DOCSLIB.ORG

Mesoscale Convective Patterns of the Southern High Plains

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mesoscale Convective Patterns of the Southern High Plains David Blanchard Mesoscale Convective Patterns NOAA/NSSL/Mesoscale Researc° h Division of the Southern High Plains Boulder, Colorado 80303 Abstract (Cunning 1986) indicate that there is, in fact, a broad spectrum of internal structural characteristics associ- Mesoscale convective systems observed in the southern High ated with MCSs. As part of the program, high-density Plains during the Oklahoma-Kansas Preliminary Regional Experi- upper-air soundings, satellite imagery, aircraft obser- ment for STORM-central (PRE-STORM) field program were ana- vations, high-density automated surface observa- lyzed using radar and rawinsonde data. Although radar data indicate that no two systems are identical, basic recurring meso- tions, and both conventional National Weather scale structures are evident. Based on these recurrent features, the Service (NWS) WSR-57 radar data and special Dop- systems have been classified into three types of mesoscale con- pler-radar data were collected (figure 1). Specifically, vective patterns: linear mesoscale systems, occluding mesoscale radar data indicate that several mesoscale patterns of systems, and chaotic mesoscale systems. Examples of all three types are discussed. High-density rawinsonde data collected in the convection are associated with MCSs. These include regions ahead of the mesoscale systems have been averaged to squall lines with leading or trailing stratiform precip- produce composite soundings; the composites exhibit differences itation, chaotic convective systems, mesoscale occlu- in both thermodynamic and wind structure between types. sions, and frontal bands. Digital and photographic data from the NWS WSR-57 radars were analyzed, and radar-observed convection within MCSs that 1. Introduction were within or near the PRE-STORM area was clas- sified according to these mesoscale patterns, to be The development of nocturnal mesoscale convective described in detail here. From this initial classifica- systems (MCSs) has been shown to be a function of tion, the relative frequencies of each pattern of meso- both large-scale synoptic patterns and terrain-in- scale convection were determined. duced features, such as elevated heat sources (Mad- Other classification schemes have been presented dox 1980; Cotton et al. 1983; Tripoli and Cotton in the literature. Bluestein and Jain (1985) and Blue- 1989). Using objective analysis and compositing stein et al. (1987) classified radar-observed types of techniques for ten mesoscale convective complexes severe and nonsevere squall-line formation that occur (MCCs), a subset of MCSs, Maddox (1983) identified in Oklahoma during the spring, and related each type several distinctive features at the surface and in the of squall line to a composite environmental sounding lower, middle, and upper troposphere during the for- and to the synoptic environment. Houze et al. (1990) mation, maturation, and dissipation stages of MCCs. presented a classification of mesoscale convection Classification as an MCC was based on characteris- associated with springtime rainstorms (i.e., at least tics observable in satellite imagery because of the 25 mm of rain in 24 h over an area exceeding 12 500 wide range of atmospheric scales that could be mon- km2) in Oklahoma. These classifications are derived itored, but did not address internal structural char- from a single radar and focus on Oklahoma. Houze acteristics. More recently, Cotton et al. (1989), using et al. (1989) discussed the interpretation of radar data compositing techniques that permit greater temporal from single- and multiple-Doppler radars during PRE- resolution, examined 134 MCC events. Their results STORM in Kansas and included a conceptual model are similar to those of Maddox, but are more detailed of the observed variations of linear mesoscale con- regarding the temporal evolution of the system. Like vection. The classification system presented here is Maddox, however, Cotton et al. did not directly ad- more general and includes all types of MCSs over dress the question of variable structures within the both Oklahoma and Kansas during their entire life- MCCs. times. It addresses the problem of identifying radar- MCCs. observed mesoscale patterns of convection on a Data collected in the southern High Plains during larger temporal and spatial scale than that of Blue- the Oklahoma-Kansas Preliminary Regional Experi- stein and Jain (1985), Bluestein et al. (1987), and ment for STORM-central (PRE-STORM) field program Houze et al. (1989, 1990), and smaller-scale internal structures than those identified by Maddox (1983) © 1990 American Meteorological Society and Cotton et al. (1989). 