scholarly journals A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2526 ◽  
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Junbo Shi ◽  
Lv Zhou ◽  
Yi Xu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Absolute Error ◽  
Satellite System ◽  
Observation Data ◽  
Radiosonde Station ◽  
Satellite Signal ◽  
Comparative Results ◽  
Global Navigation Satellite ◽  
Vapor Distribution

Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water vapor distribution using GNSS observation data, plays an increasingly important role in GNSS meteorology. In this paper, a method to improve the distribution of observations in GNSS water vapor tomography is proposed to overcome the problem of the relatively concentrated distribution of observations, enable satellite signal rays to penetrate more tomographic voxels, and improve the issue of overabundance of zero elements in a tomographic matrix. Numerical results indicate that the accuracy of the water vapor tomography is improved by the proposed method when the slant water vapor calculated by GAMIT is used as a reference. Comparative results of precipitable water vapor (PWV) and water vapor density (WVD) profiles from radiosonde station data indicate that the proposed method is superior to the conventional method in terms of the mean absolute error (MAE), standard deviations (STD), and root-mean-square error (RMS). Further discussion shows that the ill-condition of tomographic equation and the richness of data in the tomographic model need to be discussed separately.

scholarly journals Error Evaluation of L-Band InSAR Precipitable Water Vapor Measurements by Comparison with GNSS Observations in Japan

2021 ◽  
Vol 13 (23) ◽  
pp. 4866
Author(s):  
Keita Matsuzawa ◽  
Yohei Kinoshita
Keyword(s):  
Water Vapor ◽  
Ionospheric Disturbance ◽  
Precipitable Water ◽  
Absolute Error ◽  
Satellite System ◽  
Precipitable Water Vapor ◽  
Error Level ◽  
Atmospheric Observations ◽  
L Band ◽  
Global Navigation Satellite

Interferometric synthetic aperture radar (InSAR) enables us to obtain precipitable water vapor (PWV) maps with high spatial resolution through the phase difference caused by refraction in the atmosphere. Although previous studies have evaluated the error level of InSARPWV observations, they validated it only with C-band InSARPWV observations. Since ionospheric disturbance seriously contaminates the InSAR phase in the case of the lower-frequency SAR system, it is necessary for a PWV error level evaluation correcting the ionospheric effect appropriately if we use lower-frequency SAR systems, such as the Advanced Land Observing Satellite-2 (ALOS-2). In this paper, we evaluated the error level of the L-band InSARPWV observation obtained from ALOS-2 data covering four areas in Japan. We compared the InSAR observations with global navigation satellite system (GNSS) atmospheric observations and estimated the L-band InSARPWV error value by utilizing the error propagation theory. As a result, the L-band InSARPWV absolute error reached 2.83 mm, which was comparable to traditional PWV observations. Moreover, we investigated the impacts of the seasonality, the interferometric coherence, and the height dependence on the PWV observation accuracy in InSAR.

scholarly journals Water Vapor Retrievals from Spectral Direct Irradiance Measured with an EKO MS-711 Spectroradiometer—Intercomparison with Other Techniques

2021 ◽  
Vol 13 (3) ◽  
pp. 350
Author(s):  
Rosa Delia García ◽  
Emilio Cuevas ◽  
Victoria Eugenia Cachorro ◽  
Omaira E. García ◽  
África Barreto ◽  
...  
Keyword(s):  
Water Vapor ◽  
Power Plants ◽  
Precipitable Water ◽  
Satellite System ◽  
Infrared Spectrometry ◽  
Radiative Balance ◽  
Direct Normal Irradiance ◽  
Routine Basis ◽  
Solar Power Plants ◽  
Global Navigation Satellite

