# Presentation: 726136

## Using MODIS and MISR Observations to Retrieve Cloud Phase and Ice Cloud Habit

- Sally McFarlane and Roger Marchand Pacific Northwest National Laboratory

## Introduction

- Cloud phase and habit are fundamentally important to remote sensing and climate simulations
- GCM studies have shown that treatment of habit is significant, especially in tropics (Kristjansson et al., 2000)
- Satellite and ground based retrievals of cloud properties depend strongly on habit assumptions

## Put MISR Multiple Angles to Work

## Procedure

- Retrieval combines multi-angle information from MISR blue (.446 um) band with MODIS 2.1 um band for sensitivity to shape and size
- Retrieve best fit re, IWP, and crystal habit by minimizing deviation between modeled and measured reflectance over all cameras
- Ice cloud scattering properties from Yang et al. (2000) assuming gamma distribution with fixed effective variance and given re

## Case Study 1: Cirrus at SGP

| Habit | Metric | Reff | IWP |  |
| --- | --- | --- | --- | --- |
| Hollow Columns | 0.032 | 27.6 | 51.3 | 3.3 |
| 4-Bullet Rosettes | 0.039 | 27.4 m | 54.5 | 3.5 |
| Rough Aggregates | 0.041 | 37.5 | 63.5 | 2.9 |
| Plates | 0.046 | 22.5 | 62.1 | 4.8 |
| Water | 0.085 | 100 m | 364 | 5.7 |
| MODIS |  | 29.7 m | 77.0 g/m2 | 3.5 |

- Retrieval Results

## Case Study 2: Altocumulus at SGP

- Water is best fit; MODIS retrievals indicate mixed phase cloud; ARM microwave radiometer shows LWP of 40-80 g/m2
- Altocumulus actively growing as it moved over the ARM site; likely to have water at top of cloud
- Need sensitivity studies to determine depth in cloud to which retrieval is sensitive

## Current Work

- Beginning to run operationally, rather than in case study mode
- Created look-up table of MISR/MODIS reflectances as a function of habit, water path, effective radius, cloud height, solar and viewing geometry
- For each retrieval, correct reflectances for atmospheric transmittance and surface albedo
- Run retrievals on (10km)2 boxes; average MISR/MODIS reflectances and MODIS cloud properties over box
- Preliminary results for all MISR overpasses of SGP in 2001; 32 cases with clouds and available MISR + MODIS data
- Beginning comparisons with MOD06 retrievals; trying to understand differences

## Thick Cloud Retrieval Example

## Thin cloud retrieval example

## Summary of Retrieval Statistics

## Metric is measure of relative deviation from observed reflectance; metric = .05 implies matching reflectance within 5% on average
Metric increases with decreasing optical depth due to:
Averaging of reflectances
MISR parallax issues
Effect of surface albedo

- Metric increases with decreasing optical depth due to:
- Averaging of reflectances
- MISR parallax issues
- Effect of surface albedo

- How do we identify when retrieval performs well?
- Retrieval Metric
- Optical Depth
- Variability in reflectances

## Future Work

- Understand differences with MOD06 cloud property retrievals
- Develop automated statistics to determine where retrieval is performing well
- Look at effects of vertical structure; habit mixtures
- Compare retrieved IWP/effective radius to radar retrievals at ARM site
- New radar retrievals which use reflectivity and Doppler velocity can retrieve vertical profiles of Re and IWC (Mace et al., 2002)
- Retrievals are sensitive to crystal habit because particle fall speed and effective density depend on habit
- Constraining the particle habit reduces the uncertainty in the radar retrievals
- Look at retrievals over ocean to extend to lower optical depths
- Include realistic surface albedo from MOD43 product