SA44A-01 16:00h
USC/JPL GAIM: A Real-Time Global Ionospheric Data Assimilation Model
We are in the midst of a revolution in ionospheric remote sensing driven by the illuminating powers of ground and space-based GPS receivers, new UV remote sensing satellites, and the advent of data assimilation techniques for space weather. The University of Southern Califronia (USC) and the Jet Propulsion Laboratory (JPL) have jointly developed a Global Assimilative Ionospheric Model (GAIM) to monitor space weather, study storm effects, and provide ionospheric calibration for DoD customers and NASA flight projects. GAIM is a physics-based 3D data assimilation model that uses both 4DVAR and Kalman filter techniques to solve for the ion & electron density state and key drivers such as equatorial electrodynamics, neutral winds, and production terms. GAIM accepts as input ground GPS TEC data from 900+ sites, occultation links from CHAMP, SAC-C, IOX, and the coming COSMIC constellation, UV limb and nadir scans from the TIMED and DMSP satellites, and in situ data from a variety of satellites (C/NOFS & DMSP). GAIM can ingest multiple data sources in real time, updates the 3D electron density grid every 5 minutes, and solves for improved drivers every 1-2 hours. GAIM density retrievals have been validated by comparisons to vertical TEC measurements from TOPEX & JASON, slant TEC measurements from independent GPS sites, density profiles from ionosondes & incoherent scatter radars, and alternative tomographic retrievals. Daily USC/JPL GAIM runs have been operational since March 2003 using 100-200 ground GPS sites as input and TOPEX/JASON and ionosondes for daily validation. A prototype real-time GAIM system has been running since May 2004. RT GAIM ingests TEC data from 77+ streaming GPS sites every 5 minutes, adds more TEC for better global coverage every hour from hourly GPS sites, and updates the ionospheric state every 5 minutes using the Kalman filter. We plan to add TEC links from COSMIC occultations and UV radiance data from the DMSP satellites, when they become available, to the daily and RT GAIM runs. Our presentation will include results from numerous validation case studies and one year of JASON validation statistics. Customers are currently evaluating the accuracy of USC/JPL GAIM "nowcasts" for ray tracing applications and trans-ionospheric path delay calibration.
http://iono.jpl.nasa.gov/gaim
SA44A-02 16:15h
USU GAIM: An Operational Data Assimilation Model of the Ionosphere
Physics-based data assimilation models of the ionosphere were developed at Utah State University as part of a DoD Multidisciplinary University Research Initiative (MURI) program. The USU effort was called Global Assimilation of Ionospheric Measurements (GAIM). One of the USU data assimilation models has been selected for operational use at the Air Force Weather Agency (AFWA) in Omaha, Nebraska. This model is a Gauss-Markov Kalman Filter (GMKF) model, and it uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) measurements. The physics-based model is the Ionosphere Forecast Model (IFM), which is global and covers the E-region, F-region, and topside from 90 to 1400 km. It takes account of five ion species (NO$^{+}$, O$_{2}$$^{+}$, N$_{2}$$^{+}$, O$^{+}$, H$^{+}$). The Gauss-Markov Kalman Model assimilates bottom-side Ne profiles from a variable number of ionosondes, slant TEC from a variable number of ground GPS/TEC stations, in situ Ne from four DMSP satellites, and line-of-sight UV emissions measured by satellites. With the GMKF model the ionospheric densities obtained from the IFM constitute a background ionospheric density field on which perturbations are superimposed based on the available data sources and their errors. The density perturbations and the associated errors evolve over time via a statistical Gauss-Markov process. The configuration of the GMKF model and relevant applications will be presented.
SA44A-03 INVITED 16:30h
Far Ultraviolet Remote Sensing of Space Weather Parameters: Current and Future Systems
Far ultraviolet remote sensing offers the opportunity to provide a direct and timely measurement of space weather inputs. FUV remote sensing takes advantage of the fact that O2 is a strong absorber in the region between 115 and 185 nm, thus allowing thermospheric and ionospheric emissions to be observed against a dark Earth disk. FUV sensors are relatively light weight, compact, and inexpensive while offering proven technology and well validated products. We will discuss the activities at APL, in the development of sensors and operational software, to afford the user community with near real-time space weather information from FUV sensor data. In particular, we provide thermospheric density, temperature and composition; ionospheric electron density profiles and TEC; and auroral energy deposition. FUV imaging provides the ability to image ionospheric depletions. Examples of these products will be shown and the operational requirements will be discussed. We will also address the needs for future systems and their operational requirements and how they can best be addressed.
