Model‐Derived Uncertainties in Deep Ocean Temperature Trends Between 1990 and 2010

Abstract

We construct a novel framework to investigate the uncertainties and biases associated with estimates of deep ocean temperature change from hydrographic sections and demonstrate this framework in an eddy‐permitting ocean model. Biases in estimates from observations arise due to sparse spatial coverage (few sections in a basin), low frequency of occupations (typically 5–10 years apart), mismatches between the time period of interest and span of occupations, and from seasonal biases relating to the practicalities of sampling during certain times of year. Between the years 1990 and 2010, the modeled global abyssal ocean biases are small, although regionally some biases (expressed as a heat flux into the 4,000‐ to 6,000‐m layer) can be up to 0.05 W/m2. In this model, biases in the heat flux into the deep 2,000‐ to 4,000‐m layer, due to either temporal or spatial sampling uncertainties, are typically much larger and can be over 0.1 W/m2 across an ocean. Overall, 82% of the warming trend deeper than 2,000 m is captured by hydrographic section‐style sampling in the model. At 2,000 m, only half the model global warming trend is obtained from observational‐style sampling, with large biases in the Atlantic, Southern, and Indian Oceans. Biases due to different sources of uncertainty can have opposing signs and differ in relative importance both regionally and with depth, revealing the importance of reducing temporal and spatial uncertainties in future deep ocean observing design.

Understanding of Contemporary Regional Sea‐Level Change and the Implications for the Future

“…Despite dramatic improvements in the sea‐level observing system in recent years, various areas of the ocean are still undersampled and this poses challenges to identifying the steric component of SLC. Although only ~13% of the ocean heat content resides in regions that are not well‐sampled by observations (Desbruyères et al, 2016; Durack et al, 2014), there is considerable bias (Garry et al, 2019) and uncertainty (Llovel et al, 2014) in this number and warming of such regions has been increasing with time (Gleckler et al, 2016). Moreover, there are few observations below 2,000 m depth, in particular (Purkey & Johnson, 2010), but analyses in regions such as the subtropical South Pacific that have sufficient observations have revealed a decade‐long intensification in ocean heat transport convergence responsible for heat accumulation (Volkov et al, 2017).…”

Ocean and atmosphere influence on the 2015 European heatwave

“…We use a new method to initialise our experiments, taking anomaly fields from a forced ocean-only simulation (Garry et al 2019) with the same ocean model as used in the coupled model. Thereafter, these anomalies are added to the climatological mean of the ocean in the coupled model to generate an initial state.…”

Observed Ocean Bottom Temperature Variability at Four Sites in the Northwestern Argentine Basin: Evidence of Decadal Deep/Abyssal Warming Amidst Hourly to Interannual Variability During 2009–2019

“…This study presents, for the first time, unique decade-long records of hourly temperature measurements from four sites just above the ocean bottom in the Argentine Basin at 34.5°S ( Figure 1 and Table 1), at depths ranging from 1,360 to 4,757 m. These hourly temperature records, collected as part of a long-term project to observe the western boundary current variations associated with the meridional overturning circulation in the South Atlantic (e.g., Meinen et al, 2012Meinen et al, , 2013Meinen et al, , 2017Meinen et al, , 2018, represent an ideal new data set for determining the range of time scales at which near-bottom temperature varies over a full decade-long period from 2009 through 2019. This observational data set can also be used to quantify the errors in trends (e.g., Garry et al, 2019) that one might estimate over this 10 year period based on infrequent "snapshot" observations rather than hourly data.…”