Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.Assessments from the Russian ship-based campaign were performed with the support of RFBR project no. 20-55-12001 and according to the development program of the Interdisciplinary Scientific and Educational School of M.V. Lomonosov Moscow State University “Future Planet and Global Environmental Change”. Development of the methodology for aethalometric data treatment was supported by RSF project no. 19-77-30004. The BC observations on R/V Mirai were supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (Arctic Challenge for Sustainability (ArCS) project). Contributions by SMHI were funded by the Swedish Environmental Protection Agency under contract NV-03174-20 and the Swedish Climate and Clean Air Research program (SCAC) as well as partly by the Swedish National Space Board (NORD-SLCP, grant agreement ID: 94/16) and the EU Horizon 2020 project Integrated Arctic Observing System (INTAROS, grant agreement ID: 727890). Work on ACE-FTS analysis was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC). Julia Schmale received funding from the Swiss National Science Foundation (project no. 200021_188478). Duncan Watson-Parris received funding from NERC projects NE/P013406/1 (A-CURE) and NE/S005390/1 (ACRUISE) as well as funding from the European Union's Horizon 2020 research and innovation program iMIRACLI under Marie Skłodowska-Curie grant agreement no. 860100. LATMOS has been supported by the EU iCUPE (Integrating and Comprehensive Understanding on Polar Environments) project (grant agreement no. 689443) under the European Network for Observing our Changing Planet (ERA-Planet), as well as access to IDRIS HPC resources (GENCI allocation A009017141) and the IPSL mesoscale computing center (CICLAD: Calcul Intensif pour le CLimat, l’Atmosphère et la Dynamique) for model simulations. Naga Oshima was supported by the Japan Society for the Promotion of Science KAKENHI (grant nos. JP18H03363, JP18H05292, and JP21H03582), the Environment Research and Technology Development Fund (grant nos. JPMEERF20202003 and JPMEERF20205001) of the Environmental Restoration and Conservation Agency of Japan, the Arctic Challenge for Sustainability II (ArCS II) under program grant no. JPMXD1420318865, and a grant for the Global Environmental Research Coordination System from the Ministry of the Environment, Japan (MLIT1753). The research with GISS-E2.1 has been supported by the Aarhus University Interdisciplinary Centre for Climate Change (iClimate) OH fund (no. 2020-0162731), the FREYA project funded by the Nordic Council of Ministers (grant agreement nos. MST-227-00036 and MFVM-2019-13476), and the EVAM-SLCF funded by the Danish Environmental Agency (grant agreement no. MST-112-00298). Jesper Christensen (for DEHM model) received funding from the Danish Environmental Protection Agency (DANCEA funds for Environmental Support to the Arctic Region project; grant no. 2019-7975). Maria Sand has been supported by the Research Council of Norway (grant 315195, ACCEPT).Peer Reviewed"Article signat per més de 50 autors/es: Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons "Postprint (published version

Evaluating modelled tropospheric columns of CH4_4 , CO, and O3_3 in the Arctic using ground-based Fourier transform infrared (FTIR) measurements

This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM- MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH$_4$, −21 % for CO, and −18 % for O$_3$. Results for CH$_4$ are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O$_3$ has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons

HTAP3 fires: towards a multi-model, multi-pollutant study of fire impacts

Open biomass burning has major impacts globally and regionally on atmospheric composition. Fire emissions include particulate matter, tropospheric ozone precursors, greenhouse gases, as well as persistent organic pollutants, mercury and other metals. Fire frequency, intensity, duration, and location are changing as the climate warms, and modelling these fires and their impacts is becoming more and more critical to inform climate adaptation and mitigation, as well as land management. Indeed, the air pollution from fires can reverse the progress made by emission controls on industry and transportation. At the same time, nearly all aspects of fire modelling – such as emissions, plume injection height, long-range transport, and plume chemistry – are highly uncertain. This paper outlines a multi-model, multi-pollutant, multi-regional study to improve the understanding of the uncertainties and variability in fire atmospheric science, models, and fires’ impacts, in addition to providing quantitative estimates of the air pollution and radiative impacts of biomass burning. Coordinated under the auspices of the Task Force on Hemispheric Transport of Air Pollution, the international atmospheric modelling and fire science communities are working towards the common goal of improving global fire modelling and using this multi-model experiment to provide estimates of fire pollution for impact studies. This paper outlines the research needs, opportunities, and options for the fire-focused multi-model experiments and provides guidance for these modelling experiments, outputs, and analysis that are to be pursued over the next 3 to 5 years. It proposes a plan for delivering specific products at key points over this period to meet important milestones relevant to science and policy audiences

Using Ground-Based Fourier TransformInfrared Spectroscopy to Evaluate Model Concentrations of Short-Lived Climate Forcers

