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Mark A. Askelson
,
Chris J. Theisen
, and
Randall S. Johnson

Abstract

Owing to their ease of use, “simplified” propagation models, like the equivalent Earth model, are commonly employed to determine radar data locations. With the assumption that electromagnetic rays follow paths of constant curvature, which is a fundamental assumption in the equivalent Earth model, propagation equations that do not depend upon the spatial transformation that is utilized in the equivalent Earth model are derived. This set of equations provides the true constant curvature solution and is less complicated, conceptually, as it does not depend upon a spatial transformation. Moreover, with the assumption of constant curvature, the relations derived herein arise naturally from ray tracing relations. Tests show that this new set of equations is more accurate than the equivalent Earth equations for a “typical” propagation environment in which the index of refraction n decreases linearly at the rate dn/dh = −1/4a, where h is height above ground and a is Earth’s radius. Moreover, this new set of equations performs better than the equivalent Earth equations for an exponential reference atmosphere, which provides a very accurate representation of the average atmospheric n structure in the United States. However, with this n profile the equations derived herein, the equivalent Earth equations, and the relation associated with a flat Earth constant curvature model produce relatively large height errors at low elevations and large ranges. Taylor series approximations of the new equations are examined. While a second-order Taylor series approximation for height performs well under “typical” propagation conditions, a convenient Taylor series approximation for great circle distance was not obtained.

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Brian A. Klimowski
,
Mark R. Hjelmfelt
,
Matthew J. Bunkers
,
Don Sedlacek
, and
L. Ronald Johnson

Abstract

No abstract available.

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Pavlos Kollias
,
Mark A. Miller
,
Edward P. Luke
,
Karen L. Johnson
,
Eugene E. Clothiaux
,
Kenneth P. Moran
,
Kevin B. Widener
, and
Bruce A. Albrecht

Abstract

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates millimeter-wavelength cloud radars in several climatologically distinct regions. The digital signal processors for these radars were recently upgraded and allow for enhancements in the operational parameters running on them. Recent evaluations of millimeter-wavelength cloud radar signal processing performance relative to the range of cloud dynamical and microphysical conditions encountered at the ARM Program sites have indicated that improvements are necessary, including significant improvement in temporal resolution (i.e., less than 1 s for dwell and 2 s for dwell and processing), wider Nyquist velocities, operational dealiasing of the recorded spectra, removal of pulse compression while sampling the boundary layer, and continuous recording of Doppler spectra. A new set of millimeter-wavelength cloud radar operational modes that incorporate these enhancements is presented. A significant change in radar sampling is the introduction of an uneven mode sequence with 50% of the sampling time dedicated to the lower atmosphere, allowing for detailed characterization of boundary layer clouds. The changes in the operational modes have a substantial impact on the postprocessing algorithms that are used to extract cloud information from the radar data. New methods for postprocessing of recorded Doppler spectra are presented that result in more accurate identification of radar clutter (e.g., insects) and extraction of turbulence and microphysical information. Results of recent studies on the error characteristics of derived Doppler moments are included so that uncertainty estimates are now included with the moments. The microscale data product based on the increased temporal resolution of the millimeter-wavelength cloud radars is described. It contains the number of local maxima in each Doppler spectrum, the Doppler moments of the primary peak, uncertainty estimates for the Doppler moments of the primary peak, Doppler moment shape parameters (e.g., skewness and kurtosis), and clear-air clutter flags.

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Pavlos Kollias
,
Bruce A. Albrecht
,
Eugene E. Clothiaux
,
Mark A. Miller
,
Karen L. Johnson
, and
Kenneth P. Moran