Precipitable water vapor retrievals are of major importance for assessing and understanding atmospheric radiative balance and solar radiation resources. On that basis, this study presents the first PWV values measured with a novel EKO MS-711 grating spectroradiometer from direct normal irradiance in the spectral range between 930 and 960 nm at the Izaña Observatory (IZO, Spain) between April and December 2019. The expanded uncertainty of PWV (UPWV) was theoretically evaluated using the Monte-Carlo method, obtaining an averaged value of 0.37 ± 0.11 mm. The estimated uncertainty presents a clear dependence on PWV. For PWV ≤ 5 mm (62% of the data), the mean UPWV is 0.31 ± 0.07 mm, while for PWV > 5 mm (38% of the data) is 0.47 ± 0.08 mm. In addition, the EKO PWV retrievals were comprehensively compared against the PWV measurements from several reference techniques available at IZO, including meteorological radiosondes, Global Navigation Satellite System (GNSS), CIMEL-AERONET sun photometer and Fourier Transform Infrared spectrometry (FTIR). The EKO PWV values closely align with the above mentioned different techniques, providing a mean bias and standard deviation of −0.30 ± 0.89 mm, 0.02 ± 0.68 mm, −0.57 ± 0.68 mm, and 0.33 ± 0.59 mm, with respect to the RS92, GNSS, FTIR and CIMEL-AERONET, respectively. According to the theoretical analysis, MB decreases when comparing values for PWV > 5 mm, leading to a PWV MB between −0.45 mm (EKO vs. FTIR), and 0.11 mm (EKO vs. CIMEL-AERONET). These results confirm that the EKO MS-711 spectroradiometer is precise enough to provide reliable PWV data on a routine basis and, as a result, can complement existing ground-based PWV observations. The implementation of PWV measurements in a spectroradiometer increases the capabilities of these types of instruments to simultaneously obtain key parameters used in certain applications such as monitoring solar power plants performance.

scholarly journals Estimating trends in atmospheric water vapor and temperature time series over Germany

2017 ◽  
Vol 10 (9) ◽  
pp. 3117-3132 ◽  
Author(s):  
Fadwa Alshawaf ◽  
Kyriakos Balidakis ◽  
Galina Dick ◽  
Stefan Heise ◽  
Jens Wickert
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Time Windows ◽  
Temporal Trends ◽  
Precipitable Water ◽  
Satellite System ◽  
Reanalysis Data ◽  
Mean Value ◽  
Global Navigation Satellite ◽  
Gnss Time Series

Abstract. Ground-based GNSS (Global Navigation Satellite System) has efficiently been used since the 1990s as a meteorological observing system. Recently scientists have used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) data and meteorological measurements. We aim to evaluate climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: (1) estimated from ground-based GNSS observations using the method of precise point positioning, (2) inferred from ERA-Interim reanalysis data, and (3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods: the first applies least squares to deseasonalized time series and the second uses the Theil–Sen estimator. The trends estimated at 113 GNSS sites, with 10 to 19 years temporal coverage, vary between −1.5 and 2.3 mm decade−1 with standard deviations below 0.25 mm decade−1. These results were validated by estimating the trends from ERA-Interim data over the same time windows, which show similar values. These values of the trend depend on the length and the variations of the time series. Therefore, to give a mean value of the PWV trend over Germany, we estimated the trends using ERA-Interim spanning from 1991 to 2016 (26 years) at 227 synoptic stations over Germany. The ERA-Interim data show positive PWV trends of 0.33 ± 0.06 mm decade−1 with standard errors below 0.03 mm decade−1. The increment in PWV varies between 4.5 and 6.5 % per degree Celsius rise in temperature, which is comparable to the theoretical rate of the Clausius–Clapeyron equation.

scholarly journals Multi-year Precipitable Water Vapor Observations in East Manila, Philippines using Radiosonde and Global Navigation Satellite System

2020 ◽  
Vol 199 ◽  
pp. 00002
Author(s):  
Agana Louisse S. Domingo ◽  
Ernest P. Macalalad
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Global Navigation Satellite System ◽  
Precipitable Water ◽  
Satellite System ◽  
Precipitable Water Vapor ◽  
Type I ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Global Navigation Satellite

Precipitable water vapor (PWV) is a parameter that used to describe the water vapor content in the atmosphere has the potential to become a precipitation. Thus, it is important to measure PWV and investigate its trends and variability for potential forecasting precipitation. This study presents the variation of PWV at Tanay Upper Station (14°34’52.8”N, 121°22’08.9”E) from radiosonde operated by the Philippine Atmospheric, Geophysical and Astronomical Services Administration and at PIMO station (14°38’08.5”N, 121°04’39.4”E) using Global Navigation Satellite System (GNSS) operated by NASAJet Propulsion Laboratory under the International GNSS Service (IGS) network from 2015-2017. Moreover, there is no significant difference (p-values < 0.05) among PWV radiosonde, GNSS-PWV and rainfall as a function of year of observation. Monthly mean variation conforms to the Coronas climate classification, Climate Type I, in terms of the amount of precipitation. It is shown that PWV is high during wet months and least during dry months (November to April). Further, monthly mean variation is moderate correlated with surface temperature from radiosonde (R = +0.589). Evaporation rate depends on the surface temperature, which contributes in forming water vapor. The results showed that PWV from radiosonde gave reasonable values to be considered during wet and dry season as well as the seasonal variation of rainfall.

