CL4.8

The impact of various mechanisms that link Arctic and midlatitude processes occurring in conditions of amplified Arctic warming is still under debate. Observational and model studies lead to divergent conclusions. This has spurred a number of research activities aiming to apply innovative approaches to improve process understanding. Therefore, to identify robust relationships in the complex Arctic-midlatitude linkages, we apply a novel method that goes beyond simple correlation analysis, known as Causal Networks or Causal Discovery. This allows us to analyze, characterize, and quantify key processes that contribute to the linkage between the Arctic and midlatitudes on a monthly timescale. In particular, we focus on the causal connections among key actors, such as Arctic near-surface temperature and sea ice, near-surface pressure over central Asia, vertical wave propagation, and its further link to the stratospheric polar vortex. Additionally, we analyze the contribution of remote large-scale processes, such as El Niño–Southern Oscillation, Quasi Biennial Oscillation, and North Atlantic Oscillation. In this study, we summarize the comparisons between historical Coupled Model Intercomparison Project Phase 6 (CMIP6) model runs and observational data. On the one hand, our analysis shows that the majority of historical CMIP6 models agree with observations on the significant causal connection between near-surface air temperature and sea ice extent in the Arctic region. These model results also capture the tropospheric-stratospheric coupling and downward impact from the stratosphere to the troposphere shown by observations. On the other hand, we also focus on discrepancies between model simulations and observations and provide possible explanations of investigated differences. These outcomes provide the basis to investigate changes in the links between Arctic and midlatitudes for simulations with various forcings and future scenarios.

How to cite: Galytska, E., Weigel, K., Runge, J., Handorf, D., Jaiser, R., Köhler, R., and Eyring, V.: Causal evaluation of Arctic-midlatitude processes in CMIP6 model simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-870, https://doi.org/10.5194/egusphere-egu22-870, 2022.

The hydrological cycle in the Arctic is intensifying due to climate change, which could modify the climate locally, but also worldwide. For example poleward moisture transport (PMT) is projected to increase in a future climate as well as its interannual variability, mainly in summer. While the first can be attributed to increased atmospheric moisture content, the cause of the latter is still uncertain. We used the global climate model EC-Earth to examine to what extent PMT variability can be linked to atmospheric rivers (ARs) in present and future climates (2C and 3C warmer than the pre-industrial climate). It is found that most PMT variability is driven by Arctic ARs, especially over the Atlantic Ocean and to a lesser extent over the Bering Strait. In years with high PMT, a relatively large share is transported by ARs, up to 50% in the present-day climate. Moreover, our findings suggest that interannual AR-related PMT variability is more sensitive to variations in AR-intensity compared to AR-frequency in the present as well as in warmer climates. This implies that increasing interannual PMT variability is dominantly driven by the increase in PMT per AR rather than the increase in AR-occurrence. Finally, our results point at a strong contribution of ARs to interannual variability of Arctic precipitation and temperature patterns.

How to cite: Bintanja, R., Sonnemans, J., van der Wiel, K., Kolbe, M., Whan, K., and Benedict, I.: Future changes in poleward moisture transport variability associated with atmospheric rivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5436, https://doi.org/10.5194/egusphere-egu22-5436, 2022.

The Arctic sea ice cover and thickness have significantly declined since the 1970s, while exhibiting large interannual variability. Snow cover on sea ice, acting as an insulating barrier, was shown to be instrumental in driving the variability and trends in sea-ice thickness. Yet, the Arctic snow depth remains scarcely measured and overlooked in climate models, which translates to “very limited predictive skill” according to the IPCC (Special Report on the Ocean and Cryosphere in a Changing Climate). Moreover, sea-ice thickness initialization has been shown to be an important element for skilful sea-ice forecasts, and it appears plausible that the same holds for the snow layer on top.

