Ocean carbon and nitrogen isotopes in CSIRO Mk3L-COAL version 1.0: a tool for palaeoceanographic research

The isotopes of carbon (δ13C) and nitrogen (δ15N) are commonly used proxies for understanding the ocean. When used in tandem, they provide powerful insight into physical and biogeochemical processes. Here, we detail the implementation of δ13C and δ15N in the ocean component of an Earth system model. We evaluate our simulated δ13C and δ15N against contemporary measurements, place the model's performance alongside other isotope-enabled models and document the response of δ13C and δ15N to changes in ecosystem functioning. The model combines the Commonwealth Scientific and Industrial Research Organisation Mark 3L (CSIRO Mk3L) climate system model with the Carbon of the Ocean, Atmosphere and Land (COAL) biogeochemical model. The oceanic component of CSIRO Mk3L-COAL has a resolution of 1.6∘ latitude&thinsp;×&thinsp;2.8∘ longitude and resolves multimillennial timescales, running at a rate of ∼400 years per day. We show that this coarse-resolution, computationally efficient model adequately reproduces water column and core-top δ13C and δ15N measurements, making it a useful tool for palaeoceanographic research. Changes to ecosystem function involve varying phytoplankton stoichiometry, varying CaCO3 production based on calcite saturation state and varying N2 fixation via iron limitation. We find that large changes in CaCO3 production have little effect on δ13C and δ15N, while changes in N2 fixation and phytoplankton stoichiometry have substantial and complex effects. Interpretations of palaeoceanographic records are therefore open to multiple lines of interpretation where multiple processes imprint on the isotopic signature, such as in the tropics, where denitrification, N2 fixation and nutrient utilisation influence δ15N. Hence, there is significant scope for isotope-enabled models to provide more robust interpretations of the proxy records.</p

Recent warming on Spitsbergen - influence of atmospheric circulation and sea ice cover

Spitsbergen has experienced some of the most severe temperature changes in the Arctic during the last three decades. This study relates the recent warming to variations in large-scale atmospheric circulation (AC), air mass characteristics, and sea ice concentration (SIC), both regionally around Spitsbergen and locally in three fjords. We find substantial warming for all AC patterns for all seasons, with greatest temperature increase in winter. A major part of the warming can be attributed to changes in air mass characteristics associated with situations of both cyclonic and anticyclonic air advection from north and east and situations with a nonadvectional anticyclonic ridge. In total, six specific AC types (out of 21), which occur on average 41% of days in a year, contribute approximately 80% of the recent warming. The relationship between the land-based surface air temperature (SAT) and local and regional SIC was highly significant, particularly for the most contributing AC types. The high correlation between SAT and SIC for air masses from east and north of Spitsbergen suggests that a major part of the atmospheric warming observed in Spitsbergen is driven by heat exchange from the larger open water area in the Barents Sea and region north of Spitsbergen. Finally, our results show that changes in frequencies of AC play a minor role to the total recent surface warming. Thus, the strong warming in Spitsbergen in the latest decades is not driven by increased frequencies of “warm” AC types but rather from sea ice decline, higher sea surface temperatures, and a general background warming

High-resolution projections of surface water availability for Tasmania, Australia

Changes to streamflows caused by climate change may have major impacts on the management of water for hydro-electricity generation and agriculture in Tasmania, Australia. We describe changes to Tasmanian surface water availability from 1961–1990 to 2070–2099 using high-resolution simulations. Six fine-scale (&amp;sim;10 km&lt;sup&gt;2&lt;/sup&gt;) simulations of daily rainfall and potential evapotranspiration are generated with the CSIRO Conformal Cubic Atmospheric Model (CCAM), a variable-resolution regional climate model (RCM). These variables are bias-corrected with quantile mapping and used as direct inputs to the hydrological models AWBM, IHACRES, Sacramento, SIMHYD and SMAR-G to project streamflows. &lt;br&gt;&lt;br&gt; The performance of the hydrological models is assessed against 86 streamflow gauges across Tasmania. The SIMHYD model is the least biased (median bias = −3%) while IHACRES has the largest bias (median bias = −22%). We find the hydrological models that best simulate observed streamflows produce similar streamflow projections. &lt;br&gt;&lt;br&gt; There is much greater variation in projections between RCM simulations than between hydrological models. Marked decreases of up to 30% are projected for annual runoff in central Tasmania, while runoff is generally projected to increase in the east. Daily streamflow variability is projected to increase for most of Tasmania, consistent with increases in rainfall intensity. Inter-annual variability of streamflows is projected to increase across most of Tasmania. &lt;br&gt;&lt;br&gt; This is the first major Australian study to use high-resolution bias-corrected rainfall and potential evapotranspiration projections as direct inputs to hydrological models. Our study shows that these simulations are capable of producing realistic streamflows, allowing for increased confidence in assessing future changes to surface water variability

Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction

Dynamical weather and climate prediction models underpin many studies of the Earth system and hold the promise of being able to make robust projections of future climate change based on physical laws. However, simulations from these models still show many differences compared with observations. Machine learning has been applied to solve certain prediction problems with great success, and recently it's been proposed that this could replace the role of physically-derived dynamical weather and climate models to give better quality simulations. Here, instead, a framework using machine learning together with physically-derived models is tested, in which it is learnt how to correct the errors of the latter from timestep to timestep. This maintains the physical understanding built into the models, whilst allowing performance improvements, and also requires much simpler algorithms and less training data. This is tested in the context of simulating the chaotic Lorenz '96 system, and it is shown that the approach yields models that are stable and that give both improved skill in initialised predictions and better long-term climate statistics. Improvements in long-term statistics are smaller than for single time-step tendencies, however, indicating that it would be valuable to develop methods that target improvements on longer time scales. Future strategies for the development of this approach and possible applications to making progress on important scientific problems are discussed.Comment: 26p, 7 figures To be published in Journal of Advances in Modeling Earth System

Attributing human mortality during extreme heat waves to anthropogenic climate change

It has been argued that climate change is the biggest global health threat of the 21st century. The extreme high temperatures of the summer of 2003 were associated with up to seventy thousand excess deaths across Europe. Previous studies have attributed the meteorological event to the human influence on climate, or examined the role of heat waves on human health. Here, for the first time, we explicitly quantify the role of human activity on climate and heat-related mortality in an event attribution framework, analysing both the Europe-wide temperature response in 2003, and localised responses over London and Paris. Using publicly-donated computing, we perform many thousands of climate simulations of a high-resolution regional climate model. This allows generation of a comprehensive statistical description of the 2003 event and the role of human influence within it, using the results as input to a health impact assessment model of human mortality. We find large-scale dynamical modes of atmospheric variability remain largely unchanged under anthropogenic climate change, and hence the direct thermodynamical response is mainly responsible for the increased mortality. In summer 2003, anthropogenic climate change increased the risk of heat-related mortality in Central Paris by ~70% and by ~20% in London, which experienced lower extreme heat. Out of the estimated ~315 and ~735 summer deaths attributed to the heatwave event in Greater London and Central Paris, respectively, 64 (±3) deaths were attributable to anthropogenic climate change in London, and 506 (±51) in Paris. Such an ability to robustly attribute specific damages to anthropogenic drivers of increased extreme heat can inform societal responses to, and responsibilities for, climate change

Super Storm Desmond: a process-based assessment

“Super” Storm Desmond broke meteorological and hydrological records during a record warm year in the British-Irish Isles (BI). The severity of the storm may be a harbinger of expected changes to regional hydroclimate as global temperatures continue to rise. Here, we adopt a process-based approach to investigate the potency of Desmond, and explore the extent to which climate change may have been a contributory factor. Through an Eulerian assessment of water vapour flux we determine that Desmond was accompanied by an Atmospheric River (AR) of severity unprecedented since at least 1979, on account of both high atmospheric humidity and high wind speeds. Lagrangian air-parcel tracking and moisture attribution techniques show that long-term warming of North Atlantic sea surface temperatures (SSTs) has significantly increased the chance of such high humidity in ARs in the vicinity of the BI. We conclude that, given exactly the same dynamical conditions associated with Desmond, the likelihood of such an intense AR has already increased by 25% due to long-term climate change. However, our analysis represents a first-order assessment, and further research is needed into the controls influencing AR dynamics

Simplifying the clinical classification of polymerase gamma (POLG) disease based on age of onset; studies using a cohort of 155 cases

