Principles of Convection I: Buoyancy and CAPE
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A Local Large Hail Probability Equation for Columbia, Sc
EASTERN REGION TECHNICAL ATTACHMENT NO. 98-6 AUGUST, 1998 A LOCAL LARGE HAIL PROBABILITY EQUATION FOR COLUMBIA, SC Mark DeLisi NOAA/National Weather Service Forecast Office West Columbia, SC Editor’s Note: The author’s current affiliation is NWSFO Mt. Holly, NJ. 1. INTRODUCTION Skew-T/Hodograph Analysis and Research Program, or SHARP (Hart and Korotky Billet et al. (1997) derived a successful 1991). The dependent variable, hail diameter probability of large hail (diameter greater than or the absence of hail, was derived from or equal to 0.75 inch) equation as an aid in spotter reports for the CAE warning area from National Weather Service (NWS) severe May, 1995 through September, 1996. There thunderstorm warning operations. Hail of that were 136 cases used to develop the regression diameter or larger requires a severe equation. thunderstorm warning be issued by NWS offices. Shortly thereafter, a Weather The LPLH was verified using 69 spotter Surveillance Radar-1988 Doppler (WSR- reports from the period September, 1996 88D) radar probability of severe hail (POSH) through September, 1997. The POSH was became available for warning operations (Witt verified as well. Verification statistics et al. 1998). This study recreates the steps included the Brier score and the chi-square taken in Billet et al. (1997) to derive a local (32) statistic. probability of large hail equation (LPLH) for the Columbia, SC National Weather Service The goal of this study was to develop an Forecast Office (CAE) warning area, and it objective method to estimate the probability assesses the utility of the LPLH relative to the of large hail for use in forecast operations. -
Heat Advection Processes Leading to El Niño Events As
1 2 Title: 3 Heat advection processes leading to El Niño events as depicted by an ensemble of ocean 4 assimilation products 5 6 Authors: 7 Joan Ballester (1,2), Simona Bordoni (1), Desislava Petrova (2), Xavier Rodó (2,3) 8 9 Affiliations: 10 (1) California Institute of Technology (Caltech), Pasadena, California, United States 11 (2) Institut Català de Ciències del Clima (IC3), Barcelona, Catalonia, Spain 12 (3) Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain 13 14 Corresponding author: 15 Joan Ballester 16 California Institute of Technology (Caltech) 17 1200 E California Blvd, Pasadena, CA 91125, US 18 Mail Code: 131-24 19 Tel.: +1-626-395-8703 20 Email: [email protected] 21 22 Manuscript 23 Submitted to Journal of Climate 24 1 25 26 Abstract 27 28 The oscillatory nature of El Niño-Southern Oscillation results from an intricate 29 superposition of near-equilibrium balances and out-of-phase disequilibrium processes between the 30 ocean and the atmosphere. Several authors have shown that the heat content stored in the equatorial 31 subsurface is key to provide memory to the system. Here we use an ensemble of ocean assimilation 32 products to describe how heat advection is maintained in each dataset during the different stages of 33 the oscillation. 34 Our analyses show that vertical advection due to surface horizontal convergence and 35 downwelling motion is the only process contributing significantly to the initial subsurface warming 36 in the western equatorial Pacific. This initial warming is found to be advected to the central Pacific 37 by the equatorial undercurrent, which, together with the equatorward advection associated with 38 anomalies in both the meridional temperature gradient and circulation at the level of the 39 thermocline, explains the heat buildup in the central Pacific during the recharge phase. -
Use Style: Paper Title
Environmental Conditions Producing Thunderstorms with Anomalous Vertical Polarity of Charge Structure Donald R. MacGorman Alexander J. Eddy NOAA/Nat’l Severe Storms Laboratory & Cooperative Cooperative Institute for Mesoscale Meteorological Institute for Mesoscale Meteorological Studies Studies Affiliation/ Univ. of Oklahoma and NOAA/OAR Norman, Oklahoma, USA Norman, Oklahoma, USA [email protected] Earle Williams Cameron R. Homeyer Massachusetts Insitute of Technology School of Meteorology, Univ. of Oklhaoma Cambridge, Massachusetts, USA Norman, Oklahoma, USA Abstract—+CG flashes typically comprise an unusually large Tessendorf et al. 2007, Weiss et al. 2008, Fleenor et al. 2009, fraction of CG activity in thunderstorms with anomalous vertical Emersic et al. 2011; DiGangi et al. 2016). Furthermore, charge structure. We analyzed more than a decade of NLDN previous studies have suggested that CG activity tends to be data on a 15 km x 15 km x 15 min grid spanning the contiguous delayed tens of minutes longer in these anomalous storms than United States, to identify storm cells in which +CG flashes in most storms elsewhere (MacGorman et al. 2011). constituted a large fraction of CG activity, as a proxy for thunderstorms with anomalous vertical charge structure, and For this study, we analyzed more than a decade of CG data storm cells with very low percentages of +CG lightning, as a from the National Lightning Detection Network throughout the proxy for thunderstorms with normal-polarity distributions. In contiguous United States to identify storm cells in which +CG each of seven regions, we used North American Regional flashes constituted a large fraction of CG activity, as a proxy Reanalysis data to compare the environments of anomalous for storms with anomalous vertical charge structure. -
Chapter 8 Atmospheric Statics and Stability
