Numerical simulation of prominence oscillations

We present numerical simulations, obtained with the Versatile Advection Code, of the oscillations of an inverse polarity prominence. The internal prominence equilibrium, the surrounding corona and the inert photosphere are well represented. Gravity and thermodynamics are not taken into account, but it is argued that these are not crucial. The oscillations can be understood in terms of a solid body moving through a plasma. The mass of this solid body is determined by the magnetic field topology, not by the prominence mass proper. The model also allows us to study the effect of the ambient coronal plasma on the motion of the prominence body. Horizontal oscillations are damped through the emission of slow waves while vertical oscillations are damped through the emission of fast waves.Comment: 12 pages, 14 figures, accepted by Astronomy and Astrophysic

Non-adiabatic magnetohydrodynamic waves in a cylindrical prominence thread with mass flow

High-resolution observations show that oscillations and waves in prominence threads are common and that they are attenuated in a few periods. In addition, observers have also reported the presence of material flows in such prominence fine-structures. Here we investigate the time damping of non-leaky oscillations supported by a homogeneous cylindrical prominence thread embedded in an unbounded corona and with a steady mass flow. Thermal conduction and radiative losses are taken into account as damping mechanisms, and the effect of these non-ideal effects and the steady flow on the attenuation of oscillations is assessed. We solve the general dispersion relation for linear, non-adiabatic magnetoacoustic and thermal waves supported by the model, and find that slow and thermal modes are efficiently attenuated by non-adiabatic mechanisms. On the contrary, fast kink modes are much less affected and their damping times are much larger than those observed. The presence of flow has no effect on the damping of slow and thermal waves, whereas fast kink waves are more (less) attenuated when they propagate parallel (anti-parallel) to the flow direction. Although the presence of steady mass flows improves the efficiency of non-adiabatic mechanisms on the attenuation of transverse, kink oscillations for parallel propagation to the flow, its effect is still not enough to obtain damping times compatible with observations.Comment: Accepted for publication in Ap

Validation and empirical correction of MODIS AOT and AE over ocean

We present a validation study of Collection 5 MODIS level 2 Aqua and Terra AOT (aerosol optical thickness) and AE (Ångström exponent) over ocean by comparison to coastal and island AERONET (AErosol RObotic NETwork) sites for the years 2003–2009. We show that MODIS (MODerate-resolution Imaging Spectroradiometer) AOT exhibits significant biases due to wind speed and cloudiness of the observed scene, while MODIS AE, although overall unbiased, exhibits less spatial contrast on global scales than the AERONET observations. The same behaviour can be seen when MODIS AOT is compared against Maritime Aerosol Network (MAN) data, suggesting that the spatial coverage of our datasets does not preclude global conclusions. Thus, we develop empirical correction formulae for MODIS AOT and AE that significantly improve agreement of MODIS and AERONET observations. We show these correction formulae to be robust. Finally, we study random errors in the corrected MODIS AOT and AE and show that they mainly depend on AOT itself, although small contributions are present due to wind speed and cloud fraction in AOT random errors and due to AE and cloud fraction in AE random errors. Our analysis yields significantly higher random AOT errors than the official MODIS error estimate (0.03 + 0.05 τ), while random AE errors are smaller than might be expected. This new dataset of bias-corrected MODIS AOT and AE over ocean is intended for aerosol model validation and assimilation studies, but also has consequences as a stand-alone observational product. For instance, the corrected dataset suggests that much less fine mode aerosol is transported across the Pacific and Atlantic oceans

Constraining uncertainty in aerosol direct forcing

The uncertainty in present-day anthropogenic forcing is dominated by uncertainty in the strength of the contribution from aerosol. Much of the uncertainty in the direct aerosol forcing can be attributed to uncertainty in the anthropogenic fraction of aerosol in the present-day atmosphere, due to a lack of historical observations. Here we present a robust relationship between total present-day aerosol optical depth and the anthropogenic contribution across three multi-model ensembles and a large single-model perturbed parameter ensemble. Using observations of aerosol optical depth, we determine a reduced likely range of the anthropogenic component and hence a reduced uncertainty in the direct forcing of aerosol

Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation

Atmospheric aerosol has substantial impacts on climate, air quality and biogeochemical cycles, and its concentrations are highly variable in space and time. A key variability to evaluate within models that simulate aerosol is the vertical distribution, which influences atmospheric heating profiles and aerosol–cloud interactions, to help constrain aerosol residence time and to better represent the magnitude of simulated impacts. To ensure a consistent comparison between modeled and observed vertical distribution of aerosol, we implemented an aerosol lidar simulator within the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package version 2 (COSPv2). We assessed the attenuated total backscattered (ATB) signal and the backscatter ratios (SRs) at 532 nm in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1). The simulator performs the computations at the same vertical resolution as the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), making use of aerosol optics from the E3SMv1 model as inputs and assuming that aerosol is uniformly distributed horizontally within each model grid box. The simulator applies a cloud masking and an aerosol detection threshold to obtain the ATB and SR profiles that would be observed above clouds by CALIOP with its aerosol detection capability. Our analysis shows that the aerosol distribution simulated at a seasonal timescale is generally in good agreement with observations. Over the Southern Ocean, however, the model does not produce the SR maximum as observed in the real world. Comparison between clear-sky and all-sky SRs shows little differences, indicating that the cloud screening by potentially incorrect model clouds does not affect the mean aerosol signal averaged over a season. This indicates that the differences between observed and simulated SR values are due not to sampling errors, but to deficiencies in the representation of aerosol in models. Finally, we highlight the need for future applications of lidar observations at multiple wavelengths to provide insights into aerosol properties and distribution and their representation in Earth system models.</p

Host model uncertainties in aerosol radiative forcing estimates: results from the AeroCom Prescribed intercomparison study

Simulated multi-model “diversity” in aerosol direct radiative forcing estimates is often perceived as a measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated “host-model uncertainties” are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in twelve participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is −4.47Wm−2 and the inter-model standard deviation is 0.55Wm−2, corresponding to a relative standard deviation of 12 %. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.04Wm−2, and the standard deviation increases to 1.01W−2, corresponding to a significant relative standard deviation of 97 %. However, the top-of-atmosphere forcing variability owing to absorption (subtracting the scattering case from the case with scattering and absorption) is low, with absolute (relative) standard deviations of 0.45Wm−2 (8 %) clear-sky and 0.62Wm−2 (11 %) all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the Aero- Com Direct Effect experiment demonstrates that host model uncertainties could explain about 36% of the overall sulfate forcing diversity of 0.11Wm−2 in the AeroCom Direct Radiative Effect experiment

Ensembles of global climate model variants designed for the quantification and constraint of uncertainty in aerosols and their radiative forcing

Tropospheric aerosol radiative forcing has persisted for many years as one of the major causes of uncertainty in global climate model simulations. To sample the range of plausible aerosol and atmospheric states and perform robust statistical analyses of the radiative forcing, it is important to account for the combined effects of many sources of model uncertainty, which is rarely done due to the high computational cost. This paper describes the designs of two ensembles of the HadGEM-UKCA global climate model and provides the first analyses of the uncertainties in aerosol radiative forcing and their causes. The first ensemble was designed to comprehensively sample uncertainty in the aerosol state, while the other samples additional uncertainties in the physical model related to clouds, humidity and radiation, thereby allowing an analysis of uncertainty in the aerosol effective radiative forcing. Each ensemble consists of around 200 simulations of the pre-industrial and present-day atmospheres. The uncertainty in aerosol radiative forcing in our ensembles is comparable to the range of estimates from multi-model intercomparison projects. The mean aerosol effective radiative forcing is –1.45 W m–2 (credible interval –2.07 to –0.81 W m–2), which encompasses but is more negative than the –1.17 W m–2 in the 2013 Atmospheric Chemistry and Climate Model Intercomparison Project and –0.90 W m–2 in the IPCC 5th Assessment Report. The ensembles can be used to reduce aerosol radiative forcing uncertainty by challenging them with multiple measurements as well as to isolate potential causes of multi-model differences

Improvement of the retrieval algorithm for GOSAT SWIR XCO₂ and XCH₄ and their validation using TCCON data

The column-averaged dry-air mole fractions of carbon dioxide and methane (XCO2 and XCH4) have been retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations and released as a SWIR L2 product from the National Institute for Environmental Studies (NIES). XCO2 and XCH4 retrieved using the version 01.xx retrieval algorithm showed large negative biases and standard deviations (−8.85 and 4.75 ppm for XCO2 and −20.4 and 18.9 ppb for XCH4, respectively) compared with data of the Total Carbon Column Observing Network (TCCON). Multiple reasons for these error characteristics (e.g., solar irradiance database, handling of aerosol scattering) are identified and corrected in a revised version of the retrieval algorithm (version 02.xx). The improved retrieval algorithm shows much smaller biases and standard deviations (−1.48 and 2.09 ppm for XCO2 and −5.9 and 12.6 ppb for XCH4, respectively) than the version 01.xx. Also, the number of post-screened measurements is increased, especially at northern mid- and high-latitudinal areas

Diagnostic accuracy of point-of-care testing for acute coronary syndromes, heart failure and thromboembolic events in primary care: a cluster-randomised controlled trial

