Renata McCoy

Toward Understanding of Differences in Current Cloud Retrievals of ARM Ground-Based Measurements

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Observed Large-Scale Structures and Diabatic Heating and Drying Profiles during TWP-ICE

Abstract This study documents the characteristics of the large-scale structures and diabatic heating and drying profiles observed during the Tropical Warm Pool–International Cloud Experiment (TWP-ICE), which was conducted in January–February 2006 in Darwin during the northern Australian monsoon season. The examined profiles exhibit significant variations between four distinct synoptic regimes that were observed during the experiment. The active monsoon period is characterized by strong upward motion and large advective cooling and moistening throughout the entire troposphere, while the suppressed and clear periods are dominated by moderate midlevel subsidence and significant low- to midlevel drying through horizontal advection. The midlevel subsidence and horizontal dry advection are largely responsible for the dry midtroposphere observed during the suppressed period and limit the growth of clouds to low levels. During the break period, upward motion and advective cooling and moistening located primarily ...

On the diurnal cycle of deep convection, high‐level cloud, and upper troposphere water vapor in the Multiscale Modeling Framework

embeds a cloud-resolving model (CRM) at each grid column of a general circulation model to replace traditional parameterizations of moist convection and large-scale condensation. This study evaluates the diurnal cycle of deep convection, high-level clouds, and upper troposphere water vapor by applying an infrared (IR) brightness temperature (Tb) and a precipitation radar (PR) simulator to the CRM column data. Simulator results are then compared with IR radiances from geostationary satellites and PR reflectivities from the TropicalRainfallMeasuringMission(TRMM).Whiletheactualsurfaceprecipitationratein the MMF has a reasonable diurnal phase and amplitude when compared with TRMM observations, the IR simulator results indicate an inconsistency in the diurnal anomalies of high-level clouds between the model and the geostationary satellite data. Primarily because of its excessive high-level clouds, the MMF overestimates the simulated precipitation index (PI) and fails to reproduce the observed diurnal cycle phase relationships among PI, high-level clouds, and upper troposphere relative humidity. The PR simulator results show that over the tropical oceans, the occurrence fraction of reflectivity in excess of 20 dBZ is almost 1 order of magnitude larger than the TRMM data especially at altitudes above 6 km. Both results suggest that the MMF oceanic convection is overactive and possible reasons for this bias are discussed. However, the joint distribution of simulated IR Tb and PR reflectivity indicates that the most intense deep convection is found more often over tropical land than ocean, in agreement with previous observational studies.

Interactions between cumulus convection and its environment as revealed by the MC3E sounding array

This study attempts to understand interactions between midlatitude convective systems and their environments through a heat and moisture budget analysis using the sounding data collected from the Midlatitude Continental Convective Clouds Experiment (MC3E) in central Oklahoma. Distinct large-scale structures and diabatic heating and drying profiles are presented for cases of weaker and elevated thunderstorms as well as intense squall line and supercell thunderstorm events during the campaign. The elevated cell events were nocturnal convective systems occurring in an environment having low convective available potential energy (CAPE) and a very dry boundary layer. In contrast, deeper convective events happened during the morning into early afternoon within an environment associated with large CAPE and a near-saturated boundary layer. As the systems reached maturity, the diagnosed diabatic heating in the latter deep convective cases was much stronger and of greater vertical extent than the former. Both groups showed considerable diabatic cooling in the lower troposphere, associated with the evaporation of precipitation and low-level clouds. The horizontal advection of moisture also played a dominant role in moistening the lower troposphere, particularly for the deeper convective events, wherein the near surface southeasterly flow allows persistent low-level moisture return from the Gulf of Mexico to support convection. The moisture convergence often was present before these systems develop, suggesting a strong correlation between the large-scale moisture convergence and convection. Sensitivity tests indicated that the uncertainty in the surface precipitation and the size of analysis domain mainly affected the magnitude of these analyzed fields rather than their vertical structures.

The Flexible Climate Data Analysis Tools (CDAT) for Multi-model Climate Simulation Data

Being able to incorporate, inspect, and analyze data with newly developed technologies, diagnostics, and visualizations in an easy and flexible way has been a longstanding challenge for scientists interested in understanding the intrinsic and extrinsic empirical assessment of multi-model climate output. To improve research ability and productivity, these technologies and tool must be made easily available to help scientists understand and solve complex scientific climate changes. To increase productivity and ease the challenges of incorporating new tools into the hands of scientists, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) developed the Climate Data Analysis Tools (CDAT). CDAT is an application for developing and bringing together disparate software tools for the discovery, examination, and intercomparison of coupled multi-model climate data. By collaborating with top climate institutions, computational organizations, and other science communities, the CDAT community of developers is leading the way to provide proven data management, analysis, visualization, and diagnostics capabilities to scientists. This communitywide effort has developed CDAT into a powerful and insightful application for knowledge discovery of observed and simulation climate data. As an analysis engine in the Earth System Grid (ESG) data infrastructure, CDAT is making it possible to remotely access and analyze climate data located at multiple sites around the world.

Climate Data Analysis Tools Facilitate Scientific Investigations

Insightful analysis of geophysical phenomena often depends on the choice of software tools to access, manipulate, and visualize data sets of interest. These data exploration tasks can be efficiently executed in a single computational environment by the freely distributed Climate Data Analysis Tools (CDAT; http://www-pcmdi.llnl.gov/software-portal/). Although CDAT has been designed primarily for climate science applications, its capabilities are increasingly being enhanced to address the data needs of other geophysical sciences. The CDAT software is based on the object-oriented Python computer language, but the software extends existing constructs to achieve capabilities that are relevant to any gridded geophysical data. Depending on the users preference, CDAT can be fully deployed by either a script or graphical user interface.

ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scm_forcing)

The constrained variational objective analysis approach described in Zhang and Lin [1997] and Zhang et al. [2001]was used to derive the large-scale single-column/cloud resolving model forcing and evaluation data set from the observational data collected during Midlatitude Continental Convective Clouds Experiment (MC3E), which was conducted during April to June 2011 near the ARM Southern Great Plains (SGP) site. The analysis data cover the period from 00Z 22 April - 21Z 6 June 2011. The forcing data represent an average over the 3 different analysis domains centered at central facility with a diameter of 300 km (standard SGP forcing domain size), 150 km and 75 km, as shown in Figure 1. This is to support modeling studies on various-scale convective systems.