scholarly journals Sensitivity of tropospheric ozone to halogen chemistry in the chemistry-climate model LMDZ-INCA vNMHC

2021 ◽  
Author(s):  
Cyril Caram ◽  
Sophie Szopa ◽  
Anne Cozic ◽  
Slimane Bekki ◽  
Carlos Cuevas ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
Climate Model ◽  
Chemical System ◽  
Model Studies ◽  
Halogen Chemistry ◽  
The Impact

Abstract. The atmospheric chemistry of halogenated species (Cl, Br, I) participates in the global chemical sink of tropospheric ozone and perturbs the oxidizing capacity of the troposphere, notably influencing the atmospheric lifetime of methane. Global chemistry-climate models are commonly used to assess the global budget of ozone, its sensitivity to emissions of its precursors, and to project its long-term evolution. Here, we report on the implementation of tropospheric halogens chemistry in the chemistry-climate model LMDZ-INCA and its effects on the tropospheric ozone budget. Overall, the results show that the model simulates satisfactorily the impact of halogens on the photooxidizing system in the troposphere, in particular in the marine boundary layer. To elucidate the mechanisms and quantify the effects, standard metrics representative of the behavior of the tropospheric chemical system (Ox, HOx, NOx, CH4, and NMVOCs) are computed with and without halogen chemistry. Tropospheric halogens in the LMDZ-INCA model lead to a decrease of 22 % in the ozone burden, 8 % in OH, and 33 % in NOx. Additional sensitivity simulations show that the inclusion of halogens chemistry makes ozone more sensitive to perturbations in CH4, NOx, and NMVOCs. Consistent with other global model studies, the sensitivity of the tropospheric ozone burden to changes from pre-industrial to present-day emissions is found to be ~20 % lower when tropospheric halogens are taken into account.

scholarly journals Estimating the climate significance of halogen-driven ozone loss in the tropical marine troposphere

2011 ◽  
Vol 11 (12) ◽  
pp. 32003-32029 ◽  
Author(s):  
A. Saiz-Lopez ◽  
J.-F. Lamarque ◽  
D. E. Kinnison ◽  
S. Tilmes ◽  
C. Ordóñez ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Climate Models ◽  
Climate Model ◽  
Radiative Balance ◽  
Ozone Loss ◽  
Tropical Tropopause ◽  
Background Ozone ◽  
Halogen Chemistry ◽  
Marine Troposphere

Abstract. We have integrated observations of tropospheric ozone, very short-lived (VSL) halocarbons and reactive iodine and bromine species from a wide variety of tropical data sources with the global CAM-Chem chemistry-climate model and offline radiative transfer calculations to compute the contribution of halogen chemistry to ozone loss and associated radiative impact in the tropical marine troposphere. The inclusion of tropospheric halogen chemistry in CAM-Chem leads to an annually averaged depletion of around 10% (~2.5 Dobson units) of the tropical tropospheric ozone column, with largest effects in the middle to upper troposphere.This depletion contributes approximately −0.10 W m−2 to the radiative flux at the tropical tropopause. This negative flux is of similar magnitude to the ~0.33 W m−2 contribution of tropospheric ozone to present-day radiative balance as recently estimated from satellite observations. We find that the implementation of oceanic halogen sources and chemistry in climate models is an important component of the natural background ozone budget and we suggest that it needs to be considered when estimating both preindustrial ozone baseline levels and long term changes in tropospheric ozone.

scholarly journals Estimating the climate significance of halogen-driven ozone loss in the tropical marine troposphere

2012 ◽  
Vol 12 (9) ◽  
pp. 3939-3949 ◽  
Author(s):  
A. Saiz-Lopez ◽  
J.-F. Lamarque ◽  
D. E. Kinnison ◽  
S. Tilmes ◽  
C. Ordóñez ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Climate Models ◽  
Climate Model ◽  
Radiative Balance ◽  
Ozone Loss ◽  
Tropical Tropopause ◽  
Background Ozone ◽  
Halogen Chemistry ◽  
Marine Troposphere

