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Lightning is an important atmospheric process for generating reactive nitrogen, resulting in the production of tropospheric ozone, as well as igniting wildland fires, which result in potentially large emissions of many pollutants and short-lived climate forcers. Lightning is also expected to change in frequency and location with the changing climate. As such, lightning is an important component of Earth system models. Until now, the Canadian Earth System Model (CanESM) did not contain an interactive-lightning parameterization. The fire parameterization in CanESM5.1 was designed to use prescribed monthly climatological lightning. In this study, we have added a logistical regression lightning model that predicts lightning occurrence interactively based on three environmental variables and their interactions in CanESM5.1's atmospheric model, CanAM5.1 (Canadian Atmospheric Model), creating the capacity to interactively model lightning, allowing for future projections under different climate scenarios. The modelled lightning and resulting burned area were evaluated against satellite measurements over the historical period, and model biases were found to be acceptable. Modelled lightning had a small negative bias and excellent land–ocean ratio compared to satellite measurements. The modified version of CanESM5.1 was used to simulate two future climate scenarios (SSP2-4.5 and SSP5-8.5; Shared Socioeconomic Pathway) to assess how lightning and burned area change in the future. Under the higher-emissions scenario (SSP5-8.5), CanESM5.1 predicts almost no change to the global mean lightning flash rate by the end of the century (2081–2100 vs. 2015–2035 average). However, there are substantial regional changes to lightning – particularly over land – such as a mean increase of 6 % in the northern mid-latitudes and decrease of −8 % in the tropics. By the century's end, the change in global total burned area with prescribed climatological lightning was about 2 times greater than that with interactive lightning (42 % vs. 26 % increase, respectively). Conversely, in the northern mid-latitudes the use of interactive lightning resulted in 3 times more burned area compared to that with unchanging lightning (48 % vs. 16 % increase, respectively). These results show that the future changes to burned area are greatly dependent on a model's lightning scheme, both spatially and overall.

Background The long-term outcomes of COVID-19 hospitalisation in individuals with pre-existing airway diseases are unknown. Methods Adult participants hospitalised for confirmed or clinically suspected COVID-19 and discharged between 5 March 2020 and 31 March 2021 were recruited to the Post-hospitalisation COVID-19 (PHOSP-COVID) study. Participants attended research visits at 5 months and 1 year post discharge. Clinical characteristics, perceived recovery, burden of symptoms and health-related quality of life (HRQoL) of individuals with pre-existing airway disease (i.e., asthma, COPD or bronchiectasis) were compared to the non-airways group. Results A total of 615 out of 2697 (22.8%) participants had a history of pre-existing airway diseases (72.0% diagnosed with asthma, 22.9% COPD and 5.1% bronchiectasis). At 1 year, the airways group participants were less likely to feel fully recovered (20.4% versus 33.2%, p

The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture released from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire–atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational-scale burn plot (usually > 103 m2) have made it extremely challenging to capture the myriad of factors controlling fire–atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4 × 4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m2), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere–fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire–atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence.

The Canadian Earth System Model version 5.0 (CanESM5.0), the most recent major version of the global climate model developed at the Canadian Centre for Climate Modelling and Analysis (CCCma) at Environment and Climate Change Canada (ECCC), has been used extensively in climate research and for providing future climate projections in the context of climate services. Previous studies have shown that CanESM5.0 performs well compared to other models and have revealed several model biases. To address these biases, the CCCma has recently initiated the “Analysis for Development” (A4D) activity, a coordinated analysis activity in support of CanESM development. Here we describe the goals and organization of this effort and introduce two variants (“p1” and “p2”) of a new CanESM version, CanESM5.1, which features important improvements as a result of the A4D activity. These improvements include the elimination of spurious stratospheric temperature spikes and an improved simulation of tropospheric dust. Other climate aspects of the p1 variant of CanESM5.1 are similar to those of CanESM5.0, while the p2 variant of CanESM5.1 features reduced equilibrium climate sensitivity and improved El Niño–Southern Oscillation (ENSO) variability as a result of intentional tuning of the atmospheric component. The A4D activity has also led to the improved understanding of other notable CanESM5.0 and CanESM5.1 biases, including the overestimation of North Atlantic sea ice, a cold bias over sea ice, biases in the stratospheric circulation and a cold bias over the Himalayas. It provides a potential framework for the broader climate community to contribute to CanESM development, which will facilitate further model improvements and ultimately lead to improved climate change information.

