Spatiotemporal variability of surface-based temperature inversions in high-latitude northcentral Yukon valleys utilizing a dense network of elevation transects

Permafrost distribution in high-latitude continental mountains is a product of both latitudinal and elevationally controlled attributes. Frequently occurring surface-based temperature inversions (SBIs) significantly modify surface lapse rates (SLRs) annually. We aim to identify and quantify patterns of SBI characteristics in two proximal yet morphologically and vegetatively dissimilar central Yukon valleys. Elevational transect analysis is applied by using sensors in valley bottoms and 100 m upslope to determine in situ SLRs for the study period (August 2017 – August 2021). SLRs were shown to vary significantly between these dissimilar valleys. Climate reanalysis products (ClimateNA and Globsim) underestimated or almost entirely missed the presence of strong SBIs which produce annual average SLRs that range from 0.46 to 1.2 °C 100 m−1. The magnitude of these hyper-inversions was grossly underpredicted by previous surface air temperature modelling that attempted to account for SBIs across Yukon. Our results support the previously conceptualized framework that strong SBIs influence surface air temperatures and the pattern of permafrost distribution.

This paper studies surface air temperature inversions and their impact on air pollution under the background of meteorological conditions in southern Poland. The relationship of temperature gradients and air quality classes with weather conditions in the most urbanized and polluted part of Poland as represented by the Upper Silesia region (USR) within the administrative boundaries of the Górnośląsko-Zagłębiowska Metropolis (GZM) is presented. Based on probability analysis this study hierarchized the role of the selected weather elements in the development of surface-based temperature inversion (SBI) and air quality (AQ). The thresholds of weather elements for a rapid increase in the probability of oppressive air pollution episodes were distinguished. Although most SBI occurred in summer winter SBIs were of great importance. In that season a bad air quality occurred during >70% of strong inversions and >50% of moderate inversions. Air temperature more strongly triggered AQ than SBI development. Wind speed was critical for SBI and significant for AQ development. A low cloudiness favored SBI occurrence altered air quality in winter and spring during SBI and favored very bad AQ5 (>180 µg/m3) occurrence. The probability of high air pollution enhanced by SBI rapidly increased in winter when the air temperature dropped below −6 °C the wind speed decreased below 1.5 m/s and the sky was cloudless. Changes in the relative humidity did not induce rapid changes in the occurrence of bad AQ events during SBI

The frequency, strength and seasonal variations of surface-based temperature inversions (SBTIs) in Upper Silesia (Southern Poland) were examined using data from January 2001 to September 2020. Based on the air temperatures recorded at the meteorological station of the Institute of Earth Sciences in Sosnowiec (263 m a.s.l.) at heights of 2 m and 88 m above the ground, the vertical temperature gradient of the 100-m layer (γSos100 m) was determined. A lapse rate of γSos100 m > 0.5 K was defined as a temperature inversion. The measurements for 00 UTC (midnight) and 12 UTC (midday) were compared with data from the upper air station in Wrocław (116 m a.s.l.) located in the Lower Silesia Lowland, approximately 170 km NW of Sosnowiec. Based on soundings from Wrocław, in addition to the temperature gradient in the lower 100-m layer of air (γWrc100), three other characteristics of SBTIs were calculated: inversion depth (ID) or thickness in metres, inversion strength (ΔTi) in K and vertical temperature gradients across the whole SBTI layer γi in K 100 m−1. On an annual basis, the frequency of nighttime SBTIs (γ > 0.5 K 100 m−1) ranged from 47% in Sosnowiec to almost 59% in Wrocław. At both stations, the fewest SBTIs occurred in winter (23–38%) and the most in summer (64–75%). Moreover, they were more frequent in spring (52–61%) than in autumn (49–59%). The SBTI frequency was very low during the midday hours, amounting to 0.6–0.7% days a year, and it increased to 1–2% only in winter. Annually, the depth of 81% of inversions ranged between 50 and 300 m, varying seasonally from almost 67% in winter to 87% in summer. The presented research shows that SBTIs in winter were among the main factors contributing to a high concentration of particulate matter pollutants in the ground-level atmosphere. During nights with temperature inversions, the annual mean PM10 concentration reached 125% of the mean value, ranging from 114% in summer to 189% in winter.

