MHD model in HMI pipeline HMI/AIA science team meeting Sep. 8 -- 11, 2009 Stanford, CA HMI/AIA science team meeting Sep. 8 -- 11, 2009 Stanford, CA.

Slides:



Advertisements
Similar presentations
1 GONG Magnetogram pipeline. 2 The GONG Data Processing Pipeline
Advertisements

HMI Data Analysis Software Plan for Phase-D. JSOC - HMI Pipeline HMI Data Analysis Pipeline Doppler Velocity Heliographic Doppler velocity maps Tracked.
Study of Magnetic Helicity Injection in the Active Region NOAA Associated with the X-class Flare of 2011 February 15 Sung-Hong Park 1, K. Cho 1,
High Altitude Observatory (HAO) – National Center for Atmospheric Research (NCAR) The National Center for Atmospheric Research is operated by the University.
1 Hinode Coordinated Observations: Plasma Composition Photospheric composition ~ 1 in coronal hole (CH) -> fast wind Coronal composition ~1.5-3 in active.
Reviewing the Summer School Solar Labs Nicholas Gross.
Estimating Surface Flows from HMI Magnetograms Brian Welsch, SSL UC-Berkeley GOAL: Consider techniques available to estimate flows from HMI vector magnetograms,
Construction of 3D Active Region Fields and Plasma Properties using Measurements (Magnetic Fields & Others) S. T. Wu, A. H. Wang & Yang Liu 1 Center for.
Early HMI Magnetic Field Observations Early Magnetic Field Observations From HMI J. Todd Hoeksema and the HMI Magnetic Field Team: Yang Liu, Keiji Hayashi,
HMI, Photospheric Flows and ILCT Brian Welsch, George Fisher, Yan Li, & the UCB/SSL MURI & CISM Teams HMI Team Mtg., 2006M3: Mag Data Products Correlation.
High-latitude activity and its relationship to the mid-latitude solar activity. Elena E. Benevolenskaya & J. Todd Hoeksema Stanford University Abstract.
A particularly obvious example of daily changing background noise level Constructing the BEST High-Resolution Synoptic Maps from MDI J.T. Hoeksema, Y.
M3 Session AIA/HMI Science Meeting D-1 : M3-Magnetic Field Data Products Data Product Development Session Chairs: R. Larsen/Y. Liu Status: [draft]
HMI – Synoptic Data Sets HMI Team Meeting Jan. 26, 2005 Stanford, CA.
HMI/AIA Science Team Meeting, HMI Science Goals Alexander Kosovichev & HMI Team.
1 SDO/HMI Products From Vector Magnetograms Yang Liu – Stanford University
Synoptic maps and applications Yan Li Space Sciences Laboratory University of California, Berkeley, CA HMI team meeting, Jan 27, 2005, Stanford.
September 2006 CISM All Hand Meeting Progress in the Past Year and Plan for Next Year Yang Liu and the Solar Group in Stanford University
Tucson MURI SEP Workshop March 2003 Janet Luhmann and the Solar CISM Modeling Team Solar and Interplanetary Modeling.
A Data Driven Magnetohydrodynamic (MHD) Model of Active Region Evolution as a Tool for SDO/HMI Data Analyses S. T. Wu 1,2, A. H. Wang 1, Yang Liu 3, and.
HMI Magnetic Field Products jsoc.stanford.edu Line-of-sight magnetic field will be computed from Doppler Velocity in two polarizations, as is done for.
Free Energies via Velocity Estimates B.T. Welsch & G.H. Fisher, Space Sciences Lab, UC Berkeley.
Identifying and Modeling Coronal Holes Observed by SDO/AIA, STEREO /A and B Using HMI Synchronic Frames X. P. Zhao, J. T. Hoeksema, Y. Liu, P. H. Scherrer.
R. Komm & Friends NSO, Tucson R. Komm & Friends NSO, Tucson Solar Subsurface Flows from Ring-Diagram Analysis.
1 WSA Model and Forecasts Nick Arge Space Vehicles Directorate Air Force Research Laboratory.
C. May 12, 1997 Interplanetary Event. Ambient Solar Wind Models SAIC 3-D MHD steady state coronal model based on photospheric field maps CU/CIRES-NOAA/SEC.
The May 1,1998 and May 12, 1997 MURI events George H. Fisher UC Berkeley.
Flows and the Photospheric Magnetic Field Dynamics at Interior – Corona Interface Brian Welsch, George Fisher, Yan Li, & the UCB/SSL MURI & CISM Teams.
1.B – Solar Dynamo 1.C – Global Circulation 1.D – Irradiance Sources 1.H – Far-side Imaging 1.F – Solar Subsurface Weather 1.E – Coronal Magnetic Field.
Early HMI Magnetic Field Observations Early Magnetic Field Observations From HMI J. Todd Hoeksema and the HMI Magnetic Field Team: Yang Liu, Keiji Hayashi,
Connecting coronal structure to photospheric origins Active region (sunspot) evolution and solar rotation well define long term, persistent, coronal streamers.
Space Weather Forecast With HMI Magnetograms: Proposed data products Yang Liu, J. T. Hoeksema, and HMI Team.
HMI Magnetic Products & Pipeline
Active Region Flux Transport Observational Techniques, Results, & Implications B. T. Welsch G. H. Fisher
Advanced Technology Center 1 HMI Rasmus Larsen / Processing Modules Stanford University HMI Team Meeting – May 2003 Processing Module Development Rasmus.
A particularly obvious example of daily changing background noise level Constructing the BEST High-Resolution Synoptic Maps from MDI J.T. Hoeksema, Y.
HMI Science Objectives Convection-zone dynamics and the solar dynamo  Structure and dynamics of the tachocline  Variations in differential rotation 
C. May 12, 1997 Interplanetary Event. May 12, 1997 Interplanetary Coronal Mass Ejection Event CU/CIRES, NOAA/SEC, SAIC, Stanford Tatranska Lomnica, Slovakia,
Some Thoughts on HMI Data Products & Processing F. Hill Jan. 27, 2005.
The May 1997 and May 1998 MURI events George H. Fisher UC Berkeley.
RT Modelling of CMEs Using WSA- ENLIL Cone Model
Science Data Products – HMI Magnetic Field Images Pipeline 45-second Magnetic line-of-sight velocity on full disk Continuum intensity on full disk Vlos.
What coronal parameters determine solar wind speed? M. Kojima, M. Tokumaru, K. Fujiki, H. Itoh and T. Murakami Solar-Terrestrial Environment Laboratory,
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.
Sky Coordinate Image Specs Fully processed: –Merged –10-min cadence –“sky to sky” interpolation –Gaussian temporal filter –Renormalized such that time.
Standard DEM: Consider a imaging instrument with M EUV filters (for the EUVI Fe bands M = 3). The measured intensity in one image pixel is given by DEM.
The Polar Fields Seen in 17 GHz Microwave Flux and with Magnetographs Leif Svalgaard Stanford University 6 January, 2012.
1 GONG Magnetogram Data Products. 2 Sky-coordinate images Single-site or merged? –Single-site requires users to select. –Merge has lower noise, may require.
Observation on Current Helicity and Subsurface Kinetic Helicity in Solar Active Regions Gao Yu Helicity Thinkshop Main Collaborators: Zhang, H.
Synoptic Network Workshop (HAO/NCAR, April 2013) Space Weather and Synoptic Observations V J Pizzo – NOAA/SWPC.
Polar Magnetic Field Elena E. Benevolenskaya Stanford University SDO Team Meeting 2009.
Horizontal Flows in Active Regions from Multi-Spectral Observations of SDO Sushant Tripathy 1 Collaborators K. Jain 1, B. Ravindra 2, & F. Hill 1 1 National.
Introduction to Space Weather Jie Zhang CSI 662 / PHYS 660 Fall, 2009 Copyright © The Heliosphere: Solar Wind Oct. 08, 2009.
1 Pruning of Ensemble CME modeling using Interplanetary Scintillation and Heliospheric Imager Observations A. Taktakishvili, M. L. Mays, L. Rastaetter,
Helioseismology for HMI Science objectives and tasks* Data analysis plan* Helioseismology working groups and meetings *HMI Concept Study Report, Appendix.
Mapping the Solar Magnetic Surface (a la Worden & Harvey)
Xuepu Zhao Oct. 19, 2011 The Base of the Heliosphere: The Outer (Inner) Boundary Conditions of Coronal (Heliospheric) models.
HMI-WSO Solar Polar Fields and Nobeyama 17 GHz Emission
PSP, SO, and Ground-based Synoptic Observations from NSO
Large-Scale Solar Magnetic Fields – How is Solar Cycle 24 Different?
Carrington Rotation 2106 – Close-up of AR Mr 2106 Bt 2106
The Helioseismic & Magnetic Imager – Magnetic Field Data Products
The Helioseismic & Magnetic Imager – Magnetic Investigations
Exploring Large-scale Coronal Magnetic Field Over Extended Longitudes With EUVI EUVI B EIT EUVI A 23-Mar UT Nariaki Nitta, Marc DeRosa, Jean-Pierre.
HMI Investigation Overview
HMI Data Analysis Pipeline
Lecture 5 The Formation and Evolution of CIRS
Vector polarimetry with HMI
HMI Data Analysis Pipeline
Presentation transcript:

