S. Buehler, C. Emde. A simple new radiative transfer model for simulating the effect of cirrus clouds in the microwave spectral region[J]. Journal of Quantitative Spectroscopy & Radiative Transfer,2002, 75:611–624.
[59]. Wu, S-C. Optimum Frequencies of a Passive Mircrowave Radiometer for Tropospheric Path-Length Correction[J]. IEEE Trans Antennas Propag,1979,Ap-27,pp:233-239
[60]. R. Ware, D. Cimini, P. Herzegh,.. Ground-Based Radiometric Profiling during Dynamic Weather Conditions[J], Journal of Applied Meteorology, 2004.
[61]. Susanne Crewell,Harald Czekala,…,Microwave Radiometer for Cloud Carthography: A 22-channel ground-based microwave radiometer for atmosphere research. Radio Science, 2001, Vol36, PP:621-638