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An overview of the NCEP Ensemble Prediction Systems EPSs

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Title: An overview of the NCEP Ensemble Prediction Systems EPSs


1
An overview of the NCEP Ensemble Prediction
Systems (EPSs)
  • Richard H. Grumm
  • National Weather Service Office
  • State College, PA 16803

2
OVERVIEW
  • Ensemble Prediction Systems (EPS)
  • Focus on the Primary NCEP Systems
  • Short-range ensemble forecast system (SREF)
  • Global Ensemble Forecast System (GEFS)
  • North American Ensemble Forecast System (NAEFS)
  • Includes CMC-Ensemble Forecast system
  • Super ensemble? all of these plus the higher
    resolution deterministic runs from the NAM and
    GFS
  • Configurations and data.

3
Ensemble Nomenclature
  • Ensemble Prediction System ?EPS
  • Ensemble Forecast System ?EFS
  • Familiar systems
  • NCEP
  • short range ensemble forecast system (SREF)
  • Global Ensemble forecast system (GEFS)
  • Other systems and combined systems
  • Canadian Ensemble forecast system (CEFS)
  • North American Ensemble Forecast System (NAEFS)?
    joint effort.
  • European Center for Medium-range weather
    forecasts (ECMWF).
  • KMA, CMA, and JMA run systems as does Brazil.

4
The SREF
  • Configuration and set-up
  • Multi-model EPS (strength)
  • Varied resolution (32-45 km) of members
    (weakness)
  • Older versions of some operational models
    (weakness)
  • Future plans
  • Upgrade WRF members
  • Go to higher resolution
  • More post processed data sets
  • Applications
  • Strengths and weaknesses

5
NCEP Short-range ensemble forecast system (SREF)
6
SREF Future
  • Future plans
  • Upgrade to the WRF members
  • Higher resolution (need value)
  • More post processed data sets
  • Mean/spread and probabilities availabel
  • Bias corrected data is currently made for each
    member? the low hanging fruit as we can gain
    information here
  • Downscaled data sets.

7
SREF Strengths
  • Mesoscale resolution EPS
  • Timeliness
  • Available 4 times daily
  • At off times so can be ensembled with the older
    and then newer high resolution deterministic
    runs.
  • 3 hourly output
  • Good set of parameters available
  • Severe weather,Winter weather, Heavy rainfall
  • Aviation ? NCEP and those with good bandwidth can
    make products.
  • Multi-model ensemble

8
SREF Weaknesses
  • Not as fine resolution as the operational NAM
  • There is some value to the high resolution and
    more accurate model, especially at shorter ranges
  • Resolution of the model is an issue
  • Lags NAM and not much better than GFS
  • Will improve but really need 15-20 km mesoscale
    EPS
  • Perturbations

9
The GEFS
  • Configuration and set-up
  • Complex as members are low resolution compared to
    the control
  • And then, control resolution changes!
  • Future plans
  • Model improvements and resolution changes
  • Applications
  • Strengths and weaknesses

10
GEFS ConfigurationSee COMET Matrix
11
GEFS Strengths
  • Global EPS
  • Timeliness
  • Available 4 times daily
  • 6 hourly output
  • Good set of parameters available
  • Good for large scale weather and some higher
    end/larger mesoscale patterns and events.
  • Good set post processed data
  • Bias correction
  • Anomalies
  • GFE downscale winds and 2m temperatures.
  • RMOP data and images (Relative Measures of
    Predictability)

12
GEFS Weaknesses
  • Single Model Core
  • WFOs
  • Need more short-term forecast data these data are
    longer in arriving and 6-hour increments
  • Coarse data for mesoscale features.

13
GEFS Future
  • Future plans
  • Upgrades GFS implemented into the GEFS over time
  • Slow move toward higher resolution
  • More post processed data sets
  • Mean/spread and probabilities availabel
  • Bias corrected data is currently made for each
    member? the low hanging fruit as we can gain
    information here
  • Downscaled data sets? several for use in GFE
    already.

14
CMC EPShttp//www.weatheroffice.gc.ca/ensemble/in
dex_e.html
  • Meteorological Service of Canada
  • Twice a day
  • 20 perturbed members 1 control with the GEM
    model
  • 20 models have varied physics (radiation and
    convection), varied diffusion, data assimilation,
    and perturbed ICs
  • GEM core
  • A global model 400x200 points (0.9 degree
    resolution about 100.19km at 0, 76.5 40N).
  • 28 vertical levels.

15
CMC-EPS Configuration
16
CMC EFS Strengths
  • Multi-model core
  • GEM is main the core but
  • Varied physics provides model diversity to the
    system
  • Convection large scale and shallow
  • Diffusion
  • And other phsyical parameterizations varied in
    the model
  • Diverse ICs
  • CMC has mix of different ICs for each model
    core.
  • Twice daily 42 member EPS
  • 0000 and 1200 UTC
  • 20 members plus 1 control

17
The NAEFS and the CMC-EFS
  • Configuration and set-up
  • NCEP GEFS and CMC-EPS
  • Future plans
  • Applications
  • Strengths and weaknesses

18
NAEFS Strengths
  • Multi-model cores
  • NCEP has 1 core
  • CMC-EFS has diverse set of GEM cores
  • Diverse ICs
  • NCEP has 20 members all with unique ICs
  • CMC has mix of different ICs
  • Twice daily 42 member EPS
  • 0000 and 1200 UTC
  • Has nearly ideal number of members (50) and can
    make very useful probability diagrams.
  • Diverse sets of post-processed products produced
  • Bias corrected and downscaled data of 2m temps
    and winds
  • Two websites to access data CMC and NCEP

19
NAEFS Weakness
  • Timeliness
  • Takes time to move and process the data
  • Only 2X daily at 0000 and 1200 UTC

20
Post Processed Data
  • Bias correction?
  • low hanging fruit
  • Better to use for forecast products (GFE) than
    unfiltered model data
  • Downscaled data?
  • NAEFS has this with 42 member 0000 and 1200 UTC
  • GEFS has this 21 members 4X daily
  • Downscaled to GFE grids

21
Critical role of EPSs NOAA/NWS Science Infusion
Bulletin
  • Ensembles add the most value in cases and times
    of high uncertainty,
  • Never try to chose a model or a single EPS
    member, when one of comparable skill is
    available, in highly uncertainty events,
  • In quiescent weather or areas of high confidence,
    the ensemble has minimal value.
  • Science Infusion document on uncertainty.

22
All EPS and Combinations
  • Facilitate
  • Producing Probabilistic output of critical fields
  • Viewing spread and uncertainty
  • Use to quantify uncertainty and aid in
    reliability issues
  • RMOP
  • Expected verse current forecast spread.

23
REVIEW
  • We focused on the Primary NCEP Systems
  • Short-range ensemble forecast system (SREF)
  • Global Ensemble Forecast System (GEFS)
  • North American Ensemble Forecast System (NAEFS)
  • Super ensemble? all of these plus the higher
    resolution deterministic runs from the NAM and
    GFS
  • Configurations and data.
  • We looked at how these systems will all improve
    over time.

24
Some take away points
  • NCEP has
  • two local EPS in the SREF and GEFS.
  • leverages the CMC EFS to make the NAEFS 2X daily.
  • The deterministic runs are also viable ensemble
    members.
  • Post processed data
  • To aid in the forecast process ? GFE
  • Remove bias and systematic errors.
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