# Presentation: 449855

## The MUliple SCattering in Lidar Experiments (MUSCLE) Intercomparison Exercises, and Other I3RC Considerations

*Anthony B. Davis*
- Los Alamos National Laboratory
- Space & Remote Sensing Sciences Group (ISR-2)

*3rd Intercomparison of 3D Radiation Codes (I3RC) International Workshop*,
- Kiel (Germany), October 11-14, 2005

## Topics

**MUSCLE**
- what is it?
- intercomparisons
**Intercomparison overview**
- with a gap to fill?
**3D RT: Focus on the big-picture**
- where we are, and
- where to go

## MUSCLE

**Origins - 1995, ending with ...**
- Lidar-In-space Technology Experiment (LITE) on Space Shuttle in Fall 1994, esp. night orbit #135
- Applied Optics B Special Issue (5+1 papers)
**1996 - 2005 period:**
- Quebec City
- Jerusalem
- Florence
- Williamsburg
- Oberpfaffenhoffen (near München)
- St. Petersburg
- Quebec City
**Next?**

## Applied Physics B: Lasers and Optics, Volume 60, Issue 4, April 1995 

- Bruscaglioni, P.; Ismaelli, A.; Zaccanti, G.,
**Monte-Carlo calculations of LIDAR returns: Procedure and results, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 325-329.
- Flesia, C.; Schwendimann, P.,
**Analytical multiple-scattering extension of the Mie theory: The LIDAR equation, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 331-334.
- Starkov, A.V.; Noormohammadian, M.; Oppel, U.G.,
**Stochastic model and a variance-reduction Monte-Carlo method for the calculation of light transport,**
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 335-340.
- Winker, D.M.; Poole, L.R.,
**Monte-Carlo calculations of cloud returns for ground-based and space-based LIDARS,**
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 341-344.
- Zege, E.P.; Katsev, I.L.; Polonsky, I.N.,
**Analytical solution to LIDAR return signals from clouds with regard to multiple scattering, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 345-353.
- Bissonnette, L.R.; Bruscaglioni, P.; Ismaelli, A.; Zaccanti, G.; Cohen, A.;
- Benayahu, Y.; Kleiman, M.; Egert, S.; Flesia, C.; Schwendimann, P.; et al.,
**LIDAR multiple scattering from clouds, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 355-362.

## Applied Physics B: Lasers and Optics, Volume 60, Issue 4, April 1995 

- Bruscaglioni, P.; Ismaelli, A.; Zaccanti, G.,
**Monte-Carlo calculations of LIDAR returns: Procedure and results, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 325-329.
- Flesia, C.; Schwendimann, P.,
**Analytical multiple-scattering extension of the Mie theory: The LIDAR equation, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 331-334.
- Starkov, A.V.; Noormohammadian, M.; Oppel, U.G.,
**Stochastic model and a variance-reduction Monte-Carlo method for the calculation of light transport,**
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 335-340.
- Winker, D.M.; Poole, L.R.,
**Monte-Carlo calculations of cloud returns for ground-based and space-based LIDARS,**
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 341-344.
- Zege, E.P.; Katsev, I.L.; Polonsky, I.N.,
**Analytical solution to LIDAR return signals from clouds with regard to multiple scattering, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 345-353.
- Bissonnette, L.R.; Bruscaglioni, P.; Ismaelli, A.; Zaccanti, G.; Cohen, A.;
- Benayahu, Y.; Kleiman, M.; Egert, S.; Flesia, C.; Schwendimann, P.; et al.,
**LIDAR multiple scattering from clouds, **
- Applied Physics B: Lasers and Optics,
- Volume 60, Issue 4, April 1995, Pages 355-362.

- MC

- MC

- MC

## MUSCLE Comparison Plots

## 3D RT Comparisons, Compared

- I3RC (deterministic, computational)
- ICRCCM - III (statistical, modeling)
- RAMI (vegetation canopies)
- MUSCLE (localized/pulsed sources)

## 3D RT Comparisons, Compared

- I3RC (deterministic, computational)
- ICRCCM - III (statistical, modeling)
- RAMI (vegetation canopies)
- MUSCLE (localized/pulsed sources)

- pixels

- spectra

- BRDFs

- time/
- range

## 3D RT Comparisons, Compared

- I3RC (deterministic, computational)
- ICRCCM - III (statistical, modeling)
- RAMI (vegetation canopies)
- MUSCLE (localized/pulsed sources)
***Non-vegetated surfaces?***
- DIRSIG (Rochester)
- McSCENE (Spectral Sciences, Inc.)
- Something with radiosity
- Etc.

