An eight-year long reanalysis of atmospheric composition data covering the period 2003–2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by ...assimilating satellite data into a global model and data assimilation system. This reanalysis provides fields of chemically reactive gases, namely carbon monoxide, ozone, nitrogen oxides, and formaldehyde, as well as aerosols and greenhouse gases globally at a horizontal resolution of about 80 km for both the troposphere and the stratosphere. This paper describes the assimilation system for the reactive gases and presents validation results for the reactive gas analysis fields to document the data set and to give a first indication of its quality. Tropospheric CO values from the MACC reanalysis are on average 10–20% lower than routine observations from commercial aircrafts over airports through most of the troposphere, and have larger negative biases in the boundary layer at urban sites affected by air pollution, possibly due to an underestimation of CO or precursor emissions. Stratospheric ozone fields from the MACC reanalysis agree with ozonesondes and ACE-FTS data to within ±10% in most seasons and regions. In the troposphere the reanalysis shows biases of −5% to +10% with respect to ozonesondes and aircraft data in the extratropics, but has larger negative biases in the tropics. Area-averaged total column ozone agrees with ozone fields from a multi-sensor reanalysis data set to within a few percent. NO2 fields from the reanalysis show the right seasonality over polluted urban areas of the NH and over tropical biomass burning areas, but underestimate wintertime NO2 maxima over anthropogenic pollution regions and overestimate NO2 in northern and southern Africa during the tropical biomass burning seasons. Tropospheric HCHO is well simulated in the MACC reanalysis even though no satellite data are assimilated. It shows good agreement with independent SCIAMACHY retrievals over regions dominated by biogenic emissions with some anthropogenic input, such as the eastern US and China, and also over African regions influenced by biogenic sources and biomass burning.
Global tropospheric ozone distributions, budgets, and radiative forcings from an ensemble of 26 state‐of‐the‐art atmospheric chemistry models have been intercompared and synthesized as part of a ...wider study into both the air quality and climate roles of ozone. Results from three 2030 emissions scenarios, broadly representing “optimistic,” “likely,” and “pessimistic” options, are compared to a base year 2000 simulation. This base case realistically represents the current global distribution of tropospheric ozone. A further set of simulations considers the influence of climate change over the same time period by forcing the central emissions scenario with a surface warming of around 0.7K. The use of a large multimodel ensemble allows us to identify key areas of uncertainty and improves the robustness of the results. Ensemble mean changes in tropospheric ozone burden between 2000 and 2030 for the 3 scenarios range from a 5% decrease, through a 6% increase, to a 15% increase. The intermodel uncertainty (±1 standard deviation) associated with these values is about ±25%. Model outliers have no significant influence on the ensemble mean results. Combining ozone and methane changes, the three scenarios produce radiative forcings of −50, 180, and 300 mW m−2, compared to a CO2 forcing over the same time period of 800–1100 mW m−2. These values indicate the importance of air pollution emissions in short‐ to medium‐term climate forcing and the potential for stringent/lax control measures to improve/worsen future climate forcing. The model sensitivity of ozone to imposed climate change varies between models but modulates zonal mean mixing ratios by ±5 ppbv via a variety of feedback mechanisms, in particular those involving water vapor and stratosphere‐troposphere exchange. This level of climate change also reduces the methane lifetime by around 4%. The ensemble mean year 2000 tropospheric ozone budget indicates chemical production, chemical destruction, dry deposition and stratospheric input fluxes of 5100, 4650, 1000, and 550 Tg(O3) yr−1, respectively. These values are significantly different to the mean budget documented by the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (TAR). The mean ozone burden (340 Tg(O3)) is 10% larger than the IPCC TAR estimate, while the mean ozone lifetime (22 days) is 10% shorter. Results from individual models show a correlation between ozone burden and lifetime, and each model's ozone burden and lifetime respond in similar ways across the emissions scenarios. The response to climate change is much less consistent. Models show more variability in the tropics compared to midlatitudes. Some of the most uncertain areas of the models include treatments of deep tropical convection, including lightning NOx production; isoprene emissions from vegetation and isoprene's degradation chemistry; stratosphere‐troposphere exchange; biomass burning; and water vapor concentrations.
