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An optical particle counter (OPC) is used in conjunction with lidar measurements to examine the characteristics of the particle size distribution in cirrus cloud in the tropical tropopause layer (TTL) over Thailand where the TTL is defined as the height at which temperature is lower than −75°C in this paper. Of 11 OPC launches, cirrus cloud was detected at 10–15 km high on 7 occasions, cirrus was detected in the TTL in 6 cases, and simultaneous OPC and lidar measurements were made on two occasions. Comparison of lidar and OPC measurements reveal that the cloud heights of cirrus in the TTL varies by several hundred meters over distances of tens kilometers; hence the height is not always horizontally uniform. The mode radii of particles constituting the clouds are estimated by lidar and OPC measurements to be less than approximately 10 μm. The regression lines of the particle size distribution with and without cirrus cloud exhibit similar features at equivalent radii of <0.8 μm. Enhancement in the integrated number concentration at radii greater than 0.8 μm indicates that liquid particles tend to be frozen at a radius of 0.8 μm, with cirrus clouds above 10 km exhibiting similar features. On the other hand, enhancement in the particle size distribution at radii greater than 0.9 μm and a peak at around 0.8 μm in the ratio of the standard deviation of count values to that of the Poisson distribution of the averaged count values are common features of cirrus clouds in the TTL, where the ratio shows the vertical homogeneity of the particle number. These typical features suggest that the transition from liquid, sulfuric acid aerosol, to ice is more observable in the TTL and the timing of freezing may vary with height in the TTL.
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There have been numerous recent publications showing that mineral dust might be a good absorber for solar radiation in addition to its capability to act as cloud condensation nuclei (CCN) and ice forming nuclei (IFN), and could lead to reduced cloud cover and precipitation in the region where it is present. This effect is investigated using a dynamic cloud model with detailed microphysics of both warm and ice phase processes. The model is initialized using measured size distributions and concentrations of mineral dust particles. Our results show that when dust appears at the cloud-base height and below 3 km, where the temperature is warmer than −5°C, the heating induced by the presence of dust layers can inhibit the formation of cloud droplets and suppresses the development of precipitation, leading to lower cloud optical depth and albedo. On the other hand, when the dust layers are located at altitudes with temperature colder than −5°C, or above the −5°C level, mineral aerosols can act as effective ice nuclei, intensify the ice-forming processes, and may enhance the development of cloud and precipitation. It is also found that the heating effect is more pronounced in continental clouds than in maritime clouds.
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This study describes and evaluates a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval scheme particularly aimed at delivering bias-free atmospheric parameters for climate monitoring and research. The focus of the retrieval is on the sensible use of a priori information for careful high-altitude initialisation in order to maximise the usable altitude range. The RO retrieval scheme has been meanwhile applied to more than five years of data (September 2001 to present) from the German CHAllenging Minisatellite Payload for geoscientific research (CHAMP) satellite. In this study it was validated against various correlative datasets including the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Global Ozone Monitoring for Occultation of Stars (GOMOS) sensors on Envisat, five different atmospheric analyses, and the operational CHAMP retrieval product from GeoForschungsZentrum (GFZ) Potsdam. In the global mean within 10 to 30 km altitude we find that the present validation observationally constrains the potential RO temperature bias to be <0.2 K. Latitudinally resolved analyses show biases to be observationally constrained to <0.2–0.5 K up to 35 km in most cases, and up to 30 km in any case, even if severely biased (about 10 K or more) a priori information is used in the high altitude initialisation of the retrieval. No evidence is found for the 10–35 km altitude range of residual RO bias sources other than those potentially propagated downward from initialisation, indicating that the widely quoted RO promise of "unbiasedness and long-term stability due to intrinsic self-calibration" can indeed be realised given care in the data processing to strictly limit structural uncertainty. The results thus reinforce that adequate high-altitude initialisation is crucial for accurate stratospheric RO retrievals. The common method of initialising, at some altitude in the upper stratosphere, the hydrostatic integral with an upper boundary temperature or pressure value derived from meteorological analyses is prone to introduce biases from the upper boundary down to below 25 km. Also above 30 to 35 km, GNSS RO delivers a considerable amount of observed information up to around 40 km, which is particularly interesting for numerical weather prediction (NWP) systems, where direct assimilation of non-initialised observed RO bending angles (free of a priori) is thus the method of choice. The results underline the value of RO for climate applications.
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Classical error analysis in remote sounding distinguishes between four classes: "smoothing errors," "model parameter errors," "forward model errors," and "retrieval noise errors". For infrared sounding "interference errors", which, in general, cannot be described by these four terms, can be significant. Interference errors originate from spectral residuals due to "interfering species" whose spectral features overlap with the signatures of the target species. A general method for quantification of interference errors is presented, which covers all possible algorithmic implementations, i.e., fine-grid retrievals of the interfering species or coarse-grid retrievals, and cases where the interfering species are not retrieved. In classical retrieval setups interference errors can exceed smoothing errors and can vary by orders of magnitude due to state dependency. An optimum strategy is suggested which practically eliminates interference errors by systematically minimizing the regularization strength applied to joint profile retrieval of the interfering species. This leads to an interfering-species selective deweighting of the retrieval. Details of microwindow selection are no longer critical for this optimum retrieval and widened microwindows even lead to reduced overall (smoothing and interference) errors. Since computational power will increase, more and more operational algorithms will be able to utilize this optimum strategy in the future. The findings of this paper can be applied to soundings of all infrared-active atmospheric species, which include more than two dozen different gases relevant to climate and ozone. This holds for all kinds of infrared remote sounding systems, i.e., retrievals from ground-based, balloon-borne, airborne, or satellite spectroradiometers.
