Low-level Temperature Inversion Research Articles

On the Shallowing of Antarctic Low-Level Temperature Inversions Projected by CESM-LE under RCP8.5

On the Shallowing of Antarctic Low-Level Temperature Inversions Projected by CESM-LE under RCP8.5

Meteorological Formation Mechanisms and Potential Sources of an Ozone Pollution Process in Winter of 2022 in Guangdong Province

Meteorological conditions play an important role in seasonal ozone variations. In order to understand the meteorological formation mechanisms of ozone pollution in Guangdong Province in winter, the moderate ozone pollution process in Guangdong Province from January 3-6, 2022 was selected for comparison with that in autumn (high pollution season) of 2015 to 2021. The research was based on ground and vertical sounding data and reanalysis data of air quality and meteorological elements. Eight cities exceeded the standard during the pollution process, among which Zhaoqing showed moderate pollution (219 μg·m-3) on January 4th. The average O3-8h concentration in Guangdong Province was 123 μg·m-3, which was 21% higher than that in historical autumn. However, its scope of pollution was less than the historical pollution processes in autumn. Lower wind speed, longer sunshine hours, and airflow reflux effect under local circulation were the most important ground-level meteorological conditions for the ozone pollution process, whereas lower temperature might be an important reason for its small scope of pollution. Vertical detection analysis showed that the combined effect of low-level temperature inversion layer, stronger downdraft, and lower wind speed kept the NO2 concentrations at a high level, and further induced a higher increment of ozone concentration in the morning (34.2 μg·m-3 higher than that in the non-pollution period). The downward transport of ozone in the residual layer aggravated the ozone pollution on January 4th. The accumulation of ozone and its precursors was an important factor of the aggravation of ozone pollution the following day. Airflow trajectory analysis revealed that the ground-level ozone was affected by horizontal transport and vertical mixing of pollutants. Potential sources at 10 m were mainly distributed in the coastal areas from Fujian to Guangdong, and the scope of potential sources was concentrated in Guangdong as the height increased. Airflow backward trajectories at different heights during the ozone process passed over the areas of potential sources in Guangdong, which indicated that the local emissions in Guangdong had a greater impact on the ozone pollution process.

Assessment of AIRS Version 7 Temperature Profiles and Low-Level Inversions with GRUAN Radiosonde Observations in the Arctic

The extensive global climate observing system (GCOS) reference upper-air network (GRUAN) datasets provide a chance to validate newly released Atmospheric Infrared Sounder (AIRS) version 7 (v7) products over the Arctic. This manuscript reports on the analysis performed to evaluate errors from AIRS version 6 (v6) and v7 temperature profiles and to characterize the derived low-level temperature inversion (LLI) representativeness in the Arctic region. The AIRS averaging kernel, representing the AIRS measurement sensitivity, is applied to reduce the vertical resolution of the radiosonde profiles for comparison. Due to improved retrieval algorithms, v7 produces smaller biases in the troposphere and suppresses the cold bias in v6. Nevertheless, the profile-averaged root mean square error (RMSE) increased by over 30% in v7, particularly in the winter half-year when v7 showed a larger RMSE below 800 hPa. The AIRS temperature retrieval accuracy is primarily sensitive to surface type and cloud fraction. Compared to v6, v7 has less bias over frozen land and sea ice in different cloud fraction conditions. However, the RMSEs of v7 are more sensitive to the effective cloud fraction (ECF) and are highly influenced by a more significant contribution from nonfrozen land samples. Compared to the kernel-averaged radiosonde profiles, more than 80% of the temperature profiles from v6 and v7 accurately detect LLIs. The discreteness of the AIRS’s predefined pressure level results is consistent with the radiosondes only 65% of the time for LLI depth calculation. In contrast, the AIRS can obtain LLI intensity with a relatively high correlation (>0.9). With the AIRS temperature retrieval in the boundary layer further improved, it has the potential to be used as an independent LLI detector in the Arctic region.

