scholarly journals Establishment of a regional precipitable water vapor model based on the combination of GNSS and ECMWF data

2018 ◽  
Author(s):  
Yibin Yao ◽  
Xingyu Xu ◽  
Yufeng Hu

Abstract. Water vapor is the engine of the weather. Owing to its large latent energy, the phase changes of water vapor significantly affect the vertical stability, structure and energy balance of the atmosphere. Many techniques are used for measuring the water vapor in the atmosphere such as radiosondes, Global Navigation Satellite System (GNSS) and water vapor radiometer (WVR). In addition, the method that uses European Centre for Medium-range Weather Forecasts (ECMWF) data is an important method for studying the variations in precipitable water vapor (PWV). This paper used both GNSS PWV and ECMWF PWV to establish a city-level local PWV fusion model using a Gaussian Processes method. The results indicate that by integrating the precipitable water vapor obtained from GNSS and ECMWF data, the accuracy of fusion PWV is improved by 1.89 mm in active tropospheric conditions and 2.61 mm in quiescent tropospheric conditions compared with ECMWF-PWV, reaching 3.87 mm and 3.97 mm, respectively. Furthermore, the proposed fusion model is used to study the spatial and temporal distribution of PWV in Hong Kong. It is found that the accumulation of PWV corresponds to monsoon and rainfall events.

2020 ◽  
Vol 199 ◽  
pp. 00002
Author(s):  
Agana Louisse S. Domingo ◽  
Ernest P. Macalalad

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.


2020 ◽  
Vol 13 (9) ◽  
pp. 4963-4972
Author(s):  
Zhilu Wu ◽  
Yanxiong Liu ◽  
Yang Liu ◽  
Jungang Wang ◽  
Xiufeng He ◽  
...  

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.


2021 ◽  
Vol 13 (23) ◽  
pp. 4866
Author(s):  
Keita Matsuzawa ◽  
Yohei Kinoshita

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.


Author(s):  
Nguyễn Định Quốc Huỳnh ◽  
Ngọc Lâu Nguyễn

Lượng hơi nước tích tụ PWV (Precipitable Water Vapor) trong khí quyển rất cần thiết trong công tác dự báo thời tiết. Việc xác định chỉ số PWV một cách chính xác hiện nay đang là vấn đề được nhiều người quan tâm trong lĩnh vực khí tượng thủy văn. Trong bài báo này, chúng tôi trình bày thuật toán xác định chỉ số PWV và kết quả so sánh giá trị PWV từ dữ liệu bóng thám không và từ dữ liệu GNSS (Global Navigation Satellite System) tại trạm Tân Sơn Hòa TP.HCM. Độ lệch giữa các kết quả PWV nhỏ hơn 1.2mm. Ngoài ra giá trị PWV thay đổi phù hợp với thời tiết thay đổi trong ngày khảo sát.


2021 ◽  
Vol 13 (3) ◽  
pp. 350
Author(s):  
Rosa Delia García ◽  
Emilio Cuevas ◽  
Victoria Eugenia Cachorro ◽  
Omaira E. García ◽  
África Barreto ◽  
...  

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.


2021 ◽  
Author(s):  
Syachrul Arief

&lt;p&gt;The huge amount of water vapor in the atmosphere caused disastrous heavy rain and floods in early July 2018 in SW Japan. Here I present a comprehensive space geodetic study of water brought by this heavy rain done by using a dense network of Global Navigation Satellite System (GNSS) receivers.&amp;#160;&lt;/p&gt;&lt;p&gt;First, I reconstruct sea level precipitable water vapor above land region on the heavy rain. The total amount of water vapor derived by spatially integrating precipitable water vapor on land was ~25.8 Gt, which corresponds to the bucket size to carry water from ocean to land. I then compiled the precipitation measured with a rain radar network. The data showed the total precipitation by this heavy rain as ~22.11 Gt.&lt;/p&gt;&lt;p&gt;Next, I studied the crustal subsidence caused by the rainwater as the surface load. The GNSS stations located under the heavy rain area temporarily subsided 1-2 centimeters and the subsidence mostly recovered in a day. Using such vertical crustal movement data, I estimated the distribution of surface water in SW Japan.&amp;#160;&lt;/p&gt;&lt;p&gt;The total amount of the estimated water load on 6 July 2018 was ~68.2 Gt, which significantly exceeds the cumulative on-land rainfalls of the heavy rain day from radar rain gauge analyzed precipitation data. I consider that such an amplification of subsidence originates from the selective deployment of GNSS stations in the concave places, e.g. along valleys and within basins, in the mountainous Japanese Islands.&lt;/p&gt;


Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5566 ◽  
Author(s):  
Qingzhi Zhao ◽  
Xiongwei Ma ◽  
Wanqiang Yao ◽  
Yang Liu ◽  
Zheng Du ◽  
...  

Standardized precipitation evapotranspiration index (SPEI) is an acknowledged drought monitoring index, and the evapotranspiration (ET) used to calculated SPEI is obtained based on the Thornthwaite (TH) model. However, the SPEI calculated based on the TH model is overestimated globally, whereas the more accurate ET derived from the Penman–Monteith (PM) model recommended by the Food and Agriculture Organization of the United Nations is unavailable due to the lack of a large amount of meteorological data at most places. Therefore, how to improve the accuracy of ET calculated by the TH model becomes the focus of this study. Here, a revised TH (RTH) model is proposed using the temperature (T) and precipitable water vapor (PWV) data. The T and PWV data are derived from the reanalysis data and the global navigation satellite system (GNSS) observation, respectively. The initial value of ET for the RTH model is calculated based on the TH model, and the time series of ET residual between the TH and PM models is then obtained. Analyzed results reveal that ET residual is highly correlated with PWV and T, and the correlate coefficient between PWV and ET is −0.66, while that between T and ET for cases of T larger or less than 0 °C are −0.54 and 0.59, respectively. Therefore, a linear model between ET residual and PWV/T is established, and the ET value of the RTH model can be obtained by combining the TH-derived ET and estimated ET residual. Finally, the SPEI calculated based on the RTH model can be obtained and compared with that derived using PM and TH models. Result in the Loess Plateau (LP) region reveals the good performance of the RTH-based SPEI when compared with the TH-based SPEI over the period of 1979–2016. A case analysis in April 2013 over the LP region also indicates the superiority of the RTH-based SPEI at 88 meteorological and 31 GNSS stations when the PM-based SPEI is considered as the reference.


2009 ◽  
Vol 24 (4) ◽  
pp. 1085-1101 ◽  
Author(s):  
O. Bock ◽  
M. Nuret

Abstract This paper assesses the performance of the European Centre for Medium-Range Weather Forecasts-Integrated Forecast System (ECMWF-IFS) operational analysis and NCEP–NCAR reanalyses I and II over West Africa, using precipitable water vapor (PWV) retrievals from a network of ground-based GPS receivers operated during the African Monsoon Multidisciplinary Analysis (AMMA). The model analyses show reasonable agreement with GPS PWV from 5-daily to monthly means. Errors increase at shorter time scales, indicating that these global NWP models have difficulty in handling the diurnal cycle and moist processes at the synoptic scale. The ECMWF-IFS analysis shows better agreement with GPS PWV than do the NCEP–NCAR reanalyses (the RMS error is smaller by a factor of 2). The model changes in ECMWF-IFS were not clearly reflected in the PWV error over the period of study (2005–08). Radiosonde humidity biases are diagnosed compared to GPS PWV. The impacts of these biases are evidenced in all three model analyses at the level of the diurnal cycle. The results point to a dry bias in the ECMWF analysis in 2006 when Vaisala RS80-A soundings were assimilated, and a diurnally varying bias when Vaisala RS92 or Modem M2K2 soundings were assimilated: dry during day and wet during night. The overall bias is offset to wetter values in NCEP–NCAR reanalysis II, but the diurnal variation of the bias is observed too. Radiosonde bias correction is necessary to reduce NWP model analysis humidity biases and improve precipitation forecast skill. The study points to a wet bias in the Vaisala RS92 data at nighttime and suggests that caution be used when establishing a bias correction scheme.


Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2526 ◽  
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Junbo Shi ◽  
Lv Zhou ◽  
Yi Xu ◽  
...  

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.


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