Improved Global Net Surface Heat Flux
Improved Global Net Surface Heat Flux
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DOI：
10.1002/2017jc013137
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发表时间：
2018-05-01
影响因子：
3.6
通讯作者：
Grodsky, Semyon A.
中科院分区：
文献类型：
--
作者：
Carton, James A.;Chepurin, Gennady A.;Grodsky, Semyon A.
即使在时间平均值上，广泛使用的大气再分析的表面热通量估计也存在 10-30 Wm(-2) 的局部差异。这里提出了一种方法来帮助识别导致这些差异的误差，并通过利用水文观测和海洋再分析产生的温度增量来减少这些误差。该方法用于改善 2007-2014 年 8 年测试期间的三个大气再分析：MERRA-2、ERA-Interim 和 JRA-55 的气候月净表面热通量。结果表明，在大部分副热带和中纬度海洋上，通过与海洋热收支的一致性来评估的时间平均误差已减少到小于 +/- 5 Wm(-2)。对于全球海洋，经过全部修正后，8年平均全球净表面热失衡已降至3.4 Wm(-2)。还提出了一种方法，通过对许多不同的大气再分析重复该过程，然后检查估计值的分布，来量化热通量估计值的不确定性。对净表面通量的重新评估表明，除其他结果外，南大洋是大气的热源。 简单语言摘要 大气与海洋之间的热交换是海洋获得或失去热量的主要方式，因此是气候变率和变化的关键指标。目前对地表热交换（也称为地表热通量）的估计主要基于气象观测和模型，并且具有不确定性。本文提出了一种方法，通过利用称为数据同化的算法中海洋观测中包含的附加信息来改进这些估计。该方法的测试表明，可以将表面热通量的不确定性降低多达五倍。意想不到的结果之一是人们认识到南大洋正在失去热量，而不是从大气中获取热量。
Surface heat flux estimates from widely used atmospheric reanalyses differ locally by 10-30 Wm(-2) even in time mean. Here a method is presented to help identify the errors causing these differences and to reduce these errors by exploiting hydrographic observations and the resulting temperature increments produced by an ocean reanalysis. The method is applied to improve the climatological monthly net surface heat fluxes from three atmospheric reanalyses: MERRA-2, ERA-Interim, and JRA-55, during an 8 year test period 2007-2014. The results show that the time mean error, as evaluated by consistency with the ocean heat budget, is reduced to less than +/- 5 Wm(-2) over much of the subtropical and midlatitude ocean. For the global ocean, after all the corrections have been made, the 8 year mean global net surface heat imbalance has been reduced to 3.4 Wm(-2). A method is also presented to quantify the uncertainty in the heat flux estimates by repeating the procedure with many different atmospheric reanalyses and then examining the resulting spread in estimates. This reevaluation of net surface flux reveals, among other results, that the Southern Ocean is a source of heat to the atmosphere.Plain Language Summary Heat exchange between the atmosphere and ocean is the primary way the ocean gains or loses heat, and thus is a key indicator of climate variability and change. Current estimates of surface heat exchange, also known as surface heat flux, are primarily based on meteorological observations and models and are uncertain. This article proposes a method to improve these estimates by exploiting additional information contained in ocean observations in an algorithm known as data assimilation. Tests of this method are shown to reduce the uncertainty of surface heat flux by up to a factor of five. Among the unexpected results is a recognition that the Southern Ocean is losing heat, rather than gaining it from the atmosphere.