Suchergebnisse

George V. Voulgarakis is minister of public order of Greece.

This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the NMMB/BSC Chemical Transport Model (NMMB/BSC-CTM), an online chemical weather prediction system conceived for both the regional and the global scale. We provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (RMSE below 9 μg m−3). The modeled vertical distribution of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modelled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O3) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O3 and its vertical distribution. However, the model tends to overestimate O3 throughout the troposphere in several stations. This is attributed to an overestimation of CO concentration over the southern hemisphere leading to an excessive production of O3. Overall, O3 correlations range between 0.6 to 0.8 for daily mean values. The overall performance of the NMMB/BSC-CTM is comparable to that of other state-of-the-art global chemical transport models. ; The authors wish to thank WOUDC, GAW, EMEP, WDCGG, CASTNET-EPA, NADP and EANET for the provision of measurement stations. Also, thanks go to the free use of the MOPITT CO data obtained from the NASA Langley Research Center Atmospheric Science Data Center. SCIAMACHY radiances have been provided by ESA. This work is funded by grants CGL2013-46736-R, Supercomputación and e-ciencia Project (CSD2007-0050) from the Consolider-Ingenio 2010 program of the Spanish Ministry of Economy and Competitiveness. Further support was provided by the SEV-2011-00067 grant of the Severo Ochoa Program, awarded by the Spanish Government. A.H. received funding from the Earth System Science Research School (ESSReS), an initiative of the Helmholtz Association of German research centres (HGF) at the AlfredWegener Institute for Polar and Marine Research. All the numerical simulations were performed with the MareNostrum Supercomputer hosted by the Barcelona Supercomputing Center. We also thank Beatriz Monge-Sanz for providing the COPCAT coefficients. ; Peer Reviewed ; Postprint (author's final draft)

This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the NMMB/BSC Chemical Transport Model (NMMB/BSC-CTM), an online chemical weather prediction system conceived for both the regional and the global scale. We provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (RMSE below 9 μg m−3). The modeled vertical distribution of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modelled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O3) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O3 and its vertical distribution. However, the model tends to overestimate O3 throughout the troposphere in several stations. This is attributed to an overestimation of CO concentration over the southern hemisphere leading to an excessive production of O3. Overall, O3 correlations range between 0.6 to 0.8 for daily mean values. The overall performance of the NMMB/BSC-CTM is comparable to that of other state-of-the-art global chemical transport models. ; The authors wish to thank WOUDC, GAW, EMEP, WDCGG, CASTNET-EPA, NADP and EANET for the provision of measurement stations. Also, thanks go to the free use of the MOPITT CO data obtained from the NASA Langley Research Center Atmospheric Science Data Center. SCIAMACHY radiances have been provided by ESA. This work is funded by grants CGL2013-46736-R, Supercomputación and e-ciencia Project (CSD2007-0050) from the Consolider-Ingenio 2010 program of the Spanish Ministry of Economy and Competitiveness. Further support was provided by the SEV-2011-00067 grant of the Severo Ochoa Program, awarded by the Spanish Government. A.H. received funding from the Earth System Science Research School (ESSReS), an initiative of the Helmholtz Association of German research centres (HGF) at the AlfredWegener Institute for Polar and Marine Research. All the numerical simulations were performed with the MareNostrum Supercomputer hosted by the Barcelona Supercomputing Center. We also thank Beatriz Monge-Sanz for providing the COPCAT coefficients. ; Peer Reviewed ; Postprint (author's final draft)

This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH), formerly known as NMMB/BSC-CTM, that can be run on both regional and global domains. Here, we provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. We note that in this study, we omitted aerosol processes and some natural emissions (lightning and volcano emissions). The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (root mean square error – RMSE – below 5 ppb). The modeled vertical distributions of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August, probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modeled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O3) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O3 and its vertical distribution. However, the model tends to overestimate O3 throughout the troposphere in several stations. This may be attributed to an overestimation of CO concentration over the Southern Hemisphere leading to an excessive production of O3 or to the lack of specific chemistry (e.g., halogen chemistry, aerosol chemistry). Overall, O3 correlations range between 0.6 and 0.8 for daily mean values. The overall performance of the NMMB-MONARCH is comparable to that of other state-of-the-art global chemistry models. ; The authors wish to thank WOUDC, GAW, EMEP, WDCGG, CASTNET-EPA, NADP and EANET for the provision of measurement stations. The authors acknowledge for the strong support of the European Commission, Airbus, and the Airlines (Lufthansa, Austrian, Air France) who carry free of charge the MOZAIC equipment and perform the maintenance since 1994. MOZAIC is presently funded by INSU-CNRS (France), Meteo-France, and Forschungszentrum (FZJ, Julich, Germany). The MOZAIC database is supported by ETHER (CNES and INSU-CNRS). Also, thanks go to the free use of the MOPITTCO data obtained from the NASA Langley Research Center Atmospheric Science Data Center. SCIAMACHY radiances have been provided by ESA. We also thank Beatriz Monge-Sanz for providing the COPCAT coefficients. This work is funded by grants CGL2013-46736-R, Supercomputación and e-ciencia Project (CSD2007-0050) from the Consolider-Ingenio 2010 program of the Spanish Ministry of Economy and Competitiveness. Further support was provided by the SEV-2011-00067 grant of the Severo Ochoa Program, awarded by the Spanish Government. Andreas Hilboll received funding from the Earth System Science Research School (ESSReS), an initiative of the Helmholtz Association of German research centres (HGF) at the Alfred Wegener Institute for Polar and Marine Research. Carlos Pérez García-Pando acknowledges long-term support from the AXA Research Fund. The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2015-1-0007). Comments from two anonymous reviewers are gratefully acknowledge. ; Peer Reviewed ; Postprint (published version)