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We investigate the effect of using three different cross section data sets on ozone profile retrievals from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements (289–307 nm, 326–337 nm). These include Bass-Paur, Brion, and GOME flight model cross sections (references below). Using different cross sections can significantly affect the retrievals, by up to 12 Dobson Units (DU, 1 DU=2.69×10<sup>16</sup> molecules cm<sup>−2</sup>) in total column ozone, up to 10 DU in tropospheric column ozone, and up to 100% in retrieved ozone values for individual atmospheric layers. Compared to using the Bass-Paur and GOME flight model cross sections, using the Brion cross sections not only reduces fitting residuals by 15–60% in the Huggins bands, but also improves retrievals, especially in the troposphere, as seen from validation against ozonesonde measurements. Therefore, we recommend using the Brion cross section for ozone profile retrievals from ultraviolet measurements. The total column ozone retrieved using the GOME flight model cross sections is systematically lower, by 7–10 DU, than that retrieved using the Brion and Bass-Paur cross sections and is also systematically lower than Total Ozone Mapping Spectrometer (TOMS) observations. This study demonstrates the need for improved ozone cross section measurements in the ultraviolet to improve profile retrievals of this key atmospheric constituent.
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The reactivity of aromatic compounds is of great relevance to pure and applied chemical disciplines, yet existing methods for estimating gas-phase rate coefficients for their reactions with free radicals lack accuracy and universality. Here a novel approach is taken, whereby strong relationships between rate coefficients of aromatic hydrocarbons and a Randić-type topological index are investigated, optimized and developed into a method which requires no specialist software or computing power. <br><br> Measured gas-phase rate coefficients for the reaction of aromatic hydrocarbons with OH radicals were correlated with a calculated Randić-type index, and optimized by including a term for side chain length. Although this method is exclusively for use with hydrocarbons, it is more diverse than any single existing methodology since it incorporates alkenylbenzenes into correlations, and can be extended towards other radical species such as O(<sup>3</sup><i>P</i>) (and tentatively NO<sub>3</sub>, H and Cl). A comparison (with species common to both techniques) is made between the topological approach advocated here and a popular approach based on electrophilic subsituent constants, where it compares favourably. <br><br> A modelling study was carried out to assess the impact of using estimated rate coefficients as opposed to measured data in an atmospheric model. The difference in model output was negligible for a range of NO<sub>x</sub> concentrations, which implies that this method has utility in complex chemical models. <br><br> Strong relationships (e.g. for OH, <i>R</i><sup>2</sup>=0.96) between seemingly diverse compounds including benzene, multisubstituted benzenes with saturated, unsaturated, aliphatic and cyclic substitutions and the nonbenzenoid aromatic, azulene suggests that the Randić-type index presented here represents a new and effective way of describing aromatic reactivity, based on a quantitative structure-activity relationship (QSAR).
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The results from a simulation chamber study on the formaldehyde (HCHO) absorption cross section in the UV spectral region are presented. We performed 4 experiments at ambient HCHO concentrations with simultaneous measurements of two DOAS instruments in the atmosphere simulation chamber SAPHIR in Jülich. The two instruments differ in their spectral resolution, one working at 0.2 nm (broad-band, BB-DOAS), the other at 2.7 pm (high-resolution, HR-DOAS). Both instruments use dedicated multi reflection cells to achieve long light path lengths of 960 m and 2240 m, respectively, inside the chamber. During two experiments HCHO was injected into the clean chamber by thermolysis of well defined amounts of para-formaldehyde reaching mixing rations of 30 ppbV at maximum. The HCHO concentration calculated from the injection and the chamber volume agrees with the BB-DOAS measured value when the absorption cross section of Meller and Moortgat (2000) and the temperature coefficient of Cantrell (1990) were used for data evaluation. In two further experiments we produced HCHO in-situ from the ozone + ethene reaction which was intended to provide an independent way of HCHO calibration through the measurements of ozone and ethene. However, we found an unexpected deviation from the current understanding of the ozone + ethene reaction when CO was added to suppress possible oxidation of ethene by OH radicals. The reaction of the Criegee intermediate with CO could be 240 times slower than currently assumed. Based on the BB-DOAS measurements we could deduce a high-resolution cross section for HCHO which was not measured directly so far.
