Comparison of the 3D MHD Solar Wind Model Results with ACE Data 2007 SHINE Student Day Whistler, B. C., Canada C. O. Lee*, J. G. Luhmann, D. Odstrcil,

Slides:



Advertisements
Similar presentations
Reviewing the Summer School Solar Labs Nicholas Gross.
Advertisements

ESS 7 Lecture 14 October 31, 2008 Magnetic Storms
Global Distribution of Slow Solar Wind N. U. Crooker, S. W. Antiochos, X. Zhao, Yi-M. Wang, and M. Neugebauer.
Chip Manchester 1, Fang Fang 1, Bart van der Holst 1, Bill Abbett 2 (1)University of Michigan (2)University of California Berkeley Study of Flux Emergence:
Heliospheric MHD Modeling of the May 12, 1997 Event MURI Meeting, UCB/SSL, Berkeley, CA, March 1-3, 2004 Dusan Odstrcil University of Colorado/CIRES &
High-latitude activity and its relationship to the mid-latitude solar activity. Elena E. Benevolenskaya & J. Todd Hoeksema Stanford University Abstract.
A General Cone Model Approach to Heliospheric CMEs and SEP Modeling Magnetogram-based quiet corona and solar wind model The SEPs are modeled as a passive.
Synoptic maps and applications Yan Li Space Sciences Laboratory University of California, Berkeley, CA HMI team meeting, Jan 27, 2005, Stanford.
Tucson MURI SEP Workshop March 2003 Janet Luhmann and the Solar CISM Modeling Team Solar and Interplanetary Modeling.
Understanding Magnetic Eruptions on the Sun and their Interplanetary Consequences A Solar and Heliospheric Research grant funded by the DoD MURI program.
1 WSA Model and Forecasts Nick Arge Space Vehicles Directorate Air Force Research Laboratory.
CISM solar wind metrics M.J. Owens and the CISM Validation and Metrics Team Boston University, Boston MA Abstract. The Center for Space-Weather Modeling.
When will disruptive CMEs impact Earth? Coronagraph observations alone aren’t enough to make the forecast for the most geoeffective halo CMEs. In 2002,
Merging of coronal and heliospheric numerical two-dimensional MHD models D. Odstrcil, et al., J. Geophys. Res., 107, 年 10 月 14 日 太陽雑誌会 ( 速報.
Center for Space Environment Modeling W. Manchester 1, I. Roussev, I.V. Sokolov 1, 1 University of Michigan AGU Berkeley March.
A particularly obvious example of daily changing background noise level Constructing the BEST High-Resolution Synoptic Maps from MDI J.T. Hoeksema, Y.
Coronal and Heliospheric Modeling of the May 12, 1997 MURI Event MURI Project Review, NASA/GSFC, MD, August 5-6, 2003 Dusan Odstrcil University of Colorado/CIRES.
The “cone model” was originally developed by Zhao et al. ~10 (?) years ago in order to interpret the times of arrival of ICME ejecta following SOHO LASCO.
MHD Modeling of the Large Scale Solar Corona & Progress Toward Coupling with the Heliospheric Model.
Predictions of Solar Wind Speed and IMF Polarity Using Near-Real-Time Solar Magnetic Field Updates C. “Nick” Arge University of Colorado/CIRES & NOAA/SEC.
RT Modelling of CMEs Using WSA- ENLIL Cone Model
Thomas Zurbuchen University of Michigan The Structure and Sources of the Solar Wind during the Solar Cycle.
Numerical simulations are used to explore the interaction between solar coronal mass ejections (CMEs) and the structured, ambient global solar wind flow.
1 C. “Nick” Arge Space Vehicles Directorate/Air Force Research Laboratory SHINE Workshop Aug. 2, 2007 Comparing the Observed and Modeled Global Heliospheric.
Proxies of the Entire Surface Distribution of the Photospheric Magnetic Field Xuepu Zhao NAOC, Oct. 18, 2011.
Evolution of the 2012 July 12 CME from the Sun to the Earth: Data- Constrained Three-Dimensional MHD Simulations F. Shen 1, C. Shen 2, J. Zhang 3, P. Hess.
Semi-Empirical MHD Modeling of the Solar Wind Igor V. Sokolov, Ofer Cohen, Tamas I. Gombosi CSEM, University of Michigan Ilia I Roussev, Institute for.
R. Oran csem.engin.umich.edu SHINE 09 May 2005 Campaign Event: Introducing Turbulence Rona Oran Igor V. Sokolov Richard Frazin Ward Manchester Tamas I.
1 THE RELATION BETWEEN CORONAL EIT WAVE AND MAGNETIC CONFIGURATION Speakers: Xin Chen
Comparison of the 3D MHD Solar Wind Model Results with ACE Data 2007 SHINE Student Day Whistler, B. C., Canada C. O. Lee*, J. G. Luhmann, D. Odstrcil,
