海口地区GPS反演大气可降水量中加权平均温度模型构建及其应用

李光伟, 黄光瑞, 邢峰华, 敖杰

Construction of weighted mean temperature model in retrieval of atmospheric precipitable water from GPS in Haikou and its application

LI Guangwei, HUANG Guangrui, XING Fenghua, AO Jie

表5 2013—2014年海口站Tm回归模型统计检验结果

Tab.5 Statistical tests result of Tm regression model from 2013 to 2014 at Haikou station

模型名称 模型公式 样本量/个 RMSE/K 绝对误差/K 复相关系数R 夏半年 Tm=88.78+0.67Ts 672 1.814 0.376 0.6028 冬半年 Tm=72.83+0.73Ts 708 2.063 0.360 0.8133 Bevis Tm=70.2+0.72Ts 1380 4.650 -4.170 0.8085 F1 Tm=107.64+0.61Ts 1380 2.000 0.335 0.8085 F9 Tm=103.59+0.61Ts+0.03RH 1380 1.978 0.296 0.8120 F15 Tm=-72.32+1.21Ts+0.14RH-0.45Pes 1380 1.971 0.312 0.8143 F19 Tm=-35.59+1.23Ts-0.04Ps+0.15RH-0.50Pes 1380 1.961 0.289 0.8156 F20 Tm=-36.65+1.66Ts-0.47Td-0.037Ps+0.23RH-0.47Pes 1380 1.966 0.288 0.8148 FD1 Tm=40.89+0.83Ts+a_doy 1380 1.924 0.416 0.8283 FD9 Tm=31.67+0.85Ts+0.035RH+a_doy 1380 1.895 0.374 0.8324 FD11 Tm=130.34+0.78Ts-0.078Ps+0.03RH+a_doy 1380 1.861 0.327 0.8375 FD17 Tm=119.08+1.47Ts-0.71Td-0.08Ps+0.17RH+a_doy 1380 1.863 0.325 0.8370 FD20 Tm=90.95+1.43Ts-0.55Td-0.08Ps+0.16RH-0.09Pes+a_doy 1380 1.865 0.326 0.8367