Chemistry–climate interactions of aerosol nitrate from lightning

Abstract. Lightning represents one of the dominant emission sources for NOx in the troposphere. The direct release of oxidised nitrogen in the upper troposphere does not only affect ozone formation, but also chemical and microphysical properties of aerosol particles in this region. This study investigates the direct impact of LNOx emissions on upper-tropospheric nitrate using a global chemistry climate model. The simulation results show a substantial influence of the lightning emissions on the mixing ratios of nitrate aerosol in the upper troposphere of more than 50 %. In addition to the impact on nitrate, lightning substantially affects the oxidising capacity of the atmosphere with substantial implications for gas-phase sulfate formation and new particle formation in the upper troposphere. In conjunction with the condensation of nitrates, substantial differences in the aerosol size distribution occur in the upper troposphere as a consequence of lightning. This has implications for the extinction properties of the aerosol particles and for the cloud optical properties. While the extinction is generally slightly enhanced due to the LNOx emissions, the response of the clouds is ambiguous due to compensating effects in both liquid and ice clouds. Resulting shortwave flux perturbations are of ∼ −100 mW m−2 as determined from several sensitivity scenarios, but an uncertainty range of almost 50 % has to be defined due to the large internal variability of the system and the uncertainties in the multitude of involved processes. Despite the clear statistical significance of the influence of lightning on the nitrate concentrations, the robustness of the findings gradually decreases towards the determination of the radiative flux perturbations.

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Chemistry-climate interactions of aerosol nitrate from lightning

10.5194/acp-2016-426 ◽

2016 ◽

Author(s):

H. Tost

Keyword(s):

Climate Model ◽

Aerosol Particles ◽

Internal Variability ◽

Aerosol Size Distribution ◽

Upper Troposphere ◽

Uncertainty Range ◽

Mixing Ratios ◽

Microphysical Properties ◽

Climate Interactions ◽

The Impact

Abstract. Lightning represents one of the dominant emission source for NOx in the troposphere. The direct release of oxidised nitrogen in the upper troposphere does not only affect ozone formation, but also chemical and microphysical properties of aerosol particles in this region. This study investigates the direct impact of LNOx emissions on upper tropospheric nitrate using a global chemistry climate model. The simulation results show a substantial influence of the lightning emissions on the mixing ratios of nitrate aerosol in the upper troposphere of more than 50%. In addition to the impact on nitrate, lightning substantially affects the oxidising capacity of the atmosphere with substantial implications for gas phase sulphate formation and new particle formation in the upper troposphere. In conjunction with the condensation of nitrates, substantial differences in the aerosol size distribution occur in the upper troposphere as a consequence of lightning. This has implications for the extinction properties of the aerosol particles and for the cloud optical properties. While the extinction is generally slightly enhanced due to the LNOx emissions, the response of the clouds is ambiguous due to compensating effects in both liquid and ice clouds. Resulting shortwave flux perturbations are of ~−100mW/m2, but an uncertainty range of almost 50% has to be defined due to the large internal variability of the system and the uncertainties in the multitude of involved processes.

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Exploring the uncertainties in the aviation soot–cirrus effect

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-17267-2021 ◽

2021 ◽

Vol 21 (23) ◽

pp. 17267-17289

Author(s):

Mattia Righi ◽

Johannes Hendricks ◽

Christof Gerhard Beer

Keyword(s):

