scholarly journals Comparison of GNSS and INSAT-3D sounder retrieved precipitable water vapour and validation with the GPS Sonde data over Indian Subcontinent

MAUSAM ◽  
2021 ◽  
Vol 71 (1) ◽  
pp. 1-10
Author(s):  
YADAV RAMASHRAY ◽  
PUVIARASAN N ◽  
GIRI R K ◽  
TOMAR C S ◽  
SINGH VIRENDRA

Precipitable water vapour (PWV) plays a key role in the atmospheric processes from climate change to micrometeorology. Its distribution and quantity are critical for the description of state and evaluation of the atmosphere in NWP model. Lack of precise and continuous water vapour data is one of the major error sources in short term forecast of precipitation. The task of accurately measuring atmospheric water vapour is challenging. Conventional in situ measurements of atmospheric water vapour is provided by GPS Sonde humidity sensors profile twice a day at 0000 and 1200 UTC mainly from limited land regions. In recent years India Meteorological Department (IMD) is computing PWV from 19 channel sounder of INSAT-3D in three layers 1000-900 hPa, 900-700 hPa and 700-300 hPa and total PWV in the vertical column of atmosphere stretching from surface to about 100 hPa under cloud free condition. These data most commonly were validated using spatially and temporally collocated GPS Sonde measurements. In this paper, INSAT-3D satellite retrieved PWV data are validated with column integrated PWV estimates from a network of ground based Global Navigation Satellite System (GNSS) over Indian subcontinent. The PWV retrieved by INSAT-3D sounder platform is very promising, being in a good agreement with the GNSS data recorded over India for the period June, 2017 to May, 2018. The root-mean-square (rms) differences of 5.4 to 7.1 mm, bias of -4.7 to +2.1 mm and correlations coefficient of 0.79 to 0.92 was observed between INSAT-3D and GNSS PWV. The correlations coefficient between GPS Sonde and GNSS derived PWV ranges from 0.85 to 0.98.

2018 ◽  
Author(s):  
Qingzhi Zhao ◽  
Yibin Yao ◽  
Wanqiang Yao

Abstract. Apart from the well-known applications like positioning, navigation and timing (PNT), Global Navigation Satellite System (GNSS) has manifested its ability in many other areas that are vital to society largely. With the dense setting of the regional continuously operating reference station (CORS) networks, monitoring the variations in atmospheric water vapour using a GNSS technique has become the focus in the field of GNSS meteorology. Most previous studies mainly concentrate on the analysis of relationship between the two-dimensional (2-d) Precipitable Water Vapour (PWV) and rainfall while the four-dimensional (4-d) variations of atmospheric water vapour derived from the GNSS tomographic technique during rainfall events are rarely discussed. This becomes the focus of this work, which investigates the emerging field of GNSS technology for monitoring changes in atmospheric water vapour during rainfall, especially in the vertical direction. This paper includes an analysis of both 2-d, and 4-d, precipitable water vapour profiles. A period with heavy rainfall events in this study was selected to capture the signature of atmospheric water vapour variation using the ground-based GNSS tomographic technique. GNSS observations from the CORS network of Hong Kong were used. Analysed results of the 2-d PWV/4-d water vapour profiles change during the arrival, occurrence, and depression of heavy rainfall show that: (i) the PWV time series shows an increasing trend before the arrival of heavy rainfall and decreases to its average value after the depression of rainfall; (ii) rainfall leads to an anomalous variation in relative humidity and temperature while their trends are totally opposite and show daily periodicity for periods without rain (this is highly correlated with the changes in solar radiation); (iii) atmospheric water vapour presents unstable conditions with intense vertical convective motion and hydrometeors are formed before the arrival of rainfall while returning to relatively stable conditions during heavy rainfall. This study indicates the potential for using GNSS-derived 2-d PWV and 4-d profiles to monitor spatio-temporal variations in atmospheric water vapour during rainfall, which provides a better understanding of the mechanism of convection and rainfall induced by the extreme weather events.


2013 ◽  
Vol 6 (10) ◽  
pp. 2593-2605 ◽  
Author(s):  
T. Wagner ◽  
S. Beirle ◽  
H. Sihler ◽  
K. Mies

Abstract. We present a new algorithm for satellite retrievals of the atmospheric water vapour column in the blue spectral range. The water vapour absorption cross section in the blue spectral range is much weaker than in the red spectral range. Thus the detection limit and the uncertainty of individual observations are systematically larger than for retrievals at longer wavelengths. Nevertheless, water vapour retrievals in the blue spectral range have also several advantages: since the surface albedo in the blue spectral range is similar over land and ocean, water vapour retrievals are more consistent than for longer wavelengths. Compared to retrievals at longer wavelengths, the sensitivity for atmospheric layers close to the surface is higher due to the (typically 2 to 3 times) higher ocean albedo in the blue. Water vapour retrievals in the blue spectral range are also possible for satellite sensors, which do not measure at longer wavelengths of the visible spectral range like the Ozone Monitoring Instrument (OMI). We investigated details of the water vapour retrieval in the blue spectral range based on radiative transfer simulations and observations from the Global Ozone Monitoring Experiment 2 (GOME-2) and OMI. It is demonstrated that it is possible to retrieve the atmospheric water vapour column density in the blue spectral range over most parts of the globe. The findings of our study are of importance also for future satellite missions (e.g. Sentinel 4 and 5).


