Interactive comments on “Precipitable water vapor content from ESR/SKYNET Sun-sky radiometers: validation against GNSS/GPS and AERONET over three different sites in Europe” by M. Campanelli et al.

2017 ◽  
Author(s):  
Anonymous
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Water Vapor Content

scholarly journals Precipitable water vapor content from ESR/SKYNET Sun-sky radiometers: validation against GNSS/GPS and AERONET over three different sites in Europe

2017 ◽  
Author(s):  
Monica Campanelli ◽  
Alessandra Mascitelli ◽  
Paolo Sanò ◽  
Henri Diémoz ◽  
Victor Estellés ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Climatic Conditions ◽  
Precipitable Water Vapor ◽  
Water Vapor Content ◽  
Atmospheric Parameter ◽  
High Temporal Resolution ◽  
Photometric Calibration ◽  
Wide Range ◽  
Calibration Parameters

Abstract. The estimation of the precipitable water vapor content (W) with high temporal and spatial resolution is of great interest in both meteorological and climatological studies. Several methodologies based on remote sensing techniques have been recently developed, in order to obtain accurate and frequent measurements of this atmospheric parameter. Among them, the relative low cost and easy deployment of sun-sky radiometers, or sun-photometers, operating in several international networks, allowed the development of automatic estimations of W from these instruments with high temporal resolution. However the great problem of this methodology is the estimation of the sun-photometric calibration parameters. The objective of this paper is to validate a new methodology based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance at 940 nm are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site. To obtain the calibration parameters some simultaneously seasonal independent measurements of W taken over a large range of solar zenith angle and covering a wide range of W, are needed. In this work yearly GNSS/GPS dataset were used for obtaining a table of photometric calibration constants and the methodology was applied and validated in three European ESR-SKYNET network sites, characterized by different atmospheric and climatic conditions: Rome, Valencia and Aosta. Results were validated against the GNSS/GPS and AErosol Robotic NETwork (AERONET) W estimations. In both the validations the agreement was very high with a percentage RMSD of about 6 %, 13 % and 8 % in the case of GPS intercomparison at Rome, Aosta and Valencia, respectively, and of 8 % in the case of AERONET comparison in Valencia. Analysing the results by W classes, the present methodology was found to clearly improve W estimation at low W content when compared against AERONET in term of %Bias, bringing the agreement with the GPS (considered the reference one), from a %Bias of 5.76 to 0.52.

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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