Daily global analyses and 5-day forecasts are generated in the context of the European Monitoring Atmospheric Composition and Climate (MACC) project using an extended version of the Integrated ...Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The IFS now includes modules for chemistry, deposition and emission of reactive gases, aerosols, and greenhouse gases, and the 4-dimensional variational data assimilation scheme makes use of multiple satellite observations of atmospheric composition in addition to meteorological observations. This paper describes the data assimilation setup of the new Composition-IFS (C-IFS) with respect to reactive gases and validates analysis fields of ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) for the year 2008 against independent observations and a control run without data assimilation. The largest improvement in CO by assimilation of Measurements of Pollution in the Troposphere (MOPITT) CO columns is seen in the lower troposphere of the Northern Hemisphere (NH) extratropics during winter, and during the South African biomass-burning season. The assimilation of several O3 total column and stratospheric profile retrievals greatly improves the total column, stratospheric and upper tropospheric O3 analysis fields relative to the control run. The impact on lower tropospheric ozone, which comes from the residual of the total column and stratospheric profile O3 data, is smaller, but nevertheless there is some improvement particularly in the NH during winter and spring. The impact of the assimilation of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) is small because of the short lifetime of NO2, suggesting that NO2 observations would be better used to adjust emissions instead of initial conditions. The results further indicate that the quality of the tropospheric analyses and of the stratospheric ozone analysis obtained with the C-IFS system has improved compared to the previous "coupled" model system of MACC.
Can deep learning beat numerical weather prediction?
Philosophical transactions - Royal Society. Mathematical, Physical and engineering sciences/Philosophical transactions - Royal Society. Mathematical, physical and engineering sciences,
04/2021
Journal Article
Roadmap on multiscale materials modeling van der Giessen, Erik; Schultz, Peter A; Bertin, Nicolas ...
Modelling and simulation in materials science and engineering,
06/2020, Volume:
28, Issue:
4
Journal Article
Peer reviewed
Open access
Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that ...govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware.
The acute phase of sepsis is characterized by a strong inflammatory reaction. At later stages in some patients, immunoparalysis may be encountered, which is associated with a poor outcome. By ...transcriptional and metabolic profiling of human patients with sepsis, we found that a shift from oxidative phosphorylation to aerobic glycolysis was an important component of initial activation of host defense. Blocking metabolic pathways with metformin diminished cytokine production and increased mortality in systemic fungal infection in mice. In contrast, in leukocytes rendered tolerant by exposure to lipopolysaccharide or after isolation from patients with sepsis and immunoparalysis, a generalized metabolic defect at the level of both glycolysis and oxidative metabolism was apparent, which was restored after recovery of the patients. Finally, the immunometabolic defects in humans were partially restored by therapy with recombinant interferon-γ, which suggested that metabolic processes might represent a therapeutic target in sepsis.
A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new chemistry modules ...complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system in which chemical transport model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A 1 year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulfur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, and wintertime SO2, and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about 10 times more computationally efficient than IFS-MOZART.
We present and discuss a new dataset of gridded emissions covering the historical period (1850-2000) in decadal increments at a horizontal resolution of 0.5° in latitude and longitude. The primary ...purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment report (AR5). Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available at this point; 40 regions and 12 sectors are used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, is then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Simulations from two chemistry-climate models are used to test the ability of the emission dataset described here to capture long-term changes in atmospheric ozone, carbon monoxide and aerosol distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations indicate that the concentration of carbon monoxide is underestimated at the Mace Head station; however, the long-term trend over the limited observational period seems to be reasonably well captured. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates and observations.
