Thermospheric wind data obtained from the Atmosphere Explorer E and Dynamics Explorer 2 satellites have been combined with wind data for the lower and upper thermosphere from ground‐based incoherent scatter radar and Fabry‐Perot optical interferometers to generate a revision (HWM90) of the HWM87 empirical model and extend its applicability to 100 km. Comparison of the various data sets with the aid of the model shows in general remarkable agreement, particularly at mid and low latitudes. The ground‐based data allow modeling of seasonal/diurnal variations, which are most distinct at mid latitudes. While solar activity variations are now included, they are found to be small and not always very clearly delineated by the current data. They are most obvious at the higher latitudes. The model describes the transition from predominately diurnal variations in the upper thermosphere to semidiurnal variations in the lower thermosphere and a transition from summer to winter flow above 140 km to winter to summer flow below. Significant altitude gradients in the wind are found to extend to 300 km at some local times and pose complications for interpretation of Fabry‐Perot observations.

A standardized approach for the definition and reporting of vertical resolution of the ozone and temperature lidar profiles contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. Two standardized definitions homogeneously and unequivocally describing the impact of vertical filtering are recommended. The first proposed definition is based on the width of the response to a finite-impulse-type perturbation. The response is computed by convolving the filter coefficients with an impulse function, namely, a Kronecker delta function for smoothing filters, and a Heaviside step function for derivative filters. Once the response has been computed, the proposed standardized definition of vertical resolution is given by Δz = δz × H_FWHM, where δz is the lidar's sampling resolution and H_FWHM is the full width at half maximum (FWHM) of the response, measured in sampling intervals. The second proposed definition relates to digital filtering theory. After applying a Laplace transform to a set of filter coefficients, the filter's gain characterizing the effect of the filter on the signal in the frequency domain is computed, from which the cut-off frequency f_C, defined as the frequency at which the gain equals 0.5, is computed. Vertical resolution is then defined by Δz = δz∕(2f_C). Unlike common practice in the field of spectral analysis, a factor 2f_C instead of f_C is used here to yield vertical resolution values nearly equal to the values obtained with the impulse response definition using the same filter coefficients. When using either of the proposed definitions, unsmoothed signals yield the best possible vertical resolution Δz = δz (one sampling bin). Numerical tools were developed to support the implementation of these definitions across all NDACC lidar groups. The tools consist of ready-to-use “plug-in” routines written in several programming languages that can be inserted into any lidar data processing software and called each time a filtering operation occurs in the data processing chain. When data processing implies multiple smoothing operations, the filtering information is analytically propagated through the multiple calls to the routines in order for the standardized values of vertical resolution to remain theoretically and numerically exact at the very end of data processing.

A standardized approach for the definition, propagation, and reporting of uncertainty in the ozone differential absorption lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. One essential aspect of the proposed approach is the propagation in parallel of all independent uncertainty components through the data processing chain before they are combined together to form the ozone combined standard uncertainty. The independent uncertainty components contributing to the overall budget include random noise associated with signal detection, uncertainty due to saturation correction, background noise extraction, the absorption cross sections of O₃, NO₂, SO₂, and O₂, the molecular extinction cross sections, and the number densities of the air, NO₂, and SO₂. The expression of the individual uncertainty components and their step-by-step propagation through the ozone differential absorption lidar (DIAL) processing chain are thoroughly estimated. All sources of uncertainty except detection noise imply correlated terms in the vertical dimension, which requires knowledge of the covariance matrix when the lidar signal is vertically filtered. In addition, the covariance terms must be taken into account if the same detection hardware is shared by the lidar receiver channels at the absorbed and non-absorbed wavelengths. The ozone uncertainty budget is presented as much as possible in a generic form (i.e., as a function of instrument performance and wavelength) so that all NDACC ozone DIAL investigators across the network can estimate, for their own instrument and in a straightforward manner, the expected impact of each reviewed uncertainty component. In addition, two actual examples of full uncertainty budget are provided, using nighttime measurements from the tropospheric ozone DIAL located at the Jet Propulsion Laboratory (JPL) Table Mountain Facility, California, and nighttime measurements from the JPL stratospheric ozone DIAL located at Mauna Loa Observatory, Hawai'i.

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The first three Arctic winters of the ACE mission represented two extremes of winter variability: Stratospheric sudden warmings (SSWs) in 2004 and 2006 were among the strongest, most prolonged on record; 2005 was a record cold winter. Canadian Arctic Atmospheric Chemistry Experiment (ACE) Validation Campaigns were conducted at Eureka (80° N, 86° W) during each of these winters. New satellite measurements from ACE-Fourier Transform Spectrometer (ACE-FTS), Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), and Aura Microwave Limb Sounder (MLS), along with meteorological analyses and Eureka lidar temperatures, are used to detail the meteorology in these winters, to demonstrate its influence on transport, and to provide a context for interpretation of ACE-FTS and validation campaign observations. During the 2004 and 2006 SSWs, the vortex broke down throughout the stratosphere, reformed quickly in the upper stratosphere, and remained weak in the middle and lower stratosphere. The stratopause reformed at very high altitude, near 75 km. ACE measurements covered both vortex and extra-vortex conditions in each winter, except in late-February through mid-March 2004 and 2006, when the strong, pole-centered vortex that reformed after the SSWs resulted in ACE sampling only inside the vortex in the middle through upper stratosphere. The 2004 and 2006 Eureka campaigns were during the recovery from the SSWs, with the redeveloping vortex over Eureka. 2005 was the coldest winter on record in the lower stratosphere, but with an early final warming in mid-March. The vortex was over Eureka at the start of the 2005 campaign, but moved away as it broke up. Disparate temperature profile structure and vortex evolution resulted in much lower (higher) temperatures in the upper (lower) stratosphere in 2004 and 2006 than in 2005. Satellite temperatures agree well with lidar data up to 50–60 km, and ACE-FTS, MLS and SABER show good agreement in high-latitude temperatures throughout the winters. Consistent with a strong, cold upper stratospheric vortex and enhanced radiative cooling after the SSWs, MLS and ACE-FTS trace gas measurements show strongly enhanced descent in the upper stratospheric vortex in late January through March 2006 compared to that in 2005.

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.