Institute of Meteorology and Climatology, University of Natural Resources and Life Sciences, Vienna, Austria.
International Water Management Institute, Lahore, Pakistan.
Sci Data. 2023 Sep 7;10(1):590. doi: 10.1038/s41597-023-02494-4.
The modelling of electricity production and demand requires highly specific and comprehensive meteorological data. One challenge is the high temporal frequency as electricity production and demand modelling typically is done with hourly data. On the other side the European electricity market is highly connected, so that a pure country-based modelling is not expedient and at least the whole European Union (EU) area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21 century. Thus, we have developed the aggregated European wide climate data set SECURES-Met that has a temporal resolution of one hour, covers the whole EU area and other selected European countries, has a reasonable size but considers the high spatial variability.
电力生产和需求的建模需要高度具体和全面的气象数据。一个挑战是时间频率高，因为电力生产和需求建模通常使用每小时的数据。另一方面，欧洲电力市场高度互联，因此纯粹基于国家的建模是不切实际的，至少必须考虑整个欧盟（EU）地区。此外，数据集的空间分辨率必须能够代表热条件，这至少要求在山区具有高空间分辨率。所有这些要求导致历史观测数据量巨大，对于整个 21 世纪的气候变化预测数据量更大。因此，我们开发了聚合的欧洲范围气候数据集 SECURES-Met，它具有每小时的时间分辨率，涵盖整个欧盟地区和其他选定的欧洲国家，具有合理的规模，但考虑到高空间变异性。
