The lockdown measures taken to prevent a rapid spreading of the coronavirus in Europe in spring 2020 led to large emission reductions, particularly in road traffic and aviation. Atmospheric concentrations of NO2 and PM2.5 were mostly reduced when compared to observations taken for the same time period in previous years; however, concentration reductions may not only be caused by emission reductions but also by specific weather situations. In order to identify the role of emission reductions and the meteorological situation for air quality improvements in central Europe, the meteorology chemistry transport model system COSMO-CLM/CMAQ was applied to Europe for the period 1 January to 30 June 2020. Emission data for 2020 were extrapolated from most recent reported emission data, and lockdown adjustment factors were computed from reported activity data changes, e.g. Google mobility reports. Meteorological factors were investigated through additional simulations with meteorological data from previous years. The results showed that lockdown effects varied significantly among countries and were most prominent for NO2 concentrations in urban areas with 2-week-average reductions up to 55 % in the second half of March. Ozone concentrations were less strongly influenced (up to ±15 %) and showed both increasing and decreasing concentrations due to lockdown measures. This depended strongly on the meteorological situation and on the NOx / VOC emission ratio. PM2.5 revealed 2 %–12 % reductions of 2-week-average concentrations in March and April, which is much less than a different weather situation could cause. Unusually low PM2.5 concentrations as observed in northern central Europe were only marginally caused by lockdown effects. The lockdown can be seen as a big experiment about air quality improvements that can be achieved through drastic traffic emission reductions. From this investigation, it can be concluded that NO2 concentrations can be largely reduced, but effects on annual average values are small when the measures last only a few weeks. Secondary pollutants like ozone and PM2.5 depend more strongly on weather conditions and show a limited response to emission changes in single sectors.

The aim of this study is to quantify the BIAS in air pollution (PM2.5, NO2) exposure estimates that arise from neglecting population activity under COVID-19 lockdown conditions. We applied mobility data as derived from different sources (Google, Eurostat, Automatic Identification System, etc.) to model the impact of (1) changing emissions and (2) the change in population activity patterns in a European multi-city (Hamburg, Liège, Marseille) exposure study. Our results show significant underestimations of exposure estimates when activity profiles are either neglected or not adjusted for lockdown conditions.

The Earth’s climate system in the twentieth century has experienced significant effects due to human-influenced factors. In this paper, we focus on the manner in which anthropogenic aerosols have radiatively forced changes in temperature and precipitation and contrast the effects with that due to the influence of well-mixed greenhouse gases. We employ the NOAA/Geophysical Fluid Dynamics Laboratory 3rd generation global climate model to simulate and derive a mechanistic understanding of the response to the forcings. We find that, over the twentieth century, anthropogenic aerosols have counteracted greenhouse gas effects to a substantial extent with regards to climate forcing, temperature and precipitation. The manner in which this comes about is traced through the effects on the atmosphere and surface heat balance, with resultant effects on the hydrologic cycle. Understanding of the twentieth century precipitation change is a prerequisite for confidence in model-based projections of the effects in the twenty-first century in response to emission scenarios of greenhouse gases and aerosols.

Corona lockdown measures caused unprecedented emission reductions in many parts of world. However, this does not linearly translate into improved air quality, since weather phenomena like precipitation, wind and solar radiation also show a significant impact on pollutant concentration patterns. The aim of this study is to disentangle effects of emission reduction and meteorology on the air quality in Central Europe during the first major lockdown from March to June 2020. For this purpose, the Community Multiscale Air Quality Modeling System (CMAQ) was used with updated emission data for the year 2020, including time profiles for sectors and countries that approximate the lockdown emission reductions. The contributions of street traffic, air traffic, ship traffic, residential heating and industry to NO2, O3 and PM2.5 concentrations were investigated. Meteorological data was derived from the regional COSMO model in CLimate Mode (COSMO-CLM). Additional city scale measurements were used to account for exceptional weather conditions as well as emission reduction effects at hotspots like traffic stations. Therefore, selected air pollutant and meteorological measurement data in the cities of Hamburg, Liége and Marseille are compared against the statistical trend of 2015 to 2019.