The Hybrid End-To-End Aerosol Classification (HETEAC) model for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is introduced. The model serves as the common baseline for the development, evaluation, and implementation of EarthCARE algorithms. It guarantees the consistency of different aerosol products from the multi-instrument platform and facilitates the conformity of broad-band optical properties needed for EarthCARE radiative-closure assessments. While the hybrid approach ensures that the theoretical description of aerosol microphysical properties is consistent with the optical properties of the measured aerosol types, the end-to-end model permits the uniform representation of aerosol types in terms of microphysical, optical, and radiative properties. Four basic aerosol components with prescribed microphysical properties are used to compose various natural and anthropogenic aerosols of the troposphere. The components contain weakly and strongly absorbing fine-mode and spherical and non-spherical coarse-mode particles and thus are representative for pollution, smoke, sea salt, and dust, respectively. Their microphysical properties are selected such that good coverage of the observational phase space of intensive, i.e., concentration-independent, optical aerosol properties derived from EarthCARE measurements is obtained. Mixing rules to calculate optical and radiative properties of any aerosol blend composed of the four basic components are provided. Applications of HETEAC in the generation of test scenes, the development of retrieval algorithms for stand-alone and synergistic aerosol products from EarthCARE's atmospheric lidar (ATLID) and multi-spectral imager (MSI), and for radiative-closure assessments are introduced. Finally, the implications of simplifying model assumptions and possible improvements are discussed, and conclusions for future validation and development work are drawn.

Abstract Year‐round precipitation in coastal East Antarctica and Antarctic Peninsula was used to investigate the seasonal patterns in sources of atmospheric perchlorate (ClO4−). Although featuring distinct climates, the two locations exhibit similar annual mean and seasonal cycles of ClO4− concentration, with higher values in autumn and lower concentrations in winter and spring. Tropospheric formation dominates atmospheric ClO4− in spring and summer, which is influenced by both oxidants levels and environmental conditions (e.g., air humidity). Tropospheric ClO4− production may also be promoted by elevated levels of oxidants brought by air mass from the interior Antarctic ice sheet in spring and summer. The autumn concentration maximum may originate from ClO4− produced in the stratosphere through reactions between reactive chlorine and ozone during spring and summer. In winter, the stratospheric input may contribute to ClO4− via polar stratospheric clouds sedimentation.

Knowledge of microparticle geometry is essential for accurate calculation of ice core volume-related dust metrics (mass, flux, and particle size distributions) and subsequent paleoclimate interpretations, yet particle shape data remain sparse in Antarctica. Here we present 41 discrete particle shape measurements, volume calculations, and calibrated continuous particle time series spanning 50–16 ka from the South Pole Ice Core (SPC14) to assess particle shape characteristics and variability. We used FlowCAM, a dynamic particle imaging instrument, to measure aspect ratios (width divided by length) of microparticles. We then compared those results to Coulter counter measurements on the same set of samples as well as high-resolution laser-based (Abakus) data collected from SPC14 during continuous flow analysis. The 41 discrete samples were collected during three periods of millennial-scale climate variability: Heinrich Stadial 1 (18–16 ka, n=6; ∼250 years per sample), the Last Glacial Maximum (LGM) (27–18 ka, n=19; ∼460 years per sample), and during both Heinrich Stadial 4 (42–36 ka, n=8; ∼620 years per sample) and Heinrich Stadial 5 (50–46 ka, n=8; ∼440 years per sample). Using FlowCAM measurements, we calculated different particle size distributions (PSDs) for spherical and ellipsoidal volume estimates. Our calculated volumes were then compared to published Abakus calibration techniques. We found that Abakus-derived PSDs calculated assuming ellipsoidal, rather than spherical, particle shapes provide a more accurate representation of PSDs measured by Coulter counter, reducing Abakus to Coulter counter flux and mass ratios from 1.82 (spherical assumption) to 0.79 and 1.20 (ellipsoidal assumptions; 1 being a perfect match). Coarser particles (>5.0 µm diameter) show greater variation in measured aspect ratios than finer particles ( µm). While fine particle volumes can be accurately estimated using the spherical assumption, applying the same assumption to coarse particles has a large effect on inferred particle volumes. Temporally, coarse and fine particle aspect ratios do not significantly change within or among the three time periods (p value >0.05), suggesting that long-range transport of dust is likely dominated by clay minerals and other elongated minerals.

