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L. D. Travis

Abstract

Models for the origin of the contrasts in the ultraviolet images of Venus are examined in an attempt to determine the physical differences between light and dark regions fundamental to a clear understanding of the apparent cloud motions. To evaluate the meaning of the wavelength dependence of the contrasts, an improved determination of the spherical albedo curve for Venus in the 0.225 ≤ λ ≤ 1.06 μm range is made by fitting appropriate theoretical models to the observations of monochromatic magnitude as a function of phase angle. It is shown that, because of differences between the spectral dependences of spherical albedo and contrasts, at least one major absorber other than the one causing the contrasts is almost certainly required.

A popular model employing differential Rayleigh scattering due to variations in cloud height can be ruled out, but several classes of models are compatible with present observational evidence. The contrasts and the absorption associated with them may in fact be occurring below, within or above the main visible cloud layer, and thus an unambiguous interpretation of the apparent cloud motions is not possible.

Ground-based observations of the polarization for the regions of contrast may permit the field of acceptable models to be narrowed. Observations planned for the Pioneer Venus orbiter and entry probes should provide the information on local cloud properties and vertical structure necessary to reveal the physical nature of the UV markings.

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Travis M. Smith, Kimberly L. Elmore, and Shannon A. Dulin

Abstract

The problem of predicting the onset of damaging downburst winds from high-reflectivity storm cells that develop in an environment of weak vertical shear with Weather Surveillance Radar-1988 Doppler (WSR-88D) is examined. Ninety-one storm cells that produced damaging outflows are analyzed with data from the WSR- 88D network, along with 1247 nonsevere storm cells that developed in the same environments. Twenty-six reflectivity and radial velocity–based parameters are calculated for each cell, and a linear discriminant analysis was performed on 65% of the dataset in order to develop prediction equations that would discriminate between severe downburst-producing cells and cells that did not produce a strong outflow. These prediction equations are evaluated on the remaining 35% of the dataset. The datasets were resampled 100 times to determine the range of possible results. The resulting automated algorithm has a median Heidke skill score (HSS) of 0.40 in the 20–45-km range with a median lead time of 5.5 min, and a median HSS of 0.17 in the 45–80-km range with a median lead time of 0 min. As these lead times are medians of the mean lead times calculated from a large, resampled dataset, many of the storm cells in the dataset had longer lead times than the reported median lead times.

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Madison L. Miller, Valliappa Lakshmanan, and Travis M. Smith

Abstract

The location and intensity of mesocyclone circulations can be tracked in real time by accumulating azimuthal shear values over time at every location of a uniform spatial grid. Azimuthal shear at low (0–3 km AGL) and midlevels (3–6 km AGL) of the atmosphere is computed in a noise-tolerant manner by fitting the Doppler velocity observations in the neighborhood of a pulse volume to a plane and finding the slope of that plane. Rotation tracks created in this manner are contaminated by nonmeteorological signatures caused by poor velocity dealiasing, ground clutter, radar test patterns, and spurious shear values. To improve the quality of these fields for real-time use and for an accumulated multiyear climatology, new dealiasing strategies, data thresholding, and multiple hypothesis tracking (MHT) techniques have been implemented. These techniques remove nearly all nonmeteorological contaminants, resulting in much clearer rotation tracks that appear to match mesocyclone paths and intensities closely.

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Pamela L. Heinselman, David L. Priegnitz, Kevin L. Manross, Travis M. Smith, and Richard W. Adams

Abstract

A key advantage of the National Weather Radar Testbed Phased Array Radar (PAR) is the capability to adaptively scan storms at higher temporal resolution than is possible with the Weather Surveillance Radar-1988 Doppler (WSR-88D): 1 min or less versus 4.1 min, respectively. High temporal resolution volumetric radar data are a necessity for rapid identification and confirmation of weather phenomena that can develop within minutes. The purpose of this paper is to demonstrate the PAR’s ability to collect rapid-scan volumetric data that provide more detailed depictions of quickly evolving storm structures than the WSR-88D. Scientific advantages of higher temporal resolution PAR data are examined for three convective storms that occurred during the spring and summer of 2006, including a reintensifying supercell, a microburst, and a hailstorm. The analysis of the reintensifying supercell (58-s updates) illustrates the capability to diagnose the detailed evolution of developing and/or intensifying areas of 1) low-altitude divergence and rotation and 2) rotation through the depth of the storm. The fuller sampling of the microburst’s storm life cycle (34-s updates) depicts precursors to the strong surface outflow that are essentially indiscernible in the WSR-88D data. Furthermore, the 34-s scans provide a more precise sampling of peak outflow. The more frequent sampling of the hailstorm (26-s updates) illustrates the opportunity to analyze storm structures indicative of rapid intensification, the development of hail aloft, and the onset of the downdraft near the surface.

