Solar wind data assimilation - maximising the accuracy of space-weather forecasting
Solar wind data assimilation - maximising the accuracy of space-weather forecasting
批准号:
NE/S010033/1
负责人:
Mathew Owens
金额:
$45.6万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --
中文摘要
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英文摘要
"Space weather" describes changes in the Sun's magnetic field which occur over seconds to days. It can damage space- and ground-based technologies, particularly power, communication and Earth-observation systems. In order to forecast space weather with more than about 1 hour of warning time, it is necessary to accurately forecast the solar wind, the continual flow of material away from the Sun which fills the solar system. At present, telescopic observations of the Sun's surface are used to provide the starting conditions for computer simulations of the solar wind. These simulations propagate conditions all the way from the Sun to Earth, where the space-weather impact can be estimated. There are ongoing efforts to improve solar wind simulations and to make more accurate measurements of the solar wind near the Sun. But spacecraft also routinely make direct measurements of the solar wind far from the Sun, which provide useful additional information that is not presently used to improve forecasts. Experience from terrestrial weather prediction shows that the biggest advance in forecasting ability can be achieved by using the available observations to regularly "nudge" the computer simulations back towards reality.This observational "nudging" of computer models is called "data assimilation" (DA), and it is at the heart of modern weather forecasting. Accurate weather forecast lead times have advanced about a day a decade, mainly due to advances in DA. Given this success, it is time to fully explore DA capabilities for space weather, in particular the solar wind. Our group has recently made preliminary studies in this area. The proposed work will build on this to develop and test the first ever solar wind data assimilation (SWDA) system using a physics-based, operational forecast simulation of the solar wind. This represents the first effort to apply DA to the solar wind in a manner comparable to terrestrial numerical weather prediction. The solar wind, however, differs from the atmosphere and other geophysical systems in a number of fundamental ways, thus adapting existing DA techniques will involve overcoming a number of scientific challenges. This will form the core science of the proposed work.In addition to improving space-weather forecasting, the SWDA system will enable cutting-edge space-weather research. One by-product of testing the SWDA system is that we will combine models and observations to produce the most accurate estimate to date of the solar wind conditions back near the Sun, where we are unable to directly make measurements. This will help us to understand which magnetic structures on the Sun are related to different solar wind conditions, serving as a direct observational test for theoretical models of solar wind formation. The SWDA will also be used to determine where, ideally, we would position spacecraft in the solar wind in order to make the biggest improvements to space-weather forecasting. This will inform the design of future space-weather mission design.
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DOI:
10.1029/2021sw002841
发表时间:
2021-07
期刊:
Space Weather
影响因子:
--
作者:
[L. Barnard;M. Owens;C. Scott;M. Lockwood;C. A. de Koning;T. Amerstorfer;J. Hinterreiter;C. Moestl;J. Davies;P. Riley]
通讯作者:
L. Barnard;M. Owens;C. Scott;M. Lockwood;C. A. de Koning;T. Amerstorfer;J. Hinterreiter;C. Moestl;J. Davies;P. Riley
Improving CME modelling with data assimilation of Heliospheric Imager observations into the HUXt solar wind numerical model.
通过将日光层成像仪观测数据同化到 HUXt 太阳风数值模型中,改进 CME 建模。
DOI:
10.5194/egusphere-egu21-192
发表时间:
2021
期刊:
影响因子:
--
作者:
[Barnard L]
通讯作者:
Barnard L
Using the "Ghost Front" to Predict the Arrival Time and Speed of CMEs at Venus and Earth
使用“幽灵前线”预测日冕物质抛射到达金星和地球的时间和速度
DOI:
10.3847/1538-4357/aba95a
发表时间:
2020
期刊:
Astrophysical Journal
影响因子:
4.9
作者:
[Chi Yutian, Scott Christopher, Shen Chenglong, Owens Mathew, Lang Matthew, Xu Mengjiao, Zhong Zhihui, Zhang Jie, Wang Yuming, Lockwood Mike]
通讯作者:
Lockwood Mike
Sensitivity of model estimates of CME propagation and arrival time to inner boundary conditions
CME 传播和到达时间的模型估计对内部边界条件的敏感性
DOI:
10.1002/essoar.10512439.1
发表时间:
2022
期刊:
影响因子:
--
作者:
[James L]
通讯作者:
James L
Quantifying the uncertainty in CME kinematics derived from geometric modelling of Heliospheric Imager data
量化由日光层成像仪数据的几何建模得出的日冕物质抛射运动学的不确定性
DOI:
10.1002/essoar.10507552.1
发表时间:
2021
期刊:
影响因子:
--
作者:
[Barnard L]
通讯作者:
Barnard L
共 6 条
Why have space weather forecasts not improved for over a decade?
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批准号:NE/Y001052/1
-
项目类别:Research Grant
-
资助金额:$50.41万
-
财政年份:2024
-
负责人:Mathew Owens
-
依托单位:
Reading Solar System Science 2020
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批准号:ST/V000497/1
-
项目类别:Research Grant
-
资助金额:$104.09万
-
财政年份:2021
-
负责人:Mathew Owens
-
依托单位:
Space Weather Impact on Ground-based Systems
-
批准号:NE/P016928/1
-
项目类别:Research Grant
-
资助金额:$39.15万
-
财政年份:2017
-
负责人:Mathew Owens
-
依托单位:
国内基金
海外基金
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
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批准号:--
-
项目类别:--
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资助金额:40万元
-
批准年份:2020
-
负责人:Vikrant Gupta
-
依托单位: