We present multi-model global datasets of nitrogen and sulfate deposition covering time periods from 1850 to 2100, calculated within the Atmospheric Chemistry and Climate Model Intercomparison ...Project (ACCMIP). The computed deposition fluxes are compared to surface wet deposition and ice core measurements. We use a new dataset of wet deposition for 2000–2002 based on critical assessment of the quality of existing regional network data. We show that for present day (year 2000 ACCMIP time slice), the ACCMIP results perform similarly to previously published multi-model assessments. For this time slice, we find a multi-model mean deposition of approximately 50 Tg(N) yr−1 from nitrogen oxide emissions, 60 Tg(N) yr−1 from ammonia emissions, and 83 Tg(S) yr−1 from sulfur emissions. The analysis of changes between 1980 and 2000 indicates significant differences between model and measurements over the United States but less so over Europe. This difference points towards a potential misrepresentation of 1980 NH3 emissions over North America. Based on ice core records, the 1850 deposition fluxes agree well with Greenland ice cores, but the change between 1850 and 2000 seems to be overestimated in the Northern Hemisphere for both nitrogen and sulfur species. Using the Representative Concentration Pathways (RCPs) to define the projected climate and atmospheric chemistry related emissions and concentrations, we find large regional nitrogen deposition increases in 2100 in Latin America, Africa and parts of Asia under some of the scenarios considered. Increases in South Asia are especially large, and are seen in all scenarios, with 2100 values more than double their 2000 counterpart in some scenarios and reaching > 1300 mg(N) m−2 yr−1 averaged over regional to continental-scale regions in RCP 2.6 and 8.5, ~ 30–50% larger than the values in any region currently (circa 2000). However, sulfur deposition rates in 2100 are in all regions lower than in 2000 in all the RCPs. The new ACCMIP multi-model deposition dataset provides state-of-the-science, consistent and evaluated time slice (spanning 1850–2100) global gridded deposition fields for use in a wide range of climate and ecological studies.
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.
Nowadays, the assimilation of satellite observations, particularly radiances from infrared sounders, into numerical weather prediction (NWP) models plays a dominant role in improving weather ...forecasts. One of the keys to make optimal use of radiances is to simulate them with a radiative transfer model (RTM). At Météo‐France, the RTTOV RTM is used for NWP models. Currently, simulations are carried out taking into account single chemical profiles. However, neglecting the spatial and temporal variability of these gases can affect the accuracy of the simulations and thus the quality of the subsequent analyses and forecasts. To reduce the impact of this assumption on weather forecasts, we use a variational bias correction but it would be more appropriate to correct the bias directly at the source. Ozone is one of the atmospheric constituents with significant impacts on spectral radiances measured by hyperspectral infrared sounders. Thus, the objective of this paper is to replace the use of a single ozone profile with a realistic and variable ozone field in RTTOV for the simulation of infrared observation. The results show that the use of a variable ozone allows us to further reduce biases in simulation of ozone‐sensitive channels but also of channels sensitive mainly to other parameters such as CO2 for example. This has positive effects on the analyses and improves the fit of the short‐range forecasts (or analyses) to other observations such as radiosondes, microwave radiances, GNSS‐RO bending angles, etc. All of these positive impacts allow us to significantly improve weather forecasts.
Ozone is one of the atmospheric constituents with significant impacts on spectral radiances measured by hyperspectral infrared sounders. The objective of this paper is to replace the use of a single ozone profile with a realistic and variable ozone field in RTTOV for the simulation of infrared observation. The results show positive effects on analyses and allow us to better simulate other observations such as radiosondes or radiances, and to significantly improve weather forecasts.
Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative ...forcings (RFs). All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP) scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 410 mW m−2. The model range of pre-industrial to present-day changes in O3 produces a spread (±1 standard deviation) in RFs of ±17%. Three different radiation schemes were used – we find differences in RFs between schemes (for the same ozone fields) of ±10%. Applying two different tropopause definitions gives differences in RFs of ±3%. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of ±30% for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44±12%), nitrogen oxides (31 ± 9%), carbon monoxide (15 ± 3%) and non-methane volatile organic compounds (9 ± 2%); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42 mW m−2 DU−1, a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mW m−2; relative to 1750) for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) of 350, 420, 370 and 460 (in 2030), and 200, 300, 280 and 600 (in 2100). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. Climate change has relatively small impacts on global mean tropospheric ozone RF.