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John L. Cintineo, Travis M. Smith, Valliappa Lakshmanan, Harold E. Brooks, and Kiel L. Ortega

Abstract

The threat of damaging hail from severe thunderstorms affects many communities and industries on a yearly basis, with annual economic losses in excess of $1 billion (U.S. dollars). Past hail climatology has typically relied on the National Oceanic and Atmospheric Administration/National Climatic Data Center’s (NOAA/NCDC) Storm Data publication, which has numerous reporting biases and nonmeteorological artifacts. This research seeks to quantify the spatial and temporal characteristics of contiguous United States (CONUS) hail fall, derived from multiradar multisensor (MRMS) algorithms for several years during the Next-Generation Weather Radar (NEXRAD) era, leveraging the Multiyear Reanalysis of Remotely Sensed Storms (MYRORSS) dataset at NOAA’s National Severe Storms Laboratory (NSSL). The primary MRMS product used in this study is the maximum expected size of hail (MESH). The preliminary climatology includes 42 months of quality controlled and reprocessed MESH grids, which spans the warm seasons for four years (2007–10), covering 98% of all Storm Data hail reports during that time. The dataset has 0.01° latitude × 0.01° longitude × 31 vertical levels spatial resolution, and 5-min temporal resolution. Radar-based and reports-based methods of hail climatology are compared. MRMS MESH demonstrates superior coverage and resolution over Storm Data hail reports, and is largely unbiased. The results reveal a broad maximum of annual hail fall in the Great Plains and a diminished secondary maximum in the Southeast United States. Potential explanations for the differences in the two methods of hail climatology are also discussed.

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B. R. Bean, R. Gilmer, R. L. Grossman, R. McGavin, and C. Travis

Abstract

The initial analysis of the water vapor flux measurements taken onboard a NOAA DC-6 during the Barbados Oceanographic and Meteorological Experiment (BOMEX) is presented. The flux of water vapor seems to be constant in the lower subcloud layer. Day-to-day variations, as well as variations within a day are apparent in the evaporation data. Spatial variations of evaporation also seem to be present. The average value of water vapor flux for the experimental period is ∼0.5 cm day−1. Spectra of the instantaneous flux reveal significant alongwind-crosswind differences. Height variation of the wavelength of maximum spectral density for crosswind runs is confirmed. The instantaneous flux is intermittent in nature. Consideration of the cross spectra and time series signatures allows some speculation upon models which may be responsible for a major portion of the water vapor transport in the lower subcloud layer during BOMEX.

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Andrew M. Carleton, David J. Travis, Jimmy O. Adegoke, David L. Arnold, and Steve Curran

