Improving MISR-retrieved Aerosol Properties Using

GOCART Simulations

Yang Liu, PhDJune 3, 2015

St. Louis, MO

Co-authors

Shenshen Li, Emory, now at CAS Ralph Kahn, GSFC and MISR Science Team Mian Chin, GSFC Michael J. Garay, MISR Science Team

Introduction Aerosol model definitions are a

key factor in aerosol retrieval Operational retrievals pre-

defines aerosol models globally. Better retrievals can be made with local obs, but this requires extensive ground data support

CTMs can provide aerosol composition and optical properties at regional–to-global scales with complete coverage

Introduction

Research Objective

The operational algorithm: MISR EOF algorithm reduces the impact of surface

reflectance on aerosol retrieval. Defines 74 mixtures, which are combinations of up

to 3 aerosol components (out of 8). Selection of successful mixtures is not constrained

by any prior information. Conflicting mixtures can pass its retrieval criteria.

Goal: a post-processing technique to refine MISR-retrieved aerosol microphysical properties using GOCART aerosol simulations

Method

3. Recalculate aerosol optical properties with new mixtures

4. Compare updated results with AERONET observations

𝑫𝒊𝒇 𝒇 𝑨𝑵𝑮=¿𝜶𝑴𝑰𝑺𝑹−𝜶𝑮𝑶𝑪𝑨𝑹𝑻∨≤𝛆𝑨𝑵𝑮

𝑫𝒊𝒇 𝒇 𝑨𝑨𝑶𝑫=|𝑭𝒓𝒂𝒄𝑴 _ 𝑨𝑨𝑶𝑫−𝑭𝒓𝒂𝒄𝑮 _ 𝑨𝑨𝑶𝑫|≤𝛆𝐀𝐀𝐎𝐃

1. Calculate the ANG and AAOD differences between each successful MISR mixture and GOCART simulations

2. Rank Diffs below a combo of regional thresholds

Datasets

MISR Level 2; Version 22; 17.6x17.6km AERONET Level 2; AOD 32 sites; AAOD 18 sites GOCART 1x1.25 degree

SO4, BC, OC, dust, sea-salt

Domain & period: 2006~2009, Continental U.S.Parameters: AOD, ANG, Absorbing AOD (AAOD)

Selection of the Thresholds

For the best agreement of adjusted MISR retrievals with AERONET, we set and to 30% and 50%

Note: specific to the entire dataset. The selection process can be automated and more specific.

Validation of MISR and GOCART dataComparison with Operational MISR Data

Spatial Patterns - ANG

The adj. MISR ANG is similar to GOCART in the west and in spring and summer, and is similar to MISR in the east and in fall and winter

Results

Spatial Patterns - AAOD

GOCART lacks spatial contrast so our AAOD distribution is similar to MISR but has lower values

Results Cont’d

Conclusions

• A post-processing technology was developed to refine MISR retrieved aerosol properties over land with GOCART simulations.

• It improved ANG and to a lesser extent AAOD without compromising the quality of AOD

• This is a proof-of-concept work for improving satellite aerosol retrieval algorithm from the static to dynamical look-up table approach.

For details, see Li et al. (2015), Atmos. Meas. Tech.

Summary