Three algorithms extract information on precipitation type, structure, and amount from operational radar and rain gauge data. Tests on one month of data from one site show that the algorithms perform accurately and provide products that characterize the essential features of the precipitation climatology. Input to the algorithms are the operationally executed volume scans of a radar and the data from a surrounding rain gauge network. The algorithms separate the radar echoes into convective and stratiform regions, statistically summarize the vertical structure of the radar echoes, and determine precipitation rates and amounts on high spatial resolution. The convective and stratiform regions are separated on the basis of the intensity and sharpness of the peaks of echo intensity. The peaks indicate the centers of the convective region. Precipitation not identified as convective is stratiform. This method avoids the problem of underestimating the stratiform precipitation. The separation criteria are... Abstract Three algorithms extract information on precipitation type, structure, and amount from operational radar and rain gauge data. Tests on one month of data from one site show that the algorithms perform accurately and provide products that characterize the essential features of the precipitation climatology. Input to the algorithms are the operationally executed volume scans of a radar and the data from a surrounding rain gauge network. The algorithms separate the radar echoes into convective and stratiform regions, statistically summarize the vertical structure of the radar echoes, and determine precipitation rates and amounts on high spatial resolution. The convective and stratiform regions are separated on the basis of the intensity and sharpness of the peaks of echo intensity. The peaks indicate the centers of the convective region. Precipitation not identified as convective is stratiform. This method avoids the problem of underestimating the stratiform precipitation. The separation criteria are...

High-resolution radar data collected in Florida during the Convection and Precipitation/Electrification Experiment are used to elucidate the microphysical and kinematic processes occurring during the transition of a multicellular storm from convective to stratiform stages. A statistical technique is employed to examine the evolving properties of the ensemble small-scale variability of radar reflectivity, vertical velocity, and differential reflectivity over the entire storm. Differential radar reflectivity data indicate that the precipitation at upper levels was nearly glaciated early in the storm's lifetime. Dual-Doppler radar data show that throughout the storm's lifetime both updrafts and down-drafts were present at all altitudes and that most of the volume of the radar echo contained vertical velocities incapable of supporting precipitation-size particles. Thus, the ensemble microphysical properties of the storm were increasingly dominated by particles falling in an environment of weak vertic... Abstract High-resolution radar data collected in Florida during the Convection and Precipitation/Electrification Experiment are used to elucidate the microphysical and kinematic processes occurring during the transition of a multicellular storm from convective to stratiform stages. A statistical technique is employed to examine the evolving properties of the ensemble small-scale variability of radar reflectivity, vertical velocity, and differential reflectivity over the entire storm. Differential radar reflectivity data indicate that the precipitation at upper levels was nearly glaciated early in the storm's lifetime. Dual-Doppler radar data show that throughout the storm's lifetime both updrafts and down-drafts were present at all altitudes and that most of the volume of the radar echo contained vertical velocities incapable of supporting precipitation-size particles. Thus, the ensemble microphysical properties of the storm were increasingly dominated by particles falling in an environment of weak vertic...

The VAMOS¹ Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) was an international field program designed to make observations of poorly understood but critical components of the coupled climate system of the southeast Pacific. This region is characterized by strong coastal upwelling, the coolest SSTs in the tropical belt, and is home to the largest subtropical stratocumulus deck on Earth. The field intensive phase of VOCALS-REx took place during October and November 2008 and constitutes a critical part of a broader CLIVAR program (VOCALS) designed to develop and promote scientific activities leading to improved understanding, model simulations, and predictions of the southeastern Pacific (SEP) coupled ocean-atmosphere-land system, on diurnal to interannual timescales. The other major components of VOCALS are a modeling program with a model hierarchy ranging from the local to global scales, and a suite of extended observations from regular research cruises, instrumented moorings, and satellites. The two central themes of VOCALS-REx focus upon (a) links between aerosols, clouds and precipitation and their impacts on marine stratocumulus radiative properties, and (b) physical and chemical couplings between the upper ocean and the lower atmosphere, including the role that mesoscale ocean eddies play. A set of hypotheses designed to be tested with the combined field, monitoring and modeling work in VOCALS is presented here. A further goal of VOCALS-REx is to provide datasets for the evaluation and improvement of large-scale numerical models. VOCALS-REx involved five research aircraft, two ships and two surface sites in northern Chile. We describe the instrument payloads and key mission strategies for these platforms and give a summary of the missions conducted. ¹ Variability of the American Monsoon Systems, an international CLIVAR program.