Abstract

In of this observational study inquiring into the relative influences of “top down” synoptic atmospheric conditions and “bottom up” land surface mesoscale conditions in deep convection for the humid lowlands of the Midwest U.S. Central Corn Belt (CCB), the composite atmospheric environments for afternoon and evening periods of convection (CV) versus no convection (NC) were determined for two recent summers (1999 and 2000) having contrasting precipitation patterns and amounts. A close spatial correspondence was noted between composite synoptic features representing baroclinity and upward vertical motion with the observed precipitation on CV days when the “background” (i.e., free atmosphere) wind speed exceeded approximately 10 m s−1 at 500 hPa (i.e., “stronger flow”). However, on CV days when wind speeds were <∼10 m s−1 (i.e., “weaker flow”), areas of increased precipitation can be associated with synoptic composites that are not so different from those for corresponding NC days. From these observations, the presence of a land surface mesoscale influence on deep convection and precipitation is inferred that is better expressed on weaker flow days. Climatically, a likely candidate for enhancing low-level moisture convergence to promote deep convection are the quasi-permanent vegetation boundaries (QPVBs) between the two major land use and land cover (LULC) types of crop and forest that characterize much of the CCB. Accordingly, in this paper the role of these boundaries on summer precipitation variations for the CCB is extracted in two complementary ways: 1) for contrasting flow day types in the summers 1999 and 2000, by determining the spatially and temporally aggregated land surface influence on deep convection from composites of thermodynamic variables [e.g., surface lifted index (SLI), level of free convection (LFC), and lifted condensation level (LCL)] that are obtained from mapped data of the 6-h NCEP–NCAR reanalyses (NNR), and 0000 UTC rawinsonde ascents; and 2) for summer seasons 1995–2001, from the statistical associations of satellite-retrieved LULC boundary attributes (i.e., length and width) and precipitation at high spatial resolutions.

For the 1999 and 2000 summers (item 1 above), thermodynamic composites determined for V(500) categories having minimal differences in synoptic meteorological fields on CV minus NC (CV − NC) days (i.e., weaker flow), show statistically significant increases in atmospheric moisture (e.g., greater precipitable water; lower LCL and LFC) and static instability [e.g., positive convective available potential energy (CAPE)] compared to NC days. Moreover, CV days for both weaker and stronger background flow have associated subregional-scale thermodynamic patterns indicating free convection at the earth’s surface, supported by a synoptic pattern of at least weakly upward motion of air in the midtroposphere in contrast to NC days.

The possibility that aerodynamic contrasts along QPVBs readily permit air to be lofted above the LFC when the lower atmosphere is moist, thereby assisting or enhancing deep convection on CV days, is supported by the multiyear analysis (item 2 above). In early summer when LULC boundaries are most evident, precipitation on weaker flow days is significantly greater within 20 km of boundaries than farther away, but there is no statistical difference on stronger flow days. Statistical relationships between boundary mean attributes and mean precipitation change sign between early summer (positive) and late summer (negative), in accord with shifts in the satellite-retrieved maximum radiances from forest to crop areas. These phenological changes appear related, primarily, to contrasting soil moisture and implied evapotranspiration differences. Incorporating LULC boundary locations and phenological status into reliable forecast fields of lower-to-midtropospheric humidity and wind speed should lead to improved short-term predictions of convective precipitation in the Corn Belt and also, potentially, better climate seasonal forecasts.

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Skylar S. Williams, Kiel L. Ortega, Travis M. Smith, and Anthony E. Reinhart

Abstract

The Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) data set blends radar data from the WSR-88D network and Near-Storm Environmental (NSE) model analyses using the Multi-Radar Multi-Sensor (MRMS) framework. The MYRORSS data set uses the WSR-88D archive starting in 1998 through 2011, processing all valid single-radar volumes to produce a seamless three-dimensional reflectivity volume over the entire contiguous United States with an approximate 5-min update frequency. The three-dimensional grid has an approximate 1-km by 1-km horizontal dimension and is on a stretched vertical grid that extends to 20 km MSL with a maximal vertical spacing of 1 km. Several reflectivity-derived, severe storm related products are also produced, which leverage the ability to merge the MRMS and NSE data. Two Doppler velocity-derived azimuthal shear layer maximum products are produced at a higher horizontal resolution of approximately 0.5-km by 0.5-km. The initial period of record for the data set is 1998-2011.

The data set underwent intensive manual quality control to ensure that all available and valid data were included while excluding highly problematic radar volumes that were a negligible percentage of the overall data set, but which caused large data errors in some cases. This data set has applications towards radar-based climatologies, post-event analysis, machine learning applications, model verification, and warning improvements. Details of the manual quality control process are included and examples of some of these applications are presented.

