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Fast convective transport in the tropics can efficiently redistribute water vapour and pollutants up to the upper troposphere. In this study we compare tropical convection characteristics for the year 2005 in a range of atmospheric models, including numerical weather prediction (NWP) models, chemistry transport models (CTMs), and chemistry-climate models (CCMs). The model runs have been performed within the framework of the SCOUT-O3 (Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere) project. The characteristics of tropical convection, such as seasonal cycle, land/sea contrast and vertical extent, are analysed using satellite observations as a benchmark for model simulations. The observational datasets used in this work comprise precipitation rates, outgoing longwave radiation, cloud-top pressure, and water vapour from a number of independent sources, including ERA-Interim analyses. Most models are generally able to reproduce the seasonal cycle and strength of precipitation for continental regions but show larger discrepancies with observations for the Maritime Continent region. The frequency distribution of high clouds from models and observations is calculated using highly temporally-resolved (up to 3-hourly) cloud top data. The percentage of clouds above 15 km varies significantly between the models. Vertical profiles of water vapour in the upper troposphere-lower stratosphere (UTLS) show large differences between the models which can only be partly attributed to temperature differences. If a convective plume reaches above the level of zero net radiative heating, which is estimated to be ~15 km in the tropics, the air detrained from it can be transported upwards by radiative heating into the lower stratosphere. In this context, we discuss the role of tropical convection as a precursor for the transport of short-lived species into the lower stratosphere.
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The Yellow Sea, surrounded by East China and the Korea Peninsula, is a potentially important receptor for anthropogenic mercury (Hg) emissions from East Asia. However, there is little documentation about the distribution and cycle of Hg in this marine system. During the cruise covering the Yellow Sea in July 2010, gaseous elemental mercury (GEM or Hg(0)) in the atmosphere, total Hg (THg), reactive Hg (RHg) and dissolved gaseous mercury (DGM, largely Hg(0)) in the waters were measured aboard the <i>R/V Kexue III</i>. The mean (±SD) concentration of GEM over the entire cruise was 2.61 ± 0.50 ng m<sup>−3</sup> (range: 1.68 to 4.34 ng m<sup>−3</sup>), which were generally higher than other open oceans. The spatial distribution of GEM generally reflected a clear gradient with high levels near the coast of East China and low levels in open waters, suggesting the significant atmospheric Hg outflow from East China. The mean concentration of THg in the surface waters was 1.69 ± 0.35 ng l<sup>−1</sup> and the RHg accounted for a considerable fraction of THg (RHg: 1.08 ± 0.28 ng l<sup>−1</sup>, %RHg/THg = 63.9%). The mean concentration of DGM in the surface waters was 63.9 ± 13.7 pg l<sup>−1</sup> and always suggested the supersaturation of Hg(0) in the surface waters with respect to Hg(0) in the atmosphere (the degree of saturation: 7.8 ± 2.3 with a range of 3.6–14.0). The mean Hg(0) flux at the air-sea interface was estimated to be 18.3 ± 11.8 ng m<sup>−2</sup> h<sup>−1</sup> based on a two-layer exchange model. The high wind speed and DGM levels induced the extremely high Hg(0) emission rates. Measurements at three stations showed no clear vertical patterns of DGM, RHg and THg in the water column. Overall, the elevated Hg levels in the Yellow Sea compared with other open oceans suggested that the human activity has influenced the oceanic Hg cycle downwind of East Asia.
