Surface heat budget over the Weddell Sea: Buoy results and model comparisons

Abstract

[1] The surface heat budget over the Weddell Sea ice cover in 1996 was studied on the basis of data from Argos buoys equipped with meteorological sensors. In addition, a thermodynamic sea ice model, satellite-based data on the sea ice concentration, sonar results on ice thickness distribution, and output from large-scale meteorological models were all utilized. Applying the buoy data, the sensible heat flux over sea ice was calculated by Monin-Obukhov theory using the gradient method, and the latent heat flux was obtained by the bulk method. A second estimate for the surface fluxes was obtained from the thermodynamic sea ice model, which was forced by the buoy observations. The results showed a reasonable agreement. The dominating component in the heat budget over ice was the net longwave radiation, which had a mean annual cooling effect of À28 W m À2 . This was balanced by the net shortwave radiation (annual mean 13 W m À2 ), the sensible (13 W m À2 ) and latent (À3 W m À2 ) heat fluxes, and the conductive heat flux through the ice (5 W m À2 ). The regional surface fluxes over the fractured ice cover were estimated using the buoy data and Special Sensor Microwave Imager (SSMI)-derived ice concentrations. In winter the regional surface sensible heat flux was sensitive to the ice concentration and thickness distribution. The estimate for the area-averaged formation rate of new ice in leads in winter varies from 0.05 to 0.21 m per month depending on the SSMI processing algorithm applied. Countergradient fluxes occurred 8 -10% of the time. The buoy observations were compared with the operational analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the reanalyses of the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR). The 2 m air temperature and surface temperature were 3.5°and 4.4°C too high, respectively, in the ECMWF and 3.2°and 3.0°C too low in the NCEP/NCAR fields, but the models reproduced the synoptic-scale temperature variations well. The errors seem to be related to the cloud cover and the surface boundary conditions. Neither of the models recognizes leads in the ice pack, and the ice and snow thicknesses are often far from reality. The distribution of the cloud cover in the both models differed a lot from observations.

Spatial and temporal variability in summer snow pack in Dronning Maud Land, Antarctica

“…First, we compared the ECMWF-based snow fall against the observed accumulation climatology in the Dronning Maud Land as presented in Rotschky et al (2007). (Vihma et al, 2002;Tastula and Vihma, 2011), the results were very encouraging.…”

Bohai Sea Ice Parameter Estimation Based on Thermodynamic Ice Model and Earth Observation Data

“…Since its early applications for the Baltic Sea and Antarctic [69][70][71][72], the model has been further developed to investigate snow and ice thermodynamics in the Arctic Ocean [73] and lakes [74,75]. The snow and ice temperature regimes are solved by the partial-differential heat conduction equations applied for snow and ice layers, respectively.…”

Improving the WRF model's (version 3.6.1) simulation over sea ice surface through coupling with a complex thermodynamic sea ice model (HIGHTSI)

“…HIGHTSI was initially designed for seasonal ice simulation (Launiainen and Cheng, 1998;Vihma et al, 2002;Cheng et al, 2006), and it is also capable of being applied over perennial sea ice (Cheng et al, 2008b). Previous evaluations have shown that HIGHTSI can simulate the seasonal evolution of Arctic sea ice temperature and thickness well (Cheng et al, 2008b(Cheng et al, , 2013.…”