Towards the comparison of satellite- and ground-based cloud amount over China

Yawen Zhang; Hui Lu; Jun Cai

doi:10.1117/12.2068979

8 November 2014 Towards the comparison of satellite- and ground-based cloud amount over China

Yawen Zhang, Hui Lu, Jun Cai

Proceedings Volume 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V; 92590A (2014) https://doi.org/10.1117/12.2068979
Event: SPIE Asia-Pacific Remote Sensing, 2014, Beijing, China

Abstract

Cloud Amount (CA) is the dominant modulator of radiative fluxes. Satellite and ground observations act as two main sources for the global cloud climatology. In this study, we analyze the comparability of these two datasets over China. The MODIS cloud mask products which provide the pixel-based flag of cloudy or not is used to calculate satellite derived CA, while ground based CA is obtained from Synop stations which are visually estimated by observers. To match surface observations with MODIS data for comparison, a prerequisite is to determine the Effective Field of View (EFOV) of the ground observer. Instead of setting a constant EFOV, we firstly vary the radius of FOV for correlation analysis and find that a radius of 60 km is most useful for comparison purpose. The correlation coefficient ranges from 0.53 to 0.81 for different seasons, suggesting a significant relationship between satellite and ground based CA. Secondly, based on the estimated EFOV over China, an index of Effective Cloud Observation Density (ECOD) is introduced to evaluate the spatial distribution of Synop stations and the results show that western China has much lower ECOD than the eastern part. Finally, cloud fraction map and frequency distribution are applied to compare the two CA datasets and both indicate that MODIS derived and surface observed CA have similar spatial distribution, while obvious difference occurs at both high and low values.

Citation Download Citation

Yawen Zhang, Hui Lu, and Jun Cai "Towards the comparison of satellite- and ground-based cloud amount over China", Proc. SPIE 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V, 92590A (8 November 2014); https://doi.org/10.1117/12.2068979

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