Fog: Its Causes and Forecasting with Special Reference to Eastern and Southern United States (III)* J
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Pressure Gradient Force Examples of Pressure Gradient Hurricane Andrew, 1992 Extratropical Cyclone
4/29/2011 Chapter 7: Forces and Force Balances Forces that Affect Atmospheric Motion Pressure gradient force Fundamental force - Gravitational force FitiFrictiona lfl force Centrifugal force Apparent force - Coriolis force • Newton’s second law of motion states that the rate of change of momentum (i.e., the acceleration) of an object , as measured relative relative to coordinates fixed in space, equals the sum of all the forces acting. • For atmospheric motions of meteorological interest, the forces that are of primary concern are the pressure gradient force, the gravitational force, and friction. These are the • Forces that Affect Atmospheric Motion fundamental forces. • Force Balance • For a coordinate system rotating with the earth, Newton’s second law may still be applied provided that certain apparent forces, the centrifugal force and the Coriolis force, are • Geostrophic Balance and Jetstream ESS124 included among the forces acting. ESS124 Prof. Jin-Jin-YiYi Yu Prof. Jin-Jin-YiYi Yu Pressure Gradient Force Examples of Pressure Gradient Hurricane Andrew, 1992 Extratropical Cyclone (from Meteorology Today) • PG = (pressure difference) / distance • Pressure gradient force goes from high pressure to low pressure. • Closely spaced isobars on a weather map indicate steep pressure gradient. ESS124 ESS124 Prof. Jin-Jin-YiYi Yu Prof. Jin-Jin-YiYi Yu 1 4/29/2011 Gravitational Force Pressure Gradients • • Pressure Gradients – The pressure gradient force initiates movement of atmospheric mass, widfind, from areas o fhihf higher to areas o flf -
Chapter 5. Meridional Structure of the Atmosphere 1
Chapter 5. Meridional structure of the atmosphere 1. Radiative imbalance 2. Temperature • See how the radiative imbalance shapes T 2. Temperature: potential temperature 2. Temperature: equivalent potential temperature 3. Humidity: specific humidity 3. Humidity: saturated specific humidity 3. Humidity: saturated specific humidity Last time • Saturated adiabatic lapse rate • Equivalent potential temperature • Convection • Meridional structure of temperature • Meridional structure of humidity Today’s topic • Geopotential height • Wind 4. Pressure / geopotential height • From a hydrostatic balance and perfect gas law, @z RT = @p − gp ps T dp z(p)=R g p Zp • z(p) is called geopotential height. • If we assume that T and g does not vary a lot with p, geopotential height is higher when T increases. 4. Pressure / geopotential height • If we assume that g and T do not vary a lot with p, RT z(p)= (ln p ln p) g s − • z increases as p decreases. • Higher T increases geopotential height. 4. Pressure / geopotential height • Geopotential height is lower at the low pressure system. • Or the high pressure system corresponds to the high geopotential height. • T tends to be low in the region of low geopotential height. 4. Pressure / geopotential height The mean height of the 500 mbar surface in January , 2003 4. Pressure / geopotential height • We can discuss about the slope of the geopotential height if we know the temperature. R z z = (T T )(lnp ln p) warm − cold g warm − cold s − • We can also discuss about the thickness of an atmospheric layer if we know the temperature. RT z z = (ln p ln p ) p1 − p2 g 2 − 1 4. -
Pressure Gradient Force
2/2/2015 Chapter 7: Forces and Force Balances Forces that Affect Atmospheric Motion Pressure gradient force Fundamental force - Gravitational force Frictional force Centrifugal force Apparent force - Coriolis force • Newton’s second law of motion states that the rate of change of momentum (i.e., the acceleration) of an object, as measured relative to coordinates fixed in space, equals the sum of all the forces acting. • For atmospheric motions of meteorological interest, the forces that are of primary concern are the pressure gradient force, the gravitational force, and friction. These are the • Forces that Affect Atmospheric Motion fundamental forces. • Force Balance • For a coordinate system rotating with the earth, Newton’s second law may still be applied provided that certain apparent forces, the centrifugal force