High Ice Water Content Conditions Associated with Wintertime Elevated Convection in the Midwest

AbstractAircraft flying through areas of high ice water content (HIWC) can experience engine damage and/or failure. HIWC is typically associated with convection and the microphysical properties of tropical oceanic and coastal convection are well documented as a result of several field campaigns in the past decade. HIWC appears to be less common in extratropical convection, but instances of HIWC-related aircraft issues have been recorded in extratropical weather, even during winter. The present study documents the microphysical properties of HIWC between −25° and 0°C and the meteorological and thermodynamic conditions around that HIWC from five flights from the In-Cloud Icing and Large-Drop Experiment (ICICLE) in the midwestern United States in February 2019. All five cases contained elevated convection above a strong low-level temperature inversion. Values for top-of-inversion mixing ratios and total column precipitable water were about 5 g kg−1and 20 mm, respectively, according to soundings near each case. A maximum ice water content of 2.1 g m−3was observed over a length scale of about 500 m, and ice particle size distributions had mean volume equivalent diameters around 1000μm. Supercooled drizzle droplets were also observed in the vicinity of the HIWC, raising questions about the possible role of secondary ice production via the freezing and shattering of supercooled large droplets in HIWC formation. The generalizability of these results is limited by the small number of cases, but they provide some of the first in situ observations of extratropical winter HIWC and highlight the need for continued research on these conditions.Significance StatementHigh ice water content (HIWC) conditions can cause engine damage, stall, and failure in aircraft and can cause air data probes to report erroneous values. Most research on HIWC has focused on tropical convection. This paper serves to draw more attention to the aviation hazard posed by extratropical winter HIWC and the need for additional research into these environments. The cases examined also contained supercooled precipitation-sized liquid droplets. Combined with other recent research, these observations may help to motivate laboratory experiments investigating the role of secondary ice production via droplet freezing and shattering in the formation of HIWC.

Improving thermodynamic profile retrievals from microwave radiometers by including radio acoustic sounding system (RASS) observations

Abstract. Thermodynamic profiles are often retrieved from the multi-wavelength brightness temperature observations made by microwave radiometers (MWRs) using regression methods (linear, quadratic approaches), artificial intelligence (neural networks), or physical iterative methods. Regression and neural network methods are tuned to mean conditions derived from a climatological dataset of thermodynamic profiles collected nearby. In contrast, physical iterative retrievals use a radiative transfer model starting from a climatologically reasonable profile of temperature and water vapor, with the model running iteratively until the derived brightness temperatures match those observed by the MWR within a specified uncertainty. In this study, a physical iterative approach is used to retrieve temperature and humidity profiles from data collected during XPIA (eXperimental Planetary boundary layer Instrument Assessment), a field campaign held from March to May 2015 at NOAA's Boulder Atmospheric Observatory (BAO) facility. During the campaign, several passive and active remote sensing instruments as well as in situ platforms were deployed and evaluated to determine their suitability for the verification and validation of meteorological processes. Among the deployed remote sensing instruments were a multi-channel MWR as well as two radio acoustic sounding systems (RASSs) associated with 915 and 449 MHz wind profiling radars. In this study the physical iterative approach is tested with different observational inputs: first using data from surface sensors and the MWR in different configurations and then including data from the RASS in the retrieval with the MWR data. These temperature retrievals are assessed against co-located radiosonde profiles. Results show that the combination of the MWR and RASS observations in the retrieval allows for a more accurate characterization of low-level temperature inversions and that these retrieved temperature profiles match the radiosonde observations better than the temperature profiles retrieved from only the MWR in the layer between the surface and 3 km above ground level (a.g.l.). Specifically, in this layer of the atmosphere, both root mean square errors and standard deviations of the difference between radiosonde and retrievals that combine MWR and RASS are improved by mostly 10 %–20 % compared to the configuration that does not include RASS observations. Pearson correlation coefficients are also improved. A comparison of the temperature physical retrievals to the manufacturer-provided neural network retrievals is provided in Appendix A.

Characteristics of low-level temperature inversions over the Arctic Ocean during the CHINARE 2018 campaign in summer

Across the Arctic Ocean, the semi-permanent sea-ice layer insulates the atmosphere from the Arctic Ocean, thereby influencing the lower boundary conditions of the atmosphere in this region. The presence of a temperature inversion predominantly characterizes the Arctic lower troposphere throughout the year. The 9th Chinese National Arctic Research Expedition took place in the Pacific Sectors of the Arctic Ocean from July to September 2018, gathering high-resolution radiosonde data to provide a detailed structure of the low-level temperature inversion (LLI) over the summer months. Statistical analyses showed that LLIs occurred most frequently below 500m and were generally weaker and shallower than those occurring during the winter months. Low-level inversions are influenced by both local meteorology and large scale synoptic conditions. The continual presence of low-level clouds or fog tends to lift the inversion layer at the local scale, transferring it from a surface-based inversion (SBI) to an elevated inversion (EI). By contrast, SBIs were found to dominate over regions of melting sea-ice. Regimes, where the cloud top penetrated the inversion base were more frequently observed than cloud capped by inversion regimes. Inversions tended to be deeper, stronger, and with a lower base during cloud top penetrating inversion base regimes. At the synoptical scale, the intense poleward intrusions of warm air brought moist air to the top of low-level inversions, creating a robust thermal stratification between layers and promoting extensive and frequency occurrences of low cloud/fog. Moreover, the polar high contributed to establishing a multilayer inversion structure at relatively high altitudes by subsidence. These findings contribute to an improving understanding of low-level vertical temperature structures and their influence on a rapidly warming Arctic.

