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Snow physics as relevant to snow photochemistry

Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, thermal conductivity, permeability, gas diffusivity and optical properties. Inasmuch as possible, equations to parameterize these properties as functions of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth are discussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.
Simple measures of ozone depletion in the polar stratosphere

We investigate the extent to which quantities that are based on total column ozone are applicable as measures of ozone loss in the polar vortices. Such quantities have been used frequently in ozone assessments by the World Meteorological Organization (WMO) and also to assess the performance of chemistry-climate models. The most commonly considered quantities are March and October mean column ozone poleward of geometric latitude 63° and the spring minimum of daily total ozone minima poleward of a given latitude. Particularly in the Arctic, the former measure is affected by vortex variability and vortex break-up in spring. The minimum of daily total ozone minima poleward of a particular latitude is debatable, insofar as it relies on one single measurement or model grid point. We find that, for Arctic conditions, this minimum value often occurs in air outside the polar vortex, both in the observations and in a chemistry-climate model. Neither of the two measures shows a good correlation with chemical ozone loss in the vortex deduced from observations. We recommend that the minimum of daily minima should no longer be used when comparing polar ozone loss in observations and models. As an alternative to the March and October mean column polar ozone we suggest considering the minimum of daily average total ozone poleward of 63° equivalent latitude in spring (except for winters with an early vortex break-up). Such a definition both obviates relying on one single data point and reduces the impact of year-to-year variability in the Arctic vortex break-up on ozone loss measures. Further, this measure shows a reasonable correlation (r=–0.75) with observed chemical ozone loss. Nonetheless, simple measures of polar ozone loss must be used with caution; if possible, it is preferable to use more sophisticated measures that include additional information to disentangle the impact of transport and chemistry on ozone.
Retrieving global aerosol sources from satellites using inverse modeling

Understanding aerosol effects on global climate requires knowing the global distribution of tropospheric aerosols. By accounting for aerosol sources, transports, and removal processes, chemical transport models simulate the global aerosol distribution using archived meteorological fields. We develop an algorithm for retrieving global aerosol sources from satellite observations of aerosol distribution by inverting the GOCART aerosol transport model. The inversion is based on a generalized, multi-term least-squares-type fitting, allowing flexible selection and refinement of a priori algorithm constraints. For example, limitations can be placed on retrieved quantity partial derivatives, to constrain global aerosol emission space and time variability in the results. Similarities and differences between commonly used inverse modeling and remote sensing techniques are analyzed. To retain the high space and time resolution of long-period, global observational records, the algorithm is expressed using adjoint operators. Successful global aerosol emission retrievals at 2°×2.5 resolution were obtained by inverting GOCART aerosol transport model output, assuming constant emissions over the diurnal cycle, and neglecting aerosol compositional differences. In addition, fine and coarse mode aerosol emission sources were inverted separately from MODIS fine and coarse mode aerosol optical thickness data, respectively. These assumptions are justified, based on observational coverage and accuracy limitations, producing valuable aerosol source locations and emission strengths. From two weeks of daily MODIS observations during August 2000, the global placement of fine mode aerosol sources agreed with available independent knowledge, even though the inverse method did not use any a priori information about aerosol sources, and was initialized with a "zero aerosol emission" assumption. Retrieving coarse mode aerosol emissions was less successful, mainly because MODIS aerosol data over highly reflecting desert dust sources is lacking. The broader implications of applying our approach are also discussed.
Improvement of vertical and residual velocities in pressure or hybrid sigma-pressure coordinates in analysis data in the stratosphere

Stratospheric vertical winds from analysis data in pressure (p) or hybrid pressure (σ-p) coordinates, for use in e.g. chemical transport models (CTMs) or trajectory models, often suffer both from excessive noise and errors in their mean magnitude, which in turn can introduce errors in important dynamical quantities like vertical mixing or constituent transport with the residual circulation. Since vertical velocities cannot be measured directly, they are inferred from other quantities, typically from horizontal wind divergence, that is the mass continuity equation. We propose a method to calculate the vertical wind field from the thermodynamic energy equation in p or σ-p vertical coordinates that substantially reduces noise and overestimation of the residual circulation. It is completely equivalent to the approach using potential temperature (θ) as a vertical coordinate and diabatic heating rates as vertical velocities, which has already been demonstrated to give superior results to the continuity equation. It provides a quickly realizable improvement of the vertical winds, when a change of the vertical variable would cause an inadequate effort (e.g. in CTMs). The method is only applicable for stably stratified regions like the stratosphere.
Corrigendum to "Modeling the impact of sub-grid scale emission variability on upper-air concentration" published in Atmos. Chem. Phys., 8, 141–158, 2008
Technical Note: Determination of formaldehyde mixing ratios in air with PTR-MS: laboratory experiments and field measurements

Formaldehyde (HCHO), the most abundant carbonyl compound in the atmosphere, is generated as an intermediate product in the oxidation of nonmethane hydrocarbons. Proton transfer reaction mass spectrometry (PTR-MS) has the capability to detect HCHO from ion signals at m/z 31 with high time-resolution. However, the detection sensitivity is low compared to other detectable species, and is considerably affected by humidity, due to back reactions between protonated HCHO and water vapor prior to analysis. We performed a laboratory calibration of PTR-MS for HCHO and examined the detection sensitivity and humidity dependence at various field strengths. Subsequently, we deployed the PTR-MS instrument in a field campaign at Mount Tai in China in June 2006 to measure HCHO in various meteorological and photochemical conditions; we also conducted intercomparison measurements by Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS). Correction of interference in the m/z 31 signals by fragments from proton transfer reactions with methyl hydroperoxide, methanol, and ethanol greatly improves agreement between the two methods, giving the correlation [HCHO]MAX-DOAS=(0.99±0.16) [HCHO]PTR-MS+(0.02±0.38), where error limits represent 95% confidence levels.
Ten years of CO2, CH4, CO and N2O fluxes over Western Europe inferred from atmospheric measurements at Mace Head, Ireland