This repository contains annual 3D sea water age since surface contact files from a subset of simulations with GFDL's ESM4.1 climate model (Dunne et al., 2020) that were contributed to the 6th Coupled Model Intercomparison Project (CMIP6). Both the ocean model native grid and the regridded output can be found in this repository. For the regridded output, the files have been regridded from MOM6 native grid to standard World Ocean Atlas 1x1 horizontal grid, and they have been remapped from the lagrangian vertical coordinate used by GFDL's MOM6 ocean model (Adcroft et al., 2019) to standard World Ocean Atlas depths. Files have undergone QA/QC. All data files are NetCDF. Enquiries should be directed to Jasmin.John (Jasmin.John@noaa.gov) or John Dunne (John.Dunne@noaa.gov) Anyone using these data should cite Dunne et al. (2020) and Adcroft et al. (2019). See references below. Other variables associated with these simulations, along with assigned DOI's, are available through the ESGF CMIP6 portal:https://esgf-node.llnl.gov/projects/cmip6/ ______________________________________________________________________ The tar files in the repository follow this naming convention: _____.tar.gz E.g. GFDL_ESM4_CMIP6_CMIP_historical_ocean_annual_z_1x1deg_agessc.tar.gz (regridded) GFDL_ESM4_CMIP6_CMIP_historical_ocean_annual_z_agessc.tar.gz (native grid) The organization of above repository is as follows: Experiments: The concentration-forced piControl simulation: NOAA-GFDL/CMIP6/CMIP/GFDL-ESM4/ESM4_piControl_D The concentration-forced historical simulation: NOAA-GFDL/CMIP6/CMIP/GFDL-ESM4/ESM4_historical_D1 The historical simulation was spawned from year 101 of the pre-industrial control simulation For each experiment, 3D annual sea water age data can be found in the sub-directory: /ocean_annual_z_1x1deg (for regridded output) /ocean_annual_z (for native grid output) _________________________________________________________________________ NOTES: Provenance: The data provided here do not have metadata that can be used for provenance and traceability back to NOAA/GFDL. The data DOI assigned should be used when sharing and citing these data. _________________________________________________________________________

Corona lockdown measures caused unprecedented emission reductions in many parts of world. However, this does not linearly translate into improved air quality, since weather phenomena like precipitation, wind and solar radiation also show a significant impact on pollutant concentration patterns. The aim of this study is to disentangle effects of emission reduction and meteorology on the air quality in Central Europe during the first major lockdown from March to June 2020. For this purpose, the Community Multiscale Air Quality Modeling System (CMAQ) was used with updated emission data for the year 2020, including time profiles for sectors and countries that approximate the lockdown emission reductions. The contributions of street traffic, air traffic, ship traffic, residential heating and industry to NO2, O3 and PM2.5 concentrations were investigated. Meteorological data was derived from the regional COSMO model in CLimate Mode (COSMO-CLM). Additional city scale measurements were used to account for exceptional weather conditions as well as emission reduction effects at hotspots like traffic stations. Therefore, selected air pollutant and meteorological measurement data in the cities of Hamburg, Liége and Marseille are compared against the statistical trend of 2015 to 2019.

Abstract We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL—the AM4 atmosphere model, MOM6 ocean code, LM4 land model, and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0° (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1° to 0.25°. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM4 models but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM4 models.

International ship traffic is steadily increasing since many years. The associated emission of pollutants like sulphur and nitrogen compounds has strong effects on the coastal air quality and the environment. For instance, investigations of Sofiev et al. (2018) show that the ships contribute about 20 % to the sulphur dioxide and 9 % to the global emission of nitrogen oxides. Thus, shipping is also important for climate change through emissions of greenhouse gases and aerosol particles and the input of acidifying and eutrophying substances into coastal waters. The International Maritime Organization was and is on the way to implement regulations and guidelines to reduce the amount of emissions from the exhaust of ships (e.g. the Sulphur emission control area SECA for North and Batlic Sea). Moreover, new developments in ship technology and abatement measures will be developed and implemented in the next decades to support the ambitious goal of the IMO for heavy emission reductions. Therefore, our contribution aims at the quantification of ship emissions in the region of North Sea and Western Baltic Sea and the impact on the coastal ecosystem. On the one side, we focus on the recent state but on the other side we want to project the ship emissions and related pollution to future decades. Our framework is highly dependent on an accurate estimation of spatial and temporal distribution of ship emissions, which is related to ship movements and emission factors of pollutants. We utilize the HiMeMo-ship model developed at the HZG (Aulinger, 2016) and further improved during the last years. The HiMeMo-ship is a highly-flexible tool designed to calculate actual emissions and to consider also adaptation scenarios (as the MARPOL Annex VI regulation). In order to validate the results of the HZG model, we firstly present a comparison to the so-called reference inventory of the ship emission model STEAM (Jalkanen, 2012). It is shown, how robust the daily estimation of ship traffic and emissions is compared to STEAM. However, a systematic gap in CO2 and some other emissions between our model and STEAM is apparent and will be discussed in the talk, along with larger differences in some smaller areas of the Baltic Sea (complex manoeuvers and machine handling in the busy port areas). Keeping the uncertainties from ship emission estimates in mind, we utilize the atmospheric chemical transport model CMAQ to simulate the impact of ships on the concentrations of pollutants in coastal regions and the ship-related depositional flux from the air into seawater. We demonstrate under which conditions the ship emissions preferably affect the environment and how this is reduced in scenarios of future ship development and traffic.

