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

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: Paul.DiGiacomo@noaa.gov

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 equation

Leuliette 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 TurbidityOcean Color Remote Sensing of Water Turbidity

0.1

1

10

0.1 1 10

MO

DIS

Kd(P

AR

) (m

-1)

In Situ Kd(PAR) (m-1

)

New Model, Chesapeake Bay DataMODIS SWIR Derived R(645) for Kd(PAR)

1:11:2

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 Activities

R2O Assessments

“R2O”

Ops and Maintenance Activities

Ops and Maintenance Assessments

“O”

Basic Research

“R”

R2O

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

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

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