Rigorous Estimates of the Errors for the Remote Sensing Retrievals: Implementation and Illustration for Aerosol Properties Inverted from Ground-based Observations
Abstract
Reliable estimation of the errors is one of the most challenging and important tasks in the generation of reliable remote sensing retrieval product. In this presentation we discuss the methodology of error estimates generation realized in GRASP (Generalized Retrieval of Aerosol and Surface Properties). This inversion algorithm is based on the elaborated statistical optimization approach designed to retrieve detailed aerosol properties from diverse observations [Dubovik et al., 2011, 2014]. The employed approach is designed to provide statistically optimum solution that allows for comprehensive characterizations of retrieval errors. We illustrate the use of generated errors estimates for analysis accuracy tendencies in retrieval of aerosol properties from ground-based observations radiometers and lidar. Our studies are focused on the detailed analysis of the structure of retrieved parameter correlation matrices in the retrieval of multi-component aerosol mixtures. It was shown that when the optical properties of aerosol components are not very different, and/or observation conditions are rather limited the reliable retrieval of detailed parameters, such as complex refractive index, size distribution, etc., becomes very challenging. In such situations the error variances of each parameters are large and highly correlated. At the same, it is always possible to identify the characteristics that can be obtained with the reasonable accuracy. For example, total aerosol scattering and absorption of aerosol mixture can be always accurately estimated even if separation of the component properties is questionable. This and other tendencies less obvious, but quite interesting can be identified using the analysis of the correlation matrix structure. Thus, the suggested analysis of error correlation appears to be useful approach for optimizing observation schemes and retrieval setups.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.A13K2981H
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0321 Cloud/radiation interaction;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0345 Pollution: urban and regional;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0360 Radiation: transmission and scattering;
- ATMOSPHERIC COMPOSITION AND STRUCTURE