SPA-Solar and Heliospheric Physics [SH]

SH22A
 CC:716B  Tuesday  1030h

Space Weather Prediction: Are We There Yet? I


Presiding:  C Russell, UCLA; J Giacalone, University of Arizona

SH22A-01 INVITED

Between the Rock and a Hard Place: The CCMC as a Transit Station Between Modelers and Forecasters

* Hesse, M (michael.hesse@nasa.gov), NASA Goddard Space Flight Center, Code 674, Greenbelt, MD 20771, United States

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involves model evaluations, model transitions to operations, and the development of draft Space Weather forecasting tools. This presentation will focus on the latter element. Specifically, we will discuss the process of transition research models, or information generated by research models, to Space Weather Forecasting organizations. We will analyze successes as well as obstacles to further progress, and we will suggest avenues for increased transitioning success.

http://ccmc.gsfc.nasa.gov

SH22A-02 INVITED

Predicting the Space Environment: the CISM Experience and Perspective

* Hughes, W (hughes@bu.edu), Department of Astronomy, Boston University, 725 Commonwealth Ave., Boston, MA 02215, United States

The Center for Integrated Space Weather Modeling (CISM) is an NSF Science and Technology Center that is a consortium of eleven institutions headed by Boston University. CISM focuses its activities around developing a suite of coupled, physics-based simulation models that describe the space environment from the Sun to the Earth. These models are being used as scientific tools to improve our understanding of the space environment, as education tools with which to help train the next generation of space scientists and space weather professionals, and as tools with which to predict the conditions in space. In this presentation we will first discuss forecasting needs and how physics-based models can and can't help. We will then describe CISM's collaboration with the Space Weather Prediction Center and others towards transitioning physics-based models into operational use and report on recent validation studies of CISM models and their usefulness as prediction tools.

SH22A-03 INVITED

The Space Weather Modeling Framework

* Toth, G (gtoth@umich.edu), University of Michigan, 2455 Hayward, Ann Arbor, MI 48109, United States

The Center for Space Environment Modeling (CSEM) at the University of Michigan has developed the Space Weather Modeling Framework (SWMF) that integrates independently developed models into a high performance simulation tool. The SWMF models a dozen physics domains spanning from the solar corona and heliosphere to the magnetosphere, ionosphere and thermosphere of the Earth. The SWMF can perform a realistic Sun-to-thermosphere simulation faster than real time on today's supercomputers. We also use subsets of the SWMF components to model various space physics systems. I will describe the current status of the SWMF and our plans for future development.

http://butch.engin.umich.edu/swmf/

SH22A-04 INVITED

Coronal Modeling: Present Status and Challenges for the Future*

* Linker, J A (linkerj@predsci.com), Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121,
Mikic, Z (mikicz@predsci.com), Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121,
Lionello, R (lionel@predsci.com), Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121,
Riley, P (pete@predsci.com), Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121,
Titov, V (titovv@predsci.com), Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121,

The solar corona strongly influences space weather at Earth, via eruptive phenomena such as coronal mass ejections, and through its structure, which leads to the formation of fast solar wind streams that trigger recurrent geomagnetic activity. MHD models that address both the dynamics and structure of the solar corona have advanced considerably in recent years, but many challenges remain if these models are to provide reliable space weather forecasting tools. In this talk we describe these challenges and the prospects for meeting them. *Research supported by NASA, NSF and AFOSR.

SH22A-05 INVITED

Numerical Simulation of Interplanetary Coronal Mass Ejections and STEREO Observations

* Odstrcil, D (dusan.odstrcil@noaa.gov) AB: Since numerical simulation of solar eruptions is still in research phase various empirically-based techniques have been developed for predicting arrivals of coronal mass ejections (CMEs) at the Earth. These techniques take advantage of remote observations of CMEs in coronagraphs, fit their geometric and kinematic properties, and apply kinematic or numerical model to predict heliospheric propagation and evolution. Due to limited remote and in-situ observations, simple geometric structures have been assumed so far and the validation of such predictions has been limited. We use the 3-D numerical heliospheric code ENLIL to simulate propagation of well-observed interplanetary CMEs in 2007 and 2008. This heliospheric code uses the MAS or WSA coronal model for computing the structured background solar wind and the so-called CME cone model for specification of the geometric and kinematic parameters of the hydrodynamic transient disturbances. We use the ACE, MESSENGER, and STEREO in-situ observations to constrain the model predictions. We found that "traditional" approaches based on simple cone models over-predicts disturbances at those spacecraft. New geometric models of CMEs are clearly needed and we have incorporated rope-like hydrodynamic structure. We present result achieved by launching the cone-like and rope-like structures and compare the heliospheric predictions with the multi-spacecraft in-situ observations.