Climatology of low-level temperature inversions over China based on high-resolution radiosonde measurements

Low-level temperature inversions play crucial roles in inhibiting vertical exchange of energy and mass, and may lead to air pollutants accumulation. The climatological study of them provides a fundamental overview of the static stability of atmosphere and is indispensable for air pollution controls. Based on high-vertical-resolution radiosondes at 00 and 12 UTC during 2011–2018, this work comprehensively examined the spatial and temporal variability of three characteristics (occurrences, strengths, and depths) of low-level inversions in China. Results revealed that inversions are prevalent (more than 80% of the observation records) over Eastern China. The northern part of Eastern China is dominated by the thick strong surface-based inversions with median thickness and strength of 200 m and 3 K, while the southern part by thin weak elevated ones of 80 m and 0.8 K. Tibetan Plateau experiences rare inversions (less than 50% of the time) which tend to be strong thick surface-based inversions with median depth and intensity of 170 m and 4 K. Inversion depths and strengths are positively correlated. The three properties of inversions present remarkable seasonal variations. Generally, inversions are strongest, thickest, and most frequent in winter and least so in summer, with median intensity and depth ranging from 0.3 K and 80 m to 5 K and 220 m. This paper also analyzed the monthly variations of inversions of four representative stations (Harbin, Urumqi, Beijing, and Chongqing) in details. These four cities are known for frequent severe air pollution events. The quantitative investigations of inversions may play a significant role in atmospheric environmental management.

Evolution of Urban Haze in Greater Bangkok and Association with Local Meteorological and Synoptic Characteristics during Two Recent Haze Episodes.

This present work investigates several local and synoptic meteorological aspects associated with two wintertime haze episodes in Greater Bangkok using observational data, covering synoptic patterns evolution, day-to-day and diurnal variation, dynamic stability, temperature inversion, and back-trajectories. The episodes include an elevated haze event of 16 days (14–29 January 2015) for the first episode and 8 days (19–26 December 2017) for the second episode, together with some days before and after the haze event. Daily PM2.5 was found to be 50 µg m−3 or higher over most of the days during both haze events. These haze events commonly have cold surges as the background synoptic feature to initiate or trigger haze evolution. A cold surge reached the study area before the start of each haze event, causing temperature and relative humidity to drop abruptly initially but then gradually increased as the cold surge weakened or dissipated. Wind speed was relatively high when the cold surge was active. Global radiation was generally modulated by cloud cover, which turns relatively high during each haze event because cold surge induces less cloud. Daytime dynamic stability was generally unstable along the course of each haze event, except being stable at the ending of the second haze event due to a tropical depression. In each haze event, low-level temperature inversion existed, with multiple layers seen in the beginning, effectively suppressing atmospheric dilution. Large-scale subsidence inversion aloft was also persistently present. In both episodes, PM2.5 showed stronger diurnality during the time of elevated haze, as compared to the pre- and post-haze periods. During the first episode, an apparent contrast of PM2.5 diurnality was seen between the first and second parts of the haze event with relatively low afternoon PM2.5 over its first part, but relatively high afternoon PM2.5 over its second part, possibly due to the role of secondary aerosols. PM2.5/PM10 ratio was relatively lower in the first episode because of more impact of biomass burning, which was in general agreement with back-trajectories and active fire hotspots. The second haze event, with little biomass burning in the region, was likely to be caused mainly by local anthropogenic emissions. These findings suggest a need for haze-related policymaking with an integrated approach that accounts for all important emission sectors for both particulate and gaseous precursors of secondary aerosols. Given that cold surges induce an abrupt change in local meteorology, the time window to apply control measures for haze is limited, emphasizing the need for readiness in mitigation responses and early public warning.

