Ingrid Guch
Director, Cooperative Research Program
NOAA/NESDIS
CICS Science Meeting
Sep 8-9 2010
NESDIS CORP, SOCD AND GOES-R3
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
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
Secondary
Secondary
Secondary
Secondary
CREST at City
College New York
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)
4
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 Chief
Email: 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 observations
Red lines:
Inferred from budget equation
Leuliette and Miller [GRL,2009].
Ocean Color Remote Sensing of Water Turbidity
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
10
New Model, Chesapeake Bay Data
d (PAR)
291 Data: Mean Ratio = 0.958
-1
M O D IS K d (P AR ) (m )
MODIS SWIR Derived R(645) for K
1
(d)
2:1
1:1
1:2
0.1
0.1
1
In Situ K d (PAR) (m
10
-1
)
Coral Reef Watch
Mission: To provide remote sensing tools for the conservation of coral reef
ecosystems
• 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
http://coralreefwatch.noaa.gov/
Bleaching Alert Areas
POES-GOES Blended SST Analysis
December 31 2007
Daily
OI SST
RTG_HR
SST
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
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
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
http://www.star.nesdis.noaa.gov/sod/sst/squam/
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 Station Locations
Tentative glider mission plans
Ingrid Guch
Director, Cooperative Research Program
NOAA/NESDIS
CICS Science Meeting
Sep 8-9 2010
GOES-R RISK REDUCTION
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
Vision for GOES-R3

Capable, informed users

Flexible inventive providers

Knowledge brokers that recognize new connections between capabilities
and needs

Champions of new opportunities
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
Basic Research
Ops and
Maintenance
Activities
“R”
Ops and
Maintenance
Assessments
“O”
R2O Activities
R2O Assessments
“R2O”
R2O
Basic Research
Ops and
Maintenance
Activities
“R”
Ops and
Maintenance
Assessments
“O”
Focused R&D
Research
Assessments
“R2(R2O)”
R2O Activities
R2O Assessments
“R2O”
Ops and
Maintenance
Integration and
Assessments
“(R2O)2O”
Breaking down R2O Components
Basic Research
Ops and
Maintenance
Activities
“R”
Ops and
Maintenance
Assessments
“O”
Focused R&D
Research
Assessments
“R2(R2O)”
R2O Activities
R2O Assessments
“R2O”
Ops and
Maintenance
Integration and
Assessments
“(R2O)2O”
Scope of GOES-R Risk Reduction
Breaking down R2O Components
FY11 proposals due Oct 1st
www.corpblogspot.org
(click funding opportunities)
Combined Geo/Leo High Latitude Atmospheric Motion Vectors
Geostationary satellites provide Atmospheric Motion Vectors (AMV) equatorward of
~60° latitude; polar satellites provide AMVs poleward of ~70° latitude.
50o
70o
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
Animation: Example of winds from composite
-9, FY-2C, MTSAT-1R, Kalpana-1) and Leo
GEO/LEO satellite data over Antarctica.
satellites (NOAA-15 through NOAA-19, MetopA, NASA’s Terra and Aqua).
Investigators: Matthew Lazzara – PI (SSEC), Dave Santek (CIMSS),
Chris Velden (CIMSS), Jeff Key (STAR),
Jaime Daniels (STAR)
Slide courtesy of Matthew Lazzara/SSEC