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Scott N. Paine, David D. Turner, and Nils Küchler

Abstract

An absorbing load in a liquid nitrogen bath is commonly used as a radiance standard for calibrating radiometers operating at microwave to infrared wavelengths. It is generally assumed that the physical temperature of the load is stable and equal to the boiling point temperature of pure N2 at the ambient atmospheric pressure. However, this assumption will fail to hold when air movement, as encountered in outdoor environments, allows O2 gas to condense into the bath. Under typical conditions, initial boiling point drift rates of order 25 mK min−1 can occur, and the boiling point of a bath maintained by repeated refilling with pure N2 can eventually shift by approximately 2 K. Laboratory bench tests of a liquid nitrogen bath under simulated wind conditions are presented together with an example of an outdoor radiometer calibration that demonstrates the effect, and the physical processes involved are explained in detail. A key finding is that in windy conditions, changes in O2 volume fraction are related accurately to fractional changes in bath volume due to boiloff, independent of wind speed. This relation can be exploited to ensure that calibration errors due to O2 contamination remain within predictable bounds.

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Rob K. Newsom, David D. Turner, and John E. M. Goldsmith

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This study investigates the accuracy and calibration stability of temperature profiles derived from an operational Raman lidar over a 2-yr period from 1 January 2009 to 31 December 2010. The lidar, which uses the rotational Raman technique for temperature measurement, is located at the U.S. Department of Energy's Atmospheric Radiation Measurement site near Billings, Oklahoma. The lidar performance specifications, data processing algorithms, and the results of several test runs are described. Calibration and overlap correction of the lidar is achieved using simultaneous and collocated radiosonde measurements. Results show that the calibration coefficients exhibit no significant long-term or seasonal variation but do show a distinct diurnal variation. When the diurnal variation in the calibration is not resolved the lidar temperature bias exhibits a significant diurnal variation. Test runs in which only nighttime radiosonde measurements are used for calibration show that the lidar exhibits a daytime warm bias that is correlated with the strength of the solar background signal. This bias, which reaches a maximum of ~2.4 K near solar noon, is reduced through the application of a correction scheme in which the calibration coefficients are parameterized in terms of the solar background signal. Comparison between the corrected lidar temperatures and the noncalibration radiosonde temperatures show a negligibly small median bias of −0.013 K for altitudes below 10 km AGL. The corresponding root-mean-square difference profile is roughly constant at ~2 K below 6 km AGL and increases to about 4.5 K at 10 km AGL.

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

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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 T. Bray, David D. Turner, and Gijs de Boer

Abstract

Despite a need for accurate weather forecasts for societal and economic interests in the U.S. Arctic, thorough evaluations of operational numerical weather prediction in the region have been limited. In particular, the Rapid Refresh Model (RAP), which plays a key role in short-term forecasting and decision making, has seen very limited assessment in northern Alaska, with most evaluation efforts focused on lower latitudes. In the present study, we verify forecasts from version 4 of the RAP against radiosonde, surface meteorological, and radiative flux observations from two Arctic sites on the northern Alaskan coastline, with a focus on boundary-layer thermodynamic and dynamic biases, model representation of surface inversions, and cloud characteristics. We find persistent seasonal thermodynamic biases near the surface that vary with wind direction, and may be related to the RAP’s handling of sea ice and ocean interactions. These biases seem to have diminished in the latest version of the RAP (version 5), which includes refined handling of sea ice, among other improvements. In addition, we find that despite capturing boundary-layer temperature profiles well overall, the RAP struggles to consistently represent strong, shallow surface inversions. Further, while the RAP seems to forecast the presence of clouds accurately in most cases, there are errors in the simulated characteristics of these clouds, which we hypothesize may be related to the RAP’s treatment of mixed-phase clouds.

