Franco Molteni, Tim Stockdale, Frederic Vitart, Laura Ferranti ECMWF operational and research activities on extended and long range predictions Franco Molteni, Tim Stockdale, Frederic Vitart, Laura Ferranti WCRP/WGIP WMO/ETOPLSL session March 2014

The operational forecasting system High resolution forecast: twice per day 16 km 91-level, to 10 days ahead Ensemble Prediction System (ENS): twice daily 51 members, 30/60 km 62-level, to 15 days ahead Extended range forecasts : twice a week (Mon/Thursdays) 51 members, 30/60 km 92 levels, to 1 month ahead Long range forecasts: once a month (coupled to ocean model) 51 members, ~80 km 91 levels, to 7 months ahead Eurosip multi-model system : M. France, Met. Off. , NCEP and ECMWF The operational forecasting system at ECMWF consists of: - An high resol. Forecast - An ENSEMBLE of 51 forecasts that also run twice a day up 15 days --- covering the Medium range predictions: beyond 72 hours and up 240. - The Extended forecast system: These forecasts are issued twice a week (Mon/Thu) and run up to 32 days and they are an extension of the ENSEMble forecasting system Long range ensemble forecast issued once a month that run up to 7 months. This presentation is meant to be an introduction to the Extended range forecast: Currently extended range products are provided to the ECMWF Member and Co-operating States and to commercial users WCRP/WGIP WMO/ETOPLSL session March 2014

Extended-range forecasts A 51-member ensemble is integrated for 32 days twice a week (Mondays and Thursdays at 00Z) Atmospheric component: IFS with the latest operational cycle and with a T639L91 resolution till day 10 and T319L91 after day 10. Ocean-atmosphere coupling from day to NEMO (about 1 degree) every 3 hours. Initial conditions: Atmosphere: Operational 4-D var analysis + SVs+ EDA perturbations Ocean: 3D-Var analysis (NEMOVAR) + wind stress perturbations WCRP/WGIP WMO/ETOPLSL session March 2014

Extended-range forecasts WCRP/WGIP WMO/ETOPLSL session March 2014

Extended-range forecasts: Evolution of NAO skill at day 19-25. Difficulty for the MJO to cross the Maritime Continent Too weak MJO teleconnections over the Euro-Atlantic sector Too weak impact of the stratosphere on the troposphere - Evolution of the MJO skill scores (bivariate correlations applied to WHI) since 2002. The MJO skill scores have been computed on the ensemble mean of the ECMWF re-forecasts produced during a complete year. The blue, red and brown lines indicate respectively the day when the MJO bivariate correlation reaches 0.5, 0.6 and 0.8. - Evolution of the NAO skill. Correlation between the ensemble mean NAO index and the NAO index computed from ERA Interim) for the period day 19-25 for all the cases when there is an MJO in the initial conditions (amplitude of the MJO index larger than 1 independently of the phase) and when there is no MJO in the initial conditions (amplitude of the MJO index less than 1) Evolution of the MJO skill scores. The blue, red and brown lines indicate respectively the day when the MJO bivariate correlation reaches 0.5, 0.6 and 0.8. From Vitart 2013 WCRP/WGIP WMO/ETOPLSL session March 2014

Extended-range forecasts: Era-interim Forecast Too weak impact of the stratosphere on the troposphere Lag correlation between NAO and SSW index as function of preceeding or following (positive x-axis) a SSW. The black line shows the lag correlation obtained from all the re-forecasts produced between October 2011 and March 2012 and covering the years 1995 to 2001 and for each ensemble member separately. The red line shows the corresponding verification using ERA Interim. From Vitart 2013 Lag correlation between NAO and SSW index WCRP/WGIP WMO/ETOPLSL session March 2014

Extended-range forecasts: Evolution of RPSS of 2-metre temperature weekly mean anomalies over the northern Extra-tropics This should improve the calibration and allow skill assessment. Evolution of the discrete ranked probability skill score (RPSS) of 2-metre temperature weekly mean anomalies over the northern Extratropics (North of 30N) since 2002. Only land points have been scored. The RPSS has been computed from terciles and for all the ECMWF re-forecasts covering all seasons. The red line shows the RPSS of day 12-18, the brown line represents the RPSS of day 19-25 and the green line the RPSS of day 26-32. Future plans: Extension of the re-forecasts: twice a week, 11-member ensemble. Increased atmospheric horizontal resolution - Possible extension to 45/60 days - Increased oceanic resolution to a ¼ degree + sea ice model WCRP/WGIP WMO/ETOPLSL session March 2014

