The Arctic region shows some of the world's most significant signs of climate change; for instance, a negative trend in summer sea‐ice cover of around 15% per decade and Arctic amplified surface‐air warming that is three times the global average. The atmospheric energy transport plays an important role in the Arctic climate. Recently a Fourier‐based method for studying the atmospheric energy transport contribution by planetary‐ and synoptic‐scale waves has been proposed. Recent studies based on this method show that planetary waves contribute more than synoptic waves to the atmospheric energy transport into the Arctic. However, this Fourier method suffers from being incapable of resolving spatially localized systems such as cyclones. Here an attempt to evaluate this problem is presented by applying the method on synthetic and reanalysis data. In addition, an alternative method based on a wavelet decomposition is proposed and compared with the Fourier‐based method. The wavelet method is based on localized basis functions which should be capable of resolving these localized systems. The wavelet method shows an impact of synoptic‐scale transport on Arctic temperatures which is not captured by the Fourier method, whilst the planetary‐scale effect of both methods appears similar.

中文翻译：

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比较子波和傅里叶关于子午能量传输分解为天气和行星分量的观点

北极地区显示出世界上一些最重要的气候变化迹象。例如，夏季海冰覆盖率出现了每十年约15％的消极趋势，北极的地面空气变暖现象是全球平均水平的三倍。大气能量传输在北极气候中起着重要作用。最近，提出了一种基于傅立叶的方法来研究行星和天气尺度波对大气能量传输的贡献。基于这种方法的最新研究表明，行星波比天气波对大气能量输送到北极的贡献更大。但是，这种傅立叶方法不能解决诸如旋风分离器的空间局部系统。在此尝试通过将方法应用于合成和重新分析数据来评估此问题。此外，提出了一种基于小波分解的替代方法，并将其与基于傅立叶的方法进行了比较。小波方法基于局部基函数，该局部基函数应能够解析这些局部系统。小波方法显示了天气尺度传输对北极温度的影响，而傅立叶方法并未捕获这一影响，而两种方法的行星尺度影响似乎相似。