Combining altimetric height with broadscale profile data to estimate steric height, heat storage, subsurface temperature, and sea-surface temperature variability
Combining altimetric height with broadscale profile data to estimate steric height, heat storage, subsurface temperature, and sea-surface temperature variability
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DOI：
10.1029/2002jc001755
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发表时间：
2003-09
影响因子：
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通讯作者：
J. Willis;D. Roemmich;B. Cornuelle
中科院分区：
文献类型：
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作者：
J. Willis;D. Roemmich;B. Cornuelle
[1]一种新的技术相结合的高度（AH）和海表温度（SST）与原位数据，以产生改进的估计0/800米立体高度（SH），热含量和温度变化。该技术使用对AH的线性回归来构建地下量的初始猜测。然后，将该猜测向原位数据进行校正，从而产生比单独使用任一数据集所能实现的误差小得多的估计。SST数据的纳入进一步提高了估计值，并说明了如何将该程序推广到允许纳入其他数据集。该技术在西南太平洋塔斯曼海的一个区域进行了演示。计算了9年的热储存和温度变率的时间序列，在4°纬度和经度上取平均值，时间上取1年。估计值的RMS误差约为4.6 W/m2的热存储，0.10°C的地下温度和0.11°C的表面温度，和分数误差分别为20，28和18%，相对于总方差的整体空间和时间尺度考虑。这些数字比以前对这些数量的估计有很大改进。所有的时间序列都表现出强烈的年际变化，包括1997年的厄尔尼诺事件。这些技术在全球范围内的应用，可以提供新的洞察力的大气环流和上层海洋的热量收支的变化。
[1] A new technique is demonstrated for combining altimetric height (AH) and sea-surface temperature (SST) with in situ data to produce improved estimates of 0/800 m steric height (SH), heat content, and temperature variability. The technique uses a linear regression onto AH to construct an initial guess for the subsurface quantity. This guess is then corrected toward the in situ data creating an estimate with substantially less error than could be achieved using either data set alone. Inclusion of the SST data further improves the estimates and illustrates how the procedure can be generalized to allow inclusion of additional data sets. The technique is demonstrated over a region in the southwestern Pacific enclosing the Tasman Sea. Nine-year time series of heat storage and temperature variability, averaged over 4° latitude and longitude and 1 year in time, are calculated. The estimates have RMS errors of approximately 4.6 W/m2 in heat storage, 0.10°C in subsurface temperature and 0.11°C in surface temperature, and fractional errors of 20, 28, and 18%, respectively, relative to the total variance overall spatial and temporal scales considered. These represent significant improvements over previous estimates of these quantities. All the time series show strong interannual variability including the El Nino event of 1997. Application of these techniques on a global scale could provide new insight into the variability of the general circulation and heat budget of the upper ocean.