On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting
Abstract Space weather represents a severe threat to ground‐based infrastructure, satellites and communications. Accurately forecasting when such threats are likely (e.g., when we may see large induced currents) will help to mitigate the societal and financial costs. In recent years computational mo...
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| Format: | Article |
| Language: | English |
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Wiley
2022-07-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2022SW003098 |
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| author | A. W. Smith C. Forsyth I. J. Rae T. M. Garton C. M. Jackman M. Bakrania R. M. Shore G. S. Richardson C. D. Beggan M. J. Heyns J. P. Eastwood A. W. P. Thomson J. M. Johnson |
| author_facet | A. W. Smith C. Forsyth I. J. Rae T. M. Garton C. M. Jackman M. Bakrania R. M. Shore G. S. Richardson C. D. Beggan M. J. Heyns J. P. Eastwood A. W. P. Thomson J. M. Johnson |
| author_sort | A. W. Smith |
| collection | DOAJ |
| description | Abstract Space weather represents a severe threat to ground‐based infrastructure, satellites and communications. Accurately forecasting when such threats are likely (e.g., when we may see large induced currents) will help to mitigate the societal and financial costs. In recent years computational models have been created that can forecast hazardous intervals, however they generally use post‐processed “science” solar wind data from upstream of the Earth. In this work we investigate the quality and continuity of the data that are available in Near‐Real‐Time (NRT) from the Advanced Composition Explorer and Deep Space Climate Observatory (DSCOVR) spacecraft. In general, the data available in NRT corresponds well with post‐processed data, however there are three main areas of concern: greater short‐term variability in the NRT data, occasional anomalous values and frequent data gaps. Some space weather models are able to compensate for these issues if they are also present in the data used to fit (or train) the model, while others will require extra checks to be implemented in order to produce high quality forecasts. We find that the DSCOVR NRT data are generally more continuous, though they have been available for small fraction of a solar cycle and therefore DSCOVR has experienced a limited range of solar wind conditions. We find that short gaps are the most common, and are most frequently found in the plasma data. To maximize forecast availability we suggest the implementation of limited interpolation if possible, for example, for gaps of 5 min or less, which could increase the fraction of valid input data considerably. |
| format | Article |
| id | doaj-art-c6d747c6c0aa42ec962d3f0a676f5f4a |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2022-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-c6d747c6c0aa42ec962d3f0a676f5f4a2025-01-14T16:26:58ZengWileySpace Weather1542-73902022-07-01207n/an/a10.1029/2022SW003098On the Considerations of Using Near Real Time Data for Space Weather Hazard ForecastingA. W. Smith0C. Forsyth1I. J. Rae2T. M. Garton3C. M. Jackman4M. Bakrania5R. M. Shore6G. S. Richardson7C. D. Beggan8M. J. Heyns9J. P. Eastwood10A. W. P. Thomson11J. M. Johnson12Mullard Space Science Laboratory UCL Dorking UKMullard Space Science Laboratory UCL Dorking UKDepartment of Mathematics, Physics and Electrical Engineering Northumbria University Newcastle upon Tyne UKSchool of Cosmic Physics, DIAS Dunsink Observatory Dublin Institute for Advanced Studies Dublin IrelandSchool of Cosmic Physics, DIAS Dunsink Observatory Dublin Institute for Advanced Studies Dublin IrelandMullard Space Science Laboratory UCL Dorking UKBritish Antarctic Survey Cambridge UKBritish Geological Survey Edinburgh UKBritish Geological Survey Edinburgh UKImperial College London London UKImperial College London London UKBritish Geological Survey Edinburgh UKCooperative Institute for Research in Environmental Sciences University of Colorado Boulder Boulder CO USAAbstract Space weather represents a severe threat to ground‐based infrastructure, satellites and communications. Accurately forecasting when such threats are likely (e.g., when we may see large induced currents) will help to mitigate the societal and financial costs. In recent years computational models have been created that can forecast hazardous intervals, however they generally use post‐processed “science” solar wind data from upstream of the Earth. In this work we investigate the quality and continuity of the data that are available in Near‐Real‐Time (NRT) from the Advanced Composition Explorer and Deep Space Climate Observatory (DSCOVR) spacecraft. In general, the data available in NRT corresponds well with post‐processed data, however there are three main areas of concern: greater short‐term variability in the NRT data, occasional anomalous values and frequent data gaps. Some space weather models are able to compensate for these issues if they are also present in the data used to fit (or train) the model, while others will require extra checks to be implemented in order to produce high quality forecasts. We find that the DSCOVR NRT data are generally more continuous, though they have been available for small fraction of a solar cycle and therefore DSCOVR has experienced a limited range of solar wind conditions. We find that short gaps are the most common, and are most frequently found in the plasma data. To maximize forecast availability we suggest the implementation of limited interpolation if possible, for example, for gaps of 5 min or less, which could increase the fraction of valid input data considerably.https://doi.org/10.1029/2022SW003098geomagnetically induced currentsforecastingnear real timeoperationalresearch to operations |
| spellingShingle | A. W. Smith C. Forsyth I. J. Rae T. M. Garton C. M. Jackman M. Bakrania R. M. Shore G. S. Richardson C. D. Beggan M. J. Heyns J. P. Eastwood A. W. P. Thomson J. M. Johnson On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting Space Weather geomagnetically induced currents forecasting near real time operational research to operations |
| title | On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting |
| title_full | On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting |
| title_fullStr | On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting |
| title_full_unstemmed | On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting |
| title_short | On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting |
| title_sort | on the considerations of using near real time data for space weather hazard forecasting |
| topic | geomagnetically induced currents forecasting near real time operational research to operations |
| url | https://doi.org/10.1029/2022SW003098 |
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