Hearing the heat Most of the excess heat that causes global warming is absorbed by the oceans. Quantifying that heat increase is challenging because it requires many different temperature measurements over both the vertical and horizontal extent of the oceans. Wu et al. report success in this effort through the use of a different method: They inferred temperature changes from sound waves generated by repeating earthquakes (see the Perspective by Wunsch). The travel time of these earthquakes from source to receiver reflects changes in the average water temperature that they encounter. This technique should substantially enhance our ability to monitor ocean warming. Science, this issue p. 1510; see also p. 1433 Global seismic ocean thermometry using noise from earthquakes provides a distinct means of measuring ocean warming. More than 90% of the energy trapped on Earth by increasingly abundant greenhouse gases is absorbed by the ocean. Monitoring the resulting ocean warming remains a challenging sampling problem. To complement existing point measurements, we introduce a method that infers basin-scale deep-ocean temperature changes from the travel times of sound waves that are generated by repeating earthquakes. A first implementation of this seismic ocean thermometry constrains temperature anomalies averaged across a 3000-kilometer-long section in the equatorial East Indian Ocean with a standard error of 0.0060 kelvin. Between 2005 and 2016, we find temperature fluctuations on time scales of 12 months, 6 months, and ~10 days, and we infer a decadal warming trend that substantially exceeds previous estimates.

中文翻译：

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地震海洋测温

听到热量 导致全球变暖的大部分多余热量被海洋吸收。量化热量增加具有挑战性，因为它需要在海洋的垂直和水平范围内进行许多不同的温度测量。吴等人。通过使用不同的方法报告了这项工作的成功：他们从重复地震产生的声波中推断出温度变化（参见 Wunsch 的观点）。这些地震从震源到接收器的传播时间反映了它们遇到的平均水温的变化。这项技术将大大增强我们监测海洋变暖的能力。科学，这个问题 p。1510; 另见第 1433 使用地震噪声的全球地震海洋测温提供了一种独特的测量海洋变暖的方法。地球上日益丰富的温室气体所捕获的能量，有 90% 以上被海洋吸收。监测由此产生的海洋变暖仍然是一个具有挑战性的采样问题。为了补充现有的点测量，我们引入了一种方法，该方法可以根据重复地震产生的声波的传播时间来推断盆地尺度的深海温度变化。这种地震海洋温度测量的第一次实施限制了赤道东印度洋 3000 公里长剖面的平均温度异常，标准误差为 0.0060 开尔文。从 2005 年到 2016 年，我们发现了 12 个月、6 个月和~10 天的时间尺度上的温度波动，我们推断出一个大大超过先前估计的十年变暖趋势。