Abstract
Reconstructing past sea-surface temperatures (SSTs) from historical measurements containing more than 100 million ship-based observations taken by over 500,000 ships from more than 150 countries using a variety of methodologies creates a wide range of historical, scientific, and statistical challenges. The reconstruction of historical SSTs for studying climate change is particularly challenging because SST measurements are uncertain and contain systematic biases of order 0.1^\circC to 1^\circCâthese systematic biases are in the range of the historical global warming signal of approximately 1^\circC. The biases are complicated and have generally been addressed using simplified corrections. In this review, I introduce a history of SST observations, review a statistical method developed for quantifying SST biases, and illustrate scientific insights obtained from adjusted SSTs. This article also documents the scientific journey of my Ph.D. work. As a result, I report personal stories on both successes, difficulties, and setbacks along the way. The statistical method for correcting SSTs (i.e., a linear-mixed-effect intercomparison framework) depends on identifying systematic offsets between intercomparable groups of SST observations. Combining estimated offsets with physical and historical evidence has allowed for correcting discrepancies associated with SSTs, including the North Atlantic warming twice as fast as the North Pacific in the early 20th century and anomalously warm SSTs during World War II. Corrections also permit better hindcasting of Atlantic hurricanes. I conclude with some discussion on how the SST records might be further improved. Given the importance of SSTs for understanding historical changes in climate, I hope that this review can help others appreciate challenges that are present and spark some interest and ideas for further improvement.
Highlights
Sea-surface temperature (SST), typically defined at ocean depth of 20–30 cm (Kennedy et al., 2019), is a crucial quantity for studying the Earth’s climate
This review demonstrates the importance of understanding the social context and history of how data are collected and postprocessed
Such a problem is difficult because biases associated with SSTs coming from the same method can be distinct due to different instrumental designs and measurement protocols used by various subsets of ships, which will interact with the uneven sampling to create regionally varying biases
Summary
Sea-surface temperature (SST), typically defined at ocean depth of 20–30 cm (Kennedy et al., 2019), is a crucial quantity for studying the Earth’s climate. Combining different types of buoys, which sample at different depth, can result in biases due to vertical temperature gradients that often exist near the ocean surface One cause of these gradients is solar heating in low-wind conditions, which can exceed 3◦ C in some extreme cases (Kennedy et al, 2007). On account of the irreplaceable nature of these early SST measurements, adjusting biases becomes crucial for quantifying and interpreting historical climate change Such a problem, is difficult because biases associated with SSTs coming from the same method can be distinct due to different instrumental designs (e.g., different bucket materials) and measurement protocols used by various subsets of ships, which will interact with the uneven sampling to create regionally varying biases. Other postmeasurement problems may exist but have not yet been quantified systematically
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