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  William. M. LapentaActing
DirectorEnvironmental Modeling
CenterNOAA/NWS/NCEPWith contributions from
many EMC Staff
The NCEP Global and Regional Operational
Numerical Guidance Systems 
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Presentation Outline

• The EMC Mission
• Importance of satellite data to NWP
• Global Forecast Data Assimilation System
• Attributes
• Operational Requirements
• Data Assimilated
• Performance evolution since 1998
• CONUS Mesoscale Model System
• Hybrid GSI Var-EnKF Assimilation
• System Upgrade Process

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The EMC Mission..
In response to operational requirements

• Develop and Enhance numerical guidance
• Improve NCEPs numerical forecast model systems
  via
• Scientific upgrades
• Optimization
• Additional observations
• Transition operational numerical forecast models
  from research to operations
• Transform integrate
• Code
• Algorithms
• Techniques
• Manages and executes transition process including
  technical and system performance review before
  implementation
• Maintain operational model suite
• The scientific correctness and integrity of
  operational forecast modeling systems
• Modify current operational system to adapt to
  ever-present external changes

EMC location within the funnel
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NWS Seamless Suite of ForecastProducts Spanning
Weather and Climate
NCEP Model Perspective
Forecast Uncertainty
Years
Seasons
Months

• Climate Forecast System

2 Week

• North American Ensemble Forecast System

• Global Ensemble Forecast System

1 Week

• Global Forecast System

• Short-Range Ensemble Forecast

Days
Waves
Real Time Ocean Forecast System

• North American Mesoscale

Hours

• Rapid Update Cycle for Aviation

Hurricane WRF GFDL
Space Weather Tsunami
Minutes

• Dispersion Models for DHS

Health
Aviation
Recreation
Ecosystem
Agriculture
Commerce
Hydropower
Environment
Maritime
Fire Weather
Life Property
Energy Planning
Reservoir Control
Emergency Mgmt
Space Operations
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Satellite Data is Required to Help Meet Key
Performance Metrics

• Numerical Weather Prediction
• Global Anomaly Correlation Score Internal
  metric
• Related to ability to meet service-based metrics
  (below)
• National Weather Service GPRA Metrics
• ( Government Performance Results
  Act)
• Hurricane Track and Intensity Forecast Accuracy
• Winter Storm Warning Lead Time and Accuracy
• Precipitation Threat Accuracy
• Flood Warning Lead Time and Accuracy
• Marine Windspeed and Wave Height Forecast
  Accuracy
• NAM and GFS are primary tools used by the NWS to
  meet the above goals

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Global Data Assimilation System (GDAS)

• Grid-point Statistical Interpolation (GSI)
• 3D-variational approach
• Unified system for all NCEP atmospheric
  applications
• Global (GDAS/GFS)
• Regional (NDAS/NAM) HWRF
• Real Time Mesoscale Analysis (RTMA)
• Rapid Refresh (RR)
• Developed for operational application
• Forecasts must be completed within schedule
• Trade-offs
• More accurate formulation higher resolution
• Improved model improved analysis
• Enhanced physics higher resolution
• Must work everywhere all the time
• Manual intervention should be minimal
• Both operational and research data used in systems

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Assimilated Satellite Radiance Data
Global All thinned to 145km
Regional

• GOES-11 Sounder Thinned to 120km
• Channels 1-15
• Individual fields of view
• 4 Detectors treated separately
• Over ocean only
• AMSU-A Thinned to 60km
• NOAA-15 Channels 1-10, 12-13, 15
• NOAA-18 Channels 1-8, 10-13, 15
• METOP Channels1-6, 8-13, 15
• AMSU-B/MHS Thinned to 60km
• NOAA-15 Channels 1-3, 5
• NOAA-18 Channels 1-5
• METOP Channels 1-5
• HIRS Thinned to 120km
• NOAA-17 Channels 2-15

• GOES-11 Sounder
• Channels 1-15
• Individual fields of view
• 4 Detectors treated separately
• Over ocean only
• AMSU-A
• NOAA-15 Channels 1-10, 12-13, 15
• NOAA-18 Channels 1-8, 10-13, 15
• NOAA-19 Channels 1-7, 9-13, 15
• METOP Channels 1-6, 8-13, 1
• AQUA Channels 6, 8-13
• AMSU-B/MHS
• NOAA-15 Channels 1-3, 5
• NOAA-18 Channels 1-5
• METOP Channels 1-5
• HIRS
• NOAA-17 Channels 2-15

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Assimilated Conventional Data and Satellite
Products
Satellite Products
Conventional

• Radiosondes
• Pibal winds
• Synthetic tropical cyclone winds and
  pressures(when needed)
• Wind profilers
• Conventional aircraft reports
• ASDAR aircraft reports
• MDCARS aircraft reports
• Dropsondes
• Surface land observations
• Surface ship and buoy observation
• Doppler radial velocities (regional)
• VAD (NEXRAD) Winds
• TAMDAR aircraft data
• Mesonet data

• MODIS IR and water vapor winds
• GMS, METEOSAT and GOES cloud drift IR and visible
  winds
• GOES water vapor cloud top winds
• TRMM TMI precipitation estimates
• GPS precipitable water estimates
• GPS Radio occultation refractivity profiles
• SBUV ozone profiles (other ozone data under test)
• OMI total ozone

