Abstract

AbstractFuture climate change predictions by global climate models or earth system models diverge significantly, most likely due to their different cloud responses to global warming. There is an uncertainty as to how the cloud frequency (or cloud fraction) and height will change, in turn, affecting the sign, and amount of cloud feedbacks. While satellite observations have been very useful in augmenting information on clouds, it is mostly related to cloud tops, and there is a lack of information on cloud base height (CBH). In this study, a unique record of CBH information was collected at 706 Automated Surface Observing System (ASOS) ceilometer stations to evaluate the ability of the North American Regional Reanalysis (NARR) model to correctly simulate similar information. It was found that NARR can capture the geographical distribution and the seasonal variation of CBH and cloud base frequency (CBF). On average, the CBF values of NARR were 7% fewer and the CBH values of NARR were 631 m lower than those from observations that span the distance from the surface to 7,600 m. NARR simulates CBH better in arid area in the west of the contiguous United States (CONUS) than in humid areas, where NARR frequently predicted cloud bases too low compared with observations. In the west coast area of the CONUS, the discontinuity between high cloud bases over arid inland areas and low marine cloud layers from the Pacific Ocean over coastal areas produced especially large deviations between the NARR‐simulated and ASOS‐observed CBHs.

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