Yu. M. Timofeyev

A SIMPLE MODEL OF THE LINE MIXING EFFECT FOR ATMOSPHERIC APPLICATIONS: THEORETICAL BACKGROUND AND COMPARISON WITH EXPERIMENTAL PROFILES

We propose a new empirical method of band shape calculations which takes into account line mixing effects. The proposed shape is based on the strong collision model with attenuated interbranch coupling. Apart from the conventional set of spectral line parameters one needs only one additional parameter to account for line mixing effects in band profile calculations. This parameter depends on the perturbing gas type. It is the same for all molecular infrared absorption bands. The new shapes are shown to be successful in representing the measured absorption bands of CO2 in nitrogen (v2, v3, v2 + 2v3, 2v2 − v2, and 2v1 − v2) and the 3.6 μm band of O3 in nitrogen.

Numerical investigations of the accuracy of the remote sensing of non-LTE atmosphere by space-borne spectral measurements of limb i.r. radiation: 15 μm CO2 bands, 9.6 μm O3 bands and 10 μm CO2 laser bands

Abstract Inverse problems of the remote sensing of the atmosphere are formulated for the general case of an optically thick atmosphere under non-local thermodynamic equilibrium condition for the space-borne spectral measurements of the limb i.r. radiation. A feasibility study of the retrieval of the vertical profiles of different atmospheric parameters [vibrational (Tν) and kinetic (Tkin) temperatures, concentration of the absorbing gases, pressure] has been carried out by means of the error matrix calculations (optimal estimation method) for different spectral intervals of measurements (15 μm CO2 bands, 9.6 μm O3 bands and 10 μm CO2 laser bands), different spectral resolutions Δν and wide range of noise equivalent radiance (NER) values. It has been shown that limb radiation spectral measurements, for example, in 15 μm CO2 band (Δν = 1 cm−1, NER corresponding to MIPAS interferometer) enable the retrieval of Tv for CO2 states 0110, 0200, 0220, 1000 with an error less than half of the a priori uncertainty up to 112.5, 100, 102.5 and 100 km, respectively. Limb radiation measurements in the 9.6 μm O3 band make it possible to retrieve, with an accuracy about 10–30% of the a priori uncertainty, the vertical profile of the ozone concentration up to 65–90 km depending on the NER value, Δν and atmospheric model. The lower limit retrieval errors for O3 vibrational temperatures strongly depend on NER, Δν and the vibrational state under consideration, especially in the layers higher than 65 km. More than 50% decrease of a priori uncertainties (an error less than 25 K) is observed for the states of O3 molecule 001, 100, 011, 003, 012 up to 102, 94, 93, 92, 90 km, respectively (for Δν = 2.5 cm−1 and NER 10 times lower than one for MIPAS). Limb radiation measurements yield a considerable decrease (50–80%) of the a priori uncertainty of the pressure profile in the height range 30–60 km. If Tkin is considered as an independent unknown variable, the considerable amount of information on Tkin (up to 90–95 km) can be obtained only when NER is low, which is characteristic, for example, for CLAES instrument. Different ideas concerning the improvement of the retrieval accuracy are discussed.

Calculation of longwave radiation fluxes in atmospheres

A technique for the computation of longwave radiative quantities using the line-by-line approach has been developed in the Soviet Union. The method has been applied to obtain fluxes and cooling rates for standard atmospheric profiles used in the Intercomparison of Radiation Codes Used in Climate Models (ICRCCM) sponsored by the World Meteorological Organization. The sensitivity of the result to changes in the vertical quadrature scheme, the angular integration, and the spectral line shape is evaluated. Fluxes and cooling rates in the troposphere are in general agreement with those obtained with different line-by-line models. Results from parameterized models, including a wideband statistical model and one employing the integral transmission function, have been compared to the line-by-line results. Flux errors in the simplified schemes are of the order of 10 W/m 2. The sensitivity of these models to changes in atmospheric profiles, or to an increase in CO2 amount, is similar to that of the line-by-line calculations. Radiative heat exchange is a basic component of atmospheric energy transfer. The numerical models for weather forecasting, climate theory, cloud generation, and a number of mesoscale dynamic processes all invoke radiation codes to compute this quantity. The radiative flux calculation algorithms in these models differ appreciably from each other and are always an approximation to the exact solutions of the radiative transfer equations. These approximations are needed because (1) the radiative calculations have to be made quickly compared to the calculation time of the model as a whole; (2) there is insufficient information in dynamic models to calculate the fluxes, and (3) the spatial, particularly the vertical, resolutions of the models are not sufficiently detailed. The calculated fluxes in each model differ as a consequence of the distinctiveness of the specific algorithms, the initial data applied, the spectral resolutions, etc., of the model. We may thus ask how the results of the simulation of the dynamic processes in the atmosphere are affected by the differences in radiative flux calculation techniques in models. In order to settle this question, we have first attempted to clear up a simpler one: what accuracy can be achieved by means of the radiation codes used in the numerical models

