GPS-Derived Slant Water Vapor for Cloud Monitoring in Singapore

This paper presents a GPS-derived slant water vapor technique for cloud monitoring in Singapore. The normalized slant wet delay (SWD) and slant water vapor (SWV) are introduced. The suitability of the normalized SWV over SWV for cloud monitoring is demonstrated, as it is not very sensitive to the satellite elevation angle. For better illustration and representation of the spatial distribution of the normalized SWV, the skyplot is discretized into different cells based on the azimuth and elevation angles to produce the spatial plot. The spatial plots are analyzed for cloud monitoring and compared alongside the sky images. The results show that the spatial plots of normalized SWV are generally consistent with the cloud formation observed in the sky images, hence demonstrating their usefulness for cloud monitoring. The probability distribution of the normalized SWV associated with cloudy and clear sky conditions is also analyzed, which shows that the mean values of normalized SWV associated with the former are higher. Finally, the time series of the normalized SWV is explored in relation to the solar irradiance. It is shown that the time series and spatial plots of normalized SWV are also consistent with the ratio of clear sky to measured irradiance.

Automated summary

This paper presents a GPS-derived slant water vapor technique for cloud monitoring in Singapore. The normalized slant wet delay (SWD) and slant water vapor (SWV) are introduced, and their suitability for cloud monitoring is demonstrated. The spatial plots of normalized SWV show consistency with cloud formation observed in sky images, and the probability distribution of normalized SWV associated with cloudy and clear sky conditions is analyzed. The time series of normalized SWV is also explored in relation to solar irradiance.