This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH), formerly known as NMMB/BSC-CTM, that can be run on both regional and global domains. Here, we provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. We note that in this study, we omitted aerosol processes and some natural emissions (lightning and volcano emissions). The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (root mean square error – RMSE – below 5 ppb). The modeled vertical distributions of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August, probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modeled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O3) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O3 and its vertical distribution. However, the model tends to overestimate O3 throughout the troposphere in several stations. This may be attributed to an overestimation of CO concentration over the Southern Hemisphere leading to an excessive production of O3 or to the lack of specific chemistry (e.g., halogen chemistry, aerosol chemistry). Overall, O3 correlations range between 0.6 and 0.8 for daily mean values. The overall performance of the NMMB-MONARCH is comparable to that of other state-of-the-art global chemistry models. ; The authors wish to thank WOUDC, GAW, EMEP, WDCGG, CASTNET-EPA, NADP and EANET for the provision of measurement stations. The authors acknowledge for the strong support of the European Commission, Airbus, and the Airlines (Lufthansa, Austrian, Air France) who carry free of charge the MOZAIC equipment and perform the maintenance since 1994. MOZAIC is presently funded by INSU-CNRS (France), Meteo-France, and Forschungszentrum (FZJ, Julich, Germany). The MOZAIC database is supported by ETHER (CNES and INSU-CNRS). Also, thanks go to the free use of the MOPITTCO data obtained from the NASA Langley Research Center Atmospheric Science Data Center. SCIAMACHY radiances have been provided by ESA. We also thank Beatriz Monge-Sanz for providing the COPCAT coefficients. This work is funded by grants CGL2013-46736-R, Supercomputación and e-ciencia Project (CSD2007-0050) from the Consolider-Ingenio 2010 program of the Spanish Ministry of Economy and Competitiveness. Further support was provided by the SEV-2011-00067 grant of the Severo Ochoa Program, awarded by the Spanish Government. Andreas Hilboll received funding from the Earth System Science Research School (ESSReS), an initiative of the Helmholtz Association of German research centres (HGF) at the Alfred Wegener Institute for Polar and Marine Research. Carlos Pérez García-Pando acknowledges long-term support from the AXA Research Fund. The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2015-1-0007). Comments from two anonymous reviewers are gratefully acknowledge. ; Peer Reviewed ; Postprint (published version)

Past changes in global industrial aerosol emissions have played a significant role in historical shifts in African rainfall, and yet assessment of the impact on African rainfall of near-term (10–40 yr) potential aerosol emission pathways remains largely unexplored. While existing literature links future aerosol declines to a northward shift of Sahel rainfall, existing climate projections rely on RCP scenarios that do not explore the range of air quality drivers. Here we present projections from two emission scenarios that better envelop the range of potential aerosol emissions. More aggressive emission cuts result in northward shifts of the tropical rainbands whose signal can emerge from expected internal variability on short, 10–20-yr time horizons. We also show for the first time that this northward shift also impacts East Africa, with evidence of delays to both onset and withdrawal of the short rains. However, comparisons of rainfall impacts across models suggest that only certain aspects of both the West and East African model responses may be robust, given model uncertainties. This work motivates the need for wider exploration of air quality scenarios in the climate science community to assess the robustness of these projected changes and to provide evidence to underpin climate adaptation in Africa. In particular, revised estimates of emission impacts of legislated measures every 5–10 years would have a value in providing near-term climate adaptation information for African stakeholders.

