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Article summary:

1. Clouds play an important role in the formation of climate through radiative and dynamical processes.

2. There is a need to observe globally not only macroscopic variables, such as cloud amount and height, but also cloud optical and microphysical properties.

3. This article presents a new algorithm for simultaneous retrievals of cloud-top temperature, optical thickness, and effective particle radius using radiances in channels 1, 3, and 4.

Article analysis:

The article “A Global Determination of Cloud Microphysics with AVHRR Remote Sensing” provides an overview of the importance of clouds in climate formation and the need to observe their microphysical properties on a global scale. The authors present a new algorithm for simultaneous retrievals of cloud-top temperature, optical thickness, and effective particle radius using radiances in channels 1, 3, and 4. The article is well written and provides a comprehensive overview of the topic at hand.

However, there are some potential biases that should be noted when evaluating this article. First, the authors do not provide any evidence or data to support their claims about the importance of clouds in climate formation or their proposed algorithm for retrieving cloud microphysical properties from remote sensing data. Additionally, they do not explore any counterarguments or alternative methods for retrieving these properties from remote sensing data which could provide additional insight into the reliability of their proposed method. Furthermore, they do not discuss any potential risks associated with their proposed method which could lead to inaccurate results if not properly addressed.

In conclusion, while this article provides an informative overview of the importance of clouds in climate formation and presents a novel algorithm for retrieving cloud microphysical properties from remote sensing data, it does not provide sufficient evidence or explore alternative methods or potential risks associated with its proposed approach which could lead to biased results if not properly addressed.