Low Richardson Number in the Tropical Cyclone Outflow Layer
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												  The Generation of a Mesoscale Convective System from Mountain ConvectionJUNE 1999 TUCKER AND CROOK 1259 The Generation of a Mesoscale Convective System from Mountain Convection DONNA F. T UCKER Department of Physics and Astronomy, University of Kansas, Lawrence, Kansas N. ANDREW CROOK National Center for Atmospheric Research Boulder, Colorado (Manuscript received 18 November 1997, in ®nal form 13 July 1998) ABSTRACT A mesoscale convective system (MCS) that formed just to the east of Denver is investigated with a nonhy- drostatic numerical model to determine which processes were important in its initiation. The MCS developed from out¯ow from previous convective activity in the Rocky Mountains to the west. Model results indicate that this out¯ow was necessary for the development of the MCS even though a convergence line was already present in the area where the MCS developed. A simulation with a 3-km grid spacing more fully resolves the convective activity in the mountains but the development of the MCS can be simulated with a 6.67-km grid. Cloud effects on solar radiation and ice sedimentation both in¯uence the strength of the out¯ow from the mountain convection but only the ice sedimentation makes a signi®cant impact on the development of the MCS after its initiation. The frequent convective activity in the Rocky Mountains during the warm season provides out¯ow that would make MCS generation favorable in this region. Thus, there is a close connection between mountain convective activity and MCS generation. The implications of such a connection are discussed and possible directions of future research are indicated. 1. Introduction scale or mesoscale. Forced lifting always occurs on the windward side of mountains; however, the mechanisms Mesoscale convective systems (MCSs) commonly de- that promote lifting on the downwind side of mountains, velop in the central United States during the warm sea- where a large proportion of MCSs initiate, are not as son, accounting for 30%±70% of the summer precipi- obvious.
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												  The Impact of Outflow Environment on Tropical Cyclone Intensification AndVOLUME 68 JOURNAL OF THE ATMOSPHERIC SCIENCES FEBRUARY 2011 The Impact of Outflow Environment on Tropical Cyclone Intensification and Structure ERIC D. RAPPIN Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, Miami, Florida MICHAEL C. MORGAN AND GREGORY J. TRIPOLI University of Wisconsin—Madison, Madison, Wisconsin (Manuscript received 3 October 2008, in final form 5 June 2009) ABSTRACT In this study, the impacts of regions of weak inertial stability on tropical cyclone intensification and peak strength are examined. It is demonstrated that weak inertial stability in the outflow layer minimizes an energy sink of the tropical cyclone secondary circulation and leads to more rapid intensification to the maximum potential intensity. Using a full-physics, three-dimensional numerical weather prediction model, a symmetric distribution of environmental inertial stability is generated using a variable Coriolis parameter. It is found that the lower the value of the Coriolis parameter, the more rapid the strengthening. The lower-latitude simulation is shown to have a significantly stronger secondary circulation with intense divergent outflow against a com- paratively weak environmental resistance. However, the impacts of differences in the gradient wind balance between the different latitudes on the core structure cannot be neglected. A second study is then conducted using an asymmetric inertial stability distribution generated by the presence of a jet stream to the north of the tropical cyclone. The initial intensification is similar, or even perhaps slower, in the presence of the jet as a result of increased vertical wind shear. As the system evolves, convective outflow from the tropical cyclone modifies the jet resulting in weaker shear and more rapid intensification of the tropical cyclone–jet couplet.