SA44A-04 16:50h
Automated Detection and Tracking of Equatorial Plasma Depletions Using Ground-Based Optical Imagers
Optical imaging is one of the few means available for determining space weather parameters simultaneously over large areas, but tropospheric cloud cover presents a significant barrier to operational use of data from ground-based optical instruments. Distributed sensors experiencing different tropospheric conditions but with overlapping fields of view in the upper atmosphere are one possible solution to the cloud cover difficulty, while intelligent processing of imager data to discriminate between clouds and upper atmospheric features is another potential means of providing reliable data output from only a single instrument. We evaluate and discuss a variety of processing algorithms developed or adapted for the purpose of detecting and tracking equatorial plasma depletions in all-sky imager data under realistic conditions including significant cloud cover. Our most successful technique thus far relies on discrimination between depletions and other image features based on their signatures in velocity and correlation space rather than physical coordinates. In addition to allowing identification and tracking of the depletions, accurate knowledge of the velocity allows multiple frames of image data to be processed coherently in the reference frame moving with the depletions. This processing can virtually eliminate cloud effects up to 50 percent cloud cover. With externally provided velocity information (such as from a spaced-antenna scintillation system, for example) or an improved velocity algorithm, useful data can be obtained at even greater cloud cover fractions. A similar motion-based technique can also be applied to the background star field, allowing stars to be easily distinguished from pixel noise and hot pixels for rapid automatic identification of image regions affected by clouds without the need to identify, locate, or track any specific stars.
SA44A-05 17:05h
Performance of the GLOBALink/HF Network during the Halloween Storm Period of 2003
The GLOBALink/HF system, developed and managed by ARINC, is a global high frequency data link communications network providing service to commercial aviation worldwide. It consists of 14 ground stations located around the globe, and a network control center located in Annapolis. The system was designed to provide reliable aircraft communications through the use of multi-station accessibility, quasi-dynamic frequency management, and a robust time-diversity modem with equalization. Although HF (i.e., 3-30 MHz) signaling has a poor reputation when considering individual circuits, it has been shown that near-real time channel evaluation and/or adaptive frequency management can improve performance considerably. Moreover, multi-station network operation provides an additional form of diversity, which is probably the most valuable design strategy. Our paper briefly describes the system, but the major discussion will be about performance metrics derived during super storms. The Halloween storm period of October-November 2003 was a period of significant ionospheric effects. Large geomagnetic storms were evidenced. We have examined the impact on HFDL of the various phenomena observed during this period. We have found some impact on HFDL performance for the October 29-31 period, but it is minimal in amplitude. While HFDL is based upon HF propagation, a medium known for its vulnerability to ionospheric variability, the system performance metric does not reflect this vulnerability to a significant degree. This is thought to be the result of the substantial amount of diversity built into the system, especially the adaptive frequency management system, Dynacastr, a system developed by RPSI. The adaptive frequency management system involves the use of active frequency tables (or AFTs) that are based upon space weather observables. During the stormy weeks of October and November, ARINC issued over seven changes to the AFTs used by every HFDL station. These changes helped the HFDL network to maintain a delivered message success rate of 97%. The paper outlines how this was accomplished.
SA44A-06 17:20h
A dynamic model of the high-latitude geomagnetic field
A model for the time-dependence of the high-latitude ground magnetic field and its time rate of change, dB/dt, is presented. The model coefficients are computed at an annular grid from magnetic field measurements from the IMAGE meridional array. The nonlinear response at high activity is represented by a local-linear model. The magnetic field model is driven by real-time solar wind/IMF datastreams from the ACE spacecraft. We report on the field response during isolated substorms and the storms of October-November 2003. In those events the model prediction error for the field and its time rate of change is measured as a function of geomagnetic coordinates and activity level. Based on the predicted dB/dt we estimate the GIC disturbance level and compare with GIC measurements at the Finnish power grid.
http://lep694.gsfc.nasa.gov/RTSM/
SA44A-07 INVITED 17:35h
Space Weather Products from the Space Environment Center: present and future
The Space Environment Center, located in Boulder, Colorado, is the nation's official source for space weather alerts, warnings, watches and forecasts. The center has been producing space weather products for the past 40 years, and the suite of data, models and products has evolved as scientific understanding and technical capabilities have advanced. In addition, regular interaction with the user community has provided important guidance in the determination of priorities for development. More recently the center has transitioned to the National Weather Service. In this presentation I will provide a broad overview of space weather products that are currently produced by the center, with an emphasis on the more recent developments. I will also discuss a few of the models, data, and products that are in development and well on the path to becoming operational in the near future. I will also discuss some general aspects of the process for product development and implementation under the new NWS management environment.