MAUSAM ◽  
2022 ◽  
Vol 44 (3) ◽  
pp. 243-248
Author(s):  
K. NIRANJAN ◽  
Y. RAMESH BABU

Integrated atmospheric water vapour content. has been evaluated from the spectral optical depths around the PaT band of water vapour by making directly transmitted solar flux measurements at 800, 935 and 1025 nm. The temporal variation of the total precipitable water vapour shows significant seasonal variation with maximum during~ pre-monsoon and monsoon months and minimum during winter months. The integrated content shows a positive correlation with surface humidity parameters and the correlation is better during monsoon months compared to other seasons. The experimentally derived variations of water vapour are compared with the model variations formulated using radiosonde data. The aerosol extinctions derived from the, multi-spectral solar flux measurements in the visible and near IR regions increase with increasing atmospheric water vapour and this increase shows .a seasonal dependence the surface temperature also seems to affect the, aerosol extinction probably through Its effect on the mixing heights.


2018 ◽  
Vol 11 (11) ◽  
pp. 6003-6012 ◽  
Author(s):  
Shailesh Parihar ◽  
Ashim Kumar Mitra ◽  
Mrutyunjay Mohapatra ◽  
Rajjev Bhatla

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.


MAUSAM ◽  
2021 ◽  
Vol 62 (3) ◽  
pp. 441-448
Author(s):  
K.E. GANESH ◽  
T.K. UMESH ◽  
B. NARASIMHAMURTHY

Atmospheric measurements in a continental, low latitude station Mysore (12.3° N) has been carried out, for the period December 2003 to June 2006. Measurements were made using a sunphotometer with five bands in the visible and near-infrared range of the solar spectrum. To bring out the wavelength dependence of Aerosol Optical Thickness (AOT) on atmospheric water vapour, typically two wavelength channels are being used, one at 500 nm and the other at 1020 nm. A linear dependence between AOT and water vapour on meteorologically calm days is the important observation made. Growth rate of AOT is found to be larger at shorter wavelength (500 nm) than that of the longer wavelength (1020 nm). A mass-plot representation is followed on monthly basis, which is nothing but the graphical plot of spectral AOT versus water vapour of the scans for all the clear sky days of a particular month. Further investigations reveal that some months exhibit a single trend of growth of AOT with water vapour whereas double trend is the scenario for other months. These results provide insight into the changes in the atmospheric aerosol characteristics with precipitable water vapour, which is the subject matter of this paper.


2021 ◽  
Vol 13 (23) ◽  
pp. 4871
Author(s):  
Monia Negusini ◽  
Boyan H. Petkov ◽  
Vincenza Tornatore ◽  
Stefano Barindelli ◽  
Leonardo Martelli ◽  
...  

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.


MAUSAM ◽  
2021 ◽  
Vol 61 (2) ◽  
pp. 197-202
Author(s):  
J. K. S. YADAV ◽  
R. K. GIRI ◽  
D. K. MALIK

Global Positioning System (GPS) estimates the total delay in zenith direction by the propagation delay of the neutral atmosphere in presence of water vapour present in the troposphere. This total delay has been treated as a nuisance parameter for many years by the geodesists. The above delay have two parts dry delay and wet delay and known as Zenith Hydrostatic Delay (ZHD) and Zenith Wet Delay (ZWD) respectively. The Integrated Precipitable Water Vapour (IPWV) is estimated through ZWD overlying the receiver at ground-based station. The accuracy of the above said estimates depends on the quality of the predicted satellite orbits, which are not the same for each individual satellite. India Meteorological Department (IMD) is operationally estimating the IPWV on near real time basis at five places and matches fairly well (error ~6.7 mm) with Radisonde (RS) data. This paper examine the effect of International GPS Service (IGS) predicted precise orbits and near real time predicted rapid or broadcast orbits supplied by the Scripps Orbit and Permanent Array Center (SOPAC) on Zenith Total Delay (ZTD) and IPWV estimates by calculating the mean Bias and Root Mean Square Error (RMSE) for ZTD and IPWV in mm for all the five stations. The observed bias for ZTD is almost of the order of less than 1 mm in most cases and RMSE is less than 6 mm. Similarly the bias observed in the case of derived IPWV is almost negligible and RMSE is less than 1 mm.


2021 ◽  
Author(s):  
Eshetu Erkihune ◽  
Addisu Hunegnaw ◽  
Felix Norman Teferle

<p>As one of the most important components of the global hydrologic cycle, atmospheric water vapor shows significant variability in both space and time over a large range of scales. This variability results from the interactions of many different factors, including topography and the presence of specific atmospheric processes. One of the key regions for affecting global climatic variations lies in the sub-Antarctic zone over the Southern Ocean with its Antarctic Circumpolar Current and the associated Antarctic Convergence. There, in this cold and maritime region, lies South Georgia Island with its weather and climate being largely affected by both the dominating ocean currents and the westerly winds in this zone. While the island forms an important outpost for various surface observations in this largely under sampled and extremely remote region, it also forms a barrier for these winds due to its high topography. This, in turn, leads to various local meteorological phenomena, such as warm Foehn winds, which have a significant impact on the near-surface meteorology and contribute to the accelerated glacier retreat observed for the northeast of the island.</p><p>Surface meteorological data have been available for several stations near King Edward Point (KEP) in South Georgia for much of the 20<sup>th</sup> century. Since 2013 and 2014, Global Navigation Satellite System (GNSS) data have been available at five locations around the periphery of the island. In this study, we investigate the consistency between the different surface meteorological data sets and along with GNSS Precipitable Water Vapour we use these to analyse historic Foehn events.</p><p> </p>


2005 ◽  
Vol 67 (6) ◽  
pp. 623-635 ◽  
Author(s):  
Sridevi Jade ◽  
M.S.M. Vijayan ◽  
V.K. Gaur ◽  
Tushar P. Prabhu ◽  
S.C. Sahu

2021 ◽  
Author(s):  
Ramashray Yadav ◽  
Ram Kumar Giri ◽  
Virendra Singh

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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