International audienceThis work presents an evaluation of modeled atmospheric concentrations of O3, CO and CH4 from eleven models, as presented in the most recent assessment report by the Arctic Monitoring and Assessment Programme (AMAP) on short-lived climate forcers. AMAP is a scientific working group that was created to advise the Arctic Council on matters of Arctic pollution, climate change and the associated threats to local ecosystems and health. This framework is then used to inform policy and decision making through science-based assessments. The current report focuses on the impacts of Short-Lived Climate Forcers (SLCFs) on the Arctic climate, atmospheric chemistry, and human health. The report presents model-measurement comparisons to assess the performance of atmospheric modelling of SLCFs in the Arctic for the years 2008, 2009, 2014 and 2015. The 3-hourly mixing ratios of select SLCFs and related gases are modelled by CESM, CMAM, DEHM, EMEP-MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1 and WRF-Chem. This presentation will compare these outputs to corresponding trace gas measurements from ground-based Fourier Transform Infrared (FTIR) spectrometers. The FTIR instruments used are part of the Network for the Detection of Atmospheric Composition Change (NDACC) Infrared Working Group, with emphasis on results from the Canadian High Arctic site at the Polar Environment Atmospheric Research Laboratory, in Eureka, Nunavut (80.05ºN, 86.42ºW). Analyses are performed by converting model outputs into smoothed partial columns of O3, CO and CH4, at the locations of the FTIR instruments. Comparisons include seasonal cycle analysis, percent differences and regression analysis

Using Ground-Based Fourier TransformInfrared Spectroscopy to Evaluate Model Concentrations of Short-Lived Climate Forcers

International audienceThis work presents an evaluation of modeled atmospheric concentrations of O3, CO and CH4 from eleven models, as presented in the most recent assessment report by the Arctic Monitoring and Assessment Programme (AMAP) on short-lived climate forcers. AMAP is a scientific working group that was created to advise the Arctic Council on matters of Arctic pollution, climate change and the associated threats to local ecosystems and health. This framework is then used to inform policy and decision making through science-based assessments. The current report focuses on the impacts of Short-Lived Climate Forcers (SLCFs) on the Arctic climate, atmospheric chemistry, and human health. The report presents model-measurement comparisons to assess the performance of atmospheric modelling of SLCFs in the Arctic for the years 2008, 2009, 2014 and 2015. The 3-hourly mixing ratios of select SLCFs and related gases are modelled by CESM, CMAM, DEHM, EMEP-MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1 and WRF-Chem. This presentation will compare these outputs to corresponding trace gas measurements from ground-based Fourier Transform Infrared (FTIR) spectrometers. The FTIR instruments used are part of the Network for the Detection of Atmospheric Composition Change (NDACC) Infrared Working Group, with emphasis on results from the Canadian High Arctic site at the Polar Environment Atmospheric Research Laboratory, in Eureka, Nunavut (80.05ºN, 86.42ºW). Analyses are performed by converting model outputs into smoothed partial columns of O3, CO and CH4, at the locations of the FTIR instruments. Comparisons include seasonal cycle analysis, percent differences and regression analysis

Validation of Short-Lived Climate Forcer Modelling by Ground-Based Near-Infrared Fourier Transform Spectroscopy

International audienceThe Arctic Monitoring and Assessment Programme (AMAP), a working group of the Arctic Council, studies and documents the effects of climate change and pollution on Arctic climate, with the intent of informing policy recommendations. One subject of interest is the impact of Short-Lived Climate Forcers (SLCFs), atmospheric components with lifetimes shorter than that of carbon dioxide; the 2021 AMAP Assessment Report is focused on the climate and health effects of SLCFs in the Arctic and globally. AMAP uses multiple models to determine levels of SLCFs in the Arctic. These models include CESM, CMAM, DEHM, EMEP-MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem. This work compares outputs from these models for carbon monoxide and, where possible, methane, to data from ground-based Fourier Transform Infrared (FTIR) Spectrometers focused on the near-infrared spectral region. These spectrometers are part of the Total Carbon Column Observing Network (TCCON) and are located in Eureka (Nunavut, Canada), Ny Ålesund (Spitzbergen, Norway), and Sodankylä (Finland). The model outputs are mixing ratios given at three-hour intervals for the years 2009, 2014 and 2015; these are transformed as necessary to be compared to the TCCON column-averaged dry air mole fraction (Xgas) data product. TCCON has been used for many validation studies in the past and these stations in particular provide an essential high Arctic data set with very low site-to-site bias. We will assess the ability of the AMAP models to simulate high Arctic CO and CH4 in order to better understand their suitability to inform SLCF policies

Validation of Short-Lived Climate Forcer Modelling by Ground-Based Near-Infrared Fourier Transform Spectroscopy