SH22A-06 INVITED

Magnetospheric Space Weather Forecasting: Status and Challenges for the Upcoming Solar Cycle

* Raeder, J (J.Raeder@unh.edu), University of New Hampshire, Space Science Center 8 College Road, Durham, NH 03824, United States
Larson, D, University of New Hampshire, Space Science Center 8 College Road, Durham, NH 03824, United States
Li, W, University of New Hampshire, Space Science Center 8 College Road, Durham, NH 03824, United States
Vapirev, A, University of New Hampshire, Space Science Center 8 College Road, Durham, NH 03824, United States
Fuller-Rowell, T, CIRES, University of Colorado, Boulder, CO 80303, United States
Maruyama, N, CIRES, University of Colorado, Boulder, CO 80303, United States
Fok, M, NASA/GSFC, Code 673, Greenbelt, MD 20771, United States
Glocer, A, NASA/GSFC, Code 673, Greenbelt, MD 20771, United States
Toffoletto, F, Rice University, 6100 Main Street, Houston, TX 77001, United States
Hu, B, Rice University, 6100 Main Street, Houston, TX 77001, United States
Sazykin, S, Rice University, 6100 Main Street, Houston, TX 77001, United States
Richmond, A, NCAR/HAO, PO Box 3000, Boulder, CO 80307, United States
Maute, A, NCAR/HAO, PO Box 3000, Boulder, CO 80307, United States

As we approach the next solar maximum the predictive capabilities of magnetosphere models have increased significantly compared to the last maximum, due to model improvements, increased computational power, and more data sources. However, we also face new challenges as more and more human activities become susceptible to space weather effects such as trans-polar flights and GPS navigation and position controls. We first review the current status of coupled Geospace models and how new computational capabilities are making real-time forecasts much more feasible compared to just a few years ago. In the second part of this talk we outline the challenges that lie ahead to efficiently validate and transition the models into operations. We also discuss some ideas that may help streamlining the validation and transitioning process.

SH22A-07 INVITED

The Current Status and Challenges for Upper Atmosphere Models

* Schunk, R W (Robert.Schunk@usu.edu), Utah State University, Center for Atmospheric and Space Sciences, 4405 Old Main Hill, Logan, UT 84322-4405, United States

The Earth's upper atmosphere and ionosphere display highly variable and turbulent densities, temperatures, and winds, and these features are manifestations of space weather. During geomagnetic storms, wind gusts in the upper atmosphere can become supersonic, localized density troughs and peaks form, localized temperature hot spots occur, cyclonic-like and tornado-like winds periodically form, and the radiation levels can dramatically increase. Unfortunately, these space weather features can have detrimental effects on human systems and operations. As society becomes more dependent on sophisticated technological systems, specification and forecasting of space weather disturbances become crucial to our economy, safety, and security. Consequently, a significant effort is being devoted to developing both data assimilation and coupled physics-based models of the space environment. The data assimilation models are useful for specification and the coupled physics-based models are needed for forecasting. Significant progress has been made in the development of physics-based, Kalman filter, data assimilation models for the global ionosphere. The state-of-the-art models can assimilate several data types, including in situ electron densities from satellites, bottomside electron densities from 100 ionosondes, line-of-sight Total Electron Content (TEC) measurements between 1000 ground stations and the GPS satellites, TEC via occultations between low-altitude and high-altitude satellites, and line-of-sight ultraviolet emission data. Likewise, significant progress has been made in developing coupled physics-based models of the space environment from the Sun to the Earth. However, the construction of these models is not always straightforward for several reasons: (1) Although there are a lot of data available via the world wide web, the data quality is generally not adequate for data assimilation models and data errors are not routinely provided; (2) There is a limited number of real-time data sources for specification and forecast models; (3) The application of a rigorous Kalman filter is not feasible and approximations are necessary; (4) The coupled physics-based models have uncertain parameters that need to be determined and/or have missing physics; and (5) Validation of data assimilation and coupled physics-based models requires massive independent data sets so that statistics can be done to determine the accuracy of the models. The status and challenges related to the development of data assimilation and coupled physics-based models will be discussed.