Abstract

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurements (ARM) program operates millimeter-wavelength cloud radars (MMCRs) in several specific locations within different climatological regimes. These vertically pointing cloud profiling radars supply the three most important Doppler spectrum moment estimates, which are the radar reflectivity (or zero moment), the mean Doppler velocity (or first moment), and the Doppler spectrum width (or second moment), as a function of time and height. The ARM MMCR Doppler moment estimates form the basis of a number of algorithms for retrieving cloud microphysical and radiative properties. The retrieval algorithms are highly sensitive to the quality and accuracy of the MMCR Doppler moment estimates. The significance of these sensitivities should not be underestimated, because the inherent physical variability of clouds, instrument-induced noise, and sampling strategy limitations all potentially introduce errors into the Doppler moment estimates. In this article, the accuracies of the first three Doppler moment estimates from the ARM MMCRs are evaluated for a set of typical cloud conditions from the three DOE ARM program sites. Results of the analysis suggest that significant errors in the Doppler moment estimates are possible in the current configurations of the ARM MMCRs. In particular, weakly reflecting clouds with low signal-to-noise ratios (SNRs), as well as turbulent clouds with nonzero updraft and downdraft velocities that are coupled with high SNR, are shown to produce degraded Doppler moment estimates in the current ARM MMCR operational mode processing strategies. Analysis of the Doppler moment estimates and MMCR receiver noise characteristics suggests that the introduction of a set of quality control criteria is necessary for identifying periods of degraded receiver performance that leads to larger uncertainties in the Doppler moment estimates. Moreover, the temporal sampling of the ARM MMCRs was found to be insufficient for representing the actual dynamical states in many types of clouds, especially boundary layer clouds. New digital signal processors (DSPs) are currently being developed for the ARM MMCRs. The findings presented in this study will be used in the design of a new set of operational strategies for the ARM MMCRs once they have been upgraded with the new DSPs.

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Sue Ellen Haupt
,
Steven Hanna
,
Mark Askelson
,
Marshall Shepherd
,
Mariana A. Fragomeni
,
Neil Debbage
, and
Bradford Johnson

Abstract

The human population on Earth has increased by a factor of 4.6 in the last 100 years and has become more centered in urban environments. This expansion and migration pattern has resulted in stresses on the environment. Meteorological applications have helped to understand and mitigate those stresses. This chapter describes several applications that enable the population to interact with the environment in more sustainable ways. The first topic treated is urbanization itself and the types of stresses exerted by population growth and its attendant growth in urban landscapes—buildings and pavement—and how they modify airflow and create a local climate. We describe environmental impacts of these changes and implications for the future. The growing population uses increasing amounts of energy. Traditional sources of energy have taxed the environment, but the increase in renewable energy has used the atmosphere and hydrosphere as its fuel. Utilizing these variable renewable resources requires meteorological information to operate electric systems efficiently and economically while providing reliable power and minimizing environmental impacts. The growing human population also pollutes the environment. Thus, understanding and modeling the transport and dispersion of atmospheric contaminants are important steps toward regulating the pollution and mitigating impacts. This chapter describes how weather information can help to make surface transportation more safe and efficient. It is explained how these applications naturally require transdisciplinary collaboration to address these challenges caused by the expanding population.

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Igor V. Polyakov
,
Roman V. Bekryaev
,
Genrikh V. Alekseev
,
Uma S. Bhatt
,
Roger L. Colony
,
Mark A. Johnson
,
Alexander P. Maskshtas
, and
David Walsh

Abstract

Arctic atmospheric variability during the industrial era (1875–2000) is assessed using spatially averaged surface air temperature (SAT) and sea level pressure (SLP) records. Air temperature and pressure display strong multidecadal variability on timescales of 50–80 yr [termed low-frequency oscillation (LFO)]. Associated with this variability, the Arctic SAT record shows two maxima: in the 1930s–40s and in recent decades, with two colder periods in between. In contrast to the global and hemispheric temperature, the maritime Arctic temperature was higher in the late 1930s through the early 1940s than in the 1990s. Incomplete sampling of large-amplitude multidecadal fluctuations results in oscillatory Arctic SAT trends. For example, the Arctic SAT trend since 1875 is 0.09 ± 0.03°C decade−1, with stronger spring- and wintertime warming; during the twentieth century (when positive and negative phases of the LFO nearly offset each other) the Arctic temperature increase is 0.05 ± 0.04°C decade−1, similar to the Northern Hemispheric trend (0.06°C decade−1). Thus, the large-amplitude multidecadal climate variability impacting the maritime Arctic may confound the detection of the true underlying climate trend over the past century. LFO-modulated trends for short records are not indicative of the long-term behavior of the Arctic climate system. The accelerated warming and a shift of the atmospheric pressure pattern from anticyclonic to cyclonic in recent decades can be attributed to a positive LFO phase. It is speculated that this LFO-driven shift was crucial to the recent reduction in Arctic ice cover. Joint examination of air temperature and pressure records suggests that peaks in temperature associated with the LFO follow pressure minima after 5–15 yr. Elucidating the mechanisms behind this relationship will be critical to understanding the complex nature of low-frequency variability.

