Description: 〈jats:p〉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. 〈/jats:p〉

Description: The Working Group on Fisheries Benthic Impact and Trade-offs (WGFBIT) develops methods and performs assessments to evaluate benthic impact from fisheries at regional scale, while con- sidering fisheries and seabed impact trade-offs. In this report, new fishery benthic impact assessments (ToR A) are shown out for several sub- regions in (French Mediterranean, Celtic Seas). For other regions, updates of the whole assess- ment or specific steps only were presented. To further standardise the different components of the WGFBIT approach across all (sub-)re- gional assessments, a more detail overview of those components was compiled. These compo- nents were slightly different among those regions, related to variation in data availability, envi- ronmental characteristics and implementation possibilities among the (sub-)regions. In WGFBIT, assessments are sometimes based on trawl or grab data, which are sampling differ- ent components of the seafloor ecosystem and can have consequences on the created sensitivity layer. Therefore, there is looked in more detail how the sensitivity outcome (and layers) can dif- fer due to the use of benthic data gathered with different gears (grab/core, trawl or video). The preliminary comparability analyses are performed on different levels: (1) based on co-located sampling; (2) comparing sensitivity maps of the (sub-) area, based on different gears. There were differences observed in longevity distribution at locations sampled with different gears and dif- ferences in data and models lead also to differences in the sensitivity layers. The WGFBIT seafloor assessment framework is not the only way to assess benthic impacts from physical disturbance. A discussion session was held on how the future workflow on advice that ICES WGFBIT assessment contribute to, will be organized. Marine sediments harbour significant levels of biodiversity that play a key role in ecosystem functions and services such as biogeochemical cycling, carbon storage and the regulation of cli- mate. Through the removal of fauna, changes in physico-chemical nature and resuspension of sediment, bottom trawling may result in significant changes in the ecosystem functioning of shelf seas. An assumption of the current PD model is that high community biomass implies higher ecosystem functioning. However, total community biomass does not necessarily reflect changes in species and functional trait composition which play a key role in regulating ecosystem func- tions. ToR D is working on an improved understanding of the link between species functional effect traits and proxies and processes for specific ecosystem functions to improve our ability to predict the impact of fishing disturbance on benthic ecosystem functioning more accurately. Links between species traits and biogeochemical parameters and the impact of trawling on these links are being explored using multivariate ordination analyses using different fauna and bioge- ochemical datasets collected in the North Sea, Celtic Sea, Kattegat, Baltic Sea and the eastern Mediterranean. Changes due to trawling in the trajectories of species densities over time and the concurrent changes in the bioturbation and bioirrigation potential of communities are being modelled using a combination of data-driven mechanistic model and a biogeochemical model. We report on the different data analysis methods that ToR D members have developed over the last year.

Description: ICES

Description: Published

Description: Refereed