Arctic mixed-phase cloud macro- and microphysical properties are derived from a year of radar, lidar, microwave radiometer, and radiosonde observations made as part of the Surface Heat Budget of the Arctic Ocean (SHEBA) Program in the Beaufort Sea in 1997–98. Mixed-phase clouds occurred 41% of the time and were most frequent in the spring and fall transition seasons. These clouds often consisted of a shallow, cloud-top liquid layer from which ice particles formed and fell, although deep, multilayered mixed-phase cloud scenes were also observed. On average, individual cloud layers persisted for 12 h, while some mixed-phase cloud systems lasted for many days. Ninety percent of the observed mixed-phase clouds were 0.5–3 km thick, had a cloud base of 0–2 km, and resided at a temperature of −25° to −5°C. Under the assumption that the relatively large ice crystals dominate the radar signal, ice properties were retrieved from these clouds using radar reflectivity measurements. The annual average ice particle mean diameter, ice water content, and ice water path were 93 μm, 0.027 g m−3, and 42 g m−2, respectively. These values are all larger than those found in single-phase ice clouds at SHEBA. Vertically resolved cloud liquid properties were not retrieved; however, the annual average, microwave radiometer–derived liquid water path (LWP) in mixed-phase clouds was 61 g m−2. This value is larger than the average LWP observed in single-phase liquid clouds because the liquid water layers in the mixed-phase clouds tended to be thicker than those in all-liquid clouds. Although mixed-phase clouds were observed down to temperatures of about −40°C, the liquid fraction (ratio of LWP to total condensed water path) increased on average from zero at −24°C to one at −14°C. The observations show a range of ∼25°C at any given liquid fraction and a phase transition relationship that may change moderately with season.

Many of the clouds important to the Earth's energy balance, from the Tropics to the Arctic, contain small amounts of liquid water. Longwave and shortwave radiative fluxes are very sensitive to small perturbations of the cloud liquid water path (LWP), when the LWP is small (i.e., < 100 g m−2; clouds with LWP less than this threshold will be referred to as “thin”). Thus, the radiative properties of these thin liquid water clouds must be well understood to capture them correctly in climate models. We review the importance of these thin clouds to the Earth's energy balance, and explain the difficulties in observing them. In particular, because these clouds are thin, potentially mixed phase, and often broken (i.e., have large 3D variability), it is challenging to retrieve their microphysical properties accurately. We describe a retrieval algorithm intercomparison that was conducted to evaluate the issues involved. The intercomparison used data collected at the Atmospheric Radiation Measurement (ARM) Southern G... Many of the clouds important to the Earth's energy balance, from the Tropics to the Arctic, contain small amounts of liquid water. Longwave and shortwave radiative fluxes are very sensitive to small perturbations of the cloud liquid water path (LWP), when the LWP is small (i.e., < 100 g m−2; clouds with LWP less than this threshold will be referred to as “thin”). Thus, the radiative properties of these thin liquid water clouds must be well understood to capture them correctly in climate models. We review the importance of these thin clouds to the Earth's energy balance, and explain the difficulties in observing them. In particular, because these clouds are thin, potentially mixed phase, and often broken (i.e., have large 3D variability), it is challenging to retrieve their microphysical properties accurately. We describe a retrieval algorithm intercomparison that was conducted to evaluate the issues involved. The intercomparison used data collected at the Atmospheric Radiation Measurement (ARM) Southern G...

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.

Ground-based vertically pointing and airborne/spaceborne nadir-pointing millimeter-wavelength radars are being increasingly used worldwide. Though such radars are primarily designed for cloud remote sensing, they can also be used for precipitation measurements including snowfall estimates. In this study, modeling of snowfall radar properties is performed for the common frequencies of millimeter-wavelength radars such as those used by the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (Ka and W bands) and the CloudSat mission (W band). Realistic snowflake models including aggregates and single dendrite crystals were used. The model input included appropriate mass–size and terminal fall velocity–size relations and snowflake orientation and shape assumptions. It was shown that unlike in the Rayleigh scattering regime, which is often applicable for longer radar wavelengths, the spherical model does not generally satisfactorily describe scattering of larger snowflakes at millimeter wavelengths. This is especially true when, due to aerodynamic forcing, these snowflakes are oriented primarily with their major dimensions in the horizontal plane and the zenith/nadir radar pointing geometry is used. As a result of modeling using the experimental snowflake size distributions, radar reflectivity–liquid equivalent snowfall rates (Ze–S) relations are suggested for “dry” snowfalls that consist of mostly unrimed snowflakes containing negligible amounts of liquid water. Owing to uncertainties in the model assumptions, these relations, which are derived for the common Ka- and W-band radar frequencies, have significant variability in their coefficients that can exceed a factor of 2 or so. Modeling snowfall attenuation suggests that the attenuation effects in “dry” snowfall can be neglected at the Ka band for most practical cases, while at the W band attenuation may need to be accounted for in heavier snowfalls observed at longer ranges.

