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  • 1
    Publication Date: 2020-01-01
    Print ISSN: 1352-2310
    Electronic ISSN: 1873-2844
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geosciences , Physics
    Published by Elsevier
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  • 2
    Publication Date: 2017-05-05
    Description: This case study explores the potential for chemical state analysis at extratropical upper tropospheric – lower stratospheric (Ex-UTLS) height levels with airborne limb-images, assimilated into an advanced spatio-temporal system. The investigation is motivated by the limited capability of both, nadir- and limb-viewing satellite sensors to resolve highly filamented structures, delineated by sharp trace gas gradients on small horizontal and vertical scales. The EURAD-IM (EURopean Air pollution Dispersion – Inverse Model) is applied as assimilation system and designed to extend the flight path confined retrievals from GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) to both, larger areas and detailed vertical structures by a tomographic flight pattern. Related potential and limitations of the method are studied with the following features applied: (i) airborne limb-imaging observations of the Ex-UTLS, (ii) spatio-temporal extension by 4-dimensional variational data assimilation, (iii) correlation between ozone and potential vorticity (PV) as an indicator of airmasses and (iv) anisotropic and inhomogeneous horizontal background error correlations in the Ex-UTLS, spreading information towards unobserved regions along PV isopleths. This setup demonstrated substantial improvements to basic approaches in exploring new data on the spatial extend and alignment of airmasses down to small-scale filaments in the Ex-UTLS. Tomographic observations provide detailed insight for reconstructing filamentary foldings along airmass boundaries above the tropopause during this case study.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
    Publication Date: 2021-03-17
    Description: Forecasts of biogenic trace gases in the planetary boundary layer (PBL) are highly affected by simulated emission and transport processes. The Po region during the PEGASOS campaign in summer 2012 provides challenging, yet common, conditions for simulating biogenic gases in the PBL. This study identifies and quantifies principal sources of forecast uncertainties induced by various model configurations under these conditions. Specifically, the effects of model configuration on different processes affecting atmospheric distributions of biogenic trace gas distributions are analyzed based on a priori available information. The investigation is based on the EURopean Air pollution Dispersion – Inverse Model (EURAD-IM) chemistry transport model employing the Model for Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN 2.1) biogenic emission module and Regional Atmospheric Chemistry Mechanism – Mainz Isoprene Mechanism (RACM-MIM) as the gas phase chemistry mechanism. Two major sources of forecast uncertainties are identified in this study. Firstly, biogenic emissions appear to be exceptionally sensitive to land surface properties inducing total variations in local concentrations of up to 1 order of magnitude. Moreover, these sensitivities are found to be highly similar for different gases and almost constant during the campaign, varying only diurnally. Secondly, the model configuration also highly influences regional flow patterns with significant effects on pollutant transport and mixing. This effect was corroborated by diverging source regions of a representative air mass and thus applies also to non-biogenic gases. As a result, large sensitivities to model configuration are found for surface concentrations of isoprene, as well as OH, affecting reactive atmospheric chemistry. Especially in areas with small-scale emission patterns, changes in the model configuration are able to induce significantly different local concentrations. The amount and complexity of sensitivities found in this study demonstrate the need to consider forecast uncertainties in chemical transport models with a special focus on biogenic emissions and pollutant transport.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
    Publication Date: 2021-09-10
    Description: Atmospheric chemical forecasts heavily rely on various model parameters, which are often insufficiently known, such as emission rates and deposition velocities. However, a reliable estimation of resulting uncertainties with an ensemble of forecasts is impaired by the high dimensionality of the system. This study presents a novel approach, which substitutes the problem into a low-dimensional subspace spanned by the leading uncertainties. It is based on the idea that the forecast model acts as a dynamical system inducing multivariate correlations of model uncertainties. This enables an efficient perturbation of high-dimensional model parameters according to their leading coupled uncertainties. The specific algorithm presented in this study is designed for parameters that depend on local environmental conditions and consists of three major steps: (1) an efficient assessment of various sources of model uncertainties spanned by independent sensitivities, (2) an efficient extraction of leading coupled uncertainties using eigenmode decomposition, and (3) an efficient generation of perturbations for high-dimensional parameter fields by the Karhunen–Loéve expansion. Due to their perceived simulation challenge, the method has been applied to biogenic emissions of five trace gases, considering state-dependent sensitivities to local atmospheric and terrestrial conditions. Rapidly decreasing eigenvalues state that highly correlated uncertainties of regional biogenic emissions can be represented by a low number of dominant components. Depending on the required level of detail, leading parameter uncertainties with dimensions of ?(106) can be represented by a low number of about 10 ensemble members. This demonstrates the suitability of the algorithm for efficient ensemble generation for high-dimensional atmospheric chemical parameters.
