SM34A-01 INVITED 

Applying Forecast Models from the Center for Integrated Space Weather Modeling

* Gehmeyr, M), University of Colorado - LASP, 1234 Innovation Drive, Boulder, CO 80303, United States Baker, D N), University of Colorado - LASP, 1234 Innovation Drive, Boulder, CO 80303, United States Millward, G), University of Colorado - LASP, 1234 Innovation Drive, Boulder, CO 80303, United States Odstrcil, D), University of Colorado - LASP, 1234 Innovation Drive, Boulder, CO 80303, United States

The Center for Integrated Space Weather Modeling (CISM) has developed three forecast models (FMs) for the Sun-Earth chain. They have been matured by various degrees toward the operational stage. The Sun-Earth FM suite comprises empirical and physical models: the Planetary Equivalent Amplitude (AP-FM), the Solar Wind (SW- FM), and the Geospace (GS-FM) models. We give a brief overview of these forecast models and touch briefly on the associated validation studies. We demonstrate the utility of the models: AP-FM supporting the operations of the AIM (Aeronomy of Ice in the Mesosphere) mission soon after launch; SW-FM providing assistance with the interpretation of the STEREO beacon data; and GS-FM combining model and observed data to characterize the aurora borealis. We will then discuss space weather tools in a more general sense, point out where the current capabilities and shortcomings are, and conclude with a look forward to what areas need improvement to facilitate better real-time forecasts.

SM34A-02 

Operational Weather Needs For Exploration Class Missions

* guetersloh, s (stephen.guetersloh-1@nasa.gov), NASA - Johnson Space Center, 2101 NASA parkway, SF2, houston, tx 77058, United States Zapp, N (neal.zapp-1@nasa.gov), NASA - Johnson Space Center, 2101 NASA parkway, SF2, houston, tx 77058, United States Rutledge, R (robert.d.rutledge@nasa.gov), NASA - Johnson Space Center, 2101 NASA parkway, SF2, houston, tx 77058, United States Semones, E (edward.j.semones@nasa.gov), NASA - Johnson Space Center, 2101 NASA parkway, SF2, houston, tx 77058, United States Johnson, S (a.s.johnson@nasa.gov), Lockheed Martin Space Operations, 1300 Hercules, houston, tx 77258, United States Chancellor, J (jefferey.c.chancellor@nasa.gov), Lockheed Martin Space Operations, 1300 Hercules, houston, tx 77258, United States George, T (tamra.george-1@nasa.gov), Lockheed Martin Space Operations, 1300 Hercules, houston, tx 77258, United States LIn, T (tom.c.lin@nasa.gov), Lockheed Martin Space Operations, 1300 Hercules, houston, tx 77258, United States Gaza, R (ramona.gaza-1@nasa.gov), Universities Space Research Association, 3600 Bay Area Blvd., houston, tx 77058, United States Zhou, D (zhou.dazhuang-1@nasa.gov), Universities Space Research Association, 3600 Bay Area Blvd., houston, tx 77058, United States Bevill, T (terrie.j.beville@nasa.gov), Lockheed Martin Space Operations, 1300 Hercules, houston, tx 77258, United States Flanders, J (joel.m.flanders@nasa.gov), Lockheed Martin Space Operations, 1300 Hercules, houston, tx 77258, United States

The minimization of crew exposure to space radiation is a major concern for manned spaceflight and will be even more important for the modern concept of longer duration exploration. The inherent protection afforded to astronauts by the magnetic field of the Earth in Low Earth Orbit (LEO) makes operations on the space shuttle or space station very different from operations in lunar transit or on the lunar surface. LEO missions would most likely require operations which are either extreme in duration or which encounter an extreme sequence of solar activity in order to represent significant immediate crew or mission risk. With the differences in risk to crew, vehicle and mission in mind, the new space weather monitoring goals for NASA and the Space Radiation Analysis Group (SRAG) at Johnson Space Center cover two distinct areas: (a) Moon base operations and (b) manned exploration of Mars. For both scenarios, though there will be some radiation exposure during mission transit through the trapped radiation belts and GCR exposure during transit to and stay on the surface (of more concern for the Mars mission), the primary concern outside the Earth's magnetopause is that of large Solar Particle Events (SPEs). Outside of the geo-magnetosphere, however, the situation is dramatically different. Exposure to the same event on the ISS and on the surface of the Moon or Mars may differ by several orders of magnitude, making radiation exposure and the dependence on space weather a limiting factor to exploration of the solar system. In the past, the focus of funded scientific research has not necessarily been directly applicable for use for or during mission operations. However, work is currently underway to bridge the gap that exists between research goals and operational needs to transition current and future resources into space weather products and services. We present the status of current operational efforts, needs and interests in situational space weather monitoring with the goal of developing new tools that will enable exploration class missions. http://srag.jsc.nasa.gov/MissionSpaceWeather/SpaceWeather.cfm

SM34A-03 

Statistical coupling between solar wind conditions and extreme geomagnetically induced current events

* Pulkkinen, A A (antti.a.pulkkinen@nasa.gov), UMBC/GEST at NASA/GSFC, Greenbelt Road, Greenbelt, MD 20771, United States Pirjola, R (risto.pirjola@fmi.fi), Finnish Meteorological Institute, Erik Palménin aukio 1, Helsinki, 00560, Finland Viljanen, A (ari.viljanen@fmi.fi), Finnish Meteorological Institute, Erik Palménin aukio 1, Helsinki, 00560, Finland

