Surface eddy mixing in the global subtropics

The salinity of the ocean is inherently linked to the global hydrological cycle by net evaporation. The surface salinity, however does not just act like a 'rain gauge', ocean dynamics are vital in shaping the sea surface salinity (SSS) distribution. Here I investigate the effect of unsteady motions on scales of several hundred km and smaller - mesoscale eddies - on the water masses in the saltiest regions of the surface oceans. These water masses are eventually subducted equatorward and contribute to the shallow overturning circulation by transporting surface signals from the subtropics to the tropics, making them important components of the variable climate system. Towed CTD measurements in March/April 2013 (a component of the NASA SPURS process study) within the North Atlantic SSS maximum (SSS-max) reveal several relatively fresh and warm anomalies, which deviate strongly from climatological conditions. These features introduce a large amount of freshwater into the subtropical region, exceeding the amount introduced by local rain events. The scales and evolution of the features strongly suggest a connection to mesoscale dynamics. This is supported by high-resolution regional model output, which produces an abundance of features that are similar in scale and structure to those observed, confirming the importance of eddy mixing for the near surface salinity budget of the North Atlantic SSS-max. Observations from the Aquarius satellite and the Argo array in the global SSS-max revealed marked differences in the mean shape and variability of the SSS-maxima. These results motivated an investigation of the role of eddy mixing in setting the regional characteristics of SSS maxima. Observed surface velocities from altimetry are used to stir salinity fields in high-resolution idealized model experiments. Using a water mass framework (salinity coordinates) temporal variability in eddy mixing can be quantified, using diagnostics for the total diffusive flux into the SSS-maxima (transformation rate; TFR) as well as the estimated cross-contour diffusivity(effective diffusivity,$K_{eff}$). Both diagnostics reveal distinct variability in the different ocean basins. In the North Atlantic, both $TFR$ and $K_{eff}$ are dominated by changes in the velocity field while the North Pacific shows high sensitivity of the temporal variability in eddy mixing with respect to the initial conditions used, which represent seasonal/interannual change of the SSS-max shape and position. This implies that temporal variability of eddy mixing and diffusivities must be taken into account when constructing salinity budgets in these regions. Furthermore, the translation of results from one SSS-max region to the other might not be possible, particularly when considering a changing climate, which might influence the mechanisms responsible for temporal variability differently. Lastly evidence is presented for large scale diffusivity variability (particularly in the Pacific), connected to large scale climate fluctuations (ENSO). The evidence presented here suggests a significant modulation of surface diffusivities by climate variability, which represents a feedback mechanism not commonly recognized nor included in modern climate simulations

Reflections on the CLIVAR Early Career Scientists Symposium 2016

We present a summary report of the CLIVAR Early Career Scientists Symposium, a three-day event associated with the CLIVAR Open Science Conference held in Qingdao, China during September 2016. The Symposium aimed to capture the ideas of early career researchers on pressing science priorities, imminent challenges, and emerging opportunities to help guide the future evolution of CLIVAR. We identified the need for improving process-based understanding and predictability of regional climate variability and change, moving toward seamless predictions, and improving and expanding global observations. We emphasize the need for increasingly open science, including universal access to data, code, and publications as well as opportunities for international cooperation and exchange. As the next generation of climate scientists, we are dedicated to overcome the challenges outlined in this summary and are looking forward to advancing CLIVAR???s mission and activities

Das invasive Zervixkarzinom: Eine longitudinale Studie zur Früherkennung 1973 - 2002

Es werden Daten von 782 Patientinnen ausgewertet, bei denen von 1973-2002 ein Zervixk-Ca diagnostiziert wurde. Es sollte ermittelt werden, ob sich im Verlauf von 30 J. das Auftreten von Zervix-Ca, die Altersstruktur, die Teilnahme an Vorsorgeuntersuchungen oder das Spektrum Befunde verändert hat. Es zeigt sich, dass trotz Anstieg der Untersuchungszahlen die Zahl der jährlich auftretenden Zervix-Ca fast konstant bleibt. Mikrokarzinome traten in etwa einem Drittel auf. Die Patientinnen wurden je nach Anamnese in 3 Gruppen eingeteilt und deren Daten verglichen. Bei 659 Frauen konnten Angaben zur Vorsorgeanamnese ermittelt werden. 65% hatten nie eine Vorsorge in Anspruch genommen, bei 11,8% lag die Vorsorgeuntersuchung mehr als 3 Jahre zurück. Diese geringe Teilnahme hat sich im Laufe der 30 Jahre nicht geändert. Um die stagnierende Inzidenz des Zervix-Ca zu senken, ist eine Erhöhung der Teilnahmeraten notwendig

