Tuesday, 25 January 2011: 3:45 PM
307-308 (Washington State Convention Center)
Atmospheric temperature measurements from a Raman lidar, which are determined from two channels in the anti-Stokes regime of the rotational Raman spectrum, are evaluated over a multi-year period to assess bias and noise characteristics. Bias errors in the lower troposphere are estimated by comparing the Raman lidar measurements to temperature retrievals from a passive infrared spectrometer (the Atmospheric Emitted Radiance Interferometer or AERI). These comparisons are carried out at the US Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma. The ARM Raman lidar measures atmospheric temperature by detecting backscatter arising from rotational transitions in atmospheric nitrogen and oxygen molecules. The interference filters used in the two rotational Raman channels have center wavelengths at 353.3 and 354.3 nm with transmissions of larger than 35% at these wavelengths, and have significant attenuation (>1e-6) at the laser wavelength 354.7 nm). Calibration and overlap correction is achieved using data from radiosondes, which are normally launched four-times daily at SGP. For this study, Raman lidar temperature profiles were computed using hourly averages at a height resolution of 300 m. Uncertainties due to shot noise in the raw photon-counting signals were propagated through the calculations to obtain estimates of uncertainty in temperature. At night, the median absolute temperature uncertainty was about 1.5 K, and exhibited little change with height below 10 km. During the daytime, the median absolute temperature uncertainty remained roughly constant below 6 km (~1.7 K) before increasing significantly with height. Temperature data from the Atmospheric Emitted Radiance Interferometer (AERI) provided a source of independent temperature measurements, with time and height resolutions comparable to the Raman lidar data. The AERI measures the absolute downwelling infrared spectral radiance of the sky directly above the instrument with a spectral resolution of 1.0 cm-1. Temperature and water vapor profiles are computed from the AERI radiance data using a physical retrieval algorithm. Because the information content in the AERI radiances diminishes with height, the retrievals are generally limited to a maximum height of about 3 km AGL. For heights below 3 km, the correlation between the Raman and the AERI temperatures was 0.97, and the median relative bias was within ±0.5%. We also discuss potential synergies between the Raman Lidar and AERI for improved temperature and or water vapor profiling. Preliminary results will be presented to examine the impact on the AERI temperature retrievals when constrained using humidity profiles from the Raman lidar.
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