Satellite-based detection of daytime supercooled liquid-topped mixed-phase clouds over the Southern Ocean using the advanced Himawari Imager
Inaccurate mixed‐phase cloud parameterizations over the Southern Ocean remain one of the largest sources of disagreement among global models in determining shortwave cloud radiative feedbacks. Suitable global observations supporting model improvements are currently unavailable. The conventional sate...
| Published in: | Journal of Geophysical Research: Atmospheres |
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| Main Authors: | , , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley-Blackwell Publishing Inc.
2019
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| Subjects: | |
| Online Access: | https://eprints.utas.edu.au/31627/ https://eprints.utas.edu.au/31627/1/134986%20-%20Satellite-based%20detection%20of%20daytime%20supercooled%20liquid-topped%20mixed-phase%20clouds.pdf |
| Summary: | Inaccurate mixed‐phase cloud parameterizations over the Southern Ocean remain one of the largest sources of disagreement among global models in determining shortwave cloud radiative feedbacks. Suitable global observations supporting model improvements are currently unavailable. The conventional satellite cloud phase retrieval from passive radiometers is strongly biased toward cloud top without further information on the subcloud phase. Mixed‐phase clouds with the liquid‐top mixed‐phase (LTMP) structures are often classified simply as supercooled liquid. This paper presents a daytime multispectral detection algorithm for LTMP clouds, based on differential absorption between liquid and ice in shortwave infrared bands (1.61 and 2.25 μm). The LTMP algorithm, previously developed for polar‐orbiting sensors, is applied to Himawari‐8 Advanced Himawari Imager (the first of the next‐generation geostationary satellites) to probe subcloud phase for mixed‐phase clouds over the Southern Ocean. The results are compared with spaceborne active sensor data from CloudSat and CALIPSO. Ship‐based field experiment measurements are examined for selected cases to provide a more direct assessment of algorithm performance. The results show that applying the LTMP algorithm to geostationary satellites has potential to provide advanced time‐resolved observations for mixed‐phase clouds globally with improved sublayer cloud phase information that can support enhancement and validation of global models. |
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