scholarly journals The Influence of Different Modelling Factors on Global Temperature and Pressure Models and Their Performance in Different Zenith Hydrostatic Delay (ZHD) Models

2019 ◽  
Vol 12 (1) ◽  
pp. 35 ◽  
Author(s):  
Fei Yang ◽  
Xiaolin Meng ◽  
Jiming Guo ◽  
Junbo Shi ◽  
Xiangdong An ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
Absolute Error ◽  
Satellite System ◽  
Reanalysis Data ◽  
Data Sources ◽  
Radiosonde Data ◽  
Temperature And Pressure ◽  
Zenith Hydrostatic Delay ◽  
Global Mean

Surface temperature and pressure are indispensable variables in Global Navigation Satellite System (GNSS) meteorology. The lack of meteorological observations located at or near the GNSS sites is a big challenge for the calculation of accurate zenith hydrostatic delay (ZHD). Therefore, various empirical models with different model forms were established to provide temperature and pressure values. In this study, the influence of different modelling factors, including model forms, temporal resolution of the data sources, and the spatial resolution of the data sources, is evaluated and the temperature and pressure model with the best performance is developed. On the basis of the meteorological parameters estimated by the above model, we analyzed the global performance of the three most commonly used ZHD models, that is, the Saastamoinen, Hopfield, and Black models. The numerical results show that the model with the idea of time-segmented modelling performs best, of which the global mean root mean square (RMS), mean absolute error (MAE), and standard deviation (SD) are 7.87/6.33/7.17 hPa and 2.95/2.31/2.79 K for pressure and temperature, respectively, using the data sources with temporal resolution of 2 h and spatial resolution of 2.5° × 2° in the reanalysis data comparison. In comparison with the radiosonde data, the mean RMS/MAE/SD are 7.02/5.24/6.46 hPa and 4.05/3.17/3.86 K for pressure and temperature, respectively. The Saastamoinen model with a global mean bias/RMS of 1.01/16.9 mm achieved the best ZHD estimated values compared with the other two ZHD models.

Water vapour trends in Switzerland from radiometry, FTIR and GNSS ground stations

2020 ◽  
Author(s):  
Leonie Bernet ◽  
Elmar Brockmann ◽  
Thomas von Clarmann ◽  
Niklaus Kämpfer ◽  
Emmanuel Mahieu ◽  
...  
Keyword(s):  
Water Vapour ◽  
Temporal Resolution ◽  
Regional Climate ◽  
Satellite System ◽  
Reanalysis Data ◽  
High Temporal Resolution ◽  
Integrated Water Vapour ◽  
Global Navigation Satellite ◽  
Increasing Temperature ◽  
Gnss Data

<div> <div>Water vapour in the atmosphere is not only a strong greenhouse gas, but also affects many atmospheric processes such as the formation of clouds and precipitation. With increasing temperature, Integrated Water Vapour (IWV) is expected to increase. Analysing how atmospheric water vapour changes in time is therefore important to monitor ongoing climate change. To determine whether IWV increases in Switzerland as expected, we asses IWV trends from a tropospheric water radiometer (TROWARA) in Bern, from a Fourier transform infrared (FTIR) spectrometer at Jungfraujoch and from the Swiss network of ground-based Global Navigation Satellite System (GNSS) stations. In addition, trends are assessed from reanalysis data, using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) and the Modern-Era Retrospecitve Analysis for Research and Applications (MERRA-2).</div> <div>Ground-based GNSS data are well suited for IWV trends due to their high temporal resolution and the spatially dense networks. However, they are highly sensitvie to instrumental changes and care has to be taken when determining GNSS based trends. We therefore use a straightforward trend method to account for jumps in the GNSS data when instrumental changes were performed.</div> <div>Our data show mostly positive IWV trends between 2 and 5% per decade in Switzerland. GNSS trends are significant for some stations and the significance has the tendency to increase with altitude. Further, we found that IWV scales on average to lower tropospheric temperatures as expected, except in winter. However, the correlation between IWV and temperature based on reanalysis data is spatially incoherent. Besides our positive IWV trends, we found a good agreement of radiometer, GNSS and reanalysis data in Bern. Further, we found a dry bias of the FTIR compared to GNSS data at Jungfraujoch, due to the restriction of FTIR to clear-sky conditions. Our results are generally consistent with the positive water vapour feedback in a warming climate. We show that ground-based GNSS networks provide a valuable source for regional climate monitoring with high spatial and temporal resolution, but homogeneously reprocessed data and advanced trend techniques are needed to account for data jumps.</div> </div>

scholarly journals An optimal tropospheric tomography approach with the support of an auxiliary area

2018 ◽  
Vol 36 (4) ◽  
pp. 1037-1046 ◽  
Author(s):  
Qingzhi Zhao ◽  
Yibin Yao ◽  
Wanqiang Yao ◽  
Pengfei Xia
Keyword(s):  
Water Vapour ◽  
Conventional Method ◽  
Three Dimensional ◽  
Absolute Error ◽  
Satellite System ◽  
Radiosonde Data ◽  
Cosmic Radio ◽  
Negative Exponential Function ◽  
Atmospheric Sciences ◽  
Negative Exponential

