scholarly journals A New Method of GPS Water Vapor Tomography for Maximizing the Use of Signal Rays

2019 ◽  
Vol 9 (7) ◽  
pp. 1446 ◽  
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Junbo Shi ◽  
Yinzhi Zhao ◽  
Lv Zhou ◽  
...  
Keyword(s):  
Water Vapor ◽  
Density Profile ◽  
Temporal Distribution ◽  
Precipitable Water ◽  
Absolute Error ◽  
New Method ◽  
Reference Station ◽  
Full Potential ◽  
Vapor Density ◽  
Unknown Parameters

The spatio-temporal distribution of atmospheric water vapor information can be obtained by global positioning system (GPS) water vapor tomography. GPS signal rays pass through the tomographic area from different boundaries because the scope of the research region (latitude, longitude, and altitude) is designated in the process of tomographic modeling, the influence of the geographic distribution of receivers, and the geometric location of satellite constellations. Traditionally, only signal rays penetrating the entire tomographic area are considered in the computation of water vapor information, whereas those passing through the sides are neglected. Therefore, the accuracy of the tomographic result, especially at the bottom of the area, does not reach its full potential. To solve this problem, this paper proposes a new method that simultaneously considers the discretized tomographic voxels and the troposphere outside the research area as unknown parameters. This method can effectively improve the utilization of existing GPS observations and increase the number of voxels crossed by satellite signals, especially by increasing the proportion of voxels penetrated. A tomographic experiment is implemented using GPS data from the Hong Kong Satellite Positioning Reference Station Network. Compared to the traditional method, the proposed method increases the number of voxels crossed by signal rays and the utilization of the observed data by 15.14% and 19.68% on average, respectively. Numerical results, including comparisons of slant water vapor (SWV), precipitable water vapor (PWV), and water vapor density profile, show that the proposed method is better than traditional methods. In comparison to the water vapor density profile, the root-mean-square error (RMS), mean absolute error (MAE), standard deviation (SD), and bias of the proposed method are 1.39, 1.07, 1.30, and −0.21 gm−3, respectively. For the SWV and PWV comparison, the RMS/MAE of the proposed method are 10.46/8.17 mm and 4.00/3.39 mm, respectively.

Ground-Based Microwave Radiometer Profiler Observations before a Heavy Rainfall

2011 ◽  
Vol 137 ◽  
pp. 312-315
Author(s):  
Wen Jing Xu ◽  
Hong Yan Liu
Keyword(s):  
Water Vapor ◽  
Temporal Resolution ◽  
Density Profile ◽  
Heavy Rainfall ◽  
Microwave Radiometer ◽  
Cloud Water ◽  
Vapor Density ◽  
Apparent Change

Ground-based 12-channel microwave radiometer profiler TP/WVP-3000 can provide temperature and vapor density profile per minute up to 10 km height. The observations feature apparent change before heavy rainfall obtained by TP/WVP-3000 is presented in this paper. It demonstrates the detailed thermodynamic features that the atmosphere becomes colder and drier above height 3-4 km about 9 hours before the rain, the integrated water vapor gradually increases from 5 cm to 9 cm, the integrated cloud water change from near zero to 15 mm and the vapor density also increases rapidly about half an hour before the rain, which can be concluded that the radiometer profiler is able to improve the understanding of mesoscale weather in this case due to the profiler significantly improves the temporal resolution of atmospheric thermodynamic observations.

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 A new tropospheric tomography model combining the pixel-based and function-based models

2018 ◽  
Author(s):  
Yibin Yao ◽  
Linyang Xin ◽  
Qingzhi Zhao
Keyword(s):  
Water Vapor ◽  
Three Dimensional ◽  
Global Navigation Satellite Systems ◽  
Reference Station ◽  
Continuous Change ◽  
Vapor Density ◽  
Spatial Continuity ◽  
New Model ◽  
Model Combining ◽  
And Function

Abstract. As a new detection method of three-dimensional water vapor, the ground-based water vapor tomography technique using Global Navigation Satellite Systems (GNSS) observations can obtain the high spatial and temporal distribution information of tropospheric water vapor. Since the troposphere tomography was proposed, most previous studies belong to the pixel-based method, dividing the interest area into three-dimensional voxels of which the water vapor density of each voxel center is taken as the average water vapor density. However, the abovementioned method can only find the water vapor density value of the center of each voxel, which is unable to express the continuous change of water vapor in space and destroys the spatial continuity of water vapor variation. Moreover, when using the pixel-based method, too many voxels are needed to express the water vapor density, which leads to the problem of too many coefficients to be estimated. After analyzing the limitations of the traditional pixel-based troposphere tomography technique, this paper proposes a new GNSS tropospheric water vapor tomography model combining the pixel-based and function-based models for the first time. The tomographic experiences were validated using the data from 12 stations from the Hong Kong Satellite Positioning Reference Station Network (SatRef) collected between 25 March and 25 April 2014. The comparison between tomographic results and the European Centre for Medium-Range Weather Forecasts (ECMWF) data is mainly used to analyze the accuracy of the new model proposed in this paper under different conditions, for showing that this new model is superior to the traditional pixel-based model in terms of root-mean-square error (RMSE) and bias. The new model has more advantages than the traditional pixel-based model on the RMSE, especially when obtaining the water vapor in voxels without the penetration of GNSS rays, which is improved by 5.88 %. This model also solves the problem with more ease and convenience in expression.

