Steve Platnick1, Gala Wind2,1, Zhibo Zhang3, Hyoun-Myoung Cho3, G. T. Arnold2,1, Michael D. King4 , Steve Ackerman5, Brent Maddux5

1NASA Goddard Space Flight Center, 2SSAI, 3U. of Maryland Baltimore County,

4U. Colorado/LASP, 5U. Wisconsin, Madison

AGU Fall MeetingA44B

6 Dec 2012 San Francisco, CA

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples

from MODIS Collection 6 Development Code

What is a Cloud: The Pixel-Level Choices Algorithm Developer’s Make- Explicit (partly cloudy pixel filtering by the developer) - Implicit (filtering invoked by retrieval failures)

Sensitivity of Cloud Optical Property Retrievals to Choices- Sampling fraction, τ, re

Outline

Cloud

Clear

What Do We Mean by a Cloud Mask?Ideal pixel

Clear

What Do We Mean by a Cloud Mask?

Cloud

Clear

Clear

Overcast

Clear Sky

Partly Cloudy

Cloud

Clear

Clear

SatelliteCloud Mask

(likelihood of “Not Clear”)

What Do We Mean by a Cloud Mask?

MODIS Cloud Pixel Filtering Choices: Explicit & Implicit

Masked asClear &Not Clear

Total Numberof Pixels(1 km)

=

Developer Choices Retrieve edge/250m partly cloudy pixels? Provide a τ-only retrieval when multispectral retrievals fail?

Not Clear Categories: Overcast (?) Cloud Edge 250m “hole” Possibly heavy smoke/dust, glint?

Explicit filtering

Retrieval Outcomes: Successful τ & re No τ or re possible τ only (ignore re

spectral information)?

Implicit filtering

Cloud Pixel Filtering/QA Choices: C5 Granule Example1 April 2005, MODIS Aqua

MODIS 250/500 m composite

Cloud Pixel Filtering/QA Choices: C5 Granule Example1 April 2005, MODIS Aqua

Clear Sky Restoral Flags

cloudedges

250m partly cloudy pixels

spatial/spectral tests (glint, dust, smoke)

MODIS 250m Heterogeneity global analysis, low maritime water clouds

Pix

el C

ount

s

1.00.01 0.1

1km cloudedges

250mpartly cloudy

1km cloud edge &250m partly cloudremoved

3D artifactsmore likely

Pixel Filtering: Retrieval OutcomeTerra MODIS April 2005, maritime water clouds

CTP ≥ 680mb, ±30° latitude

Successful COT & re

COTre (2.1 µm)

Successful COT & re

COTre2.1 – re3.7

Pixel Filtering: Retrieval OutcomeTerra MODIS April 2005, maritime water clouds

CTP ≥ 680mb, ±30° latitude

Retrievals consistent w/breakdown of 1D forward model

• 44% of cloudy pixels are associated w/edges or designated as partly cloudy by the 250m cloud mask

• 40% of edge/partly cloudy pixel retrievals fail (simultaneous COT and re solution fall outside LUT space)

Successful COT & re

Failure (minor)Failure (major)

Pixel Filtering: Sampling StatisticsTerra MODIS April 2005, maritime water clouds

CTP ≥ 680mb, ±30° latitude

Pixel Filtering: Retrieval OutcomeSEVIRI, 15 min imagery, 11 August 2009, maritime water clouds

CTP ≥ 680mb, ±30° latitude, ±55° VZASuccessful COT & re

COTre (1.6 µm)

Successful COT & re

Failure

Fraction of Population (%)

20% of cloudy pixels are associated w/edges, 68% of those retrievals fail

Pixel Filtering/QA Choices: Global Mean SensitivityCloud Retrieval Difference: with edge/250m filtering – w/out

τ

re,2.1

∆τ=±4

∆re,2.1=±2 µmApril 2005, MODIS Terra

Summary (1)• Tropical/subtropical marine warm cloud partly-cloudy retrievals

(edge pixels and those identified by 250m observations) are biased w.r.t. the filtered pixel population.- Biases are consistent w/breakdown of 1D cloud model.- Retrievals will not correctly describe interaction of the cloud

with the radiation field, microphysics, or derived water path.- Frequency of these pixels depends on the spatial scales of the

satellite observations and the clouds.

• MODIS Cloud Product - Collection 5: These pixels were removed/filtered (“Clear Sky

Restoral” algorithm).- Collection 6: Will attempt retrievals on these pixels. Allow

users to explore the consequences of the partly cloudy categories. Regardless, a significant fraction of such retrievals “fail” for the latitude zone studied.

• All algorithms do consider the suitability of a pixel/FOV for use with the forward model – either explicitly or implicitly.

• Spatial heterogeneity and related sampling issues ARE NOT unique to the MODIS product.- Other satellite sensors have similar issues and consequently

inherent sampling biases for low marine clouds, e.g., CloudSat [Zhang et al., A33G], microwave imagers, etc.

- How to communicate to this to the variety of users is a challenge.

Summary (2)