The atmospheric water vapor retrieved by OH(8-3) band airglow from astronomical observations

2020 ◽  
Author(s):  
Weijun Liu ◽  
Jiyao Xu ◽  
Jianchun Bian ◽  
Xiao Liu ◽  
Wei Yuan ◽  
...  
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Emission Spectra ◽  
Precipitable Water ◽  
Line Of Sight ◽  
Regression Result ◽  
Absorption Cross ◽  
Standard Star ◽  
Astronomical Observations ◽  
Effective Absorption

<p>Water vapor in the atmosphere is an important trace gas, and seriously affects the ground-based astronomical observations due to water vapor attenuation and emission. It is significant to correct the effects of water vapor along the line-of-sight of astronomical target in real time. Here, we discuss a method to retrieve the precipitable water vapor (PWV) from the OH(8-3) band airglow spectrum. The pressure, temperature and water vapor profiles determine the effective absorption cross-section in PWV retrieval, so a simple and effective method of the effective absorption cross-sections using profiles from a standard atmosphere model is discussed. The Monte Carlo simulations are used to estimate the PWV retrieval. Besides, the PWV is calculated using the sky nightglows from UVES and is compared to that from the standard star spectra of UVES observed from 2000 to 2016. The results indicate that The PWV derived from OH(8-3) spectra is in good agreement with that retrieved from UVES standard star equivalent width and the averaged difference between the two is 0.66 mm. The regression result indicates that the slope α=1.06 +/-0.03 and the correlation coefficient is r=0.87. Because the sky emission spectra and the astronomical target are observed at the same time and along the same line-of-sight, the method of PWV retrieved by OH(8-3) band spectra provides a quick and economical means of correcting the effects if water vapor on ground-based astronomical observations locally, in real-time, and along the line-of-sight of astronomical observations.</p>

scholarly journals Method for retrieval of atmospheric water vapor using OH airglow for correction of astronomical observations

2020 ◽  
Vol 639 ◽  
pp. A29
Author(s):  
J. Y. Xu ◽  
W. J. Liu ◽  
J. C. Bian ◽  
X. Liu ◽  
W. Yuan ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Water Vapor ◽  
Real Time ◽  
Precipitable Water ◽  
Temporal Variations ◽  
Astronomical Observation ◽  
Line Of Sight ◽  
Infrared Band ◽  
Retrieval Method ◽  
Astronomical Observations

Context. Water vapor in the atmosphere undergoes quick spatial and temporal variations. This has a serious impact on ground-based astronomical observations from the visible band to the infrared band resulting from water vapor attenuation and emission. Aims. We seek to show how the sky spectrum of an astronomical observation can be used to determine the amount of precipitable water vapor (PWV) along the line of sight toward the science target. Methods. In this work, we discuss a method to retrieve the PWV from the OH(8-3) band airglow spectrum. We analyzed the influences of the pressure and temperature of the atmosphere and the different water vapor vertical distributions on the PWV retrieval method in detail. Meanwhile, the accuracy of the method was analyzed via Monte Carlo simulations. To further verify the method of PWV retrieval, we carried out cross comparisons between the PWV retrieved from OH airglow and PWV from the standard star spectra of UVES using equivalent widths of telluric absorption lines observed from 2000 to 2016 at Cerro Paranal in Chile. Results. The Monte Carlo tests and the comparison between the two different methods prove the availability the PWV retrieval method from OH airglow. These results show that using OH airglow spectra in astronomical observations, PWVs along the same line of sight as the astronomical observations can be retrieved in real time. Conclusions. We provide a quick and economical method for retrieving the water vapor along the same line of sight of astronomical observation in the real time. This is especially helpful to correcting the effect of water vapor on astronomical observations.

scholarly journals HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Real Time ◽  
Prediction Models ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
International Gnss Service ◽  
Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

scholarly journals PROCESSING STRATEGY FOR NEAR REAL TIME GPS PRECIPITABLE WATER VAPOR RETRIEVAL

2007 ◽  
Vol 24 (4) ◽  
pp. 275-284
Author(s):  
Jeong-Ho Baek ◽  
Jae-Won Lee ◽  
Byung-Kyu Choi ◽  
Jung-Ho Cho
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Processing Strategy

scholarly journals Real-Time Sensing of Precipitable Water Vapor From BeiDou Observations: Hong Kong and CMONOC Networks

2018 ◽  
Author(s):  
Xingxing Li ◽  
Han Tan ◽  
Xin Li ◽  
Galina Dick ◽  
Jens Wickert ◽  
...  
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Real Time ◽  
Precipitable Water ◽  
Precipitable Water Vapor

Real-time retrieval of precipitable water vapor from GPS and BeiDou observations

2015 ◽  
Vol 89 (9) ◽  
pp. 843-856 ◽  
Author(s):  
Cuixian Lu ◽  
Xingxing Li ◽  
Tobias Nilsson ◽  
Tong Ning ◽  
Robert Heinkelmann ◽  
...  
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Precipitable Water ◽  
Precipitable Water Vapor

Monitoring precipitable water vapor in real-time using global navigation satellite systems

2013 ◽  
Vol 87 (10-12) ◽  
pp. 923-934 ◽  
Author(s):  
Seung-Woo Lee ◽  
Jan Kouba ◽  
Bob Schutz ◽  
Do Hyeong Kim ◽  
Young Jae Lee
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
Navigation Satellite ◽  
Satellite Systems ◽  
Global Navigation ◽  
Global Navigation Satellite

Real-time retrieval of precipitable water vapor from GPS precise point positioning

2014 ◽  
Vol 119 (16) ◽  
pp. 10044-10057 ◽  
Author(s):  
Yubin Yuan ◽  
Kefei Zhang ◽  
Witold Rohm ◽  
Suelynn Choy ◽  
Robert Norman ◽  
...  
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Precise Point Positioning ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Point Positioning

Real-Time Retrieval of Precipitable Water Vapor From Galileo Observations by Using the MGEX Network

2020 ◽  
Vol 58 (7) ◽  
pp. 4743-4753
Author(s):  
Cuixian Lu ◽  
Guolong Feng ◽  
Yuxin Zheng ◽  
Keke Zhang ◽  
Han Tan ◽  
...  
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Precipitable Water ◽  
Precipitable Water Vapor
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