顾及时变递减因子的中国大陆地区大气可降水量垂直改正模型

Abstract

大气可降水量（PWV）在研究全球气候变化和数值天气预报中扮演着关键角色。然而，目前PWV的垂直改正主要依靠简单的经验改正模型，在一定程度上限制了多源水汽产品的高精度融合及不同水汽产品相互比较的可靠性。本文针对中国地区地形起伏大、气候多变等特点，利用2012—2017年欧洲中期天气预报中心提供的ERA5再分析资料，按全国、地理分区方法分别构建了顾及时变递减因子的中国大陆地区PWV垂直改正模型（简称为C-PWVC1模型和C-PWVC2模型）。以2017年中国地区86个探空站数据为参考值，分别将ERA5和MERRA-2再分析资料格网数据插值到探空站来对新建立的模型进行精度评估。结果表明：①C-PWVC1和C-PWVC2模型在PWV垂直改正中的性能相当；②C-PWVC模型相比于未顾及垂直改正的情况，对ERA5和MERRA-2的修正精度（RMS值）整体分别提高了16%和8%，与常用的PWV垂直改正模型相比，对ERA5改善不够显著，而对MERRA-2则提高了12%；③C-PWVC模型在两种PWV高差较大时，表现出显著的优势，对MERRA-2的改正效果比ERA5更明显；④C-PWVC模型在不同空间分辨率的ERA5上，相比于常用的PWV垂直改正模型具有更好的插值精度和稳定性，尤其在中国南部和西部地区表现出显著的优势。因此，C-PWVC模型在中国大陆地区有较好的PWV垂直改正性能，可为中国区域的多源水汽产品比较、融合提供重要应用。

Alternate abstract:

Atmospheric precipitable water vapor (PWV) plays a key role in the study of global climate change and numerical weather prediction. However, the vertical correction of PWV mainly relies on a simple empirical correction model at present, which limite the high precision fusion of multi-source water vapor products and the comparisons between different water vapor products in a way. In this paper, for the characteristics of highly undulating terrain and diverse climate in China, the PWV vertical correction models which considering the time-varying lapse rate according to the whole areas in Mainland China and geographical divisions, named as C-PWVC1 model and C-PWVC2 model respectively, are established using ERA5 reanalysis data provided by the European Center for Medium Range Weather Forecast (ECMWF) from 2012 to 2017. Taking the profiles of 86 radiosonde stations in China in 2017 as reference values, the ERA5 and MERRA-2 reanalysis gridded data are interpolated into radiosonde stations to evaluate the performance of the newly established models, respectively. The results show that the performance of C-PWVC1 and C-PWVC2 models in PWV vertical correction is comparable. Compared with the condition without vertical correction, the performances of the C-PWVC model for ERA5 and MERRA-2 are improved by 16% and 8%, respectively. Compared with the commonly used PWV vertical correction model, C-PWVC model has little improvement for ERA5, but 12% for MERRA-2. C-PWVC model shows significant advantages when the height difference between two kinds of PWVs is large, and the correction capability for MERRA-2 is greater than ERA5. Moreover, for the ERA5 with different spatial resolutions, C-PWVC model has better interpolation precision and stability when compared with the commonly used PWV vertical correction model, especially in southern and western China. Therefore, the C-PWVC model has a good performance in PWV vertical correction for Mainland China, which can provide important application for the comparison and fusion of multi-source water vapor products in China.