Fig. 1
Past records of the Baltic Sea ice cover. (a) The annual maximum ice extent (MIB) in 1901–2013; (b) the number per decade of severe (dark grey) and extremely severe (light grey) ice winters, that is, winters with MIB exceeding 230×103 km2 or 345×103 km2, respectively, during 1901–2010. The dotted and solid curves in panel (a) show the 10 and 30 yr running means, respectively.
Fig. 2
The frequency distribution of the observed annual maximum ice extent in 1952–2012. The ice winter classification is shown along the upper horizontal axis showing the ice extent limits for mild, average, severe and extremely severe ice winters.
Fig. 3
The coastal grid points in the E-OBS gridded data set for the observational air temperatures. The positions of three of the sub-basins of the Baltic Sea are shown: the Bay of Bothnia, the Gulf of Bothnia and the Gulf of Finland.
Table 1. The CMIP5 models used in this study
MIROC5Japan−3.426.50.412.8(16)2.9(14)MIROC-ESMJapan−0.422.00.283.2(23)3.9(24)MIROC-ESM-CHEMJapan−0.622.60.113.5(25)4.1(25)MRI-CGCM3Japan−4.120.30.211.8(6)2.8(11)BCC-CSM1-1China−5.120.70.722.6(15)3.7(20)INMCM4Russia−3.421.20.141.9(8)2.0(2)NorESM1-MNorway−1.418.80.192.4(11)2.6(10)NorESM1-MENorway−1.218.70.172.0(9)2.8(12)HadGEM2-ESUK−3.422.40.382.8(18)3.4(18)HadGEM2-CCUK−6.124.80.342.8(17)3.9(23)MPI-ESM-LRGermany−2.320.10.341.8(7)2.6(9)MPI-ESM-MRGermany−2.419.70.342.4(12)2.4(5)CNRM-CM5France−3.624.80.562.5(13)3.1(16)IPSL-CM5A-LRFrance−6.727.20.424.0(26)4.6(27)IPSL-CM5A-MRFrance−3.523.70.423.2(24)3.0(15)CMCC-CMItaly−7.021.40.704.5(27)5.2(28)CMCC-CMSItaly−6.422.40.724.9(28)4.4(26)GFDL-CM3USA−1.217.40.463.2(21)3.8(22)GFDL-ESM2MUSA−4.221.60.232.9(19)2.9(13)GISS-E2-RUSA−6.025.60.392.5(14)3.8(21)GISS-E2-HUSA−5.122.80.223.2(22)3.4(17)CCSM4USA−0.821.00.311.6(4)1.9(1)CESM1-CAM5USA−0.920.50.181.6(3)2.5(8)CESM1-BGCUSA−0.420.50.590.8(1)2.5(7)CanESM2Canada−1.322.30.483.0(20)3.6(19)ACCESS1-0Australia−1.818.60.221.4(2)2.1(3)ACCESS1-3Australia−0.317.20.092.2(10)2.5(6)EC-EARTHSeveral0.016.60.271.7(5)2.4(4)28-model mean−3.021.50.352.63.2Observations−2.421.30.48
[i] Columns 3–5 show (i) the November–March mean temperature (°C), (ii) the annual temperature range (°C) and (iii) the trend (°C/decade) in November–March mean temperature, all calculated for the period 1961–2010. The November–March mean temperature change ΔT (°C) between the periods 1971–2000 and 2031–2060 is given separately for the RCP4.5 and RCP8.5 scenarios. All quantities are averaged over the coastal grid points. The ordinal numbers of the models, shown in parentheses, are determined by the magnitude of the projected temperature change (in ascending order) under these two scenarios. The countries involved in the development of the EC-EARTH model are Belgium, Denmark, Ireland, Italy, the Netherlands, Norway, Portugal, Spain, Sweden and Switzerland.
Table 2. Correlations between various temperature indices derived from the 28 GCMs listed in Table 1
November–March mean temperature (i)−0.62−0.48−0.60−0.61Annual temperature range (ii)0.300.450.47November–March temperature trend (iii)0.400.53
[i] The indices representing the simulated recent past climate are (i) the November–March mean temperature, (ii) the annual temperature range, and (iii) the trend in November–March mean temperature, all calculated over the period 1961–2010. The index representing the future climate is the projected change in November–March temperature from the period 1971–2000 to 2031–2060; the correlations for this index are given separately for the RCP4.5 and RCP8.5 scenarios. Temperatures are averaged over the Baltic Sea coastal grid points (Fig. 3). Significance limits for the correlations: 0.37 (p=0.05), 0.48 (0.01), 0.59 (0.001).
Fig. 4
The regression model for the ice extent. The model was fitted to the observed annual maximum ice extent and the November–March mean temperature at coastal grid points in 1952–2012. Some winters with a very high or low value of air temperature or ice extent are annotated. The date refers to the month of January in each winter.
