Historical diurnal temperature range trends constrain future climate projections

The diurnal temperature range (DTR), which measures the difference between daily maximum and minimum temperatures, is a vital indicator of climate extremes. However, predicting future changes in DTR under global warming remains challenging due to significant uncertainties in model projections. This study uncovers a significant link between historical DTR trends and future projections on both global and regional scales. Leveraging this relationship, we introduce a constraining framework to enhance the accuracy of regional climate projections. The mechanism is that the changes in DTR are primarily driven by external forces such as greenhouse gas emissions, rather than internal climate variability. Increasing greenhouse gases reduces cloud cover, which migrates DTR decline by enhancing daytime shortwave radiation and reducing nighttime longwave radiation. While this relationship is generally robust across seasons, it weakens at high latitudes in winter due to minimal solar radiation. Our findings contribute to reducing uncertainties in model projections, offering valuable insights into future changes in DTR and their implications for regional climate responses

气温日较差（diurnal temperature range, DTR）用于表征单日最高与最低气温的差值，是气候极端事件的关键指示因子。然而，受气候模式预估结果存在显著不确定性的影响，全球变暖背景下气温日较差的未来变化预估仍颇具挑战。本研究揭示了全球及区域尺度上，历史气温日较差变化趋势与未来预估结果之间的显著关联。基于该关联，我们提出了一种约束框架，用以提升区域气候预估的准确性。其作用机制为：气温日较差的变化主要受温室气体排放等外强迫因子驱动，而非气候系统内部变率。温室气体浓度升高会减少云量，通过增强日间短波辐射、削弱夜间长波辐射，缓解气温日较差的下降趋势。尽管该关联在多数季节均表现出较强的鲁棒性，但在冬季高纬度地区，由于太阳辐射量极低，其关联强度会出现减弱。本研究成果有助于降低气候模式预估的不确定性，为理解气温日较差的未来变化及其对区域气候响应的影响提供了重要参考。