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												  An Observational Analysis Quantifying the Distance of Supercell-Boundary Interactions in the Great PlainsMagee, K. M., and C. E. Davenport, 2020: An observational analysis quantifying the distance of supercell-boundary interactions in the Great Plains. J. Operational Meteor., 8 (2), 15-38, doi: https://doi.org/10.15191/nwajom.2020.0802 An Observational Analysis Quantifying the Distance of Supercell-Boundary Interactions in the Great Plains KATHLEEN M. MAGEE National Weather Service Huntsville, Huntsville, AL CASEY E. DAVENPORT University of North Carolina at Charlotte, Charlotte, NC (Manuscript received 11 June 2019; review completed 7 October 2019) ABSTRACT Several case studies and numerical simulations have hypothesized that baroclinic boundaries provide enhanced horizontal and vertical vorticity, wind shear, helicity, and moisture that induce stronger updrafts, higher reflectivity, and stronger low-level rotation in supercells. However, the distance at which a surface boundary will provide such enhancement is less well-defined. Previous studies have identified enhancement at distances ranging from 10 km to 200 km, and only focused on tornado production and intensity, rather than all forms of severe weather. To better aid short-term forecasts, the observed distances at which supercells produce severe weather in proximity to a boundary needs to be assessed. In this study, the distance between a large number of observed supercells and nearby surface boundaries (including warm fronts, stationary fronts, and outflow boundaries) is measured throughout the lifetime of each storm; the distance at which associated reports of large hail and tornadoes occur is also collected. Statistical analyses assess the sensitivity of report distributions to report type, boundary type, boundary strength, angle of interaction, and direction of storm motion relative to the boundary.
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												  Laboratory Studies of Turbulent Mixing J.ALaboratory Studies of Turbulent Mixing J.A. Whitehead Woods Hole Oceanographic Institution, Woods Hole, MA, USA Laboratory measurements are required to determine the rates of turbulent mixing and dissipation within flows of stratified fluid. Rates based on other methods (theory, numerical approaches, and direct ocean measurements) require models based on assumptions that are suggested, but not thoroughly verified in the laboratory. An exception to all this is recently provided by direct numerical simulations (DNS) mentioned near the end of this article. Experiments have been conducted with many different devices. Results span a wide range of gradient or bulk Richardson number and more limited ranges of Reynolds number and Schmidt number, which are the three most relevant dimensionless numbers. Both layered and continuously stratified flows have been investigated, and velocity profiles include smooth ones, jets, and clusters of eddies from stirrers or grids. The dependence of dissipation through almost all ranges of Richardson number is extensively documented. The buoyancy flux ratio is the turbulent kinetic energy loss from raising the potential energy of the strata to loss of kinetic energy by viscous dissipation. It rises from zero at small Richardson number to values of about 0.1 at Richardson number equal to 1, and then falls off for greater values. At Richardson number greater than 1, a wide range of power laws spanning the range from −0.5 to −1.5 are found to fit data for different experiments. Considerable layering is found at larger values, which causes flux clustering and may explain both the relatively large scatter in the data as well as the wide range of proposed power laws.
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												  Quantifying the Impact of Synoptic Weather Types and Patterns On1 Quantifying the impact of synoptic weather types and patterns 2 on energy fluxes of a marginal snowpack 3 Andrew Schwartz1, Hamish McGowan1, Alison Theobald2, Nik Callow3 4 1Atmospheric Observations Research Group, University of Queensland, Brisbane, 4072, Australia 5 2Department of Environment and Science, Queensland Government, Brisbane, 4000, Australia 6 3School of Agriculture and Environment, University of Western Australia, Perth, 6009, Australia 7 8 Correspondence to: Andrew J. Schwartz ([email protected]) 9 10 Abstract. 11 Synoptic weather patterns are investigated for their impact on energy fluxes driving melt of a marginal snowpack 12 in the Snowy Mountains, southeast Australia. K-means clustering applied to ECMWF ERA-Interim data identified 13 common synoptic types and patterns that were then associated with in-situ snowpack energy flux measurements. 14 The analysis showed that the largest contribution of energy to the snowpack occurred immediately prior to the 15 passage of cold fronts through increased sensible heat flux as a result of warm air advection (WAA) ahead of the 16 front. Shortwave radiation was found to be the dominant control on positive energy fluxes when individual 17 synoptic weather types were examined. As a result, cloud cover related to each synoptic type was shown to be 18 highly influential on the energy fluxes to the snowpack through its reduction of shortwave radiation and 19 reflection/emission of longwave fluxes. As single-site energy balance measurements of the snowpack were used 20 for this study, caution should be exercised before applying the results to the broader Australian Alps region. 21 However, this research is an important step towards understanding changes in surface energy flux as a result of 22 shifts to the global atmospheric circulation as anthropogenic climate change continues to impact marginal winter 23 snowpacks.
