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Impact of optimized mixing heights on simulated regional atmospheric transport of CO2

The mixing height (MH) is a crucial parameter in commonly used transport models that proportionally affects air concentrations of trace gases with sources/sinks near the ground and on diurnal scales. Past synthetic data experiments indicated the possibility to improve tracer transport by minimizing errors of simulated MHs. In this paper we evaluate a method to constrain the Lagrangian particle dispersion model STILT (Stochastic Time-Inverted Lagrangian Transport) with MH diagnosed from radiosonde profiles using a bulk Richardson method. The same method was used to obtain hourly MHs for the period September/October 2009 from the Weather Research and Forecasting (WRF) model, which covers the European continent at 10 km horizontal resolution. Kriging with external drift (KED) was applied to estimate optimized MHs from observed and modelled MHs, which were used as input for STILT to assess the impact on CO2 transport. Special care has been taken to account for uncertainty in MH retrieval in this estimation process. MHs and CO2 concentrations were compared to vertical profiles from aircraft in situ data. We put an emphasis on testing the consistency of estimated MHs to observed vertical mixing of CO2. Modelled CO2 was also compared with continuous measurements made at Cabauw and Heidelberg stations. WRF MHs were significantly biased by ~10–20% during day and ~40–60% during night. Optimized MHs reduced this bias to ~5% with additional slight improvements in random errors. The KED MHs were generally more consistent with observed CO2 mixing. The use of optimized MHs had in general a favourable impact on CO2 transport, with bias reductions of 5–45% (day) and 60–90% (night). This indicates that a large part of the found CO2 model–data mismatch was indeed due to MH errors. Other causes for CO2 mismatch are discussed. Applicability of our method is discussed in the context of CO2 inversions at regional scales.
Diurnal variations of stratospheric ozone measured by ground-based microwave remote sensing at the Mauna Loa NDACC site: measurement validation and GEOSCCM model comparison

There is presently renewed interest in diurnal variations of stratospheric and mesospheric ozone for the purpose of supporting homogenization of records of various ozone measurements that are limited by the technique employed to being made at certain times of day. We have made such measurements for 19 years using a passive microwave remote sensing technique at the Mauna Loa Observatory (MLO) in Hawaii, which is a primary station in the Network for Detection of Atmospheric Composition Change (NDACC). We have recently reprocessed these data with hourly time resolution to study diurnal variations. We inspected differences between pairs of the ozone spectra (e.g., day and night) from which the ozone profiles are derived to determine the extent to which they may be contaminated by diurnally varying systematic instrumental or measurement effects. These are small, and we have reduced them further by selecting data that meet certain criteria that we established. We have calculated differences between profiles measured at different times: morning–night, afternoon–night, and morning–afternoon and have intercompared these with like profiles derived from the Aura Microwave Limb Sounder (Aura-MLS), the Upper Atmosphere Research Satellite Microwave Limb Sounder (UARS-MLS), the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES), and Solar Backscatter Ultraviolet version 2 (SBUV/2) measurements. Differences between averages of coincident profiles are typically < 1.5% of typical nighttime values over most of the covered altitude range with some exceptions. We calculated averages of ozone values for each hour from the Mauna Loa microwave data, and normalized these to the average for the first hour after midnight for comparison with corresponding values calculated with the Goddard Earth Observing System Chemistry Climate Model (GEOSCCM). We found that the measurements and model output mostly agree to better than 1.5% of the midnight value, with one noteworthy exception: The measured morning–night values are significantly (2–3 %) higher than the modeled ones from 3.2 to 1.8 hPa (~39–43 km), and there is evidence that the measured values are increasing compared to the modeled values before sunrise in this region.
Top-down estimates of biomass burning emissions of black carbon in the Western United States

