An investigation of microphysics and subgrid-scale variability in warm-rain clouds using the A-Train observations and a multiscale modeling framework

A common problem in climate models is that they are likely to produce rain at a faster rate than is observed and therefore produce too much light rain (e.g., drizzle). Interestingly, the Pacific Northwest National Laboratory (PNNL) multiscale modeling framework (MMF), whose warm-rain formation process is more realistic than other global models, has the opposite problem: the rain formation process in PNNL-MMF is less efficient than the real world. To better understand the microphysical processes in warm cloud, this study documents the model biases in PNNL-MMF and evaluates warm cloud properties, subgrid variability, and microphysics, using A-Train satellite observations to identify sources of model biases in PNNL-MMF. Like other models PNNL-MMF underpredicts the warm cloud fraction with compensating large optical depths. Associated with these compensating errors in cloudiness are compensating errors in the precipitation process. For a given liquid water path, clouds in the PNNL-MMF are less likely to produce rain than are real-world clouds. However, when the model does produce rain it is able to produce stronger precipitation than reality. As a result PNNL-MMF produces about the correct mean rain rate with an incorrect distribution of rates. The subgrid variability in PNNL-MMF is also tested, and results are fairly consistent with observations, suggesting that the possible sources of model biases are likely to be due to errors in its microphysics or dynamics rather than errors in the subgrid-scale variability produced by the embedded cloud resolving model

CloudSat and CALIPSO within the A-Train: ten years of actively observing the Earth system

One of the most successful demonstrations of an integrated approach to observe Earth from multiple perspectives is the A-Train satellite constellation (e.g. Stephens et al., 2002). The science enabled by this constellation flourished with the introduction of the two active sensors carried by the NASA CloudSat and the NASA/CNES Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites that were launched together on April 28th, 2006. These two missions have provided a 10-year demonstration of coordinated formation flying that made it possible to develop integrated products and that offered new insights on key atmospheric processes. The progress achieved over this decade of observations, summarized in this paper, clearly demonstrate the fundamental importance of the vertical structure of clouds and aerosol for understanding the influences of the larger scale atmospheric circulation on aerosol, the hydrological cycle, the cloud-scale physics and on the formation of the major storm systems of Earth. The research also underscored inherent ambiguities in radiance data in describing cloud properties and how these active systems have greatly enhanced passive observation. It is now clear that monitoring the vertical structure of clouds and aerosol is essential and a climate data record is now being constructed. These pioneering efforts are to be continued with EarthCARE mission planned for launch in 2019

Relationships between aerosol, cloud, and precipitation as observed from the A-train constellation of spaceborne sensors

Department Head: Richard Harlan Johnson.Includes bibliographical references (pages 91-99).Data from several sensors flying in NASA's A-train constellation of satellites are analyzed to examine global relationships between aerosol, clouds and precipitation with particular emphasis placed on the Earth's radiation budget. The multi-sensor data are applied to two specific studies. The first addresses the response of cloud water path to atmospheric aerosol burden and the second quantifies relationships between tropical precipitation and radiation within the context of radiative-convective equilibrium. The first focused study presents a global multi-sensor satellite examination of aerosol indirect effects on warm oceanic clouds. The study centers on the water path response of cloud to aerosol burden. It is demonstrated that high aerosol environments are associated with reduced liquid water path in nonprecipitating clouds and that the reduction in liquid water path reduces the albedo enhancement expected from decreasing effective radius. Furthermore the reduction in liquid water path is greater in thermodynamically unstable environments than in stable environments, suggesting a greater sensitivity of liquid water path to aerosol in cumulus clouds than stratus clouds. In sharp contrast with nonprecipitating clouds, the cloud liquid water path of transitional and precipitating clouds increases dramatically with aerosol, which may be indicative of an inhibited coalescence process. Following from these observations, the magnitude of the aerosol indirect albedo sensitivity (IAS) is calculated as the sum of distinct cloud regimes over the global oceans. Selection of the cloud regimes is guided by the observation that both thermodynamic stability and the presence of precipitation affect the sensitivity of cloud albedo to aerosol concentrations. The IAS, defined as the change in warm cloud albedo for a fractional change in aerosol burden, is found to be -0.42 ±0.38 Wm-2 over the global oceans. Twenty five percent of the effect is due to precipitating clouds despite the fact that only eight percent of clouds are identified as precipitating. An additional assumption of the anthropogenic aerosol fraction provides an estimate of the indirect albedo forcing (IAF) of -0.13 ± 0.14 Wm-2, which is significantly lower than the range provided by climate model estimates. The second focused study presents an analysis of anomalous precipitation, cloud, thermodynamic, and radiation variables on the tropics-wide mean spatial scale. 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 cooling 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. 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 intra-seasonal timescales associated with the Madden-Julian oscillation in the tropical atmosphere. A composite analysis showing the spatial patterns of the anomalies provides evidence that the feedback mechanism works through a modulation of the strength of the large-scale tropical overturning circulations

Modeling polarized radiances toward the development of an aerosol retrieval method

October, 2005.Includes bibliographical references (pages 107-109).Polarized radiances reflected from aerosol laden atmospheres were modeled. An atmospheric aerosol model was defined which corresponds to a clean oceanic environment composed mainly of sulfate particles. This model specifies an aerosol size distribution and optical properties. Fifteen atmospheric scenes composed of varying solar zenith angles and aerosol optical depths were defined to explore the scene dependent nature of the top of the atmosphere total and polarized radiances. The sensitivity of the forward model to aerosol optical depth was examined for these fifteen cases. A comprehensive error assessment was also performed for each of the fifteen cases. This assessment included the explicit modeling of errors due to aerosol model assumptions. The sensitivities were combined with the error estimates to produce signal to noise ratios for each scene. The signal to noise ratio demonstrates a significant viewing angle dependence for all of the fifteen cases. It was found that the angles with the largest signal to noise ratio for the total radiance are in the backscatter direction while angles in the sun glint demonstrated the lowest signal to noise ratio. It was also observed that the model sensitivity tends to decrease with optical depth while errors are shown to increase with optical. Consequently, the signal to noise ratio tends to decrease strongly with optical depth. Finally, it was found that the signal to noise ratio for the total radiances tends to be about three times as large as the polarized radiances. The total error estimates are used to develop an optimal estimation two-channel optical depth retrieval. Due to the greater signal to noise ratio of the total radiances, the polarized radiances were not used in the retrieval. Synthetic data were created to test the retrieval functionality. Two sources of bias were demonstrated. First, an a priori bias was shown which biases the retrieval towards the a priori initial guess. A second source of bias is introduced through the necessity to assume an aerosol model. It is demonstrated that these assumptions may bias the retrieval either high or low. Viewing geometries with small signal to noise ratios are shown to have a larger bias than those with large signal to noise ratio. It was concluded that the ideal multi-angular retrieval will utilize viewing geometries with large signal to noise ratios to limit the degree of the above biases. Finally, the retrieval is applied to a small sampling of POLDER II radiance data. The retrieved optical depths tend to be in qualitatively good agreement with the POLDER optical depths.Research was supported through the Ball Aerospace-CSU Joint Research program under Agreement #PO 03DLB10045

Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models

<p>Data supporting the findings of DOI: 10.1175/MWR-D-23-0078.1, a 2023 Monthly Weather Review publication with the same title as this dataset.</p&gt