Diagnostics of the prediction and maintenance of Euro-Atlantic blocking Mark Rodwell, Laura Ferranti, Linus Magnusson Workshop on Atmospheric Blocking 6-8 April 2016, University of Reading European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK ECMWF March 3, 2016 mark.rodwell@ecmwf.int 1
Difficulties in predicting blocking European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 2
Animation of bust forecast Potential Vorticity on 320K Animation of forecast started at 0 UTC on 10 April 2011 European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 3
Animation of bust forecast Potential Vorticity on 320K Block forms in observations, but not in forecast It is difficult, by day 6, to disentangle model error from the natural growth of initial condition uncertainty (chaos) Animation of forecast started at 0 UTC on 10 April 2011 European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 4
Animation of ensemble forecast: Initial peturbations Potential Vorticity on 320K
Animation of ensemble forecast Potential Vorticity on 320K Ensemble forecasting (flow evolution to day-6)
Occasional busts in forecast performance European Z500 skill at day 6 Rodwell et al, 2013, BAMS Bust around 10 April 2011 Initial condition error? Model error? Reduced predictability? Spatial Anomaly Correlation Coefficient for 500 hpa geopotential height in [12.5 o W 42.5 o E, 35 o N 75 o N]. Date is forecast start European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 7
Verifying conditions composited over many bust forecasts 500 hpa geopotential height (Z500) anomaly Rodwell et al, 2013, BAMS Rex-type block Unit = m Bold colours = statistical significance at 5% level Composite of 584 busts in ERA Interim forecast prior to 24 June 2010 European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 8
Regimes 500 hpa geopotential Ferranti et al. 2015, QJRMS m 2 s 2 Regimes based on clustering of daily anomalies for 29 cold seasons (1980-2008) European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 9
Blocking: More poorly predicted and not persistent enough Skill in predicting regime projection From Laura Ferranti NAO+ European Blocking 1 day worse than for NAO+ at CRPS=0.5 Blocking persistence: ECMWF model/analysis Day 0 Day 1 Day 5 Day 7 Day 10 100/100 70/70 44/52 36/47 29/41 European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 10
Ensemble evolution in phase space European Block Ferranti - Magnusson diagram In presentation to ECMWF Scientific Advisor Committee, 2015 - NAO + (similar to phase-space diagram of MJO) Nice way to summarise ENS in two dimensions Transition to blocking wellpredicted 4 days ahead Blocking projection perpetuates to day 10, but spread increases Initial date: 22 September 2015 0UTC Analysis HRES ENS member European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 11
Blocking onset and forecast reliability European Centre for Medium-Range Weather Forecasts Mark J Rodwell 12
Composite initial conditions of bust forecasts Rodwell et al, 2013, BAMS There is an initial flow regime: Rockies trough with high CAPE ahead Bold = 5% significance Conducive to the formation of mesoscale convective events (MCS) Remarkable that we can identify any significant initial conditions 6 days ahead of the busts this must be due to the large composite (584 events) used Other bust causes not so geographically fixed and are not highlighted by this composite-mean CAPE = Convective Available Potential Energy European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 13
Spread-error for Trough/CAPE composite ( MCS) 54 cases 200 hpa geopotential Rodwell et al., 2015, Report to SAC Error 2 Ensemble Variance Residual D+1 Not significant 95% confident D+3 D+5 Following conditions conducive to MCS development, enhanced errors and spread propagate east towards Europe Busts Note: -ve residuals occur in non-trough/cape situation too. Error 2 = EnsVar + Residual Reliability [Residual]=0 +ve residual at D+5 is not significant (Chaos? use bigger sample or shorter leadtime? But analysis uncertainty at D+1?) European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 14