    Print ISSN: 1991-959X
    Electronic ISSN: 1991-9603
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 5
    Publication Date: 2023-01-24
    Description: Despite the implication of aerosols for the radiation budget, there are persistent differences in data for the aerosol optical depth (τ) for 1998–2019. This study presents a comprehensive evaluation of the large-scale spatio-temporal patterns of mid-visible τ from modern data sets. In total, we assessed 94 different global data sets from eight satellite retrievals, four aerosol-climate model ensembles, one operational ensemble product, two reanalyses, one climatology and one merged satellite product. We include the new satellite data SLSTR and aerosol-climate simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Aerosol Comparisons between Observations and Models Phase 3 (AeroCom-III). Our intercomparison highlights model differences and observational uncertainty. Spatial mean τ for 60°N – 60°S ranges from 0.124 to 0.164 for individual satellites, with a mean of 0.14. Averaged τ from aerosol-climate model ensembles fall within this satellite range, but individual models do not. Our assessment suggests no systematic improvement compared to CMIP5 and AeroCom-I. Although some regional biases have been reduced, τ from both CMIP6 and AeroCom-III are for instance substantially larger along extra-tropical storm tracks compared to the satellite products. The considerable uncertainty in observed τ implies that a model evaluation based on a single satellite product might draw biased conclusions. This underlines the need for continued efforts to improve both model and satellite estimates of τ, for example, through measurement campaigns in areas of particularly uncertain satellite estimates identified in this study, to facilitate a better understanding of aerosol effects in the Earth system. Key Points: - Present-day patterns in aerosol optical depth differ substantially between 94 modern global data sets - The range in spatial means from individual satellites is −11% to +17% of the multi-satellite mean - Spatial means from climate model intercomparison projects fall within the satellite range but strong regional differences are identified
    Type: Article , PeerReviewed
    Format: text
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  • 6
    Publication Date: 2022-04-01
    Description: Despite the implication of aerosols for the radiation budget, there are persistent differences in data for the aerosol optical depth (τ) for 1998–2019. This study presents a comprehensive evaluation of the large‐scale spatio‐temporal patterns of mid‐visible τ from modern data sets. In total, we assessed 94 different global data sets from eight satellite retrievals, four aerosol‐climate model ensembles, one operational ensemble product, two reanalyses, one climatology and one merged satellite product. We include the new satellite data SLSTR and aerosol‐climate simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Aerosol Comparisons between Observations and Models Phase 3 (AeroCom‐III). Our intercomparison highlights model differences and observational uncertainty. Spatial mean τ for 60°N – 60°S ranges from 0.124 to 0.164 for individual satellites, with a mean of 0.14. Averaged τ from aerosol‐climate model ensembles fall within this satellite range, but individual models do not. Our assessment suggests no systematic improvement compared to CMIP5 and AeroCom‐I. Although some regional biases have been reduced, τ from both CMIP6 and AeroCom‐III are for instance substantially larger along extra‐tropical storm tracks compared to the satellite products. The considerable uncertainty in observed τ implies that a model evaluation based on a single satellite product might draw biased conclusions. This underlines the need for continued efforts to improve both model and satellite estimates of τ, for example, through measurement campaigns in areas of particularly uncertain satellite estimates identified in this study, to facilitate a better understanding of aerosol effects in the Earth system.
    Description: Plain Language Summary: Aerosols are known to affect atmospheric processes. For instance, particles emitted during dust storms, biomass burning and anthropogenic activities affect air quality and influence the climate through effects on solar radiation and clouds. Although many studies address such aerosol effects, there is a persistent difference in current estimates of the amount of aerosols in the atmosphere across observations and complex climate models. This study documents the data differences for aerosol amounts, including new estimates from climate‐model simulations and satellite products. We quantify considerable differences across aerosol amount estimates as well as regional and seasonal variations of extended and new data. Further, this study addresses the question to what extent complex climate models have improved over the past decades in light of observational uncertainty.
    Description: Key Points: Present‐day patterns in aerosol optical depth differ substantially between 94 modern global data sets. The range in spatial means from individual satellites is −11% to +17% of the multi‐satellite mean. Spatial means from climate model intercomparison projects fall within the satellite range but strong regional differences are identified.
    Description: Hans‐Ertel‐Center for Weather Research
    Description: Collaborative Research Centre 1211
    Description: Max‐Planck‐Institute for Meteorology
    Keywords: ddc:551.5
    Language: English
    Type: doc-type:article
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