Background: Evidence of the clinical benefit of 3-in-1 point-of-care testing (POCT) for cardiac troponin T (cTnT), N-terminal pro-brain natriuretic peptide (NT-proBNP) and D-dimer in cardiovascular risk stratification at primary care level for diagnosing acute coronary syndromes (ACS), heart failure (HF) and thromboembolic events (TE) is very limited. The aim of this study is to analyse the diagnostic accuracy of POCT in primary care. Methods: Prospective multicentre controlled trial cluster-randomised to POCT-assisted diagnosis and conventional diagnosis (controls). Men and women presenting in 68 primary care practices in Zurich County (Switzerland) with chest pain or symptoms of dyspnoea or TE were consecutively included after baseline consultation and working diagnosis. A follow-up visit including confirmed diagnosis was performed to determine the accuracy of the working diagnosis, and comparison of working diagnosis accuracy between the two groups. Results: The 218 POCT patients and 151 conventional diagnosis controls were mostly similar in characteristics, symptoms and pre-existing diagnoses, but differed in working diagnosis frequencies. However, the follow-up visit showed no statistical intergroup difference in confirmed diagnosis frequencies. Working diagnoses overall were significantly more correct in the POCT group (75.7% vs 59.6%, p = 0.002), as were the working diagnoses of ACS/HF/TE (69.8% vs 45.2%, p = 0.002). All three biomarker tests showed good sensitivity and specificity. Conclusion: POCT confers substantial benefit in primary care by correctly diagnosing significantly more patients

The global aerosol synthesis and science project (GASSP): Measurements and modeling to reduce uncertainty

This is the final version of the article. Available from American Meteorological Society via the DOI in this record.The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.GASSP was funded by the Natural Environment Research Council (NERC) under Grants NE/J024252/1, NE/J022624/1, and NE/J023515/1; ACID-PRUF under Grants NE/I020059/1 and NE/I020148/1; the European Union BACCHUS project under Grant 603445-BACCHUS; ACTRIS under Grants 262254 and 654109; and by the UK–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. We made use of the N8 HPC facility funded from the N8 consortium and an Engineering and Physical Sciences Research Council Grant to use ARCHER (EP/K000225/1) and the JASMIN facility (www.jasmin.ac.uk/) via the Centre for Environmental Data Analysis funded by NERC and the UK Space Agency and delivered by the Science and Technology Facilities Council. We acknowledge the following additional funding: the Royal Society Wolfson Merit Award (Carslaw); a doctoral training grant from the Natural Environment Research Council and a CASE studentship with the Met Office Hadley Centre (Regayre); the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement FP7-280025 (Stier); the Department of Energy under DE-SC0007178 (Zhang); the U.S. National Science Foundation under ATM-745986 (Snider); the NOAA Global Change Program (Nenes); NASA Global Tropospheric Experiment Program, the NASA Tropospheric Composition Program, the NASA Radiation Sciences Program, and the NASA Earth Venture Suborbital Project (Anderson); the NOAA Climate Program Office (Quinn); NSF Atmospheric Chemistry Program, the NASA Global Tropospheric Experiment, and NASA Earth Science Project Office (Clarke); German Federal Ministry of Education and Research (BMBF) CLOUD12 project Grant 01LK1222B (Kristensen); Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation and the Swedish Polar Research Secretariat (SPRS) for access to the icebreaker Oden and logistical support (Leck); the Department of Energy (DE-SC0007178) and the Max Planck Society (Andreae, Poeschl); the global environment research fund of the Ministry of the Environment in Japan (2-1403), the Arctic Challenge for Sustainability (ArCS) project of the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) in Japan, and the Japan Society for the Promotion of Science (JSPS) KAKENHI (Grants JP16H01770, JP26701004, and JP26241003) (Kondo, Oshima); Lufthansa for enabling CARIBIC and the German Federal Ministry of Education and Research (BMBF) for financing the CARIBIC instruments operation as part of the Joint Project IAGOS-D (Hermann); the Collaborative Innovation Center of Climate Change supported by the Jiangsu provincial government and the JirLATEST supported by the Ministry of Education, China (Ding and Chi); the Max Planck Institute for Chemistry, Mainz, Germany (Schmale); the NOAA Atmospheric Composition and Climate Program, the NASA Radiation Sciences Program, and the NASA Upper Atmosphere Research Program supporting the NOAA SP2 BC data acquisition and analysis (Schwarz); DOE (BER/ASR) DE-SC0016559 and EPA STAR 83587701-0 (the EPA has not reviewed this manuscript and no endorsement should be inferred) (Jimenez); and Environment and Climate Change Canada (Leaitch)