利用M IT gcm模式和最优插值法搭建的同化平台对热带太平洋赤道附近的海表温度SST数据进行了数值同化处理。结果表明,同化处理有效兼顾了模式模拟值和观测值,纠正了模式模拟值出现的误差,数值同化结果更接近于观测值。该同化平台能够更...利用M IT gcm模式和最优插值法搭建的同化平台对热带太平洋赤道附近的海表温度SST数据进行了数值同化处理。结果表明,同化处理有效兼顾了模式模拟值和观测值,纠正了模式模拟值出现的误差,数值同化结果更接近于观测值。该同化平台能够更好地反映出SST的分布特征,该同化方法可以有效地对海表数据进行数值预报。展开更多
The application of ensemble optimal interpolation in wave data assimilation in the South China Sea is presented. A sampling strategy for a stationary ensemble is first discussed. The stationary ensemble is constructed...The application of ensemble optimal interpolation in wave data assimilation in the South China Sea is presented. A sampling strategy for a stationary ensemble is first discussed. The stationary ensemble is constructed by sampling from 24-h-interval significant wave height differences of model outputs over a long period,and is validated with altimeter significant wave height data,indicating that the ensemble errors have nearly the same probability distribution function. The background error covariance fields expressed by the ensemble sampled are anisotropic. Updating the static samples by season,the seasonal characteristics of the correlation coefficient distribution are reflected. Hindcast experiments including assimilation and control runs are conducted for the summer of 2010 in the South China Sea. The effect of ensemble optimal interpolation assimilation on wave hindcasts is validated using different satellite altimeter data(Jason-1 and 2 and ENVISAT) and buoy observations. It is found that the ensemble-optimal-interpolation-based wave assimilation scheme for the South China Sea achieves improvements similar to those of the previous optimal-interpolation-based scheme,indicating that the practical application of this computationally cheap ensemble method is feasible.展开更多
文摘利用M IT gcm模式和最优插值法搭建的同化平台对热带太平洋赤道附近的海表温度SST数据进行了数值同化处理。结果表明,同化处理有效兼顾了模式模拟值和观测值,纠正了模式模拟值出现的误差,数值同化结果更接近于观测值。该同化平台能够更好地反映出SST的分布特征,该同化方法可以有效地对海表数据进行数值预报。
基金Supported by the National Special Research Fund for Non-Profit Marine Sector(Nos.201005033,201105002)the National Natural Science Foundation of China(No.U1133001)+1 种基金the National High Technology Research and Development Program of China(863 Program)(No.2012AA091801)the NSFC-Shandong Joint Fund for Marine Science Research Centers(No.U1406401)
文摘The application of ensemble optimal interpolation in wave data assimilation in the South China Sea is presented. A sampling strategy for a stationary ensemble is first discussed. The stationary ensemble is constructed by sampling from 24-h-interval significant wave height differences of model outputs over a long period,and is validated with altimeter significant wave height data,indicating that the ensemble errors have nearly the same probability distribution function. The background error covariance fields expressed by the ensemble sampled are anisotropic. Updating the static samples by season,the seasonal characteristics of the correlation coefficient distribution are reflected. Hindcast experiments including assimilation and control runs are conducted for the summer of 2010 in the South China Sea. The effect of ensemble optimal interpolation assimilation on wave hindcasts is validated using different satellite altimeter data(Jason-1 and 2 and ENVISAT) and buoy observations. It is found that the ensemble-optimal-interpolation-based wave assimilation scheme for the South China Sea achieves improvements similar to those of the previous optimal-interpolation-based scheme,indicating that the practical application of this computationally cheap ensemble method is feasible.
