Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 431496
Title Unraveling the Role of Turbulent Mixing, Surface Coupling and Radiation in a Polar Stable Boundary Layer
Author(s) Sterk, H.A.M.; Steeneveld, G.J.; Holtslag, A.A.M.
Source In: 20th Symposium on Boundary Layers and Turbulence/18th Conference on Air-Sea Interaction, American Meteorological Society (9-13 July 2012, Boston, MA). - Boston : American Meteorological Society - p. 3B.3 - 3B.3.
Event Boston : American Meteorological Society 20th Symposium on Boundary Layers and Turbulence/18th Conference on Air-Sea Interaction, Boston, 2012-07-09/2012-07-13
Department(s) Meteorology and Air Quality
Publication type Contribution in proceedings
Publication year 2012
Abstract Observations indicate that the Arctic regions are very sensitive to climate change and warm more rapidly than the global average in the last few decades, a feature known as ‘Arctic Amplification'. Global climate models reproduce a similar signal for the Arctic warming, though their magnitude varies substantially both in temporal and spatial patterns. Especially in wintertime, large biases are found, indicating the need for a better understanding of the stable boundary layer (SBL) coupled to the surface. The uncertainty may partly be caused by differences in model formulations for the most relevant snow/ice physics, atmospheric mixing and radiation used in the various models. This multiplicity of processes forces us to investigate which process has the relatively largest impact in determining the model behavior. This study focusses on the role of turbulent mixing, surface coupling and radiation in a polar boundary layer. The goal is to gain insight in the relative role of these small scale processes and how these processes can compensate each other. As such, we extend the GABLS1 model intercomparison for turbulent mixing (Cuxart et al., 2006) with the other relevant physical processes in the SBL over ice. We use the Single Column Model (SCM) version of the Weather Research and Forecasting (WRF) mesoscale meteorological model and run different combinations of boundary-layer and radiation schemes (using one state of the art surface scheme). As such, an intercomparison of schemes within a single model is obtained. We confirm a wide variety in the state of the atmosphere and the surface variables for the selected parameterization schemes. Subsequently, a sensitivity analysis for one particular combination of parameterization schemes is performed for the governing processes of turbulent mixing, surface coupling and radiation. Using a novel analysis method based on time-integrated SBL development, the variation between the sensitivity runs indicates the relative orientation of model sensitivities to variations in governing processes. Furthermore, this sensitivity can explain the variety of model results obtained in the intercomparison of different parameterization schemes. We apply the same method for several geostrophic wind speeds to represent a large range of synoptic conditions. Our preliminary results indicate a shift in process significance for different wind regimes. For low wind regimes, the model sensitivity is larger for coupling and radiation, while for high wind speeds, not surprisingly, the largest sensitivity is found for the turbulent mixing process. Additionally, for typical wind speeds we find that for the 2m temperature and net radiation budget, the orientations of the turbulent mixing and surface coupling overlap. This implies that compensating errors in the boundary-layer scheme and land-surface model can remain hidden and this may explain the relatively slow progress in model development.
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