Here, we investigate the role of atmospheric circulation anomalies in shaping the Arctic snow-cover and sea-ice thickness anomalies. In this preparatory work, spectral nudging of the large-scale atmospheric circulation towards ERA5 reanalysis data is applied to the fully coupled AWI Climate Model (AWI-CM-3). We examine the variability and trends of Arctic snowfall, snow depth, sea ice cover and thickness over a 42-year period (1979-2021), and in particular the reproduction of observed anomalies. Two nudging configurations are used, differing in strength by their relaxation timescale τ and spectral truncation wavenumber T (namely τ=24 h, T20 and τ=1 h, T159). We demonstrate the importance of atmospheric circulation anomalies in shaping variations of snow and ice thickness at sub-seasonal to interannual scales, and discuss the potential of spectral nudging as a tool to improve the initialization of sea ice forecasts.

How to cite: Athanase, M., Schwager, M., Streffing, J., Andrés-Martínez, M., Loza, S., and Goessling, H.: Impact of the atmospheric circulation on the Arctic snow cover and ice thickness variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5836, https://doi.org/10.5194/egusphere-egu22-5836, 2022.

The representation of the terrestrial thermal and hydrological states in current-generation climate models is crucial to have a realistic simulation of the subsurface physical processes and land-atmosphere coupling. This is particularly important for high-latitude permafrost regions since these areas are prone to the release of substantial amounts of carbon from degrading permafrost under climate-change conditions. Many current-generation climate models still have deficiencies in the representation of terrestrial structure and physical mechanisms, such as too shallow land depth or insufficient hydro-thermodynamic coupling. We therefore introduce a deeper bottom boundary into the JSBACH land surface model. The associated changes in the simulated terrestrial thermal state influence the near-surface hydroclimate when sufficient coupling between the thermodynamic and hydrological regimes is present. Hence, we also assess the influence of introducing various physical modifications for the representation of soil hydro-thermodynamic processes in climate projections of the 21st century. The results show significant impacts on terrestrial energy uptake, as well as changes in global near-surface ground temperatures when introducing the physical modifications. The resulting simulation of high-latitude permafrost extent is subject to large variations depending on the model configuration, reflecting the uncertainty of carbon release from permafrost degradation. We further use the modified model to assess the sensitivity of simulated high-latitude climate dynamics to different hydrological configurations in the coupled MPI-ESM. The differences in soil hydrological representation in permafrost regions could explain a large part of CMIP6 inter-model spread in simulated Arctic climate, with remote effects on subarctic dynamical systems.

How to cite: Steinert, N. J., González-Rouco, J. F., de Vrese, P., García-Bustamante, E., Hagemann, S., Jungclaus, J., Lorenz, S., Brovkin, V., Melo-Aguilar, C. A., García-Pereira, F., and Navarro, J.: Modified soil hydro-thermodynamics cause large spread in projections of Arctic and subarctic climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6020, https://doi.org/10.5194/egusphere-egu22-6020, 2022.

The SIPN South project is an international, coordinated initiative endorsed by the Year Of Polar Prediction (YOPP), that aims at identifying the skill of current seasonal predictions of sea ice around Antarctica. Here, we review and analyze the results of five years of predictions of summer sea ice conducted by 20 groups since 2017, having contributed together more than 1000 forecasts. A wide range of approaches is considered, ranging from statistical data-driven to dynamical process-based models. We evaluate the ability of the forecasts to reproduce observed sea ice area at the circumpolar and regional levels and their skill relative to trivial forecasts (climatology, persistence). We find that a substantial spread exists already at day one in the dynamical forecasts, pointing at problems with the initialization. We also find that the forecasts based on statistical modeling perform generally better than forecasts based on dynamical modeling.

How to cite: Massonnet, F., Reid, P., Lieser, J., Bitz, C., Fyfe, J., and Hobbs, W.: Evaluating the skill of seasonal forecasts of sea ice in the Southern Ocean: insights from the SIPN South project 2017-2022, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7219, https://doi.org/10.5194/egusphere-egu22-7219, 2022.

