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  • Author or Editor: David D. Turner x
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Joseph Sedlar, Laura D. Riihimaki, Kathleen Lantz, and David D. Turner

Abstract

Various methods have been developed to characterize cloud type, otherwise referred to as cloud regime. These include manual sky observations, combining radiative and cloud vertical properties observed from satellite, surface-based remote sensing, and digital processing of sky imagers. While each method has inherent advantages and disadvantages, none of these cloud-typing methods actually includes measurements of surface shortwave or longwave radiative fluxes. Here, a method that relies upon detailed, surface-based radiation and cloud measurements and derived data products to train a random-forest machine-learning cloud classification model is introduced. Measurements from five years of data from the ARM Southern Great Plains site were compiled to train and independently evaluate the model classification performance. A cloud-type accuracy of approximately 80% using the random-forest classifier reveals that the model is well suited to predict climatological cloud properties. Furthermore, an analysis of the cloud-type misclassifications is performed. While physical cloud types may be misreported, the shortwave radiative signatures are similar between misclassified cloud types. From this, we assert that the cloud-regime model has the capacity to successfully differentiate clouds with comparable cloud–radiative interactions. Therefore, we conclude that the model can provide useful cloud-property information for fundamental cloud studies, inform renewable energy studies, and be a tool for numerical model evaluation and parameterization improvement, among many other applications.

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Jianhao Zhang, Paquita Zuidema, David D. Turner, and Maria P. Cadeddu

Abstract

The interactions between equatorial convection and humidity as a function of height, at a range of time scales, remain an important research frontier. The ability of surface-based microwave radiometry to contribute to such research is assessed using retrievals of the vertical structure of atmospheric humidity above the equatorial Indian Ocean, developed as part of the Dynamics of Madden–Julian Oscillation field campaign. The optimally estimated humidity retrievals are based on radiances at five frequencies spanning 20–30 GHz and are constrained by radiometer-derived water vapor paths that compare well to radiosonde values except in highly convective conditions. The moisture retrievals possess a robust 2 degrees of freedom, allowing the atmosphere to be treated as two independent layers. A mean bias of 1 g kg−1 contains a vertical structure that is removed in the assessments. The retrieved moisture profiles are able to capture humidity variability within two layer averages at intraseasonal, synoptic, and daily time scales. The retrieved humidity profiles at hourly scales are qualitatively correct under synoptically suppressed conditions but with an exaggerated vertical bimodality. The retrievals do not match radiosonde profiles within most of the day prior to/after convection. This analysis serves to better delineate applications for radiometers. Radiometers can usefully augment more expensive radiosonde networks for longer-term monitoring given careful cross-instrument calibration. At shorter time scales, a synergism with additional instruments can likely increase the realism of the retrievals.

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Sarah M. Borg, Steven M. Cavallo, and David D. Turner

Abstract

Tropopause polar vortices (TPVs) are long-lived, coherent vortices that are based on the dynamic tropopause and characterized by potential vorticity anomalies. TPVs exist primarily in the Arctic, with potential impacts ranging from surface cyclone generation and Rossby wave interactions to dynamic changes in sea ice. Previous analyses have focused on model output indicating the importance of clear-sky and cloud-top radiative cooling in the maintenance and evolution of TPVs, but no studies have focused on local observations to confirm or deny these results. This study uses cloud and atmospheric state observations from Summit Station, Greenland, combined with single-column experiments using the Rapid Radiative Transfer Model to investigate the effects of clear-sky, ice-only, and all-sky radiative cooling on TPV intensification. The ground-based observing system combined with temperature and humidity profiles from the European Centre for Medium-Range Weather Forecasts’s fifth major global reanalysis dataset, which assimilates the twice-daily soundings launched at Summit, provides novel details of local characteristics of TPVs. Longwave radiative contributions to TPV diabatic intensity changes are analyzed with these resources, starting with a case study focusing on observed cloud properties and associated radiative effects, followed by a composite study used to evaluate observed results alongside previously simulated results. Stronger versus weaker vertical gradients in anomalous clear-sky radiative heating rates, contributing to Ertel potential vorticity changes, are associated with strengthening versus weakening TPVs. Results show that clouds are sometimes influential in the intensification of a TPV, and composite results share many similarities to modeling studies in terms of atmospheric state and radiative structure.

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Larry K. Berg, Rob K. Newsom, and David D. Turner

Abstract

One year of coherent Doppler lidar data collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement site in Oklahoma was analyzed to provide profiles of vertical velocity variance, skewness, and kurtosis for cases of cloud-free convective boundary layers. The variance was normalized by the Deardorff convective velocity scale, which was successful when the boundary layer depth was stationary but failed in situations in which the layer was changing rapidly. In this study, the data are sorted according to time of day, season, wind direction, surface shear stress, degree of instability, and wind shear across the boundary layer top. The normalized variance was found to have its peak value near a normalized height of 0.25. The magnitude of the variance changes with season, shear stress, degree of instability, and wind shear across the boundary layer top. The skewness was largest in the top half of the boundary layer (with the exception of wintertime conditions). The skewness was also found to be a function of the season, shear stress, and wind shear across the boundary layer top. Like skewness, the vertical profile of kurtosis followed a consistent pattern, with peak values near the boundary layer top. The normalized altitude of the peak values of kurtosis was found to be higher when there was a large amount of wind shear at the boundary layer top.

