Aspects of Dynamical Processes and Predictability in Medium Range Forecasts of High Impact Weather Edmund K.M. Chang School of Marine and Atmospheric Sciences Stony Brook University Stony Brook, New York, USA WWRP/THROPEX HIW Workshop Karlsruhe, Germany March 18, 2013

Alternative Title Some 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 Japan Flooding over Europe

Dundee Satellite Station: 1241 UTC 11 Aug. 2002 The Storm France Italy Dundee Satellite Station: 1241 UTC 11 Aug. 2002 Courtesy of Mel Shapiro

Dresden Germany Courtesy of Mel Shapiro

THORPEX Research Objectives: Investigate the evolution of dynamical and physical processes and their influence on forecast skill The 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 tropics From 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 DJF

Eichorn and Wirth (2013) 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 later

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 cyclones Amplitude

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

Analysis of V300 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 RWT Sensitivity signal From Zheng et al. (2013)

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 lacking Need objective identification and tracking

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

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

Ongoing research at SBU: Process studies: Climatology and variability Links to low frequency variability Dynamics of growth and decay … Forecast Science: Verify and calibrate ensemble forecasts of RWTs Links 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. 3 Japan Cal. W. Africa Courtesy Mel Shapiro

Synoptic-scale phase velocity Short-range Synoptic-scale phase velocity Wave-train group velocity Medium-range Time-mean planetary-waves Sub-seasonal to Seasonal Courtesy Mel Shapiro

Multiple scales (continued) 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 RWT

Challenges (continued) Forecast verification Object (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 processes HIW? How (and what) to verify? Especially in the medium range Verification of impact?

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