Developing a new general circulation model for planetary atmospheres - how (and why!) Claire Newman Kliegel Planetary Science Seminar March 1st 2005

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Developing a new general circulation model for
planetary atmospheres - how (and why!)Claire
NewmanKliegel Planetary Science SeminarMarch
1st 2005
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Overview of the talk

• What is a general circulation model (GCM)?
• Why develop a new model for planetary
  atmospheres what questions are we trying to
  answer?
• How is this new model being developed?
• Description of the base model the Earth-based,
  limited area Weather Research and Forecasting
  (WRF) model
• Description of the changes needed to globalize
  WRF
• Description of the changes needed to make
  planetary WRF
• Recent results and future work Earth, Mars and
  Titan

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What is a general circulation model (GCM)?
Generally is conceptually (and practically) split
into two components
physics
dynamics
Basically Newton II in 3 dimensions
force mass x acceleration (subject to mass
energy conservation)
Includes everything acting at a smaller scale to
the dynamics, all of which is represented
via parameterizations
You can actually write down the complete physics
of how air parcels move in a rotating frame
(ignoring relativity and quantum mechanics), even
if to solve the problem you need to make
approximations (like ignoring small terms,
working with a finite number of points, etc.)

• This includes
• Small scale turbulence
• Friction at the surface
• Absorption, emission and scattering of radiation

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Dynamics, e.g., the zonal (E-W) momentum
equation U, V, W wind in E-W, N-S and vertical
respectively, ? latitude, p pressure, ?
density, a planet radius, t time, X E-W
distance
Force / mass
Acceleration
DU 2?V sin? - 2?W cos? - UW Uv tan? -1 ?p
Fx Dt
a a ? ?X
Frictional force per unit mass - usually added in
during physics, as must be parameterized
Coriolis terms due to air parcel moving in a
rotating (not inertial) frame
Terms due to the coordinate system rotating
Pressure gradient force per unit mass

• Material derivative rate of change of U
  following an air parcel
• U U(t, x, y, z) gt ?U ?U/?t ?t ?U/?x ?x
  ?U/?y ?y ?U/?z ?z
• gt ?U/?t ?U/?t ?U/?x ?x/?t ?U/?y ?y/?t
  ?U/?z ?z/?t
• By definition, U ?x/?t, V ?y/?t and W ?z/?t
  
• gt DU/Dt ?U/?t ?U/?x U ?U/?y V ?U/?z W

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Examples of physics in a GCM
Radiative transfer in a planetary atmosphere
Temperature changes depend on heating rates,
which are determined from net fluxes, which in
turn depend on temperature gt many interconnected
equations and many methods of solving them to
find T(z)
Solar wavelengths
Absorption and scattering in
the atmosphere
Atmospheric layer
Atmospheric emission (T4)
Absorption and scattering in the
atmosphere
Thermal wavelengths
Absorption and scattering at the surface
Absorption and scattering at the surface
Surface
Surface emission (Tsurf4)
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Why do we need a new GCM for planetary
atmospheres?To understand this, you first need
to understandWhat questions do we want to
answer?
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Earth
Mars
Titan
N2 atmosphere Psurf 1.5x105 Pa Tsurf 93
K Thick haze layers Methane hydrology Slowly
rotating
CO2 atmosphere Psurf 610 Pa Tsurf 210 K Very
eccentric orbit Major topography Dust storms
N2 atmosphere Psurf 1x105 Pa Tsurf 288
K Water cycle Oceans land surfaces
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Onset and evolution of a Martian dust storm
Dust opacities for 2001 global storm from MGS TES
website
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Storm onset evolution multiscale feedbacks
Wind stress lifting ve feedbacks 1 - local scale
T increases inside dust cloud
Strong winds
Surface
Wind stress lifting ve feedbacks 2 - global
scale
Meridional circulation strengthens
Very strong associated winds and much more
dust lifting
Fairly strong associated winds and dust lifting
S pole
N pole
S pole
N pole
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Regions of interest on Mars
90N
60N
30N
0
30S
60S
90S
180
180
120W
60W
120E
0
60E
Tharsis strong slope flows Western boundary
currents on the eastern edge
Argyre and Hellas slope flows in region of
strong zonal winds and near cap edge
Northern plains relatively uninteresting
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Regions of interest on Mars
90N
60N
30N
0
30S
60S
90S
180
180
120W
60W
120E
0
60E
Potential areas of higher resolution
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The big questions for Mars (I)

• How do dust storms begin and evolve, and why do
  some become global?
• How do flows associated with the large topography
  interact with the global circulation?

