The Underwater Vision Profiler (UVP) provides abundant in situ data of the marine particle size distribution (PSD) on global scales and has been used for a diversity of applications, but the uncertainty associated with its measurements has not been quantified. Here we use a global compilation of UVP (version 5) observations of the PSD to assess the sampling uncertainty associated with the UVP’s sampling characteristics. We model UVP sampling uncertainty using Bayesian Poisson statistics and provide formulae for the uncertainty associated with a given sampling volume and observed particle count. We also model PSD observations using a power law with an exponential cutoff to better match the low concentration associated with rare large particles as seen by the UVP. We use the two shape parameters from this statistical model to describe changes in the PSD shape across latitude band, season, and depth. The UVP sampling uncertainty propagates into an uncertainty for modeled carbon flux exceeding 50%. The statistical model is used to extend the size interval used in a PSD-derived carbon flux model, revealing a high sensitivity of the PSD-derived flux model to the inclusion of small particles (80-128 microns). We close with recommendations on how to revise the carbon flux model, and we provide avenues to address additional uncertainties associated with UVP-derived carbon flux calculations.

Oxygen isotopes in marine sediments (δ 18 O) are used to reconstruct Earth’s past temperature and reveal a generally cooling climate over the Cenozoic (66Ma-present). This trend is punctuated by large multimillenial thermal extreme events, most notably the Paleocene-Eocene Thermal Maximum (56Ma). We show that the distribution of these thermal extremes is excellently captured by the generalized extreme value distribution. This then motivates its use to investigate the state-dependence of these extremes. The distribution’s shape, captured by the shape parameter ξ, changes consistently with baseline δ 18 O values, such that large thermal extremes (>3 standard deviations) are far more likely in warmer climate states. We project that anthropogenic warming has the potential to return the baseline climate state to one where large thermal extremes are substantially more likely. Short title: Thermal extreme state-dependence 66-0Ma One-Sentence Summary: Warmer baseline climate states are associated with more extreme multimillenial warming events over the past 66 million years.

Little is known about Southern Ocean under-ice phytoplankton, despite their suspected potential-ice and stratification conditions permitting-to produce blooms. We use a distributional approach to ask how Southern Ocean sea ice and under-ice phytoplankton characteristics are related, circumventing the dearth of co-located ice and phytoplankton data. We leverage all available Argo float profiles, together with freeboard (height of sea ice above sea level) and lead (ice fractures yielding open water) data from ICESat-2, to describe co-variations over time. We calculate moments of the probability distributions of maximum chlorophyll, particulate backscatter, the depths of these maxima, freeboard, and ice thickness. Argo moments correlate significantly with freeboard variance, lead fraction, and mixed layer depth, implying that sea ice dynamics drive plankton by modulating how much light they receive. We discuss ecological implications in the context of data limitations, and advocate for diagnostic models and field studies to test additional processes influencing under-ice phytoplankton.

The ocean stores the bulk of excess anthropogenic heat in the Earth system. The ocean heat uptake efficiency (OHUE) – the flux of heat into the ocean per degree of global warming – is therefore a key factor in how much warming will occur in the coming decades. In climate models, OHUE is well-characterised, tending to decrease on centennial timescales; in contrast, OHUE is not well-constrained from Earth observations. Here OHUE and its rate of change are diagnosed from global temperature and ocean heat content records. OHUE increased from $0.57\pm0.06$W/m$^2$K to $0.7\pm0.02$W/m$^2$K over the past five decades. This increase is attributed to steepening heat content gradients in the ocean, and corresponds to $\sim$4 years’ delay until temperature targets such as 1.5$^\circ$C or 2$^\circ$C are exceeded.

Very little is known about Southern Ocean under-ice phytoplankton, despite their suspected potential -- ice and stratification conditions permitting -- to produce blooms. Here we use a distributional approach to ask how sea ice and under-ice phytoplankton characteristics are related in the Southern Ocean, circumventing the dearth of co-located ice and phytoplankton data. We leverage all available phytoplankton data from Argo profiling floats, together with ice freeboard and lead data from ICESat-2, to describe co-variations over time. We calculate moments of the probability distributions of maximum chlorophyll, particulate backscatter, the depths of these maxima, ice freeboard, and ice thickness. Argo moments correlate moderately with ice variance, but not mean, perhaps implying that variable sea ice and leads provide more opportunities for light to reach phytoplankton. We discuss ecological implications of our results in the context of data limitations, and advocate for diagnostic models and field studies to test processes influencing under-ice phytoplankton.