Column ozone variability has important implications for surface photochemistry and the climate. Ice-core nitrate isotopes are suspected to be influenced by column ozone variability and δ15N(NO3-) has been sought to serve as a proxy of column ozone variability. In this study, we examined the ability of ice-core nitrate isotopes to reflect column ozone variability by measuring δ15N(NO3-) and Δ17O(NO3-) in a shallow ice core drilled at the South Pole. The ice core covers the period 1944–2005, and during this period δ15N(NO3-) showed large annual variability ((59.2 ± 29.3) ‰ ), but with no apparent response to the Antarctic ozone hole. Utilizing a snow photochemical model, we estimated 6.9 ‰ additional enrichments in δ15N(NO3-) could be caused by the development of the ozone hole. Nevertheless, this enrichment is small and masked by the effects of the snow accumulation rate at the South Pole over the same period of the ozone hole. The Δ17O(NO3-) record has displayed a decreasing trend by ∼ 3.4 ‰ since 1976. This magnitude of change cannot be caused by enhanced post-depositional processing related to the ozone hole. Instead, the Δ17O(NO3-) decrease was more likely due to the proposed decreases in the O3 / HOx ratio in the extratropical Southern Hemisphere. Our results suggest ice-core δ15N(NO3-) is more sensitive to snow accumulation rate than to column ozone, but at sites with a relatively constant snow accumulation rate, information of column ozone variability embedded in δ15N(NO3-) should be retrievable.

The injection of sulfur into the stratosphere by volcanic eruptions is the dominant driver of natural climate variability on interannual to multidecadal timescales. Based on a set of continuous sulfate and sulfur records from a suite of ice cores from Greenland and Antarctica, the HolVol v.1.0 database includes estimates of the magnitudes and approximate source latitudes of major volcanic stratospheric sulfur injection (VSSI) events for the Holocene (from 9500 BCE or 11 500 years BP to 1900 CE), constituting an extension of the previous record by 7000 years. The database incorporates new-generation ice-core aerosol records with a sub-annual temporal resolution and a demonstrated sub-decadal dating accuracy and precision. By tightly aligning and stacking the ice-core records on the WD2014 chronology from Antarctica, we resolve long-standing inconsistencies in the dating of ancient volcanic eruptions that arise from biased (i.e., dated too old) ice-core chronologies over the Holocene for Greenland. We reconstruct a total of 850 volcanic eruptions with injections in excess of 1 teragram of sulfur (Tg S); of these eruptions, 329 (39 %) are located in the low latitudes with bipolar sulfate deposition, 426 (50 %) are located in the Northern Hemisphere extratropics (NHET) and 88 (10 %) are located in the Southern Hemisphere extratropics (SHET). The spatial distribution of the reconstructed eruption locations is in agreement with prior reconstructions for the past 2500 years. In total, these eruptions injected 7410 Tg S into the stratosphere: 70 % from tropical eruptions and 25 % from NH extratropical eruptions. A long-term latitudinally and monthly resolved stratospheric aerosol optical depth (SAOD) time series is reconstructed from the HolVol VSSI estimates, representing the first Holocene-scale reconstruction constrained by Greenland and Antarctica ice cores. These new long-term reconstructions of past VSSI and SAOD variability confirm evidence from regional volcanic eruption chronologies (e.g., from Iceland) in showing that the Early Holocene (9500–7000 BCE) experienced a higher number of volcanic eruptions (+16 %) and cumulative VSSI (+86 %) compared with the past 2500 years. This increase coincides with the rapid retreat of ice sheets during deglaciation, providing context for potential future increases in volcanic activity in regions under projected glacier melting in the 21st century. The reconstructed VSSI and SAOD data are available at https://doi.org/10.1594/PANGAEA.928646 (Sigl et al., 2021).

