Precipitable Water Vapour Retrieval from GPS Precise Point Positioning and NCEP CFSv2 Dataset during Typhoon Events

Radiosonde is extensively used for understanding meteorological parameters in the vertical direction. Four typhoon events, including three landfalls (MERANTI, NEPARTAK, and MEGI) and one non-landfall (MALAKAS), were chosen in analysing the precipitable water vapour (PWV) characteristics in this study. The spatial distribution of the three radiosonde stations in Zhejiang province does not meet the requirement in analysing changes in PWV during typhoon event. Global position system (GPS) observations are an alternative method for deriving the PWV. This enables improvements in the temporal–spatial resolution of PWV computed by the radiosonde measurements. The National Centers for Environmental Prediction (NCEP) re-analysed data were employed for interpolating temperature and atmosphere pressure at the GPS antennas height. The PWV computed from GPS observations and NCEP re-analysed data were then compared with the true PWV. The maximum difference of radiosonde and GPS PWV was not more than 30 mm at Taiz station. The Root-Mean-Square (RMS) of PWV differences between radiosonde and GPS was not more than 5 mm in January, February, March, November, and December. It was slightly greater than 5 mm in April. High RMS in May, June, July, August, September, and October implies that differences in GPS and radiosonde PWVs are evident in these months. Correlation coefficients of GPS and radiosonde PWVs were more than 0.9, indicating that the changes in GPS and radiosonde PWVs are similar. Radiosonde calculated PWVs were used for GPS PWV calibration for understanding the PWV changes during the period of a typhoon event. The results from three landfall typhoons show that the average PWV over Zhejiang province is increasing and approaching China mainland. In contrast, MALAKAS did not make landfall and shows a decreasing PWV trend, although it was heading to China mainland. Generally, the PWV change can be used to predict whether the typhoon will make landfall in these cases. PWV spatial distribution of MERANTI shows that PWV peaks change along the typhoon epicenter over Zhejiang province.

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Evaluation of MODIS Water Vapour Products over ALGERIA using Radiosonde Data

Anuário do Instituto de Geociências - UFRJ ◽

10.11137/1982-3908_2021_44_40110 ◽

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.

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

Geodetski vestnik ◽

10.15292/geodetski-vestnik.2020.04.562-577 ◽

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.

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

Remote Sensing ◽

10.3390/rs13234871 ◽

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.

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Precipitable water vapour monitoring using ground based GPS system

MAUSAM ◽

10.54302/mausam.v61i2.802 ◽

2021 ◽

Vol 61 (2) ◽

pp. 203-212

Author(s):

N. PUVIARASAN ◽

R. K. GIRI ◽

MANISH RANALKAR

Keyword(s):

Real Time ◽

Water Vapour ◽

Global Positioning System ◽

Precipitable Water ◽

Precipitable Water Vapour ◽

Window Technique ◽

Hourly Rainfall ◽

Global Positioning ◽

Gps System ◽

Gps Observations

The sensing of near real time Precipitable Water Vapour (PWV) using Global Positioning System (GPS) over Indian region were analyzed. GPS data collected from five stations at hourly interval were utilized to determine near real time PWV using GAMIT software. Sliding window technique was used to derive near real time PWV. The PWV determined from GPS observations of each site were compared with respective radiosonde measurements. The results shows that the derived GPS precipitable water well agree for some stations with the independent radiosonde measurements. We have also examined the variation of hourly GPS-PWV with hourly rainfall observation and found that PWV increases significantly before the event take place and decreases after the event.

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

Atmospheric Measurement Techniques ◽

10.5194/amt-8-3277-2015 ◽

2015 ◽

Vol 8 (8) ◽

pp. 3277-3295 ◽

Cited By ~ 17

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.

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