Radiative Forcing ◽

Climate Model ◽

Internal Variability ◽

Reanalysis Data ◽

Ice Nucleation ◽

Cirrus Clouds ◽

Model Studies ◽

Model Dynamics ◽

Analogous Model ◽

The Impact

Abstract. A global aerosol–climate model, including a two-moment cloud microphysical scheme and a parametrization for aerosol-induced ice formation in cirrus clouds, is applied in order to quantify the impact of aviation soot on natural cirrus clouds. Several sensitivity experiments are performed to assess the uncertainties in this effect related to (i) the assumptions on the ice nucleation abilities of aviation soot, (ii) the representation of vertical updrafts in the model, and (iii) the use of reanalysis data to relax the model dynamics (the so-called nudging technique). Based on the results of the model simulations, a radiative forcing from the aviation soot–cirrus effect in the range of −35 to 13 mW m−2 is quantified, depending on the assumed critical saturation ratio for ice nucleation and active fraction of aviation soot but with a confidence level below 95 % in several cases. Simple idealized experiments with prescribed vertical velocities further show that the uncertainties on this aspect of the model dynamics are critical for the investigated effect and could potentially add a factor of about 2 of further uncertainty to the model estimates of the resulting radiative forcing. The use of the nudging technique to relax model dynamics is proved essential in order to identify a statistically significant signal from the model internal variability, while simulations performed in free-running mode and with prescribed sea-surface temperatures and sea-ice concentrations are shown to be unable to provide robust estimates of the investigated effect. A comparison with analogous model studies on the aviation soot–cirrus effect show a very large model diversity, with a conspicuous lack of consensus across the various estimates, which points to the need for more in-depth analyses on the roots of such discrepancies.

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Sub-micrometer aerosol particles in the upper troposphere/lowermost stratosphere as measured by CARIBIC and modeled using the MIT-CAM3 global climate model

Journal of Geophysical Research Atmospheres ◽

10.1029/2011jd016777 ◽

2012 ◽

Vol 117 (D11) ◽

pp. n/a-n/a ◽

Cited By ~ 7

Author(s):

Annica M. L. Ekman ◽

Markus Hermann ◽

Peter Groß ◽

Jost Heintzenberg ◽

Dongchul Kim ◽

...

Keyword(s):

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Aerosol Particles ◽

Upper Troposphere

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On the Choice of Ensemble Mean for Estimating the Forced Signal in the Presence of Internal Variability

Journal of Climate ◽

10.1175/jcli-d-17-0662.1 ◽

2018 ◽

Vol 31 (14) ◽

pp. 5681-5693 ◽

Cited By ~ 14

Author(s):

Leela M. Frankcombe ◽

Matthew H. England ◽

Jules B. Kajtar ◽

Michael E. Mann ◽

Byron A. Steinman

Keyword(s):

Regional Differences ◽

Climate Model ◽

Surface Air Temperature ◽

Internal Variability ◽

Single Model ◽

Sea Level Pressure ◽

Model Simulations ◽

Ensemble Mean ◽

Climate Model Simulations ◽

The Impact

Abstract In this paper we examine various options for the calculation of the forced signal in climate model simulations, and the impact these choices have on the estimates of internal variability. We find that an ensemble mean of runs from a single climate model [a single model ensemble mean (SMEM)] provides a good estimate of the true forced signal even for models with very few ensemble members. In cases where only a single member is available for a given model, however, the SMEM from other models is in general out-performed by the scaled ensemble mean from all available climate model simulations [the multimodel ensemble mean (MMEM)]. The scaled MMEM may therefore be used as an estimate of the forced signal for observations. The MMEM method, however, leads to increasing errors further into the future, as the different rates of warming in the models causes their trajectories to diverge. We therefore apply the SMEM method to those models with a sufficient number of ensemble members to estimate the change in the amplitude of internal variability under a future forcing scenario. In line with previous results, we find that on average the surface air temperature variability decreases at higher latitudes, particularly over the ocean along the sea ice margins, while variability in precipitation increases on average, particularly at high latitudes. Variability in sea level pressure decreases on average in the Southern Hemisphere, while in the Northern Hemisphere there are regional differences.

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Constraining the model representation of the aerosol life cycle in relation to sources and sinks.

10.5194/egusphere-egu2020-21948 ◽

2020 ◽

Author(s):

Paul Kim ◽

Daniel Partridge ◽

James Haywood

Keyword(s):

Climate Change ◽

Life Cycle ◽

Large Scale ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Evaluation Framework ◽

