Abstract

The National Lightning Detection Network (NLDN) underwent a major upgrade during 2002–03 that increased its sensitivity and improved its performance. It is important to examine cloud-to-ground (CG) lightning distributions before and after this upgrade because CG characteristics depend on both measurement capabilities and meteorological variability. This study compares preupgrade (1996–99, 2001) and postupgrade (2004–09) CG distributions over the contiguous United States to examine the influence of the recent upgrade and to provide baseline postupgrade averages. Increased sensitivity explains most of the differences in the pre- and postupgrade distributions, including a general increase in total CG and positive CG (+CG) flash densities. The increase in +CG occurs despite the use of a greater weak +CG threshold for removing ambiguous +CG reports (post 15 kA versus pre 10 kA). Conversely, the average +CG percentage decreased from 10.61% to 8.65% following the upgrade. The average +CG (−CG) multiplicity increased from 1.10 (2.05) before to 1.54 (2.41) after the upgrade. Since true +CG flashes rarely contain more than one return stroke, explanations for the greater than unity +CG multiplicities remain unclear. Postupgrade results indicate that regions with mostly weak peak current +CG flashes now exhibit greater average +CG multiplicities, whereas regions with mainly strong +CG flashes now exhibit smaller average +CG multiplicities. The combination of NLDN performance, meteorological conditions, and physical differences in first −CG return strokes over saltwater produce maxima in −CG multiplicity and peak current over the coastal waters of the southeast United States.

Abstract

Storm severity in the mid-Atlantic region of the United States is examined using lightning, radar, and model-derived information. Automated Warning Decision Support System (WDSS) procedures are developed to create grids of lightning and radar parameters, cluster individual storm features, and data mine the lightning and radar attributes of 1252 severe and nonsevere storms. The study first examines the influence of serial correlation and uses autocorrelation functions to document the persistence of lightning and radar parameters. Decorrelation times are found to vary by parameter, storm severity, and mathematical operator, but the great majority are between three and six lags, suggesting that consecutive 2-min storm samples (following a storm) are effectively independent after only 6–12 min. The study next describes the distribution of lightning jumps in severe and nonsevere storms, differences between various types of severe storms (e.g., severe wind only), and relationships between lightning and radar parameters. The 2σ lightning jump algorithm (with a 10 flashes min⁻¹ activation threshold) yields 0.92 jumps h⁻¹ for nonsevere storms and 1.44 jumps h⁻¹ in severe storms. Applying a 10-mm maximum expected size of hail (MESH) threshold to the 2σ lightning jump algorithm reduces the frequency of lightning jumps in nonsevere storms to 0.61 jumps h⁻¹. Although radar-derived parameters are comparable between storms that produce severe wind plus hail and those that produce tornadoes, tornadic storms exhibit much greater intracloud (IC) and cloud-to-ground (CG) flash rates. Correlations further illustrate that lightning data provide complementary storm-scale information to radar-derived measures of storm intensity.

Abstract

Statistical algorithms are developed to diagnose the vertical change in equivalent potential temperature (ΔΘ _e ) between 920 and 620 hPa from GOES-8 radiance data. The models are prepared using a training dataset of radiosonde releases from 10 United States cities. Simulated GOES-8 channel brightness temperatures are calculated from these soundings. The training data are stratified into several subsets (depending on time and location). Models trained only on 0000 or 1200 UTC data explain approximately 7% more of the variance in observed ΔΘ _e than those trained on both 0000 and 1200 UTC. Values of R ² from models using training data from only one are superior to those trained on multiple stations. Inclusion of the imager channels adds little information to the algorithms.

These models then are applied to data from the Limited Area Mesoscale Prediction System model to see which performs consistently better over diurnally varying conditions. Models trained only with 0000 UTC data give the best results, explaining between 63% and 81% of the variance in the independent data. The model that performed best is studied further. Biases are present when this model is applied to times other than 0000 UTC. These biases are caused by temperature differences between the 0000 UTC training data and those at the times being examined. Strong regional biases also occur when a model trained on only one location is applied to a large area. A second model is incorporated into the procedure to reduce this bias. The two-model algorithm explains more variance than the initial one-model version (93% vs 77%), and the area of strong regional bias is greatly reduced.

