High Precision Remote Air Temperature Measurement Using Vibro-Rotational Raman Scattering

Abstract:

Temperature fluctuations can affect several atmospheric processes. For example, there is strong theoretical and experimental evidence that a decrease in temperature of 2-3^° C can enhance the nucleation rate of new particles in the atmosphere by an order of magnitude. Furthermore, temperature fluctuations play a significant role in determining the water vapor mixing ratio and supersaturation, which affect the activation and growth rates of cloud droplets as well as aerosol humidification. For most Light Detection And Ranging (LiDAR) applications, temperature is typically inferred from pure rotational Raman (PRR). However, Mie scattering due to aerosol or cloud droplets can cause leakage of elastically scattered light through optical filters. This limits modern LiDAR from measuring the temperature within optically thick clouds. Temperature can also be inferred from vibro-rotational Raman (VRR) scattering in a similar fashion to PRR. VRR has the advantage of being much farther spectrally separated from elastic scattering than PRR and, therefore, is less sensitive to biases resulting from elastic scattering. Additionally, VRR scattering by major atmospheric constituents, such as N₂ and O₂, are spectrally separated, making for simpler analysis in post-processing. We measured VRR spectra of atmospheric O₂ and N₂ using a multi-pass configuration that consists of two-concave mirrors to pass a 10 W 532nm laser through a shared focal point 40 times. A 500 mm imaging spectrograph in conjunction with a long-pass filter was used to record the VRR spectrum. We show that temperature cannot be accurately determined from VRR using a simple rigid rotor model of atmospheric molecules, but a non-rigidity correction needs to be applied to improve the accuracy of the measurement. We inferred temperature from VRR spectra with accuracy less than 1K on an absolute scale and precision less than 1K without the need for a temperature calibration. This technique could be used to measure temperature profiles in heavily polluted environments, or to remotely quantify temperatures in the immediate vicinity of wildfires, for example, to study the effect of humidification on atmospheric aerosols.