Analysis of Low-level Temperature Inversions and Their Effects on Aerosols in the Lower Atmosphere

High-quality and continuous radiosonde, aerosol and surface meteorology datasets are used to investigate the statistical characteristics of meteorological parameters and their effects on aerosols. The data were collected at the Atmospheric Radiation Measurement Southern Great Plains climate research facility during 2000–15. The parameters and vertical distribution of temperature inversion layers were found to have strong diurnal and seasonal changes. For surface-based temperature inversion (SBI), the mean frequency and depth of temperature inversion layers were 39.4% and 198 m, respectively. The temperature difference between the top and bottom of SBI was 4.8°C, and so the temperature gradient was 2.4°C (100 m)−1. The detailed vertical distributions of temperature inversion had been determined, and only the temperature inversion layers below 1000 m showed diurnal and seasonal variations. Mean surface aerosol number concentrations increased by 43.0%, 21.9% and 49.2% when SBIs were present at 0530, 1730 and 2330 LST, respectively. The effect of SBI on surface aerosol concentration was weakest in summer (18.1%) and strongest in winter (58.4%). During elevated temperature inversion events, there was no noticeable difference in surface aerosol number concentrations. Temperature differences and temperature gradients across SBIs correlated fairly well with aerosol number concentrations, especially for temperature gradients. The vertical distribution of aerosol optical properties with and without temperature inversions was different. Surface aerosol measurements were representative of the air within (below), but not above, SBIs and EIs. These results provide a basis for developing a boundary layer aerosol accumulation model and for improving radiative transfer models in the lower atmosphere.

Investigating the impact of atmospheric stability on thunderstorm outflow winds and turbulence

Abstract. Downburst events initialized at various hours during the evening transition (ET) period are simulated to determine the effects of ambient stability on the outflow of downburst winds. The simulations are performed using a pseudo-spectral large eddy simulation model at high resolution to capture both the large-scale flow and turbulence characteristics of downburst winds. First, a simulation of the ET is performed to generate realistic initial and boundary conditions for the subsequent downburst simulations. At each hour in the ET, an ensemble of downburst simulations is initialized separately from the ET simulation in which an elevated cooling source within the model domain generates negatively buoyant air to mimic downburst formation. The simulations show that while the stability regime changes, the ensemble mean of the peak wind speed remains fairly constant (between 35 and 38 m s−1) and occurs at the lowest model level for each simulation. However, there is a slight increase in intensity and decrease in the spread of the maximum outflow winds as stability increases as well as an increase in the duration over which these strongest winds persist. This appears to be due to the enhanced maintenance of the ring vortex that results from the low-level temperature inversion, increased ambient shear, and a lack of turbulence within the stable cases. Coherent turbulent kinetic energy and wavelet spectral analysis generally show increased energy in the convective cases and that energy increases across all scales as the downburst passes.

Effect of Cloud Fraction on Arctic Low-Level Temperature Inversions in AIRS Observations Over Both Land and Ocean

The low-level temperature inversions have significant impacts on Arctic climate change feedbacks. The Atmospheric Infrared Sounder (AIRS) can extract the inversions over both land and ocean, and it is, however, sensitive to the presence of clouds. In this paper, we evaluate the effect of cloud fraction (CF) on AIRS inversions over both land and ocean. First, the AIRS inversions under clear-sky conditions are compared with the results from the microwave-based Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations in 2007–2013. Results show that despite the COSMIC and AIRS inversions appearing to be deeper and stronger in winter than in autumn, spring, and summer, the former is generally shallower and stronger than the latter in all seasons over both land and ocean. Time-series analysis of the mean monthly inversions from COSMIC and AIRS observations in 2007–2013 under both clear-sky and cloudy conditions further indicates that their differences are systematic and can be effectively mitigated after calibration under all sky conditions. Taking the calibrated COSMIC inversions as references, the AIRS inversion depths can be estimated with a root mean square (rms) of less than about 86 and 135 m, and the AIRS inversion strength can be obtained with an rms of better than about 1.7 °C and 1.3 °C under cloudy conditions over land and ocean, respectively. Moreover, while the AIRS inversion depths are insensitive to CF variations over both land and ocean, the inversion strengths are more sensitive to the CF variations over land than ocean.

