Comparison between two single-column models designed for short-term fog and low-clouds forecasting
Comparison between two single-column models designed for short-term fog and low-clouds forecasting
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用于短期雾和低云预报的两种单柱模型的比较
DOI：
10.5209/rev_fite.2007.v19.12432
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发表时间：
2008
影响因子：
2
通讯作者：
T. Bergot
中科院分区：
文献类型：
--
作者：
E. Terradellas;T. Bergot
在航空运输领域，雾和低云的影响很大。因此，为了减轻能见度降低的负面影响，对精确预报的需求越来越大。然而，这些预测的制作仍然是一个尚未解决的问题。在一些地方，一维（单栏）模型已被用于地方预报。它们为雾或低云形成中相关的复杂物理机制提供了许多见解。然而，在大多数情况下，与地面或大气水平不均匀性相关的任何影响仍然无法控制。2005年，在雾和低云预报领域进行了不同单柱模式的比对试验。由于结果有用但不确定，因此商定对H1 D和COBEL-ISBA进行大规模和系统的比较。在相互比较期间，这些模型已在巴黎戴高乐国际机场运行。模型之间最显着的差异是夜间冷却速率，平均而言，H1 D的冷却速率更强。原因可能在于H1 D预测的云覆盖范围比COBEL-ISBA少。检验结果表明，初始化是超短期预报的一个重要方面，COBEL-ISBA在这一点上似乎表现得更好。他们还表明，水平不均匀性的处理是很重要的较长的预测范围，和H1 D似乎在这方面表现得更好。
There is a large impact of fog and low clouds in the field of airborne transportation. As a consequence, there is an increasing demand of precise forecasts in order to mitigate the negative effects of visibility reduction. Nevertheless, the production of these forecasts constitutes an unsolved issue yet. In several places, one-dimensional (single-column) models have been tested for local forecasts. They provide many insights into the complex physical mechanisms that are relevant in the fog or low clouds formation. Nevertheless, any influence related with surface or atmospheric horizontal unhomogeneity remains, in most cases, out of control. In 2005, an intercomparison experiment among different single-column models in the field of fog and low clouds forecast was carried out. Since the results were useful but inconclusive, it was agreed to undertake a massive and systematic comparison between H1D and COBEL-ISBA. During the intercomparison period, the models have been run for Paris-Charles de Gaulle International Airport. The most significant difference between the models is found in the nocturnal cooling rate, which is -on average- stronger in H1D. The reason could lie in the fact that H1D predicts less cloud coverage than COBEL-ISBA. The verification results show that the initialization is an important aspect for very short-term forecast and COBEL-ISBA seems to perform better for this point. They also demonstrate that the treatment of horizontal heterogeneities is important for longer forecast scopes, and H1D seems to perform better for this aspect.