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NASA NTRS · Poster
Combining GOES-16 and Surface Ceilometer Data to Improve Cloud Ceiling Estimates over the U.S.
Attribution
This is the abstract and citation. Full text lives at NASA NTRS — we link out rather than host. All credit to the authors and Langley Research Center.
Abstract
Verbatim from NASA NTRS. Not paraphrased, not summarized.
To better address the low ceiling hazard to aviation, a hybrid approach is taken that utilizes satellite data to extend cloud ceiling information contained in surface station observations to much wider areas. Real-time correlative information between satellite cloud base and cloud ceiling information at surface stations are developed based on cloud type. The direct comparison of GOES-16 cloud base with surface station ceiling allows for a bias correction of the initial GOES-16 cloud base field to be applied for each identified cloud type. For any areas where certain cloud types are present in satellite retrievals but not at surface stations, low-level NWP model RH can be used in place of ceilometer data to bias correct GOES-16. Distanceweighted interpolation methods are applied to the ceilometer data and for combining ceilometer cloud ceiling with GOES-16; the cloud base from just GOES-16 is used far away from surface stations in data sparse regions such as offshore. The cloud ceilings in the hybrid interpolated product are restricted to be above the terrain height.
Authors
- Douglas A Spangenberg Science Systems and Applications (United States)
- William L Smith Langley Research Center
- Konstantin Khlopenkov Science Systems and Applications (United States)
Citation: Douglas A Spangenberg, William L Smith , Konstantin Khlopenkov (2019). Combining GOES-16 and Surface Ceilometer Data to Improve Cloud Ceiling Estimates over the U.S.. Langley Research Center. NASA NTRS ID 20200003791. https://ntrs.nasa.gov/citations/20200003791 ↗