Cloudnet

Illingworth, A. J.; Hogan, Robin J.; O’Connor, Ewan; Bouniol, Dominique; Brooks, M. E.; Delanoë, Julien; Donovan, D. P.; Eastment, J.D.; Gaussiat, Nicolas; Goddard, J.W.F.; Haeffelin, Martial; Baltink, Henk Klein; Krasnov, Oleg A.; Pelon, Jacques; Piriou, Jean‐Marcel; Protat, Alain; Russchenberg, H.W.J.; Seifert, Axel; Tompkins, Adrian M.; Zadelhoff, Gerd-Jan van; Vinit, F.; Willén, Ulrika; Wilson, Damian R.; Wrench, C. L.

doi:10.1175/bams-88-6-883

Cited by 540 publications

(289 citation statements)

References 41 publications

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“…This is revealed clearly through analysis of the Doppler spectrum. Figure 10 shows a pair of Doppler spectra sampled simultaneously in a deep ice cloud by the 35 and 94 GHz radars at the Chilbolton Observatory in the UK (see Illingworth et al, 2007, for details of the radars used). The integration time was 1 s for both radars.…”

Section: Sizing: Dual-wavelength Ratio Methodsmentioning

confidence: 99%

“…within the CloudNet and the US ARM (Atmospheric Radiation Measurement) Program, Illingworth et al, 2007;Ackerman and Stokes, 2003;Mather and Voyles, 2013) and from a variety of ship-based and airborne platforms (Kollias et al, 2007). In space, the CloudSat 94 GHz cloud profiling radar has been operating since May 2006 (Stephens et al, 2008).…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

“…During the past two decades millimetre-wavelength cloud radars have emerged as central pillars in evaluating cloud representation in GCM and NWP models (Illingworth et al, 2007). Millimetre radars are particularly attractive and effective because of their inherent compactness and portability, their high sensitivity and minimal susceptibility to Bragg scattering and ground clutter (Kollias et al, 2007).…”

Section: Radar Scattering Properties At Millimetre Wavelengthsmentioning

confidence: 99%

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G band atmospheric radars: new frontiers in cloud physics

et al. 2014

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Abstract. Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals.The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

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Section: Sizing: Dual-wavelength Ratio Methodsmentioning

confidence: 99%

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Section: Radar Scattering Properties At Millimetre Wavelengthsmentioning

confidence: 99%

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G band atmospheric radars: new frontiers in cloud physics

et al. 2014

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“…However, there is a number of approaches available to generate derived products from the data that are of immediate use both for meteorological analysis and model evaluation. The approach described herein is in some way similar to the CLOUDNET approach (Illingworth et al, 2007), but extended to three dimensional data. The most straightforward extension of the cloud profile analysis might be to construct a three-dimensional cloud mask based on gridded radar reflectivity data.…”

Section: A Statistical Coverage Product (Scp)mentioning

confidence: 99%

“…For example, as part of the CLOUDNET project, Illingworth et al (2007) use a statistical approach, which compares profiles from cloud observatories and numerical models to examine cloud cover as a function of time and height after suitable averaging over time has been undertaken. A more sophisticated approach, to examine data from model columns and profile observations, is to compare probability distributions.…”

Section: Introductionmentioning

confidence: 99%

A method for using weather radar data to test cloud resolving models

May

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2009

Meteorological Applications

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A simple method for extracting useful metrics to characterize cloud fields from volumetric radar data is described along with the use of these metrics to evaluate the performance of cloud resolving models. This method involves the calculation of a 'Statistical Coverage Product', where the fraction of a grid of radar data covered by various reflectivity thresholds and microphysical classifications is calculated, along with profiles of maximum reflectivity, areas of convective and stratiform rain, and the amounts of rainfall in these categories. The application of this method is illustrated, whereby radar observation and a cloud resolving model simulation are compared for a tropical island thunderstorm near Darwin, Australia.

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On using the relationship between Doppler velocity and radar reflectivity to identify microphysical processes in midlatitudinal ice clouds

2013

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[1] Ground-based 35 GHz profiling Doppler cloud radar observations of ice clouds were used to derive the power law relation between Doppler velocity V d and radar reflectivity Z (V d = aZ b ). By removing the vertical air motion from V d , the power law can be rewritten as V t = aZ b with V t being the reflectivity-weighted particle terminal fall velocity. Profiles of this relation are variable with height. An attempt was made to relate this variability to the dominant microphysical processes in different layers of the cloud. Based on that, the possibility of using profiles of the parameters a and b to distinguish different microphysical regimes was explored. The methodology was applied to long-term measurements (January 1997 to December 2010) at the Atmospheric Radiation Measurement site in the Southern Great Plains. Principal component analysis was used to determine the modes of the profiles that explain most of the observed variance in the observations. Profile-averaged means and standard deviations of parameters a and b amounted to 0.65 ± 0.42 and 0.03 ± 0.19, respectively. Furthermore, three commonly used microphysical relations related to bulk quantities were used to determine values of a and b. These results were found to compare reasonably well with the values obtained from the radar observations. Finally, microphysical considerations showed that radar-derived values of parameter b can be explained in terms of particle size distribution moment changes.Citation: Kalesse, H., P. Kollias, and W. Szyrmer (2013), On using the relationship between Doppler velocity and radar reflectivity to identify microphysical processes in midlatitudinal ice clouds,

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Cloudnet

Abstract: Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave radiometer data are systematically compared to models to quantify and improve their performance.

Cited by 540 publications

References 41 publications

G band atmospheric radars: new frontiers in cloud physics

G band atmospheric radars: new frontiers in cloud physics

A method for using weather radar data to test cloud resolving models

On using the relationship between Doppler velocity and radar reflectivity to identify microphysical processes in midlatitudinal ice clouds

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