Abstract

The authors estimate summer mean boundary layer water and energy budgets along a northeast Pacific transect from 35° to 15°N, which includes the transition from marine stratocumulus to trade cumulus clouds. Observational data is used from three A-Train satellites, Aqua, CloudSat, and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO); data derived from GPS signals intercepted by microsatellites of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and the container-ship-based Marine Atmospheric Radiation Measurement Program (ARM) Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI) Investigation of Clouds (MAGIC) campaign. These are unique satellite and shipborne observations providing the first global-scale observations of light precipitation, new vertically resolved radiation budget products derived from the active sensors, and well-sampled radiosonde data near the transect. In addition to the observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) fields are utilized to estimate the budgets. Both budgets approach within 3 W m⁻² averaged along the transect, although uncertainty estimates from the study are much larger than this residual. A mean entrainment rate along the transect of mm s⁻¹ is also estimated. A gradual transition is observed in the climatological mean from the stratocumulus regime to the cumulus regime characterized by an increase in boundary layer height, latent heat flux, rain, and the horizontal advection of dry air and a decrease in entrainment of warm dry air.

Abstract

This study investigates how subgrid cloud water inhomogeneity within a grid spacing of a general circulation model (GCM) links to the global climate through precipitation processes. The effect of the cloud inhomogeneity on autoconversion rate is incorporated into the GCM as an enhancement factor using a prognostic cloud water probability density function (PDF), which is assumed to be a truncated skewed-triangle distribution based on the total water PDF originally implemented. The PDF assumption and the factor are evaluated against those obtained by global satellite observations and simulated by a global cloud-system-resolving model (GCRM). Results show that the factor implemented exerts latitudinal variations, with higher values at low latitudes, qualitatively consistent with satellite observations and the GCRM. The GCM thus validated for the subgrid cloud inhomogeneity is then used to investigate how the characteristics of the enhancement factor affect global climate through sensitivity experiments with and without the factor incorporated. The latitudinal variation of the factor is found to have a systematic impact that reduces the cloud water and the solar reflection at low latitudes in the manner that helps mitigate the too-reflective cloud bias common among GCMs over the tropical oceans. Due to the limitation of the factor arising from the PDF assumption, however, no significant impact is found in the warm rain formation process. Finally, it is shown that the functional form for the PDF in a GCM is crucial to properly characterize the observed cloud water inhomogeneity and its relationship with precipitation.

Abstract

Anomalies of precipitation, cloud, thermodynamic, and radiation variables are analyzed on the large spatial scale defined by the tropical oceans. In particular, relationships between the mean tropical oceanic precipitation anomaly and radiative anomalies are examined. It is found that tropical mean precipitation is well correlated with cloud properties and radiative fields. In particular, the tropical mean precipitation anomaly is positively correlated with the top of the atmosphere reflected shortwave anomaly and negatively correlated with the emitted longwave anomaly. The tropical mean relationships are found to primarily result from a coherent oscillation of precipitation and the area of high-level cloudiness. The correlations manifest themselves radiatively as a modest decrease in net downwelling radiation at the top of the atmosphere, and a redistribution of energy from the surface to the atmosphere through reduced solar radiation to the surface and decreased longwave emission to space. Integrated over the tropical oceanic domain, the anomalous atmospheric column radiative heating is found to be about 10% of the magnitude of the anomalous latent heating. The temporal signature of the radiative heating is observed in the column mean temperature that indicates a coherent phase-lagged oscillation between atmospheric stability and convection. These relationships are identified as a radiative–convective cloud feedback that is observed on intraseasonal time scales in the tropical atmosphere.

Abstract

This study contributes to the estimation of the global mean and zonal distribution of oceanic precipitation rate using complementary information from advanced precipitation measuring sensors and provides an independent reference to assess current precipitation products. Precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and CloudSat cloud profiling radar (CPR) were merged, as the two complementary sensors yield an unprecedented range of sensitivity to quantify rainfall from drizzle through the most intense rates. At higher latitudes, where TRMM PR does not exist, precipitation estimates from Aqua’s Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) complemented CloudSat CPR to capture intense precipitation rates. The high sensitivity of CPR allows estimation of snow rate, an important type of precipitation at high latitudes, not directly observed in current merged precipitation products. Using the merged precipitation estimate from the CloudSat, TRMM, and Aqua platforms (this estimate is abbreviated to MCTA), the authors’ estimate for 3-yr (2007–09) near-global (80°S–80°N) oceanic mean precipitation rate is ~2.94 mm day⁻¹. This new estimate of mean global ocean precipitation is about 9% higher than that of the corresponding Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) value (2.68 mm day⁻¹) and about 4% higher than that of the Global Precipitation Climatology Project (GPCP; 2.82 mm day⁻¹). Furthermore, MCTA suggests distinct differences in the zonal distribution of precipitation rate from that depicted in GPCP and CMAP, especially in the Southern Hemisphere.

Abstract

Daily 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 (MSE_total) is a skillful predictor of median CF of screened low cloud grids. Values of MSE_total 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 < 0.4) or transitional Sc clouds (0.4 < CF < 0.9). With increased stability (MSE_total > 1.00), an abundance of overcast or nearly overcast low clouds exists. While both MODIS and ERA-Interim indicate a fairly smooth transition between the low cloud regimes, CAM5-Base simulates an abrupt shift from trade Cu to Sc, with trade Cu covering both too much area and occurring over excessively strong stabilities. In contrast, CAM-CLUBB simulates a smoother trade Cu to Sc transition (CTST) as a function of MSE_total, albeit with too extensive coverage of overcast Sc in the primary northeastern Pacific subsidence region. While the overall CF distribution in CAM-CLUBB is more realistic, too few transitional clouds are simulated for intermediate MSE_total compared to observations.

Abstract

The Multisensor 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) intercalibrated 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 the 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, correcting for a CLWP bias (based on matchups to clear-sky MODIS scenes), and constructing 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 Sciences Data and Information Services Center.