A combined polarimetric estimator for rainfall rate (R) retrievals from polarimetric radar measurements at X band is proposed. This estimator uses the horizontal polarization radar reflectivity Ze, differential reflectivity ZDR, and specific differential phase shift KDP, and it intrinsically accounts for changes in how drop oblateness increases with size. Because this estimator uses power measurements (i.e., Ze and ZDR), a procedure for correcting these measurements for effects of partial attenuation and differential attenuation using the differential phase measurement is suggested. An altitude correction for estimates of rainfall rates is also suggested. The proposed combined polarimetric estimator that uses KDP, ZDR, and Ze, an estimator that uses KDP alone for equilibrium drop shapes, and different Ze–R relations were applied to the 15 rain events observed with the NOAA X-band transportable polarimetric radar during the eight-week field campaign at the NASA Wallops Island facility in Virginia.... Abstract A combined polarimetric estimator for rainfall rate (R) retrievals from polarimetric radar measurements at X band is proposed. This estimator uses the horizontal polarization radar reflectivity Ze, differential reflectivity ZDR, and specific differential phase shift KDP, and it intrinsically accounts for changes in how drop oblateness increases with size. Because this estimator uses power measurements (i.e., Ze and ZDR), a procedure for correcting these measurements for effects of partial attenuation and differential attenuation using the differential phase measurement is suggested. An altitude correction for estimates of rainfall rates is also suggested. The proposed combined polarimetric estimator that uses KDP, ZDR, and Ze, an estimator that uses KDP alone for equilibrium drop shapes, and different Ze–R relations were applied to the 15 rain events observed with the NOAA X-band transportable polarimetric radar during the eight-week field campaign at the NASA Wallops Island facility in Virginia....

An operational suite of ground-based, remote sensing retrievals for producing cloud microphysical properties is described, assessed, and applied to 1 yr of observations in the Arctic. All measurements were made in support of the Surface Heat Budget of the Arctic (SHEBA) program and First International Satellite Cloud Climatology Project Regional Experiment (FIRE) Arctic Clouds Experiment (ACE) in 1997–98. Retrieval techniques and cloud-type classifications are based on measurements from a vertically pointing 35-GHz Doppler radar, microwave and infrared radiometers, and radiosondes. The retrieval methods are assessed using aircraft in situ measurements from a limited set of case studies and by intercomparison of multiple retrievals for the same parameters. In all-liquid clouds, retrieved droplet effective radii Re have an uncertainty of up to 32% and liquid water contents (LWC) have an uncertainty of 49%–72%. In all-ice clouds, ice particle mean sizes Dmean can be retrieved with an uncertainty of 26%–46% while retrieved ice water contents (IWC) have an uncertainty of 62%–100%. In general, radar-only, regionally tuned empirical power-law retrievals were best suited among the tested retrieval algorithms for operational cloud monitoring at SHEBA because of their wide applicability, ease of use, and reasonable statistical accuracy. More complex multisensor techniques provided a moderate improvement in accuracy for specific case studies and were useful for deriving location-specific coefficients for the empirical retrievals but were not as frequently applicable as the single sensor methods because of various limitations. During the yearlong SHEBA program, all-liquid clouds were identified 19% of the time and were characterized by an annual average droplet Re of 6.5 μm, LWC of 0.10 g m−3, and liquid water path of 45 g m−2. All-ice clouds were identified 38% of the time with an annual average particle Dmean of 73 μm, IWC of 0.014 g m−3, and ice water path of 30 g m−2.