GNSS-GPS derived integrated water vapor and performance assessment of ERA-5 data over India

Shaeb, K. Hareef Baba; priya, R. Kavi; Biswadip, G.; Seshasai, M. V. R.

doi:10.1016/j.jastp.2021.105807

Cited by 14 publications

(6 citation statements)

References 48 publications

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“…Kannemadugu et al (2022) 31 used ERA5 and 18 GPS station data to analyse PWV over India for the period from March 2013 to February 2014. They concluded that ERA5 PWV is consistent with GPS measurements, with a correlation coefficient ranging from 0.93 to 0.99, indicating that ERA5 can accurately capture the observed PWV variability.…”

Section: Methodsmentioning

confidence: 99%

Long-term changes in precipitable water vapour over India derived from satellite and reanalysis data for the past four decades (1980–2020)

Sarkar

Kuttippurath

Patel

2023

Environ. Sci.: Atmos.

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Section: Methodsmentioning

confidence: 99%

Long-term changes in precipitable water vapour over India derived from satellite and reanalysis data for the past four decades (1980–2020)

Sarkar

Kuttippurath

Patel

2023

Environ. Sci.: Atmos.

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“…For RMSE, uniform consistency was not observed across distinct seasons at various stations, but most stations exhibited the lowest values in winter throughout the year. Furthermore, large RMSE values were not consistently observed during seasons with high PWV [55].…”

Section: Spatial and Seasonal Pwv Variabilitymentioning

confidence: 82%

Investigating the ERA5-Based PWV Products and Identifying the Monsoon Active and Break Spells with Dense GNSS Sites in Guangxi, China

Liu,

Zhang,

Xiong

et al. 2023

Remote Sensing

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Precipitable water vapor (PWV) with high precision and high temporal resolution estimated by Global Navigation Satellite System (GNSS) is widely used in atmospheric research and weather forecasting. However, most previous works are not consensual concerning the characteristics of the PWV at different time scales and the identification of active and break spells during summ er monsoon climate in Guangxi, China. Taking radiosonde (RS) observations as reference, a strong correlation (R > 0.97) exists between GNSS PWV and RS PWV with a mean root mean square error (RMSE) of 2.68 mm. The annual, seasonal, monthly, and diurnal PWV variations of three years (2017, 2018 and 2020) over Guangxi in were comprehensively investigated using 104 GNSS stations and the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5). The mean annual bias and RMSE between GNSS PWV and ERA5 PWV are −1.04 mm and 2.63 mm, respectively. The monthly bias and RMSE range are −0.77 to 3.87 mm, 1.32 to 4.45 mm, and the daily range is −1.41 to 1.07 mm and 1.11 to 5.02 mm, respectively. Additionally, the adopted average standardized rainfall anomaly criteria also identified 7/7/3 active spells and 5/3/7 break spells during the summer monsoon (June–September) from 2017 to 2020, respectively. During the three-year period, the daily amplitude ranges for active spells varied from 1.41 to 2.49 mm, 0.69 to 5.4 mm, and 0.88 to 1.41 mm, while the ranges for break spells were 2.45 to 6.76 mm, 1.66 to 8.17 mm, and 1.48 to 2.99 mm, respectively. The results show a superior performance of GNSS PWV compared to ERA5 PWV in Guangxi, and the maximum, minimum and occurrence time of PWV anomaly vary slightly with the season and the topography of stations. Despite temperature primarily exhibiting a negative correlation with rainfall, acting as a dampener, a positive correlation remains evident between PWV and rainfall. Therefore, densely distributed GNSS stations exhibit excellent capabilities in quantifying atmospheric water vapor and facilitating real-time monitoring of small and medium-scale weather phenomena.

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“…After that, the Zenith Wet Delay (ZWD) is calculated by subtracting ZTD and ZHD (ZWD = ZTD – ZHD). In addition, the ZWD is converted into PWV at 30s intervals by the conversion factor [ 40 , 70 ] as Equations (2) , (3) ).

where

is the conversion factor computed by the mean of temperature ( Tm ) in Kelvin unit, the density of liquid water ( ρ w, 999.97 kg m −3 ) and the constant of water vapor ( Rv , 461.525 J kg K −1 ).…”

Section: Methodsmentioning

confidence: 99%

Estimating daily potential evapotranspiration using GNSS-based precipitable water vapor

Pipatsitee,

Ninsawat,

Tripathi

et al. 2023

Heliyon

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GNSS-GPS derived integrated water vapor and performance assessment of ERA-5 data over India

Cited by 14 publications

References 48 publications

Long-term changes in precipitable water vapour over India derived from satellite and reanalysis data for the past four decades (1980–2020)

Long-term changes in precipitable water vapour over India derived from satellite and reanalysis data for the past four decades (1980–2020)

Investigating the ERA5-Based PWV Products and Identifying the Monsoon Active and Break Spells with Dense GNSS Sites in Guangxi, China

Estimating daily potential evapotranspiration using GNSS-based precipitable water vapor

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