This statistical procedure for ΔΘ _e is then tested on observed GOES-8 data. A new statistical model is formed using the observed GOES-8 brightness temperatures and ΔΘ _e ’s calculated from collocated radiosonde observations. The new model yields an R ² of 67% when applied to an independent dataset. This value is smaller than those from the models using simulated data, most likely due to several additional sources of discrepancy. Finally, simulated GOES-7 Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) radiances are used to prepare a ΔΘ _e algorithm. The VAS model explains approximately 5% less variance than its GOES-8 counterpart, due to the reduced vertical resolution available on VAS.

These analyses show that regionally trained regression models can accurately diagnose convective instability while using relatively little computational time.

Abstract

Generation of available potential energy (APE) is computed for the warm sector of an extratropical cyclone containing intense convection. Three hourly mesoscale rawinsonde data from the 10–11 April day of AVESESAME 1979 are used to evaluate generation by five diabatic components. Convective latent heat release is found to be the dominant diabatic term during times of intense convection, whereas stable latent heating provides a relatively small contribution. Sensible heat transfer is important near the surface during the afternoon. Solar and infrared radiative processes are quite significant in regions of low-level stratus and convective activity. Solar absorption during midday is observed to be much greater than at the standard rawinsonde observation times. The use of subjectively specified cloud data and sophisticated radiative transfer models permit more detailed resolution of cloud effects thin possible in earlier studies of this type.

Negative generation of APE is dominant during the 24 h period because convective latent heating is superimposed on areas of negative efficiency. The only consistent positive generation is due to infrared cooling. Sensible heating is the third largest generating component, while stable heating and solar absorption are least significant. Results document rapid temporal variations in generation as well as contrasts between energetics of the warm sector and those of entire cyclones.

Abstract

Meso β-scale radiosonde data at 75 km spacings and 3 or 1.5 h intervals from the fifth day of AVE-SESAME 1979 (20–21 May) are employed to investigate moisture budgets in thunderstorm environments. Budget values are computed at nine times prior to, during, and after a convective outbreak over Oklahoma. The domain under investigation includes both convective and nonconvective areas, thereby allowing budget comparisons between the two regions.

Findings show that the convective region is characterized by strong horizontal moisture flux convergence in the low levels and weak divergence aloft. Vertical motion carries moisture into the middle and upper troposphere. Magnitudes of the moisture fluxes are directly proportional to storm intensity. The vertically integrated source/sink term also is closely related to the presence and intensity of convective activity. When converted into equivalent precipitation amounts, values correspond closely with those from a rain gage network.

Moisture budgets also are obtained from routine National Weather Service rawinsonde soundings. A comparison of results for similar locations, but derived from the two different resolutions, reveals several common processes. However, magnitudes from the mesoscale data are sometimes an order of magnitude greater than those at the synoptic scale, especially in the convective areas.

Abstract

Software build 9.0 for the Weather Surveillance Radar-1988 Doppler (WSR-88D) contains several new or improved algorithms for detecting severe thunderstorms. The WSR-88D Operational Support Facility supports testing and optimization of these algorithms by local National Weather Service offices. This paper presents a new methodology for using Storm Data in these local evaluations. The methodology defines specific conditions a storm cell must meet to be included in the evaluation. These conditions include cell intensity and duration, population density along the cell track, and any previous severe reports in the county where the storm is located. These requirements avoid including storm cells that may have produced severe weather where reports would be very unlikely. The technique provides a more accurate picture of algorithm performance than if Storm Data is used with no special considerations.

This study utilizes the new methodology with data currently available for the Tallahassee, Florida, county warning area (TLH CWA). It describes the performance of two algorithms used for detecting severe hail. The first is the Probability of Severe Hail (POSH), a component of the build 9.0 Hail Detection Algorithm. The second is the algorithm that calculates vertically integrated liquid (VIL).

Early results show that the recommended POSH threshold of 50% appears appropriate for the TLH CWA. This suggests that the height of the freezing level provides a reasonably good estimate of the best severe hail index (SHI). However, early results also indicate that the average wet-bulb temperature from 1000 to 700 mb (low-level wet-bulb temperature) might produce an even better indication of the SHI threshold. Similarly, the threshold for VIL is highly correlated to the low-level wet-bulb temperature. Finally, the VIL algorithm is found to perform as well as the POSH parameter if the best VIL threshold can be determined in advance. Since the database used in these evaluations was relatively small, these findings should be considered tentative.

