Download - nesdis CoRP , SOCD and GOES-R3
NESDIS CORP, SOCD AND GOES-R3
Ingrid GuchDirector, Cooperative Research ProgramNOAA/NESDISCICS Science MeetingSep 8-9 2010
Cooperative Research Program (“CoRP”) Challenge
To be a Coast-to-coast government and university-based research coalition for remote sensing in the environment
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 Secondary Secondary Secondary
CIMSS at University of Wisconsin Secondary Primary Secondary Secondary Secondary
CIRA at Colorado State University Secondary Secondary Primary Secondary Secondary
CICS at University of Maryland and
UNC Secondary Secondary Secondary Primary Secondary
CREST at City College New York Secondary Secondary Secondary Secondary Primary
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)
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
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
www.corpblogspot.org “End of Year” Program GOES-R Risk Reduction Jobs for NESDIS and STAR partners
Ultimate Goal
Highly successful scientists and science managers making revolutionary progress using the next generation of earth observation satellites for societal benefits
SATELLITE OCEANOGRAPHY &CLIMATOLOGY DIVISION (SOCD)
NOAA-NESDIS-STAR
Dr. Paul M. DiGiacomo, SOCD ChiefEmail: [email protected]
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
http://ibis.grdl.noaa.gov/SAT/slr
Sea Level Rise Budget
SLtotal = SLsteric + SLmass
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 observationsRed lines:Inferred from budget equationLeuliette and Miller [GRL,2009].
Diffuse attenuation coefficient Kd is a measure of the water turbidity (clear water with low Kd). A new satellite Kd 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
0.1
1
10
0.1 1 10
MO
DIS
Kd(
PAR
) (m
-1)
In Situ Kd(PAR) (m -1)
New Model, Chesapeake Bay DataMODIS SWIR Derived R(645) for Kd(PAR)
1:1 1:2
2:1
(d)
291 Data: Mean Ratio = 0.958
Coral Reef WatchMission: 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 reefshttp://coralreefwatch.noaa.gov/
POES-GOES Blended SST Analysis
December 31 2007
RTG_HR SST
December 31 2007
Daily OI SST
December 31 2007
POES_GOES
Point-for-point comparison with RTG_HR shows S.D. of 0.45 KComparison with Reynolds ¼° daily OI has S.D. of 0.65 KOnly non-MW SST analysis to show “split-Gulf Stream” feature
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
http://www.star.nesdis.noaa.gov/sod/sst/squam/
SST: Near-real time web-based SST Quality Monitor (SQUAM): Used by NESDIS, NCEP, NAVO, Meteo
FRANCE, GHRSSTThe 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
Coastal Optical Characterization Experiment (COCE) – participated in Ligurian Sea Cal/Val NATO Cruise in August/September 2010. 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
GOES-R RISK REDUCTION
Ingrid GuchDirector, Cooperative Research ProgramNOAA/NESDISCICS Science MeetingSep 8-9 2010
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
Capable, informed users
Flexible inventive providers
Knowledge brokers that recognize new connections between capabilities and needs
Champions of new opportunities
Vision for GOES-R3
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
R2O ActivitiesR2O Assessments
“R2O”
Ops and Maintenance ActivitiesOps and Maintenance Assessments
“O”
Basic Research
“R”
R2O
Focused R&DResearch Assessments“R2(R2O)”
R2O ActivitiesR2O Assessments
“R2O”
Ops and Maintenance ActivitiesOps and Maintenance Assessments
“O”
Basic Research
“R”
Ops and Maintenance Integration and Assessments“(R2O)2O”
Breaking down R2O Components
Focused R&DResearch Assessments“R2(R2O)”
R2O ActivitiesR2O
Assessments“R2O”
Ops and Maintenance ActivitiesOps 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
FY11 proposals due Oct 1st
www.corpblogspot.org (click funding opportunities)
Combined Geo/Leo High Latitude Atmospheric Motion Vectors
50o
70o
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