Chapter 8 Atmospheric Statics and Stability 1. The Hydrostatic Equation • HydroSTATIC – dw/dt = 0! • Represents the balance between the upward directed pressure gradient force and downward directed gravity. ρ = const within this slab dp A=1 dz Force balance p-dp ρ p g d z upward pressure gradient force = downward force by gravity • p=F/A. A=1 m2, so upward force on bottom of slab is p, downward force on top is p-dp, so net upward force is dp. • Weight due to gravity is F=mg=ρgdz • Force balance: dp/dz = -ρg 2. Geopotential • Like potential energy. It is the work done on a parcel of air (per unit mass, to raise that parcel from the ground to a height z. • dφ ≡ gdz, so • Geopotential height – used as vertical coordinate often in synoptic meteorology. ≡ φ( 2 • Z z)/go (where go is 9.81 m/s ). • Note: Since gravity decreases with height (only slightly in troposphere), geopotential height Z will be a little less than actual height z. 3. The Hypsometric Equation and Thickness • Combining the equation for geopotential height with the ρ hydrostatic equation and the equation of state p = Rd Tv, • Integrating and assuming a mean virtual temp (so it can be a constant and pulled outside the integral), we get the hypsometric equation: • For a given mean virtual temperature, this equation allows for calculation of the thickness of the layer between 2 given pressure levels. • For two given pressure levels, the thickness is lower when the virtual temperature is lower, (ie., denser air). • Since thickness is readily calculated from radiosonde measurements, it provides an excellent forecasting tool. -
Comparison Between Observed Convective Cloud-Base Heights and Lifting Condensation Level for Two Different Lifted Parcels
AUGUST 2002 NOTES AND CORRESPONDENCE 885 Comparison between Observed Convective Cloud-Base Heights and Lifting Condensation Level for Two Different Lifted Parcels JEFFREY P. C RAVEN AND RYAN E. JEWELL NOAA/NWS/Storm Prediction Center, Norman, Oklahoma HAROLD E. BROOKS NOAA/National Severe Storms Laboratory, Norman, Oklahoma 6 January 2002 and 16 April 2002 ABSTRACT Approximately 400 Automated Surface Observing System (ASOS) observations of convective cloud-base heights at 2300 UTC were collected from April through August of 2001. These observations were compared with lifting condensation level (LCL) heights above ground level determined by 0000 UTC rawinsonde soundings from collocated upper-air sites. The LCL heights were calculated using both surface-based parcels (SBLCL) and mean-layer parcels (MLLCLÐusing mean temperature and dewpoint in lowest 100 hPa). The results show that the mean error for the MLLCL heights was substantially less than for SBLCL heights, with SBLCL heights consistently lower than observed cloud bases. These ®ndings suggest that the mean-layer parcel is likely more representative of the actual parcel associated with convective cloud development, which has implications for calculations of thermodynamic parameters such as convective available potential energy (CAPE) and convective inhibition. In addition, the median value of surface-based CAPE (SBCAPE) was more than 2 times that of the mean-layer CAPE (MLCAPE). Thus, caution is advised when considering surface-based thermodynamic indices, despite the assumed presence of a well-mixed afternoon boundary layer. 1. Introduction dry-adiabatic temperature pro®le (constant potential The lifting condensation level (LCL) has long been temperature in the mixed layer) and a moisture pro®le used to estimate boundary layer cloud heights (e.g., described by a constant mixing ratio. -
Contribution of Horizontal Advection to the Interannual Variability of Sea Surface Temperature in the North Atlantic
964 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 33 Contribution of Horizontal Advection to the Interannual Variability of Sea Surface Temperature in the North Atlantic NATHALIE VERBRUGGE Laboratoire d'Etudes en GeÂophysique et OceÂanographie Spatiales, Toulouse, France GILLES REVERDIN Laboratoire d'Etudes en GeÂophysique et OceÂanographie Spatiales, Toulouse, and Laboratoire d'OceÂanographie Dynamique et de Climatologie, Paris, France (Manuscript received 9 February 2002, in ®nal form 15 October 2002) ABSTRACT The interannual variability of sea surface temperature (SST) in the North Atlantic is investigated from October 1992 to October 1999 with special emphasis on analyzing the contribution of horizontal advection to this variability. Horizontal advection is estimated using anomalous geostrophic currents derived from the TOPEX/ Poseidon sea level data, average currents estimated from drifter data, scatterometer-derived Ekman drifts, and monthly SST data. These estimates have large uncertainties, in particular related to the sea level product, the average currents, and the mixed-layer depth, that contribute signi®cantly to the nonclosure of the surface tem- perature budget. The large scales in winter temperature change over a year present similarities with the heat ¯uxes integrated over the same periods. However, the amplitudes do not match well. Furthermore, in the western subtropical gyre (south of the Gulf Stream) and in the subpolar regions, the time evolutions of both ®elds are different. In both regions, advection is found to contribute signi®cantly to the interannual winter temperature variability. In the subpolar gyre, advection often contributes more to the SST variability than the heat ¯uxes. It seems in particular responsible for a low-frequency trend from 1994 to 1998 (increase in the subpolar gyre and decrease in the western subtropical gyre), which is not found in the heat ¯uxes and in the North Atlantic Oscillation index after 1996. -
How Appropriate They Are/Will Be Using Future Satellite Data Sources?
