Geological Net Zero and the need for disaggregated accounting for carbon sinks.

Achieving net zero global emissions of carbon dioxide (CO), with declining emissions of other greenhouse gases, is widely expected to halt global warming. CO emissions will continue to drive warming until fully balanced by active anthropogenic CO removals. For practical reasons, however, many greenhouse gas accounting systems allow some "passive" CO uptake, such as enhanced vegetation growth due to CO fertilisation, to be included as removals in the definition of net anthropogenic emissions.

Early NRS Leg and Back Thresholds Predict Clinical Recovery after MIS Transforaminal Lumbar Interbody Fusion for Degenerative Spine Disease.

Study Design: This retrospective study included patients who underwent primary one-level minimally invasive (MIS) transforaminal lumbar interbody fusion (TLIF) for degenerative lumbar spine conditions.

Objective: To identify early predictors of failing to achieve the Oswestry Disability Index (ODI) minimum clinically important difference (MCID) one-year post-surgery.

Summary Of Background Data: Early identification of patients at risk of failing to achieve ODI-MCID is crucial for early intervention and improved postoperative counseling.

Heatwave attribution based on reliable operational weather forecasts.

The 2021 Pacific Northwest heatwave was so extreme as to challenge conventional statistical and climate-model-based approaches to extreme weather attribution. However, state-of-the-art operational weather prediction systems are demonstrably able to simulate the detailed physics of the heatwave. Here, we leverage these systems to show that human influence on the climate made this event at least 8 [2-50] times more likely.

Methane and the Paris Agreement temperature goals.

Meeting the Paris Agreement temperature goal necessitates limiting methane (CH)-induced warming, in addition to achieving net-zero or (net-negative) carbon dioxide (CO) emissions. In our model, for the median 1.5°C scenario between 2020 and 2050, CH mitigation lowers temperatures by 0.

Forecast-based attribution of a winter heatwave within the limit of predictability.

Attribution of extreme weather events has expanded rapidly as a field over the past decade. However, deficiencies in climate model representation of key dynamical drivers of extreme events have led to some concerns over the robustness of climate model-based attribution studies. It has also been suggested that the unconditioned risk-based approach to event attribution may result in false negative results due to dynamical noise overwhelming any climate change signal.

Improved calculation of warming-equivalent emissions for short-lived climate pollutants.

Anthropogenic global warming at a given time is largely determined by the cumulative total emissions (or stock) of long-lived climate pollutants (LLCPs), predominantly carbon dioxide (CO), and the emission rates (or flow) of short-lived climate pollutants (SLCPs) immediately prior to that time. Under the United Nations Framework Convention on Climate Change (UNFCCC), reporting of greenhouse gas emissions has been standardised in terms of CO-equivalent (CO-e) emissions using Global Warming Potentials (GWP) over 100-years, but the conventional usage of GWP does not adequately capture the different behaviours of LLCPs and SLCPs, or their impact on global mean surface temperature. An alternative usage of GWP, denoted GWP*, overcomes this problem by equating an increase in the emission rate of an SLCP with a one-off "pulse" emission of CO.

The many possible climates from the Paris Agreement's aim of 1.5 °C warming.

The United Nations' Paris Agreement includes the aim of pursuing efforts to limit global warming to only 1.5 °C above pre-industrial levels. However, it is not clear what the resulting climate would look like across the globe and over time.

The myriad challenges of the Paris Agreement.

The much awaited and intensely negotiated Paris Agreement was adopted on 12 December 2015 by the Parties to the United Nations Framework Convention on Climate Change. The agreement set out a more ambitious long-term temperature goal than many had anticipated, implying more stringent emissions reductions that have been under-explored by the research community. By its very nature a multidisciplinary challenge, filling the knowledge gap requires not only climate scientists, but the whole Earth system science community, as well as economists, engineers, lawyers, philosophers, politicians, emergency planners and others to step up.

Uncertain impacts on economic growth when stabilizing global temperatures at 1.5°C or 2°C warming.

Empirical evidence suggests that variations in climate affect economic growth across countries over time. However, little is known about the relative impacts of climate change on economic outcomes when global mean surface temperature (GMST) is stabilized at 1.5°C or 2°C warming relative to pre-industrial levels.

Attribution of changes in precipitation patterns in African rainforests.

Tropical rainforests in Africa are one of the most under-researched regions in the world, but research in the Amazonian rainforest suggests potential vulnerability to climate change. Using the large ensemble of Atmosphere-only general circulation model (AGCM) simulations within the weather@home project, statistics of precipitation in the dry season of the Congo Basin rainforest are analysed. By validating the model simulation against observations, we could identify a good model performance for the June, July, August (JJA) dry season, but this result does need to be taken with caution as observed data are of poor quality.

Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000.

Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 1766, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.

Cumulative carbon emissions, emissions floors and short-term rates of warming: implications for policy.

A number of recent studies have found a strong link between peak human-induced global warming and cumulative carbon emissions from the start of the industrial revolution, while the link to emissions over shorter periods or in the years 2020 or 2050 is generally weaker. However, cumulative targets appear to conflict with the concept of a 'floor' in emissions caused by sectors such as food production. Here, we show that the introduction of emissions floors does not reduce the importance of cumulative emissions, but may make some warming targets unachievable.

Warming caused by cumulative carbon emissions towards the trillionth tonne.

Global efforts to mitigate climate change are guided by projections of future temperatures. But the eventual equilibrium global mean temperature associated with a given stabilization level of atmospheric greenhouse gas concentrations remains uncertain, complicating the setting of stabilization targets to avoid potentially dangerous levels of global warming. Similar problems apply to the carbon cycle: observations currently provide only a weak constraint on the response to future emissions.

Greenhouse-gas emission targets for limiting global warming to 2 degrees C.

More than 100 countries have adopted a global warming limit of 2 degrees C or below (relative to pre-industrial levels) as a guiding principle for mitigation efforts to reduce climate change risks, impacts and damages. However, the greenhouse gas (GHG) emissions corresponding to a specified maximum warming are poorly known owing to uncertainties in the carbon cycle and the climate response. Here we provide a comprehensive probabilistic analysis aimed at quantifying GHG emission budgets for the 2000-50 period that would limit warming throughout the twenty-first century to below 2 degrees C, based on a combination of published distributions of climate system properties and observational constraints.

Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models.

In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide).

Constraints on future changes in climate and the hydrologic cycle.

What can we say about changes in the hydrologic cycle on 50-year timescales when we cannot predict rainfall next week? Eventually, perhaps, a great deal: the overall climate response to increasing atmospheric concentrations of greenhouse gases may prove much simpler and more predictable than the chaos of short-term weather. Quantifying the diversity of possible responses is essential for any objective, probability-based climate forecast, and this task will require a new generation of climate modelling experiments, systematically exploring the range of model behaviour that is consistent with observations. It will be substantially harder to quantify the range of possible changes in the hydrologic cycle than in global-mean temperature, both because the observations are less complete and because the physical constraints are weaker.

Quantifying uncertainties in climate system properties with the use of recent climate observations.

We derive joint probability density distributions for three key uncertain properties of the climate system, using an optimal fingerprinting approach to compare simulations of an intermediate complexity climate model with three distinct diagnostics of recent climate observations. On the basis of the marginal probability distributions, the 5 to 95% confidence intervals are 1.4 to 7.