NOAA Operational Geostationary Sea Surface Temperature Products from NOAA and non-NOAA Satellites

1
NOAA Operational Geostationary Sea Surface
Temperature Products from NOAA and non-NOAA
Satellites
Eileen Maturi 1 (GOVERNMENT PRINCIPAL
INVESTIGATOR) , Andy Harris2, Jonathan Mittaz2,
Christopher Merchant3 , Wen Meng4 1NOAA/NESDIS/STA
R, 2 CICS/ESSIC University of Maryland, 3
University of Edinburgh, 4 Perot Systems
SUMMARY
Requirement Generate SST environmental data
records from geostationary satellites NOAA and
non-NOAA imaging instruments to meet user needs
1) to manage marine ecosystems and forecast
their future state 2) determine the impact of sea
surface temperatures on the current state of
biodiversity in the oceans, and how to use our
oceans and coasts 3) the impact of climate
variability and change on the marine
ecosystems 4) analyze and predict ocean
processes Science Can sea surface temperatures
be generated from geostationary platforms with
the same accuracy as polar-orbiting
platforms? Benefit NOAAs MISSION
GOALS ecosystems Forecasting ecosystems
events Developing integrated ecosystem
assessments and scenarios, and building capacity
to support regional management weather and
water Improve NOAAs understanding and
forecast capability in coasts, estuaries, and
oceans climate Understand impacts of climate
variability and change on marine ecosystems to
improve management of marine ecosystems
Geostationary SST Product Coverage
The image is a 24 hour merged composite of the
Operational geostationary SST products generated
by NOAA for the period 26-27 August 2007. This
Image consists of GOES-W (11), GOES-E (12),
Meteosat-9, a gap, and MTSAT-1R data.
In December 2000, the National Oceanic and
Atmospheric Administration (NOAA) and the
National Environmental Satellite Data and
Information Service (NESDIS) began providing
operational geostationary satellite-derived sea
surface temperature (SST) measurements for the
entire Western Hemisphere. Currently, NOAAs
Office of Satellite Data Processing and
Distribution (OSDPD) generates operational SST
retrievals from GOES-11 and 12 satellites as well
as from the Japanese Multi-function Transport
Satellite (MTSAT-1R) and the European Meteosat
Second Generation (MSG) satellite. The satellites
are situated at longitudes 135 W, 75 W, 0 and
140 E respectively, making it possible to
acquire high temporal SST retrievals with
Advanced Very High Resolution Radiometer (AVHRR)
SST - like quality for most of the tropical
mid-latitudes (excluding 60 to 80 degrees east
longitude). The operational data products
include regional hourly and 3-hourly hemispheric
imagery, 24 hour merged composites, SST Level 2
preprocessed (L2P) products (GOES-SST every 1/2
hour for each hemisphere,MTSAT-1R SST L2P full
disk every hour, MSG-SST L2P full disk every
half-hour), a match-up data file for each product
and an 11 km global multi-SST analysis (NOAA-19,
MetOp-A, GOES-E/W, MTSAT-1R and MSG SSTs).
GOES-W GOES-E Meteosat-9
gap MT-SAT 1R
GOES-SST Level 2 Pre-processed Sea Surface
Temperature Products
RETRIEVAL ALGORITHMS
The derivations for each satellite consist of two
steps 1) cloud detection using a Bayesian
Probabilistic Cloud Mask and 2) application of a
radiative transfer based linear regression SST
retrieval. A new physical retrieval algorithm
is being tested for implementation in the 2010.
SURFACE SOLAR IRRADIANCE
AEROSOL OPTICAL DEPTH
WIND SPEED
SST
STANDARD DEVIATION
PROXIMITY CONFIDENCE
BIAS
11 km global multi-SST analysis (NOAA-19,
MetOp-A, GOES-E/W, MTSAT-1R and MSG SSTs)
Level-2 preprocessed SST retrievals are put
into a standard format and ancillary information
is added, including environmental conditions and
retrieval errors. The current GOES-SSTL2P product
is generated every ½ hour for GOES-E W, N S
sectors and the netcdf product file has 22
parameters for each pixel SST, time, latitude,
longitude, satellite zenith angle, aerosol
optical depth, surface solar irradiance, wind
speed, Uncertainty estimates (bias and S.D.),
Proximity Confidence Value, QC flags (including
cloud and land), Ice concentration, Deviation
from analysis SST, Temporal coincidences of
ancillary data c.f. SST observation, Source
codes for ancillary data, Probability of
clear-sky (Bayesian cloud mask). Similar SST
Level-2P products are produced for MTSAT and MSG.
VALIDATION
Science Challenges Adjust errors in retrievals
due to calibration errors while waiting for the
calibration corrections to be implemented. Next
Steps Continue to improve geostationary SST
retrieval methodology Physical Retrieval,
Aerosol corrections, diurnal warming
estimates. Transition Path Through the SPSRB
process implement the physical retrieval
methodology, the aerosol corrections and diurnal
warming estimates into the current geostationary
operational system. The CoastWatch/OceanWatch,
NWS, NMFS, GHRSST, WMO, Coral Reef Watch access
the current geostationary operational system.
All SST retrievals are validated in relation to
the drifting and fixed buoys and the Reynolds
OISST analysis. An automated validation system
exists to quality control the SST retrievals and
uses the operational match up file as an input to
calculate the number of matches, maximum bias,
mean bias on daily, weekly, and monthly
timescales. An further SST reprocessing system
for quality control is part of the validation
system to test and regenerate all SST products
when a retrieval error is discovered or a new
component of the algorithm requires testing