skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Space Weather Modeling Capabilities Assessment: Auroral Precipitation and High‐Latitude Ionospheric Electrodynamics
Abstract As part of its International Capabilities Assessment effort, the Community Coordinated Modeling Center initiated several working teams, one of which is focused on the validation of models and methods for determining auroral electrodynamic parameters, including particle precipitation, conductivities, electric fields, neutral density and winds, currents, Joule heating, auroral boundaries, and ion outflow. Auroral electrodynamic properties are needed as input to space weather models, to test and validate the accuracy of physical models, and to provide needed information for space weather customers and researchers. The working team developed a process for validating auroral electrodynamic quantities that begins with the selection of a set of events, followed by construction of ground truth databases using all available data and assimilative data analysis techniques. Using optimized, predefined metrics, the ground truth data for selected events can be used to assess model performance and improvement over time. The availability of global observations and sophisticated data assimilation techniques provides the means to create accurate ground truth databases routinely and accurately.  more » « less
Award ID(s):
1663770
PAR ID:
10374669
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Space Weather
Volume:
17
Issue:
2
ISSN:
1542-7390
Page Range / eLocation ID:
p. 212-215
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; (, Space Weather)
    Abstract Ionospheric conductance is a crucial factor in regulating the closure of magnetospheric field‐aligned currents through the ionosphere as Hall and Pedersen currents. Despite its importance in predictive investigations of the magnetosphere‐ionosphere coupling, the estimation of ionospheric conductance in the auroral region is precarious in most global first‐principles‐based models. This impreciseness in estimating the auroral conductance impedes both our understanding and predictive capabilities of the magnetosphere‐ionosphere system during extreme space weather events. In this article, we address this concern, with the development of an advanced Conductance Model for Extreme Events (CMEE) that estimates the auroral conductance from field‐aligned current values. CMEE has been developed using nonlinear regression over a year's worth of 1‐min resolution output from assimilative maps, specifically including times of extreme driving of the solar wind‐magnetosphere‐ionosphere system. The model also includes provisions to enhance the conductance in the aurora using additional adjustments to refine the auroral oval. CMEE has been incorporated within the Ridley Ionosphere Model (RIM) of the Space Weather Modeling Framework (SWMF) for usage in space weather simulations. This paper compares performance of CMEE against the existing conductance model in RIM, through a validation process for six space weather events. The performance analysis indicates overall improvement in the ionospheric feedback to ground‐based space weather forecasts. Specifically, the model is able to improve the prediction of ionospheric currents, which impact the simulateddB/dtandΔB, resulting in substantial improvements indB/dtpredictive skill. 
    more » « less
  2. ; ; ; ; (, Space Science Reviews)
    Abstract Within the fully integrated magnetosphere-ionosphere system, many electrodynamic processes interact with each other. We review recent advances in understanding three major meso-scale coupling processes within the system: the transient field-aligned currents (FACs), mid-latitude plasma convection, and auroral particle precipitation. (1) Transient FACs arise due to disturbances from either dayside or nightside magnetosphere. As the interplanetary shocks suddenly compress the dayside magnetosphere, short-lived FACs are induced at high latitudes with their polarity successively changing. Magnetotail dynamics, such as substorm injections, can also disturb the current structures, leading to the formation of substorm current wedges and ring current disruption. (2) The mid-latitude plasma convection is closely associated with electric fields in the system. Recent studies have unraveled some important features and mechanisms of subauroral fast flows. (3) Charged particles, while drifting around the Earth, often experience precipitating loss down to the upper atmosphere, enhancing the auroral conductivity. Recent studies have been devoted to developing more self-consistent geospace circulation models by including a better representation of the auroral conductance. It is expected that including these new advances in geospace circulation models could promisingly strengthen their forecasting capability in space weather applications. The remaining challenges especially in the global modeling of the circulation system are also discussed. 
