Estimation water vapor content using the mixing ratio method and validated with the ANFIS PWV model

2017 International Conference on Space Science and Communication

物理学;无线电电子学

Suparta, W.^1 ; Alhasa, K.M.^1 ; Singh, M.S.J.^2

Space Science Centre (ANGKASA), Institute of Climate Change Universiti Kebangsaan Malaysia, Bangi, Selangor Darul Ehsan

43600, Malaysia^1

Dept of Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor Darul Ehsan

43600, Malaysia^2

关键词: Adaptive neuro fuzzy inference systems (ANFIS);    Confidence levels;    Malaysia;    Mixing ratios;    Precipitable water vapor;    Surface meteorological data;    Water vapor contents;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/852/1/012041/pdf
DOI  :  10.1088/1742-6596/852/1/012041

来源: IOP

【 摘 要 】

This study reported the comparison between water vapor content, the surface meteorological data (pressure, temperature, and relative humidity), and precipitable water vapor (PWV) produced by PWV from adaptive neuro fuzzy inference system (ANFIS) for areas in the Universiti Kebangsaan Malaysia Bangi (UKMB) station. The water vapor content value was estimated with mixing ratio method and the surface meteorological data as the parameter inputs. The accuracy of water vapor content was validated with PWV from ANFIS PWV model for the period of 20-23 December 2016. The result showed that the water vapor content has a similar trend with the PWV which produced by ANFIS PWV model (r = 0.975 at the 99% confidence level). This indicates that the water vapor content that obtained with mixing ratio agreed very well with the ANFIS PWV model. In addition, this study also found, the pattern of water vapor content and PWV have more influenced by the relative humidity.