Abstract. Twenty urban neighbourhood-scale eddy covariance flux tower datasets have been harmonized and quality controlled, producing a 50 site-year collection with broad diversity in climate and urban surface characteristics. Observations are gap-filled and prepended with 10 years of reanalysis-derived local data to enable use as spin up and forcing for land surface model evaluation. For both gap filling and spin-up, ERA5 reanalysis meteorological data are bias corrected using tower observations, accounting for diurnal, seasonal and local urban effects not modelled in ERA5. The bias correction methods developed perform well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015 linear regression). Site description metadata includes local land cover fractions (buildings, roads, trees, grass etc.), building height and morphology, aerodynamic roughness estimates, population density and satellite imagery. Together, this collection can help extend our understanding of urban environmental processes through observational synthesis studies or in the evaluation of land surface environmental models in a wide range of urban settings.

中文翻译：

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来自 20 个城市通量塔站点的统一填隙数据集

摘要。已对 20 个城市社区规模的涡流协方差通量塔数据集进行了协调和质量控制，生成了 50 个站点年的集合，在气候和城市表面特征方面具有广泛的多样性。观测结果填补了空白，并以 10 年的再分析得出的本地数据为先导，以便用作地表模型评估的旋转和强制。对于间隙填充和加速，ERA5 再分析气象数据使用塔观测进行偏差校正，考虑到 ERA5 中未建模的昼夜、季节性和局部城市效应。与其他数据集（例如 WFDE5 或 FLUXNET2015 线性回归）中使用的方法相比，开发的偏差校正方法表现良好。场地描述元数据包括当地土地覆盖率（建筑物、道路、树木、草等）、建筑物高度和形态、空气动力学粗糙度估计、人口密度和卫星图像。总之，这个集合可以通过观察综合研究或在广泛的城市环境中评估地表环境模型来帮助扩展我们对城市环境过程的理解。