Aspects of Dynamical Processes and Predictability in Medium Range Forecasts of High Impact WeatherEdmund K.M. ChangSchool of Marine and Atmospheric SciencesStony Brook UniversityStony Brook, New York, USAWWRP/THROPEX HIW WorkshopKarlsruhe, GermanyMarch 18, 2013

Alternative TitleSome thoughts on predictability and dynamical processes Using Rossby Wave Trains (RWTs, or baroclinic wave packets) as an illustrative example

From THORPEX International Science Plan(Shapiro and Thorpe, 2004)Cyclogenesis near JapanFlooding over Europe

Dundee Satellite Station: 1241 UTC 11 Aug. 2002FranceItalyThe StormCourtesy of Mel Shapiro

Dresden GermanyCourtesy of Mel Shapiro

THORPEX Research Objectives:Investigate the evolution of dynamical and physical processes and their influence on forecast skillThe skill of forecast systems in predicting Rossby wave properties (amplitudes, ray paths, group velocities )The initiation of Rossby wave trains by various processes (tropical convection, extratropical cyclones, large-scale topography )The initiation of tropical convection by Rossby wave-trains propagating into the tropicsFrom Shapiro and Thorpe (2004)

Examples of progress since 2004

New techniques developed to highlight RWTs

Zimin et al. (2006): Extracting envelopes of nonzonally propagating Rossby Wave Packets

Martius et al (2006): A refined Hovmoller diagram:- Hovmoller diagram constructed following the 2 PVU PV contour instead of along a fixed latitude band

Linkage between RWTs and high impact weather events strengthened

Martius et al (2008)- Wave packet signal precedes Alpine heavy precipitation events, especially in SON and DJF0

Chang (2005): RWT signal traced back to Asia at least 3 days prior to strong cyclone events over NW Pacific

Eichorn and Wirth (2013): RWT signal traced back to Northeastern Pacific at least 6 days prior to strong cyclone events over central Europe Presence of RWT over NE Pacific significantly enhance probability of strong cyclone over Europe 6 days laterEichorn and Wirth (2013)

Characteristics of RWTs examined

Glatt et al. (2011): Used Hovmoller diagrams to examine multiple processes associated with RWTs

ET vs. Winter Rossby Waves (Torn and Hakim 2013)- composites based on 112 ET and 281 winter cyclonesAmplitude

Linkage suggested between RWTs and growth of uncertainties in medium range EPS

From Zheng et al. (2013)Majumdar et al. (2010):- distinctive targets could be traced upstream near Japan at lead time of 4-7 days. In these cases, the flow was predominantly zonal and a coherent Rossby wave packet was present over the northern Pacific Ocean.Zheng et al. (2013): Used ensemble sensitivity analysis to study U.S. east coast snowstorm on 26-28 December 2010 Sensitivity signal developed and propagated across the Pacific accompanying the development and propagation of a RWTAnalysis of V300Sensitivity signal

Many issues still remain:Process Studies:Initiation? Dissipation?What physical processes control propagation, duration, coherence, amplitude, frequency?How do atmospheric low frequency variability impact RWTs?How do RWTs impact low frequency variability?Forecast Science:How well do our forecast models predict RWTs?Do (How do) more accurate forecasts of RWTs transfer to better forecasts of high impact weather events?Does the growth of a significant RWT imply increased or decreased predictability downstream?Are RWTs initiated by ET less predictable?SERA:Can we quantify the socio-economical impacts of RWTs?

Challenges:It is difficult to define RWTs exactly (Glatt et al. 2011)An objective climatology of RWTs is still lackingNeed objective identification and tracking

Glatt et al. (2011):RWT object identification based on Hovmoller diagram

Example of objective tracking results (Courtesy Matt Souders)Jan 29 Feb 12, 2009: Focus on packet number 107An objective tracking algorithm has been developed at SBU

Ongoing research at SBU:

Process studies:Climatology and variabilityLinks to low frequency variabilityDynamics of growth and decayForecast Science:Verify and calibrate ensemble forecasts of RWTsLinks to forecast uncertainty and error growth

Challenges (continued)Multiple scales in space and time

Time/Longitude: 250-mb Meridional Wind (m s-1); 55-40N.Oct. 12

Oct. 18

Oct. 24

Nov. 3Cal.JapanW. AfricaCourtesy Mel Shapiro

Synoptic-scale phase velocity

Time-mean planetary-waves

Wave-train group velocityCourtesy Mel ShapiroShort-rangeMedium-rangeSub-seasonaltoSeasonal

Rodwell et al (2013)

- ECMWF large error forecasts over Europe associated with errors in convective heating over central U.S. which acts to slow the progression of the RWTMultiple scales (continued)

Forecast verificationObject (process) oriented forecast verification?Cyclones (Froude et al. 2007, 2009, 2010)RWTs (or any other object or process)Need to identify model errors and biases in forecasting dynamical processesHIW? How (and what) to verify?Especially in the medium rangeVerification of impact?Challenges (continued)

Opportunities (THORPEX and legacy)International field campaigns (e.g. TNAWDEX)Availability of high quality data for PDP researchState of the art reanalysisTIGGEReforecast multi-model multi-ensemble?Develop effort parallel to CMIP?Basically free and unrestricted availability of data for broad research communityBroad participation by international community (including data providers and data users)

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