Impact of snow conditions in spring dynamical seasonal predictions
Impact of snow conditions in spring dynamical seasonal predictions
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DOI：
10.1029/2002jd003113
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发表时间：
2003-08
影响因子：
--
通讯作者：
C. Schlosser;D. Mocko
中科院分区：
文献类型：
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作者：
C. Schlosser;D. Mocko
[1]结合动力季节预报项目，利用海洋-陆地-大气研究中心和戈达德地球观测系统大气环流模式进行了一套数值模拟。这些模拟旨在量化现实雪况对GCM技能的影响。在这项研究中，集合气候模拟进行了北方半球春季（3 - 6月），跨越1982年至1998年。对于这些季节性模拟的每一年，执行一对互补运行。对于其中一个模拟，允许雪条件以交互方式演变;对于另一个模拟，雪条件是根据每日全球雪深分析在GCM的每个陆地模块内规定的。在这项研究中，雪条件对模拟近地面气温的影响进行了评估。结果表明，规定的（可能是改进的）雪条件下的GCM发挥了有益的作用，巧妙地捕捉到的近地面气温年际变化的空间/时间模式，在当地尺度。通过考虑地面能量收支和积雪对地面辐射的影响，从规定的雪场产生的近地面气温技能的局部改善（无论是在空间相关性和均方根误差）被发现是强烈联系在一起的时候，积雪和平均入射短波辐射的年际变化相吻合。规定降雪的这种影响在成熟的冬季积雪广泛消融期间也是最显著的，这通常发生在北方半球的四月期间。总的来说，规定的雪对所有陆地点的影响（即，本地和非本地）显示其对近地面气温技能的影响的混合结果。这些混合的结果很可能强调了GCM将本地化的熟练反应一致地转化为非本地/远程技能的困难。最后，物理参数化的GCM应该得到改善之前，所有的季节性预测增强从改善雪条件可以实现。
[1] A suite of numerical simulations with the Center for Ocean Land Atmosphere (COLA) Studies' and the Goddard Earth Observing System (GEOS) general circulation models (GCMs) has been performed in conjunction with the Dynamical Seasonal Prediction (DSP) Project. These simulations aim to quantify the impact of realistic snow conditions on skill in the GCMs. In this study, ensemble climate simulations conducted for Northern Hemisphere spring (March–June) that span the years 1982–1998 are considered. For each year of these seasonal simulations, a pair of complementary runs is performed. For one of the simulations, snow conditions are allowed to evolve interactively; for the other simulation, the snow conditions are prescribed, according to a daily, global snow depth analysis, within each of the land modules of the GCMs. For this study, the impact of snow conditions on simulated near-surface air temperature is assessed. The results indicate that the prescribed (and presumably improved) snow conditions in the GCMs play a beneficial role in skillfully capturing the observed spatial/temporal patterns of interannual variations of near-surface air temperature, at a local scale. Through consideration of the surface energy-budget and the effect of snow cover on surface albedo, the localized improvement of near-surface air temperature skill (both in the spatial correlations and in the root-mean-square error) that results from the prescribed snowfields is found to be strongly tied to when and where the interannual variabilities of snow cover and mean incident short wave radiation coincide. This impact of prescribed snow is also most considerable during the widespread ablation of the matured winter season snow cover, which typically occurs during April over the Northern Hemisphere. Overall, the impact of the prescribed snow over all land points (i.e., local and nonlocal) shows mixed results in its effect on near-surface air temperature skill. These mixed results most likely underscore the difficulty of the GCMs to consistently translate the localized skillful response into nonlocal/remote skill. In the end, physical parameterizations in GCMs should be improved before all seasonal prediction enhancements from improved snow conditions can be realized.