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Ralph Ferraro
NOAA/NESDIS College Park, MD USA
18 November 2014 IPWG Training Workshop 1
A Review of NOAA Mission Goals and why satellites are important
Quick Review of NOAA Products Application Examples ◦ Super Storm Sandy – A hybrid tropical/mid-latitude storm ◦ Climate
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18 November 2014 IPWG Training Workshop
Ecosystems
Climate
Weather & Water
Commerce & Transportation
Supporting NOAA’s Mission
Short term to long term assessments of water is crucial to all of these program goals
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Satellites are particularly useful where ground measurements are: ◦ Not taken or missing Examples – Sparse rain gauges and data delivery failure (maybe caused
by an extreme rainfall event) ◦ Of questionable quality Examples – radar missing offshore rain; radar beam blockage in
mountains ◦ Not possible Example – Open ocean
NESDIS provides operational satellite products of
hydrological parameters for each individual satellite it operates. ◦ GOES – visible and IR based, rapid update ◦ POES – passive MW, 3 satellite, 4 hour global coverage
NOAA also utilizes satellite assets from other agencies
like NASA, DoD, EUMETSAT and JAXA
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Geostationary (Regional, rapid update)
Low Earth Orbiting (Global, 3-6 hourly)
Visible, IR and WV loops Visible, IR and microwave imagery
Rain Rate Rain and Snowfall Rate
Total Precipitable Water – TPW (cloud free)
TPW (all weather; ocean only in some cases)
Snow and Ice Cover Snow cover/water equivalent/ice concentration
Soil Moisture
Blended Products (R2O and O2R)
Blended TPW (with LEO, GPS Met and GEO data) and Rain Rate (LEO)
Ensemble Tropical Rainfall Potential (eTRaP)
NOAA CPC Cloud Morphing Product (CMORPH)
Other products emerging…GOES-R and JPSS programs
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HydroEstimator (H-E) ◦ Legacy NESDIS rainfall product based on rapid update GOES IR
measurements MiRS ◦ Primary passive MW product system that relates CLW and IWP to
surface rain rate NOAA POES, MetOp, DMSP, S-NPP
eTRaP (Ensemble Tropical Rainfall Potential) ◦ Utilizes multiple satellite product snapshots of rainfall ◦ Other agencies across the world have similar products
bTPW ◦ Utilizes multiple satellite, ground and model data for global TPW
(atmospheric rivers) CMORPH ◦ Longer latency, but global derived rainfall product that merges
MW estimates and advects with GEO based cloud motion vectors ◦ Similar to TRMM 3B42, GPM IMERG, JMA GSMaP
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A historic storm for many reasons: ◦ “Perfect storm” - Hurricane +
Nor’easter ◦ Record low pressure at
landfall for MD/DE/NJ (~945 mb)
◦ Record tidal flooding in NY&NJ ◦ Record rain, wind, snow
Loss of life ◦ 250+ in seven countries
Loss of property ◦ $100 Billion?
Permanent changes to coastal regions
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GOES HE 24-hr Rainfall Stage IV 24-hr Rainfall
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Provided by R. Kuligowski, NOAA/NESDIS/STAR
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Provided by S. Boukabara, NOAA/NESDIS/STAR
eTRaP algorithm – E. Ebert (BOM/Australia) ◦ Based on TRaP from Kusselson,
Kidder, et al. Forecast of 24-hour rainfall
potential for tropical systems about to make landfall.
Based on extrapolation of microwave-derived rainfall rates along predicted storm track.
