GloSea4: the Met Office Seasonal Forecasting System A. Arribas, M. Glover, D. Peterson, A. Maidens, M. Gordon, C. MacLachlan, A. Williams, M. Vellinga, A. Scaife, R. Graham and many others EUROBRISA Dec 2010 © Crown copyright Met Office

GloSea4 GloSea4 is not a model. GloSea4 is an Ensemble Prediction System for long-range forecasting. GloSea4 is designed to: Facilitate model development to improve skill beyond ENSO Be flexible to allow extension to monthly and decadal timescales Arribas et al. 2011: The GloSea4 Ensemble Prediction System for Seasonal Forecasting. MWR, in press © Crown copyright Met Office

Model development? Flexible? Sep 2009: Operational implementation of GloSea4 (N96L38O1L42) May 2010: Technical update of system (model versions, etc) Oct 2010: Upgrade to N96L85-O1L75 (developed under GloSea4) Assimilation of sea-ice concentration Update hindcast period to 1996 – 2010 Feb 2011: Monthly system (daily initialisation; 2 extra fcst members per day) © Crown copyright Met Office

GloSea4: How does it run? Forecast Hindcast Hindcast: Run real time weekly; 14 yrs, 3 members/week, 7-months fcst Forecast: Run real-time weekly; 14 members/week, 7-months fcst. Forecast 6th Dec‘10 13th Dec‘10 22th Dec’10 Hindcast 1st Dec 9th Dec 17th Dec 25th Dec 9th Jan 1st Jan 14-yrs: 1996-2010 © Crown copyright Met Office

GloSea4: How does it run? © Crown copyright Met Office

GloSea4: How does it run? © Crown copyright Met Office

Real-time, short hindcast (14-yrs) … Makes possible to link to model development Makes the system flexible and easy to update What are the issues for bias correction? F‘ = F - H What are the issues for skill assessment? © Crown copyright Met Office

Nino 3.4; from Nov, lead 1 The sub-sampling error: 2 sigma of means when sub-sampling N-years between 1960-2005 The signal: Year to year variability (2 sigma) Between 1960-2005 The diamonds are values for the last N-years (Figure courtesy Of Anna Maidens) © Crown copyright Met Office

N. Europe; from Nov, lead 6 The signal: Year to year variability (2 sigma) Between 1960-2005 Climate trend The sub-sampling error (Figure courtesy Of Anna Maidens) © Crown copyright Met Office

Short hindcast TROPICS SEA: The signal we are trying to predict (year to year variability) is larger than the sampling error EXTRA-TROPICS LAND: Larger sampling errors than in tropics (signal still larger). The main issue is low frequency variability (recent years are warmer!) VEREDICT: A 14-yr hindcast is sufficient for bias correction (even before even considering non-stationarity of observing systems) © Crown copyright Met Office

Skill assessment A longer hindcast set could be useful for skill assessment … but, how much can we believe the skill assessment? Hindcast are different to Forecast: Less (and worse) observations; Less ensemble members (~10 vs ~40) Periods with different low freq. variability and forcing © Crown copyright Met Office

Russian Heat-wave: Skill scores for surface temperature ROC score for upper tercile Area of Russian heatwave has skill only marginally better than climatology But skill is low, so even with a signal this strong, there is a high risk of issuing a false alarm. However, skill is higher for outer quintiles, and it’s very hard to assess skill for extreme events, as there just aren’t enough of these in our limited hindcast run to do the stats – but (hypothesis only) our feeling is that there has to be some sort of pretty strong forcing to get into such an extreme region of phases space, and that probably the results of the dynamical model are more trustworthy when it is subjected to strong forcing. © Crown copyright Met Office 12

Russian Heatwave Forecasts initialised in May, 40 members August, ensemble mean July, ensemble mean Moscow Moscow Very strong signal in both July and August ensemble means. Pdfs clearly distinct from climatology (individual ensemble members shown as diamonds) Pdfs for area average over 50-60N, 30-40E (green box). Moscow shown as green star. Pdfs ok here, as anomaly space (not percentage differences) and it’s a reasonable assumption to take temperature anomalies as Gaussian to a first approximation (not entirely correct – slight deviations in Nino regions for SST, for instance). © Crown copyright Met Office 13

So skill assessments should be taken with caution … But I’ll show you some analysis of the GloSea4 hindcast (L38 version) anyway © Crown copyright Met Office

ACC Nino 3.4 GloSea4 GloSea3 © Crown copyright Met Office

RMSE and Spread GloSea4 rmse GloSea3 rmse GloSea4 spread GloSea3 © Crown copyright Met Office

Precip. telec. (Nino – Nina) GloSea4 (89-02) Obs (79-07) JJA DJF © Crown copyright Met Office

ROC Skill Prec. over Great Horn of Africa Nino and Nina years only All years © Crown copyright Met Office

MJO © Crown copyright Met Office

NAO © Crown copyright Met Office

Telec. To Europe Nino - Nina QBO (E) – QBO (W) GloSea4 Obs © Crown copyright Met Office

February 2010 © Crown copyright Met Office

Unless you want to see the forecasts for this winter That’s all … Unless you want to see the forecasts for this winter © Crown copyright Met Office

© Crown copyright Met Office

© Crown copyright Met Office

© Crown copyright Met Office

© Crown copyright Met Office

© Crown copyright Met Office

© Crown copyright Met Office

Gracias © Crown copyright Met Office