Atmospheric temperature retrievals from lidar measurements using techniques of non-linear mathematical inversion

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[0350] Atmospheric Composition And Structure / Pressure, Density, And Temperature, [0394] Atmospheric Composition And Structure / Instruments And Techniques

Scientific paper

The conventional method of retrieving atmospheric temperatures from absolute (or relative) lidar density measurements requires the assumption of a seed pressure to initiate the temperature retrieval (e.g. Hauchecorne and Chanin, 1980). An uncertainty in this choice typically results in a systematic uncertainty in retrieved temperatures near the top 10 to 15 km of the range. This uncertainty makes the retrieved temperatures at the top of the profile of insufficient quality for scientific studies of the upper atmosphere. The application of mathematical inversion was investigated as a tool to possibly remedy this problem. A grid search technique was used to develop an alternative way of retrieving atmospheric temperature profiles from Rayleigh-scatter lidar measurements. The advantage of this technique is that the seed pressure can be chosen at the bottom, rather than at the top of the measurement range. This change is expected to be an improvement because variations in pressures at the lowest heights (typically the stratosphere) are much smaller as compared to those in the upper mesosphere or lower thermosphere, resulting in smaller uncertainties in the retrieved profile, particularly at the top of the atmosphere. Hence, use of this technique is equivalent to increasing the lidar's power-aperture product by about 4 times. After successful testing of the method on simulated lidar measurements, measurements obtained by The University of Western Ontario's Purple Crow lidar were analyzed using this technique. Results will be shown which conclusively demonstrate that this technique allows the lidar to retrieve temperatures up to heights where sufficient photocounts are obtained without large uncertainties due to seed pressure. One of the major challenges in this work was devising a numerical scheme to estimate the uncertainties in retrieved temperatures. A Monte Carlo method was used to estimate standard errors in the retrieved temperatures. The statistical uncertainties retrieved using this scheme are consistent with the statistical uncertainties in the conventional technique. In addition the systematic errors due to uncertainties in seed pressure and other input parameters can be retrieved separately from the statistical uncertainties. A. Hauchecorne and M. L. Chanin, Density and temperature profiles obtained by lidar between 35 and 70 km. Geophys. Res. Lett., 1980.

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