Transcript Slide 1

Modelling the Thermosphere-Ionosphere
Response to Space Weather Effects: the
Problem with the Inputs
Alan Aylward, George Millward, Alex Lotinga
Atmospheric Physics Laboratory
University College London
Using Global Circulation Models as a
Forecasting Tool:
• First you need to develop a global model of the upper atmosphere
• Then you need to drive it by external inputs in a realistic way
• If the physics is right it should simulate the “real” atmosphere and any
transmitted effects
• From this grew the idea of forecasting - or at least “nowcasting”. Can
you input data from, say, a solar wind monitor and predict the
ionospheric response?
• This takes “Space Weather” into the realm of “Space Weather
Forecasting” with many of its concomitant conditions
• We enter the world of data assimilation: the inputs define our accuracy
CTIP/CTIM Properties
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3-dimensional, time-dependent
Solves equations of momentum, energy and continuity for ions and neutrals
80-500km thermosphere, 110-10,000km for the ionosphere and plasmasphere
Resolution 2 degs latitude, 18 degrees longitude by 1 scale height altitude. 3060 seconds time resolution
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3 neutral constituents (O, O2, N2) and 2 ions (H+, O+)
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Wave forcing at the lower boundary(80km)
Self-consistent dynamo calculations
“Standard” input of magnetosphere-ionosphere coupling
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An empirical model of high-latitude convection gives the polar cap
electric field pattern.
Many exist - Heppner and Maynard, Foster, Weimar, Heelis, Rich
and Maynard
We use magnetospheric inputs based on statistical models of
auroral precipitation and electric fields from Tiros and Foster (FullerRowell
1987 and Foster 1986).
These inputs are linked to a power index based on TIROS/NOAA
auroral particle measurements.
Coupled Thermosphere Ionosphere Plasmasphere model (CTIP)
Atmospheric temperature changes due
to dynamic Auroral forcing
(i.e., Magnetic Storm)
Global gravity wave propagation
green/red +20K, blue -20K
QuickTime™ and a
Cinepak decompressor
are needed to see this picture.
But complications continually arise: the response to storms is not simple:
April 1997 Storm event
TEC enhancement
(particle
precipitation)
Dusk effect
(neutral
winds)
Total Electron Content (TEC) change
Negative
phase (neutral
gas
composition)
But how
realistic
are the
inputs?
SuperDARN
Super Dual Auroral Radar Network
Southern
Hemisphere
Northern Hemisphere
Joule heating from CTIP model runs
Empirical electric fields
Electric field input derived from
SuperDARN
QuickTime™ and a
PNG decompressor
are needed to see this picture.
QuickTime™ and a
PNG decompressor
are needed to see this picture.
So what else is needed?
• We can input SUPERDARN fields at 2 minutes
resolution
• But there is a precipitation pattern on top of this
• Where can we get that from? Getting matched
precipitation and electric field has long beena
problem for GCMs
OVATION model
Predicts location of auroral oval
and maps magnetospheric
boundaries onto the ionosphere
Uses:
a) DMSP satellite particle data
b) SuperDARN convection
patterns
c) All-sky imaging camera
OVATION datasets (http://sd-www.jhuapl.edu/Aurora/ovation/datasets.html)
• However even given these we still need a dense
network of stations to constrain the empirical
inputs
MIRACLE:
Magnetometers,
Ionospheric Radars,
All-sky Cameras Large
Experiment
Combined ASC images from
Kilpisjarvi and Muonio showing
an auroral arc, projected at
110km altitude.
Kurihara et al., Annales, 2006
Experience from US studies:
• A supposedly “operational” nowcasting system has been
delivered to the US Air Force using GPS inputs assimilated
into an ionosphere model
• However this is without a self-consistent thermosphere
• Contrast the density of TEC/Ne measurements with those
of neutral atmosphere composition and winds
• The northern US continent is well covered but even for
electron density/TEC coverage outside this is poor.
• Does this matter??
Global model of
Joule heating for
moderate
conditions (Thayer, 1995)
Including neutral
wind dynamo
No neutral wind
dynamo
Un=0
The Auroral zone inputs are not the only
problem
• The equatorial ionosphere is notoriously difficult to
model
• Its scale sizes do not match easily with GCMs
• It is part of a general problem that there are
aspects of modelling the
ionospheric/thermospheric behaviour which can
only be solved globally
• …..And you can’t ignore the lower atmosphere
V = E x B (20 - 40 m/s)
Conclusions
• On the whole we know the physics, much as we do with
tropospheric meteorology
• The problem with taking this to “nowcasting” and
forecasting is with resolution and inputs
• Whereas some data might be available at a high enough
resolution (electron densities) it is unlikely we will ever get
neutral atmosphere data at the same density
• “Average” and low resolution behaviour we can simulate
well already, but “local” forecasts or specific features is not
what you should expect from GCMs