Abstract. We have integrated observations of tropospheric ozone, very short-lived (VSL) halocarbons and reactive iodine and bromine species from a wide variety of tropical data sources with the global CAM-Chem chemistry-climate model and offline radiative transfer calculations to compute the contribution of halogen chemistry to ozone loss and associated radiative impact in the tropical marine troposphere. The inclusion of tropospheric halogen chemistry in CAM-Chem leads to an annually averaged depletion of around 10% (~2.5 Dobson units) of the tropical tropospheric ozone column, with largest effects in the middle to upper troposphere. This depletion contributes approximately −0.10 W m−2 to the radiative flux at the tropical tropopause. This negative flux is of similar magnitude to the ~0.33 W m−2 contribution of tropospheric ozone to present-day radiative balance as recently estimated from satellite observations. We find that the implementation of oceanic halogen sources and chemistry in climate models is an important component of the natural background ozone budget and we suggest that it needs to be considered when estimating both preindustrial ozone baseline levels and long term changes in tropospheric ozone.

scholarly journals Cluster-based analysis of multi-model climate ensembles

2018 ◽  
Vol 11 (6) ◽  
pp. 2033-2048 ◽  
Author(s):  
Richard Hyde ◽  
Ryan Hossaini ◽  
Amber A. Leeson
Keyword(s):  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
Climate Models ◽  
Climate Model ◽  
Complex Data ◽  
Similar Data ◽  
Climate Data ◽  
Efficient Manner ◽  
Clustering Techniques ◽  
Insight Into

Abstract. Clustering – the automated grouping of similar data – can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model–observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry–climate model (CCM) output of tropospheric ozone – an important greenhouse gas – from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ∼ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ∼ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere – where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models.

scholarly journals Evaluation of ACCMIP outgoing longwave radiation from tropospheric ozone using TES satellite observations

2013 ◽  
Vol 13 (8) ◽  
pp. 4057-4072 ◽  
Author(s):  
K. W. Bowman ◽  
D. T. Shindell ◽  
H. M. Worden ◽  
J.F. Lamarque ◽  
P. J. Young ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
Outgoing Longwave Radiation ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Longwave Radiation ◽  
Satellite Observations ◽  
Ensemble Mean ◽  
High Bias

Abstract. 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 120 mW m−2 OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39 ± 41 m Wm−2 relative to TES data. We show that there is a correlation (R2 = 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 100 m Wm−2. Removing these models leads to a mean ozone radiative forcing of 394 ± 42 m Wm−2. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 ± 60 m Wm−2 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.

scholarly journals The influence of mixing on the stratospheric age of air changes in the 21st century

2019 ◽  
Vol 19 (2) ◽  
pp. 921-940 ◽  
Author(s):  
Roland Eichinger ◽  
Simone Dietmüller ◽  
Hella Garny ◽  
Petr Šácha ◽  
Thomas Birner ◽  
...  
Keyword(s):  
21St Century ◽  
Climate Models ◽  
Climate Model ◽  
Phase 1 ◽  
Relative Strength ◽  
Mixing Efficiency ◽  
Climate Projections ◽  
Model Studies ◽  
State Potential

Abstract. Climate models consistently predict an acceleration of the Brewer–Dobson circulation (BDC) due to climate change in the 21st century. However, the strength of this acceleration varies considerably among individual models, which constitutes a notable source of uncertainty for future climate projections. To shed more light upon the magnitude of this uncertainty and on its causes, we analyse the stratospheric mean age of air (AoA) of 10 climate projection simulations from the Chemistry-Climate Model Initiative phase 1 (CCMI-I), covering the period between 1960 and 2100. In agreement with previous multi-model studies, we find a large model spread in the magnitude of the AoA trend over the simulation period. Differences between future and past AoA are found to be predominantly due to differences in mixing (reduced aging by mixing and recirculation) rather than differences in residual mean transport. We furthermore analyse the mixing efficiency, a measure of the relative strength of mixing for given residual mean transport, which was previously hypothesised to be a model constant. Here, the mixing efficiency is found to vary not only across models, but also over time in all models. Changes in mixing efficiency are shown to be closely related to changes in AoA and quantified to roughly contribute 10 % to the long-term AoA decrease over the 21st century. Additionally, mixing efficiency variations are shown to considerably enhance model spread in AoA changes. To understand these mixing efficiency variations, we also present a consistent dynamical framework based on diffusive closure, which highlights the role of basic state potential vorticity gradients in controlling mixing efficiency and therefore aging by mixing.