Fig. 5
Temporal evolution of the annual maximum ice extent during the course of this century. The estimates are given separately for the median values, representing a typical winter (line with dots), and for the 5th and 95th percentiles, corresponding to scant and widespread ice cover (lines with crosses). All the results are ensemble means of sea ice projections, derived from temperature responses of 28 individual CMIP5 models (Table 1). The vertical axis on the right shows the upper class limits for mild and average ice winters, according to current standards. The limit for unprecedentedly mild winters is 49×103 km2. (a) The RCP4.5 scenario, (b) the RCP8.5 scenario.
Fig. 6
Inter-model scatter and inter-annual variability of the annual maximum ice extent in 2041–2050. The median and the 5th and 95th percentiles (the horizontal axis) demonstrate inter-annual variability and the box-and-whiskers plots illustrate inter-model scatter. Within each box, the thick solid line refers to the 28-model mean ice extent, also shown in Fig. 5. The box depicts the upper and lower quartiles of the sea ice projections, whiskers the 5th and 95th quantiles. The boxes drawn with solid lines show the RCP4.5 scenario and those with dashed lines RCP8.5. The vertical axis on the right shows the upper class limits for mild and average ice winters. The limit for unprecedentedly mild winters is 49×103 km2.
Fig. 7
The annual maximum ice extent (MIB) in 2041–2050 according to each individual GCM. The numbers on the horizontal axis show the GCMs in ascending order of the projected November–March mean temperature response (for identifying the models, see Table 1). The short black line inside a box denotes the mean value of the distribution, the boxes the 25th and 75th percentiles and the whiskers the 5th and 95th percentiles of inter-annual variability for each model. The vertical axis on the right shows the upper class limits for mild and average ice winters. (a) RCP4.5, (b) RCP8.5.
Fig. 8
The annual maximum coastal sea ice thickness (cm) in typical past and future winters. The calculations with the FDD method are based on (a) observed temperatures in 1971–2000 and (b–e) the 28-model mean temperature projections under the two RCP scenarios for two future decades. The crosses denote the locations of Kemi, Loviisa (Lov) and Vilsandi (Vil).
Fig. 9
Temporal evolution of the mean maximum ice thickness at three locations during the course of this century. The ice projections for Kemi (dots), Loviisa (crosses) and Vilsandi (triangles) are based on the temperature responses of the individual GCMs. The short horizontal lines show the mean values of all the model-based projections for each decade. Note that the position of the symbols within each decade is slightly shifted to make the figure more readable. (a) RCP4.5, (b) RCP8.5.
Table 3. The projected percentage reductions in the mean maximum ice thickness (h)
1971–2000 (cm)2041–2050 (%)2081–2090 (%)2041–2050 (%)2081–2090 (%)Kemi7525 (16–44)37 (19–59)32 (18–50)63 (40–99)Loviisa3840 (20–63)57 (32–81)50 (34–67)89 (64–100)Vilsandi88 (46–100)97 (81–100)97 (80–100)100
[i] The best estimates for the declines from the period 1971–2000 to the decades 2041–2050 and 2081–2090 are based on the 28-model mean temperature projections under the RCP4.5 and RCP8.5 scenarios. The 90% confidence intervals, derived from the inter-model differences in the temperature responses, are given in parentheses. The 30 yr mean values of the observed annual maximum ice thickness in 1971–2000 at Kemi and Loviisa are shown in Column 2.
Table 4. The projected percentage changes in the annual maximum ice extent (MIB) and the mean maximum ice thickness (h)
Mid-century (2040s)
RCP4.51.428−47−46−47−25This study SRES A1B1.419−49−44−47Luomaranta et al., 2010 RCP8.51.828−55−53−54−32This studyLate century (2080s)
RCP4.52.128−58−58−59−37This study SRES B22.54−81−58−51−50Meier et al., 2004; Meier, 2006 150%a2.6b2−74−44−42−42Haapala et al., 2001 SRES A23.34−88−70−65−60Meier et al., 2004; Meier, 2006 RCP8.53.728−76−74−75−63This study
[i] The multimodel mean responses by the 2040s and 2080s under various GHG scenarios are based on previous studies and the current work. The multimodel global mean temperature change (ΔT) is derived directly from the GCMs used (this work and Luomaranta et al. (2010)) or, for the dynamical downscaling experiments, is obtained from the references for the driving GCMs (the other studies). Low, typical and high MIB refer to the 5th, 50th and 95th percentiles of inter-annual variability, respectively (this work), or to the minimum, mean and maximum values during the simulation period. The results for h refer to Kemi (this work) or the centre of the Bay of Bothnia.
[ii] a150% increase in the atmospheric CO2 concentration, compared to pre-industrial conditions. bRäisänen et al. (2001).