Summary: Background: The scale of COVID-19 and its well documented long-term sequelae support a need to understand long-term outcomes including frailty. Methods: This prospective cohort study recruited adults who had survived hospitalisation with clinically diagnosed COVID-19 across 35 sites in the UK (PHOSP-COVID). The burden of frailty was objectively measured using Fried's Frailty Phenotype (FFP). The primary outcome was the prevalence of each FFP group—robust (no FFP criteria), pre-frail (one or two FFP criteria) and frail (three or more FFP criteria)—at 5 months and 1 year after discharge from hospital. For inclusion in the primary analysis, participants required complete outcome data for three of the five FFP criteria. Longitudinal changes across frailty domains are reported at 5 months and 1 year post-hospitalisation, along with risk factors for frailty status. Patient-perceived recovery and health-related quality of life (HRQoL) were retrospectively rated for pre-COVID-19 and prospectively rated at the 5 month and 1 year visits. This study is registered with ISRCTN, number ISRCTN10980107. Findings: Between March 5, 2020, and March 31, 2021, 2419 participants were enrolled with FFP data. Mean age was 57.9 (SD 12.6) years, 933 (38.6%) were female, and 429 (17.7%) had received invasive mechanical ventilation. 1785 had measures at both timepoints, of which 240 (13.4%), 1138 (63.8%) and 407 (22.8%) were frail, pre-frail and robust, respectively, at 5 months compared with 123 (6.9%), 1046 (58.6%) and 616 (34.5%) at 1 year. Factors associated with pre-frailty or frailty were invasive mechanical ventilation, older age, female sex, and greater social deprivation. Frail participants had a larger reduction in HRQoL compared with before their COVID-19 illness and were less likely to describe themselves as recovered. Interpretation: Physical frailty and pre-frailty are common following hospitalisation with COVID-19. Improvement in frailty was seen between 5 and 12 months although two-thirds of the population remained pre-frail or frail. This suggests comprehensive assessment and interventions targeting pre-frailty and frailty beyond the initial illness are required. Funding: UK Research and Innovation and National Institute for Health Research.

This paper provides initial results from a multi-model ensemble analysis based on the volc-pinatubo-full experiment performed within the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The volc-pinatubo-full experiment is based on an ensemble of volcanic forcing-only climate simulations with the same volcanic aerosol dataset across the participating models (the 1991–1993 Pinatubo period from the CMIP6-GloSSAC dataset). The simulations are conducted within an idealized experimental design where initial states are sampled consistently across models from the CMIP6-piControl simulation providing unperturbed preindustrial background conditions. The multi-model ensemble includes output from an initial set of six participating Earth system models (CanESM5, GISS-E2.1-G, IPSL-CM6A-LR, MIROC-E2SL, MPI-ESM1.2-LR and UKESM1). The results show overall good agreement between the different models on the global and hemispheric scales concerning the surface climate responses, thus demonstrating the overall effectiveness of VolMIP's experimental design. However, small yet significant inter-model discrepancies are found in radiative fluxes, especially in the tropics, that preliminary analyses link with minor differences in forcing implementation; model physics, notably aerosol–radiation interactions; the simulation and sampling of El Niño–Southern Oscillation (ENSO); and, possibly, the simulation of climate feedbacks operating in the tropics. We discuss the volc-pinatubo-full protocol and highlight the advantages of volcanic forcing experiments defined within a carefully designed protocol with respect to emerging modelling approaches based on large ensemble transient simulations. We identify how the VolMIP strategy could be improved in future phases of the initiative to ensure a cleaner sampling protocol with greater focus on the evolving state of ENSO in the pre-eruption period.

Abstract The Arctic is warming at almost four times the global rate. An estimated sixty percent of greenhouse‐gas‐induced Arctic warming has been offset by anthropogenic aerosols, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state‐of‐the‐art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m−2), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic‐induced Arctic climate change.

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014. In response to the pattern of all aerosols effective radiative forcing (ERF), the fast temperature responses are characterized by cooling over the continental areas, especially in the Northern Hemisphere, with the largest cooling over East Asia and India, sulfate being the dominant aerosol surface temperature driver for present-day emissions. In the Arctic there is a warming signal for winter in the ensemble mean of fast temperature responses, but the model-to-model variability is large, and it is presumably linked to aerosol-induced circulation changes. The largest fast precipitation responses are seen in the tropical belt regions, generally characterized by a reduction over continental regions and presumably a southward shift of the tropical rain belt. This is a characteristic and robust feature among most models in this study, associated with weakening of the monsoon systems around the globe (Asia, Africa and America) in response to hemispherically asymmetric cooling from a Northern Hemisphere aerosol perturbation, forcing possibly the Intertropical Convergence Zone (ITCZ) and tropical precipitation to shift away from the cooled hemisphere despite that aerosols' effects on temperature and precipitation are only partly realized in these simulations as the sea surface temperatures are kept fixed. An interesting feature in aerosol-induced circulation changes is a characteristic dipole pattern with intensification of the Icelandic Low and an anticyclonic anomaly over southeastern Europe, inducing warm air advection towards the northern polar latitudes in winter.