Low-level easterly winds encircle Antarctica, helping drive coastal currents which modify transport of circumpolar deep water to ice shelves as well as the formation and distribution of sea ice. Semi-permanent katabatic winds interact with a highly variable maritime component associated with synoptic forcing, both of which are influenced by the steep orography of the Antarctic margins. In this research, representation of the terrestrial and maritime components of the easterlies in three state-of-the-art reanalyses (ERA5, MERRA2 and JRA55) is evaluated. Variability on daily timescales is analysed using self-organising maps which objectively cluster coastal flow regimes into states with different synoptic and mesoscale influences. Correlation coefficients with station and sonde observations are highest in ERA5 overall but stronger terrestrial winds in MERRA2 and JRA55 reduce biases relative to ERA5 for many states. ERA5 is the least prone to overestimating low wind speeds. Performance is reduced for all reanalyses during states dominated by terrestrial katabatics and at stations near sloping terrain. Wind speeds are consistently underestimated when cyclone activity near the steep coastal orography drives a super-geostrophic low-level jet. These results demonstrate how a characterisation of coastal wind variability on short timescales could help diagnose errors in coarser models used for future projections.

How to cite: Caton Harrison, T., Bracegirdle, T., King, J., and Biri, S.: Characterising reanalysis representation of winds at the interface between Antarctica and the Southern Ocean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7468, https://doi.org/10.5194/egusphere-egu22-7468, 2022.

The terrestrial Arctic is subject to extreme climatic changes including increases in temperature and changes in precipitation patterns. At the heart of these developments lie changes in the land surface energy budget (SEB), which couples important earth system processes including the carbon and water cycles. However, despite the importance of the SEB, uncertainties in predictions of high-latitude SEBs persist, specifically for the SEB-components sensible and latent heat fluxes.

These uncertainties have in part been attributed to insufficient representation of Arctic vegetation in land surface components of Earth system models. However, to date, a quantitative understanding of the relative importance of Arctic vegetation for the SEB compared to other important SEB-drivers is missing.

Here we harmonize in situ observations from regional and global monitoring networks and provide a quantitative, circumpolar assessment of the magnitude and seasonality of observed SEB-components over treeless land >60°N in the time period 1994-2021. Using a variance partitioning analysis, we identify vegetation type as an important predictor for SEB-components during Arctic summer, in comparison with other SEB-drivers including meteorological conditions, snow cover duration, topography, and permafrost extent. Differences among vegetation types are especially high for mean summer magnitudes of sensible and latent heat fluxes, where they reach up to 8% and 9% of the potential incoming shortwave radiation, respectively. Our comparison with SEB-observations across glacier sites show that importantly, these differences among vegetation types are of similar magnitude as differences between vegetation and glacier surfaces. In our seasonality synthesis we find that net radiation (Rnet), sensible (H) and ground (G) heat fluxes have an unexpected early start of summer-regime (when daily mean values > 0 Wm^-2), preceding the end of snowmelt by 56, 33, and 39 days, respectively. An elevated variability among vegetation types in the estimated onset (and end) dates of net positive Rnet and H (and G) relative to snowmelt (and onset) date, suggests that vegetation types differentially affect the distribution, trapping and density of snow cover, with important consequences for the cumulative energy fluxes from and to the atmosphere. Finally, we find that long-term, year-round SEB data series of Arctic tundra are still very scarce, especially in the Arctic regions of Eastern Canada and Western Russia.

In conclusion, we provide quantitative evidence of the importance of vegetation types for predicting Arctic surface energy budgets at circumpolar scale. We highlight that substantial differences among vegetation types are not only found for mean magnitudes but also the seasonality of surface energy fluxes. We contend that the land surface components of Earth system models should account for Arctic vegetation types to improve climate projections in the rapidly changing terrestrial Arctic.

How to cite: Oehri, J., Schaepman-Strub, G., Kim, J.-S., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E. S., and Reji Chacko, M. and the ArcticSEB - Synthesis Team: Vegetation Type is an Important Predictor of the Arctic Terrestrial Summer Surface Energy Budget, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7636, https://doi.org/10.5194/egusphere-egu22-7636, 2022.

