The photolysis frequency of NO2, j(NO2), was determined by various instrumental techniques and calculated using a number of radiative transfer models for 4 days in June 1998 at the International Photolysis Frequency Measurement and Modeling Intercomparison (IPMMI) in Boulder, Colorado. Experimental techniques included filter radiometry, spectroradiometry, and chemical actinometry. Eight research groups participated using 14 different instruments to determine j(NO2). The blind intercomparison experimental results were submitted to the independent experimental referee and have been compared. Also submitted to the modeling referee were the results of NO2 photolysis frequency calculations for the same time period made by 13 groups who used 15 different radiative transfer models. These model results have been compared with each other and also with the experimental results. The model calculation of clear‐sky j(NO2) values can yield accurate results, but the accuracy depends heavily on the accuracy of the molecular parameters used in these calculations. The instrumental measurements of j(NO2) agree to within the uncertainty of the individual instruments and indicate the stated uncertainties in the instruments or the uncertainties of the molecular parameters may be overestimated. This agreement improves somewhat with the use of more recent NO2 cross‐section data reported in the literature.

The relative variances in stratospheric observations of longlived trace gases CH4, N~O, CF2C12, CFC13 show large differences. These differences axe greatly reduced when the local mean standard deviation is normalized to the local vertical gradient. This ratio, called 'equivalent displacement height' exhibits ~ characteristic vertical profile which is very similar for all the longlived trace gases, as well as for O 3. With the help of this ratio, it is demonstrated that the variances are essentially due to natural causes, i.e., transport. Using the mixing length hypothesis a theoretical expression for the equivalent displacement height is derived. From it the meridional slope of the mixing surfaces and the mixing length can be calculated as function of the altitude. Additional information is obtained on the variance'of that slope. The uncertainty of the measured mean trace gas profiles is defined.Much of our faith in current models of stratospheric chemistry rests upon the fact that the model predicted trace gas distributions 'agree' with measured profiles. Agreement is not well deFmed; it usually means that the model predicted vertical profile follows approximately the shape outlined by the measurements and falls within the range of the data points. Such agreement for a sufficient number of trace gases is said to validate a model. Clearly one would prefer a more quantitative intercomparlson of model prediction with experimental observation. In the past, this was hampered by a lack of experimental data. The observations were sparse, made in different locations and seasons. Consequently the data showed a fair amount of scatter. It was difficult to decide how well the measurements represented the mean stratospheric trace gas distribution and therefore impossible to assign a meaningful uncertainty to the observations.In the meantime, the data base has somewhat improved. For a few trace gases, namely

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Abstract. New expressions for the wavelength-dependent photolysis quantum yields of CH 2 O, j , are presented. They are based on combinations of functions of the typeThe parameters A i , b i , and λ 0i which have a physical meaning, are obtained by fits to the measured j data available from literature. The altitude dependence of the photolysis frequencies resulting from the new quantum yield expressions are compared to those derived from the j recommended by JPL and IUPAC.

A photon flux model is described which determines the photodissociation coefficients for the simulation of atmospheric chemistry with a very fast algorithm. Emphasis is laid on the calculation of the radiative transfer in optically thick media, e.g. in clouds. The concept of Kubelka and Munk [1] has been adapted to atmospheric conditions. The algorithm is described in detail, and general aspects of the radiative transfer in clouds are presented. To prove the accuracy of the algorithm, the results are compared to those gained by a more sophisticated model.