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Jennifer F. Newman, Valliappa Lakshmanan, Pamela L. Heinselman, Michael B. Richman, and Travis M. Smith

Abstract

The current tornado detection algorithm (TDA) used by the National Weather Service produces a large number of false detections, primarily because it calculates azimuthal shear in a manner that is adversely impacted by noisy velocity data and range-degraded velocity signatures. Coincident with the advent of new radar-derived products and ongoing research involving new weather radar systems, the National Severe Storms Laboratory is developing an improved TDA. A primary component of this algorithm is the local, linear least squares derivatives (LLSD) azimuthal shear field. The LLSD method incorporates rotational derivatives of the velocity field and is affected less strongly by noisy velocity data in comparison with traditional “peak to peak” azimuthal shear calculations. LLSD shear is generally less range dependent than peak-to-peak shear, although some range dependency is unavoidable. The relationship between range and the LLSD shear values of simulated circulations was examined to develop a range correction for LLSD shear. A linear regression and artificial neural networks (ANNs) were investigated as range-correction models. Both methods were used to produce fits for the simulated shear data, although the ANN excelled as it could capture the nonlinear nature of the data. The range-correction methods were applied to real radar data from tornadic and nontornadic events to measure the capacity of the corrected shear to discriminate between tornadic and nontornadic circulations. The findings presented herein suggest that both methods increased shear values during tornadic periods by nearly an order of magnitude, facilitating differentiation between tornadic and nontornadic scans in tornadic events.

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Andrew M. Carleton, David L. Arnold, David J. Travis, Steve Curran, and Jimmy O. Adegoke

Abstract

In the Midwest U.S. Corn Belt, the 1999 and 2000 summer seasons (15 June–15 September) expressed contrasting spatial patterns and magnitudes of precipitation (1999: dry; 2000: normal to moist). Distinct from the numerical modeling approach often used in studies of land surface–climate interactions, a “synoptic climatological” (i.e., stratified composite) approach is applied to observation data (e.g., precipitation, radar, and atmospheric reanalyses) to determine the relative influences of “top-down” synoptic atmospheric circulation (Part I, this paper) and “bottom-up” land surface mesoscale conditions (Part II) on the predominantly convective precipitation variations. Because mesoscale modeling suggests that the free-atmosphere wind speed (“background wind”) regulates the land surface–atmosphere mesoscale interaction, each day’s spatial range of wind speed at 500 hPa [V(500)] over the Central Corn Belt (CCB) is classified into one of five categories ranging from “weak flow” to “jet maximum.” Deep convective activity (i.e., presence/absence and morphological signature type) is determined for each afternoon and early evening period from the Next Generation Weather Radar (NEXRAD) imagery. Frequencies of the resulting background wind–convection joint occurrence types for the 1999 and 2000 summer seasons are examined in the context of the statistics determined for summers in the longer period of 1996–2001, and also compose categories for which NCEP–NCAR reanalysis (NNR) fields are averaged to yield synoptic composite environments for the two study seasons. The latter composites are compared visually with high-resolution (spatial) composites of precipitation to help identify the influence of top-down climate controls.

The analysis confirms that reduced (increased) organization of radar-indicated deep convection tends to occur with weaker (stronger) background flow. The summers of 1999 and 2000 differ from one another in terms of background flow and convective activity, but more so with respect to the six-summer averages, indicating that a fuller explanation of the precipitation differences in the two summers must be sought in the analysis of additional synoptic meteorological variables. The composite synoptic conditions on convection (CV) days (no convection (NC) days) in 1999 and 2000 are generalized as follows: low pressure incoming from the west (high pressure or ridging), southerly (northerly) lower-tropospheric winds, positive (negative) anomalies of moisture in the lower troposphere, rising (sinking) air in the midtroposphere, and a location south of the upper-tropospheric jet maximum (absence of an upper-tropospheric jet or one located just south of the area). Features resembling the “northerly low-level jets” identified in previous studies for the Great Plains are present on some NC-day composites. On CV days the spatial synchronization of synoptic features implying baroclinity increases with increasing background wind speed. The CV and NC composites differ least on days of weaker flow, and there are small areas within the CCB having no obvious association between precipitation elevated amounts and synoptic circulation features favoring the upward motion of air. These spatial incongruities imply a contributory influence of “stationary” (i.e., climatic) land surface mesoscale processes in convective activity, which are examined in Part II.

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