In recent decades the Arctic has warmed faster than the global mean, especially during winter. Wintertime Arctic warming has been attributed to various mechanisms, with recent studies highlighting the important role of enhanced downward infrared radiation associated with anomalous influx of warm, moist air from lower latitudes. Here we study wintertime surface energy budget (SEB) anomalies over Arctic sea ice on synoptic time scales, using ERA5 reanalysis data (1979-2020). With a new algorithm introduced here, we identify regions exhibiting large positive daily-mean SEB anomalies, and temporally connect them to form life-cycle events. Using Lagrangian tracers, we show that the majority of these winter events are associated with inflow from the Atlantic or Pacific Oceans, driven by the large-scale circulation. They show similar temporal evolution. The onset stage, located around the marginal ice zone, is characterized by roughly equal contributions of net longwave radiation and turbulent fluxes to the positive SEB anomaly. As the events evolve and move further into the Arctic, SEB anomalies decrease due to weakening sensible heat fluxes as the surface adapts. The magnitude of the surface temperature anomaly is determined by the downward longwave radiative flux and changes little over the life-cycle. As this study highlights the importance of turbulent fluxes in driving SEB anomalies and downward longwave radiation in determining local surface warming, both components need to be properly represented by climate models in order to properly model the Arctic climate.

How to cite: Murto, S., Caballero, R., Svensson, G., Papritz, L., Messori, G., and Wernli, H.: Extreme wintertime surface energy budget anomalies in the high Arctic, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7730, https://doi.org/10.5194/egusphere-egu22-7730, 2022.

Surface temperatures in the Arctic are increasing more than twice as fast as the global average due to Arctic amplification. This warming gives rise to new types of extreme events that can have particularly large impacts. Here, we study the interplay of mean warming and changes in internal variability to better understand and constrain the intensity and frequency of temperature extremes in the Arctic, both regionally and seasonally.
For this study, we analyze projected mean and extreme surface air temperatures in the Arctic for different levels of global warming based on output data from multiple single-model initial-condition large ensembles, with the Max Planck Institute Grand Ensemble (MPI-GE) at the core of the analysis. We use a time-slice approach to construct representative samples of the pre-industrial climate and the climate at different levels of global warming, including the Paris Agreement targets of 1.5 °C and 2 °C.
Considering pan-Arctic temperatures, we find that the mean warming is strongest in winter (~3.5 times annual mean global warming) and lowest in summer (~1.05 times annual mean global warming), which leads to a weakening of the Arctic seasonal cycle with global warming. Moreover, the change in the return levels of extreme temperatures is particularly strong for cold extremes, rendering extremely cold temperatures seldom in a warming Arctic. The level of global warming is strongly impacting the frequency of extreme events. For example, warm extremes that occur every 100 years at 1.5 °C of global warming, occur more than once in 10 years at 2 °C of global warming, and cold extremes that occur every 10 years at 1.5 °C global warming, occur only about every 200 years at 2 °C of global warming (based on MPI-GE data). The response of Arctic mean temperatures to global warming results from a local temperature response that varies substantially for different regions and types of surfaces (land, ice sheet, open ocean, sea ice). We find the most drastic warming, accompanied by a strong reduction of variability, in winter temperatures over the northern Barents Sea linked to its ‘Atlantification’. Lastly, we also note a considerable difference in the Arctic temperature response for the same level of global warming in a transient versus a quasi-equilibrium climate state.
The results of our study allow us to quantify expected changes in the Arctic temperature range with global warming and also to determine when and where, for example, climate mitigation measures are most likely to be visible.

How to cite: Gieße, C., Notz, D., and Baehr, J.: Internal variability of Arctic surface air temperatures at different levels of global warming, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8442, https://doi.org/10.5194/egusphere-egu22-8442, 2022.

The future of year-to-year variability of Arctic climate change indicators such as sea ice and precipitation is still fairly uncertain. Alongside climatic changes in means, a thorough understanding of interannual variability (IAV) is needed to accurately distinguish between signal and underlying noise, as well as to describe the likelihood of extreme events. 

In this study we quantify the IAV of Arctic surface air temperature, precipitation, evaporation, and sea ice area from 1851-2100 as a function of time in order to assess the effect of climate change on future variability. By influencing the likelihood of extreme events, changes in the magnitude of IAV can not only influence the surface mass balance of the Greenland Ice Sheet, but also affect regions in lower latitudes. Investigations of global climate model output strongly suggest that intermodel differences in CMIP6 projections of IAV are largely explained by natural variability versus model physics. Our results further highlight the need to distinguish between seasons as well as regions when investigating past, present and future states of IAV of Arctic climate. For example, increases in precipitation variability will become much more significant and intense in winter (after 2040) and most pronounced in coastal regions near the Bering Strait, the GrIS and the Norwegian Sea. Depending on the season, the retreat of sea ice can alter precipitation patterns through the process of enhanced evaporation over open ocean areas. Sea ice variability can therefore explain regional and seasonal changes of the Arctic water cycle, as it shifts from being snow- to rain-dominated.

