【摘要】 针对目前多数大气加权平均温度(Tm)模型没有考虑季节性影响这一问题,该文首先利用IGRA 2005—2010年全球探空数据,分别建立了各探空站点与地表温度有关的线性Tm模型、与地表水汽压有关的指数Tm模型以及与地表温度和水汽压均有关的混合Tm模型。然后以探空站积分Tm值为参考,对上述3类模型的误差时间序列进行了分析,发现这3种模型均存在周期性误差,并在此基础上构建了考虑周期性误差修正的3类Tm新模型。利用2011—2014年全球探空数据对3类新模型进行精度验证,结果表明:3类Tm新模型的精度相比于原模型均有所提升,模型的周期性误差影响基本得以消除,且3类Tm新模型的精度基本一致。更多还原

【Abstract】 Aiming at the problem that many weighted mean temperature(Tm)models ignore the influence of seasonal variation,in this paper,we first built the line Tmmodel(L-Tm),power Tmmodel(P-Tm)and mix Tm model(M-Tm)at each selected integrated global radiosonde archive(IGRA)station using the sounding data provided by IGRA in the year 2005-2010.Then the performances of different Tm models were verified by taking integrated Tm as reference.It was found that these traditional models suffered from seasonal errors.Thus three improved Tmmodels that considered the influence of seasonal variation were proposed to reduce the influence of such errors.The results showed that compared with the traditional models,the improved models were more accurate while they were verified by IGRA data in 2011-2014.Additionally,the seasonal errors presented in the traditional models almost disappeared in the improved models,and the accuracy of three different improved Tmmodels was also similar.更多还原