Estimating currents and electric fields in the high-latitude ionosphere using ground- and space-based observations Ellen Cousins 1, Tomoko Matsuo 2,3,

Slides:



Advertisements
Similar presentations
Cluster Reveals Properties of Cold Plasma Flow May 15, 2009 Erik Engwall.
Advertisements

MURI,2008 Electric Field Variability and Impact on the Thermosphere Yue Deng 1,2, Astrid Maute 1, Arthur D. Richmond 1 and Ray G. Roble 1 1.HAO National.
Multi-Scale Probabilistic Modeling in Geospace Science Zach Thomas The Ohio State University Mentors: Tomoko Matsuo, Doug Nychka Ellen Cousins, Mike Wiltberger.
MHD Simulations of the January 10-11, 1997 Magnetic Storm Scientific visualizations provide both scientist and the general public with unprecedented view.
CHAMP Observations of Multiple Field-Aligned Currents Dimitar Danov 1, Petko Nenovski 2 Solar-Terrestrial Influences Laboratory, Bulgarian Academy of Sciences,
Figure 4: Overview of the geometry of the Rankin Inlet and Inuvik radar in MLT coordinates on Aug 08 th Merged vectors are shown in black. AMPERE.
LISN Model/Data Inversion to Determine the Drivers of the Low-Latitude Ionosphere (Comparisons with JRO ISR Drift Measurements) Vince Eccles (Modeling)
Auroral dynamics EISCAT Svalbard Radar: field-aligned beam  complicated spatial structure (
PLASMA TRANSPORT ALONG DISCRETE AURORAL ARCS A.Kullen 1, T. Johansson 2, S. Buchert 1, and S. Figueiredo 2 1 Swedish Institute of Space Physics, Uppsala.
Ionospheric Convection and Field-Aligned Currents During Strong Magnetospheric Driving: A SuperDARN/AMPERE Case Study L. B. N. Clausen (1), J. B. H. Baker.
Coupling the RCM to LFM Frank Toffoletto (Rice) and John Lyon (Dartmouth)
Ionospheric Electric Field Variations during Geomagnetic Storms Simulated using CMIT W. Wang 1, A. D. Richmond 1, J. Lei 1, A. G. Burns 1, M. Wiltberger.
Expected Influence of Crustal Magnetic Fields on ASPERA-3 ELS Observations: Insight from MGS D.A. Brain, J.G. Luhmann, D.L. Mitchell, R.P. Lin UC Berkeley.
Multipoint observations of nightside auroral activity: the Cascades2 sounding rocket mission K A Lynch, Dartmouth College 2009 Fall AGU SM53D-05 Dartmouth.
Global Distribution / Structure of Aurora Photograph by Jan Curtis Synthetic Aurora pre- midnight,multi-banded Resonant ULF waves produce pre- midnight,
CISM Advisory Council Meeting 4 March Ionosphere-Thermosphere Modeling Tim Killeen, Stan Solomon, and the CISM Ionosphere-Thermosphere Team.
Magnetosphere-Ionosphere Coupling through Plasma Turbulence at High- Latitude E-Region Electrojet Y. Dimant and M. Oppenheim Tuesday, April 13, 2010 Center.
Radio and Space Plasma Physics Group The formation of transpolar arcs R. C. Fear and S. E. Milan University of Leicester.
V. M. Sorokin, V.M. Chmyrev, A. K. Yaschenko and M. Hayakawa Strong DC electric field formation in the ionosphere over typhoon and earthquake regions V.
Geospace Variability through the Solar Cycle John Foster MIT Haystack Observatory.
Julie A. Feldt CEDAR-GEM workshop June 26 th, 2011.