Bottom water export from the western Ross Sea, 2007 through 2010

Bottom water export from the Ross Sea, February 2007 to January 2011, exhibits seasonal and interannual variability. Temperature minima coupled to salinity maxima in late austral summer, into the fall, indicate input from High-Salinity Shelf Water (HSSW). Secondary temperature minima lacking the high-salinity trait, characteristic of Low-Salinity Shelf Water (LSSW), appear in the spring. Warmer bottom water similar to modified Circumpolar Deep Water (mCDW) is observed in winter and in early summer. The LSSW and mCDW may be drawn from the Drygalski Basin, as the HSSW pool retreats poleward from the shelf break in response to increased winter polar easterlies allowing these less dense overlying waters to spill into the deep ocean within the benthic layer. Bottom salinity decreased from 2007 to 2011 by 0.007 year−1 significantly higher than regional decadal trends, which we propose is a result of HSSW retreat induced by strengthening polar easterlies

Differences Among Subtropical Surface Salinity Patterns

The subtropical ocean, exposed to evaporation excess over precipitation, is characterized by regional sea surface salinity maxima (SSS-max). Ocean circulation and mixing processes inject freshwater, establishing a quasi-steady state, though imbalances across the time spectrum result in periods of increasing and decreasing SSS-max. The integrated effect of the array of atmospheric and oceanic forces governing sea surface salinity is shaped by the specific regional ocean basin configuration as well as their coupling to the global ocean system, resulting in SSS-max patterns and locations that display marked differences between the subtropical regimes. We provide a brief description of the SSS-max characteristics of the five subtropical regimes and present aspects of their regional settings that may account for their dissimilarities

Projecting Changes in the Drivers of Compound Flooding in Europe Using CMIP6 Models

When different flooding drivers co-occur, they can cause compound floods. Despite the potential impact of compound flooding, few studies have projected how the joint probability of flooding drivers may change. Furthermore, existing projections may not be very robust, as they are based on only 5 to 6 climate model simulations. Here, we use a large ensemble of simulations from the Coupled Model Intercomparison Project 6 (CMIP6) to project changes in the joint probability of extreme storm surges and precipitation at European tide gauges under a medium and high emissions scenario, enabled by data-proximate cloud computing and statistical storm surge modeling. We find that the joint probability will increase in the northwest and decrease in most of the southwest of Europe. Averaged over Europe, the absolute magnitude of these changes is 36%–49% by 2080, depending on the scenario. The large-scale changes in the joint probability of extreme storm surges and precipitation are similar to those in the joint probability of extreme wind speeds and precipitation, but locally, differences can exceed the changes themselves. Due to internal climate variability and inter-model differences, projections based on simulations of only 5 to 6 randomly chosen CMIP6 models have a probability of higher than 10% to differ qualitatively from projections based on all CMIP6 simulations in multiple regions, especially under the medium emissions scenario and earlier in the twenty-first century. Therefore, our results provide a more robust and less uncertain representation of changes in the potential for compound flooding in Europe than previous projections

Sea Surface Salinity and Temperature Budgets in the North Atlantic Subtropical Gyre during SPURS Experiment: August 2012-August 2013

Variability at large to meso-scale in sea surface salinity (SSS) and sea surface temperature (SST) is investigated in the subtropical North Atlantic Ocean during the Subtropical Atlantic Surface Salinity Experiment Strasse/SPURS in August 2012 - August 2013. The products of the Soil Moisture and Ocean Salinity (SMOS) mission corrected from large scale systematic errors are tested and used to retrieve meso-scale salinity features, while OSTIA products, resolving meso-scale temperature features are used for SST. The comparison of corrected SMOS SSS data with drifter's in situ measurements from SPURS experiment shows a reasonable agreement, especially during winter time with RMS differences on the order of 0.15 pss (for 10 days, 75 km resolution SMOS product). The analysis of SSS (SST) variability reveals that the meso-scale eddies contribute to a substantial freshening (cooling) in the central high salinity region of the subtropical gyre, albeit smaller than Ekman and atmospheric freshwater (heat) seasonal flux, which are the leading terms in SSS (SST) budget. An error is estimated along with SSS and SST budgets; as well as sensitivity to the different products in use and residuals are discussed. The residuals in the SSS budget are large and can arise from errors in the advection fields and freshwater flux, from neglected small scale or unresolved local processes (salt fingering, vertical mixing and small scale subduction, etc.). However, their magnitude is similar to what is often parameterized as eddy horizontal diffusion to close large scale budgets

OceanGliders Oxygen SOP

The live version of this SOP is on the Ocean Gliders community in GITHUB. The home repository of this publication is in the Ocean Best Practices Repository. This standard operating procedure (SOP) document for dissolved oxygen (DO) aims to guide the user through the steps necessary to collect good quality dissolved oxygen data using ocean gliders for both real time and post deployment data streams

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore's Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to ML experts because of lack of training data and relevant, easy-to-use workflows. We present ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator's macro-scale physical state.The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res) and code (https://leap-stc.github.io/ClimSim) are released openly to support the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society