We use long-term, coincident O
3 and temperature measurements at the regionally representative US Environmental Protection Agency Clean Air Status and Trends Network (CASTNet) over the eastern US ...from 1988 through 2009 to characterize the surface O
3 response to year-to-year fluctuations in weather, for the purpose of evaluating global chemistry-climate models. We first produce a monthly climatology for each site over all available years, defined as the slope of the best-fit line (
m
O3-T) between monthly average values of maximum daily 8-hour average (MDA8) O
3 and monthly average values of daily maximum surface temperature (
T
max). Applying two distinct statistical approaches to aggregate the site-specific measurements to the regional scale, we find that summer time
m
O3-T is 3–6
ppb
K
−1 (
r
=
0.5–0.8) over the Northeast, 3–4
ppb
K
−1 (
r
=
0.5–0.9) over the Great Lakes, and 3–6
ppb
K
−1 (
r
=
0.2–0.8) over the Mid-Atlantic. The Geophysical Fluid Dynamics Laboratory (GFDL) Atmospheric Model version 3 (AM3) global chemistry-climate model generally captures the seasonal variations in correlation coefficients and
m
O3-T despite biases in both monthly mean summertime MDA8 O
3 (up to +10 to +30
ppb) and daily
T
max (up to +5
K) over the eastern US. During summer, GFDL AM3 reproduces
m
O3-T over the Northeast (
m
O3-T
=
2–6
ppb
K
−1;
r
=
0.6–0.9), but underestimates
m
O3-T by 4
ppb
K
−1 over the Mid-Atlantic, in part due to excessively warm temperatures above which O
3 production saturates in the model. Combining
T
max biases in GFDL AM3 with an observation-based
m
O3-T estimate of 3
ppb
K
−1implies that temperature biases could explain up to 5–15
ppb of the MDA8 O
3 bias in August and September though correcting for excessively cool temperatures would worsen the O
3 bias in June. We underscore the need for long-term, coincident measurements of air pollution and meteorological variables to develop process-level constraints for evaluating chemistry-climate models used to project air quality responses to climate change.
► We construct records of O
3-temperature relationships over the eastern US. ► Observed O
3-temperature relationships are used to evaluate a chemistry climate model. ► The model reproduces observed summer O
3 sensitivity to temperature over the Northeast. ► We find modeled temperature biases to partially explain excess-modeled summer O
3. ► Lasting long-term measurements are needed to support process-oriented model evaluation.
Influenza infects 5-15% of the global population each year, and obesity has been shown to be an independent risk factor for increased influenza-related complications including hospitalization and ...death. However, the risk of developing influenza or influenza-like illness (ILI) in a vaccinated obese adult population has not been addressed.
This study evaluated whether obesity was associated with increased risk of influenza and ILI among vaccinated adults.
During the 2013-2014 and 2014-2015 influenza seasons, we recruited 1042 subjects to a prospective observational study of trivalent inactivated influenza vaccine (IIV3) in adults. A total of 1022 subjects completed the study. Assessments of relative risk for laboratory confirmed influenza and ILI were determined based on body mass index. Seroconversion and seroprotection rates were determined using prevaccination and 26-35 days post vaccination serum samples. Recruitment criteria for this study were adults 18 years of age and older receiving the seasonal trivalent inactivated influenza vaccine (IIV3) for the years 2013-2014 and 2014-2015. Exclusion criteria were immunosuppressive diseases, use of immunomodulatory or immunosuppressive drugs, acute febrile illness, history of Guillain-Barre syndrome, use of theophylline preparations or use of warfarin.
Among obese, 9.8% had either confirmed influenza or influenza-like-illness compared with 5.1% of healthy weight participants. Compared with vaccinated healthy weight, obese participants had double the risk of developing influenza or ILI (relative risk=2.01, 95% CI 1.12, 3.60, P=0.020). Seroconversion or seroprotection rates were not different between healthy weight and obese adults with influenza or ILI.
Despite robust serological responses, vaccinated obese adults are twice as likely to develop influenza and ILI compared with healthy weight adults. This finding challenges the current standard for correlates of protection, suggesting use of antibody titers to determine vaccine effectiveness in an obese population may provide misleading information.
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