MHD model in HMI pipeline HMI/AIA science team meeting Sep , 2009 Stanford, CA HMI/AIA science team meeting Sep , 2009 Stanford, CA

MHD models Input : as initial & boundary values, the magnetic field data, in various formats and cadences, (and plasma parameters from observations) Output : theoretical determination / extrapolation of –3D magnetic and plasma structures, above the photosphere, and in interplanetary space including the high heliographic latitude region, –Temporal evolutions, and –Views from various directions MHD models can give unobservables MHD models can give observables by independent observations Input : as initial & boundary values, the magnetic field data, in various formats and cadences, (and plasma parameters from observations) Output : theoretical determination / extrapolation of –3D magnetic and plasma structures, above the photosphere, and in interplanetary space including the high heliographic latitude region, –Temporal evolutions, and –Views from various directions MHD models can give unobservables MHD models can give observables by independent observations

Input, (quasi-) real-time base EOF (experiment operations facility) preliminary data Synoptic / synchronic maps/frames –Global MHD/non-MHD models Disk data –(remapped in coordinates corrected in accordance with geometry & solar differential rotation) Local “patch” maps –Local MHD/non-MHD models –AR –remapped EOF (experiment operations facility) preliminary data Synoptic / synchronic maps/frames –Global MHD/non-MHD models Disk data –(remapped in coordinates corrected in accordance with geometry & solar differential rotation) Local “patch” maps –Local MHD/non-MHD models –AR –remapped

Daily MHD model (steady-state) Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours on 8-CPU(core) system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions –etc. Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours on 8-CPU(core) system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions –etc.

Daily MHD model (steady-state) Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours in 8CPUs system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours in 8CPUs system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions

Daily MHD model (steady-state) Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours in 8CPUs system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours in 8CPUs system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions

Daily MHD model (steady-state) Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours in 8CPUs system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours in 8CPUs system. With characteristics eq. matching fixed Br condition, the quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions

Daily MHD model (steady-state) Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours on 8-CPU system. With characteristics eq. matching fixed Br condition The quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions –etc. Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours on 8-CPU system. With characteristics eq. matching fixed Br condition The quasi-steady state be obtained Outputs: –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions –etc.

Daily MHD model (with time-varying Br) Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours on 8-CPU system. With characteristics eq. matching time-varying Br Under development Outputs: time-evolutions of –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions –etc. Assumption: Polytrope in Eq. of state Spatial resolution : ~ 5 degree A few hours on 8-CPU system. With characteristics eq. matching time-varying Br Under development Outputs: time-evolutions of –Open/closed coronal field structures –Rough estimation of flow speed and density –Magnetic field polarity at distant regions –Views from various directions –etc.

Surface magnetic field From North pole, lon.90 dgr., south pole Surface magnetic field From North pole, lon.90 dgr., south pole

movie

Models : contribution surface flow: FLCT, ILCT, DAVE4VM, etc. –Complete or completed by induction Eq. –ier=(int)flct(argc,argv,deltat,deltas,sigma,nnx,nny,f1,f2,ef,ef,v x,vy,evx,evy,vm); –for quick-look purpose and/or –with calibrated data. PSI’s MHD contribution surface flow: FLCT, ILCT, DAVE4VM, etc. –Complete or completed by induction Eq. –ier=(int)flct(argc,argv,deltat,deltas,sigma,nnx,nny,f1,f2,ef,ef,v x,vy,evx,evy,vm); –for quick-look purpose and/or –with calibrated data. PSI’s MHD contribution ∂ t B r =rot (v  B) | r