Satellite remote sensing of regional and seasonal Arctic cooling showing a multi-decadal trend towards brighter and more liquid clouds

Lelli, Luca; Vountas, Marco; Khosravi, Narges; Burrows, John P.

doi:10.5194/acp-23-2579-2023

Cited by 9 publications

(6 citation statements)

References 125 publications

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“…Similarly to the ice water path, also the zonally averaged liquid water path increases with temperature in all three groups in the polar regions (Figure 9c). This is consistent with the findings of Lelli et al (2023) who report an observed trend to brighter and more liquid clouds in satellite measurements over the Arctic. In contrast to the ice water path, the lowest ECS group shows the highest sensitivity in the Arctic latitude belt.…”

Section: Cloud Liquid and Ice Water Path 265supporting

confidence: 93%

Cloud properties and their projected changes in CMIP models with low/medium/high climate sensitivity

Lauer

2023

Preprint

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Abstract. Since the release of the first CMIP6 simulations one of the most discussed topics is the higher effective climate sensitivity (ECS) of some of the models resulting in an increased range of ECS values in CMIP6 compared to previous CMIP phases. An important contribution to ECS is the cloud climate feedback. Although climate models have continuously been developed and improved over the last decades, a realistic representation of clouds remains challenging. Clouds contribute to the large uncertainties in modeled ECS, as projected changes in cloud properties and cloud feedbacks also depend on the simulated present-day fields. In this study we investigate the representation of both, cloud physical and radiative properties from a total of 51 CMIP5 and CMIP6 models grouped by ECS. Model results from historical simulations are compared to observations and projected changes of cloud properties in future scenario simulations are analyzed by ECS group. In general, models in the high ECS group are typically in better agreement with satellite observations than the low and medium ECS groups. This is in particular the case for total cloud cover and ice water path in midlatitudes, especially over the Southern Ocean. Notoriously difficult tasks, however, such as simulating clouds in the Tropics or the correct representation of stratocumulus clouds remain similarly challenging for all three ECS groups. Differences in the net cloud feedback as a reaction to warming and thus differences in effective climate sensitivity among the three ECS groups are found to be driven by changes in a range of cloud regimes rather than individual regions. In polar regions, high ECS models show a weaker increase in the net cooling effect of clouds due to warming than the low ECS models. At the same time, high ECS models show a decrease in the net cooling effect of clouds over the tropical ocean and the subtropical stratocumulus regions whereas low ECS models show either little change or even an increase in the cooling effect. In the Southern Ocean, the low ECS models show a higher sensitivity of the net cloud radiative effect to warming than the high ECS models.

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Section: Cloud Liquid and Ice Water Path 265supporting

confidence: 93%

Cloud properties and their projected changes in CMIP models with low/medium/high climate sensitivity

Lauer

2023

Preprint

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“…Changes in cloud cover, especially low-level liquid containing clouds, would affect the amount of solar radiation reaching the surface. Previous studies have presented evidence for positive and negative trends in low cloud cover for the Arctic region (Boccolari and Parmiggiani, 2018;Jenkins and Dai, 2022;Lelli et al, 2023;Sviashchennikov and Drugorub, 2022;Wang et al, 2021). Increases in cloud cover would affect the amount of radiation received at the surface, which would affect ODEs mainly in March when radiation is lower compared to the later spring months.…”

Section: Discussionmentioning

confidence: 95%

On the dynamics of ozone depletion events at Villum Research Station in the High Arctic

Pernov,

Hjorth,

Sørensen

et al. 2024

Preprint

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Abstract. Ozone depletion events (ODEs) occur every spring in the Arctic and have implications for the atmospheric oxidizing capacity, radiative balance, and mercury oxidation. Here we comprehensively analyze ozone, ODEs, and their connection to meteorological and air mass history variables through statistical analyses, back-trajectories, and machine learning (ML) from observations at Villum Research Station, Station Nord, Greenland. We show that the ODE frequency and duration peak in May followed by April and March, which is likely related to air masses spending more time over sea ice and increases in radiation from March to May. Back-trajectories indicate that, as spring progresses, ODE air masses spend more time within the mixed layer and the geographic origins move closer to Villum. ODE frequency and duration are increasing during May (low confidence) and April (high confidence), respectively. Our analysis revealed that ODEs are favorable under sunny, calm conditions with air masses arriving from northerly wind directions with sea ice contact. The ML model was able to reproduce the ODE occurrence and illuminated that radiation, time over sea ice, and temperature were the most important variables for modeling ODEs during March, April, and May, respectively. Several variables displayed threshold ranges for contributing to the positive prediction of ODEs vs Non-ODEs, notably temperature, radiation, wind direction, time spent over sea ice, and snow. Our ML methodology provides a framework for investigating and comparing the environmental drivers of ODEs between different Arctic sites and can be applied to other atmospheric phenomena (e.g., atmospheric mercury depletion events).

