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香河站地基微波辐射计监测大气水汽的特征分析

Characterization of Atmospheric Water Vapor Using Ground-Based Microwave Radiometry

  • 摘要: 为了加强地基微波辐射计在气象业务中的应用,本文基于香河观测站RPG-HATPRO地基微波辐射计与CIMEL太阳光度计的同址观测条件,通过对比分析两者获取的水汽总量(Integrated Water Vapor, IWV)数据,评估地基微波辐射计反演的IWV数据质量。结果表明两者之间具有很好的一致性,相关系数接近0.99,IWV测量误差普遍在2 mm以内,验证了微波辐射计数据的可靠性。然后,利用2016~2021年地基微波辐射计的IWV数据分析研究了香河地区水汽的日、月、季节变化特征。分析表明,香河地区IWV日变化呈现“夜间高值-日间低值”特征,其中昼夜差异在夏季最显著(1.85 mm),冬季最为平稳(0.34 mm);IWV逐月和季节变化呈单峰型分布,峰值出现在夏季,低值出现在冬季,夏季值高且分散,冬季值低且集中。此外,通过对持续稳定降水天气案例分析,发现降水发生前12 h IWV持续升高,增长幅度超过29%;降水初期IWV急剧升高,增长幅度超过129%;降水持续时间与IWV增幅呈正相关;这些变化特征展示出IWV在降水预测中的潜在应用价值。

     

    Abstract: To enhance the application of ground-based microwave radiometers (MWRs) in meteorological operations, this paper first leverages observations from the MWR RPG-HATPRO and CIMEL sun photometers at Xianghe starion to compare their integrated water vapor (IWV) data, thereby assessing the quality of the MWR-derived IWV data. The results indicate good consistency between the two datasets, with a correlation coefficient close to 0.99 and IWV measurement errors generally less than 2 mm, verifying the reliability of the MWR data. Subsequently, six years of MWR IWV data were used to investigate the daily, monthly, and seasonal variations of water vapor at Xianghe starion. The analysis indicates that the daily variation of IWV at Xianghe exhibits a “high value at night and low value during the day,” with the largest diurnal difference observed in summer (1.85 mm) and the smallest in winter (0.34 mm). The monthly and seasonal variations of IWV follow a unimodal distribution, showing high and scattered values in summer and low, concentrated values in winter. In addition, case studies of continuous and stable precipitation events revealed that IWV begins rising 12 h before precipitation, with an increase rate of over 29%. During the early stage of precipitation, IWV increased sharply, with a growth rate exceeding 129%. The duration of precipitation is positively correlated with the increase in IWV, highlighting the potential of IWV observations for forecasting short-term precipitation.

     

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