The authors exploit three years of data from the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites to document for the first time the seasonally varying vertical structure of cloudiness throughout Antarctica and the high-latitude Southern Ocean. The results provide a baseline reference of Southern Hemisphere high-latitude cloudiness for future observational and modeling studies, and they highlight several previously undocumented aspects and key features of Antarctic cloudiness.The key features of high-latitude Southern Hemisphere cloudiness documented here include 1) a pronounced seasonal cycle in cloudiness over the high-latitude Southern Hemisphere, with higher cloud incidences generally found during the winter season over both the Southern Ocean and Antarctica; 2) two distinct maxima in vertical profiles of cloud incidence over the Southern Ocean, one centered near the surface and another centered in the upper troposphere; 3) a nearly discontinuous drop-off in cloudiness near 8 km over much of the continent that peaks during autumn, winter, and spring; 4) large east-west gradients in upper-level cloudiness in the vicinity of the Antarctic Peninsula that peak during the austral spring season; and 5) evidence that cloudiness in the polar stratosphere is marked not by a secondary maximum at stratospheric levels but by a nearly monotonic decrease with height from the tropopause.Key results are interpreted in the context of the seasonally varying profiles of vertical motion and static stability and compared with results of previous studies.

Multidecade global regressions of inversion strength, vertical velocity, and sea surface temperature (SST) on low cloud amount, from subdaily to multiyear time scales, refute the dominance of seasonal inversion strength on marine low cloud variability. Multiday low cloud variance averaged over the eastern Pacific and Atlantic stratocumulus regions [5 3 10 22 (cloud amount) 2 ] is twice the subdaily variance and 5 times larger than the multimonth variance. The broad multiday band contains most (60%) of the variance, despite strong seasonal (annual) and diurnal spectral peaks. Multiday low cloud amount over the eastern tropical and midlatitude oceans is positively correlated to inversion strength, with a slope of 2%-5% K 21 . Anecdotes show multiday low cloud and inversion strength anomalies propagate equatorward from midlatitudes. Previously shown correlations of low clouds to strong inversions and cool SST on monthly and longer time scales in the stratocumulus regions imply positive cloud-radiative feedbacks, with e-folding time scales of 300 days for SST and 14 days for atmospheric boundary layer temperature. On multimonth time scales, removing the effect of SST on low clouds reduces the low cloud amount explained by inversion strength by a factor of 3, but SST has a small effect at other time scales. Contrary to their positive correlation in the stratocumulus cloud decks, low clouds are anticorrelated to inversion strength over most of the tropics on daily and subdaily time scales.

The Madden‐Julian oscillation (MJO) is the principal source of tropical intraseasonal variability, yet challenges remain to accurately simulate its observed convective behavior and eastward propagation. There is specific need for evaluating the role of water within the MJO, including evaporation, vertical transport, precipitation, and latent heating of the coupled atmosphere‐ocean system. Hydrogen isotope ratios are particularly useful for investigating these aspects of the water cycle. This study complements previous characterization of MJO joint distributions for water vapor and isotopologue concentrations (δD) with consideration of moist entropy in the tropical zonal overturning circulation framework of the MJO. The goals are to distinguish the roles of convective and large‐scale dynamic processes through the life cycle of the MJO and identify shortcomings for modeling MJO humidity, clouds, and convection. From MJO composite analyses, wet equivalent potential temperature (θq) anomalies are largest at 500 hPa and tilt westward with altitude. A positive θq anomaly co‐occurs with the precipitation maxima, and negative θq anomalies co‐occur with subsidence both trailing and leading the convective center. Out of phase with θq, δD anomalies are positive east and negative west of the convective center, coherent with the regional zonal overturning stream function. These results point to a decoupling in the MJO between midtroposphere water vapor, which is tied to convective processes, and the isotopologue ratios, which are tied to the large‐scale circulation. A conceptual model is presented to describe the physical processes that explain the MJO life‐cycle for joint distributions of humidity (q) and water vapor δD.

This study is an aviation-based application of NOAA’s second-generation medium-range Global Ensemble Forecast System Reforecast (GEFS/R; i.e., hindcast or retrospective forecast) dataset. The study produced a downscaled probabilistic prediction of instrument flight conditions at major U.S. airports using an analog approach. This represents an initial step toward applications of reforecast data to probabilistic aviation decision support services. Results from this study show that even at the very coarse resolution of the GEFS/R dataset, the analog approach yielded skillful probabilistic forecasts of flight conditions (i.e., instrument flight rules vs visual flight rules) at most of the Federal Aviation Administration (FAA)’s Core 30 airports. This was particularly true over the central and eastern United States, including the important Golden Triangle, where aircraft flow affects traffic flow management across the entire national airspace system. Additionally, the results suggest that reforecast systems utilizing better horizontal and vertical resolution, in both the modeling system and the reforecast archive, would be very useful for aviation forecasting applications.

Cloud droplet number concentration (Nc) is retrieved from remotely observed marine stratocumulus cloud liquid water path (LWP), cloud optical depth (τc), and cloud thickness, using an optical model that assumes liquid water content (LWC) increases linearly from cloud base. Assuming that LWC is vertically uniform would underestimate τc by 5% and Nc by 14%. Individual retrievals of Nc from 10‐min averages vary by orders of magnitude from long‐term averages. Surface cloud condensation nuclei (CCN) number concentration NCCN is weakly but significantly correlated with Nc (R = 0.3) for the day leading and 6 hr following Nc. Consistent with coalescence and drizzle scavenging cloud droplets, lag correlations show that Nc decreases for 1 hr after the peak area‐average rain rate. Greater observed LWP for lower Nc [d(log Nc)/d(log LWP) = −2.3] is consistent with enhanced entrainment drying of clouds with greater Nc and consistent with removal of Nc by thicker clouds with more coalescence and drizzle. Stronger precipitation in clouds with greater Nc is the opposite sensitivity as expected were LWP to be controlled by the “cloud lifetime” indirect aerosol effect. The strong sensitivity of Nc to LWP suggests that cloud dynamic and thermodynamic forcings drive macrophysical variability that controls Nc in southeastern tropical Pacific stratocumulus clouds. Regressions are relatively insensitive to assumptions about the covariance of errors among the sensors.