CERRA-Land sub-daily regional reanalysis data for Europe from 1984 to present

The Copernicus European Regional ReAnalysis Land (CERRA-Land) dataset provides spatially and temporally consistent historical reconstructions of surface and soil variables at the same horizontal resolution as the CERRA high-resolution reanalysis.
The need for precipitation and surface variables at an ever-increasing spatial and temporal resolution is a recurrent demand. These variables allow, among other things, to address water resource management issues and to carry out climate change impact studies. Regional surface reanalyses are a way to reconstruct these variables for past periods covering several decades using state-of-the-art models. 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 usually 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 dataset was produced using the CERRA-Land system which consists of a land surface modelling platform SURFEX (V8.1) and a daily (24-h) total accumulated precipitation assimilation system. Most of the data are forecasts generated based on the open-loop integration of the SURFEX. The observations are not directly used in their production but have an indirect influence through the atmospheric forcing (e.g. 2m temperature) from the CERRA high-resolution reanalysis and precipitation reanalysis system used to integrate in time the SURFEX model. No downscaling method was used to build up the input forcing data because the CERRA-Land system has the same integration domain (e.g. grid spacing, orography) as the CERRA high-resolution atmospheric reanalysis. SURFEX was run offline, that is without feedback to the atmospheric analysis performed in the CERRA data assimilation cycles.
To solve both heat and water transfer equations in the soil, a discretisation of the soil into 14 layers was used. The surface precipitation analysis and the 12 snow layers model included in the CERRA-Land system significantly improve the representation of the snowpack over Europe in comparison with the CERRA dataset.
This dataset describes the evolution of soil moisture, soil temperature and snowpack in a consistent view over several decades at an enhanced resolution compared to ERA5 and ERA5-Land. The temporal and spatial resolutions of CERRA-Land data recommend this dataset, for example, for water resource management and climate change studies.
The added value of the CERRA-Land 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.
More information about the CERRA-Land dataset can be found in the Documentation section.

哥白尼欧洲区域再分析陆地（CERRA-Land）数据集提供了与CERRA高分辨率再分析相同的水平分辨率下，历史地表和土壤变量的空间和时间一致性重建。对降水和地表变量在日益增加的空间和时间分辨率的需求成为一种常态。这些变量能够解决水资源管理问题，并执行气候变化影响研究。区域地表再分析是利用最先进的模型，对涵盖数十年过去时期这些变量的重建方法。再分析通过结合模型数据和观测数据，利用物理定律构建一个完整且一致的数据集。这一被称为数据同化的原则，基于数值天气预报中心所采用的方法，即通过将先前预报与最新可用的观测数据以最优方式结合，产生新的最佳大气状态估计，称为分析，进而发布更新、改进的预报。再分析以相同的方式运作，但通常以较低分辨率进行，以便提供涵盖数十年时间的数据集。再分析不受发布及时预报的限制，因此有更多时间收集观测数据，并在时间上追溯得更远时，允许摄入改进的、重新处理的原始观测数据的更好版本，所有这些都有利于再分析产品的质量提升。该数据集是使用CERRA-Land系统生成的，该系统包括一个陆地表面建模平台SURFEX（V8.1）和一个每日（24小时）累积降水量同化系统。大部分数据是基于SURFEX的开环积分生成的预报，观测数据在生产过程中并未直接使用，但通过CERRA高分辨率再分析和降水量再分析系统中的大气强迫（例如2米温度）对SURFEX模型进行时间积分的间接影响。由于CERRA-Land系统与CERRA高分辨率大气再分析具有相同的积分域（例如网格间距、地形），因此未使用降尺度方法构建输入强迫数据。SURFEX以离线方式运行，即在没有反馈到CERRA数据同化周期中进行的大气分析的情况下运行。为了解决土壤中的热和水传输方程，使用了对土壤进行14层离散的方法。CERRA-Land系统中包含的表面降水分析和12层雪层模型与CERRA数据集相比，显著改善了欧洲雪覆盖的表示。与ERA5和ERA5-Land相比，该数据集在多个十年内对土壤湿度、土壤温度和雪覆盖的演变提供了一致的视角，并提高了分辨率。CERRA-Land数据的时间分辨率和空间分辨率推荐该数据集用于水资源管理和气候变化研究。与全球再分析产品相比，CERRA-Land数据的附加值预计将来自更高的水平分辨率，这允许使用更好的模型地形和地貌数据的描述。更多关于CERRA-Land数据集的信息可以在文档部分找到。