The impact of ultra-rapid orbits on precipitable water vapor estimation using a ground GPS network

2001 ◽  
Vol 26 (6-8) ◽  
pp. 393-398 ◽  
Author(s):  
J. Douša
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Gps Network ◽  
The Impact

The Impact of Assimilating GPS Precipitable Water Vapor in Convective-Permitting WRF-ARW on North American Monsoon Precipitation Forecasts over Northwest Mexico

2021 ◽  
Author(s):  
Christoforus Bayu Risanto ◽  
Christopher L. Castro ◽  
Avelino F. Arellano ◽  
James M. Moker ◽  
David K. Adams
Keyword(s):  
Water Vapor ◽  
Data Assimilation ◽  
North American ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
North American Monsoon ◽  
Convective Systems ◽  
Northwest Mexico ◽  
Dewpoint Temperature ◽  
The Impact

AbstractWe assess the impact of GPS precipitable water vapor (GPS-PWV) data assimilation (DA) on short-range North American monsoon (NAM) precipitation forecasts, across 38 days with weak synoptic forcing, during the NAM GPS Hydrometeorological Network field campaign in 2017 over northwest Mexico. Utilizing an ensemble-based data assimilation technique, the GPS-PWV data retrieved from 18 observation sites are assimilated every hour for 12 hours into a 30-member ensemble convective-permitting (2.5 km) Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model. As the assimilation of the GPS-PWV improves the initial condition of WRF by reducing the root mean square error and bias of PWV across 1200-1800 UTC, this also leads to an improvement in capturing nocturnal convection of mesoscale convective systems (MCSs; after 0300 UTC) and to an increase by 0.1 mm h-1 in subsequent precipitation during the 0300-0600 UTC period relative to no assimilation of the GPS-PWV (NODA) over the area with relatively more observation sites. This response is consistent with observed precipitation from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Precipitation product. Moreover, compared to the NODA, we find that the GPS-PWV DA decreases cloud top temperature, increases most unstable convective available energy and surface dewpoint temperature, and thus creates a more favorable condition for convective organization in the region.

scholarly journals On the Diurnal Cycle of GPS-Derived Precipitable Water Vapor over Sumatra

2019 ◽  
Vol 76 (11) ◽  
pp. 3529-3552
Author(s):  
Giuseppe Torri ◽  
David K. Adams ◽  
Huiqun Wang ◽  
Zhiming Kuang
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Wrf Model ◽  
Precipitable Water ◽  
Active Phase ◽  
Precipitable Water Vapor ◽  
Tectonic Activity ◽  
Western Coast ◽  
The Impact ◽  
Spectrometer Data

Abstract Convective processes in the atmosphere over the Maritime Continent and their diurnal cycles have important repercussions for the circulations in the tropics and beyond. In this work, we present a new dataset of precipitable water vapor (PWV) obtained from the Sumatran GPS Array (SuGAr), a dense network of GPS stations principally for examining seismic and tectonic activity along the western coast of Sumatra and several offshore islands. The data provide an opportunity to examine the characteristics of convection over the area in greater detail than before. In particular, our results show that the diurnal cycle of PWV on Sumatra has a single late afternoon peak, while that offshore has both a midday and a nocturnal peak. The SuGAr data are in good agreement with GPS radio occultation data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission, as well as with imaging spectrometer data from the Ozone Measuring Instrument (OMI). A comparison between SuGAr and the NASA Water Vapor Project (NVAP), however, shows significant differences, most likely due to discrepancies in the temporal and spatial resolutions. To further understand the diurnal cycle contained in the SuGAr data, we explore the impact of the Madden–Julian oscillation (MJO) on the diurnal cycle with the aid of the Weather Research and Forecasting (WRF) Model. Results show that the daily mean and the amplitude of the diurnal cycle appear smaller during the suppressed phase relative to the developing/active MJO phase. Furthermore, the evening/nighttime peaks of PWV offshore appear later during the suppressed phase of the MJO compared to the active phase.

scholarly journals Experiment on driving precipitable water vapor from ground-based GPS network in Chengdu Plain

2007 ◽  
Vol 10 (3) ◽  
pp. 181-185 ◽  
Author(s):  
Guoping Li ◽  
Dingfa Huang ◽  
Biquan Liu ◽  
Jiaona Chen
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Chengdu Plain ◽  
Gps Network

Assessment and calibration of MODIS precipitable water vapor products based on GPS network over China

2021 ◽  
Vol 254 ◽  
pp. 105504
Author(s):  
Jingna Bai ◽  
Yidong Lou ◽  
Weixing Zhang ◽  
Yaozong Zhou ◽  
Zhenyi Zhang ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Gps Network

scholarly journals Establishment and Assessment of a New GNSS Precipitable Water Vapor Interpolation Scheme Based on the GPT2w Model

2019 ◽  
Vol 11 (9) ◽  
pp. 1127 ◽  
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Xiaolin Meng ◽  
Junbo Shi ◽  
Lv Zhou
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Reference Station ◽  
Observation Data ◽  
Interpolation Scheme ◽  
Grid Data ◽  
Skill Scores ◽  
Gpt2w Model ◽  
The Impact

With the development of Global Navigation Satellite System (GNSS) reference station networks that provide rich data sources containing atmospheric information, the precipitable water vapor (PWV) retrieved from GNSS remote sensing has become one of the most important bodies of data in many meteorological departments. GNSS stations are distributed in the form of scatters, generally, these separations range from a few kilometers to tens of kilometers. Therefore, the spatial resolution of GNSS-PWV can restrict some applications such as interferometric synthetic aperture radar (InSAR) atmospheric calibration and regional atmospheric water vapor analysis, which inevitably require the spatial interpolation of GNSS-PWV. This paper explored a PWV interpolation scheme based on the GPT2w model, which requires no meteorological data at an interpolation station and no regression analysis of the observation data. The PWV interpolation experiment was conducted in Hong Kong by different interpolation schemes, which differed in whether the impact of elevation was considered and whether the GPT2w model was added. In this paper, we adopted three skill scores, i.e., compound relative error (CRE), mean absolute error (MAE), and root mean square error (RMSE), and two approaches, i.e., station cross-validation and grid data validation, for our comparison. Numerical results showed that the interpolation schemes adding the GPT2w model could greatly improve the PWV interpolation accuracy when compared to the traditional schemes, especially at interpolation points away from the elevation range of reference stations. Moreover, this paper analyzed the PWV interpolation results under different weather conditions, at different locations, and on different days.

