Forecast errors associated with midlatitude weather systems Heini Wernli – ETH Zurich With contributions from: Christian Grams, Hanna Joos, Erica Madonna,

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Presentation transcript:

Forecast errors associated with midlatitude weather systems Heini Wernli – ETH Zurich With contributions from: Christian Grams, Hanna Joos, Erica Madonna, Stephan Pfahl & Andreas Schäfler WGNE Workshop, Exeter, 18 April 2013

Analysis of mid-latitude flow features inweather systems of interest short-range fcsurface weather & extreme events 0-3 days(precip, wind, temperature)  convection, orographic flows, fronts & cyclones, … medium-range fcupper-level flow features 3-10 days  jets, Rossby waves, Rossby wave breaking, blocking, … regional / global climate modelsall of these

Coupling of surface weather & upper-level flow Baroclinic instability Hoskins et al (QJ)

Coupling of surface weather & upper-level flow Baroclinic instabilityLatent heating in warm conveyor belts (WCB) Hoskins et al (QJ)Pomroy & Thorpe 2000 (MWR)

Outline of the talk Weather systems and extremes cyclones & precipitation extremes fc validation of cyclone tracks & their extremeness Warm conveyor belts impact of WCBs on upper-level flow WCBs and large fc errors cloud microphysics and dynamics field experiment T-NAWDEX Feature-based climate model evaluation WCBs in climate models cyclones & precipitation extremes Conclusions

Heavy precipitation events & cyclones HPE: >99 percentile at every grid point (ERAinterim, ) Pfahl and Wernli 2012 (J. Clim.)

The “extremeness” of cyclones extremeness = Σ of local extreme events along track of cyclones extreme precipitation extreme 10-m wind gust cyclone track and area from Christian Grams

The “extremeness” of cyclones First results for YOTC period 05/ /2010 Top 10 “extreme cyclones”: 9 with tropical origin from Christian Grams

The “extremeness” of cyclones Are fc errors particularly large for “extreme cyclones”? from Christian Grams → extreme cyclones not particularly badly predicted → intensity errors seem to be more an issue than track errors accum. track error accum. intensity error

The “extremeness” of cyclones Are fc errors particularly large for “extreme cyclones”? from Christian Grams → extreme cyclones not particularly badly predicted → extreme cyclones have larger intensity than track errors accum. track error accum. intensity error more: Poster 17 today by Christian Grams

Joos and Wernli 2012 (QJ) within 2 days: - ascent > 600 hPa - polew. transport > 3500 km - latent heating > 20 K - low PV in the outflow flow structure in extratropical cyclones with strongest latent heat release & precipitation cloud characteristics change along flow: warm  mixed- phase  ice Key cloud system in cyclones: warm conveyor belts

Warm conveyor belts SLP and position of WCB air parcels

warm cloud Warm conveyor belts SLP and position of WCB air parcels

Warm conveyor belts SLP and position of WCB air parcels mixed-phase cloud

Warm conveyor belts SLP and position of WCB air parcels ice clouds

Warm conveyor belts SLP and position of WCB air parcels

Warm conveyor belts Important cross-isentropic transport of low-PV air Joos and Wernli 2012 (QJ)

PV on 320 K Grams et al (QJ) Warm conveyor belts Rossby wave modification due to WCB outflow

Climatology of WCBs (DJF ) WCB (ascent > 600 hPa in 2 days) starting points (t=0) Madonna et al., submitted

Climatology of WCBs (DJF ) WCB outflow points (t=48 h) Madonna et al., submitted

PV anomalies in WCB outflow regions PV anomaly in WCB outflows, averaged between hPa in DJF Madonna et al., submitted

WCBs and forecast errors? select ECMWF 5-day forecasts with 5 largest positive and 5 largest negative SLP errors over Central Europe in YEARMONTHDAY/HH / hPa 0202/ hPa 1207/ hPa 1227/ hPa / hPawinter forecasts / hPa 0114/ hPa 0208/ hPa 0209/ hPa 1021/ hPaET of “Wilma”

Forecast busts: how well represented by EPS? Look at bust no.1: _ daysSLP average over C. Europe analysis1003 hPa deterministic fc1024 hPa EPS1012 – 1037 hPa !!

generation of a positive PV anomaly (downstream trough) WCB  amplified upper-level ridge  downstream trough WCB triggers / enhances downstream Rossby wave activity Forecast busts: common dynamical pattern? In all cases: forecasts have too weak UT ridges in western North Atlantic due to too weak WCBs

PV forecast errors near the tropopause Davies and Didone (MWR in press)

PV forecast errors near the tropopause Davies and Didone (MWR in press) more: Poster 15 today by Suzanne Gray Poster 21 today by Volkmar Wirth

Microphysics in warm conveyor belts Hydrometeors in COSMO model simulation Joos and Wernli 2012 (QJ)

Microphysics in warm conveyor belts Different microphysical processes in COSMO simulation Joos and Wernli 2012 (QJ)

Microphysics in warm conveyor belts Hydrometeors: COSMO vs. IFS from Hanna Joos pressure along WCB

Microphysics in warm conveyor belts Hydrometeors: COSMO vs. IFS from Hanna Joos pressure along WCB more: Poster 10 today by Chris Dearden

T-NAWDEX: International experiment in 2016

T-NAWDEX: An ambitious project for 2016 Key objectives: take observations of - T, q, v in WCB inflow region - cloud properties during WCB ascent - jet stream modification in WCB outflow - downstream impacts Current partners US (HIAPER), Germany (HALO), UK (FAAM), France, Canada others are welcome! Next steps - Further specify scientific objectives and write science plan - Apply for funding in various countries

from Hanna Joos WCBs in the ECHAM5 climate model T42 WCB inflow at t=0 in DJF T106 WCBs inflow at t=0 in DJF

from Hanna Joos WCBs in the ECHAM5 climate model T42 WCB outflow at t=48 h in DJF T106 WCBs outflow at t=48 h in DJF

from Stephan Pfahl percentage of HPE colocated with cyclone (ERA-Interim) Climate model evaluation of link between heavy precipitation & cyclones CCSM4 present day climate simulation with 1 deg resolution CCSM4 – ERA-Interim: >20% difference over subtropical oceans and in the Mediterranean!

Conclusions The mid-latitude flow is strongly influenced by diabatic processes (e.g., in WCBs)  look in detail at link between microphysics and dynamics Associated model uncertainties are substantial  compare models with observations (dedicated field experiments!) and other models Feature-based model evaluation is useful & essential for both NWP and climate prediction