Low clouds persist in the summer Arctic with important consequences for the radiation budget. In this study, we simulate the linear relationship between liquid water content (LWC) and cloud droplet number concentration (CDNC) observed during an aircraft campaign based out of Resolute Bay, Canada, conducted as part of the Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments study in July 2014. Using a single-column model, we find that autoconversion can explain the observed linear relationship between LWC and CDNC. Of the three autoconversion schemes we examined, the scheme using continuous drizzle (Khairoutdinov and Kogan, 2000) appears to best reproduce the observed linearity in the tenuous cloud regime (Mauritsen et al., 2011), while a scheme with a threshold for rain (Liu and Daum, 2004) best reproduces the linearity at higher CDNC. An offline version of the radiative transfer model used in the Canadian Atmospheric Model version 4.3 is used to compare the radiative effects of the modelled and observed clouds. We find that there is no significant difference in the upward longwave cloud radiative effect at the top of the atmosphere from the three autoconversion schemes (p=0.05) but that all three schemes differ at p=0.05 from the calculations based on observations. In contrast, the downward longwave and shortwave cloud radiative effect at the surface for the Wood (2005b) and Khairoutdinov and Kogan (2000) schemes do not differ significantly (p=0.05) from the observation-based radiative calculations, while the Liu and Daum (2004) scheme differs significantly from the observation-based calculation for the downward shortwave but not the downward longwave fluxes.

The South Pole Ice Core (SPICEcore) was drilled in 2014–2016 to provide a detailed multi-proxy archive of paleoclimate conditions in East Antarctica during the Holocene and late Pleistocene. Interpretation of these records requires an accurate depth–age relationship. Here, we present the SPICEcore (SP19) timescale for the age of the ice of SPICEcore. SP19 is synchronized to the WD2014 chronology from the West Antarctic Ice Sheet Divide (WAIS Divide) ice core using stratigraphic matching of 251 volcanic events. These events indicate an age of 54 302±519 BP (years before 1950) at the bottom of SPICEcore. Annual layers identified in sodium and magnesium ions to 11 341 BP were used to interpolate between stratigraphic volcanic tie points, yielding an annually resolved chronology through the Holocene. Estimated timescale uncertainty during the Holocene is less than 18 years relative to WD2014, with the exception of the interval between 1800 to 3100 BP when uncertainty estimates reach ±25 years due to widely spaced volcanic tie points. Prior to the Holocene, uncertainties remain within 124 years relative to WD2014. Results show an average Holocene accumulation rate of 7.4 cm yr−1 (water equivalent). The time variability of accumulation rate is consistent with expectations for steady-state ice flow through the modern spatial pattern of accumulation rate. Time variations in nitrate concentration, nitrate seasonal amplitude and δ15N of N2 in turn are as expected for the accumulation rate variations. The highly variable yet well-constrained Holocene accumulation history at the site can help improve scientific understanding of deposition-sensitive climate proxies such as δ15N of N2 and photolyzed chemical compounds.

Abstract Background The Multidimensional Daily Diary of Fatigue-Fibromyalgia-17 instrument (MDF-Fibro-17) has been developed for use in fibromyalgia (FM) clinical studies and includes 5 domains: Global Fatigue Experience, Cognitive Fatigue, Physical Fatigue, Motivation, and Impact on Function. Psychometric properties of the MDF-Fibro-17 needed to demonstrate the appropriateness of using this instrument in clinical studies are presented. Methods Psychometric analyses were conducted to evaluate the factor structure, reliability, validity, and responsiveness of the MDF-Fibro-17 using data from a Phase 2 clinical study of FM patients (N = 381). Confirmatory factor analyses (CFA) were performed to ensure understanding of the multidimensional domain structure, and a secondary factor analysis of the domains examined the appropriateness of calculating a total score in addition to domain scores. Longitudinal psychometric analyses (test-retest reliability and responder analysis) were also conducted on the data from Baseline to Week 6. Results The CFA supported the 17-item, 5 domain structure of this instrument as the best fit of the data: comparative fit index (CFI) and non-normed fit index (NNFI) were 0.997 and 0.992 respectively, standardized root mean square residual (SRMR) was 0.010 and the root mean square error of approximation (RMSEA) was 0.06. In addition, total score (CFI and NNFI both 0.95) met required standards. For the total and 5 domain scores, reliability and validity data were acceptable: test-retest and internal consistency were above 0.9; correlations were as expected with the Global Fatigue Index (GFI) (0.62-0.75), Fibromyalgia Impact Questionnaire (FIQ) Total (0.59–0.71), and 36-Item Short Form Health Survey (SF-36) vitality (VT) (0.43–0.53); and discrimination was shown using quintile scores for the GFI, FIQ Total, and Pain Numeric Rating Scale (NRS) quartiles. In addition, sensitivity to change was demonstrated with an overall mean responder score of -2.59 using anchor-based methods. Conclusion The MDF-Fibro-17 reliably measures 5 domains of FM-related fatigue and psychometric evaluation confirms that this measure meets or exceeds each of the predefined acceptable thresholds for evidence of reliability, validity, and responsiveness to changes in clinical status. This suggests that the MDF-Fibro-17 is an appropriate and responsive measure of FM-related fatigue in clinical studies.

