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Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Towards GIC forecasting
T2 - Statistical downscaling of the geomagnetic field to improve geoelectric field forecasts
AU - Haines, Carl
AU - Owens, M
AU - Barnard, Luke
AU - Lockwood, Mike
AU - Beggan, Ciarán D.
AU - Thomson, A.W.P.
AU - Rogers, Neil
PY - 2022/1/31
Y1 - 2022/1/31
N2 - Geomagnetically induced currents (GICs) are an impact of space weather that can occur during periods of enhanced geomagnetic activity. GICs can enter into electrical power grids through earthed conductors, potentially causing network collapse through voltage instability or damaging transformers. It would be beneficial to power grid operators to have a forecast of GICs that could inform decision making on mitigating action. Long lead-time GIC forecasting requires magnetospheric models as drivers of geoelectric field models. However, estimation of the geoelectric field is sensitive to high-frequency geomagnetic field variations which operational global magneto-hydrodynamic models do not fully capture. Furthermore, an assessment of GIC forecast uncertainty would require a large ensemble of magnetospheric runs, which is computationally expensive. One solution that is widely used in climate science is “downscaling”, wherein sub-grid variations are added to model outputs on a statistical basis. We present proof-of-concept results for a method that temporally downscales low-resolution magnetic field data on a 1-hour timescale to 1-minute resolution, with the hope of improving subsequent geoelectric field magnitude estimates. An analogue ensemble (AnEn) approach is used to select similar hourly averages in a historical dataset, from which we separate the high-resolution perturbations to add to the hourly average values. We find that AnEn outperforms the benchmark linear-interpolation approach in its ability to accurately drive an impacts model, suggesting GIC forecasting would be improved. We evaluated the ability of AnEn to predict extreme events using the FSS, HSS, cost/loss analysis and BSS, finding that AnEn outperforms the “do-nothing” approach.
AB - Geomagnetically induced currents (GICs) are an impact of space weather that can occur during periods of enhanced geomagnetic activity. GICs can enter into electrical power grids through earthed conductors, potentially causing network collapse through voltage instability or damaging transformers. It would be beneficial to power grid operators to have a forecast of GICs that could inform decision making on mitigating action. Long lead-time GIC forecasting requires magnetospheric models as drivers of geoelectric field models. However, estimation of the geoelectric field is sensitive to high-frequency geomagnetic field variations which operational global magneto-hydrodynamic models do not fully capture. Furthermore, an assessment of GIC forecast uncertainty would require a large ensemble of magnetospheric runs, which is computationally expensive. One solution that is widely used in climate science is “downscaling”, wherein sub-grid variations are added to model outputs on a statistical basis. We present proof-of-concept results for a method that temporally downscales low-resolution magnetic field data on a 1-hour timescale to 1-minute resolution, with the hope of improving subsequent geoelectric field magnitude estimates. An analogue ensemble (AnEn) approach is used to select similar hourly averages in a historical dataset, from which we separate the high-resolution perturbations to add to the hourly average values. We find that AnEn outperforms the benchmark linear-interpolation approach in its ability to accurately drive an impacts model, suggesting GIC forecasting would be improved. We evaluated the ability of AnEn to predict extreme events using the FSS, HSS, cost/loss analysis and BSS, finding that AnEn outperforms the “do-nothing” approach.
KW - GIC
KW - geomagnetic fluctuations
KW - geoelectric fields and source currents
KW - statistical downscaling
U2 - 10.1029/2021SW002903
DO - 10.1029/2021SW002903
M3 - Journal article
VL - 20
JO - Space Weather
JF - Space Weather
SN - 1542-7390
IS - 1
M1 - e2021SW002903
ER -