Extending the Purple Crow Lidar Temperature Climatology Above 100 km Altitude Using an Inversion Approach
Abstract
Temperature retrievals from Rayleigh-scattering lidar measurements have been performed using the algorithm given by Chanin and Hauchecorne (1980; henceforth CH) for the last 3 decades. Recently Khanna et al. have presented an inversion approach to retrieve atmospheric temperature profiles. This method uses a nonlinear inversion method with a Monte Carlo technique to determine the statistical uncertainties for the retrieved nightly average temperature profiles. Using this approach, Purple Crow Lidar temperature profiles can now be extended 10 km higher in altitude compared to those calculated with the CH method, with reduced systematic uncertainty. Argall and Sica (2007) used the CH method to produce a climatology of the Purple Crow Lidar measurements from 1994 to 2004 which was compared with the CIRA-86 model. The CH method integrates temperatures downward, and requires the assumption of a 'seed' pressure at the highest altitude, taken from a model. Geophysical variation here, in the lower thermosphere, is sufficiently large to cause temperature retrievals to be unreliable for the top 10 or more km; uncertainties due to this pressure assumption cause the top two scale heights of temperatures from each profile to be discarded until the retrieval is no longer sensitive to the seed pressure. Khanna et al. (2012) use an inversion approach which allows the corrected lidar photocount profile to be integrated upward, as opposed to downward as required by the CH method. Khanna et al. (2012) showed that seeding the retrieval at the lowest instead of top height allows a much smaller uncertainty in the contribution of the seed pressure to the temperature compared to integrating from the top of the profile. Two other benefits to seeding the retrieval at the lower altitudes (around 30 km) include reduced geophysical variability, and the availability of routine pressure measurements from radiosondes. This presentation will show an extension of the Khanna et al. (2012) comparison to the entire measurement set from the Purple Crow Lidar. The inversion approach allows the PCL climatology to be extended in altitude by more than a scale height with greatly reduced systematic uncertainty. [1] Argall, P. and R. Sica (2007). A comparison of Rayleigh and sodium lidar temperature climatologies. Ann. Geophys.25,27-35,2007 [2] Chanin, M. and A. Hauchecorne (1980). Density and temperature profiles obtained by lidar between 35 km and 70 km. Geophys. Res. Lett 7(8), 565-568 (1980). [3] Jaya Khanna, Justin Bandoro, R. J. Sica, and C. Thomas McElroy (2012), New technique for retrieval of atmospheric temperature profiles from from Rayleigh-scatter lidar measurements using nonlinear inversion.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFMSA33B2004J
- Keywords:
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- 0394 ATMOSPHERIC COMPOSITION AND STRUCTURE Instruments and techniques;
- 3360 ATMOSPHERIC PROCESSES Remote sensing;
- 3394 ATMOSPHERIC PROCESSES Instruments and techniques;
- 0350 ATMOSPHERIC COMPOSITION AND STRUCTURE Pressure;
- density;
- and temperature