FIM Cloud Visualization for SOS and TerraViz

Steve Albers

Team Members

Jebb Stewart

Eric Hackathorn

Julien Lynge

Bob Lipschutz

Judy Henderson

Visualization Overview – Simulated VIS

• Assume both sun and viewpoint are overhead

at all points on the sphere

• Cloud Albedo derived from model data is

combined with multi-spectral land albedo

inferred from NASA’s Blue Marble image

• Simulated VIS provides best realism to produce

an “animated Blue Marble” (more so than IR)

• Physically and Empirically based for best

efficiency and reasonable accuracy

Visualization Technique• Vertically integrated hydrometeor fields are

computedo Cloud liquid, cloud ice, rain, snow, graupel (as

available)

o A.k.a. liquid/ice water path (LWP/IWP)

o Units can be either kg/m**2 or m (based on water

density)

o FIM presently groups everything into cloud liquid

• Convert LWP/IWP into optical depth

o Use typical values of droplet/crystal size (re) and

density for each type of hydrometeor (ρ)

o Account for lower density of snow or graupel

o τ ≈ (1.5 LWP)/(reρ) (Stephens 1978, with ρ term

added)

Scattering of Sunlight by Clouds & Precip

•Calculate fraction of incident sunlight scattered

upward

○ Based on optical depth and backscattering efficiency

•Backscattering efficiency

○ Ratio of backscatter coefficient to extinction coefficient

○ .063 for liquid, .14 for cloud ice or snow, 0.3 for

graupel

○ Low values explain why clouds can look opaque yet still

darker gray as seen from above

Cloud / Precip Scattering - II• Apply equation to yield cloud albedo (a) using

optical depth (τ) and backscatter efficiency (b)

○ a = τ / (τ + 1 / b)

○ Reproduces figure in Mishchenko et. al. (1996) within a

few % (for non-absorbing clouds)

○ Works with cloud liquid and cloud ice (random fractal

crystals)

○ Reduces to expected relationship: a = τ × b for small

values of τ

Cloud / Precip Scattering - III

•Cloud albedo definition and assumption

○ Top Of Atmosphere (TOA) albedo (fraction of sunlight

scattered upward by clouds) assuming dark surface

•TOA albedo (at) used for visualization

○ Combine cloud albedo (ac) derived from FIM with

ground albedo (ag) from NASA’s Blue Marble image

○ Consider cloud semi-transparency and multiple

reflections between ground and cloud

○ at = ac + (1 – ac)2 × (ag ⁄(1-acag))

○ Equivalent to equation (12) in Stephens (1978)

○ Using just cloud albedo (ac) in a linear fashion with ag

(e.g. in TerraViz) would introduce a further

approximation

Use of Blue Marble Image•Pros

○ The high resolution Blue Marble image allows for finer

detail to be shown (10km resolution), compared with

the FIM at ~13km

○ Allows for visualization in color

○ Blue Marble RGB values accurately convert to albedo

(still to do)

○ Allows for more accurate blending of cloud albedo and

ground albedo, compared with a simple overlay

○ Relatively simple and efficient, already demonstrated

•Questions / Cons

○ Wouldn’t use TOA (total) albedo or outgoing short-

wave (if available) from model

○ Wouldn’t allow “progressive disclosure” compared with

an overlay

Potential use of cloud overlay

•Pros

○ Can allow very high resolution (much less than 10km)

for land

○ Ease of use with layering in TerraViz

•Questions / Cons

○ Can it “blur” the land underneath translucent clouds

when scales go finer than ~10km?

○ Can it consider more accurate calculation of TOA (top

of atmosphere albedo), based on cloud & ground

albedo?

Implementation

•Case study with 3-D cloud water from FIM

○ Shown recently at AMS conference

○ 700MB of input for each of 168 time steps

○ Takes ~2.5 hours to process in IDL on SOS server

○ Will rerun to include recent refinements

•Speedup of processing for real-time runs

○ Precalculate vertically integrated hydrometers (i.e.

LWP)

○ About 40 times less data for ITS to write to /public

Implementation - II•Should we switch to a more rigorous RTM?

○ Would be more somewhat more accurate, particularly

when NIM comes online with improved microphysics

○ Would TOA or cloud albedo already be available from

RTM output within the FIM/NIM?

○ Can it be configured for a “sun/viewer always

overhead” setup

○ Consider just cloud albedo output to merge with higher

resolution multi-spectral land surface (e.g. Blue

Marble) data, or alternatively with “progressive

disclosure”

○ Would it allow for visualization in color (if multi-

spectral radiances are available)?

○ Separate radiation package (e.g. CRTM)?

○ What are computational resource needs?

References

Stephens, G., 1978: Radiation Profiles in Extended Water Clouds. II: Parameterization Schemes. J. Atmos. Sci. , 35, 2123-2132

Mishchenko, M., Rossow, W.B., Macke, A., 1996: Sensitivity of cirrus albedo, bidirectional reflectance, and optical thickness retrieval accuracy to ice particle shape. JGR, 101, 16973-16985

Backup Slides

Other Wavelengths?•11μ IR also shown at AMS

○ Less physically consistent with Blue Marble (visible)

○ Simplified approach works well for brightness

temperatues

○ Model OLR converted to brightness temperature with

Stefan-Boltzmann relationship, then a linear correction

applied

○ Agrees within 5-10K with satellite observations

•3.9μ, 6.7μ, 13μ, etc.

○ More impacted by various absorption lines, etc.

○ RTM more needed and appropriate