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Dongqi Lin, Ben Pickering, and Ryan R. Neely III

Abstract

In radar observations of hydrometeors, the 0°C isotherm in the atmosphere (i.e., the freezing level) usually appears as a region of enhanced reflectivity. This region is known as the bright band (BB). In this study, observations over 12 months from a vertically pointing 35-GHz radar and a collocated disdrometer at the Natural Environment Research Council (NERC) Facility for Atmospheric and Radio Research (NFARR) are used to identify and compare microphysical differences between BB and non-brightband (NBB) periods. From these observations, the relationship between radar reflectivity Z and rainfall intensity R is found to be Z = 772R 0.57 for BB periods and Z = 108R 0.99 for NBB periods. Additionally, the brightband strength (BBS) was calculated using a novel method derived from the Michelson contrast equation in an attempt to explain the observed variability in BB precipitation. A series of ZR relationships are computed with respect to BBS. The coefficients increase with increasing BBS from 227 to 926, while the exponents decrease with increasing BBS from 0.85 to 0.38. The results also indicate that NBB periods identified in the presence of a 0°C isotherm in other studies may be misclassified due to their inability to identify weak brightband periods. As such, it is hypothesized that NBB periods are solely due to warm rain processes.

Open access
Ben S. Pickering, Ryan R. Neely III, Judith Jeffery, David Dufton, and Maryna Lukach

Abstract

Observations of the precipitation rate/depth, drop-size distribution, drop-velocity distribution and precipitation type are compared from six in-situ precipitation sensor designs over 12 months to assess their performance and provide a benchmark for future design and deployment. The designs considered are: tipping-bucket (TBR), drop-counting (RAL), acoustic (JWD), optical (LPM), single-angle visiometer with capacitor (PWD21) and dual-angle visiometer (PWS100). Precipitation rates are compared for multiple time resolutions over the study period, while drop size and velocity distributions are compared with cases at stable precipitation rates. To examine precipitation type a new index and a logic algorithm to amalgamate consecutive precipitation type observations consistently is introduced and applied. Overall the choice of instrument for deployment depends on the usage. For fast response (less than 15 minutes), the PWD21 and TBR should not be used. As precipitation rate or the duration of a sample increases, the correlation of the TBR with the majority of other instruments increases. However, the PWD21 consistently underestimates precipitation. The RAL,PWS100 andJWDare within ± 15% for precipitation depth over 12 months. All instruments are inconsistent in their ability to observe drop size and velocity distributions for differing precipitation rates. There is low agreement between the instruments for precipitation type estimation. The PWD21 and PWS100 rarely report some precipitation types, but the LPM reports more broadly. Meteorological stations should use several instrument designs for redundancy and to more accurately capture precipitation characteristics.

Open access
Ryan R. Neely III, Louise Parry, David Dufton, Lindsay Bennett, and Chris Collier

Abstract

The Radar Applications in Northern Scotland (RAiNS) experiment took place from February to August 2016 near Inverness, Scotland. The campaign was motivated by the need to provide enhanced weather radar observations for hydrological applications for the Inverness region. Here we describe the campaign in detail and observations over the summer period of the campaign that show the improvements that high-resolution polarimetric radar observations may have on quantitative precipitation estimates in this region compared to concurrently generated operational radar quantitative precipitation estimates (QPEs). We further provide suggestions of methods for generating QPE using dual-polarization X-band radars in similar regions.

Open access
Benjamin J. Murray, Christoph G. Salzmann, Andrew J. Heymsfield, Steven Dobbie, Ryan R. Neely III, and Christopher J. Cox

Abstract

We are all familiar with the hexagonal shape of snow and ice crystals, and it is well established that their sixfold symmetry is derived from the arrangement of water molecules in a hexagonal crystal structure. However, atmospheric ice crystals with only threefold rotational symmetry are often observed, which is inconsistent with the hexagonal crystal structure of ordinary ice. These crystals are found in a wide range of different cloud types ranging from upper-tropospheric cirrus to contrails and diamond dust and they form at temperatures ranging from about −84° to −5°C. Recent experimental studies of ice crystal structures have shown that ice under a wide range of atmospheric conditions does not always conform to the standard hexagonal crystal structure. Instead, sequences of the hexagonal structure can be interlaced with cubic sequences to create stacking-disordered ice. This degrades the symmetry of the crystal structure so that, instead of having a hexagonal structure, they have a trigonal structure with a corresponding threefold symmetry. Hence, this implies that atmospheric ice crystals with threefold symmetry are made of stacking-disordered ice. We conclude that the presence of trigonal crystals in the atmosphere is consistent with rare Parry arc halos and also show that they have distinct radiative properties compared with hexagonal ice.

Open access
Ryan R. Neely III, Matthew Hayman, Robert Stillwell, Jeffrey P. Thayer, R. Michael Hardesty, Michael O'Neill, Matthew D. Shupe, and Catherine Alvarez

Abstract

Accurate measurements of cloud properties are necessary to document the full range of cloud conditions and characteristics. The Cloud, Aerosol Polarization and Backscatter Lidar (CAPABL) has been developed to address this need by measuring depolarization, particle orientation, and the backscatter of clouds and aerosols. The lidar is located at Summit, Greenland (72.6°N, 38.5°W; 3200 m MSL), as part of the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit Project and NOAA's Earth System Research Laboratory's Global Monitoring Division's lidar network. Here, the instrument is described with particular emphasis placed upon the implementation of new polarization methods developed to measure particle orientation and improve the overall accuracy of lidar depolarization measurements. Initial results from the lidar are also shown to demonstrate the ability of the lidar to observe cloud properties.

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Matthew D. Shupe, David D. Turner, Von P. Walden, Ralf Bennartz, Maria P. Cadeddu, Benjamin B. Castellani, Christopher J. Cox, David R. Hudak, Mark S. Kulie, Nathaniel B. Miller, Ryan R. Neely III, William D. Neff, and Penny M. Rowe

Cloud and atmospheric properties strongly influence the mass and energy budgets of the Greenland Ice Sheet (GIS). To address critical gaps in the understanding of these systems, a new suite of cloud- and atmosphere-observing instruments has been installed on the central GIS as part of the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project. During the first 20 months in operation, this complementary suite of active and passive ground-based sensors and radiosondes has provided new and unique perspectives on important cloud–atmosphere properties.

High atop the GIS, the atmosphere is extremely dry and cold with strong near-surface static stability predominating throughout the year, particularly in winter. This low-level thermodynamic structure, coupled with frequent moisture inversions, conveys the importance of advection for local cloud and precipitation formation. Cloud liquid water is observed in all months of the year, even the particularly cold and dry winter, while annual cycle observations indicate that the largest atmospheric moisture amounts, cloud water contents, and snowfall occur in summer and under southwesterly flow. Many of the basic structural properties of clouds observed at Summit, Greenland, particularly for low-level stratiform clouds, are similar to their counterparts in other Arctic regions.

The ICECAPS observations and accompanying analyses will be used to improve the understanding of key cloud–atmosphere processes and the manner in which they interact with the GIS. Furthermore, they will facilitate model evaluation and development in this data-sparse but environmentally unique region.

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