Abstract. Among most current tropospheric tomography studies, only the signals crossing out from the top boundary of the tomographic area are used for reconstructing the three-dimensional water vapour field, while signals penetrating from the side faces of the tomographic body are ignored as invalid information. Such a method wastes the valuable Global Navigation Satellite System (GNSS) observations and decreases the utilisation efficiency of GNSS rays. This is the focus of this paper, which tries to effectively use signals penetrating from the side faces of the tomographic body for water vapour reconstruction. An optimised tropospheric tomography method is proposed using an auxiliary area. The top height of the tomography body is determined based on the average water vapour distribution derived from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation (RO) products. In addition, the coefficients of a negative exponential function between the adjacent layers for vertical constraints are fitted using the COSMIC RO profiles. Thirteen GPS stations are selected in the CORS Network of Texas to perform the tomographic experiment and validate the performance of the proposed method at 00:00 and 12:00 UTC daily using the radiosonde data for a period of 15 days. Compared to the conventional method, the accuracy of the reconstructed water vapour information derived from the proposed method is increased by 14.37 % and 16.13 %, respectively, in terms of mean root mean square (rms) and mean absolute error (MAE). The tomographic results obtained from the proposed method are further validated with the slant water vapour (SWV) data derived using the GAMIT (GNSS processing software package). Results show that the rms and MAE accuracy of SWV values has been improved by 18.18 % and 27.62 %, respectively, when compared to the conventional method. Keywords. History of geophysics (atmospheric sciences)

scholarly journals Evaluation of the ZWD/ZTD Values Derived from MERRA-2 Global Reanalysis Products Using GNSS Observations and Radiosonde Data

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6440
Author(s):  
Liangke Huang ◽  
Lijie Guo ◽  
Lilong Liu ◽  
Hua Chen ◽  
Jun Chen ◽  
...  
Keyword(s):  
Satellite System ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
International Gnss Service ◽  
Vapor Detection ◽  
Lower Accuracy ◽  
Temporal And Spatial Characteristics ◽  
Global Navigation Satellite ◽  
Better Than

Tropospheric delay is one of the main errors affecting high-precision positioning and navigation and is a key parameter of water vapor detection in the Global Navigation Satellite System (GNSS). The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is the latest generation of reanalysis data collected by the National Aeronautics and Space Administration (NASA), which can be used to calculate tropospheric delay products with high spatial and temporal resolution. However, there is no report analyzing the accuracy of the zenith tropospheric delay (ZTD) and zenith wet delay (ZWD) calculated from MERRA-2 data. This paper evaluates the performance of the ZTD and ZWD values derived from global MERRA-2 data using global radiosonde data and International GNSS Service (IGS) precise ZTD products. The results are as follows: (1) Taking the precision ZTD products of 316 IGS stations from around the world from 2015 to 2017 as the reference, the average root mean square (RMS) of the ZTD values calculated from the MERRA-2 data is better than 1.35 cm, and the accuracy difference between different years is small. The bias and RMS of the ZTD values show certain seasonal variations, with a higher accuracy in winter and a lower accuracy in summer, and the RMS decreases from the equator to the poles. However, those of the ZTD values do not show obvious variations according to elevation. (2) Relative to the radiosonde data, the RMS of the ZWD and ZTD values calculated from the MERRA-2 data are better than 1.37 cm and 1.45 cm, respectively. Furthermore, the bias and RMS of the ZWD and ZTD values also show some temporal and spatial characteristics, which are similar to the test results of the IGS stations. It is suggested that MERRA-2 data can be used for global tropospheric vertical profile model construction because of their high accuracy and good stability in the global calculation of the ZWD and ZTD.

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 Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements

2021 ◽  
Vol 13 (15) ◽  
pp. 3008
Author(s):  
Lijie Guo ◽  
Liangke Huang ◽  
Junyu Li ◽  
Lilong Liu ◽  
Ling Huang ◽  
...  
Keyword(s):  
Comprehensive Evaluation ◽  
Spatial Scales ◽  
Precipitable Water ◽  
Satellite System ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
Weighted Mean Temperature ◽  
Temporal And Spatial ◽  
Environmental Prediction

