Engineering topics

McDermid, Iain S.

Publications and source records attributed to McDermid, Iain S..

4 records

NASA NTRS2008

Stable Calibration of Raman Lidar Water-Vapor Measurements

A method has been devised to ensure stable, long-term calibration of Raman lidar measurements that are used to determine the altitude-dependent mixing ratio of water vapor in the upper troposphere and lower stratosphere. Because the lidar measurements yield a quantity proportional to the mixing ratio, rather than the mixing ratio itself, calibration is necessary to obtain the factor of proportionality. The present method involves the use of calibration data from two sources: (1) absolute calibration data from in situ radiosonde measurements made during occasional campaigns and (2) partial calibration data obtained by use, on a regular schedule, of a lamp that emits in a known spectrum determined in laboratory calibration measurements. In this method, data from the first radiosonde campaign are used to calculate a campaign-averaged absolute lidar calibration factor (t(sub 1)) and the corresponding campaign-averaged ration (L(sub 1)) between lamp irradiances at the water-vapor and nitrogen wavelengths. Depending on the scenario considered, this ratio can be assumed to be either constant over a long time (L=L(sub 1)) or drifting slowly with time. The absolutely calibrated water-vapor mixing ratio (q) obtained from the ith routine off-campaign lidar measurement is given by q(sub 1)=P(sub 1)/t(sub 1)=LP(sub 1)/P(sup prime)(sub 1) where P(sub 1) is water-vapor/nitrogen measurement signal ration, t(sub 1) is the unknown and unneeded overall efficiency ratio of the lidar receiver during the ith routine off-campaign measurement run, and P(sup prime)(sub 1) is the water-vapor/nitrogen signal ratio obtained during the lamp run associated with the ith routine off-campaign measurement run. If L is assumed constant, then the lidar calibration is routinely obtained without the need for new radiosonde data. In this case, one uses L=L(sub 1) = P(sup prime)(sub 1)/t(sub 1), where P(sub 1)(sup prime) is the water-vapor/nitrogen signal ratio obtained during the lamp run associated with the first radiosonde campaign. If L is assumed to drift slowly, then it is necessary to postpone calculation of a(sub 1) until after a second radiosonde campaign. In this case, one obtains a new value, L(sub 2), from the second radiosonde campaign, and for the ith routine off-campaign measurement run, one uses an intermediate value of L obtained by simple linear time interpolation between L(sub 1) and L(sub 2).

Leblanc, Thierry↗

NASA NTRS2008

Measurements of Humidity in the Atmosphere and Validation Experiments (Mohave, Mohave II): Results Overview

The Measurements of Humidity in the Atmosphere and Validation Experiments (MOHAVE, MOHAVE-II) inter-comparison campaigns took place at the Jet Propulsion Laboratory (JPL) Table Mountain Facility (TMF, 34.5(sup o)N) in October 2006 and 2007 respectively. Both campaigns aimed at evaluating the capability of three Raman lidars for the measurement of water vapor in the upper troposphere and lower stratosphere (UT/LS). During each campaign, more than 200 hours of lidar measurements were compared to balloon borne measurements obtained from 10 Cryogenic Frost-point Hygrometer (CFH) flights and over 50 Vaisala RS92 radiosonde flights. During MOHAVE, fluorescence in all three lidar receivers was identified, causing a significant wet bias above 10-12 km in the lidar profiles as compared to the CFH. All three lidars were reconfigured after MOHAVE, and no such bias was observed during the MOHAVE-II campaign. The lidar profiles agreed very well with the CFH up to 13-17 km altitude, where the lidar measurements become noise limited. The results from MOHAVE-II have shown that the water vapor Raman lidar will be an appropriate technique for the long-term monitoring of water vapor in the UT/LS given a slight increase in its power-aperture, as well as careful calibration.

lidar↗

NASA NTRS2004

The NDSC ozone and temperature lidar alogorithm intercomparison ubutuatuve (A2I): project overview

In September 2003, the Lidar Working Group (LWG) of the Network for Detection of Stratospheric Change (NDSC) initiated an extensive project to compare the ozone and temperature algorithms used within NDSC. This initiative, referred to later as Algorithm Intercomparison Initiative (A2I), uses simulated lidar signals to test and compare various parts of the ozone and temperature lidar algorithms. In addition to the fact that it meets the requirement of the NDSC protocols, this exercise allows the detailed assessment, by all the participants, of some of the sources and magnitudes of various uncertainties associated with the algorithms, and/or with the theoretical assumptions made in these algorithms. The outcome of the A21 is to try to find common grounds in the way ozone and temperature can be retrieved in order to reduce and possibly eradicate discrepancies due to algorithm issues alone. Specific issues such as homogenizing the choice of Rayleigh extinction cross-sections, ozone absorption cross-sections, a priori information, and the definition of the vertical resolutions are among the primary targets of the A21 outcome.

lidar↗

NASA NTRS1985

Mirror-grating tuning arrangement for high resolution lasers

A tuning arrangement (10) for a tunable laser comprises a single holographic grating (12) and two flat surface reflective mirrors (13 and 14). The beam (15) from the laser cavity is incident on the grating at a grazing angle for optimum beam expansion. The diffracted beam propogates from the grating to the first mirror (13), therefrom to the second mirror (14) and is reflected at the Littrow angle to the grating, whereat it is diffracted a second time and returned to the second mirror (14) for reflection to the first mirror (13). Therefrom it is reflected back to the grating. After undergoing a third diffraction it is directed back into the cavity for further amplification.

McDermid, Iain S.↗