Study of persistent fog in Bulgaria with Sofia Stability Index, GNSS tropospheric products and WRF simulations

Stoycheva, Anastasiya; Manafov, Ilian; Vassileva, K.; Guerova, Guergana

doi:10.1016/j.jastp.2017.06.011

Cited by 5 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(6) Stoycheva et al installed GNSS at three altitudes (595, 1120, and 2290 m) in a foggy Bulgarian valley and estimated the change in air mass according to altitude using GNSS IWV and investigated the spatiotemporal characteristics of fog. (7) Furthermore, they simulated the results using a numerical forecasting model and ultimately confirmed an improvement in fog forecast ability. In this study, the relationships between fog and both precipitable water vapor (PWV) resulting from the GNSS tropospheric delay and weather data were analyzed.…”

Section: Introductionmentioning

confidence: 81%

“…Previous studies have compared PWV using GNSS with that using radiosondes or MWRs and found that they deliver similar results. (2)(3)(4)(5)(6)(7) The accuracy of PWV is affected by those of temperature and pressure, and the data from the Jeju Meteorological Office, where GNSS is installed, were used to determine these parameters.…”

Section: Relationship Between Fog and Gnss Pwvmentioning

confidence: 99%

See 1 more Smart Citation

Fog and Cloudiness Monitoring Using Global Navigation Satellite System Precipitable Water Vapor

Wonjong¹,

Choi²,

Hasu³

2022

Sensors and Materials

View full text Add to dashboard Cite

Fog is formed when water vapor in the atmosphere condenses into miniscule floating water droplets, rendering a visibility of less than 1 km. Fog causes economic damage and poses a hazard to people owing to limited visibility. Fog forecasts depend on the judgment and experience of the forecaster, who bases the forecast on analysis results from meteorological models and satellite images. However, such forecasts are complicated by spatiotemporal changes and fine physical processes. To address this issue, a variety of fog studies have used the Global Navigation Satellite System (GNSS) tropospheric signal delay as an alternative. In this study, we monitored fog and cloudiness by analyzing precipitable water vapor (PWV) extracted from GNSS tropospheric delay. The analysis of the change in PWV during fog generation showed that it is difficult to detect fog from PWV using GNSS; more precise GNSS processing is required. However, it was found that cloudiness affects the change in PWV. In particular, the change in PWV is affected by high-level and middle-level clouds rather than low-level clouds. In other words, we conducted research to detect fog and cloudiness, but it was difficult to monitor them using PWV calculated from GNSS, although the use of GNSS to monitor the high-level and middle-level clouds generated good results. The results of this study will aid in quantitative cloudiness measurements, which at present are mostly performed through non-quantitative visual inspection. Furthermore, these results are expected to be helpful in the development of automatic observation devices for cloudiness measurements, satellite image processing, and weather forecasting.

show abstract

Section: Introductionmentioning

confidence: 81%

Section: Relationship Between Fog and Gnss Pwvmentioning

confidence: 99%

Fog and Cloudiness Monitoring Using Global Navigation Satellite System Precipitable Water Vapor

Wonjong¹,

Choi²,

Hasu³

2022

Sensors and Materials

View full text Add to dashboard Cite

show abstract

“…A further step should deal with the use of IWV GNSS and ZTD GNSS as input for weather prediction, particularly for the forecast of heavy precipitation events. The assimilation of ZTD on numerical weather prediction models has been performed in several regions of the world (Stoycheva et al, 2017;Ahmed et al, 2015;Kumar et al, 2017;Rohm et al, 2019;Singh et al, 2019), with improvements in the forecast of key variables as surface pressure, moisture transport or precipitation. In this sense, considering that the IWV alone is not enough to describe precipitation variations over the region, the evolution of atmospheric pressure and wind patterns should be analyzed for a larger number of case studies, comparing forecasts and observations.…”

Section: Discussionmentioning

confidence: 99%

Estimation of integrated water vapor derived from Global Navigation Satellite System observations over Central-Western Argentina (2015–2018). Validation and usefulness for the understanding of regional precipitation events

Camisay

Rivera

Mateo

et al. 2020

Journal of Atmospheric and Solar-Terrestrial Physics

View full text Add to dashboard Cite

Use of GNSS Tropospheric Products for High-Resolution, Rapid-Update NWP and Severe Weather Forecasting (Working Group 2)

Haan

Pottiaux

Sánchez-Arriola

et al. 2019

Advanced GNSS Tropospheric Products for Monitoring Severe Weather Events and Climate

View full text Add to dashboard Cite

Study of persistent fog in Bulgaria with Sofia Stability Index, GNSS tropospheric products and WRF simulations

Cited by 5 publications

References 18 publications

Fog and Cloudiness Monitoring Using Global Navigation Satellite System Precipitable Water Vapor

Fog and Cloudiness Monitoring Using Global Navigation Satellite System Precipitable Water Vapor

Estimation of integrated water vapor derived from Global Navigation Satellite System observations over Central-Western Argentina (2015–2018). Validation and usefulness for the understanding of regional precipitation events

Use of GNSS Tropospheric Products for High-Resolution, Rapid-Update NWP and Severe Weather Forecasting (Working Group 2)

Contact Info

Product

Resources

About