and the Coriolis force, are • Geostrophic Balance and Jetstream ESS124 included among the forces acting. ESS124 Prof. Jin-Yi Yu Prof. Jin-Yi Yu Pressure Gradient Force Examples of Pressure Gradient Hurricane Andrew, 1992 Extratropical Cyclone (from Meteorology Today) • PG = (pressure difference) / distance • Pressure gradient force goes from high pressure to low pressure. • Closely spaced isobars on a weather map indicate steep pressure gradient. ESS124 ESS124 Prof. Jin-Yi Yu Prof. Jin-Yi Yu 1 2/2/2015 Balance of Force in the Vertical: Pressure Gradients Hydrostatic Balance • Pressure Gradients – The pressure gradient force initiates movement of atmospheric mass, wind, from areas of higher to areas of lower pressure Vertical -
Chapter 7.0 – Determining Wind Direction Section 7.1 Overview Of
Chapter 7.0 – Determining Wind Direction Section 7.1 Overview of Wind Direction The wind direction is a measure or indication of where the air movement originated from. The wind direction can be measured through the use of a wind sock, wind vane, or a light object attached to a pole and string (example: A ping pong ball attached to a string which is tied to a stick). Wind direction is generally reported in either Azimuth degrees or Cardinal direction. Azimuth uses a circle with the northern most position indicating 0 degrees. The Cardinal direction system gives an Azimuth degree value a name. For example, 180 degrees is South(S) and 270 degrees is West (W) (See Figure 18 - A basic compass rose). Figure 18 - A basic compass rose Section 7.2 Overview of the homemade Wind Vane The wind vane used in this design was a homemade wind vane using a miniature absolute magnetic shaft encoder. The encoder chosen for use was the MA3 produced by US Digital. The purpose for choosing this specific encoder in regards to this design was that the MA3 met four (4) critical objectives. First, the MA3 was the correct size for the application. Second, the MA3 uses an analog output of 0 volts to 5 volts with respect to the current positions (See Figure 19 – MA3 Output behaviour) Figure 19 – MA3 Output behaviour Third, the MA3 uses a 5 volt input. This was a major consideration when choosing an encoder as a 5 volt input allowed for a more simple integration. Fourth, and final, the MA3 met the requirements of being able to function in an adverse environment, having an operational temperature of -40 ºC to +125 ºC. -
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. -
Impact of Cloud Analysis on Numerical Weather Prediction in the Galician Region of Spain
Impact of Cloud Analysis on Numerical Weather Prediction in the Galician Region of Spain M. J. SOUTO, C. F. BALSEIRO AND V. P…REZ-MU—UZURI Group of Nonlinear Physics, Faculty of Physics, University of Santiago de Compostela, Santiago de Compostela, Spain Ming Xue University of Oklahoma, School of Meteorology, and CAPS Oklahoma, USA Keith BREWSTER Center for Analysis and Prediction of Storms, Oklahoma, USA April, 2001 Revised December, 2001 Corresponding author address: Dra. M. J. Souto, Group of Nonlinear Physics Faculty of Physics, University of Santiago de Compostela E-15706, Santiago de Compostela, Spain e-mail: [email protected] ABSTRACT The Advanced Regional Prediction System (ARPS) is applied to operational numerical weather forecast in Galicia, northwest Spain. A 72-hour forecast at a 10-km horizontal resolution is produced dta for the region. Located on the northwest coast of Spain and influenced by the Atlantic weather systems, Galicia has a high percentage (almost 50%) of rainy days per year. For these reasons, the precipitation processes and the initialization of moisture and cloud fields are very important. Even though the ARPS model has a sophisticated data analysis system (ADAS) that includes a 3D cloud analysis package, due to operational constraint, our current forecast starts from 12-hour forecast of the NCEP AVN model. Still, procedures from the ADAS cloud analysis are being used to construct the cloud fields based on AVN data, and then applied to initialize the microphysical variables in ARPS. Comparisons of the ARPS predictions with local observations show that ARPS can predict quite well both the daily total precipitation and its spatial distribution. -
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. -
