Terence L. Kubar

Understanding the Importance of Microphysics and Macrophysics for Warm Rain in Marine Low Clouds. Part I: Satellite Observations

The importance of macrophysical variables [cloud thickness, liquid water path (LWP)] and microphysical variables (effective radius re, effective droplet concentration Neff) on warm drizzle intensity and frequency across the tropics and subtropics is studied. In this first part of a two-part study, Moderate Resolution Imaging Spectroradiometer (MODIS) optical and CloudSat cloud radar data are used to understand warm rain in marine clouds. Part II uses simple heuristic models. Cloud-top height and LWP substantially increase as drizzle intensity increases. Droplet radius estimated from MODIS also increases with cloud radar reflectivity (dBZ) but levels off as dBZ . 0, except where the influence of continental pollution is present, in which case a monotonic increase of re with drizzle intensity occurs. Off the Asian coast and over the Gulf of Mexico, re values are smaller (by several mm) and Neff values are larger compared to more remote marine regions. For heavy drizzle intensity, both re and Neff values off the Asian coast and over the Gulf of Mexico approach re and Neff values in more remote marine regions. Drizzle frequency, defined as profiles in which maximum dBZ .2 15, increases dramatically and nearly uniformly when cloud tops grow from 1 to 2 km. Drizzle frequencies exceed 90% in all regions when LWPs exceed 250 g m 22 and Neff values are below 50 cm 23 , even in regions where drizzle occurs infrequently on the whole. The fact that the relationship among drizzle frequency, LWP, and Neff is essentially the same for all regions suggests a near universality among tropical and subtropical regions.

Understanding the Importance of Microphysics and Macrophysics for Warm Rain in Marine Low Clouds. Part II: Heuristic Models of Rain Formation

Two simple heuristic model formulations for warm rain formation are introduced and their behavior explored. The first, which is primarily aimed at representing warm rain formation in shallow convective clouds, is a continuous collection model that uses an assumed cloud droplet size distribution consistent with observations as the source of embryonic drizzle drops that are then allowed to fall through a fixed cloud, accreting cloud droplets. The second, which is applicable to steady-state precipitation formation in stratocumulus, is a simple two-moment bulk autoconversion and accretion model in which cloud liquid water is removed by drizzle formation and replenished on a externally specified time scale that reflects the efficacy of turbulent overturning that characterizes stratocumulus. The models’ behavior is shown to be broadly consistent with observations from the A-Train constellation of satellites, allowing the authors to explore reasons for changing model sensitivity to microphysical and macrophysical cloud properties. The models are consistent with one another, and with the observations, in that they demonstrate that the sensitivity of rain rate to cloud droplet concentration Nd (which here represents microphysical influence) is greatest for weakly precipitating clouds (i.e., for low cloud liquid water path and/or high Nd). For the steady-state model, microphysical sensitivity is shown to strongly decrease with the ratio of replenishment to drizzle time scales. Thus, rain from strongly drizzling and/or weakly replenished clouds shows low sensitivity to microphysics. This is essentially because most precipitation in these clouds is forming via accretion rather than autoconversion. For the continuous-collection model, as cloud liquid water content increases, the precipitation rate becomes more strongly controlled by the availability of cloud liquid water than by the initial embryo size or by the cloud droplet size. The models help to explain why warm rain in marine stratocumulus clouds is sensitive to Nd but why precipitation from thicker cumulus clouds appears to be less so.

Radiative and Convective Driving of Tropical High Clouds

Using satellite cloud data from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and collocated precipitation rates from the Advanced Microwave Scanning Radiometer (AMSR), it is shown that rain rate is closely related to the amount of very thick high cloud, which is a better proxy for precipitation than outgoing longwave radiation (OLR). It is also shown that thin high cloud, which has a positive net radiative effect on the top-of-atmosphere (TOA) energy balance, is nearly twice as abundant in the west Pacific compared to the east Pacific. For a given rain rate, anvil cloud is also more abundant in the west Pacific. The ensemble of all high clouds in the east Pacific induces considerably more TOA radiative cooling compared to the west Pacific, primarily because of more high, thin cloud in the west Pacific. High clouds are also systematically colder in the west Pacific by about 5 K. The authors examine whether the anvil cloud temperature is better predicted by low-level equivalent potential temperature (E), or by the peak in upper-level convergence associated with radiative cooling in clear skies. The temperature in the upper troposphere where E is the same as that at the lifting condensation level (LCL) seems to influence the temperatures of the coldest, thickest clouds, but has no simple relation to anvil cloud. It is shown instead that a linear relationship exists between the median anvil cloud-top temperature and the temperature at the peak in clear-sky convergence. The radiatively driven clear-sky convergence profiles are thus consistent with the warmer anvil clouds in the EP versus the WP.

