SA41B-01 INVITED
Challenges to Solar Flare Prediction
Solar flares are a significant driver of violent space weather. With the availability of high cadence photospheric and chromospheric data from the USAF's Optical Solar PAtrol Network (OSPAN) Telescope at the National Solar Observatory, we have gained insights into potential uses of the data for solar flare prediction. We will consider the need for timeliness and high cadence data. Using examples of active region temporal evolutionusing measurements of the solar photosphere and its magnetic fields,chromosphere and corona, we will explore the promises for forecasting the onset of solar flares.
SA41B-02
Using Heliospheric Imaging for Storm Forecasting – SMEI CME Observations as a Tool for Operational Forecasting at AFWA
Observations of coronal mass ejections (CMEs) from heliospheric imagers such as the Solar Mass Ejection Imager (SMEI) can lead to significant improvements in operational space weather forecasting. We are working with the Air Force Weather Agency (AFWA) to ingest SMEI all-sky imagery with appropriate tools to help forecasters improve their operational space weather forecasts. We describe two approaches: 1) Near- real time analysis of propagating CMEs from SMEI images alone combined with near-Sun observations of CME onsets and, 2) Using these calculations of speed as a mid-course correction to the HAFv2 solar wind model forecasts. HAFv2 became operational at AFWA in late 2006. The objective is to determine a set of practical procedures that the duty forecaster can use to update or correct a solar wind forecast using heliospheric imager data. SMEI observations can be used inclusively to make storm forecasts, as recently discussed in Webb et al. (Space Weather, in press, 2008). We have developed a point-and-click analysis tool for use with SMEI images and are working with AFWA to ensure that timely SMEI images are available for analyses. When a frontside solar eruption occurs, especially if within about 45 deg. of Sun center, a forecaster checks for an associated CME observed by a coronagraph within an appropriate time window. If found, especially if the CME is a halo type, the forecaster checks SMEI observations about a day later, depending on the apparent initial CME speed, for possibly associated CMEs. If one is found, then the leading edge is measured over several successive frames and an elongation-time plot constructed. A minimum of three data points, i.e., over 3-4 orbits or about 6 hours, are necessary for such a plot. Using the solar source location and onset time of the CME from, e.g., SOHO observations, and assuming radial propagation, a distance-time relation is calculated and extrapolated to the 1 AU distance. As shown by Webb et al., the storm onset time is then expected to be about 3 hours after this 1 AU arrival time (AT). The prediction program is updated as more SMEI data become available. Currently when an appropriate solar event occurs, AFWA routinely runs the HAFv2 model to make a forecast of the shock and ejecta arrival times at Earth. SMEI data can be used to improve this prediction. The HAFv2 model can produce synthetic sky maps of predicted CME brightness for comparison with SMEI images. The forecaster uses SMEI imagery to observe and track the CME. The forecaster then measures the CME location and speed using the SMEI imagery and the HAFv2 synthetic sky maps. After comparing the SMEI and HAFv2 results, the forecaster can adjust a key input to HAFv2, such as the initial speed of the disturbance at the Sun or the mid-course speed. The forecaster then iteratively runs HAFv2 until the observed and forecast sky maps match. The final HAFv2 solution becomes the new forecast. When the CME/shock arrives at (or does not reach) Earth, the forecaster verifies the forecast and updates the forecast skill statistics. Eventually, we plan to develop a more automated version of this procedure.
SA41B-03
AIM receiver/communication lock analysis: Space weather relationships
The AIM (Aeronomy of Ice in the Mesosphere) spacecraft (launched on 25 April 2007) is in low-Earth orbit. Some days after launch, AIM began to exhibit a problem in which it would not always achieve proper receiver uplink communications lock. In this context, we examined solar conditions and geomagnetic activity. We have found that higher solar wind speeds often lead to greater geomagnetic activity and this, in turn, seems to lead to improved AIM operations. In this talk we present analysis of AIM bitlock to show when relative improvements or diminutions in spacecraft operations have occurred. We conclude that the spacecraft bitlock problem clearly is related, in part, to space environment conditions (along with a gradual secular trend toward lower performance). The best predicator of 'good lock' state seems to be a shift from low (or quiet) geomagnetic and solar wind conditions toward more disturbed conditions. It is essential to note that use of space weather forecast tools has been an important, supportive adjunct to this key new space flight program.
SA41B-04
First-principles-based modeling of geomagnetically induced currents at mid- and low- latitudes
Recently, Pulkkinen et al. (2007, Annales Geophysicae) introduced an approach to predict geomagnetically induced current (GIC) flow in high-voltage power transmission systems based on first-principles modeling of the near-space plasma environment. Their approach that has already been implemented as an experimental real-time system providing forecasts of GIC in the North American power transmission system, however, is applicable only to high-latitude situations. The accumulating new evidence is indicating that GIC is not only a high-latitude phenomenon but is important also at lower latitudes. Consequently, new tools and approaches are called for to address the newly appreciated truly global nature of GIC. In this paper we will briefly describe the current implementation of the experimental real-time GIC forecasting system operated at Community Coordinated Modeling Center (CCMC) at NASA/GSFC and address the shortcomings of the system. We will introduce the approach we have chosen to attack the problem of first- principles-based mid- and low-latitude GIC. The approach not only requires more comprehensive modeling of the near-space plasma environment by means of coupling global magnetohydrodynamic models to kinetic models of the inner magnetosphere (presented in a paper by Buzulukova et al., fall AGU 2008) but also more complex modeling of the geomagnetic induction process. We will present preliminary results generated by using the new GIC modeling capability and we will discuss the means to transfer the new approach into a real-time GIC forecasting system.
