Sonia Lasher-Trapp

Rain in shallow cumulus over the ocean: the RICO Campaign

Shallow, maritime cumuli are ubiquitous over much of the tropical oceans, and characterizing their properties is important to understanding weather and climate. The Rain in Cumulus over the Ocean (RICO) field campaign, which took place during November 2004–January 2005 in the trades over the western Atlantic, emphasized measurements of processes related to the formation of rain in shallow cumuli, and how rain subsequently modifies the structure and ensemble statistics of trade wind clouds. Eight weeks of nearly continuous S-band polarimetric radar sampling, 57 flights from three heavily instrumented research aircraft, and a suite of ground- and ship-based instrumentation provided data on trade wind clouds with unprecedented resolution. Observational strategies employed during RICO capitalized on the advances in remote sensing and other instrumentation to provide insight into processes that span a range of scales and that lie at the heart of questions relating to the cause and effects of rain from shallow ...

The Influence of Entrainment and Mixing on the Initial Formation of Rain in a Warm Cumulus Cloud

AbstractThe objective of this study is to address the problem of the production of rain in warm cumulus clouds that has been observed to occur within about 20 min. A hybrid model approach is used where a microphysical parcel model is run along trajectories produced by a 3D cloud model, with sufficiently high resolution to allow explicit representation of the effects of entrainment and mixing. The model calculations take the next step from the previous study, which showed that entrainment and mixing can accelerate the diffusional growth of cloud droplets to the production of raindrops by collision and coalescence. The mechanism depends on the variability in droplet trajectories arriving at a given location and time in a cumulus cloud. The resulting broadening favors collisions among droplets in the main peak of the droplet size distribution, which leads to the production of raindrop embryos. However, this production and the subsequent growth of the embryos to become raindrops only occur in regions of relat...

The Role of Giant and Ultragiant Nuclei in the Formation of Early Radar Echoes in Warm Cumulus Clouds

Abstract Observations of the formation of the first radar echoes in small cumulus clouds are compared with results of a stochastic coalescence model run in the framework of a closed parcel. The observations were made with an instrumented aircraft and a high-powered dual-wavelength radar during the Small Cumulus Microphysics Study (SCMS) in Florida. The principal conclusion is that coalescence growth on giant and ultragiant nuclei may be sufficient to explain observations. The concentration of cloud droplets varied from under 300 cm−3 when surface winds were from the ocean, to over 1000 cm−3 when the wind direction was from the mainland. Although there is a slight tendency for the altitude of the first 0-dBZ echo to be lower on average in maritime than in continental clouds there were several cases where it was higher. The model results suggest that the lack of correlation is consistent with drops forming on giant and ultragiant nuclei. The first 0-dBZ echo was observed to form at higher altitudes in cloud...

Early Radar Echoes from Ultragiant Aerosol in a Cumulus Congestus: Modeling and Observations

Abstract The growth of ultragiant aerosol (UGA) in a Lagrangian framework within a simulated three-dimensional cloud is analyzed and compared with radar and aircraft observations of a cumulus congestus collected during the Small Cumulus Microphysics Study (SCMS). UGA are ingested into the simulated cloud and grow by continuous collection; the resulting radar reflectivity factor and raindrop concentrations are evaluated at 1-min intervals. The calculations produce a substantial echo (>30 dBZ) within a short time (18 min), containing few raindrops (0.3 L−1). The calculated radar echo is very sensitive to the amount of UGA ingested into the modeled cloud and its liquid water content. The modeled radar echo and raindrop concentrations are consistent with the observations in that the differences fall within the modeling and measurement limitations and uncertainties.

Coupling between Land Ecosystems and the Atmospheric Hydrologic Cycle through Biogenic Aerosol Pathways

AUTHOR AFFILIATIONS: BARTH, SUN, WIEDINMYER, KARL, KIM, LEVIS, MAHOWALD, MOORE, NANDI, NEMITZ, POTOSNAK, SMITH, AND STROUD—National Center for Atmospheric Research, Boulder, Colorado; MCFADDEN—University of Minnesota, Saint Paul, Minnesota; CHUANG—University of California, Santa Cruz, Santa Cruz, California; COLLINS—Texas A&M University, College Station, Texas; GRIFFIN—University of New Hampshire, Durham, New Hampshire; HANNIGAN—University of Colorado, Boulder, Colorado; LASHER-TRAPP—Purdue University, West Lafayette, Indiana; LITVAK—University of Texas, Austin, Texas; NENES—Georgia Institute of Technology, Atlanta, Georgia; RAYMOND—Bucknell University, Lewisburg, Pennsylvania; STILL—University of California, Santa Barbara, Santa Barbara, California CORRESPONDING AUTHOR: Dr. Mary Barth, NCAR/MMM, P.O. Box 3000, Boulder, CO 80307 E-mail: barthm@ucar.edu

An Investigation of the Influence of Droplet Number Concentration and Giant Aerosol Particles upon Supercooled Large Drop Formation in Wintertime Stratiform Clouds