International ship traffic is steadily increasing since many years. The associated emission of pollutants like sulphur and nitrogen compounds has strong effects on the coastal air quality and the environment. For instance, investigations of Sofiev et al. (2018) show that the ships contribute about 20 % to the sulphur dioxide and 9 % to the global emission of nitrogen oxides. Thus, shipping is also important for climate change through emissions of greenhouse gases and aerosol particles and the input of acidifying and eutrophying substances into coastal waters.Therefore, an accurate estimation of ship emissions and their spatio temporal distribution is an important key to understand and investigate coastal ecosystems. The major prerequisite is a precise record of ship movements and related pollutant emissions. In our contribution we present an intercomparison between different ship emission data models for the North and Baltic Sea region. That is the inventory of the Bundesamt für Schiffahrt und Hydrography (EMMA) and the inventory of the HZG (HiMEMO-Ship, Aulinger 2016) are compared against a reference inventory from the Finnish Meteorological institute (STEAM, Jalkanen 2012). The HiMEMO-Ship is a highly flexible tool under ongoing development and allows for temporally and spatially highly-resolved ship emission data (>=30min and >=500 m) of 9 chemical species including aerosols. The tool is designed to consider also adaptation scenarios (e.g. MARPOL Annex VI regulation).The uncertainty of the derived emissions are discussed on the basis of two means: a) a multi-parameter ensemble generated with the HZG-model and b) a multi-model ensemble using the 3 afore-mentioned approaches (“EMMA”, ”STEAM” and “HiMEMO-Ship”). The results imply that a large portion of emissions are related to ships with actually only insufficiently known characteristics, which thus cause a large range of uncertainty regarding their emission factors. Moreover, a large spread for mean NOx emissions is detected between inventories for the North Sea region. Because of complex manoeuvers and machine handling in the busy port areas, we also observe significant differences in emissions in that regions. Finally, a strategy is presented for treating the afore-mentioned issues with ship emission data in the framework of atmospheric chemistry transport modelling, i.e. deposition of pollutantsfrom the air.

Abstract We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.

We use transient GFDL‐CM3 chemistry‐climate model simulations over the 2006–2100 period to show how the influence of volcanic aerosols on the extent and timing of ozone recovery varies with (a) future greenhouse gas scenarios (Representative Concentration Pathway (RCP)4.5 and RCP8.5) and (b) halogen loading. Current understanding is that elevated volcanic aerosols reduce ozone under high halogen loading but increase ozone under low halogen loading when the chemistry is more NOx dominated. With extremely low aerosol loadings (designated here as “background”), global stratospheric ozone burden is simulated to return to 1980 levels around 2050 in the RCP8.5 scenario but remains below 1980 levels throughout the 21st century in the RCP4.5 scenario. In contrast, with elevated volcanic aerosols, ozone column recovers more quickly to 1980 levels, with recovery dates ranging from the mid‐2040s in RCP8.5 to the mid‐2050s to early 2070s in RCP4.5. The ozone response in both future emission scenarios increases with enhanced volcanic aerosols. By 2100, the 1980 baseline‐adjusted global stratospheric ozone column is projected to be 20–40% greater in RCP8.5 and 110–200% greater in RCP4.5 with elevated volcanic aerosols compared to simulations with the extremely low background aerosols. The weaker ozone enhancement at 2100 in RCP8.5 than in RCP4.5 in response to elevated volcanic aerosols is due to a factor of 2.5 greater methane in RCP8.5 compared with RCP4.5. Our results demonstrate the substantial uncertainties in stratospheric ozone projections and expected recovery dates induced by volcanic aerosol perturbations that need to be considered in future model ozone projections.

This article reports on the accuracy in aerosol‐ and cloud‐free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present‐day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present‐day conditions is essentially unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. A dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.