Water Vapour Weighted Mean Temperature Model for GPS-Derived Integrated Water
Vapour in Peninsular Malaysia

Musa, Tajul Ariffin; Mazlan, M. Hasbullah; Opaluwa, Yusuf Drisu; Musliman, Ivin Amri; Radzi, Zahira Mohd

doi:10.5194/isprs-archives-xlii-4-w5-127-2017

Cited by 4 publications

(1 citation statement)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Musa et al (2017) authors revealed that PWV measurements from both the regression line (Tm -Ts) exhibit a high degree of agreement. Tm and Ts are warm throughout the year, with just a 1.0 -2.0 K fluctuation.…”

Section: Comparison Of Tm Calculationmentioning

confidence: 95%

Estimation of precipitable water vapor from ground based GPS measurements and Radiosonde in Southeast Asian-Pacific

Malik¹

2023

Acta Geodynamica Et Geomaterialia

View full text Add to dashboard Cite

Climate change research is an important field of study. Because of the refractivity of the earth's atmosphere, Global Positioning System (GPS) signals have a significant delay, making them a suitable approach for studying atmospheric weather phenomena. The zenith wet delays (ZWD) can be determined using GPS measurements. The capability of computing precipitable water vapour (PWV) from GPS signals is helpful to comprehend unique weather events. There are two objective for this work, firstly, zenith tropospheric delay (ZTD) is estimated for total of 20 GPS stations. Results demonstrated that the average root mean square (RMS) and standard deviation (STD) of ZTD estimate is 2440.1 and 63.6 mm, respectively. We compared the calculated ZTD values with the ZTD products offered by Center of Orbit Determination in Europe (CODE) products. Comparison results showed that the average difference and STD between estimates of ZTD and CODE products is 4.84 and 3.77 mm, respectively. Secondly, estimates of ZWD is used to determine the PWV. According to the PWV estimation results, the average RMS and STD value is 35.89 and 11.14 mm, respectively. PWV estimates for 10 IGS sites are compared with Radiosonde (RS) data. Comparison results show that the GPS-PWV estimates and RS data that the R's squared, bias and difference in STD is, respectively, 0.94, -0.24 and 3.99 mm. In addition, the differences of STD between RS-PWV and GPS-PWV is 3.88 and 4.08 mm, at UTC 00:00 and UTC 12:00, respectively.

show abstract

Section: Comparison Of Tm Calculationmentioning

confidence: 95%

Estimation of precipitable water vapor from ground based GPS measurements and Radiosonde in Southeast Asian-Pacific

Malik¹

2023

Acta Geodynamica Et Geomaterialia

View full text Add to dashboard Cite

show abstract

GNSS meteorology in Egypt: Modeling weighted mean temperature from radiosonde data

Elhaty

Abdelfatah

Mousa

et al. 2019

Alexandria Engineering Journal

View full text Add to dashboard Cite

Artificial neural network for improving the estimation of weighted mean temperature in Egypt

Abdelfatah

2021

Journal of Applied Geodesy

View full text Add to dashboard Cite

One of the most important parameters in meteorological data is the Precipitable Water Vapor (PWV). It can be measured by radiosonde stations (RS), but the fact is that RS are not available in all times. Therefore, GNSS satellite signals are considered an accurate function to compute it within a conversation factor. The conversation factor depends on the weighted mean temperature ( T m {T_{m}} ) which is non-measurable. In this research, a new idea to estimate T m {T_{m}} is provided, which can potentially contribute to the GNSS meteorology. The T m {T_{m}} was designed, including six RS, over one year in Egypt as input parameters. The machine learning (ML) model has been utilized in the design (IBM SPSS Statistics 25 package). The new model needs to collect the day of year (DOY), site location information and surface temperature to predict the T m {T_{m}} . The results of ML model and four other empirical models (Bevis et al., Wayan and Iskanda, Yao and Elhaty et al. models) are compared. The validation work is carried out, using the radiosonde data, and results indicate that the new T m {T_{m}} model can achieve the best performance with RMS of 1.7 K.

show abstract

Water Vapour Weighted Mean Temperature Model for GPS-Derived Integrated Water Vapour in Peninsular Malaysia

Cited by 4 publications

References 25 publications

Estimation of precipitable water vapor from ground based GPS measurements and Radiosonde in Southeast Asian-Pacific

Estimation of precipitable water vapor from ground based GPS measurements and Radiosonde in Southeast Asian-Pacific

GNSS meteorology in Egypt: Modeling weighted mean temperature from radiosonde data

Artificial neural network for improving the estimation of weighted mean temperature in Egypt

Contact Info

Product

Resources

About