Modelling the Thermosphere-Ionosphere Response to Space Weather Effects: the Problem with the Inputs...
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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
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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
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CTIP/CTIM Properties
• 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. 30-60 seconds time resolution
• 3 neutral constituents (O, O2, N2) and 2 ions (H+, O+)
• Wave forcing at the lower boundary(80km)
• Self-consistent dynamo calculations
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“Standard” input of magnetosphere-ionosphere coupling
• 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 (Fuller-Rowell
1987 and Foster 1986).
• These inputs are linked to a power index based on TIROS/NOAA auroral particle measurements.
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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 aCinepak decompressor
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April 1997 Storm event
Dusk effect (neutral winds)
TEC enhancement (particle precipitation)
Total Electron Content (TEC) change
Negative phase (neutral gas composition)
But complications continually arise: the response to storms is not simple:
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But how realistic are the inputs?
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SuperDARNSuper Dual Auroral Radar Network
Northern Hemisphere
Southern Hemisphere
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Joule heating from CTIP model runs
Empirical electric fields
Electric field input derived from
SuperDARN
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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
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OVATION datasets (http://sd-www.jhuapl.edu/Aurora/ovation/datasets.html)
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
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• However even given these we still need a dense network of stations to constrain the empirical inputs
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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
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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??
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Global model of Joule heating for moderate conditions (Thayer, 1995)
Including neutral wind dynamo
No neutral wind dynamo Un=0
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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
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V = E x B (20 - 40 m/s)
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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