scholarly journals Trends in the atmospheric water vapour estimated from GPS data for different elevation cutoff angles

2018 ◽  
Author(s):  
Tong Ning ◽  
Gunnar Elgered
Keyword(s):  
Water Vapour ◽  
Elevation Angle ◽  
Radiosonde Data ◽  
Dependent Data ◽  
Gps Data ◽  
Mapping Functions ◽  
Ionospheric Effects ◽  
Data Weighting ◽  
Integrated Water Vapour ◽  
Gps Data Processing

Abstract. We have processed 20 years of GPS data from 8 sites in Sweden and 5 sites in Finland, using two different elevation cutoff angles 10° and 25°, to estimate the atmospheric integrated water vapour (IWV). We have also tested three additional elevation-angle-dependent parameters in the GPS data processing, i.e., (1) two different mapping functions, (2) with or without second order corrections for ionospheric effects, and (3) with or without elevation dependent data weighting. The results show that all these three parameters have insignificant impacts on the resulting linear IWV trends. We compared the GPS-derived IWV trends to the corresponding trends from radiosonde data at 7 nearby (

scholarly journals Validation of two independent retrievals of SCIAMACHY water vapour columns using radiosonde data

2013 ◽  
Vol 6 (1) ◽  
pp. 665-702 ◽  
Author(s):  
A. du Piesanie ◽  
A. J. M. Piters ◽  
I. Aben ◽  
H. Schrijver ◽  
P. Wang ◽  
...  
Keyword(s):  
Water Vapour ◽  
Correction Method ◽  
Short Wave ◽  
Mean Difference ◽  
Likelihood Method ◽  
Radiosonde Data ◽  
Retrieval Algorithm ◽  
Infrared Wavelength ◽  
Integrated Water Vapour ◽  
Iterative Maximum Likelihood

Abstract. Two independently derived SCIAMACHY total water vapour column (WVC) products are compared with integrated water vapour data calculated from radiosonde measurements, and with each other. The two SCIAMACHY WVC products are retrieved with two different retrieval algorithms applied in the visible and short wave infrared wavelength regions respectively. The first SCIAMACHY WVC product used in the comparison is ESA's level 2 version 5.01 WVC product derived with the Air Mass Corrected Differential Absorption Spectroscopy (AMC-DOAS) retrieval algorithm (SCIAMACHY-ESA). The second SCIAMACHY WVC product is derived using the Iterative Maximum Likelihood Method (IMLM) developed by Netherlands Institute for Space Research (SCIAMACHY-IMLM). Both SCIAMACHY WVC products are compared with collocated water vapour amounts determined from daily relative humidity radiosonde measurements obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) radiosonde network, over an 18 month and 2 yr period respectively. Results indicate a good agreement between the WVC amounts of SCIAMACHY-ESA and the radiosonde, and a mean difference of 0.03 g cm−2 is found for cloud free conditions. Overall the SCIAMACHY-ESA WVC amounts are smaller than the radiosonde WVC amounts, especially over oceans. For cloudy conditions the WVC bias has a clear dependence on the cloud top height and increases with increasing cloud top heights larger than approximately 2 km. A likely cause for this could be the different vertical profile shapes of water vapour and O2 leading to different relative changes in their optical thickness, which makes the AMF correction method used in the algorithm less suitable for high clouds. The SCIAMACHY-IMLM WVC amounts compare well to the radiosonde WVC amounts during cloud free conditions over land. A mean difference of 0.08 g cm−2 is found which is consistent with previous results when comparing daily averaged SCIAMACHY-IMLM WVC amounts with ECMWF model data globally. Furthermore, we show that the measurements for cloudy conditions (cloud fraction ≥ 0.5) with low clouds (cloud pressure ≥ 930 hPa) above the ocean and land compare quite well with radiosonde data.

scholarly journals Integrated water vapour from GPS

MAUSAM ◽  
2021 ◽  
Vol 58 (1) ◽  
pp. 101-106
Author(s):  
R. K. GIRI ◽  
L. R. MEENA ◽  
S. S. BHANDARI ◽  
R. C. BHATIA
Keyword(s):  
Water Vapour ◽  
Global Climate ◽  
Spatial Scales ◽  
Limited Area ◽  
Gps Data ◽  
Massachusetts Institute Of Technology ◽  
Stochastic Filtering ◽  
Wide Range ◽  
Integrated Water Vapour ◽  
Institute Of Technology