Spatio-temporally differentiated impacts of temperature inversion on surface PM2.5 in eastern China

Spatial maps of the air and ground thermal regime were generated for four Yukon valleys. The aim was to model air, ground surface, and ground temperature (at fine spatial resolution) using locally measured inverted surface lapse rates (SLR) to better predict temperature along an elevation gradient. These local models were then compared to a regional permafrost probability model, which utilized differing inversion assumptions, as well as circumpolar and national models generated without considering inversions. Overall, permafrost probability in the regional model matched well with the local models where assumptions of treeline and inverted SLRs held true. When normal SLRs were assumed, permafrost presence was overestimated in each valley. This discrepancy was greatest at high elevations where permafrost was predicted to be the coldest and most widespread. However, the difference between valleys was dependent on surface and subsurface characteristics such as higher snow cover, mature forest, or thick organic layers which show a greater disassociation from the air temperature overall. Appropriate characterization of the SLR is essential for accurate predictions of the ground thermal regime’s spatial distribution and permafrost presence. These models also provide a starting point for better predictions of warming in these valleys and other areas subject to inversions of similar magnitudes.

Abstract. Ecological and hydrological modelling at the regional scale requires distributed information on weather variables, and temperature is important among these. In an area of basin and range topography with a wide range of elevations, such as south-eastern Arizona, measurements are usually available only at a relatively small number of locations and elevations, and temperatures elsewhere must be estimated from atmospheric lapse rate. This paper derives the lapse rates to estimate maximum, minimum and mean daily temperatures from elevation. Lapse rates were calculated using air temperatures at 2 m collected during 2002 at 18 locations across south-eastern Arizona, with elevations from 779 to 2512 m. The lapse rate predicted for the minimum temperature was lower than the mean environmental lapse rate (MELR), i.e. 6 K km–1, whereas those predicted for the mean and maximum daily temperature were very similar to the MELR. Lapse rates were also derived from radiosonde data at 00 and 12 UTC (5 pm and 5 am local time, respectively). The lapse rates calculated from radiosonde data were greater than those from the 2 m measurements, presumably because the effect of the surface was less. Given temperatures measured at Tucson airport, temperatures at the other sites were predicted using the different estimates of lapse rates. The best predictions of temperatures used the locally predicted lapse rates. In the case of maximum and mean temperature, using the MELR also resulted in accurate predictions. Keywords: near surface lapse rates, semi-arid climate, mean minimum and maximum temperatures, basin and range topography

ABSTRACTPermafrost is present at multiple elevations with no defined lower limit in the southern Yukon Territory, Canada. Empirical statistical modelling of permafrost probability in the region required the development of equivalent elevation, a new variable that reflects measured differences between surface air temperature lapse rates below and above treeline. In areas where surface lapse rates are negative (normal) but gentle up to the altitudinal treeline, equivalent elevation results in a compressed elevational range. Where surface lapse rates are positive (inverted) in the forest due to the strength of winter inversions, equivalent elevations calculated for valley floors are higher than those at treeline. There is a strong relationship between the magnitude and sign of surface lapse rates below treeline and the annual amplitude of monthly air temperatures at nearby climate stations, which permits prediction of equivalent elevation for the entire region. Permafrost probability modelling using equivalent elevation produced statistically significant results in several study areas whereas actual elevation values did not. The concept is of particular use where forested areas are underlain by permafrost and may be transferable to areas with similar terrain and climate such as those in the Canadian Northwest Territories, Alaska and Mongolia. Copyright © 2011 John Wiley & Sons, Ltd.

Cold-air pooling is an important topoclimatic process that creates temperature inversions with the coldest air at the lowest elevations. Incomplete understanding of sub-canopy spatiotemporal cold-air pooling dynamics and associated ecological impacts hinders predictions and conservation actions related to climate change and cold-dependent species and functions. To determine if and how cold-air pooling influences forest composition, we characterized the frequency, strength, and temporal dynamics of cold-air pooling in the sub-canopy at local to regional scales in New England, USA. We established a network of 48 plots along elevational transects and continuously measured sub-canopy air temperatures for 6-10 months (depending on site). We then estimated overstory and understory community temperature preferences by surveying tree composition in each plot and combining these data with known species temperature preferences. We found that cold-air pooling was frequent (19-43% seasonal occurrences) and that sites with the most frequent inversions displayed inverted forest composition patterns across slopes with more cold-adapted species, namely conifers, at low instead of high elevations. We also observed both local and regional variability in cold-air pooling dynamics, revealing that while cold-air pooling is common, it is also spatially complex. Our study, which uniquely focused on broad spatial and temporal scales, has revealed some rarely reported cold-air pooling dynamics. For instance, we discovered frequent and strong temperature inversions that occurred across seasons and in some locations were most frequent during the daytime, likely affecting forest composition. Together, our results show that cold-air pooling is a fundamental ecological process that requires integration into modeling efforts predicting future forest vegetation patterns under climate change, as well as greater consideration for conservation strategies identifying potential climate refugia for cold-adapted species.

