1. 1.Introduction Prediction of sea-ice is not only important for shipping but also for weather as it can have a significant climatic impact. Sea-ice predictions are important for accurate inter-annual to decadal prediction of climate in coupled climate models. This is a perfect model study using four case studies to investigate the mechanisms of late winter (maximum) sea-ice predictability in the Greenland Sea. The Greenland Sea sea-ice depth index is defined as the 30°W—10°E, 68°N—80°N average sea-ice depth. GCEP Leon Hermanson, Rowan Sutton, Sarah Keeley, Dept of Meteorology, University of Reading, UK Multi-year Predictability of Greenland Sea Late Winter Sea-ice Depth 5. Conclusions If the large-scale influence is as high in reality as in the model, then dynamical models and good observations of temperature down to several hundred metres are beneficial for successful sea-ice prediction in the Greenland Sea. This is a perfect model study, so the results do not suggest that 40 month forecasts are feasible. However, studying these long timescales reveals the influence of the large-scale ocean forcing and the mechanisms that may give rise to predictability. The main large-scale forcing for the Greenland sea-ice depth is ocean heat transport related to an increased MOC. The sea-ice can create conditions that ensure that the same sea-ice depth anomalies re-appear the next spring, but this local forcing is less powerful than the large-scale forcing (at least in the Greenland Sea). We have not yet fully determined the role of the atmosphere in forcing predictability of sea ice depth. Figure 3 Greenland Sea sea-ice depth index (30°W—10°E, 68°N— 80°N) average anomaly for four predictability experiments represented by different colours. Units are metres. The vertical line at 39 months show the time of the anomaly maps of figure 4. Figure 2 Difference in instantaneous (00h 1 Dec- ember) ocean heat content initial conditions in the top 500m for the four experiments. Units are 10 -19 J. Figure 4 Predictability plumes for Greenland Sea sea- ice depth index (1 st column), meridional overturning circulation (MOC) index at 50°N (2 nd column) and ocean heat transport at 67°N (3 rd column) for each experiment (rows). For each ensemble, the thick line indicates the ensemble mean and the lighter shading shows one standard error of this mean calculated from the ensemble spread. Note that (f) is based on 5 members in each ensemble, all other quantities are shown for the full 10 members. Figure 1 Maps of predictable sea-ice depth in each experiment for February March April average of year 4 (a 40 month forecast). Contours show anomalous depth (interval 0.2m) and coloured contours show depth anomalies that are significant at 95% significance. Experiment 1 is top left, 2 is top right, 3 is bottom left and 4 is bottom right. 3. Predictability Results Figure 2 shows the initial ocean 500m heat content in each experiment. Figure 3 shows anomalies in the Greenland Sea sea-ice depth index for the four experi- ments. Large recurrent anomalies appear in February, March, April (FMA) and disappear in August, September, October (ASO) each year. Figure 1 shows a map of the predictable sea- ice depth in FMA, almost 3½ years from the start of the forecast. Experiments 1,3 and 4 show anomalies larger than 0.5m in the Greenland Sea. Comparing Figures 1 and 2, there appears to be a correlation between the sign of the initial ocean heat content and the sign of the sea-ice depth anomaly. 4. Possible Mechanisms The sea-ice may be influenced by large-scale and local ocean mechanisms, ice advection and atmospheric forcing. The Greenland Sea sea-ice depth index is correlated with the meridional overturning circulation (MOC) and local ocean heat transport (OHT), see Table 1 and Figure 4. Local upper ocean temperature anomalies are re- inforced by anomalies in sea-ice cover and influence the ice growth the following year, see Figure 5. QuantityC1C2C3C4C5Average Correlation MOC 30N0.00-0.30-0.45-0.48-0.15-0.28 MOC 50N-0.10-0.48-0.64-0.27-0.34-0.37 OHT 67N-0.44-0.60-0.62-0.61 -0.57 Table 1 Correlations between the Greenland Sea sea-ice depth index and MOC at 30°N, 50°N and ocean heat transport at 67°N. Correlations are shown for five 20th century coupled model integrations 1950—2000 (C1—5) and their average. FMAMJJ ASONDJ Figure 6 Climatological sea-ice depth in the HadCM3 model representative of the 1970-1990 era averaged from 80 years of simulation for February, March, April (FMA), May, June, July (MJJ), August, September, October (ASO) and November, December, January (NDJ). Note the non-linear scale of depth. Units are metres. Figure 5 Greenland Sea temperature anomaly in the top 650m against time for the four experiments. The area average used for the plots is the same as for the ice index. 2. Experimental Set Up The Hadley Centre HadCM3 coupled atmosphere- ocean-ice model is used. Four experiments with start dates 1 December 1982, 1971, 1974 and 1977 respectively. Each experiment consists of two different 10- member ensembles started from two different initial conditions consistent with the external forcing of the start date. Initial conditions were taken from five simulations of the 20 th century with estimated volcanic aerosol and greenhouse gas forcings. The HadCM3 sea-ice scheme is simple by modern standards, but should be able to give the broad picture. Climatology is shown in Figure 6. Predictability that arises from the difference in initial conditions between the experiment ensembles is found by looking for significant differences between the two ensemble means. Anomalies presented in the figures are the difference between the two ensemble means.