Chapter 7 Isopycnal and Isentropic Coordinates
Chapter 7 Isopycnal and Isentropic Coordinates The two-dimensional shallow water model can carry us only so far in geophysical uid dynam- ics. In this chapter we begin to investigate fully three-dimensional phenomena in geophysical uids using a type of model which builds on the insights obtained using the shallow water model. This is done by treating a three-dimensional uid as a stack of layers, each of con- stant density (the ocean) or constant potential temperature (the atmosphere). Equations similar to the shallow water equations apply to each layer, and the layer variable (density or potential temperature) becomes the vertical coordinate of the model. This is feasible because the requirement of convective stability requires this variable to be monotonic with geometric height, decreasing with height in the case of water density in the ocean, and increasing with height with potential temperature in the atmosphere. As long as the slope of model layers remains small compared to unity, the coordinate axes remain close enough to orthogonal to ignore the complex correction terms which otherwise appear in non-orthogonal coordinate systems. 7.1 Isopycnal model for the ocean The word isopycnal means constant density. Recall that an assumption behind the shallow water equations is that the water have uniform density. For layered models of a three- dimensional, incompressible uid, we similarly assume that each layer is of uniform density. We now see how the momentum, continuity, and hydrostatic equations appear in the context of an isopycnal model. 7.1.1 Momentum equation Recall that the horizontal (in terms of z) pressure gradient must be calculated, since it appears in the horizontal momentum equations. -
1050 Clicker Questions Exam 1
Answers to Clicker Questions Chapter 1 What component of the atmosphere is most important to weather? A. Nitrogen B. Oxygen C. Carbon dioxide D. Ozone E. Water What location would have the lowest surface pressure? A. Chicago, Illinois B. Denver, Colorado C. Miami, Florida D. Dallas, Texas E. Los Angeles, California What is responsible for the distribution of surface pressure shown on the previous map? A. Temperature B. Elevation C. Weather D. Population If the relative humidity and the temperature at Denver, Colorado, compared to that at Miami, Florida, is as shown below, how much absolute water vapor is in the air between these two locations? A. Denver has more absolute water vapor B. Miami has more absolute water vapor C. Both have the same amount of water vapor Denver 10°C Air temperature 50% Relative humidity Miami 20°C Air temperature 50% Relative humidity Chapter 2 Convert our local time of 9:45am MST to UTC A. 0945 UTC B. 1545 UTC C. 1645 UTC D. 2345 UTC A weather observation made at 0400 UTC on January 10th, would correspond to what local time (MST)? A. 11:00am January10th B. 9:00pm January 10th C. 10:00pm January 9th D. 9:00pm January 9th A weather observation made at 0600 UTC on July 10th, would correspond to what local time (MDT)? A. 12:00am July 10th B. 12:00pm July 10th C. 1:00pm July 10th D. 11:00pm July 9th A rawinsonde measures all of the following variables except: Temperature Dew point temperature Precipitation Wind speed Wind direction What can a Doppler weather radar measure? Position of precipitation Intensity of precipitation Radial wind speed All of the above Only a and b In this sounding from Denver, the tropopause is located at a pressure of approximately: 700 mb 500 mb 300 mb 100 mb Which letter on this radar reflectivity image has the highest rainfall rate? A B C D C D B A Chapter 3 • Using this surface station model, what is the temperature? (Assume it’s in the US) 26 °F 26 °C 28 °F 28 °C 22.9 °F Using this surface station model, what is the current sea level pressure? A. -
Temperature Gradient
