Kubar, TL; Waliser, DE; Li, JL; Jiang, XN (2012). On the Annual Cycle, Variability, and Correlations of Oceanic Low-Topped Clouds with Large-Scale Circulation Using Aqua MODIS and ERA-Interim. JOURNAL OF CLIMATE, 25(18), 6152-6174.
Eight years of Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) level-3 cloud data in conjunction with collocated Interim ECMWF Re-Analysis are used to investigate relationships between isolated low-topped cloud fraction (LCF) and dynamics/thermodynamics versus averaging time scale. Correlation coefficients between LCF and -SST exceed 0.70 over 56% of ocean regions from 25 degrees S to 25 degrees N for 90-day running means and exceed 0.70 between LCF and 500-hPa omega (omega(500)) for over one-third of oceans from 50 degrees S to 50 degrees N. Correlations increase most dramatically by increasing the averaging time scale from 1 day to about 15, owing to the large LCF synoptic variability and random effects that are suppressed by averaging. In five regions selected with monthly mean SSTs between 291 and 303 K, SST decreases by -0.13 K %(-1) low-cloud cover increase. Monthly LCF is also correlated with estimated inversion strength (EIS), which is SST dominated in low latitudes and free tropospheric temperature dominated in the northeast Atlantic, Pacific, and midlatitudes, though SST and stability are poor predictors of LCF over the southern oceans. Where the fraction of variance explained by the annual LCF harmonic is high, maximum LCF tends to lead minimum SST by similar to 15-30 days such that clouds can amplify the SST annual cycle, especially when LCF maxima coexist with insolation minima. Monthly mean LCF tends to scale with omega(500) exponentially over the convective margins and offshore of the Pacific Northwest, but daily climatology relationships indicate that LCF levels off and even diminishes for omega(500) > 0.05 Pa s(-1), suggesting a limit through, perhaps, a too strong suppression of boundary layer heights. This suggests the need for dynamic-regime analysis in diagnosing low cloud/circulation feedbacks.