Community Modeling: What Users Could Use Janet Luhmann SSL, University of California, Berkeley SHINE Workshop, July 2007, Whistler.
The Solar Wind.
AFRL/CISM Collaborations
Faraday Rotation: Unique Measurements of Magnetic Fields in the Outer Corona Justin C. Kasper (UM), Ofer Cohen (SAO), Steven Spangler (Iowa), Gaetan Le.
Conclusions Using the Diffusive Equilibrium Mapping Technique we have connected a starting point of a field line on the photosphere with its final location.
The Community Coordinated Modeling Center: A Brief Overview NASA Goddard Space Flight Center Lika Guhathakurta
Space weather forecasters perspective: UK David Jackson and Mark Gibbs SEREN Bz workshop, Abingdon, 9-10 July 2014.
Validation of the SWMF Coupled Model for Solar Corona – Inner Heliosphere – CME With the Observations of the May 12, 1997 Event Ofer Cohen(1), Igor V.
Interplanetary Shocks in the Inner Solar System: Observations with STEREO and MESSENGER During the Deep Solar Minimum of 2008 H.R. Lai, C.T. Russell, L.K.
Long Term Measurements of Solar Wind Fe Charge States Mark Popecki, A. Galvin, L. M. Kistler,H. Kucharek, E. Moebius, K. Simunac, P. Bochsler, L. M. Blush,
Modeling 3-D Solar Wind Structure Lecture 13. Why is a Heliospheric Model Needed? Space weather forecasts require us to know the solar wind that is interacting.
Heliospheric Simulations of the SHINE Campaign Events SHINE Workshop, Big Sky, MT, June 27 – July 2, 2004 Dusan Odstrcil 1,2 1 University of Colorado/CIRES,
Solar Wind Propagation Tool Chihiro Tao 1,2, Nicolas Andre 1, Vincent Génot 1, Alexis P. Rouillard 1, Elena Budnik 1, Arnaud Biegun 1, Andrei Fedorov 1.
State of NOAA-SEC/CIRES STEREO Heliospheric Models STEREO SWG Meeting, NOAA/SEC, Boulder, CO, March 22, 2004 Dusan Odstrcil University of Colorado/CIRES.
The heliospheric magnetic flux density through several solar cycles Géza Erdős (1) and André Balogh (2) (1) MTA Wigner FK RMI, Budapest, Hungary (2) Imperial.
Heliospheric Modeling at the CCMC and possible ways these modeling efforts can be improved MacNeice and Taktakishvili SHINE June 26, 2012.
Manuela Temmer Institute of Physics, University of Graz, Austria Tutorial: Coronal holes and space weather consequences.
Long-term measurements of the Sun’s poles show that reversal of the dominant magnetic polarity generally occurs within a year of solar maximum. Current.
Detecting, forecasting and modeling of the 2002/04/17 halo CME Heliophysics Summer School 1.
Poster X4.137 Solar Wind Trends in the Current Solar Cycle (STEREO Observations) A.B. Galvin* 1, K.D.C. Simunac 2, C. Farrugia 1 1.Space Science Center,
B.V. Jackson H.-S. Yu, P.P. Hick, A. Buffington,
Driving 3D-MHD codes Using the UCSD Tomography
Nicholeen Viall NASA/GSFC
STOCHASTIC COUPLING OF SOLAR PHOTOSPHERE AND CORONA (Astrophysical J
Lecture 12 The Importance of Accurate Solar Wind Measurements
Forecast Development at the Canadian Space Weather Forecast Centre
Xuepu Zhao Oct. 19, 2011 The Base of the Heliosphere: The Outer (Inner) Boundary Conditions of Coronal (Heliospheric) models.
ST23-D2-PM2-P-013 The UCSD Kinematic Global Solar Wind Boundary for use in ENLIL 3D-MHD Forecasting Bernard JACKSON1#+, Hsiu-Shan YU1, Paul HICK1, Andrew.
Evolution of solar wind structures between Venus and Mars orbits
Exploration of Solar Magnetic Fields from Propagating GONG Magnetograms Using the CSSS Model and UCSD Time-Dependent Tomography H.-S. Yu1, B. V. Jackson1,
Importance of Pickup Ions & Suprathermal Ions in the Inner Heliosphere
Wave heating of the partially-ionised solar atmosphere
Solar cycle variation of the heliospheric magnetic field
D. Odstrcil1,2, V.J. Pizzo2, C.N. Arge3, B.V.Jackson4, P.P. Hick4
Carrington Rotation 2106 – Close-up of AR Mr 2106 Bt 2106
How does the solar atmosphere connect to the inner heliosphere?
Lecture 5 The Formation and Evolution of CIRS
ESS 261 Topics in magnetospheric physics Space weather forecast models ____ the prediction of solar wind speed April 23, 2008.
P. Stauning: The Polar Cap (PC) Index for Space Weather Forecasts
Emerging Active Regions: turbulent state in the photosphere
Presentation transcript:

Comparison of the 3D MHD Solar Wind Model Results with ACE Data 2007 SHINE Student Day Whistler, B. C., Canada C. O. Lee*, J. G. Luhmann, D. Odstrcil, P. MacNeice, I. de Pater, P. Riley, and C. N. Arge

INTRODUCTION We generate results from inner heliospheric model ENLIL together with the Wang-Sheeley-Arge (WSA/ENLIL) and MHD-Around-a-Sphere (MAS/ENLIL) coronal magnetic field models. The 3-D WSA/ENLIL and MAS/ENLIL models are available at CCMC for simulating the ambient solar wind (out to 10 AU!). We show our 1 AU results of the comparison with ACE plasma observations. Such tests validate the models for use at quiet times, as well as establishing their usefulness for describing the ambient conditions prior to disturbances. Agreement of the model with observations could suggest that a viable option is available both to predict such enhancements from co-rotating stream interaction regions, as well as to provide an approximation to solar wind conditions when Cassini is inside Saturn's magnetosphere

Illustration of MAS coronal model (left) and ENLIL heliospheric solar wind model (right) Illustration of the coupled MAS (MHD around a sphere) [cf. Linker et al., J. Geophys. Res., 104, 9809, 1999] coronal model and the ENLIL solar wind model [cf. Odstrcil and Pizzo, J. Geophys. Res., 104, 483, 1999]. X Assumptions of model: polytropic X Coronal part can be an MAS MHD model or semi-empircal model, both of which uses magnetograms as innermost BCs Although shown above is an illustration of the MAS coronal input into ENLIL, the same concept can be applied for the WSA/ENLIL combination

WSA/ENLIL and MAS/ENLIL are solar magnetogram-based models Image credit: Mt. Wilson Solar Observatory Magnetograms are maps of line-of-sight component of magnetic flux at the photosphere. Regions of strong positive (blue) and strong negative (red) magnetic flux are shown. Input magnetograms to the solar corona models at CCMC either comes from the Mt. Wilson Solar Observatory (MWO) or the National Solar Observatory (NSO) at Kitt Peak Arizona. The fields are measured by detecting the Zeeman shift between right-hand and left-hand circularly polarized light in a magnetically sensitive absorption line (e.g. 5250 Angstroms, neutral iron Fe I).

The time range chosen for this study: January 2003 to December 2005 (Carrington Rotations 1999 to 2038) Time range of data set - Explain time range chose - Sun Solar Cycle (Sun Spot Number plot) - Ideal time to make comparison because it’s quiet solar cycle From Ron: Definitely mention which part of the solar cycle I am looking at and maybe mention why I am looking at this right now (Cassini driven). Mention in my paper that I will do the study for other parts of the same solar cycle using ACE if post-launch in 1997. He warned me that the analysis that I make from the existing data sets would only be applicable to that part of the solar cycle, which is why it important for me to mention to the audience which part of the solar cycle my research is focusing on. He said that I will find that when we are on the part of the cycle that is going from min to max, the solar wind will look quite different from the solar wind coming off from max to min. So I need to take care of the statements that I make about the solar wind and be very specific about the solar cycle that I look at! This period is an ideal time to make comparisons of the model data with spacecraft observations because it is a quiet solar cycle.

