Engineering topics

Shim, J. S.

Publications and source records attributed to Shim, J. S..

4 records

NASA NTRS2019

Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations

Accurate determination of thermospheric neutral density holds crucial importance for satellited rag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and threephysics based models of the ionosphere thermosphere are compared with the neutral densities along the Challenging MicroSatellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias),(2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set ofmetrics for the neutral density.

Eyiguler, E. Ceren Kalafatoglu↗

NASA NTRS2017

CEDAR-GEM Challenge for Systematic Assessment of Ionosphere/Thermosphere Models in Predicting TEC During the 2006 December Storm Event

In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14-15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.

Shim, J. S.↗

NASA NTRS2012

NASA GSFC CCMC Recent Model Validation Activities

The Community Coordinated Modeling Center (CCMC) holds the largest assembly of state-of-the-art physics-based space weather models developed by the international space physics community. In addition to providing the community easy access to these modern space research models to support science research, its another primary goal is to test and validate models for transition from research to operations. In this presentation, we provide an overview of the space science models available at CCMC. Then we will focus on the community-wide model validation efforts led by CCMC in all domains of the Sun-Earth system and the internal validation efforts at CCMC to support space weather servicesjoperations provided its sibling organization - NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov). We will also discuss our efforts in operational model validation in collaboration with NOAA/SWPC.

Rastaetter, L.↗

NASA NTRS2011

CEDAR Electrodynamics Thermosphere Ionosphere (ETI) Challenge for Systematic Assessment of Ionosphere/Thermosphere Models: NmF2, hmF2, and Vertical Drift Using Ground-Based Observations

Objective quantification of model performance based on metrics helps us evaluate the current state of space physics modeling capability, address differences among various modeling approaches, and track model improvements over time. The Coupling, Energetics, and Dynamics of Atmospheric Regions (CEDAR) Electrodynamics Thermosphere Ionosphere (ETI) Challenge was initiated in 2009 to assess accuracy of various ionosphere/thermosphere models in reproducing ionosphere and thermosphere parameters. A total of nine events and five physical parameters were selected to compare between model outputs and observations. The nine events included two strong and one moderate geomagnetic storm events from GEM Challenge events and three moderate storms and three quiet periods from the first half of the International Polar Year (IPY) campaign, which lasted for 2 years, from March 2007 to March 2009. The five physical parameters selected were NmF2 and hmF2 from ISRs and LEO satellites such as CHAMP and COSMIC, vertical drifts at Jicamarca, and electron and neutral densities along the track of the CHAMP satellite. For this study, four different metrics and up to 10 models were used. In this paper, we focus on preliminary results of the study using ground-based measurements, which include NmF2 and hmF2 from Incoherent Scatter Radars (ISRs), and vertical drifts at Jicamarca. The results show that the model performance strongly depends on the type of metrics used, and thus no model is ranked top for all used metrics. The analysis further indicates that performance of the model also varies with latitude and geomagnetic activity level.

Shim, J. S.↗