Microphysical Properties ◽

The Impact ◽

Source And Sink

Global climate model (GCM) ensembles still produce a significant spread of estimates for the future of climate change which hinders our ability to influence policymakers. The range of these estimates can only partly be explained by structural differences and varying choice of parameterisation schemes between GCMs. GCM representation of cloud and aerosol processes, more specifically aerosol microphysical properties, remain a key source of uncertainty contributing to the wide spread of climate change estimates. The radiative effect of aerosol is directly linked to the microphysical properties and these are in turn controlled by aerosol source and sink processes during transport as well as meteorological conditions.A Lagrangian, trajectory-based GCM evaluation framework, using spatially and temporally collocated aerosol diagnostics, has been applied to over a dozen GCMs via the AeroCom initiative. This framework is designed to isolate the source and sink processes that occur during the aerosol life cycle in order to improve the understanding of the impact of these processes on the simulated aerosol burden. Measurement station observations linked to reanalysis trajectories are then used to evaluate each GCM with respect to a quasi-observational standard to assess GCM skill. The AeroCom trajectory experiment specifies strict guidelines for modelling groups; all simulations have wind fields nudged to ERA-Interim reanalysis and all simulations use emissions from the same inventories. This ensures that the discrepancies between GCM parameterisations are emphasised and differences due to large scale transport patterns, emissions and other external factors are minimised.Preliminary results from the AeroCom trajectory experiment will be presented and discussed, some of which are summarised now. A comparison of GCM aerosol particle number size distributions against observations made by measurement stations in different environments will be shown, highlighting the difficulties that GCMs have at reproducing observed aerosol concentrations across all size ranges in pristine environments. The impact of precipitation during transport on aerosol microphysical properties in each GCM will be shown and the implications this has on resulting aerosol forcing estimates will be discussed. Results demonstrating the trajectory collocation framework will highlight its ability to give more accurate estimates of the key aerosol sources in GCMs and the importance of these sources in influencing modelled aerosol-cloud effects. In summary, it will be shown that this analysis approach enables us to better understand the drivers behind inter-model and model-observation discrepancies.

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Investigation of strongly enhanced methane Part I: Chemical feedbacks and rapid adjustments.

10.5194/egusphere-egu2020-9786 ◽

2020 ◽

Author(s):

Franziska Winterstein ◽

Patrick Jöckel ◽

Martin Dameris ◽

Michael Ponater ◽

Fabian Tanalski ◽

...

Keyword(s):

Atmospheric Chemistry ◽

Radiative Forcing ◽

Climate Model ◽

Numerical Study ◽

Stratospheric Ozone ◽

Lower Boundary ◽

Tropospheric Chemistry ◽

Substantial Part ◽

Mixing Ratios ◽

The Impact

Methane (CH4) is the second most important greenhouse gas, which atmospheric concentration is influenced by human activities and currently on a sharp rise. We present a study with numerical simulations using a Chemistry-Climate-Model (CCM), which are performed to assess possible consequences of strongly enhanced CH4 concentrations in the Earth's atmosphere for the climate.Our analysis includes experiments with 2xCH4 and 5xCH4 present day (2010) lower boundary mixing ratios using the CCM EMAC. The simulations are conducted with prescribed oceanic conditions, mimicking present day tropospheric temperatures as its changes are largely suppressed. By doing so we are able to investigate the quasi-instantaneous chemical impact on the atmosphere. We find that the massive increase in CH4 strongly influences the tropospheric chemistry by reducing the OH abundance and thereby extending the tropospheric CH4 lifetime as well as the residence time of other chemical pollutants. The region above the tropopause is impacted by a substantial rise in stratospheric water vapor (SWV). The stratospheric ozone (O3) column increases overall, but SWV induced stratospheric cooling also leads to enhanced ozone depletion in the Antarctic lower stratosphere. Regional&#160; patterns of ozone change are affected by modification of stratospheric dynamics, i.e. increased tropical up-welling and stronger meridional transport&#160; towards the polar regions. We calculate the net radiative impact (RI) of the 2xCH4 experiment to be 0.69 W m-2 and for the 5xCH4 experiment to be 1.79 W m-2. A substantial part of the RI is contributed by chemically induced O3 and SWV changes, in line with previous radiative forcing estimates and is for the first time splitted and spatially asigned to its chemical contributors.This numerical study using a CCM with prescibed oceanic conditions shows the rapid responses to significantly enhanced CH4 mixing ratios, which is the first step towards investigating the impact of possible strong future CH4 emissions on atmospheric chemistry and its feedback on climate.