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Samuel K. Degelia, Xuguang Wang, David J. Stensrud, and David D. Turner

Abstract

Nocturnal convection is often initiated by mechanisms that cannot be easily observed within the large gaps between rawinsondes or by conventional surface networks. To improve forecasts of such events, we evaluate the systematic impact of assimilating a collocated network of high-frequency, ground-based thermodynamic and kinematic profilers collected as part of the 2015 Plains Elevated Convection At Night (PECAN) experiment. For 13 nocturnal convection initiation (CI) events, we find small but consistent improvements when assimilating thermodynamic observations collected by Atmospheric Emitted Radiance Interferometers (AERIs). Through midlevel cooling and moistening, assimilating the AERIs increases the fractions skill score (FSS) for both nocturnal CI and precipitation forecasts. The AERIs also improve various contingency metrics for CI forecasts. Assimilating composite kinematic datasets collected by Doppler lidars and radar wind profilers (RWPs) results in slight degradations to the forecast quality, including decreases in the FSS and traditional contingency metrics. The impacts from assimilating thermodynamic and kinematic profilers often counteract each other, such that we find little impact on the detection of CI when both are assimilated. However, assimilating both datasets improves various properties of the CI events that are successfully detected (timing, distance, shape, etc.). We also find large variability in the impact of assimilating these remote sensing profilers, likely due to the number of observing sites and the strength of the synoptic forcing for each case. We hypothesize that the lack of flow-dependent methods to diagnose observation errors likely contributes to degradations in forecast skill for many cases, especially when assimilating kinematic profilers.

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David M. Loveless, Timothy J. Wagner, David D. Turner, Steven A. Ackerman, and Wayne F. Feltz

Abstract

Atmospheric bores have been shown to have a role in the initiation and maintenance of elevated convection. Previous observational studies of bores have been case studies of more notable events. However, this creates a selection bias toward extraordinary cases, while discussions of the differences between bores that favor convective initiation and maintenance and bores that do not are lacking from the literature. This study attempts to fill that gap by analyzing a high-temporal-resolution thermodynamic profile composite of eight bores observed by multiple platforms during the Plains Elevated Convection at Night (PECAN) campaign in order to assess the impact of bores on the environment. The time–height cross section of the potential temperature composite displays quasi-permanent parcel displacements up to 900 m with the bore passage. Low-level lifting is shown to weaken the capping inversion and reduce convective inhibition (CIN) and the level of free convection (LFC). Additionally, low-level water vapor increases by about 1 g kg−1 in the composite mean. By assessing variability across the eight cases, it is shown that increases in low-level water vapor result in increases to convective available potential energy (CAPE), while drying results in decreased CAPE. Most cases resulted in decreased CIN and LFC height with the bore passage, but only some cases resulted in increased CAPE. This suggests that bores will increase the potential for convective initiation, but future research should be directed toward better understanding cases that result in increased CAPE as those are the types of bores that will increase severity of convection.

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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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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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Michael C. Coniglio, Glen S. Romine, David D. Turner, and Ryan D. Torn

Abstract

The ability of Atmospheric Emitted Radiance Interferometer (AERI) and Doppler lidar (DL) wind profile observations to impact short-term forecasts of convection is explored by assimilating retrievals into a partially cycled convection-allowing ensemble analysis and forecast system. AERI and DL retrievals were obtained over 12 days using a mobile platform that was deployed in the preconvective and near-storm environments of thunderstorms during the afternoon in the U.S. Great Plains. The observation locations were guided by real-time ensemble sensitivity analysis (ESA) fields. AERI retrievals of temperature and dewpoint and DL retrievals of the horizontal wind components were assimilated into a control experiment that only assimilated conventional observations. Using the fractions skill score within 25-km neighborhoods, it is found that the assimilation of the AERI and DL retrievals results in far more times when the forecasts are improved than degraded in the 6-h forecast period. However, statistical confidence in the improvements often is not high and little to no relationships between the ESA fields and the actual changes in spread and skill is found. But, the focus on convective initiation and early convective evolution—a challenging forecast problem—and the fact that frequent improvements were seen despite observations from only one system over a limited period, provides encouragement to continue exploring the benefits of ground-based profilers to supplement the current upper-air observing system for severe weather forecasting applications.

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Matthew D. Shupe, Jennifer M. Comstock, David D. Turner, and Gerald G. Mace
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