## 3D RT Comparisons, Compared

- I3RC (deterministic, computational)
- ICRCCM - III (statistical, modeling)
- MUSCLE (localized/pulsed sources)
- RAMI (vegetation canopies)
***Non-vegetated surfaces?***
- DIRSIG (Rochester)
- McSCENE (Spectral Sciences, Inc.)
- Something with radiosity
- Etc.

- ???

## Focus on the Big 3D RT Picture

## 3D RT Problem Classification

|  | Diagnostics
use radiances
[sample ] | Energetics
use fluxes
[sum over ] |
| --- | --- | --- |
| “pixel” scales:
structure resolved 
[sample x] |  |  |
| “domain” scales:
structure
unresolved
[sum over x] |  |  |

## 3D RT Problem Classification

|  | Diagnostics
use radiances
[sample ] | Energetics
use fluxes
[sum over ] |
| --- | --- | --- |
| “pixel” scales:
structure resolved 
[sample x] | Adjacency problems |  |
| “domain” scales:
structure
unresolved
[sum over x] |  | GCM radiation parameterization problem |

## 3D RT Problem Classification

|  | Diagnostics
use radiances
[sample ] | Energetics
use fluxes
[sum over ] |
| --- | --- | --- |
| “pixel” scales:
structure resolved 
[sample x] | Adjacency problems | 3D radiative heating/cooling rates in CRMs |
| “domain” scales:
structure
unresolved
[sum over x] | Large-footprint problems | GCM radiation parameterization problem |

## 3D RT Problem Classification

|  | Diagnostics
use radiances
[sample ] | Energetics
use fluxes
[sum over ] |
| --- | --- | --- |
| “pixel” scales:
structure resolved 
[sample x] | Adjacency problems | 3D radiative heating/cooling rates in CRMs |
| “domain” scales:
structure
unresolved
[sum over x] | Large-footprint problems | GCM radiation parameterization problem |

- 1D

- 2D

## 3D RT Problem Classification

|  | Diagnostics
use radiances
[sample ] | Energetics
use fluxes
[sum over ] |
| --- | --- | --- |
| “pixel” scales:
structure resolved 
[sample x] | Adjacency problems | 3D radiative heating/cooling rates in CRMs |
| “domain” scales:
structure
unresolved
[sum over x] | Large-footprint problems | GCM radiation parameterization problem |

- 1D

- 2D

- 3D

- 0D

## Atmospheric 3D RT Evolution

- _1975 - 1995 (and beyond):_
- 3D damage *assessment* for 1D RT modeling i.e., uncertainty quantification
- _Since 1995:_
-  damage *mitigation* (back to 1D, w/o bias)
-  *innovation* (exploit 3D RT phenomena)

## 3D Damage Mitigation

- Effective optical depth (e.g., Cahalan 1994)
- Gamma-Weighted 2-Stream (Barker 1996)
- Rescaled optical properties (Cairns et al. 2000)
- Effective optical properties (Szczap et al. ≈2002)
- Nonlocal Independent Pixel Approximation - NIPA (Marshak et al. 1998)
- Etc.

## Innovation

- _In energetics_, this calls for **new** **equations** to solve:
- Markovian stochastic media;
- Stephens’ (1998b) closure scheme;
- Power-law propagation kernels, formerly known as Lévy/anomalous photon diffusion model.
- _In diagnostics_, this means going beyond improved or adapted sampling of photon state-space (wavelength, position/direction, maybe polarization).  Uses **3D photon flow patterns** and/or population properties.

## Innovation, continued:Examples in Remote Sensing

- Exploitation of radiative smoothing in *R* or in *T*
- Normalized Difference Cloud Index - NDCI
- “Bright/Dark” radiance ratio technique for dense compact clouds
- Pathlength moments from O2 A-band spectroscopy at fine or ultra-fine resolution
- Large-footprint cloud lidar
- LITE
- “in situ” cloud lidar (not “remote” per say)
- Off-beam cloud lidar w/ space- _and_ time-resolution
- WAIL (at LANL) & THOR (at NASA-Goddard)

## “Take Home” Messages

**Verification and Validation (V&V)**
- “solve the equations *right*”
- “solve the *right* equations”
**Work with others ...**
- Atmosphere - Ocean - Land - Planetary
- Modelers
- Observers
- Need more/better approximation techniques
- Outreach & teaching
**Dream up new observations**
- New synergies
- New instruments

- (Roache ≈2000)