Intercomparison of satellite and ground-based ozone total column measurements

Ozone total column (OTC) measurements made in 2009–2012 near St. Petersburg by a Fourier Transform Infrared (FTIR) spectrometer (Peterhof, St. Petersburg State University (SPbSU)), an M-124 filter ozonometer, and a Dobson spectrophotometer (Voeikovo, MGO), as well as measurements made by a spectrometer ozone monitoring instrument (OMI) (onboard the AURA satellite) have been analyzed and compared. Comparisons have been performed both between ensembles of ground-based measurement data, as well as between ground-based and satellite data. It has been shown that the standard deviation for all devices is 2.5–4.5%; here, the FTIR and Dobson instruments measuring the direct sun are in better agreement with OMI than the M-124 ozonometer measuring the zenith-scattered solar radiation as well. A seasonal cycle in discrepancy with amplitude of 1.5% has been detected between two series of OTC measurements made by M-124 and OMI instruments for a total of 850 days. In fall and winter, the ground-based measurements underestimate the OTC values in comparison with satellite data; in spring and summer, the situation is reversed: ground-based data overestimate the OTC values. Also, it has been revealed that FTIR measurements systematically overestimate the OTC values in comparison with other instruments: from 1.4% (for Dobson) to 3.4% (for OMI). Taking into account the spatial and temporal discrepancy of independent ensembles of measurements and an analysis of standard deviations between ground-based and satellite measurement data, the FTIR spectrometer (SPbSU) can be recommended for OTC satellite data validation.

Information content of the spectral measurements of the 0.76 μm O2 outgoing radiation with respect to the vertical aerosol optical properties

Abstract The potential accuracy for retrieval of vertical profiles of scattering and absorption aerosol coefficients from outgoing and upward spectral radiance measurements in the 0.76μm O 2 band is analyzed. The information content of the remote method for high vertical resolution is small even in case of very low measurement errors. The best retrieval accuracy is achieved for ground layer (0–2 km) where the big amount of aerosol particles is concentrated. The additional information for 12–20 km layer can be received in the presence of thick stratospheric aerosol layer, for example, after volcanic eruptions. The possibilities of remote method are considerably improved for retrieval with low vertical resolution. The method under consideration permits to retrieve really only an aerosol volume scattering coefficient, but not absorption one.

Comparison of ground-based FTIR and radio sounding measurements of water vapor total content

We compared two datasets of the total content of atmospheric water vapor received near St. Petersburg in 2009–2012 from ground-based Fourier transform spectroscopy measurements at the Peterhof station and from radio sounding at Voyeykovo station. Despite a good correlation of daily measurements in Peterhof and Voyeykovo, the standard mismatch is significant, 20% or more, for most subsets taken for the comparison. The high mismatch is mainly due to the natural spatial variability of the total content of water vapor, accounting for the 50-km distance between Peterhof and Voyeykovo. This variability needs to be considered when validating the satellite measurements of water vapor content by ground-based measurements.

Comparison of radio sounding and ground-based remote measurements of temperature profiles in the troposphere

A ground-based experiment on microwave temperature sounding in the troposphere with a RPG-HATPRO instrument, which has been performed at the Faculty of Physics, St. Petersburg State University since June, 2012, is described. On the basis of comparison of the results with radio sounding data, the temperature retrieval errors have been estimated using an algorithm provided by the manufacturer of the instrument. The errors have been compared with corresponding values for similar instruments functioning abroad. The conclusion has been drawn about a need to develop specialized algorithms and data processing procedures which include adaptation and correction of algorithms accounting for peculiarities of a specific instrument and experimental conditions.

Comparing data obtained from ground-based measurements of the total contents of O3, HNO3,HCl, and NO2 and from their numerical simulation

Chemistry climate models of the gas composition of the atmosphere make it possible to simulate both space and time variations in atmospheric trace-gas components (TGCs) and predict their changes. Both verification and improvement of such models on the basis of a comparison with experimental data are of great importance. Data obtained from the 2009–2012 ground-based spectrometric measurements of the total contents (TCs) of a number of TGCs (ozone, HNO3, HCl, and NO2) in the atmosphere over the St. Petersburg region (Petergof station, St. Petersburg State University) have been compared to analogous EMAC model data. Both daily and monthly means of their TCs for this period have been analyzed in detail. The seasonal dependences of the TCs of the gases under study are shown to be adequately reproduced by the EMAC model. At the same time, a number of disagreements (including systematic ones) have been revealed between model and measurement data. Thus, for example, the EMAC model underestimates the TCs of NO2, HCl, and HNO3, when compared to measurement data, on average, by 14, 22, and 35%, respectively. However, the TC of ozone is overestimated by the EMAC model (on average, by 12%) when compared to measurement data. In order to reveal the reasons for such disagreements between simulated and measured data on the TCs of TGCs, it is necessary to continue studies on comparisons of the contents of TGCs in different atmospheric layers.

Possibilities for determining temperature and emissivity of the land surface from data of satellite IR sounders with high spectral resolution (IRFS-2)

Numerical experiments on the simultaneous retrieval of the temperature and spectral emissivity of different land types are performed on the basis of inversion of the simulated high spectral resolution measurements by the IRFS-2 satellite IR sounder. The IRFS-2 data inversion method is based on using a priori information on the spectral behavior of emissivity of different land types and the multiple linear regression technique. The rms errors of determination of the underlying surface temperature using different solving operators are 0.26–0.71 K. The application of the developed IRFS-2 measurement inversion method makes it possible to estimate the land surface emissivity with an rms error not larger than 0.015.

Application of the information approach to the analysis of two-year microwave observations of the atmosphere by the RPG-HATPRO radiometer at St. Petersburg University

ABSTRACT Since June 2012 the ground-based microwave (MW) radiometer RPG-HATPRO (Radiometer Physics GmbH – Humidity and Temperature Profiler) G3 (generation 3) has been operating at the Faculty of Physics of St. Petersburg State University in constant mode with sampling interval of 1–2 s. The results of MW radiation brightness temperature measurements in 14 spectral channels of the RPG-HATPRO radiometer have been analysed for the time period December 2012 to November 2014. Within this time period, different data ensembles are compiled that have different duration and describe the variety of atmospheric situations at the observational site. Two different approaches are used for the assessment of the information characteristics of MW measurements. The first one is based on calculation of Shannon’s information content that characterizes the number of atmospheric states distinguishable by measurements. We use the modification proposed by Kozlov – the ‘information volume’ approach. The second approach is based on calculation of the information quantity that characterizes the degree of correlation between measurements and atmospheric state parameter variations. The information quantities are calculated and analysed for the complete set of spectral channels and for two subsets that comprised seven so-called ‘temperature’ and seven so-called ‘humidity’ channels separately. Kozlov’s ‘information volume’ approach is also applied to the problem of estimation of the optimal sampling interval of MW measurements. It is shown that for St. Petersburg University observation site that represents subarctic region with maritime climate: (1) the information volume of MW measurements for a cold and dry season is significantly less than for a warm and humid season due to lack of information from ‘humidity channels’; (2) for stable atmospheric conditions the sampling interval of MW measurements should not be greater than 100–200 s; (3) the degree of correlation between MW measurements and atmospheric temperature and humidity does not considerably depend on season of observations.