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												  Boundary Layer VerificationBoundary Layer Verification ECMWF training course April 2015 Maike Ahlgrimm Aim of this lecture • To give an overview over strategies for boundary layer evaluation • By the end of this session you should be able to: – Identify data sources and products suitable for BL verification – Recognize the strengths and limitations of the verification strategies discussed – Choose a suitable verification method to investigate model errors in boundary layer height, transport and cloudiness. smog over NYC Overview • General strategy for process-oriented model evaluation • What does the BL parameterization do? • Broad categories of BL parameterizations • Which aspects of the BL can we evaluate? – What does each aspect tell us about the BL? • What observations are available – What are the observations’ advantages and limitations? • Examples – Clear convective BL – Cloud topped convective BL – Stable BL Basic strategy for model evaluation and improvement: Observations Identify discrepancy Model Output Figure out source of model error Improve parameterization When and where does error occur? Which parameterization(s) is/are involved? What does the BL parameterization do? Attempts to integrate Turbulence transports effects of small scale temperature, moisture and turbulent motion on momentum (+tracers). prognostic variables at grid resolution. Stull 1988 Ultimate goal: good model forecast and realistic BL Broad categories of BL parameterizations Unified BL schemes Specialized BL scheme •Attempt to integrate BL (and •One parameterization for each shallow cloud) effects in one discrete BL type scheme to allow seamless transition •Simplifies parameterization for •Often statistical schemes (i.e. each type, parameterization for making explicit assumptions about each type ideally suited PDFs of modelled variables) using •Limitation: must identify BL type moist-conserved variables reliably, is noisy (lots of if •Limitation: May not work well for statements) mixed-phase or ice •Example: Met-Office (Lock et al.
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												  On the Computation of Planetary Boundary-Layer Height Using the Bulk Richardson Number MethodGeosci. Model Dev., 7, 2599–2611, 2014 www.geosci-model-dev.net/7/2599/2014/ doi:10.5194/gmd-7-2599-2014 © Author(s) 2014. CC Attribution 3.0 License. On the computation of planetary boundary-layer height using the bulk Richardson number method Y. Zhang1, Z. Gao2, D. Li3, Y. Li1, N. Zhang4, X. Zhao1, and J. Chen1,5 1International Center for Ecology, Meteorology & Environment, Jiangsu Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China 2State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China 3Program of Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ 08540, USA 4School of Atmospheric Sciences, Nanjing University, Nanjing, 210093, China 5Department of Geography, Michigan State University, East Lansing, MI 48824, USA Correspondence to: Z. Gao ([email protected]) Received: 15 March 2014 – Published in Geosci. Model Dev. Discuss.: 24 June 2014 Revised: 12 September 2014 – Accepted: 22 September 2014 – Published: 10 November 2014 Abstract. Experimental data from four field campaigns are 1 Introduction used to explore the variability of the bulk Richardson num- ber of the entire planetary boundary layer (PBL), Ribc, which The planetary boundary layer (PBL), or the atmospheric is a key parameter for calculating the PBL height (PBLH) boundary layer, is the lowest part of the atmosphere that is in numerical weather and climate models with the bulk directly influenced by earth’s surface and has significant im- Richardson number method. First, the PBLHs of three differ- pacts on weather, climate, and the hydrologic cycle (Stull, ent thermally stratified boundary layers (i.e., strongly stable 1988; Garratt, 1992; Seidel et al., 2010).
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												  Outflow from a Nocturnal ThunderstormState Water Survey Division METEOROLOGY SECTION AT THE UNIVERSITY OF ILLINOIS SWS Contract Report 242 OUTFLOW FROM A NOCTURNAL THUNDERSTORM Robert W. Scott Meteorology Section Illinois State Water Survey Technical Report 3 NSF Grant ATM 78-08865 Low Level Convergence and the Prediction of Convective Precipitation November 1980 Champaign IL 61820 The project "Low-level Convergence and the Prediction of Convective Precipitation" is a coordinated research effort by the State Water Survey Division of the Illinois Institute of Natural Resources, the Off ice of Weather Modification Research in the National Oceanic and Atmospheric Adminis tration, and the Department of Environmental Sciences of the University of Virginia. Support of this research has been provided to the State Water Survey by the Atmospheric Research Section, National Science Founda tion, through grant ATM-78-08865. This award includes funds from the Army Research Office and the Air Force Office of Scientific Research of the Department of Defense. OUTFLOW FROM A NOCTURNAL THUNDERSTORM Robert W. Scott Illinois State Water Survey TABLE OF CONTENTS Page LIST OF FIGURES iii ABSTRACT .. v ACKNOWLEDGMENTS vii INTRODUCTION 1 STORM CONDITIONS 2 METEOROLOGICAL FIELDS IN THE NETWORK 8 DISCUSSION 19 REFERENCES 26 -iii- LIST OF FIGURES Figure Page 1 Synoptic analyses on 8-9 August 1979. a. Surface chart at 1900 CDT on 8 August 1979. b. Surface chart at 0700 CDT on 9 August 1979 3 c. 850-mb chart at 1900 CDT on 8 August 1979. d. 850-mb chart at 0700 CDT on 9 August 1979 4 e. 700-mb chart at 1900 CDT on 8 August 1979.