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Global Data Assimilation UpgradeQ3FY11Late April

• Analysis Changes
• Recomputed background errors
• New version of CRTM 2.0.2
• Improved Field of View calculation
• Updates for thinning and collocation calculations
• QC and obs. error and data handling updates for
• OMI
• AMSU-A (channel 5)
• ASCAT
• SBUV/2 ozone
• Ocean buoys
• New analysis options (useful for next
• round of development)
• Model Changes
• Thermal roughness length upgrade
• (X. Zeng, U. Arizona)
• Stratospheric tuning

5-Day 500MB NH AC 00Z Cycles 16 June-29 Sept 2010
Day 8
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500-hPa Height AC Frequency Distribution, GFS 00Z
Cycle Day-5 Forecast
Northern Hemisphere
0.7
0.9
Poor forecasts (AC lt 0.7) decrease Good forecasts
(AC gt 0.9) increase
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Percentage of Poor Forecasts 5-Day 500mb AC lt
0.7 v.s. Model Upgrades
AMSU-A HIRS-3 data
T126L28 (100km) to T170L42 (70km)
Physics upgrade to prognostic cloud water,
cumulus momentum transport
T170L42 (70km) to T254L64 (55km)
T254L64 (55km) to T382 (38km) OSU 2-L LSM to 4-L
NOHA LSM
T382L64 (38km) to T574L64 (27km) New shallow
convection updated SAS and PBL
positive-definite tracer transport
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Percentage of Good Forecasts 5-Day 500mb AC lt
0.9 v.s. Model Upgrades
T382L64 (38km) to T574L64 (27km) New shallow
convection updated SAS and PBL
positive-definite tracer transport
Flow-dependent error covariance Variational QC
T254L64 (55km) to T382 (38km) OSU 2-L LSM to 4-L
NOHA LSM
T170L42 (70km) to T254L64 (55km)
AMSU-A HIRS-3 data
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NCEP Mesoscale Modeling for CONUS Planned Q3
Q4 FY11

• Rapid Refresh
• WRF-based ARW
• Use of GSI analysis
• Expanded 13 km Domain to include Alaska
• Experimental 3 km HRRR

• NAM
• NEMS based NMM
• Bgrid replaces Egrid
• Parent remains at 12 km
• Multiple Nests Run to 48hr
• 4 km CONUS nest
• 6 km Alaska nest
• 3 km HI PR nests
• 1.5-2km DHS/FireWeather/IMET possible

WRF-Rapid Refresh domain 2010
RUC-13 CONUS domain
Original CONUS domain
Experimental 3 km HRRR
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Development of GSI Hybrid Var-EnKF

• Test Period 01 Aug to 22 September 2010
• Deterministic Forecasts Operational GFS _at_
  T574L64
• Ensemble Configuration
• 80 ensemble members
• GSI for observation operators
• T254L64 operational GFS
• Initialized 00 UTC 15 July 2010 from interpolated
  GEFS members
• allowed over 2 weeks spin-up
• Assimilate all operational observations
• Includes early (GFS) and late (GDAS/cycled)
  cycles
• Operational prepbufr files (no prep/additional
  qc)
• Dual-resolution/Coupled
• High resolution control/deterministic component
• Includes TC Relocation on guess
• Ensemble is recentered every cycle about hybrid
  analysis
• Throw out EnKF analyis mean
• Bias correction (satellite) coefficients come
  from GSI/VAR

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500 hPa SH AC Time Series6 Aug to 21 Sept 2011
Day 5
0.026 AC
Black Control Red Hybrid Green Operational
Day 6
0.035 AC
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Process to Implement Major Upgradesto The NCEP
Model Production Suite

• Implementation Phase
• SPAs build NCO parallel from RFCs
• 30-day NCO parallel
• Test code stability
• Test dataflow
• Products to NCEP Centers and EMC code developers
• NCEP Centers
• Evaluate impact
• Assessments to NCEP OD

RD and Pre-Implementation Phase
Systematic Testing

• EMC Change Control Board
• Scientific Integrity
• Product Quality
• EMC Mgmt Approval

• 30-day NCO parallel stable
• NCEP centers approve

• Briefing to NCEP Director for final approval

• Generate RFCs
• Submit RFCs to NCO

Implementation
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Schedule For the GFS/GSI December 2009
Implementation

• 17 months required to develop, test and implement
• 119 person months of effort (EMC, NCO, GFDL, TPC,
  SPC, HPC, AWC)
• 17 months of continuous cycles 4/day with 16 day
  forecasts retrospective/real-time testing
  conducted for GFS/GSI
• 500 HWRF and 600 GFDL TC/Hurricane cases
  simulated
• 1000 Node hours and 75 TB of disk consumed

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Thanks for your time
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Impact of Satellite Data on NWP..
Operational ECMWF system September to December
2008. Averaged over all model layers and entire
global atmosphere. contribution of different
observations to reduction in forecast error.
Note 1) Sounders on Polar Satellites reduce
forecast error most 2) Results are relevant for
other NWP Centers, including NWS/NCEP
Forecast error contribution ()
Courtesy Carla Cardinali and Sean Healy, ECMWF