EDA reliability budget: Trough/CAPE composite 54 cases Relative to aircraft observations of zonal wind 200hPa (±15) Rodwell et al., 2015, Report to SAC EDA = Ensemble of Data Assimilations Depar 2 = Bias 2 + EnsVar + ObsUnc 2 + Residual Reliability [Residual]=0 Residual highlights MCS, and suggests lack of background variance. (Obs uncertainty changes 2 nd -order) MCS uncertainty (existence, intensity, location) not well reflected in Jetstream uncertainty (with downstream consequences) Budget useful to diagnose biases, modelling of observation error and representation of model uncertainty (including stochastically-formulated process parametrizations) European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 15
MCS Jetstream interaction (composite) Physics + analysis increment Met3D: Marc Rautenhaus u=25ms -1 Jetstream MCS 3Kd -1 Increments emphasize model systematic error: MCS does not interact enough with Jetstream Also need to strengthen stochastic physics to increase background variance? European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 16
MCS Jetstream interaction (composite) Physics + analysis increment Met3D: Marc Rautenhaus u=25ms -1 Jetstream MCS 3Kd -1 Increments emphasize model systematic error: MCS does not interact enough with Jetstream Also need to strengthen stochastic physics to increase background variance? European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 17
Maintenance of blocking European Centre for Medium-Range Weather Forecasts Mark J Rodwell 18
Initial process tendencies and analysis increment (DJF 2016) T500 Analysis increments suggest model warms over land a little too much (note different contour interval to tendencies) Dynamical and physical process tendencies integrated over the 12h background forecast of the data assimilation (EDA cntl) European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 19
Initial process tendencies and analysis increment (Blocked) T500 Cloud forcing (net latent heating associated with microphysics) highlights Warm Conveyor Belt (WCB) Note negative dynamical tendency in this region Composite over three blocked periods: Dec 4-9, Dec 26-28, Jan 26-28 (24 analysis cycles) European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 20
Initial process tendencies and analysis increment (Blocked-DJF) T500 Convective forcing unchanged relative to full season mean Increments suggest WCB cloud forcing too weak? (can probably discount effect on increments of compositing on observed blocking) Composite over three blocked periods: Dec 4-9, Dec 26-28, Jan 26-28 (24 analysis cycles) minus DJF 2015/16 European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 21
Barotropic vorticity equation in upper troposphere (analysis) Rossby wave source: -. v χ ζ DJF 2016 Blocked Blocked-DJF Vorticity advection by rotational flow: -v ψ. ζ DJF 2016 Blocked Blocked-DJF Divergence associated with WCB Deficiencies in perpetuating blocking associated with slight weakness of WCB heating? Down-stream advection (+ve) and β-effect (-ve) Rossby Wave Source and advection by rotational flow smoothed, averaged over composite and integrated 100 300 hpa European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 22
Summary Onset of blocking Difficult to predict beyond a few days associated with busts Diabatic processes important produce large-amplitude waves that break to form a block associated with instabilities that decrease predictability We may under-represent uncertainty due to systematic errors or deficiencies in stochastic physics Maintenance of blocking Warm conveyor belts important for vorticity forcing that stabilises block We may have too weak cloud forcing in the WCBs European Centre for Medium-Range Weather Forecasts Mark J Rodwell 23
Extra slides European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 24
Skill in predicting from regimes Ferranti et al. 2015, QJRMS ACC European (and Atlantic) blocking is more poorly predicted than NAO Skill in predicting from a given regime. October March, 2007 2012. 95% confidence based on bootstrapping European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 25
Reliability in ensemble forecasting Adapted from Rodwell et al., 2015, QJRMS The importance of reliability is the motivation for using proper scores (such as the Brier Score or CRPS). Reliability (at all leadtimes) should reduce jumpiness of ensemble forecasts Error 2 = EnsVar + Residual (Cross-terms on squaring have zero expectation. EnsVar is scaled variance to account for finite ensemble-size) European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 26
Reliability in ensemble data assimilation Adapted from Rodwell et al., 2015, QJRMS Depar 2 = Bias 2 + EnsVar + ObsUnc 2 + Residual European Centre for Medium-Range Weather Forecasts mark.rodwell@ecmwf.int 27