Cloud fractional coverage: A key uncertainty in current climate models
- State Univ. of New York, Albany, NY (United States)
Climate models being used to study global warming use highly uncertain and widely divergent methods for calculating fractional cloudiness, which plays a significant role in regulating global albedo and climate. In this study the author compares cloud cover formulations used by various climate models with observations of fractional cloudiness and related meteorology derived from surface reports, upper atmospheric soundings, and satellites. He found that relative humidity is the best single predictor of cloud coverage, in agreement with most climate model formulations. However, the precise functional relationships used by climate models to estimate cloud coverage disagree significantly with observed cloud relationships. In the middle troposphere, most climate models probably underestimate cloud coverage since they specify zero cloud amounts when relative humidities are below 60--80%, while observed cloud amounts range from 20--60% at these height and humidity ranges. At humidities close to saturation, current algorithms probably overestimate cloud coverage. Cloud fractional cover observations compiled in this study suggest that at any level in the atmosphere, cloud amount decreases exponentially as humidity falls below 100%, and there is no evidence for critical humidities below which no clouds exist.
- OSTI ID:
- 470969
- Report Number(s):
- CONF-960420-; ISBN 0-884736-02-5; TRN: IM9722%%92
- Resource Relation:
- Conference: 7. global warming international conference and exposition, Vienna (Austria), 1-3 Apr 1996; Other Information: PBD: 1996; Related Information: Is Part Of The 7. global warming international conference and expo: Abstracts; PB: 154 p.
- Country of Publication:
- United States
- Language:
- English
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