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												  ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARYESSENTIALS 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.
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												  Basic Features on a Skew-T ChartSkew-T Analysis and Stability Indices to Diagnose Severe Thunderstorm Potential Mteor 417 – Iowa State University – Week 6 Bill Gallus Basic features on a skew-T chart Moist adiabat isotherm Mixing ratio line isobar Dry adiabat Parameters that can be determined on a skew-T chart • Mixing ratio (w)– read from dew point curve • Saturation mixing ratio (ws) – read from Temp curve • Rel. Humidity = w/ws More parameters • Vapor pressure (e) – go from dew point up an isotherm to 622mb and read off the mixing ratio (but treat it as mb instead of g/kg) • Saturation vapor pressure (es)– same as above but start at temperature instead of dew point • Wet Bulb Temperature (Tw)– lift air to saturation (take temperature up dry adiabat and dew point up mixing ratio line until they meet). Then go down a moist adiabat to the starting level • Wet Bulb Potential Temperature (θw) – same as Wet Bulb Temperature but keep descending moist adiabat to 1000 mb More parameters • Potential Temperature (θ) – go down dry adiabat from temperature to 1000 mb • Equivalent Temperature (TE) – lift air to saturation and keep lifting to upper troposphere where dry adiabats and moist adiabats become parallel. Then descend a dry adiabat to the starting level. • Equivalent Potential Temperature (θE) – same as above but descend to 1000 mb. Meaning of some parameters • Wet bulb temperature is the temperature air would be cooled to if if water was evaporated into it. Can be useful for forecasting rain/snow changeover if air is dry when precipitation starts as rain. Can also give
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												  Tropical Cyclone Mesoscale Circulation FamiliesDOMINANT 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).
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												  The Interactions Between a Midlatitude Blocking Anticyclone and Synoptic-Scale Cyclones That Occurred During the Summer Season502 MONTHLY WEATHER REVIEW VOLUME 126 NOTES AND CORRESPONDENCE The Interactions between a Midlatitude Blocking Anticyclone and Synoptic-Scale Cyclones That Occurred during the Summer Season ANTHONY R. LUPO AND PHILLIP J. SMITH Department of Earth and Atmospheric Sciences, Purdue University, West Lafayette, Indiana 20 September 1996 and 2 May 1997 ABSTRACT Using the Goddard Laboratory for Atmospheres Goddard Earth Observing System 5-yr analyses and the Zwack±Okossi equation as the diagnostic tool, the horizontal distribution of the dynamic and thermodynamic forcing processes contributing to the maintenance of a Northern Hemisphere midlatitude blocking anticyclone that occurred during the summer season were examined. During the development of this blocking anticyclone, vorticity advection, supported by temperature advection, forced 500-hPa height rises at the block center. Vorticity advection and vorticity tilting were also consistent contributors to height rises during the entire life cycle. Boundary layer friction, vertical advection of vorticity, and ageostrophic vorticity tendencies (during decay) consistently opposed block development. Additionally, an analysis of this blocking event also showed that upstream precursor surface cyclones were not only important in block development but in block maintenance as well. In partitioning the basic data ®elds into their planetary-scale (P) and synoptic-scale (S) components, 500-hPa height tendencies forced by processes on each scale, as well as by interactions (I) between each scale, were also calculated. Over the lifetime of this blocking event, the S and P processes were most prominent in the blocked region. During the formation of this block, the I component was the largest and most consistent contributor to height rises at the center point.