How to cite: Kolbe, M., Bintanja, R., and van der Linden, E.: Interannual Variability of Arctic Climate: Seasonal and Regional Disparities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9717, https://doi.org/10.5194/egusphere-egu22-9717, 2022.

In the Arctic, observed decadal mean surface air temperatures (SATs) were 0.70°C–0.95°C lower around 1970 than around 1940. Many of the state-of-the-art climate model in the Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibited Arctic surface cooling trend during 1940–1970, which could be attributed to external forcings. Multimodel means of CMIP6 Detection and Attribution Model Intercomparison Project (DAMIP) historical simulations exhibited Arctic surface cooling of –0.22°C (±0.24°C) in 1970 versus 1940 and showed that anthropogenic aerosol forcing contributed to a cooling of −0.65°C (±0.37°C), which was partially offset by a warming of 0.44°C (±0.22°C) due to well-mixed greenhouse gases. In addition to the anthropogenic aerosol forcings, multidecadal internal variability with a magnitude of 0.47°C was the components primarily contributing to the observed Arctic cooling. The SAT spatial pattern of pan-Arctic multidecadal cooling due to the internal variability was identified by the composite analysis and resembles the obseved Arctic surface cooling pattern during 1940–1970.

How to cite: Aizawa, T., Oshima, N., and Yukimoto, S.: Evaluation of anthropogenic aerosol forcing and multidecadal internal variability contributing to mid-20th century Arctic cooling — CMIP6/DAMIP multimodel analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9781, https://doi.org/10.5194/egusphere-egu22-9781, 2022.

Snowmelt timing influences arctic-boreal ecosystem functioning through influences on surface hydrology and energy balance. Spring snow cover extent in the Northern Hemisphere has declined since the mid-20^th century by up to 46 % in June, including a strong decrease after the mid-1980s. Regions of arctic-boreal North America have simultaneously experienced increases in the number and size of fires. With early snowmelt timing, the likelihood of early fire ignitions also increases as fuel is exposed and organic soil can begin to dry. Early fire ignitions can potentially develop into larger fires as a prolonged fire season may extend the period of favourable weather conditions for fire spread. Despite the importance of snowmelt timing, ignition timing, and fire size for predicting future boreal fire regimes across North America, these relationships are not well understood. Here we analysed snowmelt and ignition timing across ecoregions for boreal North America from 2001 to 2019. Using newly developed satellite-based fire products, we retrieved and matched ignitions with snowmelt timing in a spatially explicit manner.

            Results indicate that snowmelt timing has occurred 0.2 ± 0.17 days year^-1 earlier in western arctic-boreal North America and 0.27 ± 0.33 days year^-1 later in eastern arctic-boreal North America between 2001 and 2019. Similarly, we found that ignitions have occurred 0.61 ± 1.12 days year^-1 earlier and 0.3 ± 0.58 days year^-1 later for the western and eastern ecoregions. In 13 out of 16 ecoregions, there was a significant positive relationship (p < 0.01) between the timing of snowmelt and ignition. This suggests that snowmelt timing helps controlling the fire season start. The mechanisms behind the spatial gradient in the snowmelt timing over the last two decades are less understood and may result from differences in larger climatic oscillations influencing the polar front jet stream and Arctic sea ice extent. Decades of colder air temperature and higher amounts of winter precipitation may explain the later snowmelt and fire season start in the eastern ecoregions. Our results show that a shift in the snowmelt timing has resulted in earlier fire season starts in western boreal North America and in later fire season starts in eastern boreal North America.

How to cite: Hessilt, T. D., Rogers, B. M., Potter, S., Scholten, R. C., and Veraverbeke, S.: Snowmelt timing influences the start of the Arctic-boreal fire season across North America, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10357, https://doi.org/10.5194/egusphere-egu22-10357, 2022.