Sulfate is an important component of global atmospheric aerosol, and has partially compensated for greenhouse gas-induced warming during the industrial period. The magnitude of direct and indirect radiative forcing of aerosols since preindustrial times is a large uncertainty in climate models, which has been attributed largely to uncertainties in the preindustrial environment. Here, we report observations of the oxygen isotopic composition (Δ17O) of sulfate aerosol collected in the remote marine boundary layer (MBL) in spring and summer in order to evaluate sulfate production mechanisms in pristine-like environments. Model-aided analysis of the observations suggests that 33–50 % of sulfate in the MBL is formed via oxidation by hypohalous acids (HOX = HOBr + HOCl), a production mechanism typically excluded in large-scale models due to uncertainties in the reaction rates, which are due mainly to uncertainties in reactive halogen concentrations. Based on the estimated fraction of sulfate formed via HOX oxidation, we further estimate that daily-averaged HOX mixing ratios on the order of 0.01–0.1 parts per trillion (ppt = pmol/mol) in the remote MBL during spring and summer are sufficient to explain the observations.

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

We present the WD2014 chronology for the upper part (0–2850 m; 31.2 ka BP) of the West Antarctic Ice Sheet (WAIS) Divide (WD) ice core. The chronology is based on counting of annual layers observed in the chemical, dust and electrical conductivity records. These layers are caused by seasonal changes in the source, transport, and deposition of aerosols. The measurements were interpreted manually and with the aid of two automated methods. We validated the chronology by comparing to two high-accuracy, absolutely dated chronologies. For the Holocene, the cosmogenic isotope records of 10Be from WAIS Divide and 14C for IntCal13 demonstrated that WD2014 was consistently accurate to better than 0.5 % of the age. For the glacial period, comparisons to the Hulu Cave chronology demonstrated that WD2014 had an accuracy of better than 1 % of the age at three abrupt climate change events between 27 and 31 ka. WD2014 has consistently younger ages than Greenland ice core chronologies during most of the Holocene. For the Younger Dryas–Preboreal transition (11.595 ka; 24 years younger) and the Bølling–Allerød Warming (14.621 ka; 7 years younger), WD2014 ages are within the combined uncertainties of the timescales. Given its high accuracy, WD2014 can become a reference chronology for the Southern Hemisphere, with synchronization to other chronologies feasible using high-quality proxies of volcanism, solar activity, atmospheric mineral dust, and atmospheric methane concentrations.

We present experimental evidence of relativistic electron-cyclotron resonances (RECRs) in the vicinity of the relativistically intense pump laser of a laser wakefield accelerator (LWFA). The effects of the RECRs are visualized by imaging the driven plasma wave with a few-cycle, optical probe in transverse geometry. The probe experiences strong, spectrally dependent and relativistically modified birefringence in the vicinity of the pump that arises due to the plasma electrons’ relativistic motion in the pump’s electromagnetic fields. The spectral birefringence is strongly dependent on the local magnetic field distribution of the pump laser. Analysis and comparison to both 2D and 3D particle-in-cell simulations confirm the origin of the RECR effect and its appearance in experimental and simulated shadowgrams of the laser-plasma interaction. The RECR effect is relevant for any relativistic, magnetized plasma and in the case of LWFA could provide a nondestructive, in situ diagnostic for tracking the evolution of the pump’s intensity distribution with propagation through tenuous plasma.

