Skew-T, Log-P Diagram Analysis Procedures
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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. -
Chapter 5 Measures of Humidity Phases of Water
Chapter 5 Atmospheric Moisture Measures of Humidity 1. Absolute humidity 2. Specific humidity 3. Actual vapor pressure 4. Saturation vapor pressure 5. Relative humidity 6. Dew point Phases of Water Water Vapor n o su ti b ra li o n m p io d a a at ep t v s o io e en s n d it n io o n c freezing Liquid Water Ice melting 1 Coexistence of Water & Vapor • Even below the boiling point, some water molecules leave the liquid (evaporation). • Similarly, some water molecules from the air enter the liquid (condense). • The behavior happens over ice too (sublimation and condensation). Saturation • If we cap the air over the water, then more and more water molecules will enter the air until saturation is reached. • At saturation there is a balance between the number of water molecules leaving the liquid and entering it. • Saturation can occur over ice too. Hydrologic Cycle 2 Air Parcel • Enclose a volume of air in an imaginary thin elastic container, which we will call an air parcel. • It contains oxygen, nitrogen, water vapor, and other molecules in the air. 1. Absolute Humidity Mass of water vapor Absolute humidity = Volume of air The absolute humidity changes with the volume of the parcel, which can change with temperature or pressure. 2. Specific Humidity Mass of water vapor Specific humidity = Total mass of air The specific humidity does not change with parcel volume. 3 Specific Humidity vs. Latitude • The highest specific humidities are observed in the tropics and the lowest values in the polar regions. -
Soaring Weather
Chapter 16 SOARING WEATHER While horse racing may be the "Sport of Kings," of the craft depends on the weather and the skill soaring may be considered the "King of Sports." of the pilot. Forward thrust comes from gliding Soaring bears the relationship to flying that sailing downward relative to the air the same as thrust bears to power boating. Soaring has made notable is developed in a power-off glide by a conven contributions to meteorology. For example, soar tional aircraft. Therefore, to gain or maintain ing pilots have probed thunderstorms and moun altitude, the soaring pilot must rely on upward tain waves with findings that have made flying motion of the air. safer for all pilots. However, soaring is primarily To a sailplane pilot, "lift" means the rate of recreational. climb he can achieve in an up-current, while "sink" A sailplane must have auxiliary power to be denotes his rate of descent in a downdraft or in come airborne such as a winch, a ground tow, or neutral air. "Zero sink" means that upward cur a tow by a powered aircraft. Once the sailcraft is rents are just strong enough to enable him to hold airborne and the tow cable released, performance altitude but not to climb. Sailplanes are highly 171 r efficient machines; a sink rate of a mere 2 feet per second. There is no point in trying to soar until second provides an airspeed of about 40 knots, and weather conditions favor vertical speeds greater a sink rate of 6 feet per second gives an airspeed than the minimum sink rate of the aircraft. -
Impact of Air Pollution Controls on Radiation Fog Frequency in the Central Valley of California
RESEARCH ARTICLE Impact of Air Pollution Controls on Radiation Fog 10.1029/2018JD029419 Frequency in the Central Valley of California Special Section: Ellyn Gray1 , S. Gilardoni2 , Dennis Baldocchi1 , Brian C. McDonald3,4 , Fog: Atmosphere, biosphere, 2 1,5 land, and ocean interactions Maria Cristina Facchini , and Allen H. Goldstein 1Department of Environmental Science, Policy and Management, Division of Ecosystem Sciences, University of 2 Key Points: California, Berkeley, CA, USA, Institute of Atmospheric Sciences and Climate ‐ National Research Council (ISAC‐CNR), • Central Valley fog frequency Bologna, BO, Italy, 3Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, CO, increased 85% from 1930 to 1970, USA, 4Chemical Sciences Division, NOAA Earth System Research Laboratory, Boulder, CO, USA, 5Department of Civil then declined 76% in the last 36 and Environmental Engineering, University of California, Berkeley, CA, USA winters, with large short‐term variability • Short‐term fog variability is dominantly driven by climate Abstract In California's Central Valley, tule fog frequency increased 85% from 1930 to 1970, then fluctuations declined 76% in the last 36 winters. Throughout these changes, fog frequency exhibited a consistent • ‐ Long term temporal and spatial north‐south trend, with maxima in southern latitudes. We analyzed seven decades of meteorological data trends in fog are dominantly driven by changes in air pollution and five decades of air pollution data to determine the most likely drivers changing fog, including temperature, dew point depression, precipitation, wind speed, and NOx (oxides of nitrogen) concentration. Supporting Information: Climate variables, most critically dew point depression, strongly influence the short‐term (annual) • Supporting Information S1 variability in fog frequency; however, the frequency of optimal conditions for fog formation show no • Table S1 • Table S2 observable trend from 1980 to 2016. -
Influence of the North Atlantic Oscillation on Winter Equivalent Temperature
