scholarly journals Spatio-Temporal Variations of Precipitable Water Vapor and Horizontal Tropospheric Gradients from GPS during Typhoon Lekima

2021 ◽  
Vol 13 (20) ◽  
pp. 4082
Author(s):  
Manhong Tu ◽  
Weixing Zhang ◽  
Jingna Bai ◽  
Di Wu ◽  
Hong Liang ◽  
...  
Keyword(s):  
Water Vapor ◽  
Mainland China ◽  
Precipitable Water ◽  
Temporal Variations ◽  
Empirical Orthogonal Functions ◽  
Precipitable Water Vapor ◽  
Orthogonal Functions ◽  
Global Data Assimilation System ◽  
Typhoon Center ◽  
Spatio Temporal

GPS data during Typhoon Lekima at 700 stations in China were processed by the Precise Point Positioning (PPP) method. A refined regional Tm model was used to derive the precipitable water vapor (PWV) at these GPS stations. Spatio-temporal variations of PWV with the typhoon process were analyzed. As the typhoon approached, PWV at stations near the typhoon center increased sharply from about 50 mm to nearly 80 mm and then dropped back to about 40–50 mm as the typhoon left. Comparisons of GPS, radiosonde, the Global Data Assimilation System (GDAS) Global Forecast System (GFS) analysis products and ERA5 reanalysis products at four matched GPS-RS stations show overall overestimations of PWV from radiosonde, GFS and ERA5 compared with GPS in a statistical perspective. An empirical orthogonal functions (EOF) analysis of the PWV during the typhoon event revealed some different patterns of variability, with both the first EOF (~36.1% of variance) and second EOF (~30.3% of variance) showing distinctively large anomalies over the typhoon landing locations. The typhoon caused a large horizontal tropospheric gradient (HTG) with the magnitude reaching 5 mm and the direction pointing to the typhoon center when it made a landfall on mainland China. The magnitude and the consistency of the HTG direction decreased overall as the typhoon weakened.

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.

scholarly journals Spatio-Temporal Patterns of Mass Changes in Himalayan Glaciated Region from EOF Analyses of GRACE Data

2021 ◽  
Vol 13 (2) ◽  
pp. 265
Author(s):  
Harika Munagapati ◽  
Virendra M. Tiwari
Keyword(s):  
Temperature Anomaly ◽  
Mass Gain ◽  
Snow Accumulation ◽  
Empirical Orthogonal Functions ◽  
Total Water ◽  
Orthogonal Functions ◽  
Grace Data ◽  
Grace Satellite ◽  
Spatio Temporal ◽  
Gravity Recovery

The nature of hydrological seasonality over the Himalayan Glaciated Region (HGR) is complex due to varied precipitation patterns. The present study attempts to exemplify the spatio-temporal variation of hydrological mass over the HGR using time-variable gravity from the Gravity Recovery and Climate Experiment (GRACE) satellite for the period of 2002–2016 on seasonal and interannual timescales. The mass signal derived from GRACE data is decomposed using empirical orthogonal functions (EOFs), allowing us to identify the three broad divisions of HGR, i.e., western, central, and eastern, based on the seasonal mass gain or loss that corresponds to prevailing climatic changes. Further, causative relationships between climatic variables and the EOF decomposed signals are explored using the Granger causality algorithm. It appears that a causal relationship exists between total precipitation and total water storage from GRACE. EOF modes also indicate certain regional anomalies such as the Karakoram mass gain, which represents ongoing snow accumulation. Our causality result suggests that the excessive snowfall in 2005–2008 has initiated this mass gain. However, as our results indicate, despite the dampening of snowfall rates after 2008, mass has been steadily increasing in the Karakorum, which is attributed to the flattening of the temperature anomaly curve and subsequent lower melting after 2008.

scholarly journals Forecasting Precipitable Water Vapor Using LSTMs

2020 ◽  
Author(s):  
Mayank Jain ◽  
Shilpa Manandhar ◽  
Yee Hui Lee ◽  
Stefan Winkler ◽  
Soumyabrata Dev
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor

Aerosol optical properties and precipitable water vapor column in the atmosphere of Norway

2015 ◽  
Vol 54 (6) ◽  
pp. 1505 ◽  
Author(s):  
Dennis Muyimbwa ◽  
Øyvind Frette ◽  
Jakob J. Stamnes ◽  
Taddeo Ssenyonga ◽  
Yi-Chun Chen ◽  
...  
Keyword(s):  
Optical Properties ◽  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Aerosol Optical Properties
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