scholarly journals Tropospheric ozone in CCMI models and Gaussian process emulation to understand biases in the SOCOLv3 chemistry–climate model

2018 ◽  
Vol 18 (21) ◽  
pp. 16155-16172 ◽  
Author(s):  
Laura E. Revell ◽  
Andrea Stenke ◽  
Fiona Tummon ◽  
Aryeh Feinberg ◽  
Eugene Rozanov ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Gaussian Process Emulation ◽  
Column Ozone

Abstract. Previous multi-model intercomparisons have shown that chemistry–climate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARC–IGAC (Stratosphere–troposphere Processes And their Role in Climate–International Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40 %–50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to ∼30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU – approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, “SOCOLv3.1”, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NOx), carbon monoxide, methane and other volatile organic compounds, VOCs) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NOx than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistry–climate models.

scholarly journals Including the efficacy of land ice changes in deriving climate sensitivity from paleodata

2018 ◽  
Author(s):  
Lennert B. Stap ◽  
Peter Köhler ◽  
Gerrit Lohmann
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Temperature Anomaly ◽  
Global Temperature ◽  
Radiative Forcings ◽  
Intercomparison Project ◽  
The Impact

Abstract. The influence of long-term processes in the climate system, such as land ice changes, has to be compensated for when comparing climate sensitivity derived from paleodata with equilibrium climate sensitivity (ECS) calculated by climate models, which is only generated by a CO2 change. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI], that relates the impact of land ice changes on global temperature to that of CO2 changes, in our calculation of climate sensitivity from paleodata. We apply our new approach to a proxy-inferred paleoclimate dataset, and find an equivalent ECS of 5.6 ± 1.3 K per CO2 doubling. The substantial uncertainty herein is generated by the range in ε[LI] we use, which is based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum (LGM) temperature anomaly (46 ± 14 %). The low end of our ECS estimate, which concurs with estimates from other approaches, tallies with a large influence for land ice changes. To separately assess this influence, we analyse output of the PMIP3 climate model intercomparison project. From this data, we infer a functional intermodel relation between global and high-latitude temperature changes at the LGM with respect to the pre-industrial climate, and the temperature anomaly caused by a CO2 change. Applying this relation to our dataset, we find a considerable 64 % influence for land ice changes on the LGM temperature anomaly. This is even higher than the range used before, and leads to an equivalent ECS of 3.8 K per CO2 doubling. Together, our results suggest that land ice changes play a key role in the variability of Late Pleistocene temperatures.

scholarly journals Kinematic and diabatic vertical velocity climatologies from a chemistry climate model

2016 ◽  
Vol 16 (10) ◽  
pp. 6223-6239 ◽  
Author(s):  
Charlotte Marinke Hoppe ◽  
Felix Ploeger ◽  
Paul Konopka ◽  
Rolf Müller
Keyword(s):  
Vertical Velocity ◽  
Atmospheric Chemistry ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Boreal Summer ◽  
Uniform Structure ◽  
Residual Circulation ◽  
Mixing Processes ◽  
The Impact

Abstract. The representation of vertical velocity in chemistry climate models is a key element for the representation of the large-scale Brewer–Dobson circulation in the stratosphere. Here, we diagnose and compare the kinematic and diabatic vertical velocities in the ECHAM/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model. The calculation of kinematic vertical velocity is based on the continuity equation, whereas diabatic vertical velocity is computed using diabatic heating rates. Annual and monthly zonal mean climatologies of vertical velocity from a 10-year simulation are provided for both kinematic and diabatic vertical velocity representations. In general, both vertical velocity patterns show the main features of the stratospheric circulation, namely, upwelling at low latitudes and downwelling at high latitudes. The main difference in the vertical velocity pattern is a more uniform structure for diabatic and a noisier structure for kinematic vertical velocity. Diabatic vertical velocities show higher absolute values both in the upwelling branch in the inner tropics and in the downwelling regions in the polar vortices. Further, there is a latitudinal shift of the tropical upwelling branch in boreal summer between the two vertical velocity representations with the tropical upwelling region in the diabatic representation shifted southward compared to the kinematic case. Furthermore, we present mean age of air climatologies from two transport schemes in EMAC using these different vertical velocities and analyze the impact of residual circulation and mixing processes on the age of air. The age of air distributions show a hemispheric difference pattern in the stratosphere with younger air in the Southern Hemisphere and older air in the Northern Hemisphere using the transport scheme with diabatic vertical velocities. Further, the age of air climatology from the transport scheme using diabatic vertical velocities shows a younger mean age of air in the inner tropical upwelling branch and an older mean age in the extratropical tropopause region.