Need higher resolution just in regions where
local slopes and circulations may be crucial
Must consider multi-scale feedbacks look at
local dust lifting and the effect on the local
and global circulation, which in turn affects
further lifting
gt Model with high resolution areas within global
domain, and information passing both ways (2-way
feedbacks)
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Interannual variability in Marss atmosphere
Storm season
Dust opacity
Brightness temperature
Storm season
Areocentric longitude Ls
Areocentric longitude Ls
From Liu et al. JGR 2003
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The big questions for Mars (II)

• What determines the variability in the Martian
  dust cycle and hence climate?
• What was the climate like in the past, does
  this help us understand present geological
  features?
• When and where was water stable at the surface,
  and where would subsurface water deposits be?

Need to look at interannual variability and/or
changes over long timescales
gt Need efficient and accurate (mass and angular
momentum conserving) model
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Clouds on Titan
Titan imaged over 9 days in the K filter
(centered at 2.12 ?m) which sees down to the
surface and troposphere, using the AO system at
Keck. (Images scaled to the brightest point in
each case.)
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The big questions for Titan (I)

• What controls when and where methane clouds form?

Want to use higher resolution just over regions
where clouds form now (and over other
cloud-formation regions in other seasons)
gt Need a model capable of placing high
resolution regions with the global domain
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Spinning up Titans atmosphere
The atmosphere can gain/lose angular momentum
from/to the surface When a GCM is spun up this
transfer must average to zero over a year
Results from the LMD Titan GCM, from Hourdin et
al., Icarus 1995
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The big questions for Titan (II)

• How much does interaction with the surface affect
  the atmospheric circulation?
• What determines the equatorial superrotation?
• How variable is Titans circulation and albedo
  (at different wavelengths) over the long Titan
  year?

A long Titan year and thick atmosphere (high
dynamical inertia) mean long spin-up times
gt Need a model which is fast, and accurate over
the integration times required
gt Experiments to explore sensitivities and study
variability take a long time
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The Weather Research and Forecasting (WRF) model

• Mesoscale (limited area) model for weather
  research and forecasting on Earth
• Developed by NCAR in collaboration with other
  agencies (NOAA, AFWA, etc.)
• Aim to produce a reliable mesoscale model, to be
  used for real-time forecasting and as a research
  tool, with improvements being worked into new
  releases

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Features of WRF
Mass in kg (x1018)

• Dynamics conserve mass
  and angular momentum
  - highly accurate
• Highly parallel code
  gt efficient
• Large suite of physics
  parameterizations and a
  modular form gt flexible
• Uses Arakawa C-grid

5.20354
5.20350
250
0
500
125
375
Days
V
V
V
T
T
T
U
U
U
U
V
V
V
T
T
T
U
U
U
U
V
V
V
U zonal (E-W) velocity point
T
T
T
V meridional (N-S) velocity point
U
U
U
U
T temperature / mass point
V
V
V
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Features of WRF (cont.)

• Nesting capability

Mother domain
Mother domain
Child 2
Grandchild
Child
siblings
Child 1
1-way nesting
2-way nesting

• 2-way nesting capability

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The usual approach - how mesoscale WRF runs
b) its initial and boundary conditions being
provided by a separate global model
a) place nests within a mesoscale model (WRF),
with
Separate global model
WRF
Drawbacks

1. Interface between global and mesoscale models is
   one-way gt no feedbacks from small to larger
   scale
2. Unless specially designed to match, often have
   different dynamics and/or physics - inconsistent
3. Interface is also messy, e.g., must view output
   from the two models using different tools

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Globalising WRF gives a highly accurate
efficient global model, in which we can place 1-
2-way nests
So we are basically using WRFs nesting abilities
to nest all the way down from global
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Changes required for global WRF

• Allow use of a latitude-longitude grid

WRF is set up for conformal rectangular grids
(such as polar stereograhic) where the map to
real world scaling factor is the same in the x as
in the y direction
We still need a rectangular grid, but one which
will reach from the south to the north pole gt
lat-lon grid
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If dx gap between grid points in map
coordinates, and dX actual distance (in
meters), then dX (1/mx) dx and
likewise dY (1/my) dy
Original WRF
Global WRF

• Lat-lon grid gt x a?, y a?,
• gt dx a d?, dy a d?,
• whereas dX a cos? d?, dY a d?
• gt mx dx/dX sec?, my dy/dY 1
• gt mx ? my
• gt Needed to identify which map scale factor was
  required in all equations where m appeared, and
  reintroduce map scale factors where they
  previously cancelled (so were omitted)

