CERRA sub-daily regional reanalysis data for Europe on pressure levels from 1984 to present

The Copernicus European Regional ReAnalysis (CERRA) datasets provide spatially and temporally consistent historical reconstruction of meteorological variables in the atmosphere and at the surface. There are four subsets: single levels (atmospheric and surface quantities), height levels (upper-air fields up to 500m), pressure levels (upper-air fields up to 1hPa) and model levels (native levels of the model). This entry provides reanalysis and forecast data on pressure levels for Europe from 1984 to present. Several atmospheric parameters are common to both reanalysis and forecast (e.g. temperature, wind), whilst others are produced only by the forecast model (e.g. cloud cover).
Reanalysis combines model data with observations into a complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved, reprocessed versions of the original observations, which all benefit the quality of the reanalysis product. The CERRA dataset was produced using the HARMONIE-ALADIN limited-area numerical weather prediction and data assimilation system, hereafter referred to as the CERRA system. The CERRA system employs a 3-dimensional variational data assimilation scheme of the atmospheric state at every assimilation time. The reanalysis dataset is convenient owing to its provision of atmospheric estimates at each model domain grid point over Europe for each regular output time, over a long period, and always using the same data format.
The inputs to CERRA reanalysis are the observational data, lateral boundary conditions from ERA5 global reanalysis as prior estimates of the atmospheric state and physiographic datasets describing the surface characteristics of the model. The observing system has evolved over time, and although the data assimilation system can resolve data holes, the much sparser observational networks in the past periods (for example a reduced amount of satellite data in the 1980s) can impact the quality of analyses leading to less accurate estimates. The uncertainty estimates for reanalysis variables are provided by the CERRA-EDA, a 10-member ensemble of data assimilation system.
The added value of the CERRA data with respect to the global reanalysis products is expected to come, for example, with the higher horizontal resolution that permits the usage of a better description of the model topography and physiographic data, and the assimilation of more surface observations.
More information about the CERRA dataset can be found in the Documentation section.

哥白尼欧洲区域再分析（CERRA）数据集提供了大气和地表气象变量在空间和时间上的连续历史重建。该数据集包含四个子集：单层数据（大气和地表量），高度层数据（高空场至500米），压强层数据（高空场至1百帕）以及模型层数据（模型的原始层）。本条目提供了从1984年至今的欧洲压强层再分析和预报数据。一些大气参数对于再分析和预报是共通的（例如温度、风速），而另一些则仅由预报模型产生（例如云量）。再分析通过将模型数据与观测数据结合，运用物理定律构建一个完整且一致的数据集。此一原理，即数据同化，基于数值天气预报中心所采用的方法，其中将先前预报与最新观测数据以最优方式结合，以产生大气状态的最新最佳估计，即分析，进而据此发布更新、改进的预报。再分析以降低的分辨率运行，以便提供覆盖数十年历史的时间序列数据集。由于再分析无需及时发布预报，因此有更多时间收集观测数据，并在时间上追溯得更远时，可采纳改进的、重新处理的原观测数据版本，这些均有益于提升再分析产品的质量。CERRA数据集采用HARMONIE-ALADIN有限区域数值天气预报和数据同化系统生成，以下简称CERRA系统。CERRA系统在每个同化时刻采用三维变分大气状态数据同化方案。再分析数据集的便利之处在于，它为欧洲每个模型域网格点在长时间序列内，每个常规输出时间点，始终采用相同的数据格式，提供大气估计值。CERRA再分析的输入包括观测数据，来自ERA5全球再分析的水平边界条件作为大气状态的先验估计，以及描述模型地表特征的地理数据集。观测系统随着时间的推移而发展，尽管数据同化系统能够处理数据空缺，但过去时期（例如20世纪80年代卫星数据的减少）观测网络更加稀疏，可能会影响分析的质量，导致估计值的不准确性降低。再分析变量的不确定性估计由CERRA-EDA提供，即由10个成员组成的数据同化系统集合。与全球再分析产品相比，CERRA数据集的价值预期体现在，例如，更高的水平分辨率允许使用更好的模型地形和地理数据描述，以及更多地表观测数据的同化。更多关于CERRA数据集的信息可在文档部分查阅。

搜集汇总

背景与挑战

背景概述

CERRA压力层面数据集是欧洲区域再分析数据，提供从1984年至今的高分辨率气象变量历史重建，专注于大气压力层面。该数据集结合模型和观测数据，通过数据同化方法生成长期一致的气象估计，适用于陆地和大气上层研究。