Long range forecasts: IFS (atmosphere) TL255L91 Cy36r4, 80km grid , full stratosphere Initial conditions: ERA interim / operational NEMO (ocean) Global ocean model, 1x1 resolution, 0.3 meridional near eq. Initial conditions: NEMOVAR (3D-Var) analyses Sea ice Specified values sampled from previous five years Real time forecasts: 51 member ensemble forecast to 7 months SST and atmos. perturbations added to each member Re-forecasts: 1981-2010 (30 years) 15 members every month 51 members for Feb/May/Aug/Nov starts WCRP/WGIP WMO/ETOPLSL session March 2014

Long range forecasts: ENSO forecasts 1981-1995 1996-2010 Well observed period 1996-2010 it improves the skill both in term of acc and rmse spread is also improved despite the change in the persistence. WCRP/WGIP WMO/ETOPLSL session March 2014

Long range forecasts: deterministic scores MAM JJA SON DJF WCRP/WGIP WMO/ETOPLSL session March 2014

Long range forecasts: The dependence on ensemble size Brier Skill Score (BSS) with climatology as a reference as a function of ensemble size. Two versions of the BSS are used: the uncorrected BSS as estimated from the ensemble directly. - an analytical correction of the BSS extrapolating towards a hypothetical infinite ensemble size (Ferro, 2007) . Impact of the seasonal forecast hindcast ensemble size on two estimates of the BSS. The blue dots represent the BSS as estimated from the finite ensemble. The red dots represent an extrapolation for an hypothetical ensemble of infinite size (Ferro, 2007). Different tercile events for 2m temperature and precipitation in DJF (Nov start dates) and JJA (May start dates) are shown for the Tropics, Europe and North America. The score metrics we compare are: Brier Skill Score (BSS) with climatology as a reference. Two versions of the BSS are used: the uncorrected BSS as estimated from the ensemble directly, and an analytical correction of the BSS extrapolating towards a hypothetical infinite ensemble size (Ferro, 2007). The dependence on ensemble size varies with the inherent predictability of the event.

Long range forecasts: Impact of different sources of uncertainty on the reliability skill estimates in the seasonal hind-casts as a function of ensemble size. The error bars represent the 90% confidence intervals of the skill estimates. The blue bars refer to the distribution of reliability obtained from bootstrapping the years of the hindcast period and reflect mainly the interannual variability in the 30-year period. The magenta bars were obtained by randomly subsampling an ensemble of the given size from the full set of 51 members. The score metrics we compare are:  Brier Skill Score (BSS) with climatology as a reference. Two versions of the BSS are used: the uncorrected BSS as estimated from the ensemble directly, and an analytical correction of the BSS extrapolating towards a hypothetical infinite ensemble size (Ferro, 2007).  The slope of the reliability line. The reliability line is computed as a weighted linear regression of all data points in a reliability diagram, see Figure 1. A reliability diagram is a graphical display of the relationship between the forecast probabilities for an event and the corresponding observed frequencies of the events given the forecasts. slope = 1  perfect reliability slope = 0  no reliability slope > 0.5  BSS>0 The inter-annual variability of the hind-cast period (sample) contributes the most to the uncertainties. WCRP/WGIP WMO/ETOPLSL session March 2014

Long range Forecasts: Eurosip verification 2m temp. anomaly correlation for DJF over 14 years (1996-2009) Sys4 One of the Eurosip system with best performance over Europe 19961101 12 19971101 12 19981101 9 19991101 11 20001101 12 20011101 11 20021101 11 20031101 12 20041101 11 20051101 10 20061101 12 20071101 12 20081101 12 20091101 12 20131101 40

Long range forecasts: Present research and future plans: Effect of stochastic physics in mean climate and spread Land surface initialization (SPECS) Experimentation with dynamical sea-ice Impact of enhanced resolution in both ocean and atmospheric components Predictability of the AO and the role of initial conditions Impact of sample and ensemble size on skill measures Next system is likely features: increased vertical levels and a better stratospheric physics Dynamical sea-ice and enhanced resolution for the ocean Impact of enhanced resolution in both ocean and atmospheric components (regimes, tropical storms, MJO) Impact of sample and ensemble size on skill measures (particularly important for regions low signal-to-noise ratios) WCRP/WGIP WMO/ETOPLSL session March 2014

Probabilistic skill scores – NDJFMA 1989-2008 Reliability Diagram Probability of 2-m temperature in the upper tercile Day 19-25 N. Extratropics EUROPE 0.04 0.03 -0.06 -0.09 Slide 47: Reliability of the probability that 2-metre temperature anomalies are in the upper tercile for the period day 19-25 for the Northern Extratropics (left panel) and Europe (right panel). The red (blue) line represents the reliability diagram obtained with all the cases with an MJO (no MJO) in the initial conditions. The numbers represent the Brier Skill Scores. Only land points have been included in the calculation of the reliability diagram and the Brier skill scores. This figure shows that the MJO has a major source of predictability for the time range day 19-25 in the ECMWF forecasting system. MJO in IC NO MJO in IC WCRP/WGIP WMO/ETOPLSL session March 2014