Supercooled large drops (SLD) can be a significant hazard for aviation. Past studies have shown that warm-rain processes are prevalent, or even dominant, in stratiform clouds containing SLD, but the primary factors that control SLD production are still not well understood. Giant aerosol particles have been shown to accelerate the formation of the first drizzle drops in some clouds and thus are a viable source of SLD, but observational support for testing their effectiveness in supercooled stratiform clouds has been lacking. In this study, new observations collected during six research flights from the Alliance Icing Research Study II (AIRS II) are analyzed to assess the factors that may be relevant to SLD formation, with a particular emphasis on the importance of giant aerosol particles. An initial comparison of observed giant aerosol particle number concentrations with the observed SLD suggests that they were present in sufficient numbers to be the source of the SLD. However, microphysical calculations within an adiabatic parcel model, initialized with the observed aerosol distributions and cloud properties, suggest that the giant aerosol particles were only a limited source of SLD. More SLD was produced in the modeled clouds with low droplet concentrations, simply by an efficient warm-rain process acting at temperatures below 0°C. For cases in which the warm-rain process is limited by a higher droplet concentration and small cloud depth/ liquid water content, the giant aerosol particles were then the only source of SLD. The modeling results are consistent with the observed trends in SLD across the six AIRS II cases.

The Convective Precipitation Experiment (COPE): Investigating the Origins of Heavy Precipitation in the Southwestern United Kingdom

AbstractThe Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several d...

A New Three-Dimensional Visualization System for Combining Aircraft and Radar Data and Its Application to RICO Observations

Abstract The analysis of diverse datasets from meteorological field campaigns often involves the use of separate 1D or combined 2D plots from various applications, making the determination of spatial and temporal relationships and correlations among these data, and the overall synthesis of information, extremely challenging. Presented here is a new 3D visualization tool, the Aircraft and Radar Data Collocation and Analysis in 3D (ARCA3D), that can combine data collected from different sources and at different scales, utilizing advanced visualization and user interface techniques, which allows for easier comparison and synthesis of such disparate data. The 3D tool is demonstrated with aircraft-based microphysical probe data and ground-based dual-polarization radar data all collected during the Rain in Cumulus over the Ocean (RICO) field campaign. The 3D volumes of radar data can be interactively selected and quantitatively probed, while aircraft-measured variables can be viewed along the aircraft track plo...

An Atmospheric Visual Analysis and Exploration System

Meteorological research involves the analysis of multi-field, multi-scale, and multi-source data sets. Unfortunately, traditional atmospheric visualization systems only provide tools to view a limited number of variables and small segments of the data. These tools are often restricted to 2D contour or vector plots or 3D isosurfaces. The meteorologist must mentally synthesize the data from multiple plots to glean the information needed to produce a coherent picture of the weather phenomenon of interest. In order to provide better tools to meteorologists and reduce system limitations, we have designed an integrated atmospheric visual analysis and exploration system for interactive analysis of weather data sets. Our system allows for the integrated visualization of 1D, 2D, and 3D atmospheric data sets in common meteorological grid structures and utilizes a variety of rendering techniques. These tools provide meteorologists with new abilities to analyze their data and answer questions on regions of interest, ranging from physics-based atmospheric rendering to illustrative rendering containing particles and glyphs. In this paper, we discuss the use and performance of our visual analysis for two important meteorological applications. The first application is warm rain formation in small cumulus clouds. In this, our three-dimensional, interactive visualization of modeled drop trajectories within spatially correlated fields from a cloud simulation has provided researchers with new insight. Our second application is improving and validating severe storm models, specifically the weather research and forecasting (WRF) model. This is done through correlative visualization of WRF model and experimental Doppler storm data

On Measuring the Degree of Irregularity in an Observing Network

Meteorological observing networks are nearly always irregularly distributed in space. This irregularity generally has an adverse impact on objective analysis and must be accounted for when designing an analysis scheme. Unfortunately, there has been no completely satisfactory measure of the degree of irregularity, which is of particular significance when designing artificial sampling networks for empirical studies of the impact of this spatial distribution irregularity. The authors propose a measure of the irregularity of sampling point distributions based on the gradient of the sums of the weights used in an objective analysis. Two alternatives that have been proposed, the fractal dimension and a ‘‘nonuniformity ratio,’’ are examined as candidate measures, but the new method presented here is considered superior to these because it can be used to create a spatial ‘‘map’’ that illustrates the spatial structure of the irregularities in a sampling network, as well as to assign a single number to the network as a whole. Testing the new measure with uniform and artificial networks shows that this parameter seems to exhibit the desired properties. When tested with the United States surface and upper-air networks, the parameter provides quantitative information showing that the surface network is much more irregular than the rawinsonde network. It is shown that artificial networks can be created that duplicate the characteristics of the surface and rawinsonde networks; in the case of the surface network, however, a declustered version of the observation site distribution is required.