We estimate biomass burning and anthropogenic emissions of black carbon (BC) in the western US for May–October 2006 by inverting surface BC concentrations from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using a global chemical transport model. We first use active fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the spatiotemporal distributions of the biomass burning BC emissions from the Global Fire Emissions Database (GFEDv2). The adjustment primarily shifts emissions from late to middle and early summer (a 33% decrease in September–October and a 56% increase in June–August) and leads to appreciable increases in modeled surface BC concentrations in early and middle summer, especially at the 1–2 and 2–3 km altitude ranges. We then conduct analytical inversions at both 2° × 2.5° and 0.5° × 0.667° (nested over North America) horizontal resolutions. The a posteriori biomass burning BC emissions for July–September are 31.7 Gg at 2° × 2.5° (an increase by a factor of 4.7) and 19.2 Gg at 0.5° × 0.667° (an increase by a factor of 2.8). The inversion results are rather sensitive to model resolution. The a posteriori biomass burning emissions at the two model resolutions differ by a factor of ~6 in California and the Southwest and by a factor of 2 in the Pacific Northwest. The corresponding a posteriori anthropogenic BC emissions are 9.1 Gg at 2° × 2.5° (a decrease of 48%) and 11.2 Gg at 0.5° × 0.667° (a decrease of 36%). Simulated surface BC concentrations with the a posteriori emissions capture the observed major fire episodes at most sites and the substantial enhancements at the 1–2 and 2–3 km altitude ranges. The a posteriori emissions also lead to large bias reductions (by ~30% on average at both model resolutions) in modeled surface BC concentrations and significantly better agreement with observations (increases in Taylor skill scores of 95% at 2° × 2.5° and 42 % at 0.5° × 0.667°).
Trajectory model simulations of ozone (O3) and carbon monoxide (CO) in the lower stratosphere

A domain-filling, forward trajectory model originally developed for simulating stratospheric water vapor is used to simulate ozone (O3) and carbon monoxide (CO) in the lower stratosphere. Trajectories are initialized in the upper troposphere, and the circulation is based on reanalysis wind fields. In addition, chemical production and loss rates along trajectories are included using calculations from the Whole Atmosphere Community Climate Model (WACCM). The trajectory model results show good overall agreement with satellite observations from the Aura Microwave Limb Sounder (MLS) and the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) in terms of spatial structure and seasonal variability. The trajectory model results also agree well with the Eulerian WACCM simulations. Analysis of the simulated tracers shows that seasonal variations in tropical upwelling exerts strong influence on O3 and CO in the tropical lower stratosphere, and the coupled seasonal cycles provide a useful test of the transport simulations. Interannual variations in the tracers are also closely coupled to changes in upwelling, and the trajectory model can accurately capture and explain observed changes during 2005–2011. This demonstrates the importance of variability in tropical upwelling in forcing chemical changes in the tropical lower stratosphere.
Study of global cloud droplet number concentration with A-Train satellites

Cloud droplet number concentration (CDNC) is an important microphysical property of liquid clouds that impacts radiative forcing, precipitation and is pivotal for understanding cloud–aerosol interactions. Current studies of this parameter at global scales with satellite observations are still challenging, especially because retrieval algorithms developed for passive sensors (i.e., MODerate Resolution Imaging Spectroradiometer (MODIS)/Aqua) have to rely on the assumption of cloud adiabatic growth. The active sensor component of the A-Train constellation (i.e., Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)/CALIPSO) allows retrievals of CDNC from depolarization measurements at 532 nm. For such a case, the retrieval does not rely on the adiabatic assumption but instead must use a priori information on effective radius (re), which can be obtained from other passive sensors. In this paper, re values obtained from MODIS/Aqua and Polarization and Directionality of the Earth Reflectance (POLDER)/PARASOL (two passive sensors, components of the A-Train) are used to constrain CDNC retrievals from CALIOP. Intercomparison of CDNC products retrieved from MODIS and CALIOP sensors is performed, and the impacts of cloud entrainment, drizzling, horizontal heterogeneity and effective radius are discussed. By analyzing the strengths and weaknesses of different retrieval techniques, this study aims to better understand global CDNC distribution and eventually determine cloud structure and atmospheric conditions in which they develop. The improved understanding of CDNC can contribute to future studies of global cloud–aerosol–precipitation interaction and parameterization of clouds in global climate models (GCMs).
Simulating the integrated summertime Δ14CO2 signature from anthropogenic emissions over Western Europe

