In this work, the impact of various factors on the total ozone column and erythemal UV radiation (Qery) in the territory of Northern Eurasia for the period from 1979 to 2059 based on the calculations of the chemical-climate model INM-RHSU is analyzed. The sensitivity of ozone recovery to the setting of different input data on sea surface temperature (SST) is estimated. Depending on the SST datasets, there are significant differences in ozone trends. A possible mechanism that explains the reasons for these differences is examined. The numerical experiment with the only change in ozone depleting substances according to Montreal protocol showed the ozone recovery and, as a result, Qery reduction, but this recovery is not linear. During the 2016-2020 period we estimated the 2-5% increase in Qery values relative to the baseline period (1979-1983) with about 6% maximum over Russian polar region. During the 2035-2039 period the Qery change against 1979-1983 period is about zero, during the 2055-2059 period we obtained the decrease of about 4-6% over Northern Asia and 6-8% over Northern Europe These changes corresponded to the noticeable boundary location shift of UV resources, which determine UV radiation impact on human health. The most significant changes will be observed in spring and summer: the UV deficiency zone will be expanded in the north and the UV excess zone over northern seas will be reduced in the south.

Comments of the reviewer 1: The paper presents a parametrization of the altitude effect on different types of biologically effective UV related irradiance. It is a useful tool for the scientific community using UVI measurements and it is related with specific health issues.The analysis and the presentation of the results is adequate for publication in ACP after the authors take into account the following suggestions/comments.1. Equations 7-9. What are the units used for the solar elevation here? Since the C1 ACPD Interactive commentPrinter-friendly version Discussion paper coefficients are very small compared ot the constant factor. What is their physical meaning? We used a simple polynomial regression method which provides better accounting the RAF dependence on solar elevation ( see their solar angle dependence in Figure below). The coefficients are small but they are very necessary. For example, for RAFQery at high solar elevations small coefficients at term 1 and term 2 are compensated by large multipliers (hˆ2 and h, respectively). For example, at h=90 first negative term gives -0.89, and the second term-1.41, which are of the same order with the constant 0.665. Solar elevation is given in degree.RAFQery(h)= -1.10E-04ïĆś1.49E-5 h2 + 1.57E-02ïĆś1.53E-3 h +0.665ïĆś0.0333Since this is a statistical polynomial regression approach physical meaning of coefficients is not important as we should take into account all terms at once.The polynomial regression approach provides the most accurate account of the RAF dependence on h. We have added some clarification in the text about this standard method and some other details. 2 Line 259. Since we expect the majority of aerosols to be found at lower altitudes, how realistic is to assume that the SSA is non altitude dependent. ?We assume this is possible. According to aircraft measurements (Panchenko et al.,2012) SSA at 440nm (the closest wavelength to the UV) changed from 0.87 to 0.93 but this could be a specific feature observed over Western Siberia in visible spectrum for specific conditions. Unfortunately we found no information on SSA altitude C2 ACPD Interactive commentPrinter-friendly version Discussion paper