J.-L. F. Li

Multimodel evaluation of cloud phase transition using satellite and reanalysis data

We take advantage of climate simulations from two multimodel experiments to characterize and evaluate the cloud phase partitioning in 16 general circulation models (GCMs), specifically the vertical structure of the transition between liquid and ice in clouds. We base our analysis on the ratio of ice condensates to the total condensates (phase ratio, PR). Its transition at 90% (PR90) and its links with other relevant variables are evaluated using the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation Cloud Product climatology, reanalysis data, and other satellite observations. In 13 of 16 models, the PR90 transition height occurs too low (6u2009km to 8.4u2009km) and at temperatures too warm (−13.9°C to −32.5°C) compared to observations (8.6u2009km, −33.7°C); features consistent with a lack of supercooled liquid with respect to ice above 6.5u2009km. However, this bias would be slightly reduced by using the lidar simulator. In convective regimes (more humid air and precipitation), the observed cloud phase transition occurs at a warmer temperature than for subsidence regimes (less humid air and precipitation). Only few models manage to roughly replicate the observed correlations with humidity (5/16), vertical velocity (5/16), and precipitation (4/16); 3/16 perform well for all these parameters (MPI-ESM, NCAR-CAM5, and NCHU). Using an observation-based Clausius-Clapeyron phase diagram, we illustrate that the Bergeron-Findeisen process is a necessary condition for models to represent the observed features. Finally, the best models are those that include more complex microphysics.

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...

Evaluation of an ice cloud parameterization based on a dynamical‐microphysical lifetime concept using CloudSat observations and the ERA‐Interim reanalysis

[1]xa0This study validates the cloud ice water content (IWC, non-precipitating ice/non-snow) produced by a unique prognostic cloud ice parameterization when used in the UCLA atmospheric general circulation model against CloudSat observations, and also compares it with the ERA-Interim reanalysis. A distinctive aspect of this parameterization is the novel treatment of the conversion of cloud ice to precipitating snow. The ice-to-snow autoconversion time scale is a function of differential infrared radiative heating and environmental static stability. The simulated IWC is in agreement with CloudSat observations in terms of its magnitude and three-dimensional structure. The annual and seasonal means of the zonal-mean IWC profiles from the simulations both show a local maximum in the upper troposphere in the tropics associated with deep convection, and other local maxima in the mid-troposphere in midlatitudes in both hemispheres associated with storm tracks. In contrast to the CloudSat values, the reanalysis shows much smaller IWC values in the tropics and much larger values in the lower troposphere in midlatitudes. The different vertical structures and magnitudes of IWC between the simulations and the reanalysis are likely due to differences in the parameterization of various processes in addition to the ice-to-snow autoconversion, including ice sedimentation, temperature thresholds for ice deposition and cumulus detrainment of cloud ice. However, a series of sensitivity experiments supports the conclusion that the model with a constant autoconversion time scale cannot reproduce the correct IWC distribution in both the tropics and midlatitudes, which strongly suggests the importance of physically based effects on the autoconversion timescale.

Characterizing the radiative impacts of precipitating snow in the ECMWF Integrated Forecast System global model

Global weather and climate models often exclude the effects of precipitating hydrometeors and convective core mass on radiative fluxes. In particular, many models split the ice phase into separate “cloud ice” and “snow” categories representing the smaller and larger ice particles, respectively; a separation that is generally not well defined in observations. A version of the European Centre for Medium-Range Weather Forecasts (ECMWF) global numerical weather prediction model which includes the radiative effects of cloud liquid, cloud ice, and precipitating snow is used to investigate the impact of including and excluding the radiative effects of the precipitating snow category. The results show that exclusion of precipitating snow in the radiation calculations leads to differences in the shortwave and longwave radiative fluxes of 5–15u2009Wu2009m−2 in strongly precipitating and convective areas. These differences are of the same order of magnitude as the systematic errors in the model compared to satellite observations. Corresponding biases in the radiative heating profiles are on the order of 0.15u2009Ku2009d−1. The results imply that precipitating snow should be included in the radiative calculations in all weather and climate models in the context of improving model fidelity and reducing compensating errors.

Characterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis

AbstractThe authors present an observationally based evaluation of the vertically resolved cloud ice water content (CIWC) and vertically integrated cloud ice water path (CIWP) as well as radiative shortwave flux downward at the surface (RSDS), reflected shortwave (RSUT), and radiative longwave flux upward at top of atmosphere (RLUT) of present-day global climate models (GCMs), notably twentieth-century simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), and compare these results to those of the third phase of the Coupled Model Intercomparison Project (CMIP3) and two recent reanalyses. Three different CloudSat and/or Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined ice water products and two methods are used to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations.The results s...