顾及多因子的香港地区加权平均温度Bevis精化模型

Bevis Refined Model of Weighted Average Temperature in Hong Kong Considering Multi-Factors

针对Bevis模型在香港地区精度较低的问题,基于香港地区探空站连续20 a(2000—2019年)的实测数据,建立顾及多因子的香港地区加权平均温度(T_(m))Bevis精化模型。首先,分析T_(m)与地面温度T_(s)、水汽压e_(s)、气压P之间的线性相关性;其次,采用快速傅里叶变换探测到T_(m)具有明显的年周期变化;最后在Bevis模型的基础上,综合考虑T_(s)、e_(s)、P以及年周期变化,基于非线性最小二乘法建立香港地区加权平均温度Bevis精化模型BTm。以2020年香港地区探空数据数值积分法计算的T_(m)作为参考值,对BTm模型进行精度检验,并与Bevis模型和GPT2w模型进行比较分析。结果表明:BTm模型具有相对较好的精度,其年均偏差和均方根误差(RMS)分别为-0.11 K和1.64 K,相比Bevis全球模型、GPT2w-1模型和GPT2w-5模型,其精度分别提高46.4%、35.7%和37.2%。

In view of the low accuracy of the Bevis model in Hong Kong,the measured data of the radiosonde_(s)tation in Hong Kong for 20 consecutive years(2000—2019)is used to establish the Bevis refined model of the T_(m)in Hong Kong considering multi-factors.Firstly,the linear correlation between T_(m)and surface temperature(T_(s)),water vapor pressure(e_(s))and pressure(P)are analyzed.Secondly,the annual periodic variation of T_(m)is detected by fast fourier transform.Finally,based on the Bevis model,comprehensively consider the changes of T_(s),e_(s),P and annual cycle,the Bevis refined model of weighted average temperature(BTm)in Hong Kong is established based on the nonlinear least square method.Considering the values calculated by the numerical integration method of radiosonde data in Hong Kong in 2020 as the reference values,the accuracy of the model is tested and compared with the Bevis global model and GPT2w model.The results show that the BTm model has relatively good accuracy,and its mean bias and root mean square error(RMS)are-0.11 K and 1.64 K,respectively.Compared with the Bevis global model,the GPT2w-1 model and the GPT2w-5 model,the accuracy is improved by 46.4%,35.7%and 37.2%,respectively.