Radiocarbon dioxide (14CO2, reported in Δ14CO2) can be used to determine the fossil fuel CO2 addition to the atmosphere, since fossil fuel CO2 no longer contains any 14C. After the release of CO2 at the source, atmospheric transport causes dilution of strong local signals into the background and detectable gradients of Δ14CO2 only remain in areas with high fossil fuel emissions. This fossil fuel signal can moreover be partially masked by the enriching effect that anthropogenic emissions of 14CO2 from the nuclear industry have on the atmospheric Δ14CO2 signature. In this paper, we investigate the regional gradients in 14CO2 over the European continent and quantify the effect of the emissions from nuclear industry. We simulate the emissions and transport of fossil fuel CO2 and nuclear 14CO2 for Western Europe using the Weather Research and Forecast model (WRF-Chem) for a period covering 6 summer months in 2008. We evaluate the expected CO2 gradients and the resulting Δ14CO2 in simulated integrated air samples over this period, as well as in simulated plant samples. We find that the average gradients of fossil fuel CO2 in the lower 1200 m of the atmosphere are close to 15 ppm at a 12 km × 12 km horizontal resolution. The nuclear influence on Δ14CO2 signatures varies considerably over the domain and for large areas in France and the UK it can range from 20 to more than 500% of the influence of fossil fuel emissions. Our simulations suggest that the resulting gradients in Δ14CO2 are well captured in plant samples, but due to their time-varying uptake of CO2, their signature can be different with over 3&permil; from the atmospheric samples in some regions. We conclude that the framework presented will be well-suited for the interpretation of actual air and plant 14CO2 samples.
The effect of solar zenith angle on MODIS cloud optical and microphysical retrievals within marine liquid water clouds

In this paper we use a novel observational approach to investigate MODIS satellite retrieval biases of τ and re (using three different MODIS bands: 1.6, 2.1 and 3.7 μm, denoted as re1.6, re2.1 and re3.7, respectively) that occur at high solar zenith angles (θ0) and how they affect retrievals of cloud droplet concentration (Nd). Utilizing the large number of overpasses for polar regions and the diurnal variation of θ0 we estimate biases in the above quantities for an open ocean region that is dominated by low level stratiform clouds. We find that the mean τ is fairly constant between θ0 = 50° and ~65–70°, but then increases rapidly with an increase of over 70 % between the lowest and highest θ0. The re2.1 and re3.7 decrease with θ0, with effects also starting at around θ0 = 65–70°. At low θ0, the re values from the three different MODIS bands agree to within around 0.2 μm, whereas at high θ0 the spread is closer to 1 μm. The percentage changes of re with θ0 are considerably lower than those for τ, being around 5 % and 7% for re2.1 and re3.7. For re1.6 there was very little change with θ0. Evidence is provided that these changes are unlikely to be due to any physical diurnal cycle. The increase in τ and decrease in re both contribute to an overall increase in Nd of 40–70% between low and high θ0. Whilst the overall re changes are quite small, they are not insignificant for the calculation of Nd; we find that the contributions to Nd biases from the τ and re biases were roughly comparable for re3.7, although for the other re bands the τ changes were considerably more important. Also, when considering only the clouds with the more heterogeneous tops, the importance of the re biases was considerably enhanced for both re2.1 and re3.7. When using the variability of 1 km resolution τ data (γτ) as a heterogeneity parameter we obtained the expected result of increasing differences in τ between high and low θ0 as heterogeneity increased, which was not the case when using the variability of 5 km resolution cloud top temperature (σCTT), suggesting that γτ is a better predictor of τ biases at high θ0 than σCTT. For a given θ0, large decreases in re were observed as the cloud top heterogeneity changed from low to high values, although it is possible that physical changes to the clouds associated with cloud heterogeneity variation may account for some of this. However, for a given cloud top heterogeneity we find that the value of θ0 affects the sign and magnitude of the relative differences between re1.6, re2.1 and re3.7, which has implications for attempts to retrieve vertical cloud information using the different MODIS bands. The relatively larger decrease in re3.7 and the lack of change of re1.6 with both θ0 and cloud top heterogeneity suggest that re3.7 is more prone to retrieval biases due to high θ0 than the other bands. We discuss some possible reasons for this. Our results have important implications for individual MODIS swaths at high θ0, which may be used for case studies for example. θ0 values > 65° can occur at latitudes as low as 28° in mid-winter and for higher latitudes the problem will be more acute. Also, Level-3 daily averaged MODIS cloud property data consist of the averages of several overpasses for the high latitudes, which will occur at a range of θ0 values. Thus, some biased data are likely to be included. It is also likely that some of the θ0 effects described here would apply to τ and re retrievals from satellite instruments that use visible light at similar wavelengths along with forward retrieval models that assume plane parallel clouds, such as the GOES imagers, SEVIRI, etc.
Air quality in the mid-21st century for the city of Paris under two climate scenarios; from the regional to local scale

