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ABOUT GROUNDWINDS. . . GOALS The troposphere is the region of the atmosphere that is closest to the Earth’s surface where clouds and most weather-related phenomena occur. Winds in the troposphere, in fact, have a dominant effect on weather. Measuring tropospheric winds is crucial to the understanding of atmospheric and climate dynamics for weather forecasting. Presently, wind data are collected mainly from a worldwide network of weather-balloon launches; but most of the globe (specifically, over the oceans) is not covered by this network. This sparse input is one of the factors that limit the accuracy of the forecast models. The objective of the GroundWinds program is to develop and demonstrate remote-sensing technologies that can be used to measure global tropospheric winds from orbiting satellites. The resulting data would be used as input to weather modeling calculations, with the goal of greatly improving the accuracy of long-term (greater than 2-day) weather predictions. ABOUT GROUNDWINDS. . . The LIDAR system makes use of a Fabry-Pérot interferometer as a high spectral resolution element, capable of detecting Doppler shifts of the backscattered signal that correspond to velocities less than 1 m/s. A schematic that illustrates the overall concept is presented below.
An idealized version of the spectrum of the processed return signal is shown. This spectrum is recorded as a function of time to deduce Doppler shift of the light as a function of altitude. It should be noted that this spectrum consists of two distinct components. These are a broad distribution that is caused by “Rayleigh-Brillouin” scattering from atmospheric gases, and a narrow distribution that is the result of “Mie” scattering from atmospheric aerosols. The GroundWinds system utilizes both of these components to produce a measurement of wind velocity. Each of these spectral components is measured using an interferometer whose resolution is optimized for that particular measurement. GroundWinds LIDAR facilities have been established in Bartlett, New Hampshire and at Mauna Loa, Hawaii. These facilities are being used to test certain technologies that are important to the success of the “DDD” LIDAR technique. In addition to these ground-based “test beds,” a LIDAR system called “BalloonWinds” is being developed, which will be carried above the troposphere under a high-altitude balloon for flights lasting a matter of some hours. These will demonstrate how LIDARs can work from locations closer to the viewpoint of Earth-orbiting satellites.
After some filtering, the light is introduced into the molecular interferometer. The circular fringe pattern that is created by the molecular interference optics (etalon) is present in the transmitted light, the reflected light from the etalon being the complement of the transmitted fringe pattern. In most interferometers, the reflected light is lost from the system and represents a significant inefficiency. However, in the GroundWinds interferometer the reflected light is re-injected into the molecular etalon in a process called “photon recycling.” Fiber optic arrays are used to collect light that is reflected from the etalon and to reintroduce it into the interferometer. This can be done a number of times to pass more light through the instrument. After a couple of recycling stages, the primary and recycled light is focused through a “Circle to Line Interferometer Optical” system (CLIO). This innovative device converts the circular fringes from the Fabry-Pérot into a linear pattern that is detected by a charge-coupled device (CCD) camera. The remaining reflected light is injected into the aerosol interferometer where reflected light again goes through recycling. Here again an etalon creates a velocity-sensitive circular fringe pattern that is transformed into a linear pattern by a CLIO coupled to a CCD camera. The light that was reflected on every injection is passed to a photomultiplier tube (PMT). The PMT is used to measure a photometric intensity profile. This can be used to quantify the integrated energy returned, and has value in numerically correcting for any misalignment in the etalons. The system detectors record at any one time three sets of information; 1) the aerosol fringe pattern optimized to detect the motion of aerosols, 2) the molecular direct fringe pattern, optimized to detect the motion of the molecular component of the atmosphere, and 3) the integrated photometric return.
This picture shows how the circular pattern of the Fabry-Pérot fringes are transformed by the CLIO optics into a linear pattern of “spots” that is focused onto a CCD. The outer fringes are produced by the light that passes through the recycling fiber optics. This allows additional “orders” of the fringe pattern to be analyzed for Doppler shifts. As the light from a laser pulse returns through the atmosphere, the spot pattern is shifted through the CCD, forming a group of “streaks.”
The distance along the length of the streaks is proportional to the distance from the LIDAR to the region of the atmosphere that scattered the light pulse. The deviation of the “spine” of the streak from a known reference position is a function of the Doppler shift caused by the wind velocity in that region. The upshot is that the wind vector at points along the line of sight (LOS) of the LIDAR can be measured. Combining this with vectors observed in different directions yields a sample of the wind velocity field surrounding the LIDAR. In addition, the width of the spine gives information about the temperature of the air along the LOS.
The data undergoes frequency and intensity calibrations. The multiple interference orders are used for frequency calibration purposes (determination of the frequency-pixel column relationship). Standard flat fielding techniques are used to calibrate the intensities of the measured row counts into meaningful spectra. The calibrated spectrum resulting from the reference region contains important information on the laser spectrum and the instrument response. The altitude-resolved sky spectra are interpreted through the use of the reference spectrum, molecular (Rayleigh-Brillouin) scattering model, aerosol (Mie) scattering model, and background models. Specifically, the sky spectrum from each altitude is fitted to these models. The fit parameters are Doppler shift, molecular signal strength, aerosol signal strength, and temperature (optional). The algebraic manipulations of these fit parameters produce the primary data products shown below. The vertical scale of each plot is the altitude in km above sea level. The horizontal scale is time in minutes, but each band of data represents a 30 degree clockwise sweep in azimuth. The blank sections are times when the azimuth is advanced by a large step and the receiving fiber optic is realigned.
These measurements along with other atmospheric models and theories
give rise to secondary
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