investigating titan’s surface-atmosphere interactions with a general circulation model claire e....

Investigating Titan’s Surface-Atmosphere Interactions with a General Circulation Model

Claire E. Newman,Mark I. Richardson and Yuan Lian

Ashima Research, Pasadena, CA

Why a General Circulation Model (GCM)?

• Atmospheric processes involve non-linear interactions and feedbacks => related phenomena can be complex, and hard to predict using theory or simple models

• To fully understand surface phenomena linked to the atmosphere, we must model the full 3D circulation

• Titan GCMs have uncertainties in physical processes / parameters (e.g., strength of sub-grid scale mixing) and boundary conditions (e.g., surface properties)

• We can use comparison between GCM predictions and observations to constrain and refine the GCM, and thus improve our knowledge and understanding of real Titan

Surface Phenomena Examined Here1. The observed seasonal variation in surface methane, and

estimated evaporation/precipitation rates– These depend on atmospheric transport, cloud processes, and the

atmosphere-surface exchange of heat and methane

– We use a simple methane cycle scheme in our GCM, TitanWRF:

• Surface evaporation• Atmospheric transport (advection and mixing)• Atmospheric condensation followed by instant deposition

[unless sub-saturated layers exist below, in which case sufficient condensate is re-evaporated to saturate them]• Surface precipitation of any condensate that remains• Latent heating effects and finite surface methane abundances

Shortwave heating into the surface as a function of latitude and time of year (Ls)

Newman et al. Icarus 2013, in review

Titan has a tilt, timing of perihelion, and seasons that are in many ways similar to Earth


Present day perihelion

Infinite surface methane

No latent heating effects


Surface temperature as a function of latitude and time of year


Northern spring (Ls=0-30°) Northern summer (Ls=90-120°)

Northern autumn (Ls=180-210°) Northern winter (Ls=270-300°)

Tropospheric mass streamfunctions


Peak upwelling speed in the troposphere



Peak low and mid-latitude upwelling follows the approximate path of the Inter-tropical Convergence Zone (ITCZ) where main Hadley cell branches converge and rise



Even stronger upwelling at high latitudes in late winter through into early summer



Even stronger upwelling at high latitudes in late winter through into early summer

Polar cells producing strong high latitude upwelling are greatly enhanced in TitanWRF with strong stratospheric superrotation


Meridional divergence in the lowest layer


Methane distribution in the troposphere

Column abundance (in kg m-2) Lowest layer mole fraction


Methane distribution in the troposphere

Column abundance (in kg m-2) Lowest layer mole fraction

Strong upwelling in late spring depletes near-surface methane


3 Titan years of evaporation and precipitationEvaporation rate (in mm per Earth hour)

Precipitation rate (in mm per Earth hour)




Peak evaporation in late spring through early summer


Resultant change in surface methane over timeChange (in mm) from value at start of simulation (~6 Titan years earlier)

Infinite surface methane simulations indicated that low and mid-latitudes tended to dry out, while high

latitudes tended to gain methane [as in Mitchell 2008]

Re-ran simulation starting with finite, globally-uniform surface methane cover equivalent to ~11m depth

Finite surface methane

Still no latent heating effects

Results shown for years after simulation reached steady state

=> no long-term change in surface methane distribution




Condensation (cloud) still occurs in low and mid-latitudes, but all the condensate re-evaporates before reaching the surface


3 Titan years of surface methane (in mm)


The steady state surface methane distributionSurface methane changes over the entire simulation

Titan years from start

Green line shows surface methane decrease equatorward of 60°

Red line shows surface methane increase north of 60° N

Blue line shows surface methane increase south of 60° S

In steady state, north pole has

~50% more methane than

south


The steady state surface methane distributionEvaporation, precipitation and net change over the last 3 Titan years

Planetocentric solar longitude, Ls (deg)