Water vapour is highly variable in space and time, and plays a large role in atmospheric processes that act over a wide range of temporal and spatial scales on global climate to micrometeorology. This paper deals with a new approach to remotely sense the water vapour based on the Global Position System (GPS). The signal propagating from GPS satellites to ground based receivers is delayed by atmospheric water vapour. The delay is parameterized in terms of time varying Zenith-Wet Delay (ZWD), which is retrieved by stochastic filtering of GPS data. With the help of surface pressure and temperature readings at the GPS receiver, the retrieved ZWD can be transformed into Integrated Water Vapour (IWV) overlying at the receiver with little additional uncertainties. In this study the Zenith Total time Delay (ZTD) data without met package is retrieved using the GAMIT (King and Bock, 1997) GPS data processing software developed by Massachusetts Institute of Technology (MIT) for the period of January 2003 to February 2003 for two stations New Delhi and Bangalore .The IWV retrieved from GPS and its comparison with Limited Area Model (LAM) retrieved IWV shows fairly good agreement.

scholarly journals Effects of Tropospheric Mapping Functions on GPS Data Processing

2010 ◽  
Vol 27 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Ji-Hye Won ◽  
Kwan-Dong Park ◽  
Ji-Hyun Ha ◽  
Jung-Ho Cho
Keyword(s):  
Data Processing ◽  
Gps Data ◽  
Mapping Functions ◽  
Gps Data Processing

scholarly journals Assessment of the Accuracy of the Saastamoinen Model and VMF1/VMF3 Mapping Functions with Respect to Ray-Tracing from Radiosonde Data in the Framework of GNSS Meteorology

2020 ◽  
Vol 12 (20) ◽  
pp. 3337
Author(s):  
Peng Feng ◽  
Fei Li ◽  
Jianguo Yan ◽  
Fangzhao Zhang ◽  
Jean-Pierre Barriot
Keyword(s):  
Ray Tracing ◽  
Elevation Angle ◽  
Mapping Function ◽  
Satellite System ◽  
Radiosonde Data ◽  
Mapping Functions ◽  
Gnss Meteorology ◽  
Rms Error ◽  
Zenith Hydrostatic Delay ◽  
Global Navigation Satellite

In this paper, we assess, in the framework of Global Navigation Satellite System (GNSS) meteorology, the accuracy of GNSS propagation delays corresponding to the Saastamoinen zenith hydrostatic delay (ZHD) model and the Vienna Mapping function VMF1/VMF3 (hydrostatic and wet), with reference to radiosonde ray-tracing delays over a three-year period on 28 globally distributed sites. The results show that the Saastamoinen ZHD estimates have a mean root mean square (RMS) error of 1.7 mm with respect to the radiosonde. We also detected some seasonal signatures in these Saastamoinen ZHD estimates. This indicates that the Saastamoinen model, based on the hydrostatic assumption and the ground pressure, is insufficient to capture the full variability of the ZHD estimates over time with the accuracy needed for GNSS meteorology. Furthermore, we found that VMF3 slant hydrostatic delay (SHD) estimates outperform the corresponding VMF1 SHD estimates (equivalent SHD RMS error of 4.8 mm for VMF3 versus 7.1 mm for VMF1 at 5° elevation angle), with respect to the radiosonde SHD estimates. Unexpectedly, the situation is opposite for the VMF3 slant wet delay (SWD) estimates compared to VMF1 SWD estimates (equivalent SWD RMS error of 11.4 mm for VMF3 versus 7.0 mm for VMF1 at 5° elevation angle). Our general conclusion is that the joint approach using ZHD models and mapping functions must be revisited, at least in the framework of GNSS meteorology.