On the Annual Cycle, Variability, and Correlations of Oceanic Low-Topped Clouds with Large-Scale Circulation Using Aqua MODIS and ERA-Interim

AbstractEight 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°S to 25°N for 90-day running means and exceed 0.70 between LCF and 500-hPa omega (ω500) for over one-third of oceans from 50°S to 50°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 n...

Boundary Layer and Cloud Structure Controls on Tropical Low Cloud Cover Using A-Train Satellite Data and ECMWF Analyses

Abstract The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), CloudSat radar, and the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data on the A-Train constellation complemented with the European Centre for Medium-Range Forecasts (ECMWF) analyses are used to investigate the cloud and boundary layer structure across a 10° wide cross section starting at 5°S near the international date line and extending to 35°N near the California coast from March 2008 to February 2009. The mean large-scale inversion height and low-level cloud tops, which correspond very closely to each other, are very shallow (∼500 m) over cold SSTs and high static stability near California and deepen southwestward (to a maximum of ∼1.5–2.0 km) along the cross section as SSTs rise. Deep convection near the ITCZ occurs at a surface temperature close to 298 K. While the boundary layer relative humidity (RH) is nearly constant where a boundary layer is well defined, it drops sharply near cloud top i...

A test of the simulation of tropical convective cloudiness by a cloud-resolving model.

A methodology is described for testing the simulation of tropical convective clouds by models through comparison with observations of clouds and precipitation from earth-orbiting satellites. Clouds are divided into categories that represent convective cores: moderately thick anvil clouds and thin high clouds. Fractional abundances of these clouds are computed as a function of rain rate. A three-dimensional model is forced with steady forcing characteristics of tropical Pacific convective regions, and the model clouds are compared with satellite observations for the same regions. The model produces a good simulation of the relationship between the precipitation rate and optically thick cold clouds that represent convective cores. The observations show large abundances of anvil cloud with a strong dependence on rain rate, but the model produces too little anvil cloud by a factor of about 4 and with a very weak dependence on the rain rate. The observations also show probability density functions for outgoing longwave radiation (OLR) and albedo with maxima that correspond to extended upper-level cold clouds, whereas the model does not. The sensitivity of the anvil cloud simulation to model parameters is explored using a two-dimensional model. Both cloud physical parameters and mean wind shear effects are investigated. The simulation of anvil cloud can be improved while maintaining a good simulation of optically thick cloud by adjusting the cloud physics parameters in the model to produce more ice cloud and less liquid water cloud.

Regional Assessments of Low Clouds against Large-Scale Stability in CAM5 and CAM-CLUBB Using MODIS and ERA-Interim Reanalysis Data

AbstractDaily gridded cloud data from MODIS and ERA-Interim reanalysis have been assessed to examine variations of low cloud fraction (CF) and cloud-top height and their dependence on large-scale dynamics and a measure of stability. To assess the stratocumulus (Sc) to cumulus (Cu) transition (STCT), the observations are used to evaluate two versions of the NCAR Community Atmosphere Model version 5 (CAM5), both the base model and a version that has implemented a new subgrid low cloud parameterization, Cloud Layers Unified by Binormals (CLUBB).The ratio of moist static energy (MSE) at 700–1000 hPa (MSEtotal) is a skillful predictor of median CF of screened low cloud grids. Values of MSEtotal less than 1.00 represent either conditionally or absolutely unstable layers, and probability density functions of CF suggest a preponderance of either trade Cu (median CF 1.00), an abundance of overcast or nearly overcast low clouds ...