scholarly journals A New Method for Determining an Optimal Diurnal Threshold of GNSS Precipitable Water Vapor for Precipitation Forecasting

2021 ◽  
Vol 13 (7) ◽  
pp. 1390
Author(s):  
Haobo Li ◽  
Xiaoming Wang ◽  
Suqin Wu ◽  
Kefei Zhang ◽  
Erjiang Fu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Heavy Precipitation ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
New Method ◽  
New Model ◽  
Precipitation Records ◽  
Optimal Set

Nowadays, precipitable water vapor (PWV) retrieved from ground-based Global Navigation Satellite Systems (GNSS) tracking stations has heralded a new era of GNSS meteorological applications, especially for severe weather prediction. Among the existing models that use PWV timeseries to predict heavy precipitation, the “threshold-based” models, which are based on a set of predefined thresholds for the predictors used in the model for predictions, are effective in heavy precipitation nowcasting. In previous studies, monthly thresholds have been widely accepted due to the monthly patterns of different predictors being fully considered. However, the primary weakness of this type of thresholds lies in their poor prediction results in the transitional periods between two consecutive months. Therefore, in this study, a new method for the determination of an optimal set of diurnal thresholds by adopting a 31-day sliding window was first proposed. Both the monthly and diurnal variation characteristics of the predictors were taken into consideration in the new method. Then, on the strength of the new method, an improved PWV-based model for heavy precipitation prediction was developed using the optimal set of diurnal thresholds determined based on the hourly PWV and precipitation records for the summer over the period 2010–2017 at the co-located HKSC–KP (King’s Park) stations in Hong Kong. The new model was evaluated by comparing its prediction results against the hourly precipitation records for the summer in 2018 and 2019. It is shown that 96.9% of heavy precipitation events were correctly predicted with a lead time of 4.86 h, and the false alarms resulting from the new model were reduced to 25.3%. These results suggest that the inclusion of the diurnal thresholds can significantly improve the prediction performance of the model.

scholarly journals RESEARCH ON CORS (CONTINUOUSLY OPERATING REFERENCE STATION) SYSTEM-BASED REGIONAL WATER VAPOR RETRIEVAL IN GUILIN

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 1215-1220
Author(s):  
C. L. Zhou ◽  
Y. F. Yang ◽  
M. H. Yao ◽  
X. Y. Zhong ◽  
C. M. Liao
Keyword(s):  
Water Vapor ◽  
General Trend ◽  
Precipitable Water ◽  
Base Station ◽  
Reference Station ◽  
Optimum Number ◽  
Weighted Mean ◽  
Weighted Mean Temperature ◽  
High Degree ◽  
Regional Water

Abstract. This paper was aimed at analyzing and verifying each of the parameter settings in the computing process of GAMIT. The optimum number of introduced auxiliary station was determined, and models for the weighted mean temperature of the atmosphere in Guilin were established. Under the underlying strategy of introducing all the respective most optimum criteria, the precipitable water vapor (PWV) was first calculated by using the data provided by the CORS base station in Guilin, before analyzing and comparing it with the PWV and actual precipitation obtained from the sounding data. According to the result, a high degree of coincidence was discovered among the general trend of the following three indicators: the calculated PWV, as well as the PWV and actual precipitation acquired using the sounding data, hence offering a significant value for reference in terms of extreme weather warning.

scholarly journals New parameterized model for GPS water vapor tomography

2017 ◽  
Vol 35 (2) ◽  
pp. 311-323 ◽  
Author(s):  
Nan Ding ◽  
Shubi Zhang ◽  
Qiuzhao Zhang
Keyword(s):  
Water Vapor ◽  
Water Cycle ◽  
Weather Conditions ◽  
Reference Station ◽  
Atmospheric Conditions ◽  
Vapor Density ◽  
Spatiotemporal Resolution ◽  
Parameterized Model ◽  
Time Changes ◽  
Rainy Days

