Using the current seasonal cycle to constrain snow albedo feedback in future climate change

Abstract

[1] Differences in simulations of climate feedbacks are sources of significant divergence in climate models' temperature response to anthropogenic forcing. Snow albedo feedback is particularly critical for climate change prediction in heavily-populated northern hemisphere land masses. Here we show its strength in current models exhibits a factor-of-three spread. These large intermodel variations in feedback strength in climate change are nearly perfectly correlated with comparably large intermodel variations in feedback strength in the context of the seasonal cycle. Moreover, the feedback strength in the real seasonal cycle can be measured and compared to simulated values. These mostly fall outside the range of the observed estimate, suggesting many models have an unrealistic snow albedo feedback in the seasonal cycle context. Because of the tight correlation between simulated feedback strength in the seasonal cycle and climate change, eliminating the model errors in the seasonal cycle will lead directly to a reduction in the spread of feedback strength in climate change. Though this comparison to observations may put the models in an unduly harsh light because of uncertainties in the observed estimate that are difficult to quantify, our results map out a clear strategy for targeted observation of the seasonal cycle to reduce divergence in simulations of climate sensitivity.Citation: Hall, A., and X. Qu (2006), Using the current seasonal cycle to constrain snow albedo feedback in future climate change, Geophys. Res. Lett., 33, L03502,

Recent Progress in Constraining Climate Sensitivity With Model Ensembles

“…Rather, a direct physical linkage, where both present-day behavior and future changes can be shown to be functions of the same process, is desirable. However, as demonstrated in recent work, even in instances where such a linkage would be expected based on simple mechanisms (e.g., [13]), the connection between the present-day and future behavior can be complex.…”

“…Addressing these contributions and providing an early example of an EC, Hall and Qu [13] assessed the simulated loss of springtime snow cover in the northern hemisphere normalized by warming and demonstrated its strong relationship to the sensitivity of snow cover loss under future warming. Under the assumption that both the present-day and future snow cover losses are driven primarily by temperature, rather than changes in snowfall, the study would seem to provide a simple framework for quantifying a key cryospheric contribution to ECS.…”

An analysis of present and future seasonal Northern Hemisphere land snow cover simulated by CMIP5 coupled climate models

“…Groisman et al, 1994;Déry and Brown, 2007). (ii) Hall and Qu (2006) and Fletcher et al (2012) have shown this feedback to be correctly represented only in a minority of the CMIP3 (Coupled Model Intercomparison Project -Phase 3: http://www-pcmdi.llnl.gov/ ipcc/about ipcc.php) models. Due to its low heat conductivity, snow also effectively insulates the underlying soil, with important effects on deep soil temperatures and permafrost extent (Zhang, 2005;Lawrence and Slater, 2010;Gouttevin et al, 2012).…”

Impact of different cumulus convective parameterization schemes on the simulation of precipitation over China

“…For the summer mean precipitation, the RMSE decreases from 3.42 to 3.48 for the Kain-Fritsch and Grell schemes, in southeastern China, but tends to overestimate the summer and annual mean precipitation in the Yangtze River basin, and Southern and Northeastern China regions, which are underestimated by the Grell scheme. The WRF downscaling skill reduction in winter for precipitation may be associated with model deficiencies in representing the snow feedback processes (Hall and Qu, 2006). For the annual cycle of regional mean precipitation, the Grell scheme produces lower correlations with observations than the Kain-Fritsch scheme in most regions, but reduces the wet bias in the Northwest, Northern China and Tibetan Plateau regions.…”