Numerical model forecasts of near-surface temperatures are prone to error. This is because terrain can exert a strong influence on temperature that is not captured in numerical weather models due to spatial resolution limitations. To account for the terrain height difference between the forecast model and reality, temperatures are commonly corrected using a vertical adjustment based on a fixed lapse rate. This, however, ignores the fact that true lapse rates vary from 1.2 K temperature drop per 100 m of ascent to more than 10 K temperature rise over the same vertical distance. In this work, we develop topographic visualization techniques to assess the resulting uncertainties in near-surface temperatures and reveal relationships between those uncertainties, features in the resolved and unresolved topography, and the temperature distribution in the near-surface atmosphere. Our techniques highlight common limitations of the current lapse rate scheme and hint at their topographic dependencies in the context of the prevailing weather conditions. Together with scientists working in postprocessing and downscaling of numerical model output, we use these findings to develop an improved lapse rate scheme. This model adapts to both the topography and the current weather situation. We examine the quality and physical consistency of the new estimates by comparing them with station observations around the world and by including visual representations of radiation-slope interactions.

翻译：近地表温度的数值模型预报易产生误差。这是由于地形对温度具有显著影响，而数值天气模型因空间分辨率限制未能捕捉这种影响。为弥补预报模型与实际地形之间的高度差异，通常采用基于固定递减率的垂直调整来修正温度。然而，这种方法忽略了真实递减率的变化范围——从每上升100米温度下降1.2K到相同垂直距离内温度上升超过10K。本研究开发了地形可视化技术，用于评估近地表温度的不确定性，并揭示这些不确定性与已解析及未解析地形特征、近地表大气温度分布之间的关系。我们的技术突显了当前递减率方案的常见局限性，并暗示其在主导天气条件下的地形依赖性。通过与从事数值模型输出后处理和降尺度研究的科学家合作，我们利用这些发现开发了一种改进的递减率方案。该模型能同时适应地形特征和实时天气状况。我们通过全球站点观测数据对比，并结合辐射-坡度相互作用的可视化表征，检验了新估计值的质量与物理一致性。