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A method for estimating the stratospheric particle size distribution from multiwavelength lidar measurements is presented. It is based on matching measured and model-simulated backscatter coefficients. The lidar backscatter coefficients measured at the three commonly used wavelengths 355, 532 and 1064 nm are compared to a precomputed look-up table of model-calculated values. The optical model assumes that particles are spherical and that their size distribution is unimodal. This inverse problem is not trivial because the optical model is highly non-linear with a strong sensitivity to the size distribution parameters in some cases. The errors in the lidar backscatter coefficients are explicitly taken into account in the estimation. The method takes advantage of the statistical properties of the possible solution cluster to identify the most probable size distribution parameters. In order to discard model-simulated outliers resulting from the strong non-linearity of the model, solutions farther than one standard deviation of the median values of the solution cluster are filtered out, because the most probable solution is expected to be in the densest part of the cluster. Within the filtered solution cluster, the estimation algorithm minimizes a cost function of the misfit between measurements and model simulations. <br><br> Two validation cases are presented on Polar Stratospheric Cloud (PSC) events detected above the ALOMAR observatory (69° N – Norway). A first validation is performed against optical particle counter measurements carried out in January 1996. In non-depolarizing regions of the cloud (i.e. spherical particles), the parameters of an unimodal size distribution and those of the optically dominant mode of a bimodal size distribution are quite successfully retrieved, especially for the median radius and the geometrical standard deviation. As expected, the algorithm performs poorly when solid particles drive the backscatter coefficient. A small bias is identified in modelling the refractive index when compared to previous works that inferred PSC type Ib refractive indices. The accuracy of the size distribution retrieval is improved when the refractive index is set to the value inferred in the reference paper. <br><br> Our results are then compared to values retrieved with another similar method that does not account for the effect of the measurements errors and the non-linearity of the optical model on the likelihood of the solution. The case considered is a liquid PSC observed over northern Scandinavia on January 2005. An excellent agreement is found between the two methods when our algorithm is applied without any statistical filtering of the solution cluster. However, the solution for the geometrical standard deviation appears to be rather unlikely with a value close to unity (σ≈1.04). When our algorithm is applied with solution filtering, a more realistic value of the standard deviation (σ≈1.27) is found. This highlights the importance of taking into account the non linearity of the model together with the lidar errors, when estimating particle size distribution parameters from lidar measurements.
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An intercomparison of different radiometric techniques measuring atmospheric photolysis frequencies <i>j</i>(NO<sub>2</sub>), <i>j</i>(HCHO) and <i>j</i>(O<sup>1</sup>D) was carried out in a two-week field campaign in June 2005 at Jülich, Germany. Three double-monochromator based spectroradiometers (DM-SR), three single-monochromator based spectroradiometers with diode-array detectors (SM-SR) and seventeen filter radiometers (FR) (ten <i>j</i>(NO<sub>2</sub>)-FR, seven <i>j</i>(O<sup>1</sup>D)-FR) took part in this comparison. For <i>j</i>(NO<sub>2</sub>), all spectroradiometer results agreed within ±3%. For <i>j</i>(HCHO), agreement was slightly poorer between −8% and +4% of the DM-SR reference result. For the SM-SR deviations were explained by poorer spectral resolutions and lower accuracies caused by decreased sensitivities of the photodiode arrays in a wavelength range below 350 nm. For <i>j</i>(O<sup>1</sup>D), the results were more complex within +8% and −4% with increasing deviations towards larger solar zenith angles for the SM-SR. The direction and the magnitude of the deviations were dependent on the technique of background determination. All <i>j</i>(NO<sub>2</sub>)-FR showed good linearity with single calibration factors being sufficient to convert from output voltages to <i>j</i>(NO<sub>2</sub>). Measurements were feasible until sunset and comparison with previous calibrations showed good long-term stability. For the <i>j</i>(O<sup>1</sup>D)-FR, conversion from output voltages to <i>j</i>(O<sup>1</sup>D) needed calibration factors and correction functions considering the influences of total ozone column and elevation of the sun. All instruments showed good linearity at photolysis frequencies exceeding about 10% of maximum values. At larger solar zenith angles, the agreement was non-uniform with deviations explainable by insufficient correction functions. Comparison with previous calibrations for some <i>j</i>(O<sup>1</sup>D)-FR indicated drifts of calibration factors.
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The Convective Storm Initiation Project (CSIP) took place during the summers of 2004 and 2005, centred on the research radar at Chilbolton, UK. Precursors to convective precipitation were studied, using a comprehensive and broad-based range of fieldwork and modelling. The principal aim of CSIP was the detection of the primary and secondary initiation of convective cells. The Universities Facility for Atmospheric Measurements (UFAM) Cessna 182 was used to map temperature and humidity fields over a broad area within and beyond the Chilbolton radar beam. Additionally, air motion was measured using a new turbulence probe, the AIMMS20AQ. The performance of the probe is critically appraised, based on calibrations, test flights and data flights flown during CSIP intensive operating periods. In general, the probe performed well, although some aspects require more careful data interpretation which we describe in detail.
