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Ingrid Guch Director, Cooperative Research Program NOAA/NESDIS CICS Science Meeting Sep 8-9 2010.

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Presentation on theme: "Ingrid Guch Director, Cooperative Research Program NOAA/NESDIS CICS Science Meeting Sep 8-9 2010."— Presentation transcript:

1 Ingrid Guch Director, Cooperative Research Program NOAA/NESDIS CICS Science Meeting Sep

2 Cooperative Research Program (“CoRP”) Challenge To be a C oast-to-coast government and university-based research coalition for remote sensing in the environment

3 The Federal Side  Three Federal Branches collocated with universities  Regional Atmospheric Mesoscale Meteorology Branch at CSU  Advanced Satellite Products Branch at UW  Satellite Climate Studies Branch at UMD

4 The Academic Side Ocean Analysis and Prediction Atmosphere Analysis Atmosphere Prediction Climate Analysis and Prediction Ocean Atmosphere Climate Outreach and workforce planning CIOSS at Oregon State University Primary Secondary CIMSS at University of Wisconsin Secondary Primary Secondary CIRA at Colorado State University Secondary Primary Secondary CICS at University of Maryland and UNC Secondary Primary Secondary CREST at City College New York Secondary Primary 4 STAR research areas, outreach and workforce planning are touched on by all CIs and CSC. Science areas chosen to match STAR organizational topics (satellite studies in meteorology, ocean and climate)

5 Research Partnerships  Driven by interests, knowledge, abilities, funding, relationships, requirements, challenges  Effectively using the billion-dollar satellite constellation is a complex, multi-disciplinary problem that requires partnerships  Limited funding and resources  Limited time  Partnerships with the international community, government and non-government organizations and the private sector are as critical as federal/academic partnerships, but not the focus of current CoRP Program

6 CoRP Engagement Strategies  Collocation of scientific branches with universities  Day to day interactions extremely beneficial to both NOAA and Universities  Annual Directors meeting for strategic planning  STAR/NCDC/CIRA/CIMSS/CICS/CIOSS/CREST  Satellite Algorithm Test Bed, National Climate Service and Satellite Data Assimilation current topics of high interest  Annual Science Symposium  Student and Early Career Scientist exchanges  Internal Funding Opportunity Blog  “End of Year” Program  GOES-R Risk Reduction  Jobs for NESDIS and STAR partners

7 Ultimate Goal  Highly successful scientists and science managers making revolutionary progress using the next generation of earth observation satellites for societal benefits

8 Dr. Paul M. DiGiacomo, SOCD Chief Laboratory for Satellite Altimetry (LSA) Dr. Laury Miller, LSA Chief Marine Ecosystems and Climate Branch (MECB) Dr. Celso Barrientos, MECB Chief (Acting) Ocean Sensors Branch (OSB) Dr. Alexander “Sasha” Ignatov, OSB Chief

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10 Sea Level Rise Budget SL total = SL steric + SL mass The rate of sea level rise measured by Jason-1 and Jason-2 is consistent with the rate of rise from the combination of steric sea level from Argo profiles and ocean mass inferred from the GRACE gravity mission. Blue lines: Direct observations Red lines: Inferred from budget equation Leuliette and Miller [GRL,2009].

11 Diffuse attenuation coefficient K d is a measure of the water turbidity (clear water with low K d ). A new satellite K d product developed by SOCD can provide quantitative assessments and monitoring of coastal water quality, especially in important regions such as Chesapeake Bay Ocean Color Remote Sensing of Water Turbidity

12 Coral Reef Watch Mission: To provide remote sensing tools for the conservation of coral reef ecosystems Bleaching Alert Areas Climate Change –One of NOAA’s top 3 reef threats –High temperatures cause coral bleaching Coral Reef Watch Products –Help resource managers conserve coral reefs

13 POES-GOES Blended SST Analysis December RTG_HR SST December Daily OI SST December POES_GOES Point-for-point comparison with RTG_HR shows S.D. of 0.45 K Comparison with Reynolds ¼° daily OI has S.D. of 0.65 K Only non-MW SST analysis to show “split-Gulf Stream” feature

14 STAR ASCAT Wind Product Improvements: North Pacific Extratropical Storm Example QuikSCAT data reveals area of HURRICANE force winds Operational ASCAT wind product detects only GALE force wind. Two wind warning categories lower than the actual winds. New STAR ASCAT wind product detects STORM force wind. One warning category lower