In this study we develop a secondary inorganic aerosol (SIA) module for the MOCAGE chemistry transport model developed at CNRM. The aim is to have a module suitable for running at different model ...resolutions and for operational applications with reasonable computing times. Based on the ISORROPIA II thermodynamic equilibrium module, the new version of the model is presented and evaluated at both the global and regional scales. The results show high concentrations of secondary inorganic aerosols in the most polluted regions: Europe, Asia and the eastern part of North America. Asia shows higher sulfate concentrations than other regions thanks to emission reductions in Europe and North America. Using two simulations, one with and the other without secondary inorganic aerosol formation, the global model outputs are compared to previous studies, to MODIS AOD retrievals, and also to in situ measurements from the HTAP database. The model shows a better agreement with MODIS AOD retrievals in all geographical regions after introducing the new SIA scheme. It also provides a good statistical agreement with in situ measurements of secondary inorganic aerosol composition: sulfate, nitrate and ammonium. In addition, the simulation with SIA generally gives a better agreement with observations for secondary inorganic aerosol precursors (nitric acid, sulfur dioxide, ammonia), in particular with a reduction of the modified normalized mean bias (MNMB). At the regional scale, over Europe, the model simulation with SIA is compared to the in situ measurements from the EMEP database and shows a good agreement with secondary inorganic aerosol composition. The results at the regional scale are consistent with those obtained from the global simulations. The AIRBASE database was used to compare the model to regulated air quality pollutants: particulate matter, ozone and nitrogen dioxide concentrations. Introduction of the SIA in MOCAGE provides a reduction in the PM2.5 MNMB of 0.44 on a yearly basis and up to 0.52 for the 3 spring months (March, April, May) when SIAs are at their maximum.
We have analysed time-slice simulations from 17 global models, participating in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), to explore changes in present-day (2000) ...hydroxyl radical (OH) concentration and methane (CH4) lifetime relative to preindustrial times (1850) and to 1980. A comparison of modeled and observation-derived methane and methyl chloroform lifetimes suggests that the present-day global multi-model mean OH concentration is overestimated by 5 to 10% but is within the range of uncertainties. The models consistently simulate higher OH concentrations in the Northern Hemisphere (NH) compared with the Southern Hemisphere (SH) for the present-day (2000; inter-hemispheric ratios of 1.13 to 1.42), in contrast to observation-based approaches which generally indicate higher OH in the SH although uncertainties are large. Evaluation of simulated carbon monoxide (CO) concentrations, the primary sink for OH, against ground-based and satellite observations suggests low biases in the NH that may contribute to the high north–south OH asymmetry in the models. The models vary widely in their regional distribution of present-day OH concentrations (up to 34%). Despite large regional changes, the multi-model global mean (mass-weighted) OH concentration changes little over the past 150 yr, due to concurrent increases in factors that enhance OH (humidity, tropospheric ozone, nitrogen oxide (NOx) emissions, and UV radiation due to decreases in stratospheric ozone), compensated by increases in OH sinks (methane abundance, carbon monoxide and non-methane volatile organic carbon (NMVOC) emissions). The large inter-model diversity in the sign and magnitude of preindustrial to present-day OH changes (ranging from a decrease of 12.7% to an increase of 14.6%) indicate that uncertainty remains in our understanding of the long-term trends in OH and methane lifetime. We show that this diversity is largely explained by the different ratio of the change in global mean tropospheric CO and NOx burdens (Delta CO/Delta NOx, approximately represents changes in OH sinks versus changes in OH sources) in the models, pointing to a need for better constraints on natural precursor emissions and on the chemical mechanisms in the current generation of chemistry-climate models. For the 1980 to 2000 period, we find that climate warming and a slight increase in mean OH (3.5 +/- 2.2%) leads to a 4.3 +/- 1.9% decrease in the methane lifetime. Analysing sensitivity simulations performed by 10 models, we find that preindustrial to present-day climate change decreased the methane lifetime by about four months, representing a negative feedback on the climate system. Further, we analysed attribution experiments performed by a subset of models relative to 2000 conditions with only one precursor at a time set to 1860 levels. We find that global mean OH increased by 46.4 +/- 12.2% in response to preindustrial to present-day anthropogenic NOx emission increases, and decreased by 17.3 +/-2.3%, 7.6 +/- 1.5%, and 3.1 +/- 3.0% due to methane burden, and anthropogenic CO, and NMVOC emissions increases, respectively.
