Bidecadal North Atlantic ocean circulation variability controlled by timing of volcanic eruptions

International audienceWhile bidecadal climate variability has been evidenced in several North Atlantic paleoclimaterecords, its drivers remain poorly understood. Here we show that the subset of CMIP5historical climate simulations that produce such bidecadal variability exhibits a robustsynchronization, with a maximum in Atlantic Meridional Overturning Circulation (AMOC) 15years after the 1963 Agung eruption. The mechanisms at play involve salinity advection fromthe Arctic and explain the timing of Great Salinity Anomalies observed in the 1970s and the1990s. Simulations, as well as Greenland and Iceland paleoclimate records, indicate thatcoherent bidecadal cycles were excited following five Agung-like volcanic eruptions of the lastmillennium. Climate simulations and a conceptual model reveal that destructive interferencecaused by the Pinatubo 1991 eruption may have damped the observed decreasing trend of theAMOC in the 2000s. Our results imply a long-lasting climatic impact and predictabilityfollowing the next Agung-like eruption

Drivers and uncertainties of future global marine primary production in marine ecosystem models

Past model studies have projected a global decrease in marine net primary production (NPP) over the 21st century, but these studies focused on the multi-model mean rather than on the large inter-model differences. Here, we analyze model-simulated changes in NPP for the 21st century under IPCC's high-emission scenario RCP8.5. We use a suite of nine coupled carbon–climate Earth system models with embedded marine ecosystem models and focus on the spread between the different models and the underlying reasons. Globally, NPP decreases in five out of the nine models over the course of the 21st century, while three show no significant trend and one even simulates an increase. The largest model spread occurs in the low latitudes (between 30° S and 30° N), with individual models simulating relative changes between −25 and +40 %. Of the seven models diagnosing a net decrease in NPP in the low latitudes, only three simulate this to be a consequence of the classical interpretation, i.e., a stronger nutrient limitation due to increased stratification leading to reduced phytoplankton growth. In the other four, warming-induced increases in phytoplankton growth outbalance the stronger nutrient limitation. However, temperature-driven increases in grazing and other loss processes cause a net decrease in phytoplankton biomass and reduce NPP despite higher growth rates. One model projects a strong increase in NPP in the low latitudes, caused by an intensification of the microbial loop, while NPP in the remaining model changes by less than 0.5 %. While models consistently project increases NPP in the Southern Ocean, the regional inter-model range is also very substantial. In most models, this increase in NPP is driven by temperature, but it is also modulated by changes in light, macronutrients and iron as well as grazing. Overall, current projections of future changes in global marine NPP are subject to large uncertainties and necessitate a dedicated and sustained effort to improve the models and the concepts and data that guide their developmen

Towards the prevention of acute lung injury: a population based cohort study protocol

<p>Abstract</p> <p>Background</p> <p>Acute lung injury (ALI) is an example of a critical care syndrome with limited treatment options once the condition is fully established. Despite improved understanding of pathophysiology of ALI, the clinical impact has been limited to improvements in supportive treatment. On the other hand, little has been done on the prevention of ALI. Olmsted County, MN, geographically isolated from other urban areas offers the opportunity to study clinical pathogenesis of ALI in a search for potential prevention targets.</p> <p>Methods/Design</p> <p>In this population-based observational cohort study, the investigators identify patients at high risk of ALI using the prediction model applied within the first six hours of hospital admission. Using a validated system-wide electronic surveillance, Olmsted County patients at risk are followed until ALI, death or hospital discharge. Detailed in-hospital (second hit) exposures and meaningful short and long term outcomes (quality-adjusted survival) are compared between ALI cases and high risk controls matched by age, gender and probability of developing ALI. Time sensitive biospecimens are collected for collaborative research studies. Nested case control comparison of 500 patients who developed ALI with 500 matched controls will provide an adequate power to determine significant differences in common hospital exposures and outcomes between the two groups.</p> <p>Discussion</p> <p>This population-based observational cohort study will identify patients at high risk early in the course of disease, the burden of ALI in the community, and the potential targets for future prevention trials.</p

Improved Respiratory Outcomes for X-Linked Myotubular Myopathy (XLMTM) with Gene Replacement Therapy, Resamirigene Bilparvovec (ASPIRO): Preliminary Results from ASPIRO, a Phase 1/2/3 Study

Astelas Gene Therapies

Recent progress in understanding and predicting Atlantic decadal climate variability

Recent Atlantic climate prediction studies are an exciting new contribution to an extensive body of research on Atlantic decadal variability and predictability that has long emphasized the unique role of the Atlantic Ocean in modulating the surface climate. We present a survey of the foundations and frontiers in our understanding of Atlantic variability mechanisms, the role of the Atlantic Meridional Overturning Circulation (AMOC), and our present capacity for putting that understanding into practice in actual climate prediction systems

Simulations of ocean deoxygenation in the historical era: insights from forced and coupled models

Ocean deoxygenation due to anthropogenic warming represents a major threat to marine ecosystems and fisheries. Challenges remain in simulating the modern observed changes in the dissolved oxygen (O2). Here, we present an analysis of upper ocean (0-700m) deoxygenation in recent decades from a suite of the Coupled Model Intercomparison Project phase 6 (CMIP6) ocean biogeochemical simulations. The physics and biogeochemical simulations include both ocean-only (the Ocean Model Intercomparison Project Phase 1 and 2, OMIP1 and OMIP2) and coupled Earth system (CMIP6 Historical) configurations. We examine simulated changes in the O2 inventory and ocean heat content (OHC) over the past 5 decades across models. The models simulate spatially divergent evolution of O2 trends over the past 5 decades. The trend (multi-model mean and spread) for upper ocean global O2 inventory for each of the MIP simulations over the past 5 decades is 0.03 ± 0.39×1014 [mol/decade] for OMIP1, −0.37 ± 0.15×1014 [mol/decade] for OMIP2, and −1.06 ± 0.68×1014 [mol/decade] for CMIP6 Historical, respectively. The trend in the upper ocean global O2 inventory for the latest observations based on the World Ocean Database 2018 is −0.98×1014 [mol/decade], in line with the CMIP6 Historical multi-model mean, though this recent observations-based trend estimate is weaker than previously reported trends. A comparison across ocean-only simulations from OMIP1 and OMIP2 suggests that differences in atmospheric forcing such as surface wind explain the simulated divergence across configurations in O2 inventory changes. Additionally, a comparison of coupled model simulations from the CMIP6 Historical configuration indicates that differences in background mean states due to differences in spin-up duration and equilibrium states result in substantial differences in the climate change response of O2. Finally, we discuss gaps and uncertainties in both ocean biogeochemical simulations and observations and explore possible future coordinated ocean biogeochemistry simulations to fill in gaps and unravel the mechanisms controlling the O2 changes

The need for carbon emissions-driven climate projections in CMIP7

Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), both for idealized model experiments, and for climate projections of different emissions scenarios. We argue that although this approach was pragmatic to allow parallel development of Earth System Model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth System Models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently represented upstream of ESMs in an idealized fashion during scenario development. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use, projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon-climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular sources and sinks of methane) and process-based representation of carbon removal options. Such experiments would allow resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts. Such efforts will provide information on the range of possible future climate states including Earth system processes and feedbacks which are increasingly well-represented in ESMs, thus forming a critical and complementary pillar underpinning proposed km-scale climate modeling activities and calls to better utilize novel machine learning approaches