scholarly journals Comparison of precipitable water over Ghana using GPS signals and reanalysis products

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
A. A. Acheampong ◽  
C. Fosu ◽  
L. K. Amekudzi ◽  
E. Kaas
Keyword(s):  
Water Vapour ◽  
Meteorological Parameters ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Reanalysis Data ◽  
Base Station ◽  
Base Stations ◽  
Satellite Systems ◽  
Location Map ◽  
Troposphere Delays

AbstractSignals from Global Navigational Satellite Systems (GNSS) when integrated with surface meteorological parameters can be used to sense atmospheric water vapour. Using gLAB software and employing precise point positioning techniques, zenith troposphere delays (ZTD) for a GPS base station at KNUST, Kumasi have been computed and used to retrieve Precipitable Water (PW). The PW values obtained were compared with products from ERA-Interim and NCEP reanalysis data. The correlation coefficients, r, determined from these comparisons were 0.839 and 0.729 for ERA-interim and NCEP respectively. This study has demonstrated that water vapour can be retrieved with high precision from GNSS signal. Furthermore, a location map have been produced to serve as a guide in adopting and installing GNSS base stations in Ghana to achieve a country wide coverage of GNSS based water vapour monitoring.

scholarly journals Evaluation of MODIS Water Vapour Products over ALGERIA using Radiosonde Data

2021 ◽  
Vol 44 ◽  
Author(s):  
Houaria Namaoui ◽  
Salem Kahlouche ◽  
Ahmed Hafidh Belbachir
Keyword(s):  
Water Vapour ◽  
Satellite Data ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
Precipitable Water Vapour ◽  
Total Precipitable Water ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Remote sensing of atmospheric water vapour using GNSS and Satellite data has become an efficient tool in meteorology and climate research. Many satellite data have been increasingly used to measure the content of water vapour in the atmosphere and to characterize its temporal and spatial variations. In this paper, we have used observations from radiosonde data collected from three stations (Algiers, Bechar and Tamanrasset) in Algeria from January to December 2012 to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) total precipitable water vapour (PWV) products. Results show strong agreement between the total precipitable water contents estimated based on radiosondes observations and the ones measured by the sensor MODIS with the correlation coefficients in the range 0.69 to 0.95 and a mean bias, which does not exceed 1.5.  

scholarly journals Intercomparisons of precipitable water vapour derived from radiosonde , GPS and sunphotometer observations

2020 ◽  
Vol 64 (04) ◽  
pp. 562-577
Author(s):  
Shaoqi Gong ◽  
Wenqin Chen ◽  
Cunjie Zhang ◽  
Ping Wu ◽  
Jing Han
Keyword(s):  
Water Vapour ◽  
Hydrological Cycle ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Global Scale ◽  
Precipitable Water Vapour ◽  
Climatic Regions ◽  
Systematic Biases ◽  
Matched Data ◽  
Relative Differences

The atmospheric precipitable water vapour (PWV) plays a crucial role in the hydrological cycle and energy transfer on a global scale. Radiosonde (RS), sunphotometer (SP) and GPS (as well as broader GNSS) receivers have gradually been the principal instruments for ground-based PWV observation. This study first co-locates the observation stations configured the three instruments in the globe and in three typical latitudinal climatic regions respectively, then the PWV data from the three instruments are matched each other according to the observing times. After the outliers are removed from the matched data pairs, the PWV intercomparisons for any two instruments are performed. The results show that the PWV estimates from any two instruments have a good agreement with very high correlation coefficients. The latitude and climate have no significant influence on the PWV measurements from the three instruments, indicating that the instruments are very stable and depend on their performance. The PWV differences of any two instruments display the normal distribution, indicating non-systematic biases among the two PWV datasets. The relative differences between SP and GPS are the smallest, the middle between SP and RS, and those between GPS and RS are the largest. This study will be useful to promote GPS (GNSS) and SP PWV to be a substitute for RS PWV as a benchmark because of their high temporal resolutions.

scholarly journals Estimating trends in atmospheric water vapor and temperature time series over Germany

