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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Impact of Snow Initialization in Subseasonal-to-Seasonal Winter Forecasts With the Norwegian Climate Prediction Model
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Impact of Snow Initialization in Subseasonal-to-Seasonal Winter Forecasts With the Norwegian Climate Prediction Model

机译:雪初始化在挪威气候预测模型中暂时的冬季冬季预测中的影响

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Snow initialization has been previously investigated as a potential source of predictability at the subseasonal-to-seasonal (S2S) timescale in winter and spring, through its local radiative,thermodynamical, and hydrological feedbacks. However, previous studies were conducted with low-top models over short periods only. Furthermore, the potential role of the land surface-stratosphere connection upon the S2S predictability had remained unclear. To this end, we have carried out twin 30-member ensembles of 2-month (November and December) retrospective forecasts over the period 1985-2016, with either realistic or degraded snow initialization. A high-top version of the Norwegian Climate Prediction Model is used, based on the Whole Atmosphere Community Climate Model, to insure improved coupling with the stratosphere. In a composite difference of high versus low initial Eurasian snow, the surface temperature is strongly impacted by the presence of snow, and wave activity fluxes into the stratosphere are enhanced at a 1-month lag, leading to a weakened polar vortex. Focusing further on 7 years characterized by a strongly negative phase of the Arctic Oscillation, we find a weak snow feedback contributing to the maintenance of the negative Arctic Oscillation. By comparing the twin forecasts, we extracted the predictive skill increment due to realistic snow initialization. The prediction of snow itself is greatly improved, and there is increased skill in surface temperature over snow-covered land in the first 10 days, and localized skill increments in the mid-latitude transition regions on the southern flanks of the snow-covered land areas, at lead times longer than 30 days.
机译:以前通过其当地的辐射,热力学和水文反馈,雪地初始化以前被调查为冬季和春季季期期(S2S)时间尺度的潜在可预测性来源。然而,以前的研究仅在短时间内进行了低顶模型。此外,土地表面平层连接对S2s可预测性的潜在作用仍然不清楚。为此,我们在1985 - 2016年期间的2个月(11月和12月)的追溯预测中进行了双胞胎30成员合奏,具有现实或降级的雪初始化。基于整个大气群落气候模型,使用了挪威气候预测模型的高顶版本,以确保与平流层的改进耦合。在高与低次欧亚雪的复合差异中,表面温度受到雪的存在强烈影响,并且在一个月的滞后增强了平流层的波浪活性通量,导致极性涡旋弱化。通过北极振荡的强烈负阶段,进一步关注7岁,我们发现弱雪反馈促进了对负北极振荡的维持。通过比较双胞胎预报,我们由于现实的雪初始化而提取了预测技能增量。雪本身的预测得到大大提高,在前10天内,在雪花覆盖的土地上的表面温度提高,以及雪覆的土地区域的南部侧翼的中纬度过渡区域的局部技能增量,在超过30天的交付时间。

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