scholarly journals GPS Precipitable Water Vapor Estimations over Costa Rica: A Comparison against Atmospheric Sounding and Moderate Resolution Imaging Spectrometer (MODIS)

Climate ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 63 ◽  
Author(s):  
Polleth Campos-Arias ◽  
Germain Esquivel-Hernández ◽  
José Francisco Valverde-Calderón ◽  
Stephanie Rodríguez-Rosales ◽  
Jorge Moya-Zamora ◽  
...  

The quantification of water vapor in tropical regions like Central America is necessary to estimate the influence of climate change on its distribution and the formation of precipitation. This work reports daily estimations of precipitable water vapor (PWV) using Global Positioning System (GPS) delay data over the Pacific region of Costa Rica during 2017. The GPS PWV measurements were compared against atmospheric sounding and Moderate Resolution Imaging Spectrometer (MODIS) data. When GPS PWV was calculated, relatively small biases between the mean atmospheric temperatures (Tm) from atmospheric sounding and the Bevis equation were found. The seasonal PWV fluctuations were controlled by two of the main circulation processes in Central America: the northeast trade winds and the latitudinal migration of the Intertropical Convergence Zone (ITCZ). No significant statistical differences were found for MODIS Terra during the dry season with respect GPS-based calculations (p > 0.05). A multiple linear regression model constructed based on surface meteorological variables can predict the GPS-based measurements with an average relative bias of −0.02 ± 0.19 mm/day (R2 = 0.597). These first results are promising for incorporating GPS-based meteorological applications in Central America where the prevailing climatic conditions offer a unique scenario to study the influence of maritime moisture inputs on the seasonal water vapor distribution.

2021 ◽  
Vol 13 (3) ◽  
pp. 502
Author(s):  
Eva E. Borbas ◽  
Paul W. Menzel

This paper compares the tropospheric moisture data records derived from High-resolution Infrared Radiation Sounder (HIRS) and Moderate Resolution Imaging Spectro-radiometer (MODIS) measurements from the years 2003 through 2013. Total Precipitable Water Vapor (TPW) and Upper Tropospheric Precipitable Water Vapor (UTPW) are derived using the infrared spectral bands in the CO2 and H2O absorption bands as well as in the atmospheric windows. Retrieval of TPW and UTPW uses a statistical regression algorithm performed using clear sky radiances (and Brightness Temperatures) measured over land and ocean for both day and night. The TPW and UTPW seasonal cycles of HIRS and MODIS observations are found to be in synchronization with zonal mean values for one degree latitude bands within 2.0 mm and 0.07 mm, respectively.


2019 ◽  
Vol 3 ◽  
pp. 741
Author(s):  
Wedyanto Kuntjoro ◽  
Z.A.J. Tanuwijaya ◽  
A. Pramansyah ◽  
Dudy D. Wijaya

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.


2017 ◽  
Vol 2 (6) ◽  
Author(s):  
Yaseen Kadhim Abbas Al-Timimi ◽  
Ali Challob Khraibet

Aerosol Optical Depth (AOD) is the measure of aerosol distributed with a Column of air from earth’s surface to the top of atmosphere, in this study, temperature variation of aerosol optical depth (AOD) in Baghdad was analyzed Moderate Resolution Imaging Spectrometer (MODIS) from Terra and its relationship with temperature for the period 2003 – 2015 were examined. The highest values for mean seasonal AOD were observed in spring and summer and the maximum AOD values ranged from 0.50 to 0.58 by contrast minimum AOD values ranging from 0.30 to 0.41 were found in winter and autumn. Results of study also showed that the temperature (max., min., mean air temperature and DTR) have a strong correlation with AOD (0.82, 0.83, 0.82 and 0.65) respectively.


2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha

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.


Sign in / Sign up

Export Citation Format

Share Document