Assessment of the Uncertainties in Arctic Low-Level Temperature Inversion Characteristics in Radio Occultation Observations

The variation of low-level inversion characteristics is one of the important factors for Arctic amplification. Radiosonde (RS) observations are one of the reliable tools to study Arctic inversions. However, they provide limited information on the spatial distribution of temperature inversions. The radio occultation (RO) technique can provide accurate, all-weather, high vertical resolution atmospheric parameter profiles over both land and ocean. In this paper, the RO technique is investigated to estimate the inversions, and their uncertainties are assessed via comparing with the RS inversions. Results show that the inversions (base, depth, and strength) from RS and RO observations are lower, deeper, and stronger in winter than in autumn, spring, and summer. Moreover, comparisons of spatiotemporally synchronized RO and RS inversions (i.e., Scheme I) during 2007–2013 reveal that the former are higher, deeper, and weaker than the latter. Further comparisons of RS and $5 {^{\circ }} \times 5 {^{\circ }}$ gridded RO inversions (i.e., Scheme II) show smaller overall standard deviations than Scheme I, indicating that the gridded RO observations can better describe the large-scale spatial structure of temperature inversions. Furthermore, corrections of the observed remarkable systematic differences between RO and RS inversions in both the schemes are also made. The results show that the RO inversions can be well calibrated, and that greater improvements in RO inversions calibration are achieved in Scheme II than in Scheme I. Therefore, the RO technique could be a potential tool to study the Arctic low-level temperature inversions as well as improve our understanding of Arctic climate change.

An investigation on the dynamic and scale interactive processes for estimating the predictability of cloudburst over elevated orography

The cloudburst is defined as a heavy downpour at a very high rainfall rate over small spatio-temporal scale. The Indian states of Uttarakhand (30°15′N; 79°15′E) and Himachal Pradesh (32°29′N; 75°10′E) are prone to cloudburst due to its geographical setup. The large-scale monsoon flow along with elevated orography makes cloudburst phenomena frequent a well as severe over the regions. However, cloudburst and the heavy rainfall events occasionally, become difficult to distinguish. The present study attempts to identify the processes associated with cloudburst over elevated orography and compare it with one of the most debated event of 2013 which was reported as heavy rainfall but, not a cloudburst by Indian Meteorological Department (IMD). The temporal variations of rainfall and cloud-top pressure (CTP) are considered to identify the genesis of the event. The vertical developments of the system along with large-scale circulation pattern are estimated in the present study. The result of the study reveals that the mid-tropospheric dry entrainment, low-level temperature inversion and cloud height clearly distinguish the “cloudburst” and “heavy rainfall” events and confirms that the system of 2013 was indeed a heavy rainfall event and not a cloudburst.

Climatology of low-level temperature inversions at the Prague-Libuš aerological station

Temperature inversions (TIs) have been closely studied for a variety of reasons. Here, we present an analysis of low-level TIs, based on a dataset of atmospheric soundings from the aerological station at Prague-Libus (Czech Republic). Measurements have been carried out here since 1974, at the four main synoptic hours. First, the homogeneity of both the radiosonde data and sounding-derived time series was investigated. Since the homogeneity of the derived time series was affected by changes in the observation routine, only the period of 1992–2012 was further analysed. Second, diurnal and annual regimes of surface-based (SBTIs) and elevated (ETIs) temperature inversions were described. Maximum frequency of the SBTIs occurred at 00 UTC and in September and October. During autumn, persistent SBTIs also often occurred, which could be linked to decreased cyclonicity. Third, changes in TIs were evaluated, and the strongest trends were compared with the nearby station at Kummersbruck (Germany). In all seasons except spring, nocturnal SBTIs decreased almost identically at both stations. Morning SBTIs decreased as well; however, the trend was considerably stronger at Prague; and it was also mirrored by an increase in ETIs. Since only a part of these trends could be explained by changes in the large-scale circulation, other factors (low tropospheric warming, suburbanisation) are hypothesized to have affected the trends.

Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast

Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast

Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast

Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast

Low-level temperature inversions and their effect on aerosol condensation nuclei concentrations under different large-scale synoptic circulations

