R2O at NOAA’s Space Weather Prediction Center European Space Weather Week November 16, 2009 Thomas J Bogdan SWPC Director

Space Weather im- pacts are most keen- ly felt through-out the near-Earth space environment. Ad- vanced technologies that underlie our global economy and national security are vulnerable to severe space weather Solar Irradiance Prediction Model Space Weather Prediction Models : CONOPS I 1. Solar Wind Disturbance Propagation Model 2. Energetic Particle Transport Model 5. Solar GCM 3. Geospace Response Model Forecasts of space weather are based on five essential numerical prediction models, numbered from 1 to 5 in order of increasing difficulty and decreasing present day understanding and capability. Model 5 forces models 1, 2 and 4 Model 2 requires model 1 as input Model 3 is driven by models 1, 2 and 4 Space Weather develops here, deep within the Sun, our nearest star. The Sun has a “seasonal” activity cycle that lasts, on average, about 12 years. The underlying cause of solar variability is the Sun’s magnetic field.

3 1. Solar Wind Disturbance Propagation Model 2. Energetic Particle Transport Model 3. Geospace Response Model 4. Solar Irradiance Prediction Model 5. Solar General Circulation Model Space Weather Prediction Models : CONOPS II Supplies forecasts for Earth-based customers Supplies forecasts for NASA Moon/Mars/Interplanetary Missions Solar Flares/ TSI Variation Coronal Mass Ejections/ High-Speed Streams/ Co-rotating Interaction Regions Solar Energetic Particle Events Galactic Cosmic-Ray Modulation Solar Cycle Prediction

4 1. Solar Wind Disturbance Propagation Model: Specs Solves the 3-D Equations of single fluid magnetohydrodynamics between an inner boundary of ~25-30 R SUN to an adjustable outer boundary inside of the heliospheric termination shock (approximately 100 AU). Requires specification of time-dependent driving boundary conditions on the plasma (velocity, magnetic field, density, temperature) at ~25-30 R SUN Assimilates in situ plasma data from spacecraft at L1 (and L5 in the future) and remote sensing data from heliospheric imagers and coronagraphs. Predicts the vector magnetic field, the vector plasma velocity, the plasma density and temperature anywhere in the heliosphere beyond 25 R SUN but comfortably inside 100 AU. Refresh cycle of at least 2-4 time per day.

5 1. Solar Wind Disturbance Propagation Model: Examples ENLIL was developed jointly by the NOAA/University of Colorado at Boulder Cooperative Institute for Research in Environmental Science.

6 1. Solar Wind Disturbance Propagation Model: Data Needs Coronal mass ejections must be input to the SWDP Model at the inner boundary at 25 solar radii Observations from coronagraphs and EUV imagers are critical for driving and validating the SWDP models

7 Monitors and Sentinels: The L1 and L5 Vantage Points Heliospheric Sentinels Solar Monitors An Optimal Configuration of sentinels and monitors consists of two identical spacecraft situated at the stationary L1 and L5 libration points L5 is preferable to L4 because the sun rotates as seen from above in the cartoon below in a counterclockwise fashion once in about 27 days. Therefore an L5 monitor sees about 4 days in advance around the east limb of the sun before solar activity complexes appear on the visible disk with a direct line from sun to earth. The solar wind and embedded magnetic field also rotate in the same sense with the field drawn out into a Archimedes spiral. Therefore a sentinel at L5 passes through ambient magnetized solar wind again about 4 days before the earth and its magnetosphere will traverse the same stream.

X-Ray Sensor tells when a a solar flare has occurred and records its intensity. Magnetograms provide guidance on the likelihood of solar flares and are needed to initialize Solar Wind Disturbance Propagation Model. UV/EUV images indicate where a flare has occurred and provide unique guidance on whether a prompt solar radiation storm is anticipated. Coronagraph images are needed to initialize the solar storms that are tracked by the Solar Wind Disturbance Propagation Model. 8 Monitors and Sentinels: Monitors The essential monitor data consists of an X- Ray Sensor, (vector) magnetograms (TOP), UV/EUV images (MIDDLE), and white light coronagraph images (BOTTOM).