Estimates of melt from debris-covered glaciers require distributed estimates of meteorological variables and air temperature in particular. Meteorological data are scarce for this environment, and spatial variability of temperature over debris is poorly understood. Based on multiple measurements of air and surface temperature from three ablation seasons (2012–14) we investigate the variability of temperature over Lirung Glacier, Nepal, in order to reveal how air temperature is affected by the debris cover and improve ways to extrapolate it. We investigate how much on-glacier temperature deviates from that predicted from a valley lapse rate (LR), analyse on-glacier LRs and test regression models of air temperature and surface temperature. Air temperature over the debris-covered glacier tongue is much higher than what a valley LR would prescribe, so an extrapolation from off-glacier stations is not applicable. An on-glacier LR is clearly defined at night, with strong correlation, but not during the day, when the warming debris disrupts the elevation control. An alternative to derive daytime air temperature is to use a relationship between air and surface temperature, as previously suggested. We find strong variability during daytime that should be accounted for if these regressions are used for temperature extrapolation.

Understanding surface temperature is important for habitability. Recent work on Mars has found that the dependence of surface temperature on elevation (surface lapse rate) converges to zero in the limit of a thin CO2 atmosphere. However, the mechanisms that control the surface lapse rate are still not fully understood. It remains unclear how the surface lapse rate depends on both greenhouse effect and surface pressure. Here, we use climate models to study when and why “mountaintops are cold.” We find the tropical surface lapse rate increases with the greenhouse effect and with surface pressure. The greenhouse effect dominates the surface lapse rate transition and is robust across latitudes. The pressure effect is important at low latitudes in moderately opaque (τ ∼ 0.1) atmospheres. A simple model provides insights into the mechanisms of the transition. Our results suggest that topographic cold‐trapping may be important for the climate of arid planets.

Wintertime cold air pools (CAPs) are common across the Western United States and result in cold, dense air trapped in valley basins. The CAPs are characterized by a stable atmospheric boundary layer, leading to cold air and low wind speeds. While CAP formation occurs nightly, the CAP conditions can persist into daytime and often last for multiple days (i.e., persistent cold air pool or PCAP), resulting in poor air quality in populated areas. The presence and strength of CAPs can be calculated using data from radiosondes, surface weather stations at varying elevations, and indirectly through air pollution monitors. Because vertical profile data are often limited to twice daily radiosondes, and are spatially sparse, numerical models can be a useful substitute. This work uses the European Centre for Medium-Range Weather Forecasts (ECMWFs) Reanalysis v5 (ERA) atmospheric reanalysis to provide data to classify wintertime CAP events without radiosonde observations. An automated CAP classification method using ERA outputs is evaluated using afternoon radiosonde observations in six cities (Salt Lake City, Utah; Reno, Nevada; Boise, Idaho; Denver, Colorado; Las Vegas, Nevada; Medford, and Oregon). Using this CAP determination method, days with CAP events are analyzed in 13 locations, 6 with radiosonde observations and 7 without, including the Central valley of California. The CAP classification method is evaluated at these 13 locations across the Western US over the study period of 2000–2022. The results show that the ERA model performs similarly to the radiosonde observations when used to identify CAP events. Therefore, ERA can be used to provide a reasonable estimate of CAP conditions when radiosonde data are unavailable. Providing consistent CAP classifications across space and time are necessary for regional scale CAP studies, such as human health effects modeling over large spatial and temporal scales.

A set of 17 air temperature and relative humidity sensors were used to analyze the temporal variability of surface air temperature (Tair), wet bulb temperature (Twb), and daily snowmaking hours (SM, number of hours per day with Twb < − 2 °C), lapse rates, and the occurrence of thermal inversions at the Formigal ski resort (Spanish Pyrenees) from December to March during three consecutive ski seasons (2012–2013, 2013–2014, and 2014–2015). The Tair and Twb lapse rates showed strong hourly and daily variability, with both exhibiting almost identical temporal fluctuations. The Twb exhibited average lapse rates that were slightly steeper (− 5.2 °C/km) than those observed for Tair (− 4.9 °C/km). The less steep lapse rates and most thermal inversions were observed in December. Days having less (more) steep Tair and Twb lapse rates were observed under low (high) wind speeds and high (low) relative humidity and air pressure. The temporal dynamics of the SM lapse rates was more complex, as this involved consideration of the average Tair in the ski resort, in addition to the driving factors of the spatio-temporal variability of Twb. Thus, on a number of cold (warm) days, snowmaking was feasible at all elevations at the ski resort, independently of the slopes of the lapse rates. The SM exhibited an average daily lapse rate of 8.2 h/km, with a progressive trend of increase from December to March. Weather types over the Iberian Peninsula tightly control the driving factors of the Tair, Twb, and SM lapse rates (wind speed, relative humidity, and Tair), so the slopes of the lapse rates and the frequency of inversions in relation to elevation for the three variables are very dependent on the occurrence of specific weather types. The less steep lapse rates occurred associated with advections from the southeast, although low lapse rates also occurred during advections from the east and south, and under anticyclonic conditions. The steepest Tair and Twb lapse rates were observed during north and northwest advections, while the steepest rates for SM were observed during days of cyclonic circulation and advections from the northeast.

