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Sea Ice Concentration Analyses for the Baltic Sea and Their Impact on Numerical Weather Prediction

机译:波罗的海的海冰浓度分析及其对数值天气预报的影响

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Sea ice concentration plays a fundamental role in the exchange of water and energy between the ocean and the atmosphere. Global real-time datasets of sea ice concentration are based on satellite observations, which do not necessarily resolve small-scale patterns or coastal features. In this study, the global National Centers for Environmental Prediction (NCEP) 0.5 deg sea ice concentration dataset is compared with a regional high-resolution analysis for the Baltic Sea produced 2 times per week by the Swedish Meteorological and Hydrological Institute (SMHI). In general, the NCEP dataset exhibits less spatial and temporal variability during the winter of 2003/04. Because of the coarse resolution of the NCEP dataset, ice extent is generally larger than in the SMHI analysis. Mean sea ice concentrations derived from both datasets are in reasonable agreement during the ice-growing and ice-melting periods in January and April, respectively. For February and March, during which the sea ice extent is largest, mean sea ice concentrations are lower in the NCEP dataset relative to the SMHI product. Ten-day weather forecasts based on the NCEP sea ice concentrations and the SMHI dataset have been performed, and they were compared on the local, regional, and continental scales. Turbulent surface fluxes have been analyzed based on 24-h forecasts. The differences in sea ice extent during the ice-growing period in January cause mean differences of up to 30 W m~(-2 )for sensible heat flux and 20 W m~2 for latent heat flux in parts of the Gulf of Bothnia and the Gulf of Finland. The comparison between spatially aggregated fluxes yields differences of up to 36 and 20 W m~(-2) for sensible and latent heat flux, respectively. The differences in turbulent fluxes result in different planetary boundary height and structure. Even the forecast cloud cover changes by up to 40% locally.
机译:海冰浓度在海洋与大气之间的水和能量交换中起着基本作用。海冰浓度的全球实时数据集基于卫星观察,这不一定解决小规模模式或沿海特征。在这项研究中,将全球环境预测中心(NCEP)0.5°海冰浓度数据集与瑞典气象和水文研究所(SMHI)每周产生2次的波罗的海的区域高分辨率分析。通常,NCEP数据集在2003/04年冬季呈现较少的空间和时间变异性。由于NCEP数据集的粗略分辨率,ICE程度通常大于SMHI分析中的冰范围。在1月和4月分别在冰增长和冰冻期间,源自两位数据集的平均型冰浓度分别是合理的一致。 2月和3月,在其中海冰范围是最大的,平均海冰浓度在NCEP数据集中较低,相对于SMHI产品。已经进行了本地NCEP海冰浓度和SMHI数据集的十日天气预报,并在当地,区域和大陆尺度进行比较。基于24小时预测分析了湍流表面助熔剂。在1月的冰增长期间,海冰范围的差异导致合理的热量通量最多30 W m〜(-2)的平均差异,并且在两种藻类中的潜伏热量通量20 W m〜2芬兰湾。空间聚集的助熔剂之间的比较分别产生明智和潜热通量的高达36和20Wm〜(-2)的差异。湍流助熔剂的差异导致不同的行星边界高度和结构。即使预测云覆盖仍然在本地变为高达40%。

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