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Matthew D. Shupe, David D. Turner, Alexander Zwink, Mandana M. Thieman, Eli J. Mlawer, and Timothy Shippert

Abstract

Cloud phase and microphysical properties control the radiative effects of clouds in the climate system and are therefore crucial to characterize in a variety of conditions and locations. An Arctic-specific, ground-based, multisensor cloud retrieval system is described here and applied to 2 yr of observations from Barrow, Alaska. Over these 2 yr, clouds occurred 75% of the time, with cloud ice and liquid each occurring nearly 60% of the time. Liquid water occurred at least 25% of the time, even in winter, and existed up to heights of 8 km. The vertically integrated mass of liquid was typically larger than that of ice. While it is generally difficult to evaluate the overall uncertainty of a comprehensive cloud retrieval system of this type, radiative flux closure analyses were performed in which flux calculations using the derived microphysical properties were compared with measurements at the surface and the top of the atmosphere. Radiative closure biases were generally smaller for cloudy scenes relative to clear skies, while the variability of flux closure results was only moderately larger than under clear skies. The best closure at the surface was obtained for liquid-containing clouds. Radiative closure results were compared with those based on a similar, yet simpler, cloud retrieval system. These comparisons demonstrated the importance of accurate cloud-phase and cloud-type classification, and specifically the identification of liquid water, for determining radiative fluxes. Enhanced retrievals of liquid water path for thin clouds were also shown to improve radiative flux calculations.

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Christopher J. Cox, David D. Turner, Penny M. Rowe, Matthew D. Shupe, and Von P. Walden

Abstract

The radiative properties of clouds are related to cloud microphysical and optical properties, including water path, optical depth, particle size, and thermodynamic phase. Ground-based observations from remote sensors provide high-quality, long-term, continuous measurements that can be used to obtain these properties. In the Arctic, a more comprehensive understanding of cloud microphysics is important because of the sensitivity of the Arctic climate to changes in radiation. Eureka, Nunavut (80°N, 86°25′W, 10 m), Canada, is a research station located on Ellesmere Island. A large suite of ground-based remote sensors at Eureka provides the opportunity to make measurements of cloud microphysics using multiple instruments and methodologies. In this paper, cloud microphysical properties are presented using a retrieval method that utilizes infrared radiances obtained from an infrared spectrometer at Eureka between March 2006 and April 2009. These retrievals provide a characterization of the microphysics of ice and liquid in clouds with visible optical depths between 0.25 and 6, which are a class of clouds whose radiative properties depend greatly on their microphysical properties. The results are compared with other studies that use different methodologies at Eureka, providing context for multimethod perspectives. The authors’ findings are supportive of previous studies, including seasonal cycles in phase and liquid particle size, weak temperature–phase dependencies, and frequent occurrences of supercooled water. Differences in microphysics are found between mixed-phase and single-phase clouds for both ice and liquid. The Eureka results are compared with those obtained using a similar retrieval technique during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment.

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Stefan Kneifel, Stephanie Redl, Emiliano Orlandi, Ulrich Löhnert, Maria P. Cadeddu, David D. Turner, and Ming-Tang Chen

Abstract

Microwave radiometers (MWR) are commonly used to quantify the amount of supercooled liquid water (SLW) in clouds; however, the accuracy of the SLW retrievals is limited by the poor knowledge of the SLW dielectric properties at microwave frequencies. Six liquid water permittivity models were compared with ground-based MWR observations between 31 and 225 GHz from sites in Greenland, the German Alps, and a low-mountain site; average cloud temperatures of observed thin cloud layers range from 0° to −33°C. A recently published method to derive ratios of liquid water opacity from different frequencies was employed in this analysis. These ratios are independent of liquid water path and equal to the ratio of α L at those frequencies that can be directly compared with the permittivity model predictions. The observed opacity ratios from all sites show highly consistent results that are generally within the range of model predictions; however, none of the models are able to approximate the observations over the entire frequency and temperature range. Findings in earlier published studies were used to select one specific model as a reference model for α L at 90 GHz; together with the observed opacity ratios, the temperature dependence of α L at 31.4, 52.28, 150, and 225 GHz was derived. The results reveal that two models fit the opacity ratio data better than the other four models, with one of the two models fitting the data better for frequencies below 90 GHz and the other for higher frequencies. These findings are relevant for SLW retrievals and radiative transfer in the 31–225-GHz frequency region.

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