Temperature Gradient Derivation of dT=dr In Modern Physics it is shown that the pressure of a photon gas in thermodynamic equilib- rium (the radiation pressure PR) is given by the equation 1 P = aT 4; (1) R 3 with a the radiation constant, which is related to the Stefan-Boltzman constant, σ, and the speed of light in vacuum, c, via the equation 4σ a = = 7:565731 × 10−16 J m−3 K−4: (2) c Hence, the radiation pressure gradient is dP 4 dT R = aT 3 : (3) dr 3 dr Referring to our our discussion of opacity, we can write dF = −hκiρF; (4) dr where F = F (r) is the net outward flux (integrated over all wavelengths) of photons at a distance r from the center of the star, and hκi some properly taken average value of the opacity. The flux F is related to the luminosity through the equation L(r) F (r) = : (5) 4πr2 Considering that pressure is force per unit area, and force is a rate of change of linear momentum, and photons carry linear momentum equal to their energy divided by c, PR and F obey the equation 1 P = F (r): (6) R c Differentiation with respect to r gives dP 1 dF R = : (7) dr c dr Combining equations (3), (4), (5) and (7) then gives 1 L(r) 4 dT − hκiρ = aT 3 ; (8) c 4πr2 3 dr { 2 { which finally leads to dT 3hκiρ 1 1 = − L(r): (9) dr 16πac T 3 r2 Equation (9) gives the local (i.e. -
An Objective Determination of Probability of Fog Formation *
158 BULLETIN AMERICAN METEOROLOGICAL SOCIETY An Objective Determination of Probability of Fog Formation * LOUIS BERKOFSKY Atmospheric Analysis Laboratory, Base Directorate for Geophysical Research, Air Force Cambridge Research Laboratories, 230 Albany St., Cambridge, Mass. ABSTRACT A method of approach to objective fog forecasting, based on the use of probability charts is suggested. Given two parameters, say wind speed and dew-point depression, at sunset as ordinate and abscissa of a chart, occurrences and non-occurrences of fog following sunset are plotted as functions of these parameters. Isolines of relative frequency are drawn, giving a probability chart. Two more such charts, using four additional parameters, are constructed, and a total probability of fog occurrence following sunset is computed as a linear function of the three individual probabilities. This result is used as a criterion for the forecast. Time of formation equations are developed, to be applied in the event a fog proves to be likely. I. INTRODUCTION sive—during which period the fog was mainly non-frontal. Only those cases were considered in ANY objective methods of forecasting which precipitation was not occurring at time of fog deal primarily with determination of fog formation, in order to simplify the investiga- time of formation. The determination M tion.1 of likelihood of formation is largely subjective. If it is decided subjectively that a fog must be II. THE PARAMETERS forecast, the objective time graphs are then en- No so-called objective method is truly objective, tered. Such graphs must of necessity consider due to the fact that it is necessary for the investi- only cases of occurrence, and therefore should gator to select certain parameters. -
Vortical Flows Adverse Pressure Gradient
VORTICAL FLOWS IN AN ADVERSE PRESSURE GRADIENT by John M. Brookfield Submitted to the Department of Aeronautics and Astronautics in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 1993 © Massachusetts Institute of Technology 1993 All rights reserved Signature of Author Departrnt of Aeronautics and Astronautics May 17,1993 Certified by __ Profess~'r Edward M. Greitzer Thesis Supervisor, Director of Gas Turbine Laboratory Professor of Aeronautics and Astronautics Certified by Prqse dIan A. Waitz Professor of Aeronautics and Astronautics A Certified by fessor Harold Y. Wachman Chairman, partment Graduate Committee MASSACHUSETTS INSTITUTE SOF TFr#4PJJ nnhy 'jUN 08 1993 UBRARIES VORTICAL FLOWS IN AN ADVERSE PRESSURE GRADIENT by John M. Brookfield Submitted to the Department of Aeronautics and Astronautics on May 17, 1993 in partial fulfillment of the requirements for the degree of Master of Science in Aeronautics and Astronautics Abstract An analytical and computational study was performed to examine the effects of adverse pressure gradients on confined vortical motions representative of those encountered in compressor clearance flows. The study included exploring the parametric dependence of vortex core size and blockage, as well as designing an experimental configuration to examine this phenomena in a controlled manner. Two approaches were used to assess the flows of interest. A one-dimensional analysis was developed to evaluate the parametric dependence of vortex core expansion in a diffusing duct as a function of core to diffuser radius ratio, axial velocity ratio (core to outer flow) and swirl ratio (tangential to axial velocity at the core edge) at the inlet.