Monitoring of Integrated Water Vapour from ground-based GPS observations and their assimilation in a limited-area NWP model

2002 ◽  
Vol 27 (4-5) ◽  
pp. 341-346 ◽  
Author(s):  
M. Tomassini ◽  
G. Gendt ◽  
G. Dick ◽  
M. Ramatschi ◽  
C. Schraff
Keyword(s):  
Water Vapour ◽  
Limited Area ◽  
Integrated Water Vapour ◽  
Nwp Model ◽  
Gps Observations

scholarly journals Tropospheric water vapour and relative humidity profiles from lidar and microwave radiometry

2014 ◽  
Vol 7 (5) ◽  
pp. 1201-1211 ◽  
Author(s):  
F. Navas-Guzmán ◽  
J. Fernández-Gálvez ◽  
M. J. Granados-Muñoz ◽  
J. L. Guerrero-Rascado ◽  
J. A. Bravo-Aranda ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Water Vapour ◽  
Microwave Radiometer ◽  
Radiosonde Data ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Night Time ◽  
New Approach ◽  
Lidar Measurements ◽  
Humidity Profiles

Abstract. In this paper, we outline an iterative method to calibrate the water vapour mixing ratio profiles retrieved from Raman lidar measurements. Simultaneous and co-located radiosonde data are used for this purpose and the calibration results obtained during a radiosonde campaign in summer and autumn 2011 are presented. The water vapour profiles measured during night-time by the Raman lidar and radiosondes are compared and the differences between the methodologies are discussed. Then, a new approach to obtain relative humidity profiles by combination of simultaneous profiles of temperature (retrieved from a microwave radiometer) and water vapour mixing ratio (from a Raman lidar) is addressed. In the last part of this work, a statistical analysis of water vapour mixing ratio and relative humidity profiles obtained during 1 year of simultaneous measurements is presented.

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 Evaluation of Wet Mapping Functions Used in Modeling Tropospheric Propagation Delay Effect on GPS Measurements

2017 ◽  
Vol 11 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Sobhy Abdel-Monam Younes
Keyword(s):  
A Priori ◽  
Mapping Function ◽  
Propagation Delay ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
Delay Effect ◽  
Gps Measurements ◽  
Mapping Functions ◽  
Significant Bias ◽  
Mapping Techniques

Background:The author compares several methods to map the a priori wet tropospheric delay of GNSS signals in Egypt from the zenith direction to lower elevations.Methods and Materials:The author compared the following mapping techniques against ray-traced delays computed for radiosonde profiles under the assumption of spherical symmetry: Saastamoinen, Hopfield, Black, Chao, Ifadis, Herring, Niell, Moffett, Black and Eisner and UNBabc mapping functions. Radiosonde data were computed from radiosonde stations at the Egyptian stations; in the south of Egypt, near the Mediterranean Sea, and near the Red Sea over a period of 5 years (2000-2005), most of the stations launched radiosonde twice daily, every day of the year. Moreover, data is received from the Egyptian Meteorology Authority.Results and Conclusion:The results indicate that currently, the saastamoinen mapping function should be used for all geodetic applications in Egypt, and if necessary, the Chao and Moffett mapping functions can serve as an acceptable replacement without introducing a significant bias into the station position.

scholarly journals WATER VAPOUR WEIGHTED MEAN TEMPERATURE MODEL FOR GPS-DERIVED INTEGRATED WATER VAPOUR IN PENINSULAR MALAYSIA

2017 ◽  
Vol XLII-4/W5 ◽  
pp. 127-135 ◽  
Author(s):  
T. A. Musa ◽  
M. H. Mazlan ◽  
Y. D. Opaluwa ◽  
I. A. Musliman ◽  
Z. M. Radzi
Keyword(s):  
Water Vapour ◽  
Diurnal Cycle ◽  
Specific Model ◽  
Regional Model ◽  
Peninsular Malaysia ◽  
Site Specific ◽  
Weighted Mean Temperature ◽  
Integrated Water Vapour ◽  
Relationship Of ◽  
The Impact

This paper presents the development of T<sub>M</sub> model by using the radiosonde stations from Peninsular Malaysia. Two types of T<sub>M</sub> model were developed; site-specific and regional models. The result revealed that the estimation from site-specific model has small improvement compared to the regional model, indicating that the regional model is adequately to use in estimation of GPS-derived IWV over Peninsular Malaysia. Meanwhile, this study found that the diurnal cycle of T<sub>S</sub> has influenced the T<sub>M</sub>&amp;ndash;T<sub>S</sub> relationship. The separation between daytime and nighttime observation can improve the relationship of T<sub>M</sub>&amp;ndash;T<sub>S</sub>. However, the impact of diurnal cycle to IWV estimation is less than 1&amp;thinsp;%. The T<sub>M</sub> model from Global and Tropic also been evaluated. The Tropic T<sub>M</sub> model is superior to be utilized as compared to the Global T<sub>M</sub> model.

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