While the Hawaiian Islands are experiencing long‐term warming, spatial and temporal patterns are poorly characterized. Drawing on daily temperature records from 309 stations (1905–2017), we explored relationships of surface air temperatures (Tmax, Tmin, Tavg, and diurnal temperature range) to atmospheric, oceanic, and land surface variables. Statistical modeling of spatial patterns (2006–2017) highlighted the strong negative influence of elevation and moisture on air temperature and the effects of distance inland, cloud frequency, wind speed, and the local trade wind inversion on the elevation dependence of surface air temperature. We developed time series of sea level air temperature and surface lapse rate by modeling surface air temperature as a simple function of elevation and found a strong long‐term (1905–2017) warming trend in sea level Tmin, twice that of Tmax (+0.17 vs +0.07°C/decade), suggesting regional warming, possibly enhanced by urbanization and cloud cover effects. Removing this trend, sea level Tmax and Tmin tracked SST and rainfall at decadal time scales, while Tmax increased with periods of weakened trade winds. Sea level air temperatures correlated with North Pacific climate indices, reflecting the influence of regional circulation via SST, rain, clouds, and trade winds that modulate environmental warming across the Hawaiian Islands. Increasing (steeper) Tmax surface lapse rates for the 0‐ to 1,600‐m elevation range (into the cloud zone) over 1978–2017 coincide with observations of marine boundary layer drying and rising cloud base heights, suggesting a need to better understand elevation‐dependent warming in this tropical/subtropical maritime environment and associated changes to cloud formation and persistence.

Cold-air pools pose a significant challenge for numerical weather prediction models, primarily because they are often characterized by very stable stratification. Traditional surface-layer parameterizations, which rely on Monin-Obukhov similarity theory, tend to be ineffective in these conditions. Additionally, the processes involved are highly localized and occur on small spatial scales, necessitating models with high horizontal and vertical resolutions. Within the TEAMx research programme, a model intercomparison study is being undertaken. The goal is to assess how well various numerical weather prediction models, each with a horizontal grid spacing of 1 km, can simulate a nocturnal cold-air pool within an Alpine valley. Five models are currently participating in the intercomparison study, including both operational and research models, specifically AROME, ICON, Meso-NH, the Unified Model, and WRF. For the intercomparison, a case study was selected from a multi-day undisturbed period during the PIANO (Penetration and Interruption of Alpine Foehn) field campaign conducted in the Inn Valley, Austria, in fall 2017.The presentation will show first results from the model intercomparison study. An extensive dataset is available for model evaluation from the PIANO measurement campaign, including vertical profiles of wind, temperature, and humidity from multiple Doppler wind lidars and a microwave temperature and humidity profiler, surface observations including surface-energy fluxes from multiple automatic weather stations and eddy-covariance stations, and spatially distributed temperature measurements from a dense network of temperature sensors. The model evaluation and intercomparison covers the entire lifecycle of the cold-air pool, from its initial formation in the afternoon to its dissipation the following day. The analysis addresses specifically the question of how well the simulations represent the cold-air pool's characteristics, such as its intensity, vertical structure, and spatial heterogeneity, and the processes contributing to the temporal evolution and spatial structure of the cold-air pool.

[1] This study assesses near surface lapse rates and temperatures over the past decade at two heights from the Oklahoma Mesonet. A statistically significant change in lapse rate was detected of −0.21 ± 0.09°C (10 m)−1 per decade. The trend of nighttime lapse rate was about three times larger than the magnitude of trend of the daytime lapse rate. The lapse rate trends at the time of the daily maximum and minimum temperatures were larger during calm conditions. Significantly, changes of temperature trends at a single height were inconclusive when the data was not segmented by wind speed classes. For daily maximum and minimum station series at two heights, the temperature trends of these station series were the largest for daily minimum temperature at 1.5 m under calm conditions, and the second largest for daily minimum temperatures at 9.0 m under calm conditions. These observations document that monitoring long term near-surface daily minimum temperature trends at a single level on light wind nights will not produce the same trends as for long term temperature trends at other heights near the surface.