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Carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) are the two most important anthropogenic greenhouse gases contributing to global climate change. SCIAMACHY onboard ENVISAT (launch 2002) was the first and is now with TANSO onboard GOSAT (launch 2009) one of only two satellite instruments currently in space whose measurements are sensitive to CO<sub>2</sub> and CH<sub>4</sub> concentration changes in the lowest atmospheric layers where the variability due to sources and sinks is largest. <br><br> We present long-term SCIAMACHY retrievals (2003–2009) of column-averaged dry air mole fractions of both gases (denoted XCO<sub>2</sub> and XCH<sub>4</sub>) derived from absorption bands in the near-infrared/shortwave-infrared (NIR/SWIR) spectral region focusing on large-scale features. The results are obtained using an upgraded version (v2) of the retrieval algorithm WFM-DOAS including several improvements, while simultaneously maintaining its high processing speed. The retrieved mole fractions are compared to global model simulations (CarbonTracker XCO<sub>2</sub> and TM5 XCH<sub>4</sub>) being optimised by assimilating highly accurate surface measurements from the NOAA/ESRL network and taking the SCIAMACHY averaging kernels into account. The comparisons address seasonal variations and long-term characteristics. <br><br> The steady increase of atmospheric carbon dioxide primarily caused by the burning of fossil fuels can be clearly observed with SCIAMACHY globally. The retrieved global annual mean XCO<sub>2</sub> increase agrees with CarbonTracker within the error bars (1.80±0.13 ppm yr<sup>−1</sup> compared to 1.81±0.09 ppm yr<sup>−1</sup>). The amplitude of the XCO<sub>2</sub> seasonal cycle as retrieved by SCIAMACHY, which is 4.3±0.2 ppm for the Northern Hemisphere and 1.4±0.2 ppm for the Southern Hemisphere, is on average about 1 ppm larger than for CarbonTracker. <br><br> An investigation of the boreal forest carbon uptake during the growing season via the analysis of longitudinal gradients shows good agreement between SCIAMACHY and CarbonTracker concerning the overall magnitude of the gradients and their annual variations. The analysis includes a discussion of the relative uptake strengths of the Russian and North American boreal forest regions. <br><br> The retrieved XCH<sub>4</sub> results show that after years of stability, atmospheric methane has started to rise again in recent years which is consistent with surface measurements. The largest increase is observed for the tropics and northern mid- and high-latitudes amounting to about 7.5±1.5 ppb yr<sup>−1</sup> since 2007. Due care has been exercised to minimise the influence of detector degradation on the quantitative estimate of this anomaly.
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The relative roles of volume and surface nucleation were investigated for the homogeneous freezing of pure water droplets. Experiments were carried out in a cryogenic laminar aerosol flow tube using supercooled water aerosols with maximum volume densities at radii between 1 and 3 μm. Temperature- and size-dependent values of volume- and surface-based homogeneous nucleation rates between 234.8 and 236.2 K were derived using a microphysical model and aerosol phase compositions and size distributions determined from infrared extinction measurements in the flow tube. The results show that the contribution from nucleation at the droplet surface increases with decreasing droplet radius and dominates over nucleation in the bulk droplet volume for droplets with radii smaller than approximately 5 μm. This is interpreted in terms of a lowered free energy of ice germ formation in the surface-based process. The implications of surface nucleation for the parameterization of homogeneous ice nucleation in numerical models are considered.
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Means, standard deviations, homogeneity parameters used in models based on their ratio, and the probability distribution functions (PDFs) of cloud properties from the MODerate resolution Infrared Spectrometer (MODIS) are estimated globally as function of averaging scale varying from 5 to 500 km. The properties – cloud fraction, droplet effective radius, and liquid water path – all matter for cloud-climate uncertainty quantification and reduction efforts. Global means and standard deviations are confirmed to change with scale. For the range of scales considered, global means vary only within 3% for cloud fraction, 7% for liquid water path, and 0.2% for cloud particle effective radius. These scale dependences contribute to the uncertainties in their global budgets. Scale dependence for standard deviations and generalized flatness are compared to predictions for turbulent systems. Analytical expressions are identified that fit best to each observed PDF. While the best analytical PDF fit to each variable differs, <i>all</i> PDFs are well described by log-normal PDFs when the mean is normalized by the standard deviation inside each averaging domain. Importantly, log-normal distributions yield significantly better fits to the observations than gaussians at all scales. This suggests a possible approach for both sub-grid and unified stochastic modeling of these variables at all scales. The results also highlight the need to establish an adequate spatial resolution for two-stream radiative studies of cloud-climate interactions.
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Size and time-resolved roadside enrichments of atmospheric particulate pollutants in PM<sub>10</sub> were detected and quantified in a Mediterranean urban environment (Barcelona, Spain). Simultaneous data from one urban background (UB), one traffic (T) and one heavy traffic (HT) location were analysed, and roadside PM<sub>10</sub> enrichments (RE) in a number of elements arising from vehicular emissions were calculated. Tracers of primary traffic emissions (EC, Fe, Ba, Cu, Sb, Cr, Sn) showed the largest REs (>70%). Other traffic tracers (Zr, Cd) showed lower but still consistent REs (25–40%), similar to those obtained for mineral matter resulting from road dust resuspension (Ca, La, Ce, Ti, Ga, Sr, 30–40%). The sum of primary and secondary organic carbon showed a RE of 41%, with contributions of secondary OC (SOC) to total OC ranging from 46% at the HT site, 63% at the T site, and 78% in the UB. Finally, other trace elements (As, Co, Bi) showed unexpected but consistent roadside enrichments (23% up to 69%), suggesting a link to traffic emissions even though the emission process is unclear. <br><br> Hourly-resolved PM speciation data proved to be a highly resourceful tool to determine the source origin of atmospheric pollutants in urban environments. At the HT site, up to 62% of fine Mn was attributable to industrial plumes, whereas coarse Mn levels were mainly attributed to traffic. Similarly, even though Zn showed on average no roadside enrichment and thus was classified as industrial, the hourly-resolved data proved that at least 15% of coarse Zn may be attributed to road traffic emissions. In addition, our results indicate that secondary nitrate formation occurs within the city-scale, even in the absence of long atmospheric residence times or long-range atmospheric transport processes. Characteristic tracer ratios of road traffic emissions were identified: Cu/Sb = 6.8–8.0, Cu/Sn = 4.7–5.4 and Sn/Sb = 1.5.