Tangential discontinuities as “roots” of auroral arcs: an electrostatic magnetosphere-ionosphere coupling mode M. Echim (1,2), M. Roth (1), J.de Keyser.
Kick off meeting, swarm E2E study, nio #1 8-Sep-15 Development Approach Task 1: Industrial Module –to be used by industry for their system simulation –Output:
Dr. Hugh Blanton ENTC Magnetostatics Dr. Blanton - ENTC Magnetostatics 3 Magnetostatics Magnetism Chinese—100 BC Arabs—1200 AD Magnetite—Fe.
GPS derived TEC Measurements for Plasmaspheric Studies: A Tutorial and Recent Results Mark Moldwin LD Zhang, G. Hajj, I. Harris, T. Mannucci, X. PI.
UTSA Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE) G. S. Bust and G. Crowley UTSA S. Datta-Barua ASTRA.
Lecture 16 Simulating from the Sun to the Mud. Space Weather Modeling Framework – 1 [Tóth et al., 2007] The SWMF allows developers to combine models without.
Magnetosphere-Ionosphere coupling processes reflected in
Space Science MO&DA Programs - September Page 1 SS It is known that the aurora is created by intense electron beams which impact the upper atmosphere.
Ionospheric Electrodynamics & Low-Earth Orbiting Satellites (LEOS) J-M Noël, A. Russell, D. Burrell & S. Thorsteinson Royal Military College of Canada.
Large electric fields near the nightside plasmapause observed by the Polar spacecraft K.-H. Kim 1, F. Mozer 2, and D.-H. Lee 1 1 Department of Astronomy.
Specifying Instantaneous Currents and Electric Fields in the High-Latitude Ionosphere FESD-ECCWES Meeting, 21 July 20141/15 Ellen Cousins 1, Tomoko Matsuo.
Magnetosphere-Ionosphere coupling in global MHD simulations and its improvement Hiroyuki Nakata The Korea-Japan Space Weather Modeling workshop 2008/8/12,
Data Assimilation for the Space Environment Ludger Scherliess Center for Atmospheric and Space Sciences Utah State University Logan, Utah GEM.
Ionospheric Research at USU R.W. Schunk, L. Scherliess, J.J. Sojka, D.C. Thompson & L. Zhu Center for Atmospheric & Space Sciences Utah State University.
Drift Resonant Interactions of Radiation Belt Electrons with ULF waves. L. G. Ozeke, I. R. Mann, A. Degeling, V. Amalraj, and I. J. Rae University of Alberta.
Observation of global electromagnetic resonances by low-orbiting satellites Surkov V. V. National Research Nuclear University MEPhI.
Data Assimilation With VERB Code
07/11/2007ESSW4, Brussels1 Coupling between magnetospheric and auroral ionospheric scales during space weather events M. ECHIM (1,2), M. ROTH(1) and J.
The Mesoscale Ionospheric Simulation Testbed (MIST) Regional Data Assimilation Model Joseph Comberiate Michael Kelly Ethan Miller June 24, 2013.
11 th EISCAT Workshop, Menlo Park, August 2003 Session: M-I Coupling Magnetospheric plasma drift as simultaneously observed by Cluster (EDI) and.
Testing the Equipotential Magnetic Field Line Assumption Using SuperDARN Measurements and the Cluster Electron Drift Instrument (EDI) Joseph B. H. Baker.
Guan Le NASA Goddard Space Flight Center Challenges in Measuring External Current Systems Driven by Solar Wind-Magnetosphere Interaction.
