Constructing a precipitable water vapor map from regional GNSS network observations without collocated meteorological data for weather forecasting

Abstract

Abstract. Surface pressure (Ps) and weighted mean temperature (Tm) are two necessary variables for the accurate retrieval of precipitable water vapor (PWV) from Global Navigation Satellite System (GNSS) zenith total delay (ZTD) estimates. The lack of Ps or Tm information is a concern for those GNSS sites that are not collocated with meteorological sensors. This paper investigates an alternative method of inferring accurate Ps and Tm at the GNSS station using nearby synoptic observations. Ps and Tm obtained at the nearby synoptic sites are interpolated onto the location of the GNSS station by performing both vertical and horizontal adjustments, in which the parameters involved in Ps and Tm calculation are estimated from ERA-Interim reanalysis profiles. In addition, we present a method of constructing high-quality PWV maps through vertical reduction and horizontal interpolation of the retrieved GNSS PWVs. To evaluate the performances of the Ps and Tm retrieval, and the PWV map construction, GNSS data collected from 58 stations of the Hunan GNSS network and synoptic observations from 20 nearby sites in 2015 were processed to extract the PWV so as to subsequently generate the PWV maps. The retrieved Ps and Tm and constructed PWV maps were assessed by the results derived from radiosonde and the ERA-Interim reanalysis. The results show that (1) accuracies of Ps and Tm derived by synoptic interpolation are within the range of 1.7–3.0 hPa and 2.5–3.0 K, respectively, which are much better than the GPT2w model; (2) the constructed PWV maps have good agreements with radiosonde and ERA-Interim reanalysis data with the overall accuracy being better than 3 mm; and (3) PWV maps can well reveal the moisture advection, transportation and convergence during heavy rainfall.

Evaluating Aerosol Optical Depth From Himawari‐8 With Sun Photometer Network

“…The observed reflectance of the top of atmosphere is corrected by gas absorption at visible to near‐infrared channels. A gas correction was implemented for water vapor and ozone (Yoshida et al, ), because their amount varies significantly with location and time (Chen et al, ). Surface reflectance is an essential parameter for building lookup tables (LUTs).…”

A New Method for Refining the GNSS-Derived Precipitable Water Vapor Map

“…The latest studies (e.g., [19,20]) have shown that GNSS-derived PWV has considerable potential applications in precipitation forecasting or meteorological disaster warning. Furthermore, the analysis of water vapor changing trends or the forecasting of short-term precipitation events requires the transformation of one-dimensional PWV data from observation networks to two-dimensional data through spatial interpolation [21]. The spatial interpolation algorithm consists of showing the dynamic distribution for water vapor within the CORS coverage area by real-time processing the GNSS-derived PWV of each receiver in the CORS network.…”

Determination of Weighted Mean Temperature (Tm) Lapse Rate and Assessment of Its Impact on Tm Calculation

“…A linear relationship exists between Tm and height [36], [37], (10) can be used to characterize the vertical dependence of Tm, namely the Tm lapse rate:…”

“…Zhang et al [36] explored the Tm lapse rate in China using the ERA-Interim data set over a whole year period and demonstrated that the accuracy of Tm estimated was improved with the Tm lapse rate in China areas. Chen et al [37] estimated the Tm lapse rate in some synoptic sites in Hunan Province of China to obtain the more accurate PWV maps. However, the Tm lapse rate was only mentioned briefly but not in depth, or just researched regionally in the previous literatures.…”