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Model Output Statistics

Model Output Statistics. Transforming model output into useful forecast parameters. Forecast Output United States (FOUS). Raw model output (e.g. from NGM, NAM, GFS) Only includes such parameters as Mean relative humidity in certain layers Vertical velocity at 700 mb 1000-500 mb thickness

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Model Output Statistics

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  1. Model Output Statistics Transforming model output into useful forecast parameters

  2. Forecast Output United States (FOUS) • Raw model output (e.g. from NGM, NAM, GFS) • Only includes such parameters as • Mean relative humidity in certain layers • Vertical velocity at 700 mb • 1000-500 mb thickness • Temperature at a few model layers • Not incredibly useful for surface forecasting applications

  3. UTC time of model cycle Day of month Station ID Temp(C) of layer 5 SLP (coded) Vert. Veloc. (‘-’ is down) 6-hr Accum Precip 0.01” Mean RH in lowest layer Mean RH up to 500 mb Mean RH (500- 200 mb) Fcst. valid time WDIR (lowest model layer) WSPD (kt) in lowest layer 1000- 500 mb thickness (dm) Temp. (C) of lowest layer Temp. (C) of layer 3 Lifted Index

  4. Model Output Statistics (MOS) • Production of surface variables not created by dynamical models • Improvement of other variables that are created by dynamical models • Developed at the Meteorological Development Lab (MDL)

  5. How MOS Works • Relates model output variables to common forecast variables (e.g. surface temperature, dew point, precipitation) through statistical techniques • Analyze past correlations between model outputs and forecast variables • ‘Analog’ method of forecasting • MOS is produced from NGM, NAM, and GFS models

  6. ** See page 21-22 in text for decoding information

  7. Interpreting some MOS output • Probability of Precipitation (P06, P12) • Precipitation chance (%) for a point • ’40%’ means it will precipitate 4/10 times at that point in the given situation • Probability of Snow (POS) • Conditional probability • If precipitation occurs, this is the chance (%) that it will be snow • Actual chance of snow is the product of P06/P012 and POS

  8. Things to consider when using MOS output for forecasting • Not proficient at depicting local and mesoscale events • Beware of rare events (since MOS is statistical) • MOS better 1.5 and 4.5 months into the season • Uses seasonal equations tuned to be best at those times • Extended forecasts less skillful • Trends toward climatology • MOS usually too warm for shallow cold air events • common east of Appalachians

  9. MOS Seasonal Equations

  10. MAV – GFS MOS MET – ETA MOS FWC – NGM MOS MEX – GFSX MOS (Extended)

  11. MOS Links • Changes/updates • http://www.nws.noaa.gov/mdl/synop/changes.php • FAQ • http://www.nws.noaa.gov/mdl/synop/faq.php • Definition of MOS elements/acronyms • http://www.nws.noaa.gov/mdl/synop/avnacronym.htm • MOS performance (WRF vs. GFS vs. NAM) • http://www.nws.noaa.gov/mdl/synop/wrfmoseval.htm • MDL • http://www.nws.noaa.gov/tdl/

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