# Presentation: 146435

## Observations of 3D Radiative Effects in MODIS Cloud Optical Thickness Retrievals

**Alexander Marshak and Tamás Várnai **
- (UMBC/JCET and NASA/GSFC)

## _x0008_Outline 

- Introduction
- Importance of 3D effects
- Pre-MODIS study of 3D effects
- LANDSAT, AVHRR, POLDER
- Theoretical simulations  of MODIS images
- Uncertainties based on stochastic models
- MODIS observations and products
- Statistical asymmetry
- Effect of view angles
- Effect of sub-pixel variability
- Wavenumber spectra
- Conclusions

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## What are 3D Radiative Effects?

- Effects of neighboring pixels (e.g., shadowing)

- 1km
-  MODIS pixel

- Sub-pixel
- variability

- 1km
-  MODIS pixel

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Importance of understanding 3D effects

- Based on a sample set of RT calculations carried out at 250-m resolution for SZA=60o

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Some earlier (pre-MODIS) studies at high resolution, diffusion smoothes images

- 60 km by 60 km Landsat scene

- from Cahalan and Snider (1989)

- Smoothing scale=
- (mfp*cloud thickness)1/2
- from Marshak et al. (1995)
- and Davis et al. (1997)

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Earlier studies  For oblique sun, clouds appear too thick   &   forward reflection is too low 

- from Loeb and Coakley (1998)

- Based on AVHRR data

- from Buriez et al. (2001)

- Based on Polder data

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## How are 3D effects studied?

- • Theoretical simulations of horizontally inhomogeneous clouds and application of 3D radiative transfer;

- • Statistical analysis of satellite data and products;

- • Combination of theoretical simulations with a statistical analysis of satellite data.

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Theoretical simulations

- Test datasets are realizations of “realistic” stochastic cloud models

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Theoretical simulations (cont.)

- MAS 35x35 km2 field of marine Sc measured at 50-m resolution

- Estimated error bounds for optical thickness retrieved at 1-km resolution

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## MODIS data

- Examine MODIS data: how frequently 3D effects influence the measured radiances and the retrieved cloud properties:
- Optical thickness
- Particle effective radius
- Cloud water path

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Statistical asymmetry in clouds

-  Toward sun       Away from sun
- Tfront > Tbehind             Tfront < Tbehind

- Cold
- Warm

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Procedure for MODIS images

- March & Sept. 2001
- NH & SH, Latitude ≈ 45°
- 120 images (107+ pixels)
- 2000 km x 450 km
- Solar zenith angle ≈ 40°-60°
- 1 km radiance, cloud products
- All clouds (e.g., ice & liquid)

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Number of pixels

- # of “illuminated” and “shadowed” pixels in 50x50 km2 areas are statistically equal

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Symmetry at 11 m

- So is IR brightness temperature

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Asymmetry at 0.86 and 2.1 m

- Each dot corresponds to a 50x50 km2 area.  Averaged reflectancies over “illuminated” pixels are plotted vs. “shadowed” ones.
- The ill. slopes are much brighter than the shad. ones!

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Effects on MODIS products: and reff

- Comparison of mean optical depth, , and mean effective radius, *r*eff, at the illuminated and shadowed portion of 50 by 50 km areas
- 3D effects have a strong influence!

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Influence on cloud water path

- Strong asymmetry in cloud water path

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Histogram of absolute and relative asymmetries of 

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Viewing angles

- pdf of  for each column

- Some optical thicknesses, 

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Viewing angles (cont.)

- FWD = 115o
- BWD = 50o

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Four bidirectional reflectances; 3D simulations

******v****=60******
******v****=180******

******v****=60******
******v****=0******

******o****=60******
**********o****=0******

******v****=0******
**********v****=0******

******v****=60******
******v****=90******

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Influence of sub-pixel variability250 m vs. 1 km

- Cu clouds, cloud fraction = 0.9, SZA=33o

- mean1 km = 11.7
- mean250 m = 11.8
- std1 km = 8.3
- std250 m = 8.8
- std250 m->1 km = 8.5

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## _x0008_Estimate level and sign of uncertainties for each pixel 

- Asymmetry:
- 	1 km MODIS data
- Biases caused by neighboring pixels:
- 	Combine with theoretical simulations
- Biases due to sub-pixel variability:
- 	250 m MODIS images

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## 50 by 50 km example

- 51x51 km2 cloud fields over the North Atlantic (1305 UTC 1 Nov 2000) for SZA=75o.  Cloud fraction = 0.78 and mean tau=39.

- (%)

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Overall uncertainties for 50 by 50 km areas

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Wavenumber spectrum

- VIS
- Band 2

- NIR
- Band 7

- IR
- Band 11

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Wavenumber spectrum (cont.)

- MODIS, 250 m data
- 1024 x 1024 pxls

- MISR, 275 m data
- Nadir view
- 1024 x 1024 pxls

- Alexander Marshak & Tamás Várnai

- 07/22/2002

## Observations of 3D Radiative Effects in MODIS Cloud Optical Thickness Retrievals

**Alexander Marshak and Tamás Várnai **
- (UMBC/JCET and NASA/GSFC)