15 SST: Near-real time web-based SST Quality Monitor (SQUAM): Used by NESDIS, NCEP, NAVO, Meteo FRANCE, GHRSST The SST Quality Monitor (SQUAM) is a web-based near-real time tool. Currently, SQUAM monitors AVHRR products from NOAA-16, -17, -18, -19, and MetOp-A. Objectives of SQUAM: Monitor SST products online for self-, cross-product and cross-platform consistency; quickly identify deficiencies & areas for improvement; establish benchmark SST metrics for quick evaluation of SST products in NPOESS/JPSS era SQUAM Tool used by: SST Team to improve quality of SST products NCEP SST Team to validate and improve global analyses products NAVOCEANO, Meteo FRANCE, GHRSS to validate and improve SST products Will be also used for NPOESS/JPSS Cal/Val

16 Coastal Optical Characterization Experiment (COCE) – participated in Ligurian Sea Cal/Val NATO Cruise in August/September This is part of an ongoing inter-comparison of in-situ cal/val technologies that will be used to intercalibrate bio-optical in-situ instruments with the MOBY, and Boussole moorings. Tentative glider mission plans Tentative Station Locations

17 Ingrid Guch Director, Cooperative Research Program NOAA/NESDIS CICS Science Meeting Sep

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19 Improvements over current capabilities: Imager (ABI) - Improved resolution (4x), faster coverage (5X), more bands (3X) and more coverage simultaneously Lightning detection (GLM) - Continuous coverage of total lightning flash rate over land and water Solar/Space Monitoring (SUVI/EXIS/SEISS/MAG) - Better Imager (UV over X-Ray) and improved heavy ion detection, adds low energy electrons and protons

20  Capable, informed users  Flexible inventive providers  Knowledge brokers that recognize new connections between capabilities and needs  Champions of new opportunities Vision for GOES-R3

21 GOES-R Risk Reduction covers items necessary for GOES-R success but not covered by AWG or Proving Grounds  Exploratory Algorithms, New Products and Applications  Multisensor (at least one GOES-R sensor)  Multisatellite (at least one is GOES-R)  Data assimilation and nowcasting  Space Weather  GOES-R demonstrations and training  Demonstrate new GOES-R capabilities to public and private sector users in an efficient, timely manner  “Science Arm” of GOES-R Proving Ground  Training leverages NESDIS Cooperative Institute heritage in Visit, Comet, SHyMet courses as well as NASA/SPoRT center R3 conducts science and outreach activities that are needed for users to fully exploit all GOES-R instruments and capabilities

22 R2O Activities R2O Assessments “R2O” Ops and Maintenance Activities Ops and Maintenance Assessments “O” Basic Research “R” R2O

23 Focused R&D Research Assessments “R2(R2O)” R2O Activities R2O Assessments “R2O” Ops and Maintenance Activities Ops and Maintenance Assessments “O” Basic Research “R” Ops and Maintenance Integration and Assessments “(R2O)2O” Breaking down R2O Components

24 Focused R&D Research Assessments “R2(R2O)” R2O Activities R2O Assessments “R2O” Ops and Maintenance Activities Ops and Maintenance Assessments “O” Basic Research “R” Ops and Maintenance Integration and Assessments “(R2O)2O” Breaking down R2O Components Scope of GOES-R Risk Reduction

25 FY11 proposals due Oct 1 st (click funding opportunities)

26 Combined Geo/Leo High Latitude Atmospheric Motion Vectors 50 o 70 o Animation: Example of winds from composite GEO/LEO satellite data over Antarctica. Investigators: Matthew Lazzara – PI (SSEC), Dave Santek (CIMSS), Chris Velden (CIMSS), Jeff Key (STAR), Jaime Daniels (STAR) Geostationary satellites provide Atmospheric Motion Vectors (AMV) equatorward of ~60° latitude; polar satellites provide AMVs poleward of ~70° latitude. Developing novel ways to fill this gap is the next step in providing complete wind coverage for NWP applications. Data from a variety of satellites are blended and used for AMV generation. The images are composites of the Geo (GOES, Meteosat-7 and -9, FY-2C, MTSAT-1R, Kalpana-1) and Leo satellites (NOAA-15 through NOAA-19, Metop- A, NASA’s Terra and Aqua). Slide courtesy of Matthew Lazzara/SSEC


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