A new model for vertical adjustment of precipitable water vapor with consideration of the time-varying lapse rate

Huang, Liangke; Li, Wen; Mo, Zhixiang; Zhang, Hongxing; Li, Junyu; Chen, Fade; Liu, Lilong; Jiang, Weiping

doi:10.1007/s10291-023-01506-5

Cited by 15 publications

(13 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, we will conduct an external consistency validation by using the m T reference values calculated from the numerical integration of hourly stratified water vapor pressure and temperature data provided by ERA5 (https://cds.climate.copernicus.eu/) in the zenith direction at the grid points. The detailed process can be found in 15 . The ERA5 reanalysis data has a spatial resolution of 0.25°×0.25° and a temporal resolution of 1 hour.…”

Section: Discussionmentioning

confidence: 99%

“…Before constructing the m T grid model, spatial interpolation is required for s T . In the interpolation process, the initial challenge to address is the inconsistency between the elevation surfaces of the meteorological stations and grid points 15 , which can induce significant systematic biases in interpolated temperatures, particularly in regions with high latitudes and complex terrains. Thus, a novel method considering the correction of hourly NSTLR is proposed and implemented to improve the accuracy of spatial interpolation of surface temperature at hourly resolution.…”

Section: Methodsmentioning

confidence: 99%

“…With the advancement of global navigation satellite system (GNSS), the remarkable advantages of high accuracy, all-weather capability, high spatial-temporal resolution, and low cost-effectiveness have positioned it as an emerging and robust tool in remotely sensing PWV, which has gradually evolved into a mature field known as GNSS meteorology [10][11][12][13][14][15][16] . When electromagnetic wave signals pass through the troposphere, they are influenced by atmospheric effects, resulting in refraction and bending of satellite signals.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A method for constructing the weighted mean temperature grid model considering the hourly near-surface temperature lapse rate in GNSS PWV

Yue,

Wang,

et al. 2024

Preprint

View full text Add to dashboard Cite

Weighted mean temperature (Tm) serves as a crucial parameter in converting tropospheric zenith wet delay into precipitable water vapor in global navigation satellite system meteorology. Different from the traditional strategy, this study developed a new method of atmospheric Tm grid model construction with high precision and high spatiotemporal resolution while taking into account the hourly near-surface air temperature lapse rates (NSTLR). Core research contents include the regional hourly NSTLR estimation and Tm grid model establishment. This proposed method was validated and analyzed using measured data from 109 meteorological stations in Shandong Province, located in eastern China. The result shows that compared with the correction by environmental lapse rate, the overall accuracy of the Tm grid model established by the hourly NSTLR correction can be improved by about 10.3% and 19.4%, respectively, when Tm reference values calculated based on the measured temperature and ERA5 reanalysis data were used. Furthermore, statistics show that for the Taishan Station with the highest altitude (1543 meters), the accuracy can be increased by 21.1% and 28.7%, respectively. Therefore, the proposed method is of great practical significance for the Tm construction by using ground-based meteorological observation, especially for the areas with large terrain changes.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A method for constructing the weighted mean temperature grid model considering the hourly near-surface temperature lapse rate in GNSS PWV

Yue,

Wang,

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Water vapor is a critical component of the atmosphere, influencing weather, climate variability, and extreme weather events [1]. Factors such as the coastal land position and topography influence the variations in water vapor, thereby causing regional differences in precipitation [2,3].…”

Section: Introductionmentioning

confidence: 99%

A Refined Atmospheric Weighted Average Temperature Model Considering Multiple Factors in the Qinghai–Tibet Plateau Region

Tian,

Xiong,

Wang

et al. 2023

Atmosphere

View full text Add to dashboard Cite

The Qinghai–Tibet Plateau region has significant altitude fluctuations and complex climate changes. However, the current global weighted average temperature (Tm) model does not fully consider the impact of meteorological and elevation factors on it, resulting in existing models being unable to accurately predict the Tm in the region. Therefore, this study constructed a weighted average temperature refinement model (XTm) related to surface temperature, water vapor pressure, geopotential height, annual variation, and semi-annual variation based on measured data from 13 radiosonde stations in the Qinghai–Tibet Plateau region from 2008 to 2017. Using the Tm calculated via the numerical integration method of radiosonde observations in the Qinghai–Tibet Plateau region from 2018 to 2019 as a reference value, the quality of the XTm model was tested and compared with the Bevis model and GPT2w (global pressure and temperature 2 wet) model. The results show that for 13 modeling stations, the bias and root-mean-square (RMS) values of the XTm model were −0.02 K and 2.83 K, respectively; compared with the Bevis, GPT2-1, and GPT2w-5 models, the quality of XTm was increased by 47%, 38%, and 47%, respectively. For the four non-modeling stations, the average bias and RMS values of the XTm model were 0.58 K and 2.78 K, respectively; compared with the other three Tm models, the RMS values and the mean bias were both minimal. In addition, the XTm model was also used to calculate the global navigation satellite system (GNSS) precipitable water vapor (PWV), and its average values for the theoretical RMSPWV and RMSPWV/PWV generated by water vapor calculation were 0.11 mm and 1.03%, respectively. Therefore, in the Qinghai–Tibet Plateau region, the XTm model could predict more accurate Tm values, which, in turn, is important for water vapor monitoring.

show abstract

“…Common methods for PWV vertical correction involve establishing empirical vertical correction models to enhance the applicability of PWV vertical correction (Emardson and Johansson, 1998;Dousa and Elias, 2014;Huang et al, 2023). Reitan (1963) introduced an empirical formula describing water vapor density's exponential decrease in the vertical direction, based on the relationship between PWV near the surface and at high altitudes.…”

mentioning

confidence: 99%

A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest

Li,

Wang,

Liu

et al. 2023

Preprint

View full text Add to dashboard Cite

Abstract. Various ground-based observing techniques provide precipitable water vapor (PWV) products with different spatial resolutions. To effectively integrate these products, especially in terms of vertical orientation, spatial interpolation is essential. In this context, we have developed a model to characterize PWV variation with altitude in the study area. Our model, known as RF-PWV (a PWV vertical correction grid model with a 1° x 1° resolution), is constructed using random forest based on the relationship between PWV differences from the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) monthly average hourly data and height differences and time. When validated against 1-h ERA5 PWV profiles, RF-PWV exhibits a 99.84 % reduction in Bias and a 63.41 % decrease in RMSE compared to the most recent model, C-PWVC1. Furthermore, when validated against radiosonde data, RF-PWV shows a 96.36 % reduction in Bias and a 5 % decrease in RMSE compared to C-PWVC1. Additionally, RF-PWV outperforms C-PWVC1 in terms of resistance to seasonal and height differences interference. The model eliminates the need for meteorological parameters, allowing for high-precision PWV vertical correction by inputting only time and height differences. Consequently, RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.

show abstract

A new model for vertical adjustment of precipitable water vapor with consideration of the time-varying lapse rate

Cited by 15 publications

References 40 publications

A method for constructing the weighted mean temperature grid model considering the hourly near-surface temperature lapse rate in GNSS PWV

A method for constructing the weighted mean temperature grid model considering the hourly near-surface temperature lapse rate in GNSS PWV

A Refined Atmospheric Weighted Average Temperature Model Considering Multiple Factors in the Qinghai–Tibet Plateau Region

A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest

Contact Info

Product

Resources

About