Dynamic Time Warping as a Means of Assessing Solar Wind Time Series

Samara, Evangelia; Laperre, Brecht; Kieokaew, Rungployphan; Temmer, Manuela; Verbeke, C.; Rodriguez, L.; Magdalenić, Jasmina; Poedts, Stefaan

doi:10.3847/1538-4357/ac4af6

Cited by 22 publications

(21 citation statements)

References 45 publications

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“…Dynamic Time Warping (DTW) is as an effective algorithm to quantify the agreement between two time series and is used here to compare the model and in situ solar wind velocities. The DTW algorithm was initially used to aid automated speech recognition and has recently been used in a variety of fields such as economics (Franses and Wiemann 2020), biology (Skutkova et al 2013), and space weather (Samara et al 2022;Owens and Nichols 2021).…”

Section: Dynamic Time Warpingmentioning

confidence: 99%

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An inner boundary condition for solar wind models based on coronal density

Bunting¹,

Morgan²

2022

J. Space Weather Space Clim.

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Accurate forecasting of the solar wind has grown in importance as society becomes increasingly dependent on technology that is susceptible to space weather events. This work describes an inner boundary condition for ambient solar wind models based on tomography maps of the coronal plasma density gained from coronagraph observations, providing a novel alternative to magnetic extrapolations. The tomographical density maps provide a direct constraint of the coronal structure at heliocentric distances of 4 to 8 Rs, thus avoiding the need to model the complex non-radial lower corona. An empirical inverse relationship converts densities to solar wind velocities which are used as an inner boundary condition by the Heliospheric Upwind Extrapolation (HUXt) model to give ambient solar wind velocity at Earth. The dynamic time warping (DTW) algorithm is used to quantify the agreement between tomography/HUXt output and insitu data. An exhaustive search method is then used to adjust the lower boundary velocity range in order to optimize the model. Early results show a 40% decrease in mean absolute error between measured and modelled velocities compared to that of the coupled MAS/HUXt model. The use of density maps gained from tomography as an inner boundary constraint is thus a valid alternative to coronal magnetic models, and offers a significant advancement in the field given the availability of routine space-based coronagraph observations.

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Section: Dynamic Time Warpingmentioning

confidence: 99%

“…A metric used in this study in order to quantify the DTW distance is the Sequence Similarity Factor (SSF). SSF, as defined by Samara et al (2022), is described in eq 2:…”

Section: Dynamic Time Warpingmentioning

confidence: 99%

An inner boundary condition for solar wind models based on coronal density

Bunting¹,

Morgan²

2022

J. Space Weather Space Clim.

View full text Add to dashboard Cite

show abstract

“…In addition, we make use of dynamic time warping (DTW). Recently the usage of DTW in quantifying the performance of Solar Wind models has been explored (Samara et al, 2022a). Here, we use DTW in a simple form, calculating the normalized DTW cost for each HSS, then comparing the median values.…”

Section: Discussionmentioning

confidence: 99%

“…The sum of all Euclidean distances along the optimal path is then normalized by the amount of data points per time series. For implementation we use the python package openly provided by Giorgino (2009); see also Niennattrakul, Ruengronghirunya, and Ratanamahatana (2009) and Samara et al (2022a).…”

Section: Discussionmentioning

confidence: 99%

Improvements to the Empirical Solar Wind Forescast (ESWF)

Milošić

Temmer

Heinemann

et al. 2022

Preprint

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The empirical solar wind forecast (ESWF) model in its current version 2.0 runs as a space safety service in the frame of ESA’s Heliospheric Weather Expert Service Centre. The ESWF model forecasts the solar wind speed at Earth with a leadtime of 4 days. The algorithm uses an empirical relation found between the area of solar coronal holes (CHs), as observed in EUV within a 15° meridional slice, and the in-situ measured solar wind speed at 1 AU. This