994 Vol. 71, No. 7, July 1990 Unauthenticated | Downloaded 10/10/21 10:14 PM UTC Bulletin American Meteorological Society 995 2. Data sources a. Radar data The first step in viewing and analyzing the radar data involved using standard 16-mm film of the radar- scope. Radar-observed mesoscale patterns of con- vection and motions were documented for each day when MCSs were present within the range of the ra- dar. All 61 days of May and June, for both the Okla- homa City, Oklahoma (OKC), and Wichita, Kansas (ICT), radar sites were examined. Nearby sites (Amar- illo, Texas [AMA], Garden City, Kansas [GCK], and Kansas City, Missouri [MCI]) were used when the OKC or ICT radars were not available, or when the MCS was partially beyond the range of the two sites. Detailed examination and comparison of the meso- scale echo patterns were accomplished by compos- iting digital-radar data. The composite radar data provided a large-scale overview of the mesoscale convection that could not be obtained from a single radar. NWS radar-data processor (RADAP II) (Greene FIG. 1. Location of the PRE-STORM field program and et al. 1983) data were available from several NWS placement of the observational network. WSR-57 radar sites within and adjacent to the PRE- STORM experimental network and consisted of dig- included plotting thermodynamic diagrams and time- itized radar reflectivity from volume scans taken height cross sections of potential temperature and every 10-20 min. These digitized data have a spatial winds, and the objective and subjective analyses of resolution of 2° azimuthally and 1.85 km (1 n mi) numerous parameters on constant pressure levels. radially. Digitized radar data were also recorded by With these analyses, bad data were detected and cor- the NOAA/Hurricane Research Division (HRD) at the rected or deleted when not correctable. ICT radar site; these data had a resolution of 2° azi- The soundings were divided into groups corre- muthally and —0.9 km (0.5 n mi) radially. These sponding to the various types of mesoscale organi- higher-resolution data were used when available, zation of convection within the MCS. Soundings that and the ICT RADAP II data were used at other times. were not representative of the ambient conditions The NWS operated another radar digitizer at MCI ahead of the MCS were not used. The soundings were with resolution similar to the HRD digitizer. The data interpolated to levels spaced 25 mb apart from the from both digitizers had more quantization intervals surface to 100 mb; surface data were not changed. and finer resolution than the RADAP II data. There were occasional instances when the reflectivity val- Finally, soundings were averaged to determine mean ues at the boundary between adjacent radars did not thermodynamic and wind properties for each meso- match, owing to attenuation, distance, different cal- scale convective pattern type. ibrations, or nonstandard beam propagation; but in most cases the boundaries matched satisfactorily. De- spite these occasional problems, no reflectivity data 3. Classification of mesoscale were rejected because the data were used in a qual- convective patterns itative instead of quantitative manner (i.e., the pri- mary goal was to ascertain the radar-echo pattern). During the PRE-STORM field program, MCSs oc- b. Rawinsonde data curred within the region on 21 days. These MCSs To address the environmental conditions supporting exhibited a variety of different spatial characteristics, the different mesoscale patterns of convection, spe- but can be broadly classified into three basic patterns cial high-density PRE-STORM and NWS soundings of mesoscale convection illustrated schematically in were examined. PRE-STORM soundings were taken figure 2. Table 1 shows the number of events for each every 3 h, and occasionally as often as every 1.5 h. pattern of mesoscale convection observed during the Locations of the sounding sites are shown in figure 1; PRE-STORM field program. Some days experienced station spacing averaged approximately 200 km. more than one MCS, so there was a total of 25 MCS