中国区域对流层关键参量格网产品空间插值模型精化

Spatial interpolation model refinement for tropospheric key parameters grid product in China

获取高时空分辨率的对流层关键参量对气候灾害研究、气象监测、GNSS导航等领域具有重要意义。通过对MERRA-2再分析资料的空间插值模型进行精化研究,可为高时空分辨率的对流层关键参量经验模型构建提供重要思路。通过引入残差函数对顾及垂直递减率的空间插值模型进行精化,构建了RECT_(m)-H模型,以中国区域89个探空站实测大气加权平均温度T_(m)和温度T作为参考值,对模型进行插值精度评估。结果表明,T_(m)和T年均RMS分别为1.71和2.25 K,说明引入残差函数可以有效提升空间插值模型精度,降低模型区域间精度差异。

It is of great significance to obtain the key tropospheric parameters with high spatial and temporal resolution in the fields of climate disaster research,meteorological monitoring and GNSS navigation.The refinement of spatial interpolation model of MREEA-2 reanalysis data can provide an important idea for the construction of empirical model of tropospheric key parameters with high spatial and temporal resolution.The residual function is introduced to refine the spatial interpolation model with the vertical decline rate,and the rectm-h model is constructed.The interpolation accuracy of the model is evaluated by the measured T_(m) and surface temperature of 89 radiosonde stations in China as reference values.The results show that the average annual RMS of T_(m) is 1.71 K,and the average annual RMS of temperature is 2.25 K.The introduction of residual function can effectively improve the accuracy of spatial interpolation model and reduce the accuracy difference between model regions.