Recent advances in global MHD-based modeling of geomagnetically induced currents (GIC) from upstream solar wind (L1 observations) to the ground have opened new avenues for physics-based space weather forecasting. More specifically, Pulkkinen et al . (2007, Annales Geophysicae) showed that global MHD was able to generate realistic, in terms of spatiotemporal structure, GIC fluctuations having amplitudes comparable to the observed values. However, the situation is significantly more demanding if heliospheric models instead of L1 observations are used to generate the magnetospheric/GIC activity. Although current MHD-based solar wind models are capable of producing realistic large-scale behavior of the solar wind, for example, the turbulent interplanetary magnetic field (IMF) fluctuations are missing to a large degree. This obviously poses a problem for GIC modeling as the turbulent nature of IMF is possibly one of the main sources for large GIC. In this work a model for statistical coupling between hourly solar wind parameters and maximum GIC values observed on the ground is constructed. OMNI and IMAGE magnetometer array data from 1995-2006 are facilitated in the construction of the model. It is shown that there is a clear statistical coupling between the solar wind parameters, most importantly solar wind convective electric field and maximum GIC. The established connection between GIC and large-scale solar wind features enables new strategies for GIC forecasting even in the (partial) absence of information about turbulent IMF. In one possible strategy one would use heliospheric MHD models to generate large-scale solar wind features at L1, which would then be used to generate statistical estimate for GIC. In this paper the generation and the usage of the statistics in space weather forecasting and in other contexts is discussed.

SM34A-04 

Geomagnetic Storm and Substorm Predictions with the Real-Time WINDMI Model

* Mays, M L (lmays@physics.utexas.edu), The University of Texas at Austin, Institute for Fusion Studies, 1 University Station - C1500, Austin, TX 78712, Horton, W (horton@physics.utexas.edu), The University of Texas at Austin, Institute for Fusion Studies, 1 University Station - C1500, Austin, TX 78712, Kozyra, J U (jukozyra@umich.edu), University of Michigan, Department of Atmospheric, Oceanic and Space Sciences, 2455 Hayward St., Ann Arbor, MI 48109,

The Real-Time WINDMI model is an implementation of WINDMI, a low dimensional, plasma physics-based, nonlinear dynamical model of the coupled magnetosphere-ionosphere system. The system of nonlinear ordinary differential equations, which describes energy transfer into, and between dominant components of the nightside magnetosphere and ionosphere, is solved numerically to determine the state of each component. The model characterizes the energy stored in the ring current and the region 1 field-aligned current which are compared to the Dst and AL indices. Solar wind parameter measurements are available from the ACE satellite in real-time. These quantities are automatically downloaded every 10 minutes and used to derive the input solar wind driving voltage to the model. This allows the computation of model Dst and AL values by Real-Time WINDMI about 1-2 hours before index data is available at the Kyoto WDC Quicklook website. Model results are shown on the website (http://orion.ph.utexas.edu/~windmi/realtime/) and there is also an email alert system which sends a notification when Dst activity is predicted below -50 nT or AL activity below -500 nT. When data is available the model parameters are optimized every hour using a genetic algorithm, which has already been implemented for WINDMI. The model has captured about 13 storm and/or substorm events in the past 1.5 years it has been running. For these events, the Real-Time WINDMI output is studied for the rectified driving voltage compared to the Siscoe et al. voltage as input. The events the model did not capture are also investigated. The work is supported by NSF grant ATM-0638480. http://orion.ph.utexas.edu/~windmi/realtime/.

SM34A-05 

Forecasting the Spatio-Temporal Dynamics of the Magnetosphere

Chen, J (chenjian@astro.umd.edu), University of Maryland, Department of Astronomy, College Park, MD 20770, Sharma, A (ssh@astro.umd.edu), University of Maryland, Department of Astronomy, College Park, MD 20770, * Veeramani, T (tmani@umd.edu), University of Maryland, Department of Astronomy, College Park, MD 20770,

The spatio-temporal dynamics of the magnetosphere is a crucial component of effective space weather forecasting. The extensive data of the solar wind-magnetosphere interaction has been used to build predictive models of the magnetosphere based on nonlinear dynamical approaches. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the magnetic field variations at the ground stations as the magnetospheric response. The magnetic field perturbation at the ground and the corresponding solar wind data stations during the solar maximum period are compiled for these studies. The ground magnetometer data are from from CANOPUS, IMAGE and WDC magnetometer chain of stations. This new data set is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. In order to understand the predictability of space weather, the correlated database is used to study the causal relationships based on information theoretic approaches. This yields the mutual information between the solar wind variables and the ground magnetic field variations, and among the ground stations themselves. The information flow within the coupled system is analyzed by computing the transfer entropy among them.

SM34A-06 INVITED 

The Space Weather Re-analysis Project

* Ridley, A A (ridley@umich.edu), University of Michigan, Center for Space Environment Modeling Space Research Building, Ann Arbor, MI 48109-2143, United States Kihn, E (eric.a.kihn@noaa.gov), National Geophysical Data Center, NOAA 325 Broadway, Boulder, CO 80305-3328, United States

The Space Weather Re-analysis (SWR) project has a goal of creating a data-driven complete picture of the geospace environment over a whole solar cycle. While this long-term goal will most likely not be reached for many years, there has been significant progress in making data-driven modeling results available for significant amounts of time. For example, the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) technique was run for 14 years at a one-minute cadence utilizing ground-based magnetometer measurements. The Global Ionosphere-Thermosphere Model (GITM) has been run for about 8 years utilizing the AMIE output, providing hourly specifications of the upper atmosphere. This talk will discuss the issues in processing vast amounts of data for this project, validating the results, and some of the science that has resulted from undertaking this project. http://amie.engin.umich.edu/

Author(s) (2007), Title, Eos Trans. AGU, 88(52), Fall Meet. Suppl., Abstract #####-##.