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Twice-daily ozonesondes were launched from Harrow, in southwestern Ontario, Canada, during the BAQS-Met (Border Air Quality and Meteorology Study) field campaign in June and July of 2007. A co-located radar windprofiler measured tropopause height continuously. These data, in combination with continuous surface ozone measurements and geo-statistical interpolation of satellite ozone observations, present a consistent picture and indicate that a number of significant ozone enhancements in the troposphere were observed that were the result of stratospheric intrusion events. The combined observations have also been compared with results from two Environment Canada numerical models, the operational weather prediction model GEM (as input to FLEXPART), and a new version of the regional air quality model AURAMS, in order to examine the ability of these models to accurately represent sporadic cross-tropopause ozone transport events. The models appear to reproduce intrusion events with some skill, implying that GEM dynamics (which also drive AURAMS) are able to represent such events well. There are important differences in the quantitative comparison, however; in particular, the poor vertical resolution of AURAMS around the tropopause causes it to bring down too much ozone in individual intrusions. These campaign results imply that stratospheric intrusions are important to the ozone budget of the mid-latitude troposphere, and appear to be responsible for much of the variability of ozone in the free troposphere. GEM-FLEXPART calculations indicate that stratospheric ozone intrusions contributed significantly to surface ozone on several occasions during the BAQS-Met campaign, and made a moderate but significant contribution to the overall tropospheric ozone budget.

The Resolute Bay VHF radar, located in Nunavut, Canada (75.0° N, 95.0° W) and operating at 51.5 MHz, has been used to investigate Polar Mesosphere Summer Echoes (PMSE) since 1997. PMSE are a unique form of strong coherent radar echoes, and their understanding has been a challenge to the scientific community since their discovery more than three decades ago. While other high latitude radars have recorded strong levels of PMSE activities, the Resolute Bay radar has observed relatively lower levels of PMSE strengths. In order to derive absolute measurements of PMSE strength at this site, a technique is developed to determine the radar efficiency using cosmic (sky) noise variations along with the help of a calibrated noise source. VHF radars are only rarely calibrated, but determination of efficiency is even less common. Here we emphasize the importance of efficiency for determination of cross-section measurements. The significant advantage of this method is that it can be directly applied to any MST radar system anywhere in the world as long as the sky noise variations are known. The radar efficiencies for two on-site radars at Resolute Bay are determined. PMSE backscatter cross-section is estimated, and decade-long PMSE strength variations at this location are investigated. It was noticed that the median of the backscatter cross-section distribution remains relatively unchanged, but over the years a great level of variability occurs in the high power tail of the distribution.

An ensemble of space-borne and ground-based instruments has been used to evaluate the quality of the version 2.2 temperature retrievals from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS). The agreement of ACE-FTS temperatures with other sensors is typically better than 2 K in the stratosphere and upper troposphere and 5 K in the lower mesosphere. There is evidence of a systematic high bias (roughly 3–6 K) in the ACE-FTS temperatures in the mesosphere, and a possible systematic low bias (roughly 2 K) in ACE-FTS temperatures near 23 km. Some ACE-FTS temperature profiles exhibit unphysical oscillations, a problem fixed in preliminary comparisons with temperatures derived using the next version of the ACE-FTS retrieval software. Though these relatively large oscillations in temperature can be on the order of 10 K in the mesosphere, retrieved volume mixing ratio profiles typically vary by less than a percent or so. Statistical comparisons suggest these oscillations occur in about 10% of the retrieved profiles. Analysis from a set of coincident lidar measurements suggests that the random error in ACE-FTS version 2.2 temperatures has a lower limit of about ±2 K.

The Purple Crow Lidar (PCL) is a large power-aperture product monostatic Rayleigh-Raman-Sodium-resonance-fluorescence lidar, which has been in operation at the Delaware Observatory (42.9° N, 81.4° W, 237 m elevation) near the campus of The University of Western Ontario since 1992. Kinetic-energy density has been calculated from the Rayleigh-scatter system measurements of density fluctuations at temporal-spatial scales relevant for gravity waves, e.g. soundings at 288 m height resolution and 9 min temporal resolution in the upper stratosphere and mesosphere. The seasonal averages from 10 years of measurements show in all seasons some loss of gravity-wave energy in the upper stratosphere. During the equinox periods and summer the measurements are consistent with gravity waves growing in height with little saturation, in agreement with the classic picture of the variations in the height at which gravity waves break given by Lindzen (1981). The mean values compare favourably to previous measurements when computed as nightly averages, but the high temporal-spatial resolution measurements show considerable day-to-day variability. The variability over a night is often extremely large, with typical RMS fluctuations of 50 to 100% at all heights and seasons common. These measurements imply that using a daily or nightly-averaged gravity-wave energy density in numerical models may be highly unrealistic.

Temperature measurements from the PCL Rayleigh lidar located near London, Canada, taken during the 11 year period from 1994 to 2004 are used to form a temperature climatology of the middle atmosphere. A unique feature of the PCL temperature climatology is that it extends from 35 to 95 km allowing comparison with other Rayleigh lidar climatologies (which typically extend up to about 85 km), as well as with climatologies derived from sodium lidar measurements which extend from 83 to 108 km. The derived temperature climatology is compared to the CIRA-86 climatological model and to other lidar climatologies, both Rayleigh and sodium. The PCL climatology agrees well with the climatologies of other Rayleigh lidars from similar latitudes, and like these other climatologies shows significant differences from the CIRA-86 temperatures in the mesosphere and lower thermosphere. Significant disagreement is also found between the PCL climatology and sodium lidar climatologies measured in the central and western United States at similar latitudes, with the PCL climatology consistently 10 to 15 K cooler in the 85 to 90 km region.

It has long been assumed that Rayleigh lidar can be used to measure atmospheric temperature profiles up to about 90 or 100 km and that above this region the technique becomes invalid due to changes in atmospheric composition which affect basic assumptions on which Rayleigh lidar is based. Modern powerful Rayleigh lidars are able to measure backscatter from well above 100 km requiring a closer examination of the effects of the changing atmospheric composition on derived Rayleigh lidar temperature profiles. The NRLMSISE-00 model has been used to simulate lidar signal (photon-count) profiles, taking into account the effects of changing atmospheric composition, enabling a quantitative analysis of the biases and errors associated with extending Rayleigh lidar temperature measurements above 100 km. The biases associated with applying a nominal correction for the change in atmospheric composition with altitude has also been investigated. The simulations reported here show that in practice the upper altitude limit for Rayleigh lidar is imposed more by the accuracy of the temperature or pressure used to seed the temperature retrieval algorithm than by accurate knowledge of the atmospheric composition as has long been assumed.