9 1. Solar Wind Disturbance Propagation Model 2. Energetic Particle Transport Model 3. Geospace Response Model 4. Solar Irradiance Prediction Model 5. Solar General Circulation Model Space Weather Prediction Models : CONOPS II Supplies forecasts for Earth-based customers Supplies forecasts for NASA Moon/Mars/Interplanetary Missions Solar Flares/ TSI Variation Coronal Mass Ejections/ High-Speed Streams/ Co-rotating Interaction Regions Solar Energetic Particle Events Galactic Cosmic-Ray Modulation Solar Cycle Prediction

10 2. Energetic Particle Transport Model: Specs Solves the kinetic Vlasov (i.e., collisionless Boltzmann)equations for the single-particle distribution function for multiple species (i.e., protons, alpha’s, and heavy ions). Electrons are often treated as a ‘fluid’. Requires –Specification of the time-dependent background magnetohydrodynamic state of the heliosphere (i.e., output of the Solar Wind Disturbance Propagation Model) –Prescription of the particle diffusion tensors –Prescription for particle acceleration at shock fronts –Specification of the solar energetic particle fluxes from solar flares at R SUN and the galactic cosmic ray flux from the ISM Assimilates in situ energetic particle data from L1 and L5, and remote sensing of type I, II, III and IV radio emission Predicts energetic particle fluxes throughout the heliosphere beyond 25 R SUN Refresh after each solar flare greater than a specified threshold

11 2. Energetic Particle Transport Model: Example: University of Arizona Model 10 hrs 20 hrs 30 hrs Intensity of 1 MeV protons Intensity of protons > 10 keV Charged particles are channeled along the spiral magnetic field lines provided by the Solar Wind Disturbance Propagation Model Charged particles are accelerated in the vicinity of collisionless shock fronts provided by the Solar Wind Disturbance Propagation Model

12 3. Geospace Response Model: Specs Consists of coupled –MAGNETOSPHERE, –PLASMASPHERE/EXOSPHERE, –IONOSPHERE/THERMOSPHERE, –MESOSPHERE/STRATOSPHERE/TROPOSPHERE models Solves different set of equations for physical variables and chemical species in each model domain, and uses flux couplers across model interfaces Requires specification of solar wind parameters and energetic particle populations on the nose of the magnetospheric bow shock, and solar irradiance as a function of wavelength Assimilates in situ satellite observations, radio occultation, atmospheric soundings, multi-wavelength imagery, and data from ionosondes, ground magnetometers, riometers and GPS reference sites Predicts terrestrial weather, ionospheric electron density, cross-polar cap potential, neutral winds, particle precipitation and energy deposition, ground-induced currents and HF communications conditions Refresh currently unknown, but perhaps four times per day and after solar flares that exceed critical thresholds

13 3. Geospace Response Model: Magnetosphere A Magnetosphere Model forms the outer envelope for the Geospace Response Model It is driven by the specified solar wind and embedded coronal mass ejections on the upstream side provided by the Solar Wind Disturbance Propagation Model, energetic ions and electrons from the Energetic Particle Transport Model, and short-wavelength irradiance from the Solar Irradiance Prediction Model. It couples to a Plasmasphere/ Exosphere Model on a sphere with a radius of 2 R EARTH

km Troposphere/Stratosphere/Mesosphere km Ionosphere/Thermosphere ,000 km Plasmasphere/Exosphere Ions control the dynamics. Electrons transport heat and electric current. Neutral Atoms and Molecules are rare and tend to follow ballistic trajectories. Ions and Neutrals both contribute to the dynamics and are collisionally coupled. Electrons transport heat and electric current. Neutral Atoms and Molecules dominate dynamics and transport. Ions and Electrons are too rare to transport electric currents. 3. Geospace Response Model: The Inner -Spheres ,000 km Magnetosphere Ions and Electrons only.