Data checks were performed on all soundings and events. Table 2 lists all the days during PRE-STORM Unauthenticated | Downloaded 10/10/21 10:14 PM UTC 996 Vol. 71, No. 7, July 7 990 TABLE 1: Frequency of occurrence of the different convective patterns observed during the PRE-STORM field program. Convective pattern Cases Percent Linear 17 68 Occluding 2 8 Chaotic 6 24 convection occurred with approximately equal fre- quencies; there were ten meso-a- and seven meso- p-scale events. Figures 2a-c show a typical devel- opment of echoes into a linear structure and, finally, into a mature system having a region of trailing stra- tiform precipitation and a "reflectivity trough" or "transition" region located between the stratiform precipitation and the leading line of convection (Sommeria and Testud 1984; Smull
Load more

Recommended publications
  • A Study of Synoptic-Scale Tornado Regimes
    Garner, J. M., 2013: A study of synoptic-scale tornado regimes. Electronic J. Severe Storms Meteor., 8 (3), 1–25. A Study of Synoptic-Scale Tornado Regimes JONATHAN M. GARNER NOAA/NWS/Storm Prediction Center, Norman, OK (Submitted 21 November 2012; in final form 06 August 2013) ABSTRACT The significant tornado parameter (STP) has been used by severe-thunderstorm forecasters since 2003 to identify environments favoring development of strong to violent tornadoes. The STP and its individual components of mixed-layer (ML) CAPE, 0–6-km bulk wind difference (BWD), 0–1-km storm-relative helicity (SRH), and ML lifted condensation level (LCL) have been calculated here using archived surface objective analysis data, and then examined during the period 2003−2010 over the central and eastern United States. These components then were compared and contrasted in order to distinguish between environmental characteristics analyzed for three different synoptic-cyclone regimes that produced significantly tornadic supercells: cold fronts, warm fronts, and drylines. Results show that MLCAPE contributes strongly to the dryline significant-tornado environment, while it was less pronounced in cold- frontal significant-tornado regimes. The 0–6-km BWD was found to contribute equally to all three significant tornado regimes, while 0–1-km SRH more strongly contributed to the cold-frontal significant- tornado environment than for the warm-frontal and dryline regimes. –––––––––––––––––––––––– 1. Background and motivation As detailed in Hobbs et al. (1996), synoptic- scale cyclones that foster tornado development Parameter-based and pattern-recognition evolve with time as they emerge over the central forecast techniques have been essential and eastern contiguous United States (hereafter, components of anticipating tornadoes in the CONUS).
    [Show full text]
  • Weather Charts Natural History Museum of Utah – Nature Unleashed Stefan Brems
    Weather Charts Natural History Museum of Utah – Nature Unleashed Stefan Brems Across the world, many different charts of different formats are used by different governments. These charts can be anything from a simple prognostic chart, used to convey weather forecasts in a simple to read visual manner to the much more complex Wind and Temperature charts used by meteorologists and pilots to determine current and forecast weather conditions at high altitudes. When used properly these charts can be the key to accurately determining the weather conditions in the near future. This Write-Up will provide a brief introduction to several common types of charts. Prognostic Charts To the untrained eye, this chart looks like a strange piece of modern art that an angry mathematician scribbled numbers on. However, this chart is an extremely important resource when evaluating the movement of weather fronts and pressure areas. Fronts Depicted on the chart are weather front combined into four categories; Warm Fronts, Cold Fronts, Stationary Fronts and Occluded Fronts. Warm fronts are depicted by red line with red semi-circles covering one edge. The front movement is indicated by the direction the semi- circles are pointing. The front follows the Semi-Circles. Since the example above has the semi-circles on the top, the front would be indicated as moving up. Cold fronts are depicted as a blue line with blue triangles along one side. Like warm fronts, the direction in which the blue triangles are pointing dictates the direction of the cold front. Stationary fronts are frontal systems which have stalled and are no longer moving.