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Atmospheric water vapour is highly variable both in space and time. In an operational sense, only radiosonde provide vertical information on water vapour. Radiosondes are generally launched two to four times per day at synoptic times and sample primarily synoptic scales. For nowcasting purposes these observations are very valuable but obviously lose their importance with elapsing time. Water vapour observations from a surface network of Global Positioning System (GPS) receivers can fill this information gap. In this paper, a GPS network is used to observe integral water vapour quantities along the line of sight, so-called Slant Water Vapour (SWV). Using a variational technique (3DVAR) a three-dimensional water vapour field is reconstructed and its performance is investigated by assimilating SWV observations deduced from a simulated atmosphere (so-called nature run). The forecasts from a high resolution limited area model (HIRLAM) embedded in the synthetic atmosphere of the nature run is compared to the separate GPS-3DVAR estimates. This experiment showed that assimilation of SWV resulted in a smaller bias and standard deviation than the HIRLAM forecast with the nature run. Besides simulated data, real SWV observations are used to assess impact. Two experiments were conducted; one with a HIRLAM six hour forecast as a background field (updated every six hours) and one with persistence as background (updated every hour). The first experiment showed a reduction of the bias between radiosonde observations compared to HIRLAM forecast. The second experiment, which has no information inherited from HIRLAM, showed to have smaller biases with independent radiosonde observations than the HIRLAM analysis. The used network, however was too sparse to detect water vapour inversions correctly.
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We studied the OH oxidation of submicron aerosol particles consisting of pure palmitic acid (PA) or thin (near monolayer) coatings of PA on aqueous and effloresced inorganic salt particles. Experiments were performed as a function of particle size and OH exposure using a continuous-flow photochemical reaction chamber coupled to a chemical ionization mass spectrometer (CIMS) system, for detection of gas and particle-bound organics, and a DMA/CPC for monitoring particle size distributions. The loss rate of PA observed for pure PA aerosols and PA on crystalline NaCl aerosols indicates that the OH oxidation of PA at the gas-aerosol interface is efficient. The pure PA oxidation data are well represented by a model consisting of four main processes: 1) surface-only reactions between OH and palmitic acid, 2) secondary reactions between palmitic acid and OH oxidation products, 3) volatilization of condensed-phase mass, and 4) a surface renewal process. Using this model we infer a value of γ<sup>OH</sup> between 0.8 and 1. The oxidation of palmitic acid in thin film coatings of salt particles is also efficient, though the inferred γ<sup>OH</sup> is lower, ranging from ~0.3+0.1/−0.05) for coatings on solid NaCl and ~0.05 (±0.01) on aqueous NaCl particles. These results, together with simultaneous data on particle size change and volatilized oxidation products, provide support for the ideas that oxidative aging of aliphatic organic aerosol is a source of small oxidized volatile organic compounds (OVOCs), and that OH oxidation may initiate secondary condensed-phase reactions.
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We report an extensive airborne characterization of aerosol downwind of a massive bovine source in the San Joaquin Valley (California) on two flights during July 2007. The Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter probed chemical composition, particle size distribution, mixing state, sub- and supersaturated water uptake behavior, light scattering properties, and the interrelationship between these parameters and meteorology. Total PM<sub>1.0</sub> levels and concentrations of organics, nitrate, and ammonium were enhanced in the plume from the source as compared to the background aerosol. Organics dominated the plume aerosol mass (~56–64%), followed either by sulfate or nitrate, and then ammonium. Particulate amines were detected in the plume aerosol by a particle-into-liquid sampler (PILS) and via mass spectral markers in the Aerodyne C-ToF-AMS. Amines were found to be a significant atmospheric base even in the presence of ammonia; particulate amine concentrations are estimated as at least 14–23% of that of ammonium in the plume. Enhanced sub- and supersaturated water uptake and reduced refractive indices were coincident with lower organic mass fractions, higher nitrate mass fractions, and the detection of amines. The likelihood of suppressed droplet growth owing to kinetic limitations from hydrophobic organic material is explored. After removing effects associated with size distribution and mixing state, the normalized activated fraction of cloud condensation nuclei (CCN) increased as a function of the subsaturated hygroscopic growth factor, with the highest activated fractions being consistent with relatively lower organic mass fractions and higher nitrate mass fractions. Subsaturated hygroscopic growth factors for the organic fraction of the aerosol are estimated based on employing the Zdanovskii-Stokes Robinson (ZSR) mixing rule. Representative values for a parameterization treating particle water uptake in both the sub- and supersaturated regimes are reported for incorporation into atmospheric models.
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The representation of data, whether geophysical observations, numerical model output or laboratory results, by a best fit straight line is a routine practice in the geosciences and other fields. While the literature is full of detailed analyses of procedures for fitting straight lines to values with uncertainties, a surprising number of scientists blindly use the standard least-squares method, such as found on calculators and in spreadsheet programs, that assumes no uncertainties in the <i>x</i> values. Here, the available procedures for estimating the best fit straight line to data, including those applicable to situations for uncertainties present in both the <i>x</i> and <i>y</i> variables, are reviewed. Representative methods that are presented in the literature for bivariate weighted fits are compared using several sample data sets, and guidance is presented as to when the somewhat more involved iterative methods are required, or when the standard least-squares procedure would be expected to be satisfactory. A spreadsheet-based template is made available that employs one method for bivariate fitting.
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The nitrate radical (NO<sub>3</sub>) has been detected in visible limb-scattered spectra measured by the Optical Spectrograph and InfraRed Imager System (OSIRIS) on-board the Odin satellite when observing at large solar zenith angles (91–97°). Apparent slant column densities of NO<sub>3</sub> at tangent heights between 10 and 45 km are derived via spectral fitting in the 610–680 nm window. Using observations from multiple scans spanning solar zenith angles of 91–97°, the rapid evolution of NO<sub>3</sub> through sunrise and sunset can be traced. Slant column densities are found to be generally consistent with those simulated using a radiative transfer model with coupled photochemistry. In addition, a strong dependence of NO<sub>3</sub> with temperature is observed. These results indicate that our current knowledge of NO<sub>3</sub> photochemistry is generally consistent with OSIRIS observations to within the limitations of the radiative transfer modeling. Furthermore, they reveal that OSIRIS possesses signal-to-noise sufficient to make useful measurements of scattered sunlight out to solar zenith angles of 91–97° and suggest the possibility of retrieving profile information for NO<sub>3</sub> and other species at large solar zenith angles.
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