scholarly journals Assimilation of GNSS PWV with NCAR-RTFDDA to Improve Prediction of a Landfall Typhoon

2022 ◽  
Vol 14 (1) ◽  
pp. 178
Author(s):  
Haishen Wang ◽  
Yubao Liu ◽  
Yuewei Liu ◽  
Yunchang Cao ◽  
Hong Liang ◽  
...  
Keyword(s):  
Water Vapor ◽  
Data Assimilation ◽  
Precipitable Water ◽  
Satellite System ◽  
Navigation Satellite ◽  
System A ◽  
Spiral Rainbands ◽  
Global Navigation Satellite ◽  
Four Dimensional Data Assimilation ◽  
The Impact

Precipitable water vapor (PWV) retrieved from ground-based global navigation satellite system (GNSS) stations acquisition signal of a navigation satellite system provides high spatial and temporal resolution atmospheric water vapor. In this paper, an observation-nudging-based real-time four-dimensional data assimilation (RTFDDA) approach was used to assimilate the PWV estimated from GNSS observation into the WRF (Weather Research and Forecasting) modeling system. A landfall typhoon, “Mangkhut”, is chosen to evaluate the impact of GNSS PWV data assimilation on its track, intensity, and precipitation prediction. The results show that RTFDDA can assimilate GNSS PWV data into WRF to improve the water vapor distribution associated with the typhoon. Assimilating the GNSS PWV improved the typhoon track and intensity prediction when and after the typhoon made landfall, correcting a 5–10 hPa overestimation (too deep) of the central pressure of the typhoon at landfall. It also improved the occurrence and the intensity of the major typhoon spiral rainbands.

scholarly journals Validating HY-2A CMR precipitable water vapor using ground-based and shipborne GNSS observations

2020 ◽  
Vol 13 (9) ◽  
pp. 4963-4972
Author(s):  
Zhilu Wu ◽  
Yanxiong Liu ◽  
Yang Liu ◽  
Jungang Wang ◽  
Xiufeng He ◽  
...  
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Satellite System ◽  
Precipitable Water Vapor ◽  
Tropospheric Delay ◽  
High Temporal Resolution ◽  
International Gnss Service ◽  
Global Navigation Satellite ◽  
Gnss Observations

Abstract. The calibration microwave radiometer (CMR) on board the Haiyang-2A (HY-2A) satellite provides wet tropospheric delay correction for altimetry data, which can also contribute to the understanding of climate system and weather processes. The ground-based global navigation satellite system (GNSS) provides precise precipitable water vapor (PWV) with high temporal resolution and could be used for calibration and monitoring of the CMR data, and shipborne GNSS provides accurate PWV over open oceans, which can be directly compared with uncontaminated CMR data. In this study, the HY-2A CMR water vapor product is validated using ground-based GNSS observations of 100 International GNSS Service (IGS) stations along the global coastline and 56 d shipborne GNSS observations over the Indian Ocean. The processing strategy for GNSS data and CMR data is discussed in detail. Special efforts were made in the quality control and reconstruction of contaminated CMR data. The validation result shows that HY-2A CMR PWV agrees well with ground-based GNSS PWV with 2.67 mm as the root mean square (rms) within 100 km. Geographically, the rms is 1.12 mm in the polar region and 2.78 mm elsewhere. The PWV agreement between HY-2A and shipborne GNSS shows a significant correlation with the distance between the ship and the satellite footprint, with an rms of 1.57 mm for the distance threshold of 100 km. Ground-based GNSS and shipborne GNSS agree with HY-2A CMR well.

scholarly journals A New GNSS-Derived Water Vapor Tomography Method Based on Optimized Voxel for Large GNSS Network

2020 ◽  
Vol 12 (14) ◽  
pp. 2306 ◽  
Author(s):  
Yibin Yao ◽  
Chen Liu ◽  
Chaoqian Xu
Keyword(s):  
Water Vapor ◽  
Conventional Method ◽  
Three Dimensional ◽  
Absolute Error ◽  
Satellite System ◽  
Tomographic Method ◽  
Tomography Method ◽  
Gnss Network ◽  
Global Navigation Satellite ◽  
Gnss Networks

