Are atmospheric models too cold in the mountains? The state of science and insights from the SAIL field campaign

Abstract Mountains play an outsized role for water resource availability, and the amount and timing of water they provide depends strongly on temperature. To that end, we ask: how well are atmospheric models capturing mountain temperatures? We synthesize results showing that high resolution, regionally relevant climate models produce two-meter air temperatures (T2m) colder than what is observed (a “cold bias”), particularly in snow-covered mid-latitude mountain ranges during winter. We find common cold biases in 44 studies across global mountain ranges, including single-model and multi-model ensembles. We explore the factors driving these biases and examine the physical mechanisms, data limitations, and observational uncertainties behind T2m. Our analysis suggests that the biases are genuine and not due to observation sparsity or resolution mismatches. Cold biases occur primarily on mountain peaks and ridges, whereas valleys are often warm biased. Our literature review suggests that increasing model resolution does not clearly mitigate the bias. By analyzing data from the SAIL field campaign in the Colorado Rocky Mountains, we test various hypotheses related to cold biases, and find that local wind circulations, longwave radiation, and surface-layer parameterizations contribute to the T2m biases in this particular location. We conclude by emphasizing the value of coordinated model evaluation and development efforts in heavily instrumented mountain locations for addressing the root cause(s) of T2m biases and improving predictive understanding of mountain climates.