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MOS

MOS. AVN = Dynamical Model Seven fundamental equations ! AVN MOS = Statistical Model No seven fundamental equations ! Equations are statistical, not dynamical !. MOS: Equation Development. Y1 = mx1 + b1. MOS: Temperature. Predictors Model low level temps (i.e. 850mb/2m)

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MOS

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  1. MOS • AVN = Dynamical Model • Seven fundamental equations ! • AVN MOS = Statistical Model • No seven fundamental equations ! • Equations are statistical, not dynamical !

  2. MOS: Equation Development Y1 = mx1 + b1

  3. MOS: Temperature • Predictors • Model low level temps (i.e. 850mb/2m) • Model relative humidity • Accounts for clouds • Model wind direction /speed • Climatology • Previous days min (max) • Single site development

  4. MOS: Precipitation • Predictors • Model mean relative humidity (i.e. 1000-500mb layer average) • Precipitation output of model • Model vertical velocity (i.e. 700, 500, 850mb) • Model low level wind direction (i.e. 10m) • Regional development

  5. MOS: Wind • Predictors • Low-level wind direction/speed output of model (i.e. 10m, 850mb wind) • Single site development

  6. MOS Characteristics • Requires large sample size • Several years of model output • Increases statistical significance

  7. MOS • Partially removes systematic model errors (i.e. biases) • If model has a cool bias at 850mb, MOS will account for/remove model bias • Works best when models are not tweaked (i.e. no change to physics)

  8. MOS: Equation Application

  9. GFS MODEL • Station: UNV Lat: 40.85 Lon: -77.83 Elev: 378 Closest grid pt: 29.6 km. • Initialization Time: 08-02-26 1200 UTC • HOUR VALID PMSL THCK 6HRPCN 2m_TMP 850TMP 850REL 700REL 10m_WD 850WND • ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ • 000 26/12 1006 540 29 -1 91 98 14/003 20/026 • 006 26/18 997 543 0.38 33 1 99 100 12/005 20/037 • 012 27/00 993 540 0.13 34 0 97 79 30/005 26/018 • 018 27/06 997 530 0.02 28 -8 100 92 31/014 34/028 • 024 27/12 1002 522 0.01 20 -10 89 91 31/014 33/034 • 030 27/18 1006 517 0.01 23 -13 90 99 30/014 31/027 • 036 28/00 1010 511 0.01 16 -16 89 75 31/013 31/032 • 042 28/06 1014 507 0.01 12 -18 91 44 30/011 31/031 • 048 28/12 1018 504 0.01 11 -19 98 44 29/010 30/032 • 054 28/18 1022 506 0.01 19 -17 98 17 29/013 30/025 • 060 29/00 1027 513 0.02 18 -16 98 11 29/008 30/027 • 066 29/06 1031 519 0.00 12 -14 45 9 26/003 28/019 • 072 29/12 1030 524 0.00 13 -9 52 90 16/007 24/023

  10. GFS MOS • KUNV GFS MOS GUIDANCE 2/26/2008 1200 UTC • DT /FEB 26/FEB 27 /FEB 28 /FEB 29 • HR 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 06 12 • N/X 25 27 15 24 16 • TMP 36 35 34 33 32 29 26 25 26 25 21 19 18 17 17 19 23 24 21 19 17 • DPT 31 31 29 29 26 22 18 16 13 11 9 7 6 6 5 4 4 4 3 8 10 • CLD OV OV OV OV OV OV OV OV OV OV OV OV OV SC BK BK BK SC CL SC OV • WDR 05 36 30 29 29 29 29 29 29 29 29 29 28 28 28 28 28 28 28 23 15 • WSP 03 04 06 11 14 15 13 13 14 14 12 11 11 10 09 13 14 13 06 02 03 • P06 100 51 35 24 26 11 10 2 0 0 0 • P12 65 41 11 6 1 • Q06 3 1 0 0 0 0 0 0 0 0 0 • Q12 1 1 0 0 0 • T06 1/ 0 2/ 1 0/ 1 0/ 0 0/ 0 0/ 0 0/ 0 0/ 0 0/ 3 0/ 0 • T12 3/ 1 0/ 1 0/ 0 0/ 0 0/ 3 • POZ 7 0 2 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 • POS 41 33 55 65 96100100100100100100100100100 99100100100100100 99 • TYP S R S S S S S S S S S S S S S S S S S S S • SNW 4 1 0 • CIG 3 3 3 4 4 6 6 5 6 6 6 6 6 6 6 6 6 6 8 8 7 • VIS 3 3 4 3 5 5 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 • OBV BR BR BR BR N N N N N N N N N N N N N N N N N

