Representing climate and extreme weather events in integrated assessment models: A review of existing methods and options for development

The lack of information about future changes in extreme weather is a major constraint of Integrated Assessment Models (IAMs) of climate change. The generation of descriptions of future climate in current IAMs is assessed.We also review recent work on scenario development methods for weather extremes, focusing on those issues which are most relevant to the needs of IAMs. Finally, some options for implementing scenarios of weather extremes in IAMs are considered

Uncertainty in climate change impacts on basin-scale freshwater resources – preface to the special issue: the QUEST-GSI methodology and synthesis of results

This paper presents a preface to this Special Issue on the results of the QUEST-GSI (Global Scale Impacts) project on climate change impacts on catchment-scale water resources. A detailed description of the unified methodology, subsequently used in all studies in this issue, is provided. The project method involved running simulations of catchment-scale hydrology using a unified set of past and future climate scenarios, to enable a consistent analysis of the climate impacts around the globe. These scenarios include "policy-relevant" prescribed warming scenarios. This is followed by a synthesis of the key findings. Overall, the studies indicate that in most basins the models project substantial changes to river flow, beyond that observed in the historical record, but that in many cases there is considerable uncertainty in the magnitude and sign of the projected changes. The implications of this for adaptation activities are discussed

Pattern scaling using ClimGen: monthly-resolution future climate scenarios including changes in the variability of precipitation

Development, testing and example applications of the pattern-scaling approach for generating future climate change projections are reported here, with a focus on a particular software application called “ClimGen”. A number of innovations have been implemented, including using exponential and logistic functions of global-mean temperature to represent changes in local precipitation and cloud cover, and interpolation from climate model grids to a finer grid while taking into account land-sea contrasts in the climate change patterns. Of particular significance is a new approach for incorporating changes in the inter-annual variability of monthly precipitation simulated by climate models. This is achieved by diagnosing simulated changes in the shape of the gamma distribution of monthly precipitation totals, applying the pattern-scaling approach to estimate changes in the shape parameter under a future scenario, and then perturbing sequences of observed precipitation anomalies so that their distribution changes according to the projected change in the shape parameter. The approach cannot represent changes to the structure of climate timeseries (e.g. changed autocorrelation or teleconnection patterns) were they to occur, but is shown here to be more successful at representing changes in low precipitation extremes than previous pattern-scaling methods

Lower Left Ventricular Ejection Fraction Relates to Cerebrospinal Fluid Biomarker Evidence of Neurodegeneration in Older Adults

BACKGROUND: Subclinical cardiac dysfunction is associated with decreased cerebral blood flow, placing the aging brain at risk for Alzheimer's disease (AD) pathology and neurodegeneration. OBJECTIVE: This study investigates the association between subclinical cardiac dysfunction, measured by left ventricular ejection fraction (LVEF), and cerebrospinal fluid (CSF) biomarkers of AD and neurodegeneration. METHODS: Vanderbilt Memory & Aging Project participants free of dementia, stroke, and heart failure (n = 152, 72±6 years, 68% male) underwent echocardiogram to quantify LVEF and lumbar puncture to measure CSF levels of amyloid-β42 (Aβ42), phosphorylated tau (p-tau), and total tau (t-tau). Linear regressions related LVEF to CSF biomarkers, adjusting for age, sex, race/ethnicity, education, Framingham Stroke Risk Profile, cognitive diagnosis, and apolipoprotein E ɛ4 status. Secondary models tested an LVEF x cognitive diagnosis interaction and then stratified by diagnosis (normal cognitive (NC), mild cognitive impairment (MCI)). RESULTS: Higher LVEF related to decreased CSF Aβ42 levels (β= -6.50, p = 0.04) reflecting greater cerebral amyloid accumulation, but this counterintuitive result was attenuated after excluding participants with cardiovascular disease and atrial fibrillation (p = 0.07). We observed an interaction between LVEF and cognitive diagnosis on CSF t-tau (p = 0.004) and p-tau levels (p = 0.002), whereas lower LVEF was associated with increased CSF t-tau (β= -9.74, p = 0.01) and p-tau in the NC (β= -1.41, p = 0.003) but not MCI participants (p-values>0.13). CONCLUSIONS: Among cognitively normal older adults, subclinically lower LVEF relates to greater molecular evidence of tau phosphorylation and neurodegeneration. Modest age-related changes in cardiovascular function may have implications for pathophysiological changes in the brain later in life