We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model ...tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5-20 ppb) in the Southern Hemisphere (SH) and modest high bias (5-10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005-2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120mW/ sq. m OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39+/- 41mW/ sq. m relative to TES data. We show that there is a correlation (Sq. R = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750-2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100mW/ sq. m. Removing these models leads to a mean ozone radiative forcing of 394+/- 42mW/ sq. m. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 +/- 60mW/ sq. m derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.
Results from simulations performed for the Atmospheric Chemistry and Climate Modeling Intercomparison Project (ACCMIP) are analysed to examine how OH and methane lifetime may change from present day ...to the future, under different climate and emissions scenarios. Present day (2000) mean tropospheric chemical lifetime derived from the ACCMIP multi-model mean is 9.8+/-1.6 yr (9.3+/-0.9 yr when only including selected models), lower than a recent observationally-based estimate, but with a similar range to previous multi-model estimates. Future model projections are based on the four Representative Concentration Pathways (RCPs), and the results also exhibit a large range. Decreases in global methane lifetime of 4.5 +/- 9.1% are simulated for the scenario with lowest radiative forcing by 2100 (RCP 2.6), while increases of 8.5+/-10.4% are simulated for the scenario with highest radiative forcing (RCP 8.5). In this scenario, the key driver of the evolution of OH and methane lifetime is methane itself, since its concentration more than doubles by 2100 and it consumes much of the OH that exists in the troposphere. Stratospheric ozone recovery, which drives tropospheric OH decreases through photolysis modifications, also plays a partial role. In the other scenarios, where methane changes are less drastic, the interplay between various competing drivers leads to smaller and more diverse OH and methane lifetime responses, which are difficult to attribute. For all scenarios, regional OH changes are even more variable, with the most robust feature being the large decreases over the remote oceans in RCP8.5. Through a regression analysis, we suggest that differences in emissions of non-methane volatile organic compounds and in the simulation of photolysis rates may be the main factors causing the differences in simulated present day OH and methane lifetime. Diversity in predicted changes between present day and future OH was found to be associated more strongly with differences in modelled temperature and stratospheric ozone changes. Finally, through perturbation experiments we calculated an OH feedback factor (F) of 1.24 from present day conditions (1.50 from 2100 RCP8.5 conditions) and a climate feedback on methane lifetime of 0.33+-0.13 yr/K, on average. Models that did not include interactive stratospheric ozone effects on photolysis showed a stronger sensitivity to climate, as they did not account for negative effects of climate-driven stratospheric ozone recovery on tropospheric OH, which would have partly offset the overall OH/methane lifetime response to climate change.
We test the current generation of global chemistry-climate models in their ability to simulate observed, present-day surface ozone. Models are evaluated against hourly surface ozone from 4217 ...stations in North America and Europe that are averaged over 1 degree 1 degree grid cells, allowing commensurate model-measurement comparison. Models are generally biased high during all hours of the day and in all regions. Most models simulate the shape of regional summertime diurnal and annual cycles well, correctly matching the timing of hourly (~ 15:00 local time (LT)) and monthly (mid-June) peak surface ozone abundance. The amplitude of these cycles is less successfully matched. The observed summertime diurnal range (~ 25 ppb) is underestimated in all regions by about 7 ppb, and the observed seasonal range (~ 21 ppb) is underestimated by about 5 ppb except in the most polluted regions, where it is overestimated by about 5 ppb. The models generally match the pattern of the observed summertime ozone enhancement, but they overestimate its magnitude in most regions. Most models capture the observed distribution of extreme episode sizes, correctly showing that about 80 % of individual extreme events occur in large-scale, multi-day episodes of more than 100 grid cells. The models also match the observed linear relationship between episode size and a measure of episode intensity, which shows increases in ozone abundance by up to 6 ppb for larger-sized episodes. We conclude that the skill of the models evaluated here provides confidence in their projections of future surface ozone.
The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and ...2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.
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