MULTI-LEVEL MODELING OF
PLUTO'S SURFACE AND
ATMOSPHERE
Young, Buie, Young & Olkin
Multi-level modeling of Pluto's surface
and atmosphere

Goal


Basic idea


Understand Pluto, make predictions for the New Horizons
flyby, and position ourselves to capitalize on funding for
Pluto research, which will be a hot topic for the next several
years
We have developed a new SwRI model of Pluto’s seasons,
which can be used in four papers with high impact.
Big Picture

This will establish the dominance of our group in seasonal
modeling of Pluto and other icy bodies, and interpretation
of their visible, thermal, and infrared data.
Technical background

Transport of Volatile N2
Between surface and
atmosphere
 From summer to winter


Observables
Visible appearance
 Temperatures
 Infrared (IR) spectra
 Time variation of these
quantities
 Context for New
Horizons

Role of volatile transport on Pluto



About a meter of N2 migrates each season.
Pressures vary by orders of magnitude over Pluto’s
season. The history of atmospheric pressure
depends critically on the location of the volatiles.
Volatile migration with albedo feedback probably
explains why Pluto has extreme albedo contrasts.
VT3D example 1 of 3:
Low thermal inertia, low N2 inventory
VT3D example 2 of 3:
Low thermal inertia, larger N2 inventory
VT3D example 1 of 3:
high thermal inertia, high N2 inventory
Proposal background
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
2010/2011: began numeric framework for threedimensional volatile transport (VT3D)
2012: submitted first model description paper
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2012: submited first data-driven paper

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Young 2012: Volatile transport on inhomogeneous surfaces:
I – Analytic expressions, with application to Pluto’s day
Young 2012, Pluto’s Seasons: New Predictions for New Horizons
Mostly compares modeled pressured with stellar occultation
constraints on time variability of Pluto’s atmosphere
This work used minor funds from NASA Planetary
Atmospheres, NASA Planetary Astronomy, Spitzer, New
Horizons.
Work proposed here for 2013/2014



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Apr-Jun 2013: submit VT3D paper & release code
Jul-Sep 2013: compare with visible data
Oct-Dec 2013: compare with thermal data
Jan-Mar 2014: compare with infrared data
Task 1: Disseminate VT3D model

Model Strengths
Speed
 Accuracy
 Flexibility
 Visualization
 Wide
applicability to
Pluto, Triton,
and Kuiper-belt
objects (KBOs)



Publish Model
Release code
Task 2: Compare visible data & model

Model
Color & albedo
depends on
terrain, age
 Variation with
latitude &
longitude


Constraining
Observations
Albedo
 Color

Task 3: Compare thermal data & model

Model
Emissivity
depends on
terrain, age,
deposition rate
 Variation with
latitude &
longitude


Observations

Thermal
lightcurves vs.
wavelength
and year
Task 4: Compare infrared data & model

Model



Spectra depends
on terrain, age,
temperature,
deposition rate
Variation with
latitude &
longitude
Observations

Spectra & band
depth vs.
longitude and
year
Timeline and milestones
April '13 May '13
Jun '13
Jul '13
Aug '13
Sep '13
Oct '13
Nov '13
Dec '13
Jan '14
Feb '14
Mar '14
VT3D dissemination (L. Young & PL1); 25% of project
Submit VT3D paper
VT3D paper in press
Comparison with visible observatons (M. Buie & PL1); 25% of project
Simulate visible data from VT3D
Submit visible paper
Visible paper in press
Comparison with thermal observations (E. Young & PL1); 25% of project
Simulate thermal data from VT3D
Submit thermal paper
Comparison with infrared (IR) observations (C. Olkin & PL1); 25% of project
Simulate infrared data from VT3D
Submit IR paper
Areas of risk and risk mitigation
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Risk: Competition by other volatile transport models

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
C. Hansen: revival of 1996 Pluto seasonal models
F. Forget: volatile transport element in Global Climate Models
New work relating to the safety of New Horizons risks delaying
the completion of our models, which opens us up to the danger of
being outstripped by others
Mitigation


VT3D is faster and more flexible than competitors models.
Use a mix of junior and senior scientists.


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1 hour of senior per 5.5 hour of junior personnel
Four well-defined, focused projects
Quick publication of high impact papers
Make code publically available to dominate this field
Benefits to SwRI

Establish a competitive edge for SwRI Pluto scientists
Develop and demonstrate state-of-the-art models
 Ensure high visibility


Capitalize on Pluto-related funding

A specific NASA Pluto Data Analysis Program is planned
 Competition
shows level of high importance and interest
of Pluto volatile transport

Experience shows that spacecraft encounters generate
interest (and funding). We expect NASA, NSF, and
telescope allocation committees will be favorably disposed
to proposals to study Pluto and related objects (Triton and
Kuiper-belt objects).