Applying the New MODIS-Based Precipitable Water Vapor Retrieval Algorithm Developed in the North Hemisphere to the South Hemisphere

2021 ◽  
pp. 1-12
Author(s):  
Jia He ◽  
Zhizhao Liu
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Retrieval Algorithm ◽  
The South ◽  
The North

scholarly journals Assessments of GMI-Derived Precipitable Water Vapor Products over the South and East China Seas Using Radiosonde and GNSS

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Biyan Chen ◽  
Wujiao Dai ◽  
Zhizhao Liu ◽  
Lixin Wu ◽  
Pengfei Xia
Keyword(s):  
Water Vapor ◽  
Weather Forecasting ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Weather Conditions ◽  
Precipitable Water Vapor ◽  
East China ◽  
China Seas ◽  
The South ◽  
Mean Square Errors

Satellite remote sensing of the atmospheric water vapor distribution over the oceans is essential for both weather and climate studies. Satellite onboard microwave radiometer is capable of measuring the water vapor over the oceans under all weather conditions. This study assessed the accuracies of precipitable water vapor (PWV) products over the south and east China seas derived from the Global Precipitation Measurement Microwave Imager (GMI), using radiosonde and GNSS (Global Navigation Satellite System) located at islands and coasts as truth. PWV measurements from 14 radiosonde and 5 GNSS stations over the period of 2014–2017 were included in the assessments. Results show that the GMI 3-day composites have an accuracy of better than 5 mm. A further evaluation shows that RMS (root mean square) errors of the GMI 3-day composites vary greatly in the range of 3∼14 mm at different radiosonde/GNSS sites. GMI 3-day composites show very good agreements with radiosonde and GNSS measured PWVs with correlation coefficients of 0.896 and 0.970, respectively. The application of GMI products demonstrates that it is possible to reveal the weather front, moisture advection, transportation, and convergence during the Meiyu rainfall. This work indicates that the GMI PWV products can contribute to various studies such as climate change, hydrologic cycle, and weather forecasting.

scholarly journals Application of GNSS Methodologies to Obtain Precipitable Water Vapor (PWV) and Its Comparison with Radiosonde Data

Proceedings ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 24 ◽  
Author(s):  
Raquel Perdiguer-López ◽  
José Luis Berné-Valero ◽  
Natalia Garrido-Villén
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Weather Conditions ◽  
Precipitable Water Vapor ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
The North ◽  
Radiosonde Station ◽  
Observation Method ◽  
North Of Spain

A processing methodology with GNSS observations to obtain Zenith Tropospheric Delay using Bernese GNSS Software version 5.2 is revised in order to obtain Precipitable Water Vapor (PWV). The most traditional PWV observation method is the radiosonde and it is often used as a standard to validate those derived from GNSS. For this reason, a location in the north of Spain, in A Coruña, which has a GNSS station with available data and also a radiosonde station, was chosen. Two GPS weeks, in different weather conditions were calculated. The result of the comparison between the GNSS- retrieved PWV and Radiosonde-PWV is explained in the last section of this paper.

scholarly journals An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Fang-Cheng Zhou ◽  
Xiaoning Song ◽  
Pei Leng ◽  
Hua Wu ◽  
Bo-Hui Tang
Keyword(s):  
Water Vapor ◽  
Root Mean Square Error ◽  
Land Surface ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Passive Microwave ◽  
Retrieval Algorithm ◽  
Mean Square ◽  
Error Analyses ◽  
Liquid Water In Clouds

Precipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1) land surface emissivities (LSE) at two adjacent frequencies are equal and (2) there are simple parameterizations that relate transmittance, atmospheric effective radiating temperature, and PWV. Error analyses were performed using radiosonde sounding observations from Zhangye, China, and CE318 measurements of Dalanzadgad (43°34′37′′N, 104°25′8′′E) and Singapore (1°17′52′′N, 103°46′48′′E) sites from Aerosol Robotic Network (AERONET), respectively. In Zhangye, the algorithm had a Root Mean Square Error (RMSE) of 4.39 mm and a bias of 0.36 mm on cloud-free days, while on cloudy days there was an RMSE of 4.84 mm and a bias of 0.52 mm because of the effect of liquid water in clouds. The validations in Dalanzadgad and Singapore sites showed that the retrieval algorithm had an RMSE of 4.73 mm and a bias of 0.84 mm and the bigger errors appeared when the water vapor was very dry or very moist.

scholarly journals Spatio-Temporal Variability of the Precipitable Water Vapor over Peru through MODIS and ERA-Interim Time Series

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 192 ◽  
Author(s):  
Katherine Ccoica-López ◽  
Jose Pasapera-Gonzales ◽  
Juan Jimenez
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Radiosonde Data ◽  
North Coast ◽  
Study Region ◽  
The North

Precipitable water vapor (PWV) is a meteorological variable that influences the main processes that occur in the atmosphere. It is not a homogeneous variable, but varies both temporally and spatially according to local conditions. This study analyzes the spatial and temporal variability of the PWV in Peru using MODIS satellite data (MOD05/MYD05 products) during the period 2000 to 2017. MODIS-derived PWV values were complemented with ERA-Interim reanalysis data to take the study period back to 1979. PWV values extracted from MODIS and ERA-Interim were compared against in situ values obtained from five radiosonde stations between the years of 2003 and 2016 (non-continuous data). The study was performed over nine sub-regions of the Peruvian territory: coastal, highland, and jungle sub-regions, which in turn were classified into northern, central and southern regions. The analysis of spatial variability was performed using monthly semivariograms and influencing parameters such as sill and range, whereas the temporal variation was examined by time series of monthly, seasonal, and multi-annual means. The Mann-Kendall test was also applied to determine the presence of trends. The spatial analysis evidenced the heterogeneity of the PWV over the study region, and in most of the sub-regions there was directional variability during the austral summer and austral winter, with the Northeast (NE) and East (E) directions having the greatest spatial variability. The omnidirectional analysis of the sill and range showed that there was a high spatial variability of PWV mainly over the northern and southern jungle, even exceeding the limit area of these sub-regions. The temporal analysis shows that this variability occurs more in the north and center of the jungle and in the north coast, where the content of PWV is higher in relation to other regions, while the central and southern highlands have the lowest values. In addition, the trend test determines that there is a slight increase in PWV for the coast and jungle regions of Peru. Validation analysis using the radiosonde data showed a similar performance of both datasets (MODIS and ERA), with better results for the case of the MODIS product (RMSE < 0.6 cm and R2 = 0.71).

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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