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Description and Preliminary Evaluation of the Expanded UW

Description and Preliminary Evaluation of the Expanded UW S hort R ange E nsemble F orecast System Maj. Tony Eckel, USAF University of Washington Atmospheric Sciences Department Advisor: Prof. Cliff Mass March 2002. Overview. UW SREF Methodology Generating New Initial Conditions

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Description and Preliminary Evaluation of the Expanded UW

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  1. Description and Preliminary Evaluation of the Expanded UW Short Range Ensemble Forecast System Maj. Tony Eckel, USAF University of Washington Atmospheric Sciences Department Advisor: Prof. Cliff Mass March 2002

  2. Overview • UW SREF Methodology • Generating New Initial Conditions • Case Study • Error Statistics • Individual SREF Members • Ensemble-Based Probability • Summary

  3. From our point of view, truth is random sample from the pdf - Let all ICs evolve to build PDF at future time (i.e., a forecast pdf) - Error growth spreads out PDF as forecast lead time increases 24hr Forecast State 48hr Forecast State Ensemble Forecasting Theory - Construct the initial state of the atmosphere with multiple, equally likely analyses, or initial conditions (ICs) Frequency Initial State

  4. analysis pdf Limitations of EF Difficult to consistently construct the “correct” analysis/forecast pdf. Errors in mean and spread result from: 1) Model error 2) Choice of ICs 3) Under sampling due to limits of computer processing Result: EF products don’t always perform the way they should. (especially a problem for SREF) ensemble pdf Frequency Initial State 24hr Forecast State 48hr Forecast State

  5. UW SREF Methodology Overview Analysis pdf cwb avn cwb cmc gsp eta ngp C gsp T ngp cmc avn eta uk Forecast pdf uk 7 “independent” atmospheric analyses, the centroid, plus 7 “mirrored” ICs Analysis pdf : Forecast pdf : 15 divergent, “equally likely” solutions using the same primitive equation model, MM5 phase space A point in phase space completely describes an instantaneous state of the atmosphere. For a model, a point is the vector of values for all parameters (pres, temp, etc.) at all grid points at one time. 48hr true state 48hr forecast state (core) 48hr forecast state (perturbation)

  6. 1006 1004 1002 1000 998 996 994 cmcg C cmcg* ngps cmcg eta ukmo cmcg* Sea Level Pressure (mb) tcwb gasp avn cent ~1000 km 170°W 165°W 160°W 155°W 150°W 145°W 140°W 135°W Filling in the Holes of the IC Cloud STEP 1: Calculate best guess for truth (the centroid) by averaging all analyses. STEP 2: Find error vector in model phase space between one analysis and the centroid by differencing all state variables over all grid points. STEP 3: Make a new IC by mirroring that error about the centroid.

  7. ICs: Analyses, Centroid, and Mirrors • Strengths • Good representation of analysis error • Perturbations to synoptic scale disturbances • Magnitude of perturbation(s) set by spread among analyses • Bigger spread  Bigger perturbations • Dynamically conditioned ICs • Computationally affordable • Weaknesses • Limited by number and quality of available analyses • May miss key features of analysis error • Analyses must be independent (i.e., dissimilar biases) • Calibration difficult; no stability since analyses may change techniques

  8. CASE STUDY: Thanksgiving Day Non-Wind Event eta-MM5 Initialized: 00z, 21 Nov 2001 (Tuesday evening) 42h, valid 22 Nov 18z 39h, valid 22 Nov 15z (Thursday 7AM) (Thursday 10AM) Note: This study used only 13 ensemble members since missing gasp grids.

  9. ZCZC SEANPWSEA WWUS45 KSEA 212348 URGENT - WEATHER MESSAGE NATIONAL WEATHER SERVICE SEATTLE WA 344 PM PST WED NOV 21 2001 AN INTENSE LOW PRESSURE SYSTEM WILL MOVE ALONG THE NORTH WASHINGTON COAST EARLY MORNING THANKSGIVING DAY...AND MOVE INLAND OVER THE NORTH INTERIOR OF WESTERN WASHINGTON BY MIDDAY. STRONG SOUTH WINDS WILL DEVELOP ALONG THE COAST AFTER MIDNIGHT. AS THIS SYSTEM MOVES INLAND THANKSGIVING MORNING IT HAS THE POTENTIAL TO CAUSE HIGH WINDS ACROSS THE INTERIOR OF WESTERN WASHINGTON AFTER ABOUT 8 AM. ...HIGH WIND WATCH FOR THURSDAY MORNING THROUGH THURSDAY EVENING REMAINS IN EFFECT...

  10. 12km Inner Domain cmcg cmcg* avn avn* eta eta* ngps ngps* ukmo ukmo* tcwb tcwb* cent Root Mean Square Error (RMSE) by Model Verification 36km Outer Domain RMSE of MSLP (mb) 48h 36h 24h cmcg cmcg* avn avn* eta eta* ngps ngps* ukmo ukmo* tcwb tcwb* cent 12h

  11. Initialization cmcg C cmcg* 00h cmcg* 21 Nov 00z 00h cmcg 21 Nov 00z 00h cent 21 Nov 00z

  12. 36 Hour Forecast 36h cmcg 22 Nov 12z 36h cmcg* 22 Nov 12z “Verification” 00h cent 22 Nov 12z 36h cent 22 Nov 12z

  13. “Verification” 42h (18z, 22 Nov) mslp and sfc wind. cent ngps ngps* eta* eta ukmo cmcg ukmo* cmcg* tcwb avn avn* tcwb*

  14. 10% Ensemble-Based Probability of Wind Speed 30% 50% Prob. of (sustained) Winds > 21 kt 10% 90% 39h, 22 Nov 21z 42h, 22 Nov 18z 39h, 22 Nov 15z (Thursday 1PM) (Thursday 10AM) (Thursday 7AM)

  15. Summary • Set of 15 ICs for UW SREF are not optimal, but may be good enough to represent important features of analysis error • The centroid may be the best bet deterministic model run, in the big picture • Need further evaluation • How often does the ensemble fail to capture the truth? • How reliable are the probabilities? • Does the ensemble dispersion represent forecast uncertainty?

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