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“…The data record covers the period 1982-2016 and was funded by the European Space Agency (ESA) as part of the ESA Climate Change Ini-tiative (CCI) programme. Although the morning (AM) sensor series was available, it was found that only the afternoon (PM) series has the radiometric stability needed for trend studies (Lelli et al, 2023). The second satellite record is produced by the National Oceanic and Atmospheric Administration (NOAA) and the National Centers for Environmental Information (NCEI) from the High Resolution Infrared Radiation Sounder (HIRS) instruments on board the NOAA and MetOp (Meteorological Operational) satellites (Zhang et al, 2021).…”

Section: 7mentioning

confidence: 99%

“…The trends are 0.138 ± 0.017, 0.037 ± 0.010, and 0.106 ± 0.009 W m −2 yr −1 for BEST COMB, CMIP6/w, and CMIP6/s, respectively. The uncertainty ranges account for the standard deviation of the trends, using the bootstrap method of Lelli et al (2023). The fluxes are averaged over the Arctic area north of 66 • N and account for the extended winter period DJFM.…”

Section: Pan-arctic Atmospheric Energy Transport Convergencementioning

confidence: 99%

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

Linke,

Quaas,

Baumer

et al. 2023

Atmos. Chem. Phys.

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Abstract. The Arctic has warmed more rapidly than the global mean during the past few decades. The lapse rate feedback (LRF) has been identified as being a large contributor to the Arctic amplification (AA) of climate change. This particular feedback arises from the vertically non-uniform warming of the troposphere, which in the Arctic emerges as strong near-surface and muted free-tropospheric warming. Stable stratification and meridional energy transport are two characteristic processes that are evoked as causes for this vertical warming structure. Our aim is to constrain these governing processes by making use of detailed observations in combination with the large climate model ensemble of the sixth Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large spread in AA and Arctic LRF, which are positively correlated for the historical period of 1951–2014. Thus, we present process-oriented constraints by linking characteristics of the current climate to historical climate simulations. In particular, we compare a large consortium of present-day observations to co-located model data from subsets that show a weak and strong simulated AA and Arctic LRF in the past. Our analyses suggest that the vertical temperature structure of the Arctic boundary layer is more realistically depicted in climate models with weak (w) AA and Arctic LRF (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions in the present climate for boreal autumn and winter and over sea ice, which is more consistent with the observations. These results are based on observations from the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic, long-term measurements at the Utqiaġvik site in Alaska, USA, and dropsonde temperature profiling from aircraft campaigns in the Fram Strait. In addition, the atmospheric energy transport from lower latitudes that can further mediate the warming structure in the free troposphere is more realistically represented by CMIP6/w models. In particular, CMIP6/w models systemically simulate a weaker Arctic atmospheric energy transport convergence in the present climate for boreal autumn and winter, which is more consistent with fifth generation reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5). We further show a positive relationship between the magnitude of the present-day transport convergence and the strength of past AA. With respect to the Arctic LRF, we find links between the changes in transport pathways that drive vertical warming structures and local differences in the LRF. This highlights the mediating influence of advection on the Arctic LRF and motivates deeper studies to explicitly link spatial patterns of Arctic feedbacks to changes in the large-scale circulation.

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Satellite remote sensing of regional and seasonal Arctic cooling showing a multi-decadal trend towards brighter and more liquid clouds

Cited by 9 publications

References 125 publications

Cloud properties and their projected changes in CMIP models with low/medium/high climate sensitivity

Cloud properties and their projected changes in CMIP models with low/medium/high climate sensitivity

On the dynamics of ozone depletion events at Villum Research Station in the High Arctic

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

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