The Global Navigation Satellite System (GNSS) tomographic technique can be used for remote sensing of the three-dimensional water vapor (WV) distribution in the troposphere, which has attracted considerable interest. However, a significant problem in this technique is the excessive reliance on constraints (particularly in large GNSS networks). In this paper, we propose an improved tomographic method based on optimized voxel, which only considers the voxels passed by GNSS rays. The proposed method can completely prevent the tomographic algorithm interference of constraints that originated from empirical functions. Experiments in Nanjing in the periods of day-of-year (DOY) 182–184, 2019, and 244–246, 2019, show that the mean absolute error (MAE) and root mean square error (RMSE) of the WV density profile obtained using the proposed method are 0.9 and 1.3 g/m3, while those obtained using the conventional method are 1.3 and 1.8 g/m3, respectively, with respect to the radiosonde (RS) method. The numerical results show that the proposed method is reliable and has a superior accuracy to that of the conventional method.

scholarly journals A method to improve the utilization of GNSS observation for water vapor tomography

2016 ◽  
Vol 34 (1) ◽  
pp. 143-152 ◽  
Author(s):  
Y. B. Yao ◽  
Q. Z. Zhao ◽  
B. Zhang
Keyword(s):  
Water Vapor ◽  
Absolute Error ◽  
Satellite System ◽  
Research Area ◽  
Radiosonde Data ◽  
Gps Data ◽  
Full Potential ◽  
Research Areas ◽  
Global Navigation Satellite ◽  
Areas Of Interest

Abstract. Existing water vapor tomographic methods use Global Navigation Satellite System (GNSS) signals penetrating the entire research area while they do not consider signals passing through its sides. This leads to the decreasing use of observed satellite signals and allows for no signals crossing from the bottom or edge areas especially for those voxels in research areas of interest. Consequently, the accuracy of the tomographic results for the bottom of a research area, and the overall reconstructed accuracy do not reach their full potential. To solve this issue, an approach which uses GPS data with both signals that pass the side and top of a research area is proposed. The advantages of proposed approach include improving the utilization of existing GNSS observations and increasing the number of voxels crossed by satellite signals. One point should be noted that the proposed approach needs the support of radiosonde data inside the tomographic region. A tomographic experiment was implemented using observed GPS data from the Continuously Operating Reference System (CORS) Network of Zhejiang Province, China. The comparison of tomographic results with data from a radiosonde shows that the root mean square error (RMS), bias, mean absolute error (MAE), and standard deviation (SD) of the proposed approach are superior to those of the traditional method.

scholarly journals A Case Study of the 3D Water Vapor Tomography Model Based on a Fast Voxel Traversal Algorithm for Ray Tracing

2021 ◽  
Vol 13 (12) ◽  
pp. 2422
Author(s):  
Heng Hu ◽  
Min Liu ◽  
Jiqin Zhong ◽  
Xin Deng ◽  
Yunchang Cao ◽  
...  
Keyword(s):  
Water Vapor ◽  
Ray Tracing ◽  
Three Dimensional ◽  
Satellite System ◽  
Horizontal Distribution ◽  
Observation Data ◽  
Vapor Density ◽  
Average Deviation ◽  
Global Navigation Satellite ◽  
Traversal Algorithm

A fast voxel traversal algorithm for ray tracing was applied to build a 4 × 4 × 20 tomography model using the observation data of 11 ground-based Global Navigation Satellite System (GNSS) meteorology (GNSS/MET) stations in Hebei Province, China. The precipitation water vapor (PWV) observed at 05 a.m. (Universal Time Coordinated: UTC) on 10 December 2019, was used to reconstruct three-dimensional (3D) water vapor density fields over the test area. The tomographic results (GNSS_T) show that the water vapor density above this area is mainly below 25 g/m3 and is concentrated between the first to the fourth layers. The vertical distribution conforms to the exponential characteristics, while the horizontal distribution shows a decreasing trend from southwest to northeast. In addition, the results of the 0.25° grid dataset generated by the Global Forecast System (GFS) of the National Center for Environmental Forecasting (NCEP) (GFS_L) were interpolated to the height of the tomographic grid, which is in good agreement with the tomographic results. GFS_L is larger than GNSS_T on the first floor at the surface, with an average deviation of 0.19 g/m3. In contrast, GFS_L from the second floor to the top of the model is smaller than GNSS_T, with the average deviations distributed between −0.08 and −0.15 g/m3.

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