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Retrieval of temperature from a multiple-channel Rayleigh-scatter lidar using an optimal estimation method
Applied Optics
|May 14, 2015
Summary
An optimal estimation method (OEM) improves middle atmosphere temperature measurements using Rayleigh-scatter lidar. This advanced technique provides accurate temperature profiles and a comprehensive uncertainty analysis for atmospheric change assessment.
Area of Science:
- Atmospheric science
- Remote sensing
- Lidar technology
Background:
- Middle atmosphere temperature measurement is crucial for assessing atmospheric change.
- Current Rayleigh-scatter lidar temperature retrieval methods have limitations.
Purpose of the Study:
- To introduce and validate an optimal estimation method (OEM) for improved lidar temperature retrievals.
- To address shortcomings in existing temperature retrieval schemes.
Main Methods:
- Development of forward models for simultaneous retrieval of temperature, dead time, and background.
- Application of the optimal estimation method (OEM) for comprehensive uncertainty analysis.
- Characterization of measurement uncertainties including statistical, smoothing, and systematic errors.
Main Results:
- The OEM provides robust temperature profile estimates with detailed uncertainty budgets.
- Vertical resolution and retrieval validity limits are quantitatively determined.
- Successful retrieval of single temperature profiles from multi-channel lidar measurements.
Conclusions:
- The OEM offers a significant advancement for lidar temperature retrievals, overcoming previous limitations.
- This method enables accurate atmospheric change assessment and provides a full uncertainty budget.
- Opens new avenues for integrating active and passive remote sensing instruments in atmospheric science.
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