收稿日期: 2014-02-25
修回日期: 2014-03-14
网络出版日期: 2015-01-15
基金资助
国家自然科学基金(41231170)和中国科学院西部行动计划项目(KZCX2-XB3-15)资助
Estimation model of the atmospheric parameters in the research of quantitative microwave remote sensing
Received date: 2014-02-25
Revised date: 2014-03-14
Online published: 2015-01-15
被动微波遥感对地表参数的反演研究中通常会忽略大气的影响.在定量遥感精度要求较高的情况下,建立大气参数的定量估算模型以剔除大气影响,对于提高反演精度具有积极作用.本文基于辐射传输模型,总结出大气向上和向下亮温及大气透过率这3个大气参数均与大气可降水量密切相关.利用MonoRTM模型和全球946条大气廓线建立晴空条件下大气亮温和大气透过率与大气可降水量之间的函数关系,发现大气亮温与大气可降水量呈正相关,大气透过率与大气可降水量呈负相关.本文利用中国张掖地区探空数据集对大气参数估算模型进行验证.模拟结果与通过MonoRTM模拟的结果基本一致,表明本模型具有较高的可靠性.通过本模型可定量计算大气对被动微波遥感的影响,提高微波遥感定量反演的精度.
周芳成 , 宋小宁 , 李召良 , 马建威 . 微波遥感定量反演研究中大气参数的估算模型[J]. 中国科学院大学学报, 2015 , 32(1) : 63 -69 . DOI: 10.7523/j.issn.2095-6134.2015.01.011
Usually, atmospheric effects on microwave remote sensing are ignored because of the penetration of microwave. However, for quantitative inversion in which high precision inversion is required, atmospheric effects should be taken into account. Based on the radiative transfer model, three atmospheric parameters, upwelling and downwelling atmospheric brightness temperature and atmospheric transmissivity, were proved to be much influenced by precipitable water vapor. The MonoRTM and 946 global atmospheric profiles were used to simulate these atmospheric parameters. Then we got regression models for PWV(precipitable water vapor) and atmospheric brightness temperatures and for PWV and atmospheric transmissivity, respectively. Finally, Zhangye radiosonde data sets were used to validate the models, and verification results showed that the estimation models had high credibility.
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