CCMC User Interface http://ccmc.gsfc.nasa.gov (top) User can select preferences in the run request interface: - desired Carrington Rotation (solar rotation of 27.3 days as observed from Earth) - input solar coronal model (MAS or WSA) - solar magnetograms from NSO or MWO - maximum radial distance of run (2 AU or 10 AU) (bottom) User can produce various output data in different formats such as color contour plots, 1D line plots, surface plots, etc., and can select the plotting parameters, such as plot variables (up to 3), plot axes range, etc.

Illustration from model results of how solar wind dynamic pressure evolves for one Carrington Rotation (top) An example of CCMC-generated output of a 2-D color contour plot for the variation in pressure with radial distance. (bottom) An example of a time series for dynamic pressure generated by the authors from the CCMC-generated ASCII text data output file.

Adopted plot style for displaying solar wind parameters Shown are time series of dynamic pressure (left) modeled at 1 AU for Carrington Rotation (CR) 2017 and 2018. The time series can be stacked against each other, where the magnitude of the dynamic pressure is now represented in color (above); highs = red, lows = blue. A time series organized by CR can be displayed in this fashion, forming a color contour plot of CR vs. day of CR (day 1, day 2, . . . day 27). +

Kitt Peak National Solar Comparison of different coronal models (left) and input solar magnetograms (right). Mt. Wilson Solar Observatory (MWO) MAS Coronal Input MAS-based values have less mid-range values (green) compared with WSA-based values. Kitt Peak National Solar Observatory (NSO) WSA Coronal Input There are small differences between MWO- and NSO-based values

Comparison of MAS/Enlil and WSA/Enlil with ACE Density at 1 AU For CRs 1999-2020 where the stream interaction regions are a 2-sector structure, there are 2 corresponding high-density ridges (reds). For CRs 2020 to 2038, there are 4 high-density ridges corresponding with a 4-sector structure. The model (right) compares fairly well with ACE (above). Although the model values are much higher than the observations, it should be noted that there are data dropouts in ACE densities whenever the values are very high.

Comparison of MAS/Enlil and WSA/Enlil with ACE Velocity at 1 AU In the modeled velocity (right), it can be seen that the pattern of high velocity values (orange-red) match fairly well with those from the ACE observations (above). Noticeable in the model velocity plots are the high values – they are not as high (orange) as those from the ACE observations (more red) . Ron also mentioned that some of the velocity data is off (sometimes the values goes to 250 km/sec, which is wrong). This is a somewhat systematic error that may or may not be documented in the publications. He said the way to check for whether the velocity values are trustworthy or not is to look at the SIS data, where there are measurements of 2 energy levels. He said to look at the higher energy channel data and look at whether there are values (differential flux) that hits the 50 mark. If so, then take a look at the velocities to see if they go to 250 km/sec. If so, don't trust that velocity value. Ron said the person to talk to this about if I have any questions is someone named Ruth over at LANL. (Keep in mind that the velocity values can go to 250 km/sec in reality but as far as whether the solar wind instrument measured the values correctly, that is another story.)

Comparison of MAS/Enlil and WSA/Enlil with ACE Dynamic Pressure at 1 AU Compared to ACE observations (above), the MAS/Enlil result (bottom right) seem to compare better overall than those from WSA/Enlil (top right). High pressure ridges (reds) are more accurately derived by MAS/Enlil than WSA/Enlil in terms of structure and magnitude of the values.

CONCLUDING REMARKS The model results at 1 AU correlate fairly well with ACE spacecraft observations for density, velocity, and dynamic pressure. We are in the process of comparing results for magnetic field polarities – ACE magnetic field data in GSE coordinates needs to be transformed to the coordinate system of the ENLIL model (HEEQ, sun-centered). This model runs routinely at CCMC. Note that the models do not yet include CMEs but future plans include adding such transient structures. Future work includes comparing results with the STEREO observations. In addition, we will also test the models for their performance in simulating the solar wind at other radial distances other than 1 AU.

Thank you!