Cerebrospinal fluid and plasma neurofilament light relate to abnormal cognition

Introduction Neuroaxonal damage may contribute to cognitive changes preceding clinical dementia. Accessible biomarkers are critical for detecting such damage. Methods Plasma and cerebrospinal fluid (CSF) neurofilament light (NFL) were related to neuropsychological performance among Vanderbilt Memory & Aging Project participants (plasma n = 333, 73 ± 7 years; CSF n = 149, 72 ± 6 years) ranging from normal cognition (NC) to mild cognitive impairment (MCI). Models adjusted for age, sex, race/ethnicity, education, apolipoprotein E ε4 carriership, and Framingham Stroke Risk Profile. Results Plasma NFL was related to all domains (P values ≤ .008) except processing speed (P values ≥ .09). CSF NFL was related to memory and language (P values ≤ .04). Interactions with cognitive diagnosis revealed widespread plasma associations, particularly in MCI participants, which were further supported in head-to-head comparison models. Discussion Plasma and CSF NFL (reflecting neuroaxonal injury) relate to cognition among non-demented older adults albeit with small to medium effects. Plasma NFL shows particular promise as an accessible biomarker with relevance to cognition in MCI

Emulating global climate change impacts on crop yields

The potential effects of climate change on the environment and society are many. In order to effectively quantify the uncertainty associated with these effects, highly complex simulation models are run with detailed representations of ecosystem processes. These models are computationally expensive and can involve a computer run of several days. Computationally cheaper models can be obtained from large ensembles of simulations using statistical emulation. The purpose of this paper is to construct a cheaper computational model (emulator) from simulations of the Lund- Potsdam-Jena managed Land (LPJmL), which is a dynamic global vegetation and crop model. This paper focuses on statistical emulation of potential crop yields from LPJmL and an emulator is constructed using a combination of ordinary least squares, principal component analysis and weighted least squares methods. For five climate models, under cross-validation the percentage of variance explained ranges from 60- 88% for the rainfed crops and 62-93% for the irrigated crops. The emulator can be used to predict potential crop yield change under any future climate scenarios and management options

Impact of socioeconomic deprivation on rate and cause of death in severe mental illness

Background: Socioeconomic status has important associations with disease-specific mortality in the general population. Although individuals with Severe Mental Illnesses (SMI) experience significant premature mortality, the relationship between socioeconomic status and mortality in this group remains under investigated.<p></p> Aims: To assess the impact of socioeconomic status on rate and cause of death in individuals with SMI (schizophrenia and bipolar disorder) relative to the local (Glasgow) and wider (Scottish) populations.<p></p> Methods: Cause and age of death during 2006-2010 inclusive for individuals with schizophrenia or bipolar disorder registered on the Glasgow Psychosis Clinical Information System (PsyCIS) were obtained by linkage to the Scottish General Register Office (GRO). Rate and cause of death by socioeconomic status, measured by Scottish Index of Multiple Deprivation (SIMD), were compared to the Glasgow and Scottish populations.<p></p> Results: Death rates were higher in people with SMI across all socioeconomic quintiles compared to the Glasgow and Scottish populations, and persisted when suicide was excluded. Differences were largest in the most deprived quintile (794.6 per 10,000 population vs. 274.7 and 252.4 for Glasgow and Scotland respectively). Cause of death varied by socioeconomic status. For those living in the most deprived quintile, higher drug-related deaths occurred in those with SMI compared to local Glasgow and wider Scottish population rates (12.3% vs. 5.9%, p = <0.001 and 5.1% p = 0.002 respectively). A lower proportion of deaths due to cancer in those with SMI living in the most deprived quintile were also observed, relative to the local Glasgow and wider Scottish populations (12.3% vs. 25.1% p = 0.013 and 26.3% p = <0.001). The proportion of suicides was significantly higher in those with SMI living in the more affluent quintiles relative to Glasgow and Scotland (54.6% vs. 5.8%, p = <0.001 and 5.5%, p = <0.001). Discussion and conclusions: Excess mortality in those with SMI occurred across all socioeconomic quintiles compared to the Glasgow and Scottish populations but was most marked in the most deprived quintiles when suicide was excluded as a cause of death. Further work assessing the impact of socioeconomic status on specific causes of premature mortality in SMI is needed

The impacts avoided with a 1.5 °C climate target: a global and regional assessment

The 2015 Paris Agreement commits countries to pursue efforts to limit the increase in global mean temperature to 1.5 °C above pre-industrial levels. We assess the consequences of achieving this target in 2100 for the impacts that are avoided, using several indicators of impact (exposure to drought, river flooding, heat waves and demands for heating and cooling energy). The proportion of impacts that are avoided is not simply equal to the proportional reduction in temperature. At the global scale, the median proportion of projected impacts avoided by the 1.5 °C target relative to a rise of 4 °C ranges between 62 and 95% across sectors: the greatest reduction is for heat wave impacts. The 1.5 °C target results in impacts that would be between 27 and 62% lower than with the 2 °C target. For each indicator, there are differences in the proportions of impacts avoided between regions depending on exposure and the regional changes in climate (particularly precipitation). Uncertainty in the proportion of impacts that are avoided for a specific sector depends on the range in the shape of the relationship between global temperature change and impact, and this varies between sectors