scholarly journals Representing ozone extremes in European megacities: the importance of resolution in a global chemistry climate model

2014 ◽  
Vol 14 (8) ◽  
pp. 3899-3912 ◽  
Author(s):  
Z. S. Stock ◽  
M. R. Russo ◽  
J. A. Pyle
Keyword(s):  
Atmospheric Chemistry ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Surface Ozone ◽  
Global Climate Models ◽  
Ozone Concentrations ◽  
Coarse Resolution ◽  
Highly Nonlinear ◽  
The Impact

Abstract. The continuing growth of the world's urban population has led to an increasing number of cities with more than 10 million inhabitants. The higher emissions of pollutants, coupled to higher population density, makes predictions of air quality in these megacities of particular importance from both a science and a policy perspective. Global climate models are typically run at coarse resolution to enable both the efficient running of long time integrations, and the ability to run multiple future climate scenarios. However, when considering surface ozone concentrations at the local scale, coarse resolution can lead to inaccuracies arising from the highly nonlinear ozone chemistry and the sensitivity of ozone to the distribution of its precursors on smaller scales. In this study, we use UM-UKCA, a global atmospheric chemistry model, coupled to the UK Met Office Unified Model, to investigate the impact of model resolution on tropospheric ozone, ranging from global to local scales. We focus on the model's ability to represent the probability of high ozone concentrations in the summer and low ozone concentrations, associated with polluted megacity environments, in the winter, and how this varies with horizontal resolution. We perform time-slice integrations with two model configurations at typical climate resolution (CR, ~150 km) and at a higher resolution (HR, ~40 km). The CR configuration leads to overestimation of ozone concentrations on both regional and local scales, while it gives broadly similar results to the HR configuration on the global scale. The HR configuration is found to produce a more realistic diurnal cycle of ozone concentrations and to give a better representation of the probability density function of ozone values in urban areas such as the megacities of London and Paris. We find the observed differences in model behaviour between CR and HR configurations to be largely caused by chemical differences during the winter and meteorological differences during the summer.

scholarly journals The influence of mixing on stratospheric circulation changes in the 21st century

2018 ◽  
Author(s):  
Roland Eichinger ◽  
Simone Dietmüller ◽  
Hella Garny ◽  
Petr Sacha ◽  
Thomas Birner ◽  
...  
Keyword(s):  
21St Century ◽  
Climate Models ◽  
Climate Model ◽  
Phase 1 ◽  
Relative Strength ◽  
Mixing Efficiency ◽  
Climate Projections ◽  
Model Studies ◽  
State Potential

Abstract. Climate models consistently predict an acceleration of the Brewer-Dobson circulation (BDC) due to climate change in the 21st century. However, the strength of this acceleration varies considerably among individual models, which constitutes a notable source of uncertainty for future climate projections. To shed more light upon the magnitude of this uncertainty and on its causes, we analyze the stratospheric mean age of air (AoA) of 10 climate projection simulations from the Chemistry Climate Model Initiative phase 1 (CCMI-I), covering the period between 1960 and 2100. In agreement with previous multi-model studies, we find a large model spread in the magnitude of the AoA trend over the simulation period. Differences between future and past AoA are found to be predominantly due to differences in mixing (reduced aging by mixing and recirculation) rather than differences in residual mean transport. We furthermore analyze the mixing efficiency, a measure of the relative strength of mixing for given residual mean transport, which was previously hypothesized to be a model constant. Here, the mixing efficiency is found to vary not only across models, but also over time in all models. Changes in mixing efficiency are shown to be closely related to changes in AoA and quantified to roughly contribute 10 % to the long-term AoA decrease over the 21st century. Additionally, mixing efficiency variations are shown to considerably enhance model spread in AoA changes. To understand these mixing efficiency variations, we also present a consistent dynamical framework based on diffusive closure, which highlights the role of basic state potential vorticity gradients in controlling mixing efficiency and therefore aging by mixing.

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