METO 621 Lesson 16. Transmittance For monochromatic radiation the transmittance, T, is given simply by The solution for the radiative transfer equation.

Slides:



Advertisements
Similar presentations
Modeling of Data. Basic Bayes theorem Bayes theorem relates the conditional probabilities of two events A, and B: A might be a hypothesis and B might.
Advertisements

Chemical Kinetics : rate of a chemical reaction Before a chemical reaction can take place the molecules involved must be raised to a state of higher potential.
METO621 Lesson 18. Thermal Emission in the Atmosphere – Treatment of clouds Scattering by cloud particles is usually ignored in the longwave spectrum.
METO 621 Lesson 6. Absorption by gaseous species Particles in the atmosphere are absorbers of radiation. Absorption is inherently a quantum process. A.
Continuous Probability Distributions.  Experiments can lead to continuous responses i.e. values that do not have to be whole numbers. For example: height.
Lesson 3 METO 621. Basic state variables and the Radiative Transfer Equation In this course we are mostly concerned with the flow of radiative energy.
METO 621 CHEM Lesson 7. Albedo 200 – 400 nm Solar Backscatter Ultraviolet (SBUV) The previous slide shows the albedo of the earth viewed from the nadir.
ABSORPTION Beer’s Law Optical thickness Examples BEER’S LAW
METO 621 Lesson 9. Solution for Zero Scattering If there is no scattering, e.g. in the thermal infrared, then the equation becomes This equation can be.
METO 621 LESSON 8. Thermal emission from a surface Let be the emitted energy from a flat surface of temperature T s, within the solid angle d  in the.
single line curve of growth m: molecules cm -2 cm – atm g cm -2 as we increase amount of gas from m 1 to m 3 we see more absorption.
METO 621 Lesson 13. Separation of the radiation field into orders of scattering If the source function is known then we may integrate the radiative transfer.
ABSORPTION Beer’s Law Optical thickness Examples BEER’S LAW Note: Beer’s law is also attributed to Lambert and Bouguer, although, unlike Beer, they did.
METO 621 Lesson 10. Upper half-range intensity For the upper half-range intensity we use the integrating factor e -  In this case we are dealing with.
Statistical Properties of Wave Chaotic Scattering and Impedance Matrices Collaborators: Xing Zheng, Ed Ott, ExperimentsSameer Hemmady, Steve Anlage, Supported.
Ch 5.1: Review of Power Series Finding the general solution of a linear differential equation depends on determining a fundamental set of solutions of.
Introduction to radiative transfer
METO 621 Lesson 5. Natural broadening The line width (full width at half maximum) of the Lorentz profile is the damping parameter, . For an isolated.
Development of Empirical Models From Process Data
1 EE 616 Computer Aided Analysis of Electronic Networks Lecture 9 Instructor: Dr. J. A. Starzyk, Professor School of EECS Ohio University Athens, OH,
METO 621 Lesson 12. Prototype problems in Radiative Transfer Theory We will now study a number of standard radiative transfer problems. Each problem assumes.
LESSON 4 METO 621. The extinction law Consider a small element of an absorbing medium, ds, within the total medium s.
METO 621 Lesson 27. Albedo 200 – 400 nm Solar Backscatter Ultraviolet (SBUV) The previous slide shows the albedo of the earth viewed from the nadir.
How confident are we that our sample means make sense? Confidence intervals.
Ch 11 – Probability & Statistics
Parallel RLC Network. Objective of Lecture Derive the equations that relate the voltages across a resistor, an inductor, and a capacitor in parallel as:
621 project Spring project 1. The heating rate is defined as :- Let us assume that the effect of scattering is small, and that in the ultraviolet.
Lecture 12 Monte Carlo Simulations Useful web sites:
Physics 114: Lecture 15 Probability Tests & Linear Fitting Dale E. Gary NJIT Physics Department.
Laws of Radiation Heat Transfer P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi Macro Description of highly complex Wave.
© Copyright McGraw-Hill CHAPTER 6 The Normal Distribution.
To fluxes & heating rates: Want to do things like:  Calculate IR forcing due to Greenhouse Gases  Changes in IR forcing due to changes in gas constituents.
Series RLC Network. Objective of Lecture Derive the equations that relate the voltages across a resistor, an inductor, and a capacitor in series as: the.
1 More about the Sampling Distribution of the Sample Mean and introduction to the t-distribution Presentation 3.
1 Atmospheric Radiation – Lecture 8 PHY Lecture 8 Radiative Transfer Band Models.
The basics - 0 Definitions The Radiative Transfer Equation (RTE)
Physics 114: Lecture 10 PDFs Part Deux Dale E. Gary NJIT Physics Department.
AME Int. Heat Trans. D. B. Go Radiation with Participating Media Consider the general heat equation We know that we can write the flux in terms of.
© 2003 Prentice-Hall, Inc.Chap 6-1 Business Statistics: A First Course (3 rd Edition) Chapter 6 Sampling Distributions and Confidence Interval Estimation.
Estimation in Sampling!? Chapter 7 – Statistical Problem Solving in Geography.
Average Lifetime Atoms stay in an excited level only for a short time (about 10-8 [sec]), and then they return to a lower energy level by spontaneous emission.
STATISTIC & INFORMATION THEORY (CSNB134) MODULE 7C PROBABILITY DISTRIBUTIONS FOR RANDOM VARIABLES ( NORMAL DISTRIBUTION)
Approximate letter grade assignments ~ D C B 85 & up A.
Biostatistics Dr. Chenqi Lu Telephone: Office: 2309 GuangHua East Main Building.
Step Response Series RLC Network.
Doc.: IEEE /0553r1 Submission May 2009 Alexander Maltsev, Intel Corp.Slide 1 Path Loss Model Development for TGad Channel Models Date:
COST 723 Training School - Cargese October 2005 KEY 1 Radiative Transfer Bruno Carli.
General Relativity Physics Honours 2008 A/Prof. Geraint F. Lewis Rm 560, A29 Lecture Notes 10.
13-1 Lesson 13 Objectives Begin Chapter 5: Integral Transport Begin Chapter 5: Integral Transport Derivation of I.T. form of equation Derivation of I.T.
Laser physics and its application Introductory Concept The word LASER is an acronym for Light Amplification by Stimulated Emission of Radiation Lasers,
Chapter 8: Simple Linear Regression Yang Zhenlin.
Continuous Probability Distribution By: Dr. Wan Azlinda Binti Wan Mohamed.
Math 3120 Differential Equations with Boundary Value Problems
One Function of Two Random Variables
Intro to Statistics for the Behavioral Sciences PSYC 1900 Lecture 7: Regression.
1 Atmospheric Radiation – Lecture 13 PHY Lecture 13 Remote sensing using emitted IR radiation.
The inference and accuracy We learned how to estimate the probability that the percentage of some subjects in the sample would be in a given interval by.
ECMWF The ECMWF Radiation Transfer schemes 1 Photon path distribution method originally developed by Fouquart and Bonnel (1980). [see lecture notes for.
Saturation Roi Levy. Motivation To show the deference between linear and non linear spectroscopy To understand how saturation spectroscopy is been applied.
Chapter 13 – Behavior of Spectral Lines
Chapter 7 Sampling Distributions.
Chapter 7 Sampling Distributions.
Probability & Statistics Probability Theory Mathematical Probability Models Event Relationships Distributions of Random Variables Continuous Random.
Econometric Models The most basic econometric model consists of a relationship between two variables which is disturbed by a random error. We need to use.
Chapter 7 Sampling Distributions.
Chapter 7 Sampling Distributions.
CHAPTER – 1.2 UNCERTAINTIES IN MEASUREMENTS.
Chapter 7 Sampling Distributions.
CHAPTER – 1.2 UNCERTAINTIES IN MEASUREMENTS.
Presentation transcript:

METO 621 Lesson 16

Transmittance For monochromatic radiation the transmittance, T, is given simply by The solution for the radiative transfer equation was:

Transmittance Which is equivalent to similarly

Transmittance If we switch from the optical depth coordinate to altitude, z, then we get The change of sign before the integral is because the integral range is reversed when moving from  to z

Transmission in spectrally complex media So far we have defined the monochromatic transmittance, T  We can also define a beam absorptance  b ( ), where  b ( ) =1- T  But in radiative transfer we must consider transmission over a broad spectral range,  (Often called a band) In this case the mean band absorptance is defined as Here u is the total mass along the path, and k is the monochromatic mass absorption coefficient.

Schematic for A

Transmission in spectrally complex media Similarly for the transmittance

Transmission in spectrally complex media If in the previous equation we replace the frequency with wavenumber then the product The relationship of W to u is known as the curve of growth

Absorption in a Lorentz line shape

Transmission in spectrally complex media Consider a single line with a Lorentz line shape. As u gets larger the absorptance gets larger. However as u increases the center of the line absorbs all of the radiation, while the wings absorb only some of the radiation. At this point only the wings absorb. We can write the band transmittance as;

Transmission in spectrally complex media Let  be large enough to include all of the line, then we can extend the limits of the integration to ±∞. Landenburg and Reichle showed that

Transmission in spectrally complex media For small x, known as the optically thin condition,

Elsasser band model

Elsasser Band Model Elsasser and Culbertson (1960) assumed evenly spaced lines (d apart) of equal S that overlapped. They showed that the transmittance could be expressed as

Statistical Band Model (Goody) Goody studied the water-vapor bands and noted the apparent random line positions and band strengths. Let us assume that the interval  contains n lines of mean separation d, i.e.  =nd Let the probability that line i has a line strength S i be P(S i ) where P is normally assumed to have a Poisson distribution

Statistical Band Model (Goody) For any line the most probable value of S is given by The transmission T over an interval  is given by

Statistical Band Model (Goody) For n lines the total transmission T is given by T=T 1 T 2 T 3 T 4 …………..T n

Statistical Band Model (Goody)

We have reduced the parameters needed to calculate T to two These two parameters are either derived by fitting the values of T obtained from a line-by-line calculation, or from experimental data.

Summary of band models

K distribution technique