Background: Variants in POLG are one of the most common causes of inherited mitochondrial disease. Phenotypic classification of POLG disease has evolved haphazardly making it complicated and difficult to implement in everyday clinical practise. The aim of our study was to simplify the classification and facilitate better clinical recognition. / Methods: A multinational, retrospective study using data from 155 patients with POLG variants recruited from seven European countries. / Results: We describe the spectrum of clinical features associated with POLG variants in the largest known cohort of patients. While clinical features clearly form a continuum, stratifying patients simply according to age of onset—onset prior to age 12 years; onset between 12 and 40 years and onset after the age of 40 years, permitted us to identify clear phenotypic and prognostic differences. Prior to 12 years of age, liver involvement (87%), seizures (84%), and feeding difficulties (84%) were the major features. For those with onset between 12 and 40 years, ataxia (90%), peripheral neuropathy (84%), and seizures (71%) predominated, while for those with onset over 40 years, ptosis (95%), progressive external ophthalmoplegia (89%), and ataxia (58%) were the major clinical features. The earlier the onset the worse the prognosis. Patients with epilepsy and those with compound heterozygous variants carried significantly worse prognosis. / Conclusion: Based on our data, we propose a simplified POLG disease classification, which can be used to guide diagnostic investigations and predict disease course

Climate Impacts From a Removal of Anthropogenic Aerosol Emissions

Limiting global warming to 1.5 or 2.0°C requires strong mitigation of anthropogenic greenhouse gas (GHG) emissions. Concurrently, emissions of anthropogenic aerosols will decline, due to coemission with GHG, and measures to improve air quality. However, the combined climate effect of GHG and aerosol emissions over the industrial era is poorly constrained. Here we show the climate impacts from removing present-day anthropogenic aerosol emissions and compare them to the impacts from moderate GHG-dominated global warming. Removing aerosols induces a global mean surface heating of 0.5–1.1°C, and precipitation increase of 2.0–4.6%. Extreme weather indices also increase. We find a higher sensitivity of extreme events to aerosol reductions, per degree of surface warming, in particular over the major aerosol emission regions. Under near-term warming, we find that regional climate change will depend strongly on the balance between aerosol and GHG forcing

The impact of gender, puberty, and pregnancy in patients with POLG disease

OBJECTIVE: To study the impact of gender, puberty, and pregnancy on the expression of POLG disease, one of the most common mitochondrial diseases known. METHODS: Clinical, laboratory, and genetic data were collected retrospectively from 155 patients with genetically confirmed POLG disease recruited from seven European countries. We used the available data to study the impact of gender, puberty, and pregnancy on disease onset and deterioration. RESULTS: We found that disease onset early in life was common in both sexes but there was also a second peak in females around the time of puberty. Further, pregnancy had a negative impact with 10 of 14 women (71%) experiencing disease onset or deterioration during pregnancy. INTERPRETATION: Gender clearly influences the expression of POLG disease. While onset very early in life was common in both males and females, puberty in females appeared associated both with disease onset and increased disease activity. Further, both disease onset and deterioration, including seizure aggravation and status epilepticus, appeared to be associated with pregnancy. Thus, whereas disease activity appears maximal early in life with no subsequent peaks in males, both menarche and pregnancy appear associated with disease onset or worsening in females. This suggests that hormonal changes may be a modulating factor

Safety of drug use in patients with a primary mitochondrial disease: An international Delphi-based consensus

Clinical guidance is often sought when prescribing drugs for patients with primary mitochondrial disease. Theoretical considerations concerning drug safety in patients with mitochondrial disease may lead to unnecessary withholding of a drug in a situation of clinical need. The aim of this study was to develop consensus on safe medication use in patients with a primary mitochondrial disease. A panel of 16 experts in mitochondrial medicine, pharmacology, and basic science from six different countries was established. A modified Delphi technique was used to allow the panellists to consider draft recommendations anonymously in two Delphi rounds with predetermined levels of agreement. This process was supported by a review of the available literature and a consensus conference that included the panellists and representatives of patient advocacy groups. A high level of consensus was reached regarding the safety of all 46 reviewed drugs, with the knowledge that the risk of adverse events is influenced both by individual patient risk factors and choice of drug or drug class. This paper details the consensus guidelines of an expert panel and provides an important update of previously established guidelines in safe medication use in patients with primary mitochondrial disease. Specific drugs, drug groups, and clinical or genetic conditions are described separately as they require special attention. It is important to emphasise that consensus-based information is useful to provide guidance, but that decisions related to drug prescribing should always be tailored to the specific needs and risks of each individual patient. We aim to present what is current knowledge and plan to update this regularly both to include new drugs and to review those currently included