International audienceThe Arctic Monitoring and Assessment Programme (AMAP), a working group of the Arctic Council, studies and documents the effects of climate change and pollution on Arctic climate, with the intent of informing policy recommendations. One subject of interest is the impact of Short-Lived Climate Forcers (SLCFs), atmospheric components with lifetimes shorter than that of carbon dioxide; the 2021 AMAP Assessment Report is focused on the climate and health effects of SLCFs in the Arctic and globally. AMAP uses multiple models to determine levels of SLCFs in the Arctic. These models include CESM, CMAM, DEHM, EMEP-MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem. This work compares outputs from these models for carbon monoxide and, where possible, methane, to data from ground-based Fourier Transform Infrared (FTIR) Spectrometers focused on the near-infrared spectral region. These spectrometers are part of the Total Carbon Column Observing Network (TCCON) and are located in Eureka (Nunavut, Canada), Ny Ålesund (Spitzbergen, Norway), and Sodankylä (Finland). The model outputs are mixing ratios given at three-hour intervals for the years 2009, 2014 and 2015; these are transformed as necessary to be compared to the TCCON column-averaged dry air mole fraction (Xgas) data product. TCCON has been used for many validation studies in the past and these stations in particular provide an essential high Arctic data set with very low site-to-site bias. We will assess the ability of the AMAP models to simulate high Arctic CO and CH4 in order to better understand their suitability to inform SLCF policies

Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model

The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In order to study the effects of atmospheric aerosols in this warming, recent past (1990-2014) and future (2015-2050) simulations have been carried out using the GISS-E2.1 Earth system model to study the aerosol burdens and their radiative and climate impacts over the Arctic (> 60 degrees N), using anthropogenic emissions from the Eclipse V6b and the Coupled Model Inter-comparison Project Phase 6 (CMIP6) databases, while global annual mean greenhouse gas concentrations were prescribed and kept fixed in all simulations. Results showed that the simulations have underestimated observed surface aerosol levels, in particular black carbon (BC) and sulfate (SO42-), by more than 50 %, with the smallest biases calculated for the atmosphere-only simulations, where winds are nudged to reanalysis data. CMIP6 simulations performed slightly better in reproducing the observed surface aerosol concentrations and climate parameters, compared to the Eclipse simulations. In addition, simulations where atmosphere and ocean are fully coupled had slightly smaller biases in aerosol levels compared to atmosphere-only simulations without nudging. Arctic BC, organic aerosol (OA), and SO(4)(2-)burdens decrease significantly in all simulations by 10 %-60% following the reductions of 7 %-78% in emission projections, with the Eclipse ensemble showing larger reductions in Arctic aerosol burdens compared to the CMIP6 ensemble. For the 2030-2050 period, the Eclipse ensemble simulated a radiative forcing due to aerosol-radiation interactions (RFARI) of -0.39 +/- 0.01Wm(-2), which is -0.08Wm(-2) larger than the 1990-2010 mean forcing (-0.32Wm(-2)), of which -0.24 +/- 0.01Wm(-2) was attributed to the anthropogenic aerosols. The CMIP6 ensemble simulated a RFARI of --0.35 to -0.40Wm(-2) for the same period, which is -0.01 to -0.06Wm(-2) larger than the 1990-2010 mean forcing of 0.35Wm(-2). The scenarios with little to no mitigation (worst-case scenarios) led to very small changes in the RFARI, while scenarios with medium to large emission mitigations led to increases in the negative RFARI, mainly due to the decrease in the positive BC forcing and the decrease in the negative SO42- forcing. The anthropogenic aerosols accounted for -0.24 to -0.26Wm(-2) of the net RFARI in 2030-2050 period, in Eclipse and CMIP6 ensembles, respectively. Finally, all simulations showed an increase in the Arctic surface air temperatures throughout the simulation period. By 2050, surface air temperatures are projected to increase by 2.4 to 2.6 degrees C in the Eclipse ensemble and 1.9 to 2.6 degrees C in the CMIP6 ensemble, compared to the 1990-2010 mean. Overall, results show that even the scenarios with largest emission reductions leads to similar impact on the future Arctic surface air temperatures and sea-ice extent compared to scenarios with smaller emission reductions, implying reductions of greenhouse emissions are still necessary to mitigate climate change

Clean air policies are key for successfully mitigating Arctic warming

A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air pollutants and greenhouse gases to assess climate and human health co-benefits of emissions reductions. Fossil fuel use is projected to rapidly decline in an increasingly sustainable world, resulting in far-reaching air quality benefits. Despite human health benefits, reductions in sulfur emissions in a more sustainable world could enhance Arctic warming by 0.8 °C in 2050 relative to the 1995–2014, thereby offsetting climate benefits of greenhouse gas reductions. Targeted and technically feasible emissions reduction opportunities exist for achieving simultaneous climate and human health co-benefits. It would be particularly beneficial to unlock a newly identified mitigation potential for carbon particulate matter, yielding Arctic climate benefits equivalent to those from carbon dioxide reductions by 2050

Evaluating modelled tropospheric columns of CH4, CO, and O3 in the Arctic using ground-based Fourier transform infrared (FTIR) measurements

International audienceThis study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons pre- sented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM- MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and min- imum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons