Quantifying how land surface height, such as that of the Tibetan region, has changed with time is crucial for understanding a range of Earth processes, including atmospheric dynamics, biotic evolution and tectonics. Elevation reconstructions are highly uncertain and controversial, in part because of assumptions used in their calculation. The largest uncertainties are in the choice of unconstrained thermal lapse rates. Thermal lapse rates are defined as a change in surface temperature with altitude and have long been used to estimate paleoelevation. If we know both the lapse rate and the temperature at two sites at different elevations, then in theory we can calculate their height difference. There are different types of lapse rates (Dry, Saturated, Environmental and Terrestrial), yet which is the most useful for paleoaltimetry is unknown. Previous paleoelevation studies have often used observed modern-day global annual mean free air or terrestrial thermal lapse rates to measure elevation change, with the assumption that observed modern-day lapse rates are similar to those of the past. Here, using the HadCM3L paleoclimate model we demonstrate that Eocene global mean free air and terrestrial thermal lapse rates are not only different from the modern, but also show little predictive skill in reproducing prescribed model topography. Free-air lapse rates are largely insensitive to increased pCO₂ (showing only a decrease of ∼0.1-0.5 °C/km), whereas lapse rates at Earth's surface, the most applicable for fossil-based paleoaltimetry, differed significantly locally and globally in the past compared to the Pre-industrial. This suggests that modern terrestrial lapse rate expressions are inappropriate for tracking altitude changes through geologic time. Moist processes and resultant moisture content of airmasses play a critical role in much of this uncertainty. The use of a wet-bulb temperature-derived lapse rate reduces this uncertainty significantly improving the predictive skill. Local terrestrial thermal lapse rates can be useful in paleoaltimetry, but only through climate model mediation where uncertainties can be reduced and quantified. Critically, paleoclimate models offer the opportunity to provide mean sea-level surface temperature to derive an elevation estimate where proxy-based values may not be available.

量化地表高度（例如藏族地区的地表高度）如何随时间变化是了解一系列地球过程（包括大气动力学，生物演化和构造）的关键。高程重建具有高度不确定性和争议性，部分原因是其计算中使用了一些假设。最大的不确定性在于选择不受约束的热失效率。热失误率定义为地表温度随海拔高度的变化，长期以来一直用于估算古海拔。如果我们知道两个海拔高度不同的地点的流逝速率和温度，那么从理论上讲我们可以计算出它们的高度差。失败率有不同类型（干燥，饱和，环境和陆地），但对于古生物学而言最有用的是未知的。以前的古海拔研究经常使用观测到的现代全球年平均自由空气或陆地热流失率来测量海拔变化，并假设观测到的现代流失率与过去相似。在这里，使用HadCM3L古气候模型，我们证明始新世的全球平均自由空气和陆地热流失率不仅与现代不同，而且在再现规定的模型地形方面几乎没有预测能力。自由空气流失率对增加不敏感 使用HadCM3L古气候模型，我们证明始新世的全球平均自由空气和陆地热流失率不仅与现代不同，而且在再现规定的模型地形方面几乎没有预测能力。自由空气流失率对增加不敏感 使用HadCM3L古气候模型，我们证明始新世的全球平均自由空气和陆地热流失率不仅与现代不同，而且在再现规定的模型地形方面几乎没有预测能力。自由空气流失率对增加不敏感p CO ₂（仅下降约0.1-0.5 °C / km），而地球表面的流失率，最适用于基于化石的古时计，过去在局部和全球与工业化前相比有很大差异。这表明现代地面失速率表达式不适用于跟踪地质时间内的海拔变化。在许多不确定性因素中，潮湿过程和空气气团中的水分含量起着至关重要的作用。使用湿球温度衍生的失败率降低了这种不确定性，从而显着提高了预测技巧。局部地球的热失效率在古时制中可能是有用的，但只能通过可以减少和量化不确定性的气候模式调解。至关重要的是