Conformal grid gt for all map projections
available (mercator, polar stereographic, etc.),
mx my at all points gt Only one map scale
factor (m) used, and omitted altogether when mx
and my cancelled
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Changes required for global WRF

• Deal with polar boundary conditions

V
V
Place v points at poles, with v there
0 Nothing is allowed to pass directly over the
poles - atmospheric mass is pushed around the
pole in longitude instead - and no fluxes can
come from the polar points when calculating
variables
U
U
U
T
T
V
V
T
T
U
U
U
V
V

• Deal with instabilities at the model top

The basic mesoscale WRF model generally only
reached a maximum of 30km, plus was regularly
(and frequently) forced by a separate
GCM However, standalone global WRF will
develop upper level instabilities due to spurious
wave reflection at the model top if these are not
damped in some way - we must therefore introduce
a sponge layer
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Changes required for global WRF

• Avoid instabilities due to E-W distance between
  grid points becoming small near poles

• This is a problem due to the CFL (Courant
  Friedrichs Lewy) criterion
• ? t lt ? x / U where U is the fastest
  moving wave in the problem
• gt As ? x -gt 0, ? t must -gt 0 also,
  which is very expensive
• gt a) Use a small ? t (far less than needed to
  satisfy at the equator), OR
• b) Increase largest effective scale ? x by
  filtering out smaller
• wavelengths (e.g. retaining only
  wavenumber 1 at the pole itself)
• Usual method in GCMs is to use a
  polar Fourier filter

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Changes for planetary WRF
Models are generally very Earth-specific!

• Remove hardwired planet-specific constants -
  instead use parameters which vary with planet
• Change Earth time to general planet time
• Allow orbital parameters to be specified
• Add physics parameterizations where needed

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Results for Earth (up to 3.)

1. Solid-body rotation test (for a non-rotating
   planet!) including solid body rotation over the
   poles
2. Held-Suarez standard test of a dynamical core
   Newtonian relaxation to typical tropospheric
   temperature profiles with Rayleigh friction
   (winds slowed towards zonal mean) increasing with
   height
3. Polvani-Kushner extension to Held-Suarez added a
   simple stratosphere with cooling over winter pole
   
4. Further testing to look at wave propagation etc.

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1. Initial wind pattern for solid body rotation
over the poles
North pole
North pole
South pole
South pole
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Wind pattern after 1 1/2 days
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Wind pattern after 4 1/2 days
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2. The Held-Suarez test a. Zonal mean T
averaged over last 1000 days
Global WRF
Expected result
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2. The Held-Suarez test b. Zonal mean u
averaged over last 1000 days
Global WRF
Expected result
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3. Polvani-Kushner - in initial stages (up to 380
days, but need average over last 9000 days of
10000 day experiment)
Zonal mean u in global WRF at 380 days
Expected zonal mean u (average over last 9,000
days)
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Results for Mars (up to 3.)

1. No CO2 condensation, no atmospheric dust, no
   topography, diurnally-averaged heating
2. Added topography, diurnal cycle
3. Mars with a realistic (but prescribed)
   atmospheric dust content and with a CO2 cycle
4. Mars with interactive dust lifting and transport
5. High resolution nests over Hellas, Tharsis, etc.

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Northern summer solstice GFDL Mars GCM and
WRF without dust
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Northern summer solstice Oxford Mars GCM and
WRF without dust
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Southern spring equinox GFDL Mars GCM and
WRF without dust
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Ls 190 global WRF zonal mean T, u wind
MGS TES zonal mean T
MGS TES zonal mean u
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Results for Titan (up to 1.)

1. Prescribed haze distribution
2. Include interactive haze production and transport
   using a microphysics scheme
3. Add methane cloud microphysics
4. Introduce photochemistry schemes

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1. Prescribed haze distribution some results we
   will compare with

Northern winter solstice
Northern spring equinox
a. Meridional streamfunctions produced by the LMD
Titan GCM
b. Zonal mean zonal winds produced by the LMD
Titan GCM
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Conclusions

• Global, planetary WRF is a highly efficient and
  accurate global model in which high resolution
  2-way nests can be embedded
• It has performed (and is performing) well in
  general tests (e.g. mass conservation) and tests
  used for other Earth GCMs (e.g. Held-Suarez)
• Initial Mars results (no dust or CO2 cycle) match
  those from other Mars GCMs

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Conclusions

• Ongoing work includes Mars with realistic dust
  and a CO2 cycle, and spinning up Titans
  atmosphere (including running in parallel on a
  beowulf cluster)