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Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-8-10755-2015 ◽

2015 ◽

Vol 8 (10) ◽

pp. 10755-10792

Author(s):

A. M. Dzambo ◽

D. D. Turner ◽

E. J. Mlawer

Keyword(s):

Water Vapor ◽

Statistical Significance ◽

Microwave Radiometer ◽

Precipitable Water ◽

Upper Troposphere ◽

Clear Sky ◽

Microwave Radiometers ◽

The Impact ◽

Dry Bias ◽

Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km MSL), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, mid-latitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RH are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

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Simulation of black carbon in snow and its climate impact in the Canadian Global Climate Model

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-18839-2015 ◽

2015 ◽

Vol 15 (13) ◽

pp. 18839-18882 ◽

Cited By ~ 1

Author(s):

M. Namazi ◽

K. von Salzen ◽

J. N. S. Cole

Keyword(s):

Black Carbon ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Surface Air Temperature ◽

Climate Impact ◽

Radiative Forcings ◽

Mixing Ratios ◽

Emission Changes ◽

The Impact

Abstract. A new physically-based parameterization of black carbon (BC) in snow was developed and implemented in the Canadian Atmospheric Global Climate Model (CanAM4.2). Simulated BC snow mixing ratios and BC snow radiative forcings are in good agreement with measurements and results from other models. Simulations with the improved model yield considerable trends in regional BC concentrations in snow and BC snow radiative forcings during the time period from 1950–1959 to 2000–2009. Increases in radiative forcings for Asia and decreases for Europe and North America are found to be associated with changes in BC emissions. Additional sensitivity simulations were performed in order to study the impact of BC emission changes between 1950–1959 and 2000–2009 on surface albedo, snow cover fraction, and surface air temperature. Results from these simulations indicate that impacts of BC emission changes on snow albedos between these two decades are small and not significant. Overall, changes in BC concentrations in snow have much smaller impacts on the cryosphere than the net warming surface air temperatures during the second half of the 20th century.

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Stratospheric ozone depletion from future nitrous oxide increases

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-29447-2013 ◽

2013 ◽

Vol 13 (11) ◽

pp. 29447-29481

Author(s):

W. Wang ◽

W. Tian ◽

S. Dhomse ◽

F. Xie ◽

J. Shu

Keyword(s):

Nitrous Oxide ◽

Ozone Depletion ◽

Climate Model ◽

Stratospheric Ozone ◽

Linear Regression Analysis ◽

Chemical Effect ◽

Mixing Ratios ◽

Ozone Trends ◽

The Impact ◽

Middle Stratosphere

Abstract. We have investigated the impact of assumed nitrous oxide (N2O) increases on stratospheric chemistry and dynamics by a series of idealized simulations. In a future cooler stratosphere the net yield of NOy from a changed N2O is known to decrease, but NOy can still be significantly increased by the increase of N2O. Results with a coupled chemistry-climate model (CCM) show that increases in N2O of 50%/100% between 2001 and 2050 result in more ozone destruction, causing a reduction in ozone mixing ratios of maximally 6%/10% in the middle stratosphere at around 10 hPa. This enhanced destruction could cause an ozone decline in the second half of this century in the middle stratosphere. However, the total ozone column still shows an increase in future decades, though the increase of 50%/100% in N2O caused a 2%/6% decrease in TCO compared with the reference simulation. N2O increases have significant effects on ozone trends at 20–10 hPa in the tropics and at northern high latitude, but have no significant effect on ozone trends in the Antarctic stratosphere. The ozone depletion potential for N2O in a future climate depends both on stratospheric temperature changes and tropospheric N2O changes, which have reversed effects on ozone in the middle and upper stratosphere. A 50% CO2 increase in conjunction with a 50% N2O increase cause significant ozone depletion in the middle stratosphere and lead to an increase of ozone in the upper stratosphere. Based on the multiple linear regression analysis and a series of sensitivity simulations, we find that the chemical effect of N2O increases dominates the ozone changes in the stratosphere while the dynamical and radiative effects of N2O increases are insignificant on average. However, the dynamical effect of N2O increases may cause large local changes in ozone mixing ratios, particularly, in the Southern Hemisphere lower stratosphere.

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Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

Atmospheric Measurement Techniques ◽

10.5194/amt-9-1613-2016 ◽

2016 ◽

Vol 9 (4) ◽

pp. 1613-1626 ◽

Cited By ~ 9

Author(s):

Andrew M. Dzambo ◽

David D. Turner ◽

Eli J. Mlawer

Keyword(s):

Water Vapor ◽

Statistical Significance ◽

Microwave Radiometer ◽

Precipitable Water ◽

Upper Troposphere ◽

Clear Sky ◽

Microwave Radiometers ◽

The Impact ◽

Dry Bias ◽

Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

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