    [Show full text]
  • The Lagrange Torando During Vortex2. Part Ii: Photogrammetry Analysis of the Tornado Combined with Dual-Doppler Radar Data
    6.3 THE LAGRANGE TORANDO DURING VORTEX2. PART II: PHOTOGRAMMETRY ANALYSIS OF THE TORNADO COMBINED WITH DUAL-DOPPLER RADAR DATA Nolan T. Atkins*, Roger M. Wakimoto#, Anthony McGee*, Rachel Ducharme*, and Joshua Wurman+ *Lyndon State College #National Center for Atmospheric Research +Center for Severe Weather Research Lyndonville, VT 05851 Boulder, CO 80305 Boulder, CO 80305 1. INTRODUCTION studies, however, that have related the velocity and reflectivity features observed in the radar data to Over the years, mobile ground-based and air- the visual characteristics of the condensation fun- borne Doppler radars have collected high-resolu- nel, debris cloud, and attendant surface damage tion data within the hook region of supercell (e.g., Bluestein et al. 1993, 1197, 204, 2007a&b; thunderstorms (e.g., Bluestein et al. 1993, 1997, Wakimoto et al. 2003; Rasmussen and Straka 2004, 2007a&b; Wurman and Gill 2000; Alexander 2007). and Wurman 2005; Wurman et al. 2007b&c). This paper is the second in a series that pre- These studies have revealed details of the low- sents analyses of a tornado that formed near level winds in and around tornadoes along with LaGrange, WY on 5 June 2009 during the Verifica- radar reflectivity features such as weak echo holes tion on the Origins of Rotation in Tornadoes Exper- and multiple high-reflectivity rings. There are few iment (VORTEX 2). VORTEX 2 (Wurman et al. 5 June, 2009 KCYS 88D 2002 UTC 2102 UTC 2202 UTC dBZ - 0.5° 100 Chugwater 100 50 75 Chugwater 75 330° 25 Goshen Co. 25 km 300° 50 Goshen Co. 25 60° KCYS 30° 30° 50 80 270° 10 25 40 55 dBZ 70 -45 -30 -15 0 15 30 45 ms-1 Fig.
    [Show full text]
  • Squall Lines: Meteorology, Skywarn Spotting, & a Brief Look at the 18
    Squall Lines: Meteorology, Skywarn Spotting, & A Brief Look At The 18 June 2010 Derecho Gino Izzi National Weather Service, Chicago IL Outline • Meteorology 301: Squall lines – Brief review of thunderstorm basics – Squall lines – Squall line tornadoes – Mesovorticies • Storm spotting for squall lines • Brief Case Study of 18 June 2010 Event Thunderstorm Ingredients • Moisture – Gulf of Mexico most common source locally Thunderstorm Ingredients • Lifting Mechanism(s) – Fronts – Jet Streams – “other” boundaries – topography Thunderstorm Ingredients • Instability – Measure of potential for air to accelerate upward – CAPE: common variable used to quantify magnitude of instability < 1000: weak 1000-2000: moderate 2000-4000: strong 4000+: extreme Thunderstorms Thunderstorms • Moisture + Instability + Lift = Thunderstorms • What kind of thunderstorms? – Single Cell – Multicell/Squall Line – Supercells Thunderstorm Types • What determines T-storm Type? – Short/simplistic answer: CAPE vs Shear Thunderstorm Types • What determines T-storm Type? (Longer/more complex answer) – Lot we don’t know, other factors (besides CAPE/shear) include • Strength of forcing • Strength of CAP • Shear WRT to boundary • Other stuff Thunderstorm Types • Multi-cell squall lines most common type of severe thunderstorm type locally • Most common type of severe weather is damaging winds • Hail and brief tornadoes can occur with most the intense squall lines Squall Lines & Spotting Squall Line Terminology • Squall Line : a relatively narrow line of thunderstorms, often