15 1. Solar Wind Disturbance Propagation Model 2. Energetic Particle Transport Model 3. Geospace Response Model 4. Solar Irradiance Prediction Model 5. Solar General Circulation Model Space Weather Prediction Models : CONOPS II Supplies forecasts for Earth-based customers Supplies forecasts for NASA Moon/Mars/Interplanetary Missions Solar Flares/ TSI Variation Coronal Mass Ejections/ High-Speed Streams/ Co-rotating Interaction Regions Solar Energetic Particle Events Galactic Cosmic-Ray Modulation Solar Cycle Prediction

16 Solves the equations of radiative transfer coupled with the statistical rate equations for numerous ionic species and energy level populations Requires specification of the heat flux brought to the solar surface through convection and the varying physical conditions (velocity, magnetic field, temperature) in the solar atmosphere Assimilates spectral irradiance observations and spectroheliograms/magnetograms in various wavelength regions from x-rays to radio Predicts time variations of the spectral irradiance from radio to x-ray wavelengths Refresh on the time scales of hours to minutes 4. Solar Irradiance Prediction Model: Specs

17 5. Solar General Circulation Model: Specs Consists of solar interior (r < R SUN ) and envelope (R SUN < r < 25 R SUN ) models that are separated by the photosphere Each solves the single-fluid equations of magneto- hydrodynamics, but on distinct spatial and temporal scales. In the interior, radiative transfer can generally be treated in the diffusion approximation, but this approach is untenable in the envelope. In the envelope rate and population levels for a few major ions and neutrals must be tracked consistently. In the interior, nuclear reactions must be followed. Energetic particles must be treated kinetically in the envelope. Requires, in principle, no additional information to be supplied by other models. Assimilates remotely sensed spectropolarimetric, helioseismic, and neutrino observations. Predicts plasma parameters and energetic particle fluxes at 25 R SUN plus spectral irradiance at 1 AU via the Solar Irradiance Prediction Model. Refresh on time scales from minutes to hours

18 Research to Operations Timeline for Numerical Space Weather Modeling transition to operations operations + maintenance transition to operations FY2010FY2012FY2014FY2018 Solar Wind Disturbance Propagation Model Energetic Particle Transport Model Geospace Response Model Solar Irradiance Prediction Model Solar General Circulation Model r&d Note: O+M includes O2R feedback to continuing R&D T2O occurs in stages for models with multiple components operations + maintenance

19 A Vision for NOAA’s Space Weather Modeling: Summary Current space weather numerical prediction models are empirical and driven by observed statistical correlations, climatology, and space situational awareness. A Sun-to-Earth chain of cause-and- effect space weather phenomena permits a modular approach to forecast and prediction. In order of increasing difficulty these forecast modules are: –Solar Wind Disturbance Propagation –Energetic Particle Transport –Geospace Response –Solar Irradiance Prediction –Solar General Circulation In order of cause-to-effect these forecast modules are: –Solar General Circulation –Solar Irradiance Prediction –Solar Wind Disturbance Propagation –Energetic Particle Transport –Geospace Response The intrinsic potential for increased lead times for severe space weather warnings is as follows: –Solar Wind Disturbance Propagation [hours to days] –Energetic Particle Transport [minutes to hours] –Geospace Response [minutes to hours] –Solar Irradiance Prediction [hours to years] –Solar General Circulation [hours to years] All component modules of the end-to-end space weather numerical prediction suite will require: –Extensive ingest and assimilation of a wide variety of ground-based and satellite data to maintain fidelity. –Vast numbers of CPU and Cycle on high performance computing platforms, to achieve the requisite spatial and temporal resolution dictated by the underlying physics. –Periodic refresh of model methods and algorithms as new research becomes available and as customer needs continue to evolve for superior products and services.

SWPC’s Goal: Provide the right information… in the right format... at the right time… to the right people… to make the right decisions