Ensembles improve deterministic forecasts and provide uncertainty information
Produced worldwide and used by operational agencies
Additional ensemble members (GOES, LEO) plus orographic, shear, storm rotation adjustments planned
QPFEM P≥50 mm
QPFPM
P≥100 mm
P≥150 mm
P≥200 mm
18 UTC / 23 - 00 UTC / 24 00 – 06 UTC / 24 06 – 12 UTC / 24 12 – 18 UTC / 24
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24-hr estimates ending 06 UTC 30 October 2011
Multiple satellite estimates used for this ensemble prediction ◦ POES NOAA-18 and NOAA-19
(AMSU) ◦ MetOp-A (AMSU) ◦ TRMM (TMI) ◦ DMSP-17 and DMSP-18 (SSMIS)
Maximum 24-hr rainfall predicted approximately 8 inches in MD/DE
Probability of 4 inch rain
exceeds 50% over large region
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Storm Track 24-hr rain
Estimate 0600 UTC
Probability Of 100 mm Or more
bTPW algorithm – Kidder and Jones, 2007 ◦ Histogram matching to common
reference The bTPW product combines
all available data sources into a “seamless” product for use by the NWS forecaster ◦ Ocean – Satellite MW ◦ Land – Satellite MW and GOES
Sounder; GPS Met Most flooding events can be
linked to “atmospheric rivers” – high TPW that focus on a given location for extended period ◦ Connection from (sub)tropics to
mid and high latitudes Product is useful to weather
forecasters ◦ Timing & magnitude of moisture
“surges” (NWP models might miss) Companion TPW Anomaly
(from climatology) Product
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Provided by S. Kussleson, NESDIS/SAB
Blended TPW 21 UTC
1 May 2010
18 November 2014 IPWG Training Workshop 15 Provided by S. Kussleson, NOAA/NESDIS/SAB
18 November 2014 IPWG Training Workshop 16 Provided by S. Kussleson, NOAA/NESDIS/SAB
18 November 2014 IPWG Training Workshop 17 Provided by S. Kussleson, NOAA/NESDIS/SAB
18 November 2014 IPWG Training Workshop 18 Provided by S. Kussleson, NOAA/NESDIS/SAB
• Satellite retrieved water equivalent snowfall rate (SFR) over global land
• Uses measurements from passive microwave sensors, AMSU/MHS/ATMS
• AMSU/MHS SFR is operational at NESDIS with five satellites through (N18, N19, MOA, MOB, S-NPP)
•Up to 10 obs/day at a given location
•Resolution: 16 km x 16 km at nadir
• Maximum snowfall rate: 5 mm/hr
• Validated against NMQ, StageIV, and gauge snowfall data
Provided by H.Meng, NOAA/NESDIS/STAR
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Provided by H.Meng, NOAA/NESDIS/STAR
18 November 2014 IPWG Training Workshop
Monthly mean products derived from SSM/I since July 1987: ◦ Precipitation rate and
frequency ◦ Snow cover frequency ◦ Sea-ice concentration ◦ Oceanic total precipitable
water ◦ Oceanic cloud liquid water
and frequency ◦ Ocean surface wind speed
Products are now generated and archived at NOAA/NCDC
Used by NCEP/CPC, JMA, GEWEX/GPCP
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Current Algorithm: Global Hydro-Estimator ◦ Global coverage, 65 S – 65 N at
satellite scan schedule ◦ Single-band (IR window) algorithm
with fixed calibration using NWP model data to adjust for moisture, stability, topography
Next-Generation Algorithm ◦ Multi-band algorithm with
adjustable calibration (vs. MW rain rates)
◦ Current-GOES (2/5 bands) being run in real time and evaluated by several NWS forecast offices
◦ Feedback leading to algorithm improvements
Provided by R. Kuligowski, NOAA/NESDIS/STAR
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Extreme precipitation research: event climatology, QPE improvement, forecast challenges, high-impact event case studies
Research-to-operations transitions focus Develop NOAA GPM “Proving Ground” – generate and serve GPM-era products to
NWSFO’s and NOAA Testbeds for use and evaluation
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• 1 minute GOES visible and DCLMA • Simulate GOES-R ABI and GLM • Lightning “jumps” related to tornadic storms
• GPROF AMSR-2 Rain Rates • 1 second lightning from DCLMA • Lightning related to 89 GHz scattering
Provided by P. Meyers, Univ. of Maryland
[email protected] NOAA Operational Products ◦ bTPW - http://www.ospo.noaa.gov/Products/bTPW/index.html ◦ eTRaP - http://www.ssd.noaa.gov/PS/TROP/etrap.html ◦ H-E - http://www.ospo.noaa.gov/Products/atmosphere/ghe/ ◦ MiRS - http://www.ospo.noaa.gov/Products/atmosphere/mirs/index.html ◦ SFR - http://www.star.nesdis.noaa.gov/corp/scsb/mspps_backup/snowrate.html
Climate Products ◦ SSMI - http://www.ncdc.noaa.gov/oa/rsad/ssmi/gridded/index.php
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