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A method is developed based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) level 1 attenuated backscatter profile data for deriving the mean extinction coefficient of water droplets close to cloud top. The method is applicable to low level (cloud top <2 km), opaque water clouds in which the lidar signal is completely attenuated beyond about 100 m of penetration into the cloud. The photo multiplier tubes (PMTs) of the 532 nm detectors (parallel and perpendicular polarizations) of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) both exhibit a non-ideal recovery of the lidar signal after striking a strongly backscattering target (such as water cloud or surface). Therefore, the effects of any transient responses of CALIOP on the attenuated backscatter profile of the water cloud must first be removed in order to obtain a reliable (validated) attenuated backscatter profile. Then, the slope of the exponential decay of the validated water cloud attenuated backscatter profile, and the multiple scattering factor are used for deriving the mean extinction coefficient of low-level water cloud droplets close to cloud top. This novel method was evaluated and compared with the previous method which combined the cloud effective radius (3.7-μm) reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate the mean extinction coefficient. Statistical results show that the extinction coefficients derived by the new method based on CALIOP alone agree reasonbably well with those obtained in the previous study using combined CALIOP and MODIS data. The mean absolute relative difference in extinction coefficient is about 13.4%. An important advantage of the new method is that it can be used to derive the extinction coefficient also during night time, and it is also applicable when multi-layered clouds are present. Overall, the stratocumulus dominated regions experience larger day-night differences which are all negative and seasonal. However, a contrary tendency consisted in the global mean values. The global mean cloud water extinction coefficients during different seasons range from 26 to 30 km<sup>−1</sup>, and the differences between day and night time are all positive and small (about 1–2 km<sup>−1</sup>). In addition, the global mean layer-integrated depolarization ratios of liquid water clouds during different seasons range from 0.2 to 0.23, and the differences between day and night also are small, about 0.01.
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In situ measurements of acyl peroxy nitrates (PANs), including peroxyacetyl nitrate (PAN), peroxypropionyl nitrate (PPN), and peroxymethacryloyl nitrate (MPAN), were conducted using a gas chromatography-electron capture detector (GC-ECD) system during the photochemical smog season in Beijing, China. The maximum mixing ratios were 17.81, 2.48, and 0.27 ppbv for PAN, PPN, and MPAN, respectively. During the measurement period, PAN levels twice exceeded the maximum recommended mixing ratio established by the World Health Organization (WHO). Average ratios of PAN/PPN, PAN/MPAN, and PPN/MPAN were 7.41, 47.65, and 6.91, respectively. The average ratio of PAN/O<sub>3</sub> (0.15) in Beijing was significantly higher than those in other areas studied. The frequencies of PANs showed both Gaussian and Weibull modes of distribution. Wind direction was closely related to PAN variation. Anthropogenic sources played an important role in PAN formation, as estimated from PPN and MPAN levels. Relative humidity (RH) and total particle surface area were related with the heterogeneous reactions of PANs with surface concentrations of particulate matter ≤10 μm in diameter.
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Mesoscale modeling of the urban boundary layer requires careful parameterization of the surface due to its heterogeneous morphology. Model estimated meteorological quantities, including the surface energy budget and canopy layer variables, will respond accordingly to the scale of representation. This study examines the sensitivity of the surface energy balance, canopy layer and boundary layer meteorology to the scale of urban surface representation in a real urban area (Detroit-Windsor (USA-Canada)) during several dry, cloud-free summer periods. The model used is the Weather Research and Forecasting (WRF) model with its coupled single-layer urban canopy model. Some model verification is presented using measurements from the Border Air Quality and Meteorology Study (BAQS-Met) 2007 field campaign and additional sources. Case studies span from "neighborhood" (10 s ~308 m) to very coarse (120 s ~3.7 km) resolution. Small changes in scale can affect the classification of the surface, affecting both the local and grid-average meteorology. Results indicate high sensitivity in turbulent latent heat flux from the natural surface and sensible heat flux from the urban canopy. Small scale change is also shown to delay timing of a lake-breeze front passage and can affect the timing of local transition in static stability.
