In this study, we show that limitations in the representation of land cover and vegetation seasonality in the European Centre for Medium-Range Weather Forecasting (ECMWF) model are partially responsible for large biases (up to ∼10°C, either positive or negative depending on the region) on the simulated daily maximum land surface temperature (LST) with respect to satellite Earth Observations (EOs) products from the Land Surface Analysis Satellite Application Facility. The error patterns were coherent in offline land-surface and coupled land-atmosphere simulations, and in ECMWF's latest generation reanalysis (ERA5). Subsequently, we updated the ECMWF model's land cover characterization leveraging on state-of-the-art EOs—the European Space Agency Climate Change Initiative land cover data set and the Copernicus Global Land Services leaf area index. Additionally, we tested a clumping parameterization, introducing seasonality to the effective low vegetation coverage. The updates reduced the overall daily maximum LST bias and unbiased root-mean-squared errors. In contrast, the implemented updates had a neutral impact on daily minimum LST. Our results also highlighted the complex regional heterogeneities in the atmospheric sensitivity to land cover and vegetation changes, particularly with issues emerging over eastern Brazil and northeastern Asia. These issues called for a re-calibration of model parameters (e.g., minimum stomatal resistance, roughness length, rooting depth), along with a revision of several model assumptions (e.g., snow shading by high vegetation).

中文翻译：

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升级 ECMWF 耦合系统中的土地覆盖和植被季节性：使用 FLUXNET 站点、METEOSAT 卫星地表温度和 ERA5 大气再分析进行验证

在这项研究中，我们表明，欧洲中期天气预报中心 (ECMWF) 模型中土地覆盖和植被季节性表示的局限性是造成较大偏差的部分原因（高达 ∼10°C，正或负取决于地表分析卫星应用设施的卫星地球观测 (EOs) 产品模拟的每日最高地表温度 (LST)。错误模式在离线地表和耦合的陆地-大气模拟以及 ECMWF 的最新一代再分析 (ERA5) 中是一致的。随后，我们更新了 ECMWF 模型' 利用最先进的 EO（欧洲航天局气候变化倡议土地覆盖数据集和哥白尼全球土地服务叶面积指数）对土地覆盖进行表征。此外，我们测试了聚类参数化，将季节性引入有效的低植被覆盖率。更新减少了总体每日最大 LST 偏差和无偏均方根误差。相比之下，实施的更新对每日最低 LST 的影响是中性的。我们的研究结果还强调了大气对土地覆盖和植被变化的敏感性存在复杂的区域异质性，特别是巴西东部和亚洲东北部出现的问题。这些问题需要重新校准模型参数（例如，最小气孔阻力、粗糙度长度、生根深度），