Evaporation N of 60° NPrecipitation N of 60° NNet N of 60° N

Evaporation S of 60° SPrecipitation S of 60° SNet S of 60° S

Results did not include evaporative cooling at the surface, or evaporative cooling / condensational heating in the atmosphere – i.e., there were no latent heat effects

Finite surface methane

And latent heating effects


3 Titan years of condensation and precipitationColumn-integrated methane condensate (in kg m-2 over 8 Titan days)





*

* * *

* *

Times and locations of rainfall inferred from ISS observations

*

* * *

* *




Only the strongest upwelling and condensation events result in surface precipitation


3 Titan years of surface methane (in mm)


Surface temperatures and evaporative coolingNo evaporative cooling With evaporative cooling

Evaporative cooling + higher surface thermal inertiaIncluding latent heating modifies the surface heat balance and produces much larger Tsurf gradients (and lower mean Tsurf) than observed

The (currently uniform) surface thermal inertia is one of many parameters that impact this => may perhaps be constrained by comparison between modeled and observed Tsurf


Impact of reversing timing of perihelionCu

mul

ative

mas

s ch

ange

(kg)

Present day timing (just after southern summer solstice)

‘Reversed’ timing (just after northern summer solstice)

Green line shows surface methane decrease equatorward of 60°

Red line shows surface methane increase north of 60° N

Blue line shows surface methane increase south of 60° S

North gains relative to south

South gains relative to north

Methane cycle conclusions• TitanWRF shows partial match to several aspects, including

evaporation rates and cloud and rainfall observations

• We predict more surface methane in northern than in southern high latitudes, with this reversed when perihelion is switched from southern to northern summer

• In TitanWRF, this is basically due to more high latitude evaporation during the warmer (perihelion) summer

• Ongoing work involves the improved treatment of cloud physics and methane’s behavior at/below the surface, before using observations to constrain the model further

Surface Phenomena Examined Here1. The observed seasonal variation in surface methane and

estimated evaporation/precipitation rates

2. Observed dune characteristics

– Dunes are the time-integrated result of a non- linear, threshold-dependent, wind-driven process (saltation)

– We predict dune orientations using the Gross Bedform-Normal Transport (GBNT) approach

– We predict the direction of dune migration / motion using the net (resultant) sand transport direction over a Titan year

Predicting Titan dune characteristics

• Expect overall direction of motion / migration to be roughly the resultant transport direction R

• R at any given time depends on– the choice of threshold wind stress

for saltation to occur, and– the sand flux formulation

• R is then summed over a full Titan year to give the long-term resultant transport direction

Predicting direction of dune motion in a given wind field:

See Rubin & Hunter, Science, 1987 for a full description of the GBNT approach

• Basic concept: dunes form due to sand transport in both directions across bedform

• => Dunes will be oriented such that the total transport across the dune crest is maximized

• Total transport = |B|+|C| summed over entire year = Gross Bedform-Normal Transport

• Also depends on threshold and sand flux formulation

B

C

Predicting dune orientations in a given wind field:

Predicting Titan dune characteristics

Dune crest orientation & resultant transport direction predicted for a threshold of 0.014Pa and no topography

• Very little eastward resultant transport (very few eastward-pointing black arrows) equatorward of 25°• => Almost all dune motion expected to be toward the west

But if we include topography into TitanWRF…

An extrapolated ‘plausible’ global topography map based on Cassini Radar data (pre Lorenz et al.’s 2013 map, which we will use next)

[data provided by Karl Mitchell and Jeff Andrews-Hanna]

30°N

30°S

0°

from Lorenz and Radebaugh

Dune conclusions• Interaction between dunes and topographic obstacles

hypothesized to imply largely eastward dune movement

• Topography + higher thresholds can produce more predicted eastward resultant transport

• However, predicted dune crest orientations are less consistent with observations for these conditions

• Predicted dune morphology (based on relationship between predicted orientation and resultant transport direction) is also less consistent with dunes observed

investigating titan’s surface-atmosphere interactions with a general circulation model claire e....

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