Description: Polar regions offer the opportunity to study many processes under strongly simplified conditions ('natural laboratory'). For example, the plateau areas of the polar ice sheets represent areas with an almost ideal homogeneous surface over a scale of several 100 km, which are extraordinary suited for studies of the stable boundary layer (SBL). In coastal areas we find often a transition of the SBL to a convective boundary layer (CBL) over polynyas, which allows for near-ideal studies of internal boundary layers. The sea ice areas in polar regions are another example for natural laboratory conditions, since they represent large areas with well-defined heterogeneities of two surface types. The present review shows examples of how the polar areas can be used as a natural laboratory for field experiments in the Arctic and Antarctic with a focus on the work performed by German research groups.

Description: The simulation of extremes using climate models is still a challenging task. Currently, the model grid horizontal resolution of state-of-the art regional climate models (RCMs) is about 11–25 km, which may still be too coarse to represent local extremes realistically. In this study we use dynamically downscaled ERA-40 reanalysis data of the RCM COSMO-CLM at 18 km resolution, downscale it dynamically further to 4.5 km and finally to 1.3 km to investigate the impact of the horizontal resolution on extremes. Extremes are estimated as return levels for the 2, 5 and 10‑year return periods using ‘peaks-over-threshold’ (POT) models. Daily return levels are calculated for precipitation and maximum 2 m temperature in summer as well as precipitation and 2 m minimum temperature in winter. The results show that CCLM is able to capture the spatial and temporal structure of the observed extremes, except for summer precipitation extremes. Furthermore, the spatial variability of the return levels increases with resolution. This effect is more distinct in case of temperature extremes due to a higher correlation with the better resolved orography. This dependency increases with increasing horizontal resolution. In comparison to observations, the spatial variability of temperature extremes is better simulated at a resolution of 1.3 km, but the return levels are cold-biased in summer and warm-biased in winter. Regarding precipitation, the spatial variability improves as well, although the return levels were slightly overestimated in summer by all CCLM simulations. In summary, the results indicate that an increase of the horizontal resolution of CCLM does have a significant effect on the simulation of extremes and that impact models and assessment studies may benefit from such high-resolution model output.

Description: The presence of clouds in the Arctic regulates the surface energy budget (SEB) over the sea-ice surface and the ice-free ocean. Following several previous field campaigns, the cloud-radiation relationship, including cloud vertical structure and phase, has been elucidated; however, modeling of this relationship has matured slowly. In recognition of the recent decline in the Arctic sea-ice extent, representation of the cloud system in numerical models should consider the effects of areas covered by sea ice and ice-free areas. Using an in situ stationary meteorological observation data set obtained over the ice-free Arctic Ocean by the Japanese Research Vessel Mirai (September 2014), coordinated evaluation of six regional climate models (RCMs) with nine model runs was performed by focusing on clouds and the SEB. The most remarkable findings were as follows: (1) reduced occurrence of unstable stratification with low-level cloud water in all models in comparison to the observations, (2) significant differences in cloud water representations between single- and double-moment cloud schemes, (3) extensive differences in partitioning of hydrometeors including solid/liquid precipitation, and (4) pronounced lower-tropospheric air temperature biases. These issues are considered as the main sources of SEB uncertainty over ice-free areas of the Arctic Ocean. The results from a coupled RCM imply that the SEB is constrained by both the atmosphere and the ocean (and sea ice) with considerable feedback. Coordinated improvement of both stand-alone atmospheric and coupled RCMs would promote a more comprehensive and improved understanding of the Arctic air-ice-sea coupled system.