Past changes in global industrial aerosol emissions have played a significant role in historical shifts in African rainfall and yet assessment of the impact on African rainfall of near term (10-40 year) potential aerosol emission pathways remains largely unexplored. Whilst existing literature links future aerosol declines to a northward shift of Sahel rainfall, existing climate projections rely on RCP scenarios that do not explore the range of air quality drivers. Here we present projections from two emission scenarios that better envelope the range of potential aerosol emissions. More aggressive emission cuts results in northward shifts of the tropical rain-bands whose signal can emerge from expected internal variability on short, 10-20 year, time horizons. We also show for the first time that this northward shift also impacts East Africa, with evidence of delays to both onset and withdrawal of the Short Rains. However, comparisons of rainfall impacts across models suggest that only certain aspects of both the West and East African model responses may be robust, given model uncertainties. This work motivates the need for wider exploration of air quality scenarios in the climate science community to assess the robustness of these projected changes and to provide evidence to underpin climate adaptation in Africa. In particular, revised estimates of emission impacts of legislated measures every 5-10 years would have a value in providing near term climate adaptation information for African stakeholders.

This is the final version. Available on open access from the European Geosciences Union via the DOI in this record ; Code and data availability. The benchmarking code is archived at https://zenodo.org/record/3879161#.Xtq-py-z2fU (last access: 5 June 2020) (https://doi.org/10.5281/zenodo.3879161, Kelley, 2020), which also contains the code to produce the figures presented here. The FireMIP model output is archived at https://zenodo.org/record/3555562#.Xell3C2ZOcY (last access: 22 November 2019) (https://doi.org/10.5281/zenodo.3555562, Hantson et al., 2019). Data availability for each reference dataset is provided in Table A1. ; Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle and to infer relationships between climate, land use and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation of how well different models represent various aspects of fire regimes. The Fire Model Intercomparison Project (FireMIP) is coordinating the evaluation of state-of-the-art global fire models, in order to improve projections of fire characteristics and fire impacts on ecosystems and human societies in the context of global environmental change. Here we perform a systematic evaluation of historical simulations made by nine FireMIP models to quantify their ability to reproduce a range of fire and vegetation benchmarks. The FireMIP models simulate a wide range in global annual total burnt area (39–536 Mha) and global annual fire carbon emission (0.91–4.75 Pg C yr−1) for modern conditions (2002–2012), but most of the range in burnt area is within observational uncertainty (345–468 Mha). Benchmarking scores indicate that seven out of nine FireMIP models are able to represent the spatial pattern in burnt area. The models also reproduce the seasonality in burnt area reasonably well but struggle to simulate fire season length and are largely unable to represent interannual variations in burnt area. However, models that represent cropland fires see improved simulation of fire seasonality in the Northern Hemisphere. The three FireMIP models which explicitly simulate individual fires are able to reproduce the spatial pattern in number of fires, but fire sizes are too small in key regions, and this results in an underestimation of burnt area. The correct representation of spatial and seasonal patterns in vegetation appears to correlate with a better representation of burnt area. The two older fire models included in the FireMIP ensemble (LPJ–GUESS–GlobFIRM, MC2) clearly perform less well globally than other models, but it is difficult to distinguish between the remaining ensemble members; some of these models are better at representing certain aspects of the fire regime; none clearly outperforms all other models across the full range of variables assessed. ; European Union FP7 ; German Federal Ministry of Education and Research (BMBF) ; European Research Council (ERC) ; Natural Environment Research Council (NERC) ; Deutsche Forschungsgemeinschaft (DFG) ; National Natural Science Foundation of China ; Strategic Research Area MERGE (ModElling the Regional and Global Earth system) ; Lund University Centre for Studies of Carbon Cycle and Climate Interactions (LUCCI)

This is the author accepted manuscript. The final version is available from EGU via the DOI in this record. ; The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over 2 decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. In this paper, we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. We have also created supplementary tables that describe, in thorough mathematical detail, the structure of each model. ; S. Rabin was supported by a National Science Foundation Graduate Research Fellowship and by the Carbon Mitigation Initiative, and along with S. Hantson and A. Arneth would like to acknowledge support by the EU FP7 projects BACCHUS (grant agreement no. 603445) and LUC4C (grant agreement no. 603542). This work was supported, in part, by the German Federal Ministry of Education and Research (BMBF), through the Helmholtz Association and its research programme ATMO, and the HGF Impulse and Networking 5 fund. F. Li was funded by the National Natural Science Foundation of China under Grant No. 41475099 and the CAS Youth Innovation Promotion Association Fellowship. The UK Met Office contribution was funded by BEIS under the Hadley Centre Climate Programme contract (GA01101). G. A. Folberth also wishes to acknowledge funding received from the European Union's Horizon 2020 research and innovation programme under grant agreement No 641816 (CRESCENDO). J. O. Kaplan was supported by the European Research Council (COEVOLVE, 313797).

The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over two decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. Here we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. The works published in this journal are distributed under the Creative Commons Attribution 3.0 License. This license does not affect the Crown copy-right work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 3.0 License and the OGL are interoperable and do not conflict with, reduce, or limit each other.