Abstract

Passive microwave brightness temperatures (T_B 's) at 92 and 183 GHz from an aircraft thunderstorm overflight are compared with values calculated from radar-derived hydrometer profiles and a modified proximity sounding. Two methods for modeling particles in the ice canopy are contrasted. The fist is a “traditional” approach employing Marshall–Palmer ice spheres. The second, or “alternative,” method partitions 20% of the ice water content into a Marshall–Palmer component for graupel and hail, and 80% into a modified gamma spherical particle size distribution function representing ice crystals.

Results from the alternative approach are superior to those from the traditional method in the anvil and mature convective core. In the decaying convective region, the traditional approach yields better agreement with observed magnitude. Neither method, however, matches the geometry of the observed T_B depression associated with the decaying convective core. This is likely due to the presence of graupel, which is not detected as a special signature in radar reflectivity, but does diminish T_B 's through scattering. Brightness temperatures at the relatively high microwave frequencies considered are shown to be very sensitive to the ice-particle size distribution.

Abstract

An algorithm is examined that uses Visible–Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) 11- and 12-µm (split-window) data to derive column-integrated water content (IWC) at mesoscale resolution. The algorithm is physically based and derives its first-guess information from radiosonde data. The procedure is applied first to a test case dataset and then to the 19 June 1986 study day from the Cooperative Huntsville Meteorological Experiment (COHMEX). Ground truth data for verifying results from the technique include IWC from National Weather Service and COHMEX radiosondes, the Multispectral Atmospheric Mapping Sensor (MAMS), and a special set of VAS soundings (12 channel) using an independent retrieval method. Results from the test case show reasonable accuracy with the root-mean-square errors as low as ±3.8 mm. On the 19 June case study day IWC analyses depict reasonable gradients and exhibit good spatial and temporal continuity. Furthermore, they provide insight into preferred regions for cumulus cloud and thunderstorm formation. On the average, a mean absolute retrieval error of 2.4 mm (an 8.1% error) and a root-mean-square error of ±2.9 mm are obtained on the case study day. These results compare favorably with those from existing VAS IWC techniques. Overall, the findings indicate that the technique has excellent potential to depict mesoscale moisture variations.

Abstract

The Advanced Regional Prediction System is used to perform a three-dimensional numerical simulation of land–water circulations near Cape Canaveral, Florida. Three two-way nested grids having spacings of 1.6, 0.4, and 0.1 km are employed. Results show that the structures of both the sea and river breezes compare well with observation and theory.

Horizontal convective rolls (HCRs), Kelvin–Helmholtz instability (KHI), and their interactions with the sea and river breezes also are investigated. HCRs form over the heated land surface at periodic intervals. The HCRs have two preferred spatial scales: large and small. Inclusion of both the large and small HCRs yields aspect ratios that are smaller than most previous observations. However, when considering only the larger HCRs, agreement is better. The smaller HCRs eventually dissipate or merge with their larger HCR counterparts. These mergers intensify the vertical motion within the larger circulations.

The HCRs are observed to tilt upward in advance of the Indian River breeze (IRB), and then advect over and behind the land–water circulation. There is evidence that an HCR advects 2.5 km behind the surface front. The orientation of the IRB causes its interaction with an HCR to change from an intersection to a merger. This produces positive vertical vorticity that causes the IRB to rotate counterclockwise. The detailed physiography and surface characteristics used in this research allow these complex asymmetric interactions to be simulated.

In addition, the configuration of this simulation allows an even smaller-scale feature, KHI, to be observed on top of and behind the Indian River breeze front. It appears as vortices or billows that grow in amplitude and propagate backward relative to the front. The structure of the billows agrees well with previous theoretical and modeling results. Local regions of upward motion associated with the billows may be a preferred area for postfrontal convection.

Abstract

Mesoscale surface data and special satellite-derived soundings from the Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) are used to investigate a case of sudden mesoscale drying at the surface on 17 June 1986, a day during the Cooperative Huntsville Meteorological Experiment (COHMEX). Dewpoints fall as much as −6.3°C in less than 1 h over a small portion of central Tennessee. The drying occurs prior to the onset of convective activity. The satellite retrievals detect a narrow tongue of midtropospheric dry air that overlays moist air near the surface. The analyses indicate that heating-induced surface-based mixing penetrates the midlevels, bringing drier air to the surface and resulting in the sudden decreases in surface dewpoints.