Cooperative Institute for Climate & Satellites - Maryland

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Research Topics:

Data Fusion and Algorithm Development
Calibration and Validation
Surface Observation Networks
Future Satellite Programs
Scientific Support of the GOES-R Mission
Scientific Support of the JPSS Mission
Climate Research, Data Assimilation, and Modeling
Climate Data & Information Records/Scientific Data Stewardship
Land and Hydrology
Earth System Modeling from Satellites
National Climate Assessments
Environmental Decision Support Science
Geographical Sciences
Results: 71 Articles found.

Validation of Operational AMSR2 SSTs

Code has been written and tested for AMSR-2 validation and datasets have been procured for a designated test period.  Initial results indicate the performance of GAASP processing chain is meeting requirements.  Interesting features are noted in data that illustrate the importance of understanding real SST signals from underlying geophysical processes that might be incorrectly interpreted as algorithm error.

Research Topics: Data Fusion and Algorithm Development
Task Leader: Andy Harris
CICS Scientist: Andy Harris
Sponsor: JPSSO
Published Date: 7/25/2014

GOES-R Risk Reduction – Ocean Dynamics

The 4D-Var regional modeling and data assimilation system has been successfully ported from Oregon State University to the S4 supercomputer hosted at UW-Madison.  A graduate student has been retained and is being trained in the use of the S4 and other NOAA computing systems, and in running the ocean model.

Research Topics: Data Fusion and Algorithm Development
Task Leader: Andy Harris
CICS Scientist: Andy Harris
Sponsor: NESDIS GOESPO & STAR
Published Date: 7/25/2014

Assimilation of VIIRS SSTs and Radiances into Level 4 Analyses

Code has been written and tested to ingest all three variants of the ACSPO VIIRS SST data format.  Trial runs have shown a significant increase in data coverage obtained from VIIRS, although biases are somewhat characteristic of previous AVHRR products.  This is not surprising since the current ACSPO algorithms are essentially identical to those developed for AVHRR, i.e. they do not take advantage of additional channels in the retrieval.

Research Topics: Data Fusion and Algorithm Development
Task Leader: Andy Harris
CICS Scientist: Andy Harris
Sponsor: JPSSO
Published Date: 7/25/2014

Enhancing Soil Moisture Data and their Applications for Agricultural and Numerical Weather Forecasts

As part of the NASA project team, we are tasked to provide global soil moisture data product to USDA Foreign Agricultural Service (FAS) and NOAA NWS-NCEP weather forecast models. In the past years, we continuously provided daily satellite soil moisture data product from European Space Agency’s Soil Moisture Ocean Salinity (SMOS) satellite to the USDA-FAS for their world crop forecast analysts.

Research Topics: Data Fusion and Algorithm Development
Task Leader: Christopher Hain
CICS Scientist: Christopher Hain
Sponsor: NESDIS STAR
Published Date: 7/25/2014

Development of Global Soil Moisture Product System (SMOPS)

We have upgraded SMOPS to ingest soil moisture retrievals from Metop-B ASCAT. To prepare the upgrade, Metop-B ASCAT soil moisture data are evaluated against Metop-A ASCAT data. SMOPS is the NOAA-NESDIS Global Soil Moisture Operational Product System. It provides soil moisture observations from microwave satellite for use in NWS-NCEP weather and climate prediction models.

Research Topics: Data Fusion and Algorithm Development
Task Leader: Christopher Hain
CICS Scientist: Christopher Hain
Sponsor: NESDIS STAR
Published Date: 7/25/2014
Results: 71 Articles found.
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