Ice core nitrate concentrations peak in the summer in both Greenland and Antarctica. Two nitrate concentration peaks in one annual layer have been observed some years in ice cores in Greenland from samples dating post-1900, with the additional nitrate peak occurring in the spring. The origin of the spring nitrate peak was hypothesized to be pollution transport from the mid-latitudes in the industrial era. We performed a case study on the origin of a spring nitrate peak in 2005 measured from a snowpit at Summit, Greenland, covering 3 years of snow accumulation. The effect of long-range transport of nitrate on this spring peak was excluded by using sulfate as a pollution tracer. The isotopic composition of nitrate (δ15N, δ18O and Δ17O) combined with photochemical calculations suggest that the occurrence of this spring peak is linked to a significantly weakened stratospheric ozone (O3) layer. The weakened O3 layer resulted in elevated UVB (ultraviolet-B) radiation on the snow surface, where the production of OH and NOx from the photolysis of their precursors was enhanced. Elevated NOx and OH concentrations resulted in enhanced nitrate production mainly through the NO2 + OH formation pathway, as indicated by decreases in δ18O and Δ17O of nitrate associated with the spring peak. We further examined the nitrate concentration record from a shallow ice core covering the period from 1772 to 2006 and found 19 years with double nitrate peaks after the 1950s. Out of these 19 years, 14 of the secondary nitrate peaks were accompanied by sulfate peaks, suggesting long-range transport of nitrate as their source. In the other 5 years, low springtime O3 column density was observed, suggesting enhanced local production of nitrate as their source. The results suggest that, in addition to direct transport of nitrate from polluted regions, enhanced local photochemistry can also lead to a spring nitrate peak. The enhanced local photochemistry is probably associated with the interannual variability of O3 column density in the Arctic, which leads to elevated surface UV radiation in some years. In this scenario, enhanced photochemistry caused increased local nitrate production under the condition of elevated local NOx abundance in the industrial era.

Satellite-based cloud top effective radius retrieved by the CERES Science Team were combined with simulated aerosol concentrations from CCCma CanAM4 to examine relationships between aerosol and cloud that underlie the first aerosol indirect (cloud albedo) effect. Evidence of a strong negative relationship between sulphate, and organic aerosols, with cloud top effective radius was found for low clouds, indicating both aerosol types are contributing to the first indirect effect on a global scale. Furthermore, effects of aerosol on the cloud droplet effective radius are more pronounced for larger cloud liquid water paths. While CanAM4 broadly reproduces the observed relationship between sulphate aerosols and cloud droplets, it does not reproduce the dependency of cloud top droplet size on organic aerosol concentrations nor the dependency on cloud liquid water path. Simulations with a modified version of the model yield a more realistic dependency of cloud droplets on organic carbon. The robustness of the methods used in the study are investigated by repeating the analysis using aerosol simulated by the GOCART model and cloud top effective radii derived from the MODIS Science Team.

We present a reinforcement learning‐based heuristic for a two‐player interdiction game called the dynamic shortest path interdiction problem (DSPI). The DSPI involves an evader and an interdictor who take turns in the problem, with the interdictor selecting a set of arcs to attack and the evader choosing an arc to traverse at each step of the game. Our model employs the Monte Carlo tree search framework to learn a policy for the players using randomized roll‐outs. This policy is stored as an asymmetric game tree and can be further refined as the game unfolds. We leverage alpha–beta pruning and existing bounding schemes in the literature to prune suboptimal branches. Our numerical experiments demonstrate that the prescribed approach yields near‐optimal solutions in many cases and allows for flexibility in balancing solution quality and computational effort. [ABSTRACT FROM AUTHOR]

We study a two-stage shortest-path interdiction problem between an interdictor and an evader, in which the cost for an evader to use each arc is given by the arc's base cost plus an additional cost if the arc is attacked by the interdictor. The interdictor acts first to attack a subset of arcs, and then the evader traverses the network using a shortest path. In the problem we study, the interdictor does not know the exact value of each base cost, but instead only knows the (non-negative uniform) distribution of each arc's base cost. The evader observes both the subset of arcs attacked by the interdictor and the true base cost values before traversing the network. The interdictor seeks to maximize the conditional value-at-risk of the evader's shortest-path costs, given some specified risk parameter. We provide an exact method for this problem that utilizes row generation, partitioning, and bounding strategies, and demonstrate the efficacy of our approach on a set of randomly generated instances. [ABSTRACT FROM AUTHOR]