2017 ◽  
Author(s):  
Fadwa Alshawaf ◽  
Kyriakos Balidakis ◽  
Galina Dick ◽  
Stefan Heise ◽  
Jens Wickert
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Temporal Trends ◽  
Precipitable Water ◽  
Reanalysis Data ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Surface Measurements ◽  
Standard Deviations ◽  
Gnss Time Series

Abstract. Ground-based GNSS (Global Navigation Satellite Systems) have efficiently been used since the 1990s as a meteorological observing system. Recently scientists used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts Reanalysis (ERA-Interim) data and meteorological measurements. We aim at evaluating climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: 1) estimated from ground-based GNSS observations using the method of precise point positioning, 2) inferred from ERA-Interim reanalysis data, and 3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods, the first applies least squares to seasonally-adjusted time series and the second using the Theil-Sen estimator. The trends estimated at 113 GNSS sites, with 10 and 19 year temporal coverage, varies between −1.5 and 2 mm/decade with standard deviations below 0.25 mm/decade. These values depend on the length and the variations of the time series. Therefore, we estimated the PWV trends using ERA-Interim and surface measurements spanning from 1991 to 2016 (26 years) at synoptic 227 stations over Germany. The former shows positive PWV trends below 0.5 mm/decade while the latter shows positive trends below 0.9 mm/decade with standard deviations below 0.03 mm/decade. The estimated PWV trends correlate with the temperature trends.

scholarly journals Potential of INSAT-3D sounder-derived total precipitable water product for weather forecast

2018 ◽  
Vol 11 (11) ◽  
pp. 6003-6012 ◽  
Author(s):  
Shailesh Parihar ◽  
Ashim Kumar Mitra ◽  
Mrutyunjay Mohapatra ◽  
Rajjev Bhatla
Keyword(s):  
Water Vapour ◽  
Weather Forecasting ◽  
Meteorological Data ◽  
Processing System ◽  
Correlation Coefficients ◽  
India Meteorological Department ◽  
Precipitable Water ◽  
Weather Forecast ◽  
Satellite System ◽  
Total Precipitable Water

Abstract. The objectives of the INSAT-3D satellite are to enhance the meteorological observations and to monitor the Earth's surface for weather forecasting and disaster warning. One of the weather-monitoring capabilities of the INSAT-3D sounder is the estimation of water vapour in the atmosphere. The amount of water vapour present in the atmospheric column is derived as the total precipitable water (TPW) product from the infrared radiances measured by the INSAT-3D sounder. The present study is based on TPW derived from INSAT-3D sounder, radiosonde (RS) observations and the corresponding National Oceanic and Atmospheric Administration (NOAA) satellite. To assess retrieval performances of INSAT-3D sounder-derived TPW, RS TPW observations are considered for the validation from May to September 2016 from 34 stations belonging to the India Meteorological Department (IMD). The analysis is performed on daily, monthly, and subdivisional bases over the Indian region. The comparison of INSAT-3D TPW with RS TPW on daily and monthly bases shows that the root mean square error (RMSE) and correlation coefficients (CC) are ∼8 mm and 0.8, respectively. However, on subdivisional and overall scales, the RMSE found to be in the range of 1 to 2 mm and CC was around 0.9 in comparison with RS and NOAA. The spatial distribution of INSAT-3D TPW with actual rainfall observation is also investigated. In general, INSAT-3D TPW corresponds well with rainfall observation; however, it has found that heavy rainfall events occur in the presence of high TPW values. In addition, the cases of thunderstorm events were assessed using TPW from INSAT-3D and network of Global Navigation Satellite System (GNSS) receiver. This shows the good agreement between TPW from INSAT-3D and GNSS during the mesoscale activity. The improvement in the estimation of TPW is carried out by applying the GSICS calibration corrections (Global Space-based Inter-Calibration System) to the radiances from infrared (IR) channels of the sounder, which is used by IMDPS (INSAT Meteorological Data Processing System). The current TPW from INSAT-3D satellite can be utilized operationally for weather monitoring and forecast purposes. It can also offer substantial opportunities for improvement in nowcasting studies.