Investigation of Field-aligned Currents Onboard of Interkosmos Bulgaria-1300 Satellite Dimitar Danov Solar-Terrestrial Influences Laboratory, Bulgarian.
Session SA33A : Anomalous ionospheric conductances caused by plasma turbulence in high-latitude E-region electrojets Wednesday, December 15, :40PM.
École Doctorale des Sciences de l'Environnement d’Île-de-France Année Universitaire Modélisation Numérique de l’Écoulement Atmosphérique et Assimilation.
New Science Opportunities with a Mid-Latitude SuperDARN Radar Raymond A. Greenwald Johns Hopkins University Applied Physics Laboratory.
Study on the Impact of Combined Magnetic and Electric Field Analysis and of Ocean Circulation Effects on Swarm Mission Performance by S. Vennerstrom, E.
Study of an Improved Comprehensive Magnetic Field Inversion Analysis for Swarm MTR, E2Eplus Study Work performed by Nils Olsen, Terence J. Sabaka, Luis.
Electron density profile retrieval from RO data Xin’an Yue, Bill Schreiner  Abel inversion error of Ne  Data Assimilation test.
Future China Geomagnetism Satellite Mission (CGS) Aimin Du Institute of Geology and Geophysics, CAS 2012/11/18 Taibei.
Polar Telecon Peter Chi: Travel-time magnetoseismology 1 Travel-time Magnetoseismology Peter J. Chi and C. T. Russell UCLA/IGPP Acknowledgments:
Continuous Global Birkeland Currents from the Active Magnetosphere and Planetary Electrodynamics Response Experiment Brian J Anderson, The Johns Hopkins.
© Copyright QinetiQ limited 2006 On the application of meteorological data assimilation techniques to radio occultation measurements of.
Lecture 15 Modeling the Inner Magnetosphere. The Inner Magnetosphere The inner magnetosphere includes the ring current made up of electrons and ions in.
Thermospheric density variations due to space weather Tiera Laitinen, Juho Iipponen, Ilja Honkonen, Max van de Kamp, Ari Viljanen, Pekka Janhunen Finnish.
Energy inputs from Magnetosphere to the Ionosphere/Thermosphere ASP research review Yue Deng April 12 nd, 2007.
Cluster observation of electron acceleration by ULF Alfvén waves
S. Datta-Barua, Illinois Institute of Technology G. S. Bust, JHUAPL
Atmosphere-Ionosphere Wave Coupling as Revealed in Swarm Plasma Densities and Drifts Jeffrey M. Forbes Department of Aerospace Engineering Sciences, University.
Welcome to Equatorial-PRIMO
Disturbance Dynamo Effects in the Low Latitude Ionosphere
Evidence for Dayside Interhemispheric Field-Aligned Currents During Strong IMF By Conditions Seen by SuperDARN Radars Joseph B.H. Baker, Bharat Kunduri.
The ionosphere is much more structured and variable than ever predicted. Solar Driven Model Since 2000, we have seen more, very clear evidence that the.
Prospects for real-time physics-based thermosphere ionosphere models for neutral density specification and forecast Tim Fuller-Rowell, Mariangel Fedrizzi,
Astrid Maute, Art Richmond, Ben Foster
The Physics of Space Plasmas
Magnetospheric Modeling
Earth’s Ionosphere Lecture 13
The Upper Atmosphere: Problems in Developing Realistic Models
Presentation transcript:

Estimating currents and electric fields in the high-latitude ionosphere using ground- and space-based observations Ellen Cousins 1, Tomoko Matsuo 2,3, Art Richmond 1 1 NCAR-HAO, 2 CU-CIRES, 3 NOAA-SWPC FESD-ECCWES Meeting – 10 Feb 20141/13 J || ΣpΣp Φ

High-latitude Ionospheric Currents  Currents from magnetosphere close through high-latitude ionosphere  Drive currents parallel to and perpendicular to ionospheric electric field (Pedersen & Hall currents) E E E E  Satellites sample magnetic perturbations (  field-aligned currents)  SuperDARN radars sample plasma drifts (  electric fields)  Goal: Combine the two data sets and estimate complete (2D) current & electric field distribution FESD-ECCWES Meeting – 10 Feb 20142/13

[Brian Anderson] Active Magnetosphere and Planetary Electrodynamics Response Experiment AMPERE: StandardAMPERE: High ~1° lat. res.~ 0.1° lat. res. 3FESD-ECCWES Meeting – 10 Feb 2014 Magnetometer on every satellite 6 orbit planes (12 cuts in local time) ~11 satellites/plane 9 minute spacing - re-sampling cadence 780 km altitude, circular, polar orbits Iridium for Science

Using observations of Inverse procedure to infer maps of Assimilative Mapping of Ionospheric Electrodynamics [Richmond and Kamide, 1988] Linear relationships (for a given Σ) Given 2 of E, Σ, ΔB, can in theory solve for remaining variables FESD-ECCWES Meeting – 10 Feb 20144/13 Electric field (from SuperDARN) Conductance (height-integrated conductivity) – tensor (no observations for this study) Magnetic pertubations (from AMPERE) Ionospheric current density (no observations for this study) - Electrostatic potential - Field aligned current density ()

x a – analysis y – observations x b – background model H – forward operator K – Kalman gain P b – background model error covariance R – observational error covariance  Use the optimal interpolation (OI) method of data assimilation  Optimally combine information from observations and a background model, taking into account error properties of both x b yx b x a = x b + K (y – H x b ) K = P b H T (H P b H T + R) -1 FESD-ECCWES Meeting – 10 Feb 20145/13 Assimilative Mapping Procedure [From EOF] [analysis] [physics + Σ]

 Use the optimal interpolation (OI) method of data assimilation  Optimally combine information from observations and a background model, taking into account error properties of both  Background model and its error properties (from EOF analysis) previously determined for SuperDARN data  Recently did similar analysis for AMPERE data  But only have 1 week of data (used years for SuperDARN analysis)  Data quality issues FESD-ECCWES Meeting – 10 Feb 20146/13 Assimilative Mapping Procedure

Calculated using just across-track component of ΔB EOF 2 mean EOF 1 EOF 5 EOF 3 EOF 4 EOF 2 mean EOF 1 EOF 5 EOF 3 EOF 4 Calculated using just along-track component of ΔB Relative contribution of mean and each EOF to total observed ΔB 2 (more flat spectrum) (more peaked spectrum) FESD-ECCWES Meeting – 10 Feb 20147/13 AMPERE EOFs

x a – analysis y – observations x b – background model H – forward operator K – Kalman gain P b – background model error covariance R – observational error covariance  Use the optimal interpolation (OI) method of data assimilation  Optimally combine information from observations and a background model, taking into account error properties of both x b yx b x a = x b + K (y – H x b ) K = P b H T (H P b H T + R) -1 FESD-ECCWES Meeting – 10 Feb 20148/13 [From EOF] [analysis] [physics + Σ] Assimilative Mapping Procedure

FESD-ECCWES Meeting – 10 Feb 20149/13 Ionospheric Conductance  Height-integrated conductivity (tensor)  Assumed infinite along magnetic field lines  Pederson/Hall conductance || / to E  Solar-produced component  Empirical model – assumed to be reasonably accurate  Auroral component unknown  Highly variable in space and time  Estimate using empirical model  Could adjust using information from observations (have had limited success)  Night-side background level  Less well known than day-side  Use as fudge factor Solar Noon 45° Auroral Background

 1 st working with the two data sets separately – large disagreement  Likely due to errors & biases in the data & errors in conductance model FESD-ECCWES Meeting – 10 Feb /13 Assimilative Mapping Examples SuperDARN AMPERE Σ bgd = 0.3 Σ bgd = 3 Φ J || AMPERE SuperDARN  More agreement if night-side conductance inflated to 3

 Solving with both data sets simultaneously FESD-ECCWES Meeting – 10 Feb /13 Assimilative Mapping Examples J || ΣpΣp Φ

FESD-ECCWES Meeting – 10 Feb /13 Assimilative Mapping Examples BYBZBYBZ AMPERE SuperDARN

FESD-ECCWES Meeting – 10 Feb /13 Next Steps  Validation, refinement of procedure by comparing mapped results to independent observations  Have begun testing against subset of SuperDARN or AMPERE data excluded from fit  Look at geomagnetic disturbance within the week-long AMPERE data set