Different Convective Indices - - - How appropriate they are/will be using future satellite data sources? Ralph A. Petersen1 1 Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin – Madison, Madison, Wisconsin, USA Will additional input from Steve Weiss, NOAA/NWS/Storm Prediction Center ✓ Increasing the Utility / Value of real-time Satellite Sounder Products to fill gaps in their short-range forecasting processes Creating Temperature/Moisture Soundings from Infra-Red (IR) Satellite Observations A Conceptual Tutorial All level of the atmosphere is continually emit radiation toward space. Satellites observe the net amount reaching space. • Conceptually, we can think about the atmosphere being made up of many thin layers Start from the bottom and work up. 1 – The greatest amount of radiation is emitted from the earth’s surface 4 - Remember, Stefan’s Law: Emission ~ σTSfc 2 – Molecules of various gases in the lowest layer of the atmosphere absorb some of the radiation and then reemit it upward to space and back downward to the earth’s surface - Major absorbers are CO2 and H2O 4 - Emission again ~ σT , but TAtmosphere<TSfc - Amount of radiation decreases with altitude Creating Temperature/Moisture Soundings from Infra-Red (IR) Satellite Observations A Conceptual Tutorial All level of the atmosphere is continually emit radiation toward space. Satellites observe the net amount reaching space. • Conceptually, we can think about the atmosphere being made up of many thin layers Start from the bottom and work -
Atmospheric Instability Parameters Derived from Msg Seviri Observations
P3.33 ATMOSPHERIC INSTABILITY PARAMETERS DERIVED FROM MSG SEVIRI OBSERVATIONS Marianne König*, Stephen Tjemkes, Jochen Kerkmann EUMETSAT, Darmstadt, Germany 1. INTRODUCTION K-Index: Convective systems can develop in a thermo- (Tobs(850)–Tobs(500)) + TDobs(850) – (Tobs(700)–TDobs(700)) dynamically unstable atmosphere. Such systems may quickly reach high altitudes and can cause severe Lifted Index: storms. Meteorologists are thus especially interested to Tobs - Tlifted from surface at 500 hPa identify such storm potentials when the respective system is still in a preconvective state. A number of Maximum buoyancy: obs(max betw. surface and 850) obs(min betw. 700 and 300) instability indices have been defined to describe such Qe - Qe situations. Traditionally, these indices are taken from temperature and humidity soundings by radiosondes. As (T is temperature, TD is dewpoint temperature, and Qe radiosondes are only of very limited temporal and is equivalent potential temperature, numbers 850, 700, spatial resolution there is a demand for satellite-derived 300 indicate respective hPa level in the atmosphere) indices. The Meteorological Product Extraction Facility (MPEF) for the new European Meteosat Second and the precipitable water content as additionally Generation (MSG) satellite envisages the operational derived parameter. derivation of a number of instability indices from the brightness temperatures measured by certain SEVIRI 3. DESCRIPTION OF ALGORITHMS channels (Spinning Enhanced Visible and Infrared Imager, the radiometer onboard MSG). The traditional 3.1 The Physical Retrieval physical approach to this kind of retrieval problem is to infer the atmospheric profile via a constrained inversion An iterative solution to the inversion equation (e.g. and compute the indices then directly from the obtained Ma et al. -
Basic Features on a Skew-T Chart
Skew-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 -
Lecture 18 Condensation And
Lecture 18 Condensation and Fog Cloud Formation by Condensation • Mixed into air are myriad submicron particles (sulfuric acid droplets, soot, dust, salt), many of which are attracted to water molecules. As RH rises above 80%, these particles bind more water and swell, producing haze. • When the air becomes supersaturated, the largest of these particles act as condensation nucleii onto which water condenses as cloud droplets. • Typical cloud droplets have diameters of 2-20 microns (diameter of a hair is about 100 microns). • There are usually 50-1000 droplets per cm3, with highest droplet concentra- tions in polluted continental regions. Why can you often see your breath? Condensation can occur when warm moist (but unsaturated air) mixes with cold dry (and unsat- urated) air (also contrails, chimney steam, steam fog). Temp. RH SVP VP cold air (A) 0 C 20% 6 mb 1 mb(clear) B breath (B) 36 C 80% 63 mb 55 mb(clear) C 50% cold (C)18 C 140% 20 mb 28 mb(fog) 90% cold (D) 4 C 90% 8 mb 6 mb(clear) D A • The 50-50 mix visibly condenses into a short- lived cloud, but evaporates as breath is EOM 4.5 diluted. Fog Fog: cloud at ground level Four main types: radiation fog, advection fog, upslope fog, steam fog. TWB p. 68 • Forms due to nighttime longwave cooling of surface air below dew point. • Promoted by clear, calm, long nights. Common in Seattle in winter. • Daytime warming of ground and air ‘burns off’ fog when temperature exceeds dew point. • Fog may lift into a low cloud layer when it thickens or dissipates. -
Wind Enhances Differential Air Advection in Surface Snow at Sub- Meter Scales Stephen A
Wind enhances differential air advection in surface snow at sub- meter scales Stephen A. Drake1, John S. Selker2, Chad W. Higgins2 1College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, 97333, USA 5 2Biological and Ecological Engineering, Oregon State University, Corvallis, 97333, USA Correspondence to: Stephen A. Drake ([email protected]) Abstract. Atmospheric pressure gradients and pressure fluctuations drive within-snow air movement that enhances gas mobility through interstitial pore space. The magnitude of this enhancement in relation to snow microstructure properties cannot be well predicted with current methods. In a set of field experiments we injected a dilute mixture of 1% carbon 10 monoxide and nitrogen gas of known volume into the topmost layer of a snowpack and, using a distributed array of thin film sensors, measured plume evolution as a function of wind forcing. We found enhanced dispersion in the streamwise direction and also along low resistance pathways in the presence of wind. These results suggest that atmospheric constituents contained in snow can be anisotropically mixed depending on the wind environment and snow structure, having implications for surface snow reaction rates and interpretation of firn and ice cores. 15 1 Introduction Atmospheric pressure changes over a broad range of temporal and spatial scales stimulate air movement in near-surface snow pore space (Clarke et al., 1987) that redistribute radiatively and chemically active trace species (Waddington et al., 1996) such as O3 (Albert et al., 2002), OH (Domine and Shepson, 2002) and NO (Pinzer et al., 2010) thereby influencing their reaction rates. Pore space in snow is saturated within a few millimeters of depth in the snowpack that does not have 20 large air spaces (Neumann et al., 2009) so atmospheric pressure changes induce interstitial air movement that enhances snow metamorphism (Calonne et al., 2015; Ebner et al., 2015) and augments vapor exchange between the snowpack and atmosphere. -
P7.1 a Comparative Verification of Two “Cap” Indices in Forecasting Thunderstorms
P7.1 A COMPARATIVE VERIFICATION OF TWO “CAP” INDICES IN FORECASTING THUNDERSTORMS David L. Keller Headquarters Air Force Weather Agency, Offutt AFB, Nebraska 1. INTRODUCTION layer parcels are then sufficiently buoyant to rise to the Level of Free Convection (LFC), resulting in convection The forecasting of non-severe and severe and possibly thunderstorms. In many cases dynamic thunderstorms in the continental United States forcing such as low-level convergence, low-level warm (CONUS) for military customers is the responsibility of advection, or positive vorticity advection provide the Air Force Weather Agency (AFWA) CONUS Severe additional force to mechanically lift boundary layer Weather Operations (CONUS OPS), and of the Storm parcels through the inversion. Prediction Center (SPC) for the civilian government. In the morning hours, one of the biggest Severe weather is defined by both of these challenges in severe weather forecasting is to organizations as the occurrence of a tornado, hail determine not only if, but also where the cap will break larger than 19 mm, wind speed of 25.7 m/s, or wind later in the day. Model forecasts help determine future damage. These agencies produce ‘outlooks’ denoting soundings. Based on the model data, severe storm areas where non-severe and severe thunderstorms are indices can be calculated that help measure the expected. Outlooks are issued for the current day, for predicted dynamic forcing, instability, and the future ‘tomorrow’ and the day following. The ‘day 1’ forecast state of the capping inversion. is normally issued 3 to 5 times per day, the ‘day 2’ and One measure of the cap is the Convective ‘day 3’ forecasts less frequently.