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Abstract The age of seawater refers to the amount of time that has elapsed since that water encountered the surface. This age measures the ventilation rate of the ocean, and the spatial distribution of age can be influenced by multiple processes, such as overturning circulation, ocean mixing, and air–sea exchange. In this work, we aim to gain new quantitative insights about how the ocean’s age tracer distribution reflects the strength of the meridional overturning circulation and diapycnal diffusivity. We propose an integral constraint that relates the age tracer flow across an isopycnal surface to the geometry of the surface. With the integral constraint, a relationship between the globally averaged effective diapycnal diffusivity and the meridional overturning strength at an arbitrary density level can be inferred from the age tracer concentration near that level. The theory is tested in a set of idealized single-basin simulations. A key insight from this study is that the age difference between regions of upwelling and downwelling, rather than any single absolute age value, is the best indicator of overturning strength. The framework has also been adapted to estimate the strength of abyssal overturning circulation in the modern North Pacific, and we demonstrate that the age field provides an estimate of the circulation strength consistent with previous studies. This framework could potentially constrain ocean circulation and mixing rates from age-like realistic tracers (e.g., radiocarbon) in both past and present climates. Significance StatementThe age of seawater—the local mean time since local water from different pathways was last at the surface—is a valuable indicator of ocean circulation and the transport time scale of heat and carbon. We introduce a novel constraint that relates total age flow across a density surface to its geometry, which provides new insights into constraining ocean circulation and mixing rates from age-like realistic tracers (e.g., radiocarbon). 

Abstract The nonnormality of temperature probability distributions and the physics that drive it are important due to their relationships to the frequency of extreme warm and cold events. Here we use a conditional mean framework to explore how horizontal temperature advection and other physical processes work together to control the shape of daily temperature distributions during 1979–2019 in the ERA5 dataset for both JJA and DJF. We demonstrate that the temperature distribution in the middle and high latitudes can largely be linearly explained by the conditional mean horizontal temperature advection with the simple treatment of other processes as a Newtonian relaxation with a spatially variant relaxation time scale and equilibrium temperature. We analyze the role of different transient and stationary components of the horizontal temperature advection in affecting the shape of temperature distributions. The anomalous advection of the stationary temperature gradient has a dominant effect in influencing temperature variance, while both that term and the covariance between anomalous wind and anomalous temperature have significant effects on temperature skewness. While this simple method works well over most of the ocean, the advection–temperature relationship is more complicated over land. We classify land regions with different advection–temperature relationships under our framework, and find that for both seasons the aforementioned linear relationship can explain ∼30% of land area, and can explain either the lower or the upper half of temperature distributions in an additional ∼30% of land area. Identifying the regions where temperature advection explains shapes of temperature distributions well will help us gain more confidence in understanding the future change of temperature distributions and extreme events.