MODIS Level 3:

Future Issues and Considerations

Brent Maddux

MODIS Level 3:

Future Issues and Considerations

Brent Maddux

2001-2004 Cloud Fraction Mean 1

0.5

0

⺋ Do they represent known physical phenomenon well?

⺋ What is L3 saying? ₪ Some limitations of L3 SDSs ₪ How do we interpret the data effectively?

⺋ decrease the limitations ⺋ improve physical meaning and interpretation

How do the MODIS L3 products look:

Going from information to knowledge:

Next steps:

DJF High Cloud DJF All CloudHIRSHIRS

Aqua

TerraTerra

Aqua

1.0

0.8

0.6

0.4

0.2

0.0

Dust or high aerosol events

200 400 600 800 1000mb

Cloud Top Pressure May 1st, 2003

₪ Events last several days

₪ Few if any visible clouds

₪ 750-900 mb

₪ For daily data this can be accounted for, but not weekly or monthly.

0 200 400 600 800

Aqua

Terra

Difference

-800 -400 0 400 800

Cloud Ice Water Path December 2002

Major ice cloud events?

g/m^2

g/m^2

0 150 300

Difference

Cloud Liquid Water Path December 2002

Aqua

Terra

g/m^2

g/m^2

-150 0 150

Major liquid cloud events?

Possible Solutions:

0 15 30

Ocean Mass Concentration

₪ Conduct secondary data processing

₪ Remove questionable data

₪ Create uncertainty products

0 500 1000

Cloud Top Pressure

1x10^-6 g/m^2

mb

0 15 30 45 60

µm

0 200 400 600 800

0 250 500 750 1000

g/m^2

mb

Ice Particle Size and Tropical Deep Convection Evolution

-Uniform re ice over cores

-Isolated deep convection

-Evident cirrus shields

₪ Ice particle size increase away from deep convection

Ice Particle Radius

Ice Water

Path

Cloud Top

Pressure

₪ What would scatter plots show?

Mean SDS Comparisons

₪ Mean phase properties can’t be fully characterized

0 15 30 45 60

0 15 30 45 60

Ice Effective Radius (µm)

Clo

ud T

op P

ress

ure

(m

b)

Ice Effective Radius (µm)

Wate

r Path

of

Ice

(g/m

^2

)0

1

00

0 2

00

0

0 5

00

10

00

IWP vs Re Ice

CTP vs Re Ice

₪ cloud regimes

₪ cloud height or phase

₪ particle size or path

Ambiguous

Property comparison limitations:

₪ data subsets (large particle size, phase, etc)

₪ multiple data set comparison

Possible solutions:

₪ new joint histogram (in collection 5)

₪ means of property subsets

₪ multi dimensional histograms

Mean Ice Properties:

Summary and Conclusions:

₪ Implement a secondary processing between L2 and L3.

₪ Add additional SDSs

1) that can be used to further compare the microphysical properties of clouds and other atmospheric parameters

2) that allow for a further intuitive interpretations

3) near nadir.

Image courtesy of MODIS Rapid Response Project at NASA/GSFC

Nov 2001

October 2002