GPS气象学中垂直干分量延时的精确确定(英文)

Precise Determination of Dry Zenith Delay for GPS Meteorology Applications

确定大气中可降水分的含量是 GPS气象学的目的之一。可降水分含量对应于 GPS信号中湿分量延时。现有高精度 GPS软件包只能提供天顶方向的对流层延时 ,但是 ,对流层延时由干分量和湿分量延时组成。因此 ,精确确定干分量延时 ,是分离湿分量延时的关键 ,也是GPS气象学中必不可少的工作。 现有 3种经验模型计算垂直干分量延时 ,即萨氏 (Saastamoinen)模型 ,霍氏 (Hopfield)模型和布兰克 (Black)模型。它们的具体形式分别为 :dz S=0 .2 2 77PF(φ,H )F(φ,H )≡ 1 -0 .0 0 2 6cos(2φ) -0 .0 0 0 2 8H (1 )dz H=1 .5 5 2 (h-H ) PTh≡ 40 .0 82 + 0 .1 4898(T-2 73 .1 6) (2 )dz B=0 .2 3 43 (T-4 .1 2 ) PT (3 )式中 ,垂直干分量延时的单位是 cm;P为气压 ,T为绝对温度 ,H为测站海拔高 ,φ是测站纬度 ;下标 S,H和 B分别代表萨氏 ,霍氏和布兰克模型。现有文献简单认为以上 3种模型没有误差[1,12 ] ,或几毫米的误差[2 ,4～ 6 ,10 ] ,没有详细讨论这些模型的精度。 3种模型中 ,垂直干分量延时是气压和温度观测值的函数 ,式 (1 )～式 (3 )分别对气压和温度微分后 ,并保证其系数达到最大值 ,可以得到垂直干分量延时与气压及温度的微分关系。由此得到 :如果?

Determination of dry zenith delay, DZD, is important for separating water vapor content from GPS solutions in GPS meteorology. The existing models usually cannot meet this need with high accuracy. In this study, we calibrated three popular DZD models namely Saastamoinen, Hopfield and Black models for local GPS meteorology application using radiosonde data. We test the models by comparing the predicted delays from the calibrated models against the observed delays from radiosonde data that are not included in the solution. Calibrated models on the average show 98 pc improvement over the uncalibrated model predictions over one month period. A comparison of the DZDs calculated from GPS measurements over a month period with calibrated and uncalibrated model prediction shows, on the average, 96 pc better agreement for the calibrated models.