SA41B-05
The Operational USU GAIM Model
The operational Utah State University (USU) Global Assimilation of Ionospheric Measurements (GAIM) Gauss- Markov Kalman filter (GAIM-GM) uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of measurements in either real time or historical study modes. The USU GAIM-GM is now operational at the Air Force Weather Agency (AFWA) and the NASA Community Coordinated Modeling Center (CCMC). The model runs continuously in real time at AFWA and is available at the CCMC for "runs on request" for interested parties. 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 1400km. It takes account of five ion species (NO+, O2+, N2+, O+, H+). With the GAIM-GM model the ionospheric electron densities obtained from IFM are used as a background upon which perturbations are imposed based on available data and their errors. The density perturbations and associated errors evolve over time via a statistical Gauss-Markov process. The operational Gauss-Markov filter assimilates bottom-side electron density profiles from a variable number of ionosondes; slant TEC from a variable number of GPS satellite/ground station combinations; in-situ electron density from DMSP satellites; and certain line-of-sight UV radiances from satellite-based instruments. The operational model is currently being upgraded, primarily to improve model performance. This will be accomplished by splitting the global model into multiple regions that can run on multiple CPUs. Inter-regional communications within the model of both the state and covariance arrays results in model output equivalent to the monolithic global model, but at substantially increased speed. This allows additional data (both increased numbers of existing data types, and new data types) to be assimilated while maintaining real time operations. We will also discuss plans for future upgrades to the model.
SA41B-06
Challenges of Validating Global Assimilative Models of the Ionosphere
This paper addresses the often surprisingly difficult challenges that arise in conceptually simple validations of global models of the ionosphere. AFRL has been tasked with validating the Utah State University GAIM (Global Assimilation of Ionospheric Measurements) model of the ionosphere, which is run in real time by the Air Force Weather Agency. The USU-GAIM model currently assimilates, in addition to the voluminous GPS TEC data, in situ densities from DMSP satellites, UV radiances from SSUSI sensors on the DMSP satellites, and vertical profiles provided by a limited number of Digisondes. AFRL has performed a large number of USU-GAIM validations, using as ground truth values of foF2 and M(3000)F2 from non-assimilated ionograms, the in situ electron density at ~400 km provided by CHAMP, and the vertical TEC provided over ocean areas by TOPEX and JASON. USU GAIM runs at AFRL in about one-third real time. For validations against ionogram characteristics, AFRL usually works with a full month of GAIM and Digisonde data, which takes ~10 days to run. The long run times make it difficult to address essential "what if" scenarios, except for limited time intervals. Compounded with the problem of long run times is the fact that the UV observations are from a satellite that is only very rarely in near conjunction with the ground-truth satellites such as CHAMP and JASON, or near ground-based ionosondes. Exacerbating this problem even further is the fact that the most reliable assimilated UV data is from the evening equatorial ionosphere. It is often not possible to obtain useful ionogram characteristics for the evening equatorial ionosphere because of the occurrence of irregularities that lead to spread F echoes on the ionograms. We will discuss the impact of these various challenges on the lessons that can be learned from validation studies of global ionospheric models.
SA41B-07
New Space Weather Systems Under Development and Their Contribution to Space Weather Management
There have been notable successes during the past decade in the development of operational space
environment systems. Examples include the Magnetospheric Specification Model (MSM) of the Earth's
magnetosphere, 2000; SOLAR2000 (S2K) solar spectral irradiances, 2001; High Accuracy Satellite Drag
Model (HASDM) neutral atmosphere densities, 2004; Global Assimilation of Ionospheric Measurements
(GAIM) ionosphere specification, 2006; Hakamada-Akasofu-Fry (HAF) solar wind parameters, 2007;
Communication Alert and Prediction System (CAPS) ionosphere, high frequency radio, and scintillation S4
index prediction, 2008; and GEO Alert and Prediction System (GAPS) geosynchronous environment satellite
charging specification and forecast, 2008. Operational systems that are in active operational implementation
include the Jacchia-Bowman 2006/2008 (JB2006/2008) neutral atmosphere, 2009, and the Nowcast of
Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) aviation radiation model using the Radiation
Alert and Prediction System (RAPS), 2010. U.S. national agency and commercial assets will soon reach a
state where specification and prediction will become ubiquitous and where coordinated management of the
space environment and space weather will become a necessity. We describe the status of the CAPS, GAPS,
RAPS, and JB2008 operational development. We additionally discuss the conditions that are laying the
groundwork for space weather management and estimate the unfilled needs as we move beyond
specification and prediction efforts.
http://SpaceWx.com
SA41B-08
Real-Time and Event-Based Prediction Capabilities of Modern Space Science Models
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 analyze current forecasting potential of state-of-the-art models. These capabilities will be
demonstrated by an example, and we will comment on readiness for operations.
http://ccmc.gsfc.nasa.gov