Editing Emerging technologies, emerging markets – fostering the innovation potential of research infrastructures
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Atmospheric LIDAR is a class of instruments that uses laser light to study atmospheric properties from the ground up to the top of the atmosphere (Kavaya and Menzies 1985). Such instruments have been used to study, among other, atmospheric gases, aerosols, clouds, and temperature. The transmission unit consists of a laser source, followed by a series of mirrors, and a beam expander, which sends the collimated light beam vertically up to the open atmosphere. Part of the transmitted radiation is scattered by atmospheric components (i.e., gases, molecules, aerosols, clouds) backward to the LIDAR, where a telescope collects it. The backscattered light is driven to an optical analyser where the optical signal is first spectrally separated, amplified and transformed to an electrical signal. Finally, the signal is digitized and stored in a computer unit. While knowing the aerosol properties (forward problem) and predicting the LIDAR signal is a straightforward calculation, the inverse process is mathematically ill-posed (i.e., non-unique and incomplete solution space), showing a strong sensitivity on input uncertainties. | Atmospheric LIDAR is a class of instruments that uses laser light to study atmospheric properties from the ground up to the top of the atmosphere (Kavaya and Menzies 1985). Such instruments have been used to study, among other, atmospheric gases, aerosols, clouds, and temperature. The transmission unit consists of a laser source, followed by a series of mirrors, and a beam expander, which sends the collimated light beam vertically up to the open atmosphere. Part of the transmitted radiation is scattered by atmospheric components (i.e., gases, molecules, aerosols, clouds) backward to the LIDAR, where a telescope collects it. The backscattered light is driven to an optical analyser where the optical signal is first spectrally separated, amplified and transformed to an electrical signal. Finally, the signal is digitized and stored in a computer unit. While knowing the aerosol properties (forward problem) and predicting the LIDAR signal is a straightforward calculation, the inverse process is mathematically ill-posed (i.e., non-unique and incomplete solution space), showing a strong sensitivity on input uncertainties. | ||
− | + | TABLE 28 STRENGTHS AND LIMITATIONS OF LIDARS | |
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− | + | TABLE 29 COMPANIES PRODUCING LIDARS | |
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====2.2.2.3 Aerosol chemical properties==== | ====2.2.2.3 Aerosol chemical properties==== |