    [Show full text]
  • NWS Unified Surface Analysis Manual
    Unified Surface Analysis Manual Weather Prediction Center Ocean Prediction Center National Hurricane Center Honolulu Forecast Office November 21, 2013 Table of Contents Chapter 1: Surface Analysis – Its History at the Analysis Centers…………….3 Chapter 2: Datasets available for creation of the Unified Analysis………...…..5 Chapter 3: The Unified Surface Analysis and related features.……….……….19 Chapter 4: Creation/Merging of the Unified Surface Analysis………….……..24 Chapter 5: Bibliography………………………………………………….…….30 Appendix A: Unified Graphics Legend showing Ocean Center symbols.….…33 2 Chapter 1: Surface Analysis – Its History at the Analysis Centers 1. INTRODUCTION Since 1942, surface analyses produced by several different offices within the U.S. Weather Bureau (USWB) and the National Oceanic and Atmospheric Administration’s (NOAA’s) National Weather Service (NWS) were generally based on the Norwegian Cyclone Model (Bjerknes 1919) over land, and in recent decades, the Shapiro-Keyser Model over the mid-latitudes of the ocean. The graphic below shows a typical evolution according to both models of cyclone development. Conceptual models of cyclone evolution showing lower-tropospheric (e.g., 850-hPa) geopotential height and fronts (top), and lower-tropospheric potential temperature (bottom). (a) Norwegian cyclone model: (I) incipient frontal cyclone, (II) and (III) narrowing warm sector, (IV) occlusion; (b) Shapiro–Keyser cyclone model: (I) incipient frontal cyclone, (II) frontal fracture, (III) frontal T-bone and bent-back front, (IV) frontal T-bone and warm seclusion. Panel (b) is adapted from Shapiro and Keyser (1990) , their FIG. 10.27 ) to enhance the zonal elongation of the cyclone and fronts and to reflect the continued existence of the frontal T-bone in stage IV.
    [Show full text]
  • December 2013
    Oklahoma Monthly Climate Summary DECEMBER 2013 A frigid and sometimes icy December seemed a fitting way to 1.53 inches, about a half-inch below normal, to rank as the close out the boisterous weather of 2013. Preliminary data from 59th wettest December on record. That total is possibly an the Oklahoma Mesonet ranked the month as the 17th coolest underestimate due to the frozen precipitation, although the December on record at nearly 4 degrees below normal. Records moisture pattern across various parts of the state was quite of this type for Oklahoma date back to 1895. The statewide clear. Far southeastern Oklahoma received from 3-5 inches average temperature as recorded by the Mesonet was 35.2 during the month while western areas of the state received degrees. As chilly as it seemed, however, that mark provided less than a half-inch, in general. little threat to 1983’s record cold of 25.8 degrees, but also far cooler than 2012’s 42.1 degrees. There were two significant The cold December propelled 2013’s statewide average winter storms during December, each creating headaches for annual temperature to a mark of 58.9 degrees, 0.8 degrees travelers and power utility companies. The first storm struck on below normal and the 27th coolest calendar year on record for December 5-6 in two separate waves and brought freezing rain, the state. That mark stands in stark contrast to 2012’s record sleet and snow across the state. Significant snow totals of 5-6 warm year of 63.1 degrees.