  11. MOS ERRORS: Who’s at fault? • Dynamic model (gfs model) • Garbage In = Garbage Out • Statistical model (gfs mos) • Imperfect statistical relationships (i.e. lines of best fit are not line of prefect fit!) • Forecasting MOS error (utilizing association method)

  12. HOW TO BEAT MOS • Know how it works • MOS tends to do well: • Weather near climatology (equations lean toward modal case) • MOS tends to do poor: • Weather departs from climatology ( the “outliers” of the scatter plot) • Bad model data used as input (GI=GO)

  13. MOS: Equation Development Y1 = mx1 + b1

  14. HOW TO BEAT MOS- temp • Tend to go lower than MOS by day if: • It’s precipitating • Overrunning situation • Spatially thin, optically thick cloud (non-climo) • Snow cover (esp. in non climo., treeless area) • Shallow cold air mass • Sea breeze in hot air mass with cold water • YESTERDAY'S OBSERVED MAX/MIN TEMP • Expected air mass will be record-breaking • YESTERDAY'S MAXIMUM TEMPERATURE

  15. MOS ERROR: OVERUNNING 850mb Predictor gives a very poor forecast!

  16. MOS ERROR: SPATIALLY THIN/OPTICALLY THICK CLOUD

  17. MOS ERROR: Shallow Chill Worse for NGM mos …. not as bad for ETA and GFS MOS

  18. MOS ERROR: Shallow Chill

  19. MOS ERROR: Shallow Chill

  20. MOS ERROR: Shallow Chill

  21. Beating MOS • How to account for shallow chill problem: • Recognize pattern • Look at 2m temps from model (ETA/AVN) • If much colder than MOS, then lower MOS

  22. MOS ERROR: FRONTS Relaxed gradient aloft gets translated to the surface

  23. MOS ERROR: FRONTS Relaxed gradient aloft gets translated to the surface

  24. HOW TO BEAT MOS • Tend to forecast higher than MOS by day: • Mainly sunny • In warm sector • Especially if in the cooler season and it’s breezy and prev. night was warm • Expected air mass is record-breaking

  25. HOW TO BEAT MOS • Forecast lower than MOS at night if: • Clear • Calm • Low dew points • Snow cover • (unless its ‘climatological’!)

  26. HOW TO BEAT MOS • Which city is more likely to have the bigger bust in the following situation? • Clear skies, light winds, snow cover • ST. LOUIS vs. INTERNATIONAL FALLS

  27. HOW TO BEAT MOS • Forecast higher than MOS at night if: • Cloudy • Breezy • Higher dew points • Not precipitating

  28. MOS ERROR: CYCLONE

  29. HOW TO BEAT MOS • PRECIPITATION • Will tend to miss mesoscale events tied to topography • Lake-effect • Under predicts upslope areas, Over predicts in downslope areas • WIND • A little inflation of sustained winds

  30. HOW TO BEAT MOS • Other considerations: • NGM beyond 48-hours …. Watch out! • Beware if MOS exceeds 850mb ‘rules’ • Lean toward MOS product that makes the most sense: • (i.e. AVNMOS: 65F NGMMOS: 72F and character of day: optically thick/spat. thin overcast) • If unsure, go CONSENSUS MOS ............ wins over long haul!

  31. HOW TO BEAT MOS • Analogous thickness approach!! • Use analogous thickness method to “advect” mos errors to forecast location! • If MOS is busting upstream and same weather regime is heading to forecast site, assume error continues!

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