scholarly journals Water Vapour Assessment Using GNSS and Radiosondes over Polar Regions and Estimation of Climatological Trends from Long-Term Time Series Analysis

2021 ◽  
Vol 13 (23) ◽  
pp. 4871
Author(s):  
Monia Negusini ◽  
Boyan H. Petkov ◽  
Vincenza Tornatore ◽  
Stefano Barindelli ◽  
Leonardo Martelli ◽  
...  
Keyword(s):  
Water Vapour ◽  
Correlation Coefficients ◽  
Arctic Region ◽  
Precipitable Water ◽  
Satellite System ◽  
The Arctic ◽  
Polar Regions ◽  
Precipitable Water Vapour ◽  
Water Vapour Content

The atmospheric humidity in the Polar Regions is an important factor for the global budget of water vapour, which is a significant indicator of Earth’s climate state and evolution. The Global Navigation Satellite System (GNSS) can make a valuable contribution in the calculation of the amount of Precipitable Water Vapour (PW). The PW values retrieved from Global Positioning System (GPS), hereafter PWGPS, refer to 20-year observations acquired by more than 40 GNSS geodetic stations located in the polar regions. For GNSS stations co-located with radio-sounding stations (RS), which operate Vaisala radiosondes, we estimated the PW from RS observations (PWRS). The PW values from the ERA-Interim global atmospheric reanalysis were used for validation and comparison of the results for all the selected GPS and RS stations. The correlation coefficients between times series are very high: 0.96 for RS and GPS, 0.98 for RS and ERA in the Arctic; 0.89 for RS and GPS, 0.97 for RS and ERA in Antarctica. The Root-Mean-Square of the Error (RMSE) is 0.9 mm on average for both RS vs. GPS and RS vs. ERA in the Arctic, and 0.6 mm for RS vs. GPS and 0.4 mm for RS vs. ERA in Antarctica. After validation, long-term trends, both for Arctic and Antarctic regions, were estimated using Hector scientific software. Positive PWGPS trends dominate at Arctic sites near the borders of the Atlantic Ocean. Sites located at higher latitudes show no significant values (at 1σ level). Negative PWGPS trends were observed in the Arctic region of Greenland and North America. A similar behaviour was found in the Arctic for PWRS trends. The stations in the West Antarctic sector show a general positive PWGPS trend, while the sites on the coastal area of East Antarctica exhibit some significant negative PWGPS trends, but in most cases, no significant PWRS trends were found. The present work confirms that GPS is able to provide reliable estimates of water vapour content in Arctic and Antarctic regions too, where data are sparse and not easy to collect. These preliminary results can give a valid contribution to climate change studies.

scholarly journals Observations of precipitable water vapour over complex topography of Ethiopia from ground-based GPS, FTIR, radiosonde and ERA-Interim reanalysis

2015 ◽  
Vol 8 (8) ◽  
pp. 3277-3295 ◽  
Author(s):  
G. Mengistu Tsidu ◽  
T. Blumenstock ◽  
F. Hase
Keyword(s):  
Water Vapour ◽  
Surface Pressure ◽  
Land Surface ◽  
Addis Ababa ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Steady Increase ◽  
Data Sets ◽  
Precipitable Water Vapour ◽  
Direct Role

