The Global Wind Oscillation AprilMay 2007 Edward Berry

The Global Wind Oscillation April-May 2007 Edward Berry NOAA/NWS Dodge City, Kansas Klaus Weickmann NOAA/ESRL/PSD, Boulder, Colorado High Plains Conference Hastings, NE August 16 th, 2007

Background > WB(2007) proposed a Global Synoptic Dynamic Model of subseasonal atmospheric variabilty (GSDM) > GSDM considers the interaction of 3 -4 different time scales including the MJO recurrence time > Purpose of GSDM is to extend current thinking beyond the MJO > The Global Wind Oscillation (GWO) objectively represents a non-oscillatory component of the GSDM

Outline of Talk * Review the GSDM * Introduce the GWO * Case Study * Risk Assessment Plots * Summary

There is no Cookbook!!!

• Subseasonal Forecasting Tools mountains – Numerical Models • ensembles (multi-model) • ocean coupled – Statistical Models • composites • regressions convection – Statistical-Dynamical • linear inverse models • analogues of forecasts – Global Synoptic-Dynamic Model (GSDM) • Weather Climate Linkage – Regime transitions – Extreme events eddies

What is the GSDM? § Evolutionary framework for weatherclimate diagnosis and forecasting § Core subseasonal time scales - fast, slow and “quasi-o”; also ENSO, etc. § Physical Processes – Tropical Convection (tropical OLR modes) – Momentum Transports (eddy vs. HC/FC) – Torques (Mountain and friction) § New way to evaluate model predictions § Used to keep pulse on evolving climate state: from synoptic storms to decadal shifts

GLOBAL SYNOPTIC DYNAMIC MODEL (GSDM) Each stage shows spatial structure of 3 -4 time scales Wave energy dispersion favors high impact weather across USA Plains Below normal temperatures possible across central and eastern USA High Impact weather event possible along USA west coast Heavy precipitation event possible Southwest USA

What is the GWO? • Quasi-phase space plot of normalized AAM against normalized AAM tendency • Similar to MJO phase space plots such as WH(2004) • Objectively represents portion of GSDM most closely linked with AAM variations – Tropical Convection (tropical OLR modes) implicitly – Momentum Transports (eddy vs. HC/FC) – Torques (Mountain and friction) • Captures behaviors such as poleward propagation of zonal mean wind anomalies • Provides considerable independent information on variations of the global circulation

4/3 Relative AAM Tendency Stage 1 5/11 Stage 2 5/26 4/26 Stage 3 5/16 4/9 4/16 5/22 Stage 4 Relative AAM

Case Study: Week-2 Forecast for 18 -25 May 2007 ØWestern USA Trough when models forecasted a ridge ØSevere storms across the Plains ØGWO provided additional predictive insight

MAY 11

#1 #2

E W W E #1 E 4/3 4/9 4/16 E E W E #2 E W 4/26 W E 5/11 E 5/22 5/26 5/16

L H H L L H H L May 7 L H H H L HL H H May 11 250 mb Daily Mean Vector Wind Anomalies

H H L L H H May 15 H L L L H H H H May 19 250 mb Daily Mean Vector Wind Anomalies

H L L H L H L H H H May 23 250 mb Daily Mean Vector Wind Anomalies

PDF for AMJ GSDM Stage 2 vs. 4 Western USA 850 Ta Stage 2 Probs ordinate Stage 4 Std dev abscissa -4. 25 -1. 75 +4. 25

Summary and Conclusions • GSDM provides link between weather and climate • GWO is objective representing a portion of the GSDM • Risk assessment maps based on the GSDM are being developed • Present efforts include Hydro. Met Testbed for west coast floods and CPC Global Tropical HA • Subseasonal forecasts (weeks 1 -4) must be probabilistic and verified accordingly

QUESTIONS?

Summary and Conclusions l l l GSDM provides link between weather and climate GWO is objective representing a portion of the GSDM Risk assessment maps based on the GSDM are being developed Present efforts include Hydro. Met Testbed for west coast floods and CPC Global Tropical HA Subseasonal forecasts (weeks 1 -4) must be probabilistic and verified accordingly

. 11 May .

W W #1 E W 4/3 4/9 4/16 4/26 #2 W E E 5/11 5/16 5/22 5/26

#2 #1 4/3 4/9 4/16 4/26 5/11 5/22 5/16 5/26

#2 #1 4/3 4/9 4/16 4/26 5/11 5/22 5/16 5/26