Sensing atmospheric water vapor with the global positioning system

1993 ◽  
Vol 20 (23) ◽  
pp. 2631-2634 ◽  
Author(s):  
Christian Rocken ◽  
Randolph Ware ◽  
Teresa Van Hove ◽  
Fredrick Solheim ◽  
Chris Alber ◽  
...  
Keyword(s):  
Water Vapor ◽  
Global Positioning System ◽  
Atmospheric Water Vapor ◽  
Positioning System ◽  
Atmospheric Water ◽  
Global Positioning

GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system

1992 ◽  
Vol 97 (D14) ◽  
pp. 15787 ◽  
Author(s):  
Michael Bevis ◽  
Steven Businger ◽  
Thomas A. Herring ◽  
Christian Rocken ◽  
Richard A. Anthes ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Global Positioning System ◽  
Atmospheric Water Vapor ◽  
Positioning System ◽  
Atmospheric Water ◽  
Gps Meteorology ◽  
Global Positioning

Pointed water vapor radiometer corrections for accurate global positioning system surveying

1993 ◽  
Vol 20 (23) ◽  
pp. 2635-2638 ◽  
Author(s):  
Randolph Ware ◽  
Christian Rocken ◽  
Fredrick Solheim ◽  
Teresa Van Hove ◽  
Chris Alber ◽  
...  
Keyword(s):  
Water Vapor ◽  
Global Positioning System ◽  
Positioning System ◽  
Global Positioning ◽  
Water Vapor Radiometer

scholarly journals Altitude misestimation caused by the Vaisala RS80 pressure bias and its impact on meteorological profiles

2015 ◽  
Vol 8 (10) ◽  
pp. 4043-4054 ◽  
Author(s):  
Y. Inai ◽  
M. Shiotani ◽  
M. Fujiwara ◽  
F. Hasebe ◽  
H. Vömel
Keyword(s):  
Climate Change ◽  
Water Vapor ◽  
Global Positioning System ◽  
Pressure Sensor ◽  
Vertical Gradient ◽  
Equatorial Region ◽  
Positioning System ◽  
Global Positioning ◽  
Using Data ◽  
Height Data

Abstract. Previous research has found that conventional radiosondes equipped with a traditional pressure sensor can be subject to a pressure bias, particularly in the stratosphere. This study examines this pressure bias and the resulting altitude misestimation, and its impact on temperature, ozone, and water vapor profiles is considered using data obtained between December 2003 and January 2010 during the Soundings of Ozone and Water in the Equatorial Region (SOWER) campaigns. The payload consisted of a radiosonde (Vaisala RS80), ozone and water vapor sondes, and a global positioning system (GPS) sensor. More than 30 soundings are used in this study. As GPS height data are thought to be highly accurate, they can be used to calculate pressure. The RS80 pressure bias in the tropical stratosphere is estimated to be −0.4 ± 0.2 hPa (1σ) between 20 and 30 km. As this pressure bias is negative throughout the stratosphere, it leads to systematic overestimation of geopotential height by 43 ± 23, 110 ± 40, and 240 ± 92 m (1σ) at 20, 25, and 30 km, respectively when it is calculated by using the hypsometric equation. Because of the altitude overestimation, we see some offsets in observation parameters having a vertical gradient such as temperature, ozone, and water vapor. Those offsets in the meteorological soundings obtained using the RS80 may have generated an artificial trend in the meteorological records when radiosondes were changed from the RS80, which had no GPS unit, to the new ones with a GPS unit. Therefore, it is important to take those offsets into account in climate change studies.

scholarly journals Column water vapor determination in night period with a lunar photometer prototype

2013 ◽  
Vol 6 (1) ◽  
pp. 767-793
Author(s):  
A. Barreto ◽  
E. Cuevas ◽  
B. Damiri ◽  
P. M. Romero ◽  
F. Almansa
Keyword(s):  
Water Vapor ◽  
Comparative Study ◽  
Global Positioning System ◽  
High Mountain ◽  
Positioning System ◽  
Gps Receiver ◽  
Preliminary Results ◽  
Global Positioning ◽  
Lc Filter ◽  
Night Period

Abstract. In this paper we present the preliminary results of atmospheric column integrated water vapor (PWV) obtained with a new Lunar Cimel photometer (LC) at the high mountain Izaña Observatory in the period July–August, 2011. We have compared nocturnal PWV from LC with PWV from a Global Positioning System (GPS) receiver and nighttime radiosondes (RS92). LC data have been calibrated using the Lunar Langley Method (LLM). We complemented this comparative study using quasi-simultaneous daytime PWV from Cimel AERONET (CA), GPS and RS92. Comparison of daytime PWV from CA shows differences against GPS and RS92 up to 0.18 cm. Two different filters, with and approximate bandwidth of 10 nm and central wavelengths at 938 nm (Filter#1) and 937 nm (Filter#2), were mounted into the LC. Filter#1 is currently used in operational AERONET sunphotometers. PWV obtained with LC-Filter#1 showed an overestimation above 0.18 and 0.25 cm compared to GPS and RS92, respectively, meanwhile Filter#2, with a reduced out-of-band radiation, showed very low differences compared with the same references (≤0.03 cm). These results demonstrate the ability of the new lunar photometer to obtain accurate and continuous PWV measurements at night in addition to the notably influence of the filter's transmissivity response on PWV determination at nighttime. The use of enhanced bandpass filters in lunar photometry, which is affected by more important inaccuracies than sun-photometry, is necessary to infer PWV with similar precision than AERONET.

Variations of the Precipitation Water Vapor by Using GPS Data Triggered Raining in the Summer of Thailand

2015 ◽  
Vol 804 ◽  
pp. 279-282
Author(s):  
Nithiwatthn Choosakul
Keyword(s):  
Water Vapor ◽  
Global Positioning System ◽  
Gps Data ◽  
Positioning System ◽  
Global Positioning ◽  
Precipitation Water ◽  
High Level

The variation of water vapor can be detected from the Global Positioning System (GPS) data. The GPS signal was delayed when propagated through the wet atmosphere. The delayed signal can be retrieved into Precipitation Water Vapor (PWV) data. The GPS data of CUSV station from 2009 to 2012 were used in this research. The results showed that the PWV varied during the summer of Thailand. The PWV were slightly increased from 20 mm at the beginning of the season to 40 mm at the end of season. The increased PWV data were shown as linear line. A slope of the linear line may relate with the amount of the cumulative rain in the season. The steeper line might relate to the great number of raining in the end of the season, otherwise, the fairly gradual line might relate to the raining at any time in the season. The high level of PWV up to around 33 mm could induce the rain in the summer of Thailand.

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