MJO forecast: The time evolution of the MJO predicted by the EPS is described by a multivariate MJO index (Wheeler and Hendon 2004 Mon. Wea. Rev. vol. 132, 8 p 1917-1932). The diagram represents 8 regions of the two dimensional phase space defined by the first two principal components (RMM1 and RMM2) of a combined fields (OLR zonal wind at 850 hPa and 200 hPa) averaged between 15S and 15N. Individual ensemble member values at day 1, 5, 10, 15 and 20 are represented respectively by a red, pink orange blue and green circles. The ensemble mean values (black triangles) are joined by a solid black line and the analysis values of the preceeding 30 days are joined by a grey line. The grey squares represent the analysis values of the preceeding 5, 10, 15, 20, 25 and 30 days. Points representing sequential values trace anticlock-wise trajectories around the origin,indicating systematic eastward propagation of the MJO. Large amplitudes (outside of the circle) signify strong cycles of the MJO, while weak activity appears as rather random motion near the origin. WCRP/WGIP WMO/ETOPLSL session March 2014

Tropical storm density Tropical storm density during the period October to March 1995-2001 (left panels) and when there is an MJO in Phase 2 or 3 (right panels). The top panels show observations (from Joint Typhoon Warning Center), the middle panel shows the tropical storm densities from the re-forecasts produced in 2011, and the bottom panel shows the tropical storm densities from the re-forecasts produced in 2002. The tropical storm density is calculated by computing the number of tropical storms passing within 500 kilometres and then normalise that number by the total number of tropical storms over the whole basin WCRP/WGIP WMO/ETOPLSL session March 2014

Weekly mean Accumulated Cyclone Energy (ACE) The ACE of a tropical storm is calculated by summing the square of the estimated maximum sustained velocity of every active tropical storm at six-hour intervals. The ACE of a time period is the sum of the ACEs for each storm and takes into account the number, strength, and duration of all the tropical storms in the period. The 51-member ensemble forecast is compared with the model climatology (5-member ensemble over the past 18 years). A Wilcoxon-Mann-Whitney (WMW) test is then applied to evaluate if the predicted tropical storm frequency/location are significantly different from the climatology. The ocean basins where the WMW test detects a significance larger than 90% have a shaded background. Green bars represent the ensemble mean of the forecast and orange bars represent climatology. The values of each bar are written in black. Available are also the tropical storm frequency: The "Tropical storms" have a relatively large range of wind speed (wind speed higher than 17m*s(-1)), so includes storms of hurricane strength. And Probabilities of tropical storms will strike within 300Km for weekly periods. WCRP/WGIP WMO/ETOPLSL session March 2014

Skill of the ECMWF Monthly Forecasting System ROC score: 2-meter temperature in the upper tercile Day 5-11 Day 12-18 Day 19-25 Day 26-32 Slide 16 Map of ROC scores of the probability that 2-meter temperature averaged over the period day 12-18 is in the upper tercile. Only the scores over land points are shown. The terciles have been defined from the model climatology. The verification period is Oct 2004-May 2008. Red areas indicate areas where the ROC score exceeds 0.5 (better than climatology). This plot shows that the coupled model performs better than climatology for the period days 12-18. For the period days 19-26, the skill is much lower than for days 12-18, as expected. The red is largely dominating overall, suggesting that the model generally performs better than climatology at this time scale. Europe seems to be a difficult region, with very low skill at this time range. Tropical regions display the strongest skill after 30 days, suggesting that the coupled model at this time range starts to behave more like seasonal forecasting. WCRP/WGIP WMO/ETOPLSL session March 2014

Conclusion SSTs, Soil moisture, stratospheric initial conditions and MJO are source of predictability at the intra-seasonal time scale. In particular the MJO has a significant impact on the forecast skill scores beyond day 20. Model improvements, particularly in simulating the MJO activity are likely to be beneficial for monthly forecasting. The monthly forecasting system produces forecasts for days 12-18 that are generally better than climatology and persistence of day 5-11. Beyond day 20, the monthly forecast is marginally skilful. For some applications and some regions, these forecasts could however be of some interest. WCRP/WGIP WMO/ETOPLSL session March 2014

Real time forecast Reforecast (1981-2010) 51 members every months 15 members every months 51 members for May and Nov. Previous studies (Déqué, 1997; Kumar et al., 2001) suggested that larger sizes of the reforecast ensembles would be needed for regions of low inherent predictability The operational seasonal forecasts (System 4) are based on an ensemble of 51 members for their global predictions. However the ensemble size of the corresponding retrospective forecasts is 15 members over 30 years period (1981-2010). Just for May and November starting dates the reforecast has been expanded to 51 members. We study the impact of the ensemble size on probabilistic forecast skill, in particular on Brier Skill Score and reliability, for regions of high and low signal-to-noise ratios.