基于GNSS的MODIS大气可降水量校正模型

MODIS大气可降水量（PWV）空间分辨率高但易受云雨等环境因素影响，精度不高.GNSS PWV 空间分辨率较低但具有全天候、不受天气影响、精度高的优点.研究表明两者存在显著的线性相关性，结合两者的优点，基于GNSS PWV校正MODIS PWV可获取大面积高精度的PWV.针对传统的线性回归校正模型没有考虑云、气溶胶等的影响使两种数据线性相关性变差的问题，本文在传统的线性校正模型上增加了使用年积日的非线性周期项的方法来构建校正模型.利用2017—2019年香港地区GNSS对流层延迟与MODIS近红外数据，使用频谱分析线性残差项，结果表明残差具有显著的年周期.对比传统模型，本文模型的平均绝对误差、平均相对误差、均方根误差和拟合度都有明显的改善，表明本文模型可行有效且精度较高.

A correction model for MODIS precipitable water vapor based on GNSS data

MODIS Precipitable Water Vapor (PWV) has high spatial resolution but is easily affected by environmental factors such as clouds and rain,and its accuracy is not high.GNSS PWV has low spatial resolution but has advantages of all-weather,weather-free,and high accuracy.Previous researches have shown a significant linear correlation between the two.Combining the advantages of both,correcting MODIS PWV based on GNSS PWV data can obtain PWV for large area with high precision.Yet traditional linear regression correction model does not take into account the deterioration of the linear correlation due to influences from environmental factors such as clouds and aerosols.To address this,a non-linear term of Day of Year is added to traditional linear model thus construct a new correction model.The GNSS tropospheric delay and MODIS near-infrared data in Hong Kong during 2017-2019 are used to verify the proposed correction model,and the result of linear residual spectrum shows a significant annual cycle.Compared with traditional correction model,the new model is significantly improved in aspects of average absolute error,average relative error,root mean square error,and fitting,which verifies the new model in feasibility and accuracy for MODIS PWV correction.