Kerstin Hartung

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice : the Larcform 1 single column model intercomparison

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modelled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: Some models lack the cloudy state of the boundary layer due to the representation of mixed-phase micro-physics or to the interaction between micro-and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behaviour.

The Abisko Polar Prediction School

Polar regions are experiencing rapid climate change, faster than elsewhere on Earth with consequences for the weather and sea ice. This change is opening up new possibilities for businesses such as tourism, shipping, fisheries and oil and gas extraction, but also bringing new risks to delicate polar environments. Effective weather and climate prediction is essential to managing these risks, however our ability to forecast polar environmental conditions over periods from days to decades ahead falls far behind our abilities in the mid-latitudes. In order to meet the growing societal need for young scientists trained in this area, a Polar Prediction School for early career scientists from around the world was held in April 2016.

Resolution, physics and atmosphere–ocean interaction – How do they influence climate model representation of Euro-Atlantic atmospheric blocking?

Abstract Atmospheric blocking events are known to locally explain a large part of climate variability. However, despite their relevance, many current climate models still struggle to represent the observed blocking statistics. In this study, simulations of the global climate model EC-Earth are analysed with respect to atmospheric blocking. Seventeen simulations map the uncertainty space defined by the three-model characteristics: atmospheric resolution, physical parameterization and complexity of atmosphere–ocean interaction, namely an atmosphere coupled to an ocean model or forced by surface data. Representation of the real-world statistics is obtained from reanalyses ERA-20C, JRA-55 and ERA-Interim which agree on Northern Hemisphere blocking characteristics. Blocking events are detected on a central blocking latitude which is individually determined for each simulation. The frequency of blocking events tends to be underestimated relative to ERA-Interim over the Atlantic and western Eurasia in winter and overestimated during spring months. However, only few model setups show statistically significant differences compared to ERA-Interim which can be explained by the large inter-annual variability of blocking. Results indicate slightly larger biases relative to ERA-Interim in coupled than in atmosphere-only models but differences between the two are not statistically significant. Although some resolution dependence is present in spring, the signal is weak and only statistically significant if the physical parameterizations of the model are improved simultaneously. Winter blocking is relatively more sensitive to physical parameterizations, and this signal is robust in both atmosphere-only and coupled simulations, although stronger in the latter. Overall, the model can capture blocking frequency well despite biases in representing the mean state of geopotential height over this area. Blocking signatures of geopotential height are represented more similar to ERA-Interim and only weak sensitivities to model characteristics remain.

Larcform 1 - single column model intercomparison of Arctic air formation, link to model results in NetCDF format

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, not least because they lack or misrepresent physical processes that are specific to high latitudes. The Arctic boundary layer in winter has been observed to be in either a radiatively clear or cloudy state: The radiatively clear state is characterized by strong surface radiative cooling leading to the build-up of surface-based temperature inversions, whereas the cloudy state occurs when cloud liquid water is present in the atmospheric column, allowing little or no surface radiative cooling and leading to weaker and typically elevated temperature inversions. Many large-scale models have been shown to lack the cloudy state, and some do substantially underestimate stability in the clear state. We here present results from the first Lagrangian ARCtic air FORMation experiment (Larcform 1), a GASS (Global atmospheric system studies) single-column model intercomparison which reproduces these biases of large-scale models in an idealised setup.