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We will develop an optimized active fire detection algorithm for the new generation of geostationary satellites: Himawari-8, GOES-R, GOES-S, and Meteosat Third Generation (MTG).
Research Topics:
Scientific Support for the GOES-R Mission
Task Leader:
Louis Giglio
CICS Scientist:
Michael Humber
Sponsor:
NOAA ROSES
Published Date:
11/10/2020
This study will merge the Geostationary Lightning Mapper (GLM) and the Lightning Imaging Sensor (LIS) on the International Space Station (ISS) datasets by developing a statistical model to downscale GLM resolution.
Research Topics:
Climate Research, Data Assimilation, and Modeling
Task Leader:
E. Hugo Berbery
CICS Scientist:
Daile Zhang
Sponsor:
NOAA ROSES
Published Date:
11/10/2020
The Advanced Baseline Imager (ABI) data from new GOES-16(R) and GOES-17(S) satelliteswill be used to improve snow cover products.
Research Topics:
Data Fusion and Algorithm Development
Task Leader:
Peter Romanov
Sponsor:
NOAA ROSES
Published Date:
11/10/2020
This project will upgrade the GOES Evapotranspiration and Drought (GET-D) product system software package with the recent improvements to the Atmosphere-Land Exchange Inversion model (ALEXI) model and Advanced Baseline Imagers (ABI) observations.
Research Topics:
Land and Hydrology
Task Leader:
Li Fang
Sponsor:
NOAA ROSES
Published Date:
11/10/2020
This project will continue NOAA’s National Centers for Environmental Information stewardship of ocean exploration data funded and collected by NOAA’s Office of Ocean Exploration and Research (OER).
Research Topics:
Climate Data & Information Records/Scientific Data Stewardship
Task Leader:
E. Hugo Berbery
CICS Scientist:
Anna Lienesch
Sponsor:
NCEI Ocean
Published Date:
11/10/2020
Results: 100 Articles found.