    [Show full text]
  • Meteorology – Lecture 19
    Meteorology – Lecture 19 Robert Fovell [email protected] 1 Important notes • These slides show some figures and videos prepared by Robert G. Fovell (RGF) for his “Meteorology” course, published by The Great Courses (TGC). Unless otherwise identified, they were created by RGF. • In some cases, the figures employed in the course video are different from what I present here, but these were the figures I provided to TGC at the time the course was taped. • These figures are intended to supplement the videos, in order to facilitate understanding of the concepts discussed in the course. These slide shows cannot, and are not intended to, replace the course itself and are not expected to be understandable in isolation. • Accordingly, these presentations do not represent a summary of each lecture, and neither do they contain each lecture’s full content. 2 Animations linked in the PowerPoint version of these slides may also be found here: http://people.atmos.ucla.edu/fovell/meteo/ 3 Mesoscale convective systems (MCSs) and drylines 4 This map shows a dryline that formed in Texas during April 2000. The dryline is indicated by unfilled half-circles in orange, pointing at the more moist air. We see little T contrast but very large TD change. Dew points drop from 68F to 29F -- huge decrease in humidity 5 Animation 6 Supercell thunderstorms 7 The secret ingredient for supercells is large amounts of vertical wind shear. CAPE is necessary but sufficient shear is essential. It is shear that makes the difference between an ordinary multicellular thunderstorm and the rotating supercell. The shear implies rotation.
    [Show full text]
  • Coniglio Et Al. (2006)
    P1.30 FORECASTING THE SPEED AND LONGEVITY OF SEVERE MESOSCALE CONVECTIVE SYSTEMS Michael C. Coniglio∗1 and Stephen F. Corfidi2 1NOAA/National Severe Storms Laboratory, Norman, OK 2NOAA/Storm Prediction Center, Norman, OK 1. INTRODUCTION b. MCS maintenance Forecasting the details of mesoscale convective Predicting MCS maintenance is fraught with systems (MCSs) (Zipser 1982) continues to be a difficult challenges such as understanding how deep convection problem. Recent advances in numerical weather is sustained through system/environment interactions prediction models and computing power have allowed (Weisman and Rotunno 2004, Coniglio et al. 2004b, for explicit real-time prediction of MCSs over the past Coniglio et al. 2005), how pre-existing mesoscale few years, some of which have supported field features influence the system (Fritsch and Forbes 2001, programs (Davis et al. 2004) and collaborative Trier and Davis 2005), and how the disturbances experiments between researchers and forecasters at generated by the system itself can alter the system the Storm Prediction Center (SPC) (Kain et al. 2005). structure and longevity (Parker and Johnson 2004c). While these numerical forecasts of MCSs are promising, the utility of these forecasts and how to best use the From an observational perspective, Evans and capabilities of the high-resolution models in support of Doswell (2001) suggest that the strength of the mean operations is unclear, especially from the perspective of wind (0-6 km) and its effects on cold pool development the Storm Prediction Center (SPC) (Kain et al. 2005). and MCS motion play a significant role in sustaining Therefore, refining our knowledge of the interactions of long-lived forward-propagating MCSs that produce MCSs with their environment remains central to damaging surface winds (derechos) through modifying advancing our near-term ability to forecast MCSs.
    [Show full text]
  • The Evolution of the 10–11 June 1985 PRE-STORM Squall Line: Initiation
    478 MONTHLY WEATHER REVIEW VOLUME 125 The Evolution of the 10±11 June 1985 PRE-STORM Squall Line: Initiation, Development of Rear In¯ow, and Dissipation SCOTT A. BRAUN AND ROBERT A. HOUZE JR. Department of Atmospheric Sciences, University of Washington, Seattle, Washington (Manuscript received 12 December 1995, in ®nal form 12 August 1996) ABSTRACT Mesoscale analysis of surface observations and mesoscale modeling results show that the 10±11 June squall line, contrary to prior studies, did not form entirely ahead of a cold front. The primary environmental features leading to the initiation and organization of the squall line were a low-level trough in the lee of the Rocky Mountains and a midlevel short-wave trough. Three additional mechanisms were active: a southeastward-moving cold front formed the northern part of the line, convection along the edge of cold air from prior convection over Oklahoma and Kansas formed the central part of the line, and convection forced by convective out¯ow near the lee trough axis formed the southern portion of the line. Mesoscale model results show that the large-scale environment signi®cantly in¯uenced the mesoscale cir- culations associated with the squall line. The qualitative distribution of along-line velocities within the squall line is attributed to the larger-scale circulations associated with the lee trough and midlevel baroclinic wave. Ambient rear-to-front (RTF) ¯ow to the rear of the squall line, produced by the squall line's nearly perpendicular orientation to strong westerly ¯ow at upper levels, contributed to the exceptional strength of the rear in¯ow in this storm.
