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171.
Shabnam JafariKhasragh Jennifer V. Lukovich Xianmin Hu Paul G. Myers Kevin Sydor David G. Barber 《大气与海洋》2013,51(2):120-133
ABSTRACTSea surface temperature (SST) from four Nucleus for European Modelling of the Ocean (NEMO) model simulations is analyzed to study the bulk flux parameterization to compute SST over the Hudson Bay Complex (HBC) for the summer months (August and September) from 2002 to 2009. The NEMO simulation was forced with two atmospheric forcing sets with different resolutions: the Coordinated Ocean-ice Reference Experiment, version 2 (COREv2), as the lower resolution and the Canadian Meteorological Centre’s Global Deterministic Prediction System Reforecasts (CGRF) as the higher resolution. The CGRF forcing is also implemented in the third and fourth runs using different runoff data and different NEMO resolutions (1/12° versus 1/4°). Results show that all four modelled SSTs followed observed SST patterns, with regional differences in SST bias between simulations with different atmospheric forcing. The SST differences are small between simulations forced with the same atmospheric forcing but with different model resolution or runoff. This implies that the model resolution and runoff have a small effect on the simulated SST in the HBC. Moreover, to better capture the effect of near-surface temperature (Tair) on simulated SST, we conducted three analyses using the Haney flux linearization formula. Results from these assessments did not indicate any direct influence on the model-simulated SSTs by Tair. Looking at the heat flux as a signature for SST showed that both averaged spatial distribution and time series of net heat flux produced by the three CGRF forcing simulations were higher than the net heat flux generated by the CORE 2 simulation. This was generally true for all four components of the total heat flux (sensible, latent, shortwave, and longwave) individually as well. Total heat flux in summer is governed by the shortwave heat flux, with values up to 120?W?m?2 in August, and the longwave heat flux is the main contributor to the total heat flux differences. These heat flux differences lead to corresponding colder model SSTs for the CGRF runs and warmer SSTs for the CORE 2 simulations. 相似文献
172.
Abstract An evaluation of the Canadian Land Surface Scheme (CLASS) 3.1 snow cover simulations at four sites included in the Snow Model Intercomparison Project (SnowMIP) revealed that CLASS was able to provide realistic representations of snow cover accumulation, melt and physical properties over a range of snow cover climates. The modified snow aging parametrization in CLASS 3.1 provided improved simulations of snowpack density which resulted in a marked reduction in the root‐mean‐square (rms) error for daily snow depth, and slight improvements in snow surface temperature. CLASS 3.1 still exhibited a tendency to overestimate snow cover duration which is attributed to the way shallow snow ablation is treated. CLASS provided generally realistic simulations of daily and seasonal variation in snow albedo although cold snow albedo was underpredicted by 0.10 to 0.15 at a site with a deep (> 2 m) cold snowpack. CLASS also exhibited a tendency to overpredict late spring snow albedo which was reduced by the addition of a snow layer subroutine that kept track of snow albedo by precipitation event. CLASS had a noticeable cold bias averaging 3°–4°C at two mountain sites included in the comparison. The bias was closely linked to atmospheric stability and could exceed 10°C under conditions of strong radiative cooling and low wind speeds. The CLASS energy deficit under these conditions was determined to be ~20–40 W m?2 and was mostly accounted for by introducing a windless exchange coefficient into the calculation of sensible heat fluxes following the approach used in a number of other physical snowpack models. CLASS provided realistic simulations of daily snowmelt runoff with the exception of the Weissfluhjoch site which was characterized by a deep cold snowpack. A preliminary assessment of snow water equivalent (SWE) rms error for the 23 models participating in SnowMIP showed that CLASS was one of the better single layer snow models included in the comparison. CLASS performance was comparable to the multi‐layer CROCUS snowpack model in the evaluations carried out in this study. 相似文献