Knowledge of the statistical characteristics of inversions and their effects on aerosols under different large-scale synoptic circulations is important for studying and modeling the diffusion of pollutants in the boundary layer. Based on results generated using the self-organizing map (SOM) weather classification method, this study compares the statistical characteristics of surface-based inversions (SBIs) and elevated inversions (EIs), and quantitatively evaluates the effect of SBIs on aerosol condensation nuclei (CN) concentrations and the relationship between temperature gradients and aerosols for six prevailing synoptic patterns over the the Southern Great Plains (SGP) site during 2001–10. Large-scale synoptic patterns strongly influence the statistical characteristics of inversions and the accumulation of aerosols in the low-level atmosphere. The activity, frequency, intensity, and vertical distribution of inversions are significantly different among these synoptic patterns. The vertical distribution of inversions varies diurnally and is significantly different among the different synoptic patterns. Anticyclonic patterns affect the accumulation of aerosols near the ground more strongly than cyclonic patterns. Mean aerosol CN concentrations increase during SBIs compared to no inversion cases by 16.1%, 22.6%, 24.5%, 58.7%, 29.8% and 23.7% for the six synoptic patterns. This study confirms that there is a positive correlation between temperature gradients and aerosol CN concentrations near the ground at night under similar large-scale synoptic patterns. The relationship is different for different synoptic patterns and can be described by linear functions. These findings suggest that large-scale synoptic patterns change the static stability of the atmosphere and inversions in the lower atmosphere, thereby influencing the diffusion of aerosols near the ground.

Temperature Inversion Breakup with Impacts on Air Quality in Urban Valleys Influenced by Topographic Shading

AbstractUrban valleys can experience serious air pollution problems as a combined result of their limited ventilation and the high emission of pollutants from the urban areas. Idealized simulations were analyzed to elucidate the breakup of an inversion layer in urban valleys subject to a strong low-level temperature inversion and topographic effects on surface heating such as topographic shading, as well as the associated air pollution transport mechanisms. The results indicate that the presence and evolution in time of the inversion layer and its interplay with an urban heat island within the valley strongly influence the venting of pollutants out of urban valleys. Three mechanisms of air pollution transport were identified. These are transport by upslope winds, transport by an urban heat island–induced circulation, and transport within a closed slope-flow circulation below an inversion layer.

Observations and Modeling of Atmospheric Profiles in the Arctic Seasonal Ice Zone

Abstract The authors use the Polar Weather Research and Forecasting (WRF) Model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) in the summer of 2013 over the Beaufort Sea. With the SIZRS dropsonde data, the performance of WRF simulations and two forcing datasets is evaluated: the Interim ECMWF Re-Analysis (ERA-Interim) and the Global Forecast System (GFS) analysis. General features of observed mean profiles, such as low-level temperature inversion, low-level jet (LLJ), and specific humidity inversion are reproduced by all three models. A near-surface warm bias and a low-level moist bias are found in ERA-Interim. WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing. The improvement in the mean LLJ is likely related to the lower values of the boundary layer diffusion in WRF than in ERA-Interim and GFS, which also explains the lower near-surface temperature in WRF than the forcing. The relative humidity profiles have large differences between the observations, the ERA-Interim, and the GFS. The WRF simulated relative humidity closely resembles the forcings, suggesting the need to obtain more and better-calibrated humidity data in this region. The authors find that the sea ice concentrations in the ECMWF model are sometimes significantly underestimated due to an inappropriate thresholding mechanism. This thresholding affects both ERA-Interim and the ECMWF operational model. The scale of impact of this issue on the atmospheric boundary layer in the marginal ice zone is still unknown.

Causes and consequences of mid–21st-century rapid ice loss events simulated by the Rossby centre regional atmosphere-ocean model

Recent observations and modelling studies suggest that the Arctic climate is undergoing important transition. One manifestation of this change is seen in the rapid sea-ice cover decrease as experienced in 2007 and 2012. Although most numerical climate models cannot adequately reproduce the recent changes, some models produce similar Rapid Ice Loss Events (RILEs) during the mid–21st-century. This study presents an analysis of four specific RILEs clustered around 2040 in three transient climate projections performed with the coupled Rossby Centre regional Atmosphere-Ocean model (RCAO). The analysis shows that long-term thinning causes increased vulnerability of the Arctic Ocean sea-ice cover. In the Atlantic sector, pre-conditioning (thinning of sea ice) combined with anomalous atmospheric and oceanic heat transport causes large ice loss, while in the Pacific sector of the Arctic Ocean sea-ice albedo feedback appears important, particularly along the retreating sea-ice margin. Although maximum sea-ice loss occurs in the autumn, response in surface air temperature occurs in early winter, caused by strong increase in ocean-atmosphere surface energy fluxes, mainly the turbulent fluxes. Synchronicity of the events around 2040 in the projections is caused by a strong large-scale atmospheric circulation anomaly at the Atlantic lateral boundary of the regional model. The limited impact on land is caused by vertical propagation of the surface heat anomaly rather than horizontal, caused by the absence of low-level temperature inversion over the ocean.