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Michael E. Feinholz
,
Stephanie J. Flora
,
Mark A. Yarbrough
,
Keith R. Lykke
,
Steven W. Brown
,
B. Carol Johnson
, and
Dennis K. Clark

Abstract

The Marine Optical System is a spectrograph-based sensor used on the Marine Optical Buoy for the vicarious calibration of ocean color satellite sensors. It is also deployed from ships in instruments used to develop bio-optical algorithms that relate the optical properties of the ocean to its biological content. In this work, an algorithm is applied to correct the response of the Marine Optical System for scattered, or improperly imaged, light in the system. The algorithm, based on the measured response of the system to a series of monochromatic excitation sources, reduces the effects of scattered light on the measured source by one to two orders of magnitude. Implications for the vicarious calibration of satellite ocean color sensors and the development of bio-optical algorithms are described. The algorithm is a one-dimensional point spread correction algorithm, generally applicable to nonimaging sensors, but can in principle be extended to higher dimensions for imaging systems.

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Matthew J. Bunkers
,
Jeffrey S. Johnson
,
Lee J. Czepyha
,
Jason M. Grzywacz
,
Brian A. Klimowski
, and
Mark R. Hjelmfelt

Abstract

The local and larger-scale environments of 184 long-lived supercell events (containing one or more supercells with lifetimes ≥4 h; see Part I of this paper) are investigated and subsequently compared with those from 137 moderate-lived events (average supercell lifetime 2–4 h) and 119 short-lived events (average supercell lifetime ≤2 h) to better anticipate supercell longevity in the operational setting. Consistent with many previous studies, long-lived supercells occur in environments with much stronger 0–8-km bulk wind shear than what is observed for short-lived supercells; this strong shear leads to significant storm-relative winds in the mid- to upper levels for the longest-lived supercells. Additionally, the bulk Richardson number falls into a relatively narrow range for the longest-lived supercells—ranging mostly from 5 to 45. The mesoscale to synoptic-scale environment can also predispose a supercell to be long or short lived, somewhat independent of the local environment. For example, long-lived supercells may occur when supercells travel within a broad warm sector or else in close proximity to mesoscale or larger-scale boundaries (e.g., along or near a warm front, an old outflow boundary, or a moisture/buoyancy axis), even if the deep-layer shear is suboptimal. By way of contrast, strong atmospheric forcing can result in linear convection (and thus shorter-lived supercells) in a strongly sheared environment that would otherwise favor discrete, long-lived supercells.

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Igor V. Polyakov
,
Genrikh V. Alekseev
,
Roman V. Bekryaev
,
Uma S. Bhatt
,
Roger Colony
,
Mark A. Johnson
,
Valerii P. Karklin
,
David Walsh
, and
Alexander V. Yulin

Abstract

Examination of records of fast ice thickness (1936–2000) and ice extent (1900–2000) in the Kara, Laptev, East Siberian, and Chukchi Seas provide evidence that long-term ice thickness and extent trends are small and generally not statistically significant, while trends for shorter records are not indicative of the long-term tendencies due to large-amplitude low-frequency variability. The ice variability in these seas is dominated by a multidecadal, low-frequency oscillation (LFO) and (to a lesser degree) by higher-frequency decadal fluctuations. The LFO signal decays eastward from the Kara Sea where it is strongest. In the Chukchi Sea ice variability is dominated by decadal fluctuations, and there is no evidence of the LFO. This spatial pattern is consistent with the air temperature–North Atlantic Oscillation (NAO) index correlation pattern, with maximum correlation in the near-Atlantic region, which decays toward the North Pacific. Sensitivity analysis shows that dynamical forcing (wind or surface currents) dominates ice-extent variations in the Laptev, East Siberian, and Chukchi Seas. Variability of Kara Sea ice extent is governed primarily by thermodynamic factors.

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Pavlos Kollias
,
Eugene E. Clothiaux
,
Thomas P. Ackerman
,
Bruce A. Albrecht
,
Kevin B. Widener
,
Ken P. Moran
,
Edward P. Luke
,
Karen L. Johnson
,
Nitin Bharadwaj
,
James B. Mead
,
Mark A. Miller
,
Johannes Verlinde
,
Roger T. Marchand
, and
Gerald G. Mace
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