Abstract. Water vapour is one of the most important greenhouse gases. Long-term changes in the amount of water vapour in the atmosphere need to be monitored not only for its direct role as a greenhouse gas but also because of its role in amplifying other feedbacks such as clouds and albedo. In recent decades, monitoring of water vapour on a regular and continuous basis has become possible as a result of the steady increase in the number of deployed global positioning satellite (GPS) ground-based receivers. However, the Horn of Africa remained a data-void region in this regard until recently, when some GPS ground-receiver stations were deployed to monitor tectonic movements in the Great Rift Valley. This study seizes this opportunity and the installation of a Fourier transform infrared spectrometer (FTIR) at Addis Ababa to assess the quality and comparability of precipitable water vapour (PWV) from GPS, FTIR, radiosonde and interim ECMWF Re-Analysis (ERA-Interim) over Ethiopia. The PWV from the three instruments and the reanalysis show good correlation, with correlation coefficients in the range from 0.83 to 0.92. On average, GPS shows the highest PWV followed by FTIR and radiosonde observations. ERA-Interim is higher than all measurements with a bias of 4.6 mm compared to GPS. The intercomparison between GPS and ERA-Interim was extended to seven other GPS stations in the country. Only four out of eight GPS stations included simultaneous surface pressure observations. Uncertainty in the model surface pressure of 1 hPa can cause up to 0.35 mm error in GPS PWV. The gain obtained from using observed surface pressure in terms of reducing bias and strengthening correlation is significant but shows some variations among the GPS sites. The comparison between GPS and ERA-Interim PWV over the seven other GPS stations shows differences in the magnitude and sign of bias of ERA-Interim with respect to GPS PWV from station to station. This feature is also prevalent in diurnal and seasonal variabilities. The spatial variation in the relationship between the two data sets is partly linked to variation in the skill of the European Centre for Medium-Range Weather Forecasts (ECMWF) model over different regions and seasons. This weakness in the model is related to poor observational constraints from this part of the globe and sensitivity of its convection scheme to orography and land surface features. This is consistent with observed wet bias over some highland stations and dry bias over few lowland stations. The skill of ECMWF in reproducing realistic PWV varies with time of the day and season, showing large positive bias during warm and wet summer at most of the GPS sites.

scholarly journals Inter-comparison of retrievals of Integrated Precipitable Water Vapour IPWV) made by INSAT-3DR satellite-borne Infrared Radiometer Sounding and CAMS reanalysis data with ground-based Indian GNSS data

2021 ◽  
Author(s):  
Ramashray Yadav ◽  
Ram Kumar Giri ◽  
Virendra Singh
Keyword(s):  
Water Vapour ◽  
Monsoon Season ◽  
Winter Season ◽  
Precipitable Water ◽  
Satellite System ◽  
Reanalysis Data ◽  
Regional Variability ◽  
Precipitable Water Vapour ◽  
Post Monsoon ◽  
Gnss Data

Abstract. The spatiotemporal variations of integrated precipitable water vapor (IPWV) are very important to understand the regional variability of water vapour. Traditional in-situ measurements of IPWV in Indian region are limited and therefore the performance of satellite and Copernicus Atmosphere Meteorological Service (CAMS) retrievals with Indian Global Navigation Satellite System (GNSS) taking as reference has been analyzed. In this study the CAMS reanalysis retrieval one year (2018), Indian GNSS and INSAT-3DR sounder retrievals data for one & half years (January-2017 to June-2018) has been utilized and computed statistics. It is noticed that seasonal correlation coefficient (CC) values between INSAT-3DR and Indian GNSS data mainly lie within the range of 0.50 to 0.98 for all the selected 19 stations except Thiruvanathpuram (0.1), Kanyakumari (0.31), Karaikal (0.15) during monsoon and Panjim (0.2) during post monsoon season respectively. The seasonal CC values between CAMS and INSAT-3DR IPWV are ranges 0.73 to .99 except Jaipur (0.16) & Bhubneshwar (0.29) during pre-monsoon season, Panjim (0.38) during monsoon, Nagpur (0.50) during post-monsoon and Dibrugarh (0.49) Jaipur (0.58) & Bhubneshwar (0.16) during winter season respectively .The root mean square error (RMSE) values are higher under the wet conditions (Pre Monsoon & Monsoon season) than under dry conditions (Post Monsoon & Winter season) and found differences in magnitude and sign of bias of INSAT-3DR, CAMS with respect to GNSS IPWV from station to station and season to season. This study will help to improve understanding and utilization of CASMS and INSAT-3DR data more effectively along with GNSS data over land, coastal and desert locations in term of seasonal flow of IPWV which is an essential integrated variable in forecasting applications.

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