Due to its special observation principle, GPS remote sensing atmospheric precipitation has the advantages of high time resolution and no weather conditions, and has been widely used in the research field of atmospheri...Due to its special observation principle, GPS remote sensing atmospheric precipitation has the advantages of high time resolution and no weather conditions, and has been widely used in the research field of atmospheric precipitation. Using ground-based GPS precipitate water vapor data (GPS-PWV) and radiosonde-precipitate water vapor data (RS-PWV) that integrated by Radiosonde data, the error between GPS-PWV and RS-PWV in Tengchong is analyzed on its distribution of wet and dry seasons, also the difference between 00:00 UTC and 12:00 UTC. Results show that the RMSE of GPS-PWV and RS-PWV on both 00:00 UTC and 12:00 UTC are less than 5 mm, they correspond with each other well and their correlation coefficient is above 0.95, additionally, GPS-PWV value is stable than RS-PWV value. On the whole, the value of GPS-PWV is slightly larger than RS-PWV. And the mean absolute error between them has higher values, 4.5 mm in 2011 and 4.7 mm in 2012 from May to October (local rainy season) and lower values, 2.8 mm in 2011 and 3.1 mm in 2012 in November to April (local dry season). Besides, the mean absolute error in the morning seems has a difference with its component in the evening. Specifically, it is bigger on 12:00 UTC than on 00:00 UTC and the mean absolute errors on 12:00 UTC of two years are 27% and 11% larger than errors on 00:00 UTC respectively. The correlation of mean absolute error and surface vapor pressure, surface air temperature is examined in this study as well. We achieved that the correlation coefficient between mean absolute error and surface vapor pressure, surface air temperature equals 0.32, 0.37 separately. Diverse characters of mean absolute error under different precipitation conditions are also discussed. The outcome is that the mean absolute error has a higher value on rainy days and a lower value on clear days. However, during the precipitation periods, it appears that the mean absolute error and the rainfall situation don’t agree with each other well, it is likely to change randomly.展开更多
文摘Due to its special observation principle, GPS remote sensing atmospheric precipitation has the advantages of high time resolution and no weather conditions, and has been widely used in the research field of atmospheric precipitation. Using ground-based GPS precipitate water vapor data (GPS-PWV) and radiosonde-precipitate water vapor data (RS-PWV) that integrated by Radiosonde data, the error between GPS-PWV and RS-PWV in Tengchong is analyzed on its distribution of wet and dry seasons, also the difference between 00:00 UTC and 12:00 UTC. Results show that the RMSE of GPS-PWV and RS-PWV on both 00:00 UTC and 12:00 UTC are less than 5 mm, they correspond with each other well and their correlation coefficient is above 0.95, additionally, GPS-PWV value is stable than RS-PWV value. On the whole, the value of GPS-PWV is slightly larger than RS-PWV. And the mean absolute error between them has higher values, 4.5 mm in 2011 and 4.7 mm in 2012 from May to October (local rainy season) and lower values, 2.8 mm in 2011 and 3.1 mm in 2012 in November to April (local dry season). Besides, the mean absolute error in the morning seems has a difference with its component in the evening. Specifically, it is bigger on 12:00 UTC than on 00:00 UTC and the mean absolute errors on 12:00 UTC of two years are 27% and 11% larger than errors on 00:00 UTC respectively. The correlation of mean absolute error and surface vapor pressure, surface air temperature is examined in this study as well. We achieved that the correlation coefficient between mean absolute error and surface vapor pressure, surface air temperature equals 0.32, 0.37 separately. Diverse characters of mean absolute error under different precipitation conditions are also discussed. The outcome is that the mean absolute error has a higher value on rainy days and a lower value on clear days. However, during the precipitation periods, it appears that the mean absolute error and the rainfall situation don’t agree with each other well, it is likely to change randomly.
