The U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Program is deploying sensitive, millimeter-wave cloud radars at its Cloud and Radiation Test Bed (CART) sites in Oklahoma, Alaska, and the tropical western Pacific Ocean. The radars complement optical devices, including a Belfort or Vaisala laser ceilometer and a micropulse lidar, in providing a comprehensive source of information on the vertical distribution of hydrometeors overhead at the sites. An algorithm is described that combines data from these active remote sensors to produce an objective determination of hydrometeor height distributions and estimates of their radar reflectivities, vertical velocities, and Doppler spectral widths, which are optimized for accuracy. These data provide fundamental information for retrieving cloud microphysical properties and assessing the radiative effects of clouds on climate. The algorithm is applied to nine months of data from the CART site in Oklahoma for initial evaluation. Much of the algorithm's calculations deal with merging and optimizing data from the radar's four sequential operating modes, which have differing advantages and limitations, including problems resulting from range sidelobes, range aliasing, and coherent averaging. Two of the modes use advanced phase-coded pulse compression techniques to yield approximately 10 and 15 dB more sensitivity than is available from the two conventional pulse modes. Comparison of cloud-base heights from the Belfort ceilometer and the micropulse lidar confirms small biases found in earlier studies, but recent information about the ceilometer brings the agreement to within 20-30 m. Merged data of the radar's modes were found to miss approximately 5.9% of the clouds detected by the laser systems. Using data from only the radar's two less-sensitive conventional pulse modes would increase the missed detections to 22%-34%. A significant remaining problem is that the radar's lower-altitude data are often contaminated with echoes from nonhydrometeor targets, such as insects.

A new millimeter-wave cloud radar (MMCR) has been designed to provide detailed, long-term observations of nonprecipitating and weakly precipitating clouds at Cloud and Radiation Testbed (CART) sites of the Department of Energy's Atmospheric Radiation Measurement (ARM) program. Scientific requirements included excellent sensitivity and vertical resolution to detect weak and thin multiple layers of ice and liquid water clouds over the sites and longterm, unattended operations in remote locales. In response to these requirements, the innovative radar design features a vertically pointing, single-polarization, Doppler system operating at 35 GHz (K a band). It uses a low-peak-power transmitter for long-term reliability and high-gain antenna and pulse-compressed waveforms to maximize sensitivity and resolution. The radar uses the same kind of signal processor as that used in commercial wind profilers. The first MMCR began operations at the CART in northern Oklahoma in late 1996 and has operated continuously there for thousands of hours. It routinely provides remarkably detailed images of the ever-changing cloud structure and kinematics over this densely instrumented site. Examples of the data are presented. The radar measurements will greatly improve quantitative documentation of cloud conditions over the CART sites and will bolster ARM research to understand how clouds impact climate through their effects on radiative transfer. Millimeter-wave radars such as the MMCR also have potential applications in the fields of aviation weather, weather modification, and basic cloud physics research.

The maritime mountain ranges of western North America span a wide range of elevations and are extremely sensitive to flooding from warm winter storms, primarily because rain falls at higher elevations and over a much greater fraction of a basin’s contributing area than during a typical storm. Accurate predictions of this rain–snow line are crucial to hydrologic forecasting. This study examines how remotely sensed atmospheric snow levels measured upstream of a mountain range (specifically, the bright band measured above radar wind profilers) can be used to accurately portray the altitude of the surface transition from snow to rain along the mountain’s windward slopes, focusing on measurements in the Sierra Nevada, California, from 2001 to 2005. Snow accumulation varies with respect to surface temperature, diurnal cycles in solar radiation, and fluctuations in the free-tropospheric melting level. At 1.5°C, 50% of precipitation events fall as rain and 50% as snow, and on average, 50% of measured precipitation contributes to increases in snow water equivalent (SWE). Between 2.5° and 3°C, snow is equally likely to melt or accumulate, with most cases resulting in no change to SWE. Qualitatively, brightband heights (BBHs) detected by 915-MHz profiling radars up to 300 km away from the American River study basin agree well with surface melting patterns. Quantitatively, this agreement can be improved by adjusting the melting elevation based on the spatial location of the profiler relative to the basin: BBHs decrease with increasing latitude and decreasing distance to the windward slope of the Sierra Nevada. Because of diurnal heating and cooling by radiation at the mountain surface, BBHs should also be adjusted to higher surface elevations near midday and lower elevations near midnight.

Recent studies using vertically pointing S-band profiling radars showed that coastal winter storms in California and Oregon frequently do not display a melting-layer radar bright band and inferred that these nonbrightband (NBB) periods are characterized by raindrop size spectra that differ markedly from those of brightband (BB) periods. Two coastal sites in northern California were revisited in the winter of 2003/04 in this study, which extends the earlier work by augmenting the profiling radar observations with collocated raindrop disdrometers to measure drop size distributions (DSD) at the surface. The disdrometer observations are analyzed for more than 320 h of nonconvective rainfall. The new measurements confirm the earlier inferences that NBB rainfall periods are characterized by greater concentrations of small drops and smaller concentrations of large drops than BB periods. Compared with their BB counterparts, NBB periods had mean values that were 40% smaller for mean-volume diameter, 32% smaller for rain intensity, 87% larger for total drop concentration, and 81% larger (steeper) for slope of the exponential DSDs. The differences are statistically significant. Liquid water contents differ very little, however, for the two rain types. Disdrometer-based relations between radar reflectivity (Z ) and rainfall intensity (R) at the site in the Coast Range Mountains were Z ϭ 168R 1.58 for BB periods and Z ϭ 44R 1.91 for NBB. The much lower coefficient, which is characteristic of NBB rainfall, is poorly represented by the Z-R equations most commonly applied to data from the operational network of Weather Surveillance Radar-1988 Doppler (WSR-88D) units, which underestimate rain accumulations by a factor of 2 or more when applied to nonconvective NBB situations. Based on the observed DSDs, it is also concluded that polarimetric scanning radars may have some limited ability to distinguish between regions of BB and NBB rainfall using differential reflectivity. However, differential-phase estimations of rain intensity are not useful for NBB rain, because the drops are too small and nearly spherical. On average, the profiler-measured echo tops were 3.2 km lower in NBB periods than during BB periods, and they extended only about 1 km above the 0°C altitude. The findings are consistent with the concept that precipitation processes during BB periods are dominated by ice processes in deep cloud layers associated with synoptic-scale forcing, whereas the more restrained growth of hydrometeors in NBB periods is primarily the result of orographically forced condensation and coalescence processes in much shallower clouds.