New meteorological products based on Sentinel-1 and GNSS

2020 ◽  
Author(s):  
Giovanni Nico ◽  
Francesco Vespe ◽  
Olimpia Masci ◽  
Pedro Mateus ◽  
João Catalão ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Precipitable Water ◽  
Propagation Delay ◽  
Precipitable Water Vapor ◽  
Sar Interferometry ◽  
Extreme Weather Events ◽  
Geophysical Research ◽  
Gnss Data ◽  
The Impact

<p>Recently, the SAR Meteorology technique has demostrated the advantages of assimilating Sentinel-1 maps of Precipitable Water Vapor (PWV) in high resolution Numerical Weather Models (NWP) when forecasting extreme weather events [1]. The impact of Sentinel-1 information on NWP forecast depends on the acquisition parameters of Sentinel-1 images and the physical status of atmosphere [2]. Besides meteorological applications, enhancing NWP forecast could have an impact also on the mitigation of atmospheric artifacts in SAR interferometry applications based on NWP simulations [3].</p><p>This work describes a methodology to provide measurements of microwave propagation delay in troposphere. The proposed methodology is based on the processing of Sentinel-1 and GNSS data. In particular, Sentinel-1 images are processed by means of SAR Interferometry technique to get measurements of propagation delay in troposphere over land assuming that phase contribution due terrain displacements can be neglected. To fulfil this condition, the interferometric processing is carried out on Sentinel-1 images having the shortest temporal baseline of six days. Interferometric coherence is used to select portions of the interferogram where to estimates of PWV and the corresponding precision are provided. GNSS measurements of propagation delay in atmosphere are used to validate the Sentinel-1 measurements and derive a quality figure of PWV maps. A procedure is presented to concatenate PWV maps in time in order to derive a time series of spatially dense PWV measurements and the corresponding precisions.</p><p>Furthermore, Radio Occultation (RO) profiles are obtained by processing GNSS data. Profiles will be used to derive an estimate of propagation delay in troposphere over sea. In such a way, maps of propagation delay in atmosphere over both land and sea, even though characterized by a different spatial density of measurements, will be provided.</p><p>The study area includes the Basilicata, Calabria and Apulia regions and the Gulf of Taranto, southern Italy.</p><p>This work was supported by the Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR), Italy, under the project OT4CLIMA.</p><p>References</p><p>[1] P. Mateus, J. Catalão, G. Nico, “Sentinel-1 interferometric SAR mapping of precipitable water vapor over a country-spanning area”, IEEE Transactions on Geoscience and Remote Sensing, 55(5), 2993-2999, 2017.</p><p>[2] P.M.A. Miranda, P. Mateus, G. Nico, J. Catalão, R. Tomé, M. Nogueira, “InSAR meteorology: High‐resolution geodetic data can increase atmospheric predictability”, Geophysical Research Letters, 46(5), 2949-2955, 2019.</p><p>[3] G. Nico, R. Tome, J. Catalao, P.M.A. Miranda, “On the use of the WRF model to mitigate tropospheric phase delay effects in SAR interferograms”, IEEE Transactions on Geoscience and Remote Sensing, 49(12), 4970-4976, 2011.</p>

KORELASI MUSIMAN ANTARA ZENITH WET DELAY (ZWD) DAN DEBIT SUNGAI DI DAS CIKAPUNDUNG HULU, KAWASAN BANDUNG UTARA, JAWA BARAT

2019 ◽  
Vol 3 ◽  
pp. 741
Author(s):  
Wedyanto Kuntjoro ◽  
Z.A.J. Tanuwijaya ◽  
A. Pramansyah ◽  
Dudy D. Wijaya
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Zenith Wet Delay

Kandungan total uap air troposfer (precipitable water vapor) di suatu tempat dapat diestimasi berdasarkan karakteristik bias gelombang elektromagnetik dari satelit navigasi GPS, berupa zenith wet delay (ZWD). Pola musiman deret waktu ZWD sangat penting dalam studi siklus hidrologi khususnya yang terkait dengan kejadian-kejadian banjir. Artikel ini menganalisis korelasi musiman antara ZWD dan debit sungai Cikapundung di wilayah Bandung Utara berdasarkan estimasi rataan pola musimannya. Berdasarkan rekonstruksi sejumlah komponen harmonik ditemukan bahwa pola musiman ZWD memiliki kemiripan dan korelasi yang kuat dengan pola musiman debit sungai. Pola musiman ZWD dan debit sungai dipengaruhi secara kuat oleh fenomena pertukaran Monsun Asia dan Monsun Australia. Korelasi linier di antara keduanya menunjukkan hasil yang sangat kuat, dimana hampir 90% fluktuasi debit sungai dipengaruhi oleh kandungan uap air di troposfer dengan level signifikansi 95%. Berdasarkan spektrum amplitudo silang dan koherensi, kedua kuantitas ini nampak didominasi oleh siklus monsun satu tahunan disertai indikasi adanya pengaruh siklus tengah tahunan dan 4 bulanan.

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.

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