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Satellite observations of atmospheric CO<sub>2</sub> offer the potential to identify regional carbon surface sources and sinks and to investigate carbon cycle processes. The extent to which satellite measurements are useful however, depends on the near surface sensitivity of the chosen sensor. In this paper, the capability of the SCIAMACHY instrument on board ENVISAT, to observe lower tropospheric and surface CO<sub>2</sub> variability is examined. To achieve this, atmospheric CO<sub>2</sub> retrieved from SCIAMACHY near infrared (NIR) spectral measurements, using the Full Spectral Initiation (FSI) WFM-DOAS algorithm, is compared to in-situ aircraft observations over Siberia and additionally to tower and surface CO<sub>2</sub> data over Mongolia, Europe and North America. <br><br> Preliminary validation of daily averaged SCIAMACHY/FSI CO<sub>2</sub> against ground based Fourier Transform Spectrometer (FTS) column measurements made at Park Falls, reveal a negative bias of about −2.0% for collocated measurements within ±1.0° of the site. However, at this spatial threshold SCIAMACHY can only capture the variability of the FTS observations at monthly timescales. To observe day to day variability of the FTS observations, the collocation limits must be increased. Furthermore, comparisons to in-situ CO<sub>2</sub> observations demonstrate that SCIAMACHY is capable of observing a seasonal signal that is representative of lower tropospheric variability on (at least) monthly timescales. Out of seventeen time series comparisons, eleven have correlation coefficients of 0.7 or more, and have similar seasonal cycle amplitudes. Additional evidence of the near surface sensitivity of SCIAMACHY, is provided through the significant correlation of FSI derived CO<sub>2</sub> with MODIS vegetation indices at over twenty selected locations in the United States. The SCIAMACHY/MODIS comparison reveals that at many of the sites, the amount of CO<sub>2</sub> variability is coincident with the amount of vegetation activity. The presented analysis suggests that SCIAMACHY has the potential to detect CO<sub>2</sub> variability within the lowermost troposphere arising from the activity of the terrestrial biosphere.
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Reliable reference profiles and estimates of variability are a necessity for a variety of processes relating to ENVISAT including the development of key aspects and inputs for the operational processor for the Michelson Interferometer for Passive Atmospheric Sounding. MIPAS reference atmospheres have therefore been produced in two forms, namely standard atmospheres for modelling and error analysis for typical atmospheric situations and the IG2 seasonal climatologies for initial guess profiles used as part of the operational processing. The reference states cover 36 species on a common altitude, pressure, and temperature grid from 0 to 120 km, and include both means and estimates of variability (maximum, minimum and one sigma values). This paper describes V3.1 of the standard atmospheres and V4.0 of the IG2 atmospheres which are the current versions of the reference atmospheres. Particular attention is paid to the MIPAS operational geophysical products (pressure/temperature, H<sub>2</sub>O, O<sub>3</sub>, CH<sub>4</sub>, N<sub>2</sub>O, HNO<sub>3</sub> and NO<sub>2</sub>) and to CO<sub>2</sub> whose mixing ratio is required for the retrieval of pressure and temperature. A dynamic representation of CO<sub>2</sub> is presented which shows the presence of CO<sub>2</sub> gradients in the troposphere and the lower stratosphere. <br><br> Since these atmospheres have been produced independently of MIPAS data, it is also possible to compare the data to the MIPAS operational products and derive valuable information on both the reference atmospheres and on MIPAS data products themselves. This process has been performed for V4.61/V4.62 data from the year 2003 as part of the MIPAS validation activity. It is demonstrated that the agreement between the MIPAS mean data and the reference atmospheres is very good in mid-latitudes and the tropics, verifying these data to first order. There is also reasonable agreement in standard deviations between the IG2 atmospheres and the corresponding sigmas calculated from the MIPAS data. Knowledge of tropospheric concentrations of CH<sub>4</sub> and N<sub>2</sub>O is used to examine the accuracy of the MIPAS data and their susceptibility to cloud effects. It is shown that for the highest accuracy, MIPAS data should be filtered with cloud index values of 2.5 for N<sub>2</sub>O and 3.5 for CH<sub>4</sub>. Once such filtering has been performed, the MIPAS data for these species appear to be accurate to within 10% in the upper troposphere. The use of cloud index data in combination with MIPAS data is recommended for studies of the polar winter stratosphere and the upper troposphere/lower stratosphere.
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This paper characterizes vertical ozone profiles retrieved with the IMK-IAA (Institute for Meteorology and Climate Research, Karlsruhe – Instituto de Astrofisica de Andalucia) science-oriented processor from high spectral resolution data (until March 2004) measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the environmental satellite Envisat. Bias determination and precision validation is performed on the basis of correlative measurements by ground-based lidars, Fourier transform infrared spectrometers, and microwave radiometers as well as balloon-borne ozonesondes, the balloon-borne version of MIPAS, and two satellite instruments (Halogen Occultation Experiment and Polar Ozone and Aerosol Measurement III). Percentage mean differences between MIPAS and the comparison instruments for stratospheric ozone are generally within ±10%. The precision in this altitude region is estimated at values between 5 and 10% which gives an accuracy of 15 to 20%. Below 18 km, the spread of the percentage mean differences is larger and the precision degrades to values of more than 20% depending on altitude and latitude. The main reason for the degraded precision at low altitudes is attributed to undetected thin clouds which affect MIPAS retrievals, and to the influence of uncertainties in the water vapor concentration.