Ground-based measurements of particle size and fall speed distributions using a Particle Size and Velocity (PARSIVEL) disdrometer are compared among samples obtained in mixed precipitation (rain and wet snow) and rain in the Oregon Cascade Mountains and in dry snow in the Rocky Mountains of Colorado. Coexisting rain and snow particles are distinguished using a classification method based on their size and fall speed properties. The bimodal distribution of the particles’ joint fall speed–size characteristics at air temperatures from 0.5° to 0°C suggests that wet-snow particles quickly make a transition to rain once melting has progressed sufficiently. As air temperatures increase to 1.5°C, the reduction in the number of very large aggregates with a diameter > 10 mm coincides with the appearance of rain particles larger than 6 mm. In this setting, very large raindrops appear to be the result of aggregrates melting with minimal breakup rather than formation by coalescence. In contrast to dry snow and rain, the fall speed for wet snow has a much weaker correlation between increasing size and increasing fall speed. Wet snow has a larger standard deviation of fall speed (120%–230% relative to dry snow) for a given particle size. The average fall speed for observed wet-snow particles with a diameter ≥ 2.4 mm is 2 m s−1 with a standard deviation of 0.8 m s−1. The large standard deviation is likely related to the coexistence of particles of similar physical size with different percentages of melting. These results suggest that different particle sizes are not required for aggregation since wet-snow particles of the same size can have different fall speeds. Given the large standard deviation of fall speeds in wet snow, the collision efficiency for wet snow is likely larger than that of dry snow. For particle sizes between 1 and 10 mm in diameter within mixed precipitation, rain constituted 1% of the particles by volume within the isothermal layer at 0°C and 4% of the particles by volume for the region just below the isothermal layer where air temperatures rise from 0° to 0.5°C. As air temperatures increased above 0.5°C, the relative proportions of rain versus snow particles shift dramatically and raindrops become dominant. The value of 0.5°C for the sharp transition in volume fraction from snow to rain is slightly lower than the range from 1.1° to 1.7°C often used in hydrological models.

Ship‐based radar measurements obtained during the East Pacific Investigation of Climate 2001 stratocumulus (Sc) cruise are used to derive characteristics of the rainfall from drizzling Sc. Reflectivity to rain rate (Z–R) relationships are determined from shipboard raindrop‐size distribution measurements obtained from observations using filter‐paper, and compared to Z–R relationships derived from aircraft probe data from below north‐east Atlantic drizzling Sc and stratus. A model for the evaporation and sedimentation of drizzle is combined with reflectivity profiles from a millimetre‐wavelength cloud radar to derive information on the mean raindrop radius and drizzle drop concentrations at cloud base, and to show how Z–R relationships change with height below the cloud base. The Z–R relationships are used in conjunction with shipborne C‐band radar reflectivity data to estimate areal average precipitation with uncertainties at cloud base and at the surface. In the Sc drizzle Z–R relationship, Z = aR^b (where a and b are constants), the estimated exponent b = 1.1 to 1.4 is lower than commonly observed in deep convective rain (b = 1.5). Analyses indicate that variations in Sc rain rates and reflectivities are influenced both by fluctuations in drizzle drop concentration and in mean radius, but that number concentration contributes more to the modulation of rain rate in Sc. Rain rates derived using the scanning C‐band radar are found to be spatially variable, with much of the accumulation originating from a small fraction of the drizzling area. The observations also suggest that rain rate in marine Sc is strongly dependent on cloud liquid‐water path, and inversely correlated with cloud droplet concentration. Copyright © 2004 Royal Meteorological Society