Presentation is loading. Please wait.

Presentation is loading. Please wait.

Photo by Chuck Doswell Ground Flash Fraction Retrieval Algorithm GLM Science Meeting December 1-3, 2010, Huntsville, AL Dr. William Koshak, NASA/MSFC/VP61.

Similar presentations


Presentation on theme: "Photo by Chuck Doswell Ground Flash Fraction Retrieval Algorithm GLM Science Meeting December 1-3, 2010, Huntsville, AL Dr. William Koshak, NASA/MSFC/VP61."— Presentation transcript:

1 photo by Chuck Doswell Ground Flash Fraction Retrieval Algorithm GLM Science Meeting December 1-3, 2010, Huntsville, AL Dr. William Koshak, NASA/MSFC/VP61

2 # GLM Flashes Ground Flash Fraction Retrieval Algorithm (today’s talk) # GLM Ground Flashes # GLM Cloud Flashes MSFC LNOM (lightning NOx) Air Quality Models (e.g. CMAQ) Global Chemistry/Climate Models (e.g. GISS Model E, Geos Chem) Desired Future Application

3 Algorithm is used to solve an Inversion Problem Algorithm is used to solve an Inversion Problem Unknown Measurements K (Kernel) (Footprints)(Dragon)

4 What % Strike Ground?

5 Consider a (linear) Optics Analog Mueller Matrix: A matrix which can be used to reproduce the effect of a given optical element when applied to a Stokes vector.Stokes vector Optical ElementMueller Matrix (Singular) Linear horizontal polarizer Right-handed circular polarizer Optical Elements K observer Source

6 In Reality: Multiple Scattering Medium

7 Actual Forward Multiple Scattering Problem

8 Eqs. (21) is the Forward Problem … it’s ugly. Inverse Problem is uglier.

9 Is there a channel to ground? Formal Inverse Problem: Reconstruct Channel from Intensity

10 Historical Recap Several studied the forward problem Thomason & Krider 1982 (Monte Carlo) Koshak et al. 1994 (Boltzmann Diffusion) Suszcynsky et al. 2000 (optical & vhf data, not theory) Light et al. 2001 (Monte Carlo) Davis & Marshak 2002 (Green’s functions) Nobody published the inverse problem for channel reconstruction; flash-by-flash-discrimination (FBFD) Neural Net (Boccippio … unknown status); probabilistic FBFD Bayesian Inversion (Koshak); ground flash fraction retrieval

11 Bayesian Inversion

12 Find & examine the “group” in the flash having the Maximum Area. Use just 1 physical parameter

13 Distributions of the Maximum Group Area (MGA) Ground FlashesCloud Flashes

14 Shifted MGA y = MGA – 64 km 2

15

16

17

18 Retrieval Errors with Increasing N (N = # flashes observed)

19 Improvements using Normal Priors Priors P(µ g ) and P(µ c ) are Uniformly Distributed Priors P(µ g ) and P(µ c ) are Normally Distributed P(α, µ g, µ c ) = P(α) P(µ g ) P(µ c ) = 1· P(µ g ) P(µ c )

20 Retrieved Ground Flash Fraction

21 Koshak, W. J., Optical Characteristics of OTD Flashes and the Implications for Flash-Type Discrimination, J. Atmos. Oceanic Technol., 27, 1822-1838, 2010. (November issue) Koshak, W. J., R. J. Solakiewicz, Retrieving the Fraction of Ground Flashes from Satellite Lightning Imager Data Using CONUS-Based Optical Statistics, accepted in J. Atmos. Oceanic Technol., August 30, 2010. Koshak, W. J., A Mixed Exponential Distribution Model for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data, accepted in J. Atmos. Oceanic Technol., August 30, 2010. For More Details …


Download ppt "Photo by Chuck Doswell Ground Flash Fraction Retrieval Algorithm GLM Science Meeting December 1-3, 2010, Huntsville, AL Dr. William Koshak, NASA/MSFC/VP61."

Similar presentations


Ads by Google