Impact of observation-based snow albedo parameterization on global ocean simulation results
Impact of observation-based snow albedo parameterization on global ocean simulation results
复制标题
基于观测的雪反照率参数化对全球海洋模拟结果的影响
DOI:
10.1016/j.polar.2020.100521
复制
发表时间:
2020
期刊:
影响因子:
1.8
通讯作者:
and G. Yamanaka
中科院分区:
文献类型:
--
作者:
Toyoda;T.;T. Aoki;M. Niwano;T. Tanikawa;L. S. Urakawa;H. Tsujino;H. Nakano;K. Sakamoto;N. Hirose;and G. Yamanaka
Albedo parameterization is of fundamental importance for accurate representation of high-latitude climate variability by modeling studies. Field observations show that near-infrared snow albedo decreases dramatically when surface air temperature exceeds −2 °C. This can influence reproduction of sea ice simulations taking into consideration the importance of the drastic change in albedo in early melt season for the seasonal change of sea ice extent. Therefore, we conducted global ocean data-assimilative simulation experiments using a modified snow albedo parameterization. The modified parameterization reduced the albedo directly and achieved a comparable indirect reduction via changes in the modeled snow and sea ice distributions (ice–albedo feedback). As a result, sea ice thickness was reduced by more than 0.4–1 cm over most of the central Arctic Ocean. Sea ice velocities were also reduced by enhanced ocean drag with weakened surface ocean circulation in the Beaufort Gyre. In the Southern Ocean, the modified parameterization caused snow thicknesses to be decreased by up to 2 cm in the Weddell Sea. These impacts, which were generally larger than the spread of ensemble experiment results and therefore robust, at least in our model, provide useful information for quantifying the results of albedo modification in climate modeling studies.