Fusion of surface ceilometer data and satellite cloud retrievals in 2D mesh interpolating model with clustering

Konstantin Khlopenkov; Douglas Spangenberg; William L. Smith Jr.

doi:10.1117/12.2533370

9 October 2019 Fusion of surface ceilometer data and satellite cloud retrievals in 2D mesh interpolating model with clustering

Konstantin Khlopenkov, Douglas Spangenberg, William L. Smith Jr.

Author Affiliations +

Proceedings Volume 11152, Remote Sensing of Clouds and the Atmosphere XXIV; 111521F (2019) https://doi.org/10.1117/12.2533370
Event: SPIE Remote Sensing, 2019, Strasbourg, France

Abstract

For accurate cloud ceiling information, a data fusion approach is proposed that utilizes satellite data to extend surface station information to much wider areas. Cloud base height (CBH) retrieved from satellite observations provides for much larger spatial coverage and higher resolution. The direct comparison of GOES-16 CBH with surface station ceiling yields a local bias that has to be corrected for in the initial GOES-16 cloud base information. This sparsely sampled bias correction presents an irregular 2D mesh of control points, which is then interpolated by constructing a continuous smooth field using polyharmonic splines. The influence of remote stations is restricted by grouping the control points into clusters depending on an effective distance. This cluster-based approach allows for constructing separate spline surfaces corresponding to physically different clouds. The obtained continuous bias correction function is then applied to the entire GOES-16 pixel level CBH except for areas far away from surface stations in data sparse regions such as offshore. The described method is currently being tested using daytime-only observations over the central and eastern United States. Overall, this approach has potential to provide more accurate, high spatial resolution cloud ceiling information for the aviation community.

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Konstantin Khlopenkov, Douglas Spangenberg, and William L. Smith Jr. "Fusion of surface ceilometer data and satellite cloud retrievals in 2D mesh interpolating model with clustering", Proc. SPIE 11152, Remote Sensing of Clouds and the Atmosphere XXIV, 111521F (9 October 2019); https://doi.org/10.1117/12.2533370

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KEYWORDS

Clouds

Satellites

Data modeling

Data fusion

Earth observing sensors

Satellite imaging

Spatial resolution

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