The relationship between precipitable water vapor and surface humidity in New Zealand

1977 ◽  
Vol 26 (2-3) ◽  
pp. 197-212 ◽  
Author(s):  
Stanton E. Tuller
Keyword(s):  
Water Vapor ◽  
New Zealand ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
The Relationship

scholarly journals The relationship between raining and GPS – precipitable water vapor

2019 ◽  
Vol 1380 ◽  
pp. 012142
Author(s):  
Nithiwatthn Choosakul ◽  
Sarawut Jaiyen ◽  
Umpon Jairuk ◽  
Janthanee Authisin
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
The Relationship

The Transmittance to Direct Irradiance due to Absorption by Precipitable Water Vapor in the Atmosphere

2014 ◽  
Vol 979 ◽  
pp. 7-10 ◽  
Author(s):  
Sayan Phokate ◽  
Nitiphat Pisutthipong
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Radiation Absorption ◽  
Chiang Mai ◽  
Climatological Data ◽  
The Difference ◽  
High Level ◽  
The Relationship

This research aims to calculate the transmittance to direct irradiance due to absorption by precipitable water vapor in the atmosphere of Thailand, estimation of the absorptance by water vapor in the atmosphere and calculate the precipitable water vapor in the atmosphere. The precipitable water vapor in the atmosphere was calculated from upper air checking data relative humidity and temperature. The data were collected at four meteorological monitoring station located in Chiang Mai, Ubon Ratchathani, Bangkok and Songkhla during the years 1991-2010. The figures for precipitable water vapor obtained from this investigation were used to formulate a mathematical model relating to the precipitable water from four stations with surface climatological data, relative humidity and temperature at the same stations. The result showed that the relationship has a relatively high level of reliability. The precipitable water vapor obtained from upper air nearly is equal to the value from the model. The difference in the Root Mean Square Error (RMSE) is equal to 0.250 cm. Then, the researcher used a model to calculate the amount of precipitable water vapor at 85 meteorology stations nationwide. The result showed that the precipitable water vapor was less in the dry (November to March) and relative high in the rainy season (April-October). The average per year was found to be 4.559 cm. When analyzing the solar radiation absorption by water vapor in the atmosphere, found that the absorption is more or less depending on the precipitable water vapor in the atmosphere, which has an average annual as 15.53 percent. The transmittance to direct irradiance due to absorption average per year was found to be 84.51 percent.

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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