Model Task 1: Setting up the base state ATM 562 Fall 2015 Fovell (see course notes, Chapter 9) 1.

Slides:



Advertisements
Similar presentations
1 The structure and evolution of stars Lecture 3: The equations of stellar structure Dr. Stephen Smartt Department of Physics and Astronomy
Advertisements

RAMS/BRAMS Basic equations and some numerical issues.
Last Lab: (Hail formation) Anthony R. Lupo Atms 4310 / 7310 Lab 13.
The structure and evolution of stars
Hydrostatic Equilibrium Chapt 3, page 28
MET 61 1 MET 61 Introduction to Meteorology MET 61 Introduction to Meteorology - Lecture 2 “The atmosphere (II)” Dr. Eugene Cordero San Jose State University.
Chapter 9 Vertical Motion. (1) Divergence in two and three dimensions. The del “or gradient” operator is a mathematical operation performed on something.
Chapter 8 Coordinate Systems.
Measurement of atmospheric pressure with the mercury barometer: vacuum AB h CHAPTER 2. ATMOSPHERIC PRESSURE.
D A C B z = 20m z=4m Homework Problem A cylindrical vessel of height H = 20 m is filled with water of density to a height of 4m. What is the pressure at:
REPETITIVE EXECUTION MET 50. FABULOUS “DO LOOPS” MET 50.
MET 61 1 MET 61 Introduction to Meteorology MET 61 Introduction to Meteorology - Lecture 4 “Heat in the atmosphere” Dr. Eugene Cordero San Jose State University.
MET 61 1 MET 61 Introduction to Meteorology MET 61 Introduction to Meteorology - Lecture 3 Thermodynamics I Dr. Eugene Cordero San Jose State University.
January 29-30, 2013 simulated composite reflectivity (dBZ).January 29-30, 2013 simulated surface equivalent potential temperature (K) and winds (m/s).
* Reading Assignments:
Pressure. Solids, Liquids, and Gases  Solid IncompressibleIncompressible Subject to shear forceSubject to shear force  Gas Compressible Not subject.
Objectives Learn about Psychometrics Psychometric chart Equations.
* Reading Assignments:
Presentation Slides for Chapter 5 of Fundamentals of Atmospheric Modeling 2 nd Edition Mark Z. Jacobson Department of Civil & Environmental Engineering.
1 Gases Chapter Properties of Gases Expand to completely fill their container Take the Shape of their container Low Density –much less than solid.
1 Gases Chapter Properties of Gases Expand to completely fill their container Take the Shape of their container Low Density –much less than solid.
Pressure. Solids, Liquids, and Gases  Solid IncompressibleIncompressible Subject to shear forceSubject to shear force  Gas Compressible Not subject.
Copyright©2004 by Houghton Mifflin Company. All rights reserved. 1 Introductory Chemistry: A Foundation FIFTH EDITION by Steven S. Zumdahl University of.
Different options for the assimilation of GPS Radio Occultation data within GSI Lidia Cucurull NOAA/NWS/NCEP/EMC GSI workshop, Boulder CO, 28 June 2011.
Fronts and Frontogenesis
Atmospheric Moisture Vapor pressure (e, Pa) The partial pressure exerted by the molecules of vapor in the air. Saturation vapor pressure (e s, Pa ) The.
Understanding the USEPA’s AERMOD Modeling System for Environmental Managers Ashok Kumar Abhilash Vijayan Kanwar Siddharth Bhardwaj University of Toledo.
Initialization for Real Data Cases Dave Gill
Chapter 1 Properties of the Atmosphere How is the atmosphere characterized?
Model Task 2: Calculating CAPE and CIN ATM 562 Fall 2015 Fovell (see updated course notes, Chapter 10) 1.
Model Task 0B: Implementing different schemes ATM 562 Fall 2015 Fovell 1.
Lab 6: Saturation & Atmospheric Stability
Presentation Slides for Chapter 7 of Fundamentals of Atmospheric Modeling 2 nd Edition Mark Z. Jacobson Department of Civil & Environmental Engineering.
AOSS 401, Fall 2006 Lecture 9 September 26, 2007 Richard B. Rood (Room 2525, SRB) Derek Posselt (Room 2517D, SRB)
1 The structure and evolution of stars Lecture 3: The equations of stellar structure.
Model Task 3: Grid setup, initial condition and visualization ATM 562 Fall 2015 Fovell (see updated course notes, Chapter 11) 1.
Objectives Describe psychrometric quantities Given any two psychrometric quantities, calculate any other quantity Use Tables A4 or psychrometric charts.
Model Task 5: Implementing the 2D model ATM 562 Fall 2015 Fovell (see updated course notes, Chapter 13) 1.
Lecture 20 Ground Water (3) Ground water movement
Model Task 4: Time stepping and the leapfrog scheme ATM 562 Fall 2015 Fovell (see updated course notes, Chapter 12) 1.
VIRTUAL TEMPERATURE T V (Virtual Temp.) is the temperature a dry air parcel would be if its pressure and density were equal to a given moist air sample.
Compressible vs. anelastic (Elliptic equation example) ATM 562 Fovell Fall, 2015.
Adjoint models: Theory ATM 569 Fovell Fall 2015 (See course notes, Chapter 15) 1.
Heat  First Law of Thermodynamics: The change in internal energy of a closed system,  U, is given by: where,  Q = heat added to the system,  W = work.
Moisture  There are several methods of expressing the moisture content (water in vapor form) of a volume of air.  Vapor Pressure: The partial pressure.
ThermodynamicsM. D. Eastin We need to understand the environment around a moist air parcel in order to determine whether it will rise or sink through the.
Hydrologic Losses - Evaporation Learning Objectives Be able to calculate Evaporation from a lake or reservoir using the following methods – Energy Balance.
Cloud Formation Do Now: Science Trivia Pressure Song 3 times.
Hydrologic Losses - Evaporation
SO254 Introduction to Meteorology
Table of Contents 1. Section 2.1 Rates of change and Limits.
Moisture Variables & The Equation of State for Moist Air
TATVA INSTITUTES OF TECHNOLOGICAL STUDIES, MODASA
Chapter 11 Preview Objectives Diffusion and Effusion
Hydrostatics Dp Dz Air Parcel g.
Review Moist virtual effect
Hyperspectral Wind Retrievals Dave Santek Chris Velden CIMSS Madison, Wisconsin 5th Workshop on Hyperspectral Science 8 June 2005.
Fall 2000 Author: Dr. Ken Crawford University of Oklahoma
Bill Scheftic Atmo 558 May 6th 2008
Pressure & Depth.
Hydrologic Losses - Evaporation
Model Vertical Coordinates and Levels and Nesting
Hurricane Sandy. Hurricane Sandy Hurricane Sandy.
Chapter 3 Properties of Engineering Working Fluid
Index of Refraction and Speed of Light
Static flow and Its Application
1. Transformations of Moist Air
About 71% of the Surface of the Earth Is Covered with Water.
Rate of Change and Slope
The structure and evolution of stars
Presentation transcript:

Model Task 1: Setting up the base state ATM 562 Fall 2015 Fovell (see course notes, Chapter 9) 1

Overview Construct the base state (function of z alone) for five prognostic variables (u, w, , q v, and  ) and also . The Weisman and Klemp (1982) sounding will be adopted.  and q v functions of z will be provided, and  and  will be computed. The grid will be staggered, using Arakawa’s “C” grid arrangement. Fake points above and below the model will facilitate handling of the boundary conditions.

“C” grid arrangement (s = scalar) k+1 k+1/2 k k-1/2 k-1 NOTE: u(i,k), w(i,k) and s(i,k) not same point! ∆z ∆x

Vertical grid Fortran – The surface resides at the k = 2 level for w. – k = 2 is also first real scalar level, so height of this level above is z T = (k-1.5)∆z, or 0.5∆z above ground C++ and other zero-based index languages – The surface resides at the k = 1 level for w. – k = 1 is also first real scalar level, so height of this level above is z T = (k-0.5)∆z, or (still) 0.5∆z above ground For this example problem, we take NZ = 40 and ∆z = 700 m

W-K sounding Base state potential temperature (z T = scalar height [temperature] above ground; z TR = tropopause height above ground [12 km]; q TR = tropopause pot. temp. [343 K]; T TR = tropopause temp. [213 K]; g = 9.81 m/s 2 ; c pd = 1004 J/kg/K). Note this is not  v. Base state water vapor mixing ratio can be specified as:

Real and fake points For Fortran, the real points in the vertical for a scalar are k = 2, nz-1, with k=2 scalar level 0.5∆z above surface. Once we define mean potential temperature and mixing ratio (which I will call tb and qb ) for the real points, we need to also fill in the fake points. – Note the k=1 fake point is below the ground! – We will presume the values 0.5∆z below the ground = those 0.5∆z above ground. That is, we assume zero gradient. With tb and qb, we can compute tbv, or mean virtual potential temperature, for all real and fake points.

Derived quantities Given mean , q v, we will compute the base state nondimensional pressure (p) presuming it is hydrostatic Recall given p 0 = Pa, R d = 287 J/kg/K:

Computing mean  psurf = Pa is the provided surface pressure. We need to compute pressures starting at 0.5∆z above the surface, and then every ∆z above that ! tbv = virtual potential temperature, already computed p0 = xk = rd/cpd pisfc = (psurf/p0)**xk pib(2) = pisfc-grav*0.5*dz/(cpd*tbv(2)) do k = 3, nz-1 tbvavg = 0.5*(tbv(k)+tbv(k-1)) pib(k) = pib(k-1) - grav*dz/(cp*tbvavg) enddo

Concept pib(2) = pisfc -grav*0.5*dz/(cpd*tbv(2)) pib(k) = pib(k-1) - grav*dz/(cp*tbvavg)

Base state density As a scalar, density is logically defined at the scalar/u height, but is useful also to define density at w heights. I will call these RHOU and RHOW. RHOU will be computed using and averaged to form RHOW rhow(k) = 0.5*(rhou(k) + rhou(k-1))

Saturation mixing ratio (q vs ) One form of Tetens’ equation for q vs You can substitute usingand Ref: Soong and Ogura (1973)

Some results (see notes) z(km) tb(K) qb(g/kg) rhou(kg/m^3) rel. hum (%) E E E E E E E E [...] E E E E E E E E E E Please hand in your code and your version of this table