{"id":8844,"date":"2025-07-30T14:14:47","date_gmt":"2025-07-30T19:14:47","guid":{"rendered":"https:\/\/permafrostnet.ca\/?p=8844"},"modified":"2026-07-16T16:00:39","modified_gmt":"2026-07-16T21:00:39","slug":"modelling-the-temporal-dynamics-of-subarctic-surface-temperature-inversions-from-atmospheric-reanalysis-for-producing-point-scale-multi-decade-meteorological-time-series-in-mountains","status":"publish","type":"post","link":"https:\/\/permafrostnet.ca\/fr\/blog\/modelling-the-temporal-dynamics-of-subarctic-surface-temperature-inversions-from-atmospheric-reanalysis-for-producing-point-scale-multi-decade-meteorological-time-series-in-mountains\/","title":{"rendered":"Modelling the temporal dynamics of subarctic surface temperature inversions from atmospheric reanalysis for producing point-scale multi-decade meteorological time series in mountains"},"content":{"rendered":"

The vertical profile of air temperatures in subarctic regions is difficult to quantify, especially in areas with mountainous terrain subject to strong and lasting inversion events.\u00a0<\/h2>\n\n\n\n

Relying on observational data is not possible in most places due to sparse weather stations.<\/p>\n\n\n\n

Une \u00e9tude r\u00e9cente de Victor Pozsgay<\/a> tackles the challenge of developing a model that leverages atmospheric reanalysis data and calibrates it using data from five weather stations in the Yukon, Canada.<\/p>\n\n\n\n

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Map of the study area showing the five sites around Dawson City, Yukon Territory, Canada. The basemap is composed of the Esri World Terrain Base and Esri World Hillshade layers, and is projected in the WGS 1984 Web Mercator projection.<\/figcaption><\/figure>\n<\/div>\n\n\n
<\/div>\n\n\n\n

Accurately tracking air temperatures in subarctic mountainous regions is a challenging task, especially due to the prevalence of strong and frequent temperature inversions. These inversions play a critical role in shaping permafrost distribution and regional climate dynamics, yet traditional observations are sparse because of the lack of weather stations in rugged terrain. Victor’s study tackles this challenge by developing a model that leverages atmospheric reanalysis data and calibrates it using actual data from the Yukon. The calibrated model successfully reflects the trends in inversion frequency, strength, and depth that have been evolving since 1948, departing from typical warming patterns seen elsewhere. This approach makes it possible to produce reliable, point-scale meteorological time series for even the most inaccessible locations\u2014an essential advance for studies of permafrost and the broader climate system. The model\u2019s reliance on global reanalysis data and minimal location-specific calibration means it is poised to be both future-proof and widely applicable for regional climate applications, offering a much-needed solution for addressing data gaps in complex, mountainous terrains.<\/p>\n\n\n\n

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Mean daily pressure-level temperatures for several altitudes at and above the Dawson Airport (ERA5 data on 1 February 2007). The dependence with altitude is linear above 2300\u00a0m, where the linear lapse rate can be fitted. Below this, a \u2018\u2018lapse\u2019\u2019 temperature is extrapolated at the grid and station levels. In the grey band, the altitudinal temperature behaviour is inverted, increasing with elevation. The elevation of the five stations used is reported on the right-hand side. The reanalysis data appear in blue, with points representing the pressure level air temperature\u00a0T<\/em>pl<\/sub>\u00a0and a triangle at the grid level for the surface temperature\u00a0T<\/em>sur<\/sub>. Finally, the observed temperature\u00a0T<\/em>obs<\/sub>\u00a0is a green diamond at the station\u2019s elevation.<\/figcaption><\/figure>\n<\/div>\n\n\n
<\/div>\n\n\n\n

Victor Pozsgay\u00a0and\u00a0Stephan Gruber. 2025. Modelling the temporal dynamics of subarctic surface temperature inversions from atmospheric reanalysis for producing point-scale multi-decade meteorological time series in mountains.\u00a0Arctic Science<\/em>.\u00a011<\/strong>: 1-16.\u00a0https:\/\/doi.org\/10.1139\/as-2025-0027<\/a><\/p>\n\n\n\n

<\/div>\n\n\n\n

<\/p>","protected":false},"excerpt":{"rendered":"

Relying on observational data is not possible in most places due to sparse weather stations. A recent study by Victor Pozsgay tackles the challenge of developing a model that leverages atmospheric reanalysis data and calibrates it using data from five weather stations in the Yukon, Canada. 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