Abstract. Water vapor is the basic parameter used to describe atmospheric conditions. It is rarely contained in the atmosphere during the water cycle, but it is the most active element in rapid space–time changes. Measuring and monitoring the distribution and quantity of water vapor is a necessary task. GPS tomography is a powerful means of providing high spatiotemporal resolution of water vapor density. In this paper, a spatial structure model of a humidity field is constructed using voxel nodes, and new parameterizations for acquiring data about water vapor in the troposphere via GPS are proposed based on inverse distance weighted (IDW) interpolation. Unlike the density of water vapor that is constant within a voxel, the density at a certain point is determined by IDW interpolation. This algorithm avoids the use of horizontal constraints to smooth voxels that are not crossed by satellite rays. A prime number decomposition (PND) access order scheme is introduced to minimize correlation between slant wet delay (SWD) observations. Four experimental schemes for GPS tomography are carried out in dry weather from 2 to 8 August 2015 and rainy days from 9 to 15 August 2015. Using 14 days of data from the Hong Kong Satellite Positioning Reference Station Network (SatRef), the results indicate that water vapor density derived from 4-node methods is more robust than that derived from that of 8 nodes or 12 nodes, or that derived from constant refractivity schemes and the new method has better performance under stable weather conditions than unstable weather (e.g., rainy days). The results also indicate that an excessive number of interpolations in each layer reduce accuracy. However, the accuracy of the tomography results is gradually reduced with increases in altitude below 7000 m. Moreover, in the case of altitudes between 7000 m and the upper boundary layer, the accuracy can be improved by a boundary constraint.

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 Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique

2021 ◽  
Vol 13 (3) ◽  
pp. 386
Author(s):  
Jinyun Guo ◽  
Rui Hou ◽  
Maosheng Zhou ◽  
Xin Jin ◽  
Chengming Li ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Water Vapor ◽  
Forest Fire ◽  
Forest Fires ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Pollution Monitoring ◽  
New Method ◽  
Radiosonde Data ◽  
Southeastern Australia

From late 2019 to early 2020, forest fires in southeastern Australia caused huge economic losses and huge environmental pollution. Monitoring forest fires has become increasingly important. A new method of fire detection using the difference between global navigation satellite system (GNSS)-derived precipitable water vapor and radiosonde-derived precipitable water vapor (ΔPWV) is proposed. To study the feasibility of the new method, the relationship is studied between particulate matter 10 (PM10) (2.5 to 10 microns particulate matter) and ΔPWV based on Global Positioning System (GPS) data, radiosonde data, and PM10 data from 1 June 2019 to 1 June 2020 in southeastern Australia. The results show that before the forest fire, ΔPWV and PM10 were smaller and less fluctuating. When the forest fire happened, ΔPWV and PM10 were increasing. Then after the forest fire, PM10 became small with relatively smooth fluctuations, but ΔPWV was larger and more fluctuating. Correlation between the 15-day moving standard deviation (STD) time series of ΔPWV and PM10 after the fire was significantly higher than that before the fire. This study shows that ΔPWV is effective in monitoring forest fires based on GNSS technique before and during forest fires in climates with more uniform precipitation, and using ΔPWV to detect forest fires based on GNSS needs to be further investigated in climates with more precipitation and severe climate change.

scholarly journals Optimization of GPS water vapor tomography technique with radiosonde and COSMIC historical data

2016 ◽  
Vol 34 (9) ◽  
pp. 789-799 ◽  
Author(s):  
Shirong Ye ◽  
Pengfei Xia ◽  
Changsheng Cai
Keyword(s):  
Water Vapor ◽  
Conventional Method ◽  
Historical Data ◽  
Interpolation Method ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Precipitable Water ◽  
Vapor Density ◽  
Tomographic Method ◽  
Zenith Hydrostatic Delay

Abstract. The near-real-time high spatial resolution of atmospheric water vapor distribution is vital in numerical weather prediction. GPS tomography technique has been proved effectively for three-dimensional water vapor reconstruction. In this study, the tomography processing is optimized in a few aspects by the aid of radiosonde and COSMIC historical data. Firstly, regional tropospheric zenith hydrostatic delay (ZHD) models are improved and thus the zenith wet delay (ZWD) can be obtained at a higher accuracy. Secondly, the regional conversion factor of converting the ZWD to the precipitable water vapor (PWV) is refined. Next, we develop a new method for dividing the tomography grid with an uneven voxel height and a varied water vapor layer top. Finally, we propose a Gaussian exponential vertical interpolation method which can better reflect the vertical variation characteristic of water vapor. GPS datasets collected in Hong Kong in February 2014 are employed to evaluate the optimized tomographic method by contrast with the conventional method. The radiosonde-derived and COSMIC-derived water vapor densities are utilized as references to evaluate the tomographic results. Using radiosonde products as references, the test results obtained from our optimized method indicate that the water vapor density accuracy is improved by 15 and 12 % compared to those derived from the conventional method below the height of 3.75 km and above the height of 3.75 km, respectively. Using the COSMIC products as references, the results indicate that the water vapor density accuracy is improved by 15 and 19 % below 3.75 km and above 3.75 km, respectively.

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