We examine the applicability of the assumption that nighttime ozone is in photochemical equilibrium. The analysis is based on calculations with a 3‐D chemical transport model. These data are used to determine the ratio of correct (calculated) O3 density to its equilibrium value for the conditions of the nighttime mesosphere depending on the altitude, latitude, and month in the annual cycle. The results obtained demonstrate that the retrieval of O and H distributions using the assumption of photochemical ozone equilibrium may lead to a significant error below 81–87 km depending on season. Possible modifications of the currently used approach that allow improving the quality of retrieval of O and H mesospheric distributions from satellite‐based observations are discussed.
Abstract. For the retrieval of atomic oxygen via ozone observations in the extended mesopause region under sunlight conditions, two assumptions are used: first, the photochemical equilibrium of ozone and, second, that the ozone losses are dominated by ozone's dissociation from solar UV radiation, silently ignoring the O 3 destruction by atomic hydrogen. We verify both by 3-D modeling. We found that ozone approaches photochemical equilibrium at 75-100 km for daytime conditions. Hence, the first assumption is valid. However, the reaction of ozone with atomic hydrogen was found to be an important loss process and should not be omitted in retrieving atomic oxygen.
Abstract. This Technical Note presents a statistical approach to evaluating simultaneous measurements of several atmospheric components under the assumption of photochemical equilibrium. We consider simultaneous measurements of OH, HO 2 , and O 3 at the altitudes of the mesosphere as a specific example and their daytime photochemical equilibrium as an evaluating relationship. A simplified algebraic equation relating local concentrations of these components in the 50-100 km altitude range has been derived. The parameters of the equation are temperature, neutral density, local zenith angle, and the rates of eight reactions. We have performed a one-year simulation of the mesosphere and lower thermosphere using a 3-D chemical-transport model. The simulation shows that the discrepancy between the calculated evolution of the components and the equilibrium value given by the equation does not exceed 3-4 % in the full range of altitudes independent of season or latitude. We have developed a statistical Bayesian evaluation technique for simultaneous measurements of OH, HO 2 , and O 3 based on the equilibrium equation taking into account the measurement error. The first results of the application of the technique to MLS/Aura data (Microwave Limb Sounder) are presented in this Technical Note. It has been found that the satellite data of the HO 2 distribution regularly demonstrate lower altitudes of this component's mesospheric maximum. This has also been confirmed by model HO 2 distributions and comparison with offline retrieval of HO 2 from the daily zonal means MLS radiance.
In this work, we compare the values of 15 convective indices obtained from radiosonde and microwave temperature and water vapor profiles simultaneously measured over Nizhny Novgorod (56.2°N, 44°E) during 5 convective seasons of 2014–2018. A good or moderate correlation (with coefficients of ~0.7–0.85) is found for most indices. We assess the thunderstorm prediction skills with a lead time of 12 h for each radiosonde and microwave index. It is revealed that the effectiveness of thunderstorm prediction by microwave indices is much better than by radiosonde ones. Moreover, a good correlation between radiosonde and microwave values of a certain index does not necessarily correspond to similar prediction skills. Eight indices (Showalter Index, Maximum Unstable Convective Available Potential Energy (CAPE), Total Totals index, TQ index, Jefferson Index, S index, K index, and Thompson index) are regarded to be the best predictors from both the true skill statistics (TSS) maximum and Heidke skill score (HSS) maximum points of view. In the case of radiosonde data, the best indices are the Jefferson Index, K index, S index, and Thompson index. Only TSS and HSS maxima for these indices are close to the microwave ones, whereas the prediction skills of other radiosonde indices are essentially worse than in the case of microwave data. The analysis suggests that the main possible reason of this discrepancy is an unexpectedly low quality of radiosonde data.
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