We estimated CO2, CH4, CO and N2O emission fluxes over the British Isles and Western Europe using atmospheric radon observations and concentrations recorded at the Mace Head Atmospheric Research Station between 1996 and 2005. We classified hourly concentration data into either long-range European or regional sources from Ireland and UK, by using local wind speed data in conjunction with 222Rn and 212Pb threshold criteria. This leads to the selection of about 7% of the total data for both sectors. We then used continuous 222Rn measurements and assumptions on the surface emissions of 222Rn to deduce the unknown fluxes of CO2, CH4, CO and N2O. Our results have been compared to the UNFCCC, EMEP and EDGAR statistical inventories and to inversion results for CH4. For Western Europe, we found yearly mean fluxes of 4.1±1.5 106 kg CO2 km−2 yr−1 , 11.9±2.0 103 kg CH4 km−2 yr−1, 12.8±4.2 103 kg CO km−2 yr−1 and 520.2±129.2 kg N2O km−2 yr−1, respectively, for CO2, CH4, CO and N2O over the period 1996–2005. The method based upon 222Rn to infer emissions has many sources of systematic errors, in particular its poorly known and variable footprint, uncertainties in 222Rn soil fluxes and in atmospheric mixing of air masses with background air. However, these biases are likely to remain constant in the long-term, which makes the method quite efficient to detect trends in fluxes. Over the last ten years period, the decrease of the anthropogenic CH4, CO and N2O emissions in Europe estimated by inventories (respectively −30%, −35% and −23%) is confirmed by the Mace Head data within 2%. Therefore, the 222Rn method provides an independent way of verification of changes in national emissions derived from inventories. Using European-wide estimates of the CO/CO2 emission ratio, we also found that it is possible to separate the fossil fuel CO2 emissions contribution from the one of total CO2 fluxes. The fossil fuel CO2 emissions and their trends derived in that manner agree very well with inventories.
Technical note: Measuring tropospheric OH and HO2 by laser-induced fluorescence at low pressure. A comparison of calibration techniques

The hydroxyl radical (OH) is one of the most important oxidants in the atmosphere, as it is involved in many reactions that affect regional air quality and global climate change. Because of its high reactivity, measurements of OH radical concentrations in the atmosphere are difficult, and often require careful calibrations that rely on the production of a known concentration of OH at atmospheric pressure. The Indiana University OH instrument, based on the Fluorescence Assay by Gas Expansion technique (FAGE), has been calibrated in the laboratory using two different approaches: the production of OH from the UV-photolysis of water-vapor, and the steady-state production of OH from the reaction of ozone with alkenes. The former technique relies on two different actinometric methods to measure the product of the lamp flux at 184.9 nm and the photolysis time. This quantity derived from N2O actinometry was found to be 1.5 times higher than that derived from O2 actinometry. The water photolysis and ozone-alkene techniques are shown to agree within their experimental uncertainties (respectively 17% and 44%), although the sensitivities derived from the ozone-alkene technique were systematically lower by 40% than those derived from the water-vapor UV- photolysis technique using O2 actinometry. The agreement between the two different methods improves the confidence of the water-vapor photolysis method as an accurate calibration technique for HOx instruments. Because several aspects of the mechanism of the gas phase ozonolysis of alkenes are still uncertain, this technique should be used with caution to calibrate OH instruments.
Quality assessment of water cycle parameters in REMO by radar-lidar synergy

A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better match with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study. Rain rates are similar, but the representativeness of both observations and grid box values is low.
Comparison of satellite limb-sounding humidity climatologies of the uppermost tropical troposphere

Humidity climatologies of the tropical uppermost troposphere from satellite limb emission measurements have been compared. Four instruments are considered; UARS-MLS, Odin-SMR, and Aura-MLS operating in the microwave region, and MIPAS in the infrared region. A reference for the comparison is obtained by MOZAIC in-situ measurements. The upper tropospheric humidity products were compared on basis of their empirical probability density functions and seasonally averaged horizontal fields at two altitude layers, 12 and 15 km. The probability density functions of the microwave datasets were found to be in very good agreement with each other, and were also consistent with MOZAIC. The average seasonal humidities differ with less than 10%RHi between the instruments, indicating that stated measurement accuracies of 20–30% are conservative estimates. The systematic uncertainty in Odin-SMR data due to cloud correction was also independently estimated to be 10%RHi. MIPAS humidity profiles were found to suffer from cloud contamination, with only 30% of the measurements reaching into the upper troposphere, but under clear-sky conditions there is a good agreement between MIPAS, Odin-SMR and Aura-MLS. Odin-SMR and the two MLS datasets can be treated as independent, being based on different underlying spectroscopy and technology. The good agreement between the microwave limb-sounders, and MOZAIC, is therefore an important step towards understanding the upper tropospheric humidity. The found accuracy of 10%RHi is approaching the level required to validate climate modelling of the upper troposphere humidity. The comparison of microwave and infrared also stresses that microwave limb-sounding is necessary for a complete view of the upper troposphere.