The Eurasian continent has experienced significant year-to-year variations of summer heat waves during the past decades. Several possible factors, such as ocean temperature, soil moisture, and changes in land use and greenhouse gases, have been identified in previous studies, but the mechanisms are still unclear. In this study, it is found that the Tibetan Plateau snow cover (TPSC) is closely linked to the interannual variations of summer heat waves over Eurasia. The TPSC variability explains more than 30 % of the total variances of heat wave variability in the southern Europe and northeastern Asia (SENA) region. A set of numerical experiments reveal that the reduced TPSC may induce a distinct teleconnection pattern across the Eurasian continent, with two anomalous high pressure centers in the upper troposphere over the SENA region, which may lead to a reduction of the cloud formation near the surface. The less cloud cover tends to increase the net shortwave radiation and favor a stronger surface sensible heat flux in the dry surface condition over the SENA region, resulting in a deeper, warmer and drier atmospheric boundary layer that would further inhibit the local cloud formation. Such a positive land-atmosphere feedback may dry the surface even further, heat the near-surface atmosphere and thereby intensify the local heat waves. The above dynamical processes also operate on interdecadal time scales. Given the reduction of the TPSC could become more pronounced with increasing levels of greenhouse gases in a warming climate, we infer that the TPSC may play an increasingly important role in shaping the summer heat waves over the SENA region in next decades.

Uncertainties in the climate response to a doubling of atmospheric CO2 concentrations are quantified in a perturbed land surface parameter experiment. The ensemble of 108 members is constructed by systematically perturbing five poorly constrained land surface parameters of global climate model individually and in all possible combinations. The land surface parameters induce small uncertainties at global scale, substantial uncertainties at regional and seasonal scale and very large uncertainties in the tails of the distribution, the climate extremes. Climate sensitivity varies across the ensemble mainly due to the perturbation of the snow albedo parameterization, which controls the snow albedo feedback strength. The uncertainty range in the global response is small relative to perturbed physics experiments focusing on atmospheric parameters. However, land surface parameters are revealed to control the response not only of the mean but also of the variability of temperature. Major uncertainties are identified in the response of climate extremes to a doubling of CO2. During winter the response both of temperature mean and daily variability relates to fractional snow cover. Cold extremes over high latitudes warm disproportionately in ensemble members with strong snow albedo feedback and large snow cover reduction. Reduced snow cover leads to more winter warming and stronger variability decrease. As a result uncertainties in mean and variability response line up, with some members showing weak and others very strong warming of the cold tail of the distribution, depending on the snow albedo parametrization. The uncertainty across the ensemble regionally exceeds the CMIP3 multi-model range. Regarding summer hot extremes, the uncertainties are larger than for mean summer warming but smaller than in multi-model experiments. The summer precipitation response to a doubling of CO2 is not robust over many regions. Land surface parameter perturbations and natural variability alter the sign of the response even over subtropical regions.