    [Show full text]
  • A 10-Year Radar-Based Climatology of Mesoscale Convective System Archetypes and Derechos in Poland
    AUGUST 2020 S U R O W I E C K I A N D T A S Z A R E K 3471 A 10-Year Radar-Based Climatology of Mesoscale Convective System Archetypes and Derechos in Poland ARTUR SUROWIECKI Department of Climatology, University of Warsaw, and Skywarn Poland, Warsaw, Poland MATEUSZ TASZAREK Department of Meteorology and Climatology, Adam Mickiewicz University, Poznan, Poland, and National Severe Storms Laboratory, Norman, Oklahoma, and Skywarn Poland, Warsaw, Poland (Manuscript received 29 December 2019, in final form 3 May 2020) ABSTRACT In this study, a 10-yr (2008–17) radar-based mesoscale convective system (MCS) and derecho climatology for Poland is presented. This is one of the first attempts of a European country to investigate morphological and precipitation archetypes of MCSs as prior studies were mostly based on satellite data. Despite its ubiquity and significance for society, economy, agriculture, and water availability, little is known about the climatological aspects of MCSs over central Europe. Our results indicate that MCSs are not rare in Poland as an annual mean of 77 MCSs and 49 days with MCS can be depicted for Poland. Their lifetime ranges typically from 3 to 6 h, with initiation time around the afternoon hours (1200–1400 UTC) and dissipation stage in the evening (1900–2000 UTC). The most frequent morphological type of MCSs is a broken line (58% of cases), then areal/cluster (25%), and then quasi- linear convective systems (QLCS; 17%), which are usually associated with a bow echo (72% of QLCS). QLCS are the feature with the longest life cycle.
    [Show full text]
  • ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
    ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere.
    [Show full text]
  • Tropical Cyclone Mesoscale Circulation Families
    DOMINANT TROPICAL CYCLONE OUTER RAINBANDS RELATED TO TORNADIC AND NON-TORNADIC MESOSCALE CIRCULATION FAMILIES Scott M. Spratt and David W. Sharp National Weather Service Melbourne, Florida 1. INTRODUCTION Doppler (WSR-88D) radar sampling of Tropical Cyclone (TC) outer rainbands over recent years has revealed a multitude of embedded mesoscale circulations (e.g. Zubrick and Belville 1993, Cammarata et al. 1996, Spratt el al. 1997, Cobb and Stuart 1998). While a majority of the observed circulations exhibited small horizontal and vertical characteristics similar to extra- tropical mini supercells (Burgess et al. 1995, Grant and Prentice 1996), some were more typical of those common to the Great Plains region (Sharp et al. 1997). During the past year, McCaul and Weisman (1998) successfully simulated the observed spectrum of TC circulations through variance of buoyancy and shear parameters. This poster will serve to document mesoscale circulation families associated with six TC's which made landfall within Florida since 1994. While tornadoes were not associated with all of the circulations (manual not algorithm defined), those which exhibited persistent and relatively strong rotation did often correlate with touchdowns (Table 1). Similarities between tornado- producing circulations will be discussed in Section 7. Contained within this document are 0.5 degree base reflectivity and storm relative velocity images from the Melbourne (KMLB; Gordon, Erin, Josephine, Georges), Jacksonville (KJAX; Allison), and Eglin Air Force Base (KEVX; Opal) WSR-88D sites. Arrows on the images indicate cells which produced persistent rotation. 2. TC GORDON (94) MESO CHARACTERISTICS KMLB radar surveillance of TC Gordon revealed two occurrences of mesoscale families (first period not shown).
    [Show full text]