Understanding the Microphysical Control and Spatial-Temporal Variability of Warm Rain Probability Using CloudSat and MODIS Observations.

By combining measurements from MODIS and the CloudSat radar, we develop a parameterization scheme to quantify the combined microphysical controls by liquid water path (LWP) and cloud droplet number concentration (CDNC) of the probability of precipitation (PoP) in marine low cloud over tropical oceans. We demonstrate that the spatial-temporal variation of grid-mean in-cloud can be largely explained by the variation of the joint probability density function of LWP and CDNC in the phase space specified by the bivariate PoP (LWP and CDNC) function. Through a series of sensitivity tests guided by this understanding, we find that in the Southeastern Pacific and Atlantic the stratocumulus to cumulus transition of the is mainly due to the variation of CDNC while the annual cycle is mainly due to the variation of LWP. The results of this study provide a viable way to diagnose the root cause of warm rain problems in global climate models.

An Observational View of Relationships Between Moisture Aggregation, Cloud, and Radiative Heating Profiles.

Data from several coincident satellite sensors are analyzed to determine the dependence of cloud and precipitation characteristics of tropical regions on the variance in the water vapor field. Increased vapor variance is associated with decreased high cloud fraction and an enhancement of low-level radiative cooling in dry regions of the domain. The result is found across a range of sea surface temperatures and rain rates. This suggests the possibility of an enhanced low-level circulation feeding the moist convecting areas when vapor variance is large. These findings are consistent with idealized models of self-aggregation, in which the aggregation of convection is maintained by a combination of low-level radiative cooling in dry regions and mid-to-upper-level radiative warming in cloudy regions.

The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP).

The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988 - 2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) inter-calibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2 and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and monthly-mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, a correction for a CLWP bias (based on matchups to clear-sky MODIS scenes), and the construction of a total (cloud+rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e. CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from -15% (e.g. global oceanic stratocumulus decks) to +5-10% (e.g. portions of the higher-latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Science Data and Information Services Center (http://disc.sci.gsfc.nasa.gov).