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Intercomparison and validation of snow albedo parameterization schemes in climate models

机译：气候模型中雪反照率参数化方案的比对和验证

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摘要

Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings.
机译：众所周知，雪反照率对于高纬度和高海拔的热交换至关重要，由于其强大的正反馈特性，它也是通用循环模型（GCM）的重要参数。在这项研究中，对七个GCM雪反照率方案和一个多元线性回归模型进行了比较，并对照了来自斯瓦尔巴特群岛，法国阿尔卑斯山和前苏联六个站点的59年现场数据进行了验证。对于每个站点，通过构建95％的置信区间，可以确定用于模拟雪反照率的重要气象参数。发现重要参数为：温度，积雪深度，正度日和积雪深度的模拟值，并建立了包含这些参数的多元线性回归模型。总体而言，比对表明，在所有模型中，模拟雪反照率的变化都大于观测到的反照率，而且该反照率通常被低估了。另外，对于几个模型，在冬季雪变质过程中，雪反照率的下降速度比观测到的反照率更快或幅度更大。温度依赖性方案和预后方案均显示出缺点。

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