    more » « less
  3. ; ; ; ; (, Space Weather)
    Abstract We develop an Imbalanced Regression Artificial Neural Network model for the Auroral electrojet index (IRANNA) to predict the SuperMAG SML index, addressing the heavily imbalanced distribution of the SML data set. The data set contains mostly quiet‐time values of lesser importance and very few strong‐to‐extreme values of interest, such as those associated with super substorms. Traditional prediction models, which minimize mean squared error uniformly across the whole data set, are often skewed by this imbalance, prioritizing the lower, quiet‐time values and consequently underestimating strong geomagnetic events. The IRANNA model addresses this issue by using a customized weighting scheme in the loss function, enabling it to predict strong‐to‐extreme events accurately for the first time. The model takes solar wind parameters as inputs and predicts the logarithm of the absolute SML values. It does not rely on past values of the SML index, differentiating it from other models that use historical data for prediction. The model has demonstrated its ability to predict the peak amplitudes of strong‐to‐extreme events across various statistical analyses, event studies, and virtual experiments. Despite this success, challenges remain, particularly during localized electrojet events and when upstream solar wind data propagation is unreliable. This study emphasizes the importance of using imbalanced regression techniques, especially in space physics, where data sets are inherently skewed. It also highlights the potential of the IRANNA model to provide valuable insights into the magnetosphere's response to solar wind driving, improving space weather forecasting and offering new tools for investigating magnetospheric dynamics. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, Journal of Geophysical Research: Space Physics)
    Abstract The accurate determination of auroral precipitation in global models has remained a daunting and rather inexplicable obstacle. Understanding the calculation and balance of multiple sources that constitute the aurora, and their eventual conversion into ionospheric electrical conductance, is critical for improved prediction of space weather events. In this study, we present a semi‐physical global modeling approach that characterizes contributions by four types of precipitation—monoenergetic, broadband, electron, and ion diffuse—to ionospheric electrodynamics. The model uses a combination of adiabatic kinetic theory and loss parameters derived from historical energy flux patterns to estimate auroral precipitation from magnetohydrodynamic (MHD) quantities. It then converts them into ionospheric conductance that is used to compute the ionospheric feedback to the magnetosphere. The model has been employed to simulate the 5–7 April 2010Galaxy15space weather event. Comparison of auroral fluxes show good agreement with observational data sets like NOAA‐DMSP and OVATION Prime. The study shows a dominant contribution by electron diffuse precipitation, accounting for ∼74% of the auroral energy flux. However, contributions by monoenergetic and broadband sources dominate during times of active upstream solar conditions, providing for up to 61% of the total hemispheric power. The study also finds a greater role played by broadband precipitation in ionospheric electrodynamics which accounts for ∼31% of the Pedersen conductance. 
    more » « less
  5. ; ; ; ; ; ; (, Frontiers in Astronomy and Space Sciences)
    In this study, a detailed metric survey on the “Galaxy 15” (April 2010) space weather event is conducted to validate MAGNetosphere–Ionosphere–Thermosphere (MAGNIT), a semi-physical auroral ionospheric conductance model characterizing four precipitation sources, against AMPERE measurements via field-aligned current (FAC) characteristics. As part of this study, the comparative performance of three ionosphere electrodynamic specifications involving auroral conductance models, MAGNIT, Ridley Legacy Model (RLM) (empirical), and Conductance Model for Extreme Events (CMEE) (empirical), within the Space Weather Modeling Framework (SWMF), is demonstrated. Overall, MAGNIT exhibits marginally improved predictions; root mean square error values in upward and downward FACs of MAGNIT predictions compared to AMPERE data are smaller than those of CMEE and Ridley Ionosphere Model (RIM) by ∼ 12.7% and ∼ 6.24% before the storm, ∼ 4.52% and ∼ 2.13% better during the main phase, ∼ 1.98% and ∼ 1.27% worse during the second minimum, and better by ∼ 1.84% and ∼ 1.49% by the beginning of the recovery, respectively. In all three model configurations, the dusk and night magnetic local time (MLT) sectors over-predict throughout the storm, while the day and dawn MLT sectors under-predict in response to interplanetary magnetic field (IMF) conditions. In addition to accuracy and bias, similar results and conclusions are drawn from additional metrics, including in the categories of correlation, precision, extremes, and skill, and recommendations are made for the best-performing model configuration in each metric category. Visual data–model comparisons conducted by studying the FAC location and latitude/MLT spread throughout various phases of the storm suggest that the spatial extent of the FACs is captured relatively well in the night-side auroral oval, unlike in the day-side oval. The spread in latitude of the FACs matches that in the previous literature on other model performances. This information on auroral precipitation sources and their weight on FACs, along with metrics from model–data comparisons, can be used to modify MAGNIT settings to optimize SWMF model performance. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email