During the second week of September 2013, a seasonally uncharacteristic weather pattern stalled over the Rocky Mountain Front Range region of northern Colorado bringing with it copious amounts of moisture from the Gulf of Mexico, Caribbean Sea, and the tropical eastern Pacific Ocean. This feed of moisture was funneled toward the east-facing mountain slopes through a series of mesoscale circulation features, resulting in several days of unusually widespread heavy rainfall over steep mountainous terrain. Catastrophic flooding ensued within several Front Range river systems that washed away highways, destroyed towns, isolated communities, necessitated days of airborne evacuations, and resulted in eight fatalities. The impacts from heavy rainfall and flooding were felt over a broad region of northern Colorado leading to 18 counties being designated as federal disaster areas and resulting in damages exceeding $2 billion (U.S. dollars). This study explores the meteorological and hydrological ingredients that led to this extreme event. After providing a basic timeline of events, synoptic and mesoscale circulation features of the event are discussed. Particular focus is placed on documenting how circulation features, embedded within the larger synoptic flow, served to funnel moist inflow into the mountain front driving several days of sustained orographic precipitation. Operational and research networks of polarimetric radar and surface instrumentation were used to evaluate the cloud structures and dominant hydrometeor characteristics. The performance of several quantitative precipitation estimates, quantitative precipitation forecasts, and hydrological forecast products are also analyzed with the intention of identifying what monitoring and prediction tools worked and where further improvements are needed.

Two-dimensional video disdrometer (2DVD) data were analyzed from two equatorial Indian (Gan) and west Pacific Ocean (Manus) islands where precipitation is primarily organized by the intertropical convergence zone and the Madden–Julian oscillation (MJO). The 18 (3.5) months of 2DVD data from Manus (Gan) Island show that 1) the two sites have similar drop size distribution (DSD) spectra of liquid water content, median diameter, rain rate R, radar reflectivity z, normalized gamma number concentration Nw, and other integral rain parameters; 2) there is a robust Nw-based separation between convective (C) and stratiform (S) DSDs at both sites that produces consistent separation in other parameter spaces. The 2DVD data indicate an equatorial, maritime average C/S rainfall accumulation fraction (frequency) of 81/19 (41/59) at these locations. It is hypothesized that convective fraction and frequency estimates are slightly higher than previous radar-based studies, because the ubiquitous weak, shallow convection (<10 mm h−1) characteristic of the tropical warm pool is properly resolved by this high-resolution DSD dataset and identification method. This type of convection accounted for about 30% of all rain events and 15% of total rain volume. These rain statistics were reproduced when newly derived C/S R(z) equations were applied to 2DVD-simulated reflectivity. However, the benefits of using separate C/S R(z) equations are only realizable when C/S partitioning properly classifies each rain type. A single R(z) relationship fit to all 2DVD data yielded accurate total rainfall amounts but overestimated (underestimated) the stratiform (convective) rain fraction by ±10% and overestimated (underestimated) stratiform (convective) rain accumulation by +50% (−15%).

Understanding drop size distribution (DSD) variability has important implications for remote sensing and numerical modeling applications. Twelve disdrometer datasets across three latitude bands are analyzed in this study, spanning a broad range of precipitation regimes: light rain, orographic, deep convective, organized midlatitude, and tropical oceanic. Principal component analysis (PCA) is used to reveal comprehensive modes of global DSD spatial and temporal variability. Although the locations contain different distributions of individual DSD parameters, all locations are found to have the same modes of variability. Based on PCA, six groups of points with unique DSD characteristics emerge. The physical processes that underpin these groups are revealed through supporting radar observations. Group 1 (group 2) is characterized by high (low) liquid water content (LWC), broad (narrow) distribution widths, and large (small) median drop diameters D0. Radar analysis identifies group 1 (group 2) as convective (stratiform) rainfall. Group 3 is characterized by weak, shallow radar echoes and large concentrations of small drops, indicative of warm rain showers. Group 4 identifies heavy stratiform precipitation. The low latitudes exhibit distinct bimodal distributions of the normalized intercept parameter N w, LWC, and D0 and are found to have a clustering of points (group 5) with high rain rates, large N w, and moderate D0, a signature of robust warm rain processes. A distinct group associated with ice-based convection (group 6) emerges in the midlatitudes. Although all locations exhibit the same covariance of parameters associated with these groups, it is likely that the physical processes responsible for shaping the DSDs vary as a function of location.

Although much work has been done at S band to automatically identify hydrometeors by using polarimetric radar, several challenges are presented when adapting such algorithms to X band. At X band, attenuation and non-Rayleigh scattering can pose significant problems. This study seeks to develop a hydrometeor identification (HID) algorithm for X band based on theoretical simulations using the T-matrix scattering model of seven different hydrometeor types: rain, drizzle, aggregates, pristine ice crystals, low-density graupel, highdensity graupel, and vertical ice. Hail and mixed-phase hydrometeors are excluded for the purposes of this study. Non-Rayleigh scattering effects are explored by comparison with S-band simulations. Variable ranges based on the theoretical simulations are used to create one-dimensional fuzzy-logic membership beta functions that form the basis of the new X-band HID. The theory-based X-band HID is applied to a case from the Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project 1 (IP1) network of X-band radars, and comparisons are made with similar S-band hydrometeor identification algorithms applied to data from the S-band polarimetric Next Generation Weather Radar (NEXRAD) prototype radar, KOUN. The Xband HID shows promise for illustrating bulk hydrometeor types and qualitatively agrees with analysis from KOUN. A simple reflectivity-and temperature-only HID is also applied to both KOUN and CASA IP1 data to reveal benefits of the polarimetric-based HID algorithms, especially in the classification of ice hydrometeors and oriented ice crystals.

A new 10-category, polarimetric-based hydrometeor identification algorithm (HID) for C band is developed from theoretical scattering simulations including wet snow, hail, and big drops/melting hail. The HID is applied to data from seven wet seasons in Darwin, Australia, using the polarimetric C-band (C-POL) radar, to investigate microphysical differences between monsoon and break periods. Scattering simulations reveal significant Mie effects with large hail (diameter . 1.5 cm), with reduced reflectivity and enhanced differential reflectivity Z dr and specific differential phase K dp relative to those associated with S band. Wet snow is found to be associated with greatly depreciated correlation coefficient r hv and moderate values of Z dr . It is noted that large oblate liquid drops can produce the same electromagnetic signatures at C band as melting hail falling quasi stably, resulting in some ambiguity in the HID retrievals. Application of the new HID to seven seasons of C-POL data reveals that hail and big drops/melting hail occur much more frequently during break periods than during monsoon periods. Break periods have a high frequency of vertically aligned ice above 12 km, suggesting the presence of strong electric fields. Reflectivity and mean drop diameter D 0 statistics demonstrate that convective areas in both monsoon and break periods may have robust coalescence or melting precipitation ice processes, leading to enhanced reflectivity and broader distributions of D 0 . Conversely, for stratiform regions in both regimes, mean reflectivity decreases below the melting level, indicative of evaporative processes. Break periods also have larger ice water path fractions, indicating substantial mixedphase precipitation generation as compared with monsoonal periods. In monsoon periods, a larger percentage of precipitation is produced through warm-rain processes.