INFLUENCE OF THE NORTH ATLANTIC OSCILLATION ON WINTER EQUIVALENT TEMPERATURE J. Florencio Pérez (1), Luis Gimeno (1), Pedro Ribera (1), David Gallego (2), Ricardo García (2) and Emiliano Hernández (2) (1) Universidade de Vigo (2) Universidad Complutense de Madrid Introduction Data Analysis Overview Increases in both troposphere temperature and We utilized temperature and humidity data WINTER TEMPERATURE water vapor concentrations are among the expected at 850 hPa level for the 41 yr from 1958 to WINTER AVERAGE EQUIVALENT climate changes due to variations in greenhouse gas 1998 from the National Centers for TEMPERATURE 1958-1998 TREND 1958-1998 concentrations (Kattenberg et al., 1995). However Environmental Prediction–National Center for both increments could be due to changes in the frecuencies of natural atmospheric circulation Atmospheric Research (NCEP–NCAR) regimes (Wallace et al. 1995; Corti et al. 1999). reanalysis. Changes in the long-wave patterns, dominant We calculated daily values of equivalent airmass types, strength or position of climatological “centers of action” should have important influences temperature for every grid point according to on local humidity and temperatures regimes. It is the expression in figure-1. The monthly, known that the recent upward trend in the NAO seasonal and annual means were constructed accounts for much of the observed regional warming from daily means. Seasons were defined as in Europe and cooling over the northwest Atlantic Winter (January, February and March), Hurrell (1995, 1996). However our knowledge about Spring (April, May and June), Summer (July, the influence of NAO on humidity distribution is very August and September) and Fall (October, limited. In the three recent global humidity November and December). -
Physics, Chapter 17: the Phases of Matter
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Robert Katz Publications Research Papers in Physics and Astronomy 1-1958 Physics, Chapter 17: The Phases of Matter Henry Semat City College of New York Robert Katz University of Nebraska-Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/physicskatz Part of the Physics Commons Semat, Henry and Katz, Robert, "Physics, Chapter 17: The Phases of Matter" (1958). Robert Katz Publications. 165. https://digitalcommons.unl.edu/physicskatz/165 This Article is brought to you for free and open access by the Research Papers in Physics and Astronomy at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Robert Katz Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. 17 The Phases of Matter 17-1 Phases of a Substance A substance which has a definite chemical composition can exist in one or more phases, such as the vapor phase, the liquid phase, or the solid phase. When two or more such phases are in equilibrium at any given temperature and pressure, there are always surfaces of separation between the two phases. In the solid phase a pure substance generally exhibits a well-defined crystal structure in which the atoms or molecules of the substance are arranged in a repetitive lattice. Many substances are known to exist in several different solid phases at different conditions of temperature and pressure. These solid phases differ in their crystal structure. Thus ice is known to have six different solid phases, while sulphur has four different solid phases. -
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. -
Effect of Wind on Near-Shore Breaking Waves
EFFECT OF WIND ON NEAR-SHORE BREAKING WAVES by Faydra Schaffer A Thesis Submitted to the Faculty of The College of Engineering and Computer Science in Partial Fulfillment of the Requirements for the Degree of Master of Science Florida Atlantic University Boca Raton, Florida December 2010 Copyright by Faydra Schaffer 2010 ii ACKNOWLEDGEMENTS The author wishes to thank her mother and family for their love and encouragement to go to college and be able to have the opportunity to work on this project. The author is grateful to her advisor for sponsoring her work on this project and helping her to earn a master’s degree. iv ABSTRACT Author: Faydra Schaffer Title: Effect of wind on near-shore breaking waves Institution: Florida Atlantic University Thesis Advisor: Dr. Manhar Dhanak Degree: Master of Science Year: 2010 The aim of this project is to identify the effect of wind on near-shore breaking waves. A breaking wave was created using a simulated beach slope configuration. Testing was done on two different beach slope configurations. The effect of offshore winds of varying speeds was considered. Waves of various frequencies and heights were considered. A parametric study was carried out. The experiments took place in the Hydrodynamics lab at FAU Boca Raton campus. The experimental data validates the knowledge we currently know about breaking waves. Offshore winds effect is known to increase the breaking height of a plunging wave, while also decreasing the breaking water depth, causing the wave to break further inland. Offshore winds cause spilling waves to react more like plunging waves, therefore increasing the height of the spilling wave while consequently decreasing the breaking water depth. -
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. -
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. -
Forecasting of Thunderstorms in the Pre-Monsoon Season at Delhi
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Publications of the IAS Fellows Meteorol. Appl. 6, 29–38 (1999) Forecasting of thunderstorms in the pre-monsoon season at Delhi N Ravi1, U C Mohanty1, O P Madan1 and R K Paliwal2 1Centre for Atmospheric Sciences, Indian Institute of Technology, New Delhi 110 016, India 2National Centre for Medium Range Weather Forecasting, Mausam Bhavan Complex, Lodi Road, New Delhi 110 003, India Accurate prediction of thunderstorms during the pre-monsoon season (April–June) in India is essential for human activities such as construction, aviation and agriculture. Two objective forecasting methods are developed using data from May and June for 1985–89. The developed methods are tested with independent data sets of the recent years, namely May and June for the years 1994 and 1995. The first method is based on a graphical technique. Fifteen different types of stability index are used in combinations of different pairs. It is found that Showalter index versus Totals total index and Jefferson’s modified index versus George index can cluster cases of occurrence of thunderstorms mixed with a few cases of non-occurrence along a zone. The zones are demarcated and further sub-zones are created for clarity. The probability of occurrence/non-occurrence of thunderstorms in each sub-zone is then calculated. The second approach uses a multiple regression method to predict the occurrence/non- occurrence of thunderstorms. A total of 274 potential predictors are subjected to stepwise screening and nine significant predictors are selected to formulate a multiple regression equation that gives the forecast in probabilistic terms.