Information content of thermal infrared a microwave bands for simultaneous retrieval of cirrus ice water path and particle effective diameter
Abstract
Due to their high spatial and temporal coverage, cirrus clouds have a profound role in regulating the Earth's energy budget. Variability of their radiative, geometric, and microphysical properties can pose significant uncertainties in global climate model simulations if not adequately constrained. Thus, the development of retrieval methodologies able to accurately retrieve ice cloud properties and present associated uncertainties is essential. The effectiveness of cirrus cloud retrievals relies on accurate a priori understanding of ice radiative properties, as well as the current state of the atmosphere. Current studies have implemented information content theory analyses prior to retrievals to quantify the amount of information that should be expected on parameters to be retrieved, as well as the relative contribution of information provided by certain measurement channels. Through this analysis, retrieval algorithms can be designed in a way to maximize the information in measurements, and therefore ensure enough information is present to retrieve ice cloud properties. In this study, we present such an information content analysis to quantify the amount of information to be expected in retrievals of cirrus ice water path and particle effective diameter using sub-millimeter and thermal infrared radiometry. Preliminary results show these bands to be sensitive to changes in ice water path and effective diameter, and thus lend confidence their ability to simultaneously retrieve these parameters. Further quantification of sensitivity and the information provided from these bands can then be used to design and optimal retrieval scheme. While this information content analysis is employed on a theoretical retrieval combining simulated radiance measurements, the methodology could in general be applicable to any instrument or retrieval approach.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.A31D2210B
- Keywords:
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- 3311 Clouds and aerosols;
- ATMOSPHERIC PROCESSES;
- 3359 Radiative processes;
- ATMOSPHERIC PROCESSES;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 3367 Theoretical modeling;
- ATMOSPHERIC PROCESSES