Surface-based temperature inversions (SBIs) strongly influence air temperature variability in high-latitude mountains, yet their spatial structure remains poorly resolved. To address this gap, a dense network of air temperature sensors was deployed and elevational transect analysis (ETA) was applied to quantify surface lapse rates (SLRs) and SBI characteristics at fine temporal and spatial scales. SBI frequency and SLR magnitude increased significantly in anomalously warm summers, linking large-scale climate variability and valley-scale elevational temperature patterns. Contrary to the common assumption of linear lapse rates, annual and monthly mean SLRs were most strongly positive within the lowest 60 m of the valleys and weakened rapidly upslope. This highlights the importance of sampling valley bottoms and lower slopes to capture SBI intensity. Using ETA, SBI depth was quantified for the first time and found on average to be shallow (<250 m), rarely extending above the ridgetops (500 m). SBI development and breakup were not solely driven by cold air pooling and daytime convective mixing but were also driven by processes such as warming or cooling aloft. These findings provide new insights into the SBI structure in subarctic valleys. They strengthen the physical basis for representing temperature variability, essential to modeling surface phenomena such as permafrost distribution.
Noad et al. (Tue,) studied this question.
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