Tropospheric delay is a major error source in the Global Navigation Satellite System (GNSS), and the weighted mean temperature (Tm) is a key parameter in precipitable water vapor (PWV) retrieval. Although reanalysis products like the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim) data have been used to calculate and model the tropospheric delay, Tm, and PWV, the limitations of the temporal and spatial resolutions of the reanalysis data have affected their performance. The release of the fifth-generation accurate global atmospheric reanalysis (ERA5) and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) provide the opportunity to overcome these limitations. The performances of the zenith tropospheric delay (ZTD), zenith wet delay (ZWD), Tm, and zenith hydrostatic delay (ZHD) of ERA5 and MERRA-2 data from 2016 to 2017 were evaluated in this work using GNSS ZTD and radiosonde data over the globe. Taking GNSS ZTD as a reference, the ZTD calculated from MERRA-2 and ERA5 pressure-level data were evaluated in temporal and spatial scales, with an annual mean bias and root mean square (RMS) of 2.3 and 10.9 mm for ERA5 and 4.5 and 13.1 mm for MERRA-2, respectively. Compared to radiosonde data, the ZHD, ZWD, and Tm derived from ERA5 and MERRA-2 data were also evaluated on temporal and spatial scales, with annual mean bias values of 1.1, 1.7 mm, and 0.14 K for ERA5 and 0.5, 4.8 mm, and –0.08 K for MERRA-2, respectively. Meanwhile, the annual mean RMS was 4.5, 10.5 mm, and 1.03 K for ERA5 and 4.4, 13.6 mm, and 1.17 K for MERRA-2, respectively. Tropospheric parameters derived from MERRA-2 and ERA5, with improved temporal and spatial resolutions, can provide a reference for GNSS positioning and PWV retrieval.

scholarly journals Improved Zenith Tropospheric Delay Modeling Using the Piecewise Model of Atmospheric Refractivity

2020 ◽  
Vol 12 (23) ◽  
pp. 3876
Author(s):  
Liu Yang ◽  
Jingxiang Gao ◽  
Dantong Zhu ◽  
Nanshan Zheng ◽  
Zengke Li
Keyword(s):  
Weather Forecasting ◽  
Vertical Direction ◽  
Satellite System ◽  
Exponential Model ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
Zenith Tropospheric Delay ◽  
Piecewise Model ◽  
Surrounding Areas

As one of the atmosphere propagation delays, the tropospheric delay is a significant error source that should be properly handled in high-precision global navigation satellite system (GNSS) applications. We propose an improved zenith tropospheric delay (ZTD) modeling method whereby the piecewise model of the atmospheric refractivity is introduced. Compared with using the exponential model to fit ZTD in vertical direction, the ZTD piecewise model has a better performance. Based on ERA5 2.5° × 2.5° reanalysis data produced by the European Centre for Medium-Range Weather Forecasting (ECMWF) from 2013 to 2017, we establish the regional gridded ZTD model (RGZTD) using a trigonometric function for China and the surrounding areas, which ranges from 70° E to 135° E in longitude and from 15° N to 55° N in latitude. To verify the performance of RGZTD model, the ERA5 ZTD data in 2017–2018, the radiosonde ZTD data from 86 radiosonde stations over China in 2017–2018, and the tropospheric delay products on 251 GNSS stations from Crustal Movement Observation Network of China (CMONOC) in 2016–2017 are used as external compliance check data. The results show that the overall accuracy of RGZTD model is better than that of exponential model, UNB3m model, and GPT3 model. Moreover, the accuracy can be improved by about 13.4%, 7.1%, and 6.2% when ERA5 reanalysis data, radiosonde data, and CMONOC data are used as reference values, respectively. High-accuracy ZTD data can be provided because the RGZTD model takes into account the vertical variation of ZTD through the new piecewise model.

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.

A four-channel ICCD framing camera with nanosecond temporal resolution and high spatial resolution

2021 ◽  
pp. 1-9
Author(s):  
Yuman Fang ◽  
Minrui Zhang ◽  
Junfeng Wang ◽  
Lehui Guo ◽  
Xueling Liu ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
High Spatial Resolution ◽  
Framing Camera

scholarly journals Super-resolution time-resolved imaging using computational sensor fusion

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Callenberg ◽  
A. Lyons ◽  
D. den Brok ◽  
A. Fatima ◽  
A. Turpin ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Single Photon ◽  
Super Resolution ◽  
Numerical Data ◽  
Data Cube ◽  
Fluorescence Lifetime Imaging ◽  
Time Resolved ◽  
Temporal Precision

AbstractImaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence lifetime imaging. However, compromises that sacrifice, for example, spatial resolution at the expense of temporal resolution are often required, in particular when the full 3-dimensional data cube is required in short acquisition times. We introduce a sensor fusion approach that combines data having low-spatial resolution but high temporal precision gathered with a single-photon-avalanche-diode (SPAD) array with data that has high spatial but no temporal resolution, such as that acquired with a standard CMOS camera. Our method, based on blurring the image on the SPAD array and computational sensor fusion, reconstructs time-resolved images at significantly higher spatial resolution than the SPAD input, upsampling numerical data by a factor $$12 \times 12$$ 12 × 12 , and demonstrating up to $$4 \times 4$$ 4 × 4 upsampling of experimental data. We demonstrate the technique for both LIDAR applications and FLIM of fluorescent cancer cells. This technique paves the way to high spatial resolution SPAD imaging or, equivalently, FLIM imaging with conventional microscopes at frame rates accelerated by more than an order of magnitude.

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