Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project has been established in 2016. It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, ship-borne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data

Erratum to Regional hydrological cycle changes in response to an ambitious mitigation scenario

International audienceUnfortunately, in the aforementioned contribution, Fig. 5 (Monthly multi-model (mean and range) precipitation change (mm/day) for 2080–2099 minus 1980–1999 averaged over the 26 regions, E1 (black) and A1B (grey) scenarios) contains an error. For two of the contributing models (ECHAM5-C and INGVCE) the evapotranspiration data had the wrong sign, leading to an opposing annual cycle in these models compared to the other models. The corrected Fig. 5 is presented here. It can be seen that the annual cycles of the climate change signals in evapotranspiration in the two scenarios agree much better between the different models than previously estimated. The general picture clearly underscores the findings from the preceding Figs. 3 and 4 that the climate change signals are much reduced under the E1 scenario compared to the A1B scenario. This is true for the ensemble properties (means, percentiles, ..

Perception of emotion in psychiatric disorders: On the possible role of task, dynamics, and multimodality

Experimental evidence suggests an impairment in emotion perception in numerous psychiatric disorders. The results to date are primarily based on research using static displays of emotional facial expressions. However, our natural environment is dynamic and multimodal, comprising input from various communication channels such as facial expressions, emotional prosody, and emotional semantics, to name but a few. Thus, one critical open question is whether alterations in emotion perception in psychiatric populations are confirmed when testing patients in dynamic and multimodal naturalistic settings. Furthermore, the impact task demands may exert on results also needs to be reconsidered. Focusing on schizophrenia and depression, we review evidence on how emotions are perceived from faces and voices in these disorders and examine how experimental task demands, stimulus dynamics, and modality may affect study results