Ozone and PM2.5 concentrations over the city of Paris are modeled with the CHIMERE air-quality model at 4 km × 4 km horizontal resolution for two future emission scenarios. A high-resolution (1 km × 1 km) emission projection until 2020 for the greater Paris region is developed by local experts (AIRPARIF) and is further extended to year 2050 based on regional-scale emission projections developed by the Global Energy Assessment. Model evaluation is performed based on a 10-year control simulation. Ozone is in very good agreement with measurements while PM2.5 is underestimated by 20% over the urban area mainly due to a large wet bias in wintertime precipitation. A significant increase of maximum ozone relative to present-day levels over Paris is modeled under the "business-as-usual" scenario (+7 ppb) while a more optimistic "mitigation" scenario leads to a moderate ozone decrease (−3.5 ppb) in year 2050. These results are substantially different to previous regional-scale projections where 2050 ozone is found to decrease under both future scenarios. A sensitivity analysis showed that this difference is due to the fact that ozone formation over Paris at the current urban-scale study is driven by volatile organic compound (VOC)-limited chemistry, whereas at the regional-scale ozone formation occurs under NOx-sensitive conditions. This explains why the sharp NOx reductions implemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas, projections at both scales yield similar results showing that the longer timescale processes of emission transport and ozone formation are less sensitive to model resolution. PM2.5 concentrations decrease by 78% and 89% under business-as-usual and mitigation scenarios, respectively, compared to the present-day period. The reduction is much more prominent over the urban part of the domain due to the effective reductions of road transport and residential emissions resulting in the smoothing of the large urban increment modeled in the control simulation.
Uptake of HO2 radicals onto Arizona test dust particles using an aerosol flow tube

Uptake coefficients for HO2 radicals onto Arizona test dust (ATD) aerosols were measured at room temperature and atmospheric pressure using an aerosol flow tube and the sensitive fluorescence assay by gas expansion (FAGE) technique, enabling HO2 concentrations in the range 3–10 × 108 molecule cm−3 to be investigated. The uptake coefficients were measured as 0.031 ± 0.008 and 0.018 ± 0.006 for the lower and higher HO2 concentrations, respectively, over a range of relative humidities (5–76%). A time dependence for the HO2 uptake onto the ATD aerosols was observed, with larger uptake coefficients observed at shorter reaction times. The combination of time and HO2 concentration dependencies suggest either the partial saturation of the dust surface or that a chemical component of the dust is partially consumed whilst the aerosols are exposed to HO2. A constrained box model is used to show that HO2 uptake to dust surfaces may be an important loss pathway of HO2 in the atmosphere.
Systematic analysis of tropospheric NO2 long-range transport events detected in GOME-2 satellite data

Intercontinental long-range transport (LRT) events of NO2 relocate the effects of air pollution from emission regions to remote, pristine regions. We detect transported plumes in tropospheric NO2 columns measured by the GOME-2/MetOp-A instrument with a specialized algorithm and trace the plumes to their sources using the HYSPLIT Lagrangian transport model. With this algorithm we find 3808 LRT events over the ocean for the period 2007 to 2011. LRT events occur frequently in the mid-latitudes, emerging usually from coastal high-emission regions. In the free troposphere, plumes of NO2 can travel for several days to the polar oceanic atmosphere or to other continents. They travel along characteristic routes and originate from both continuous anthropogenic emission and emission events such as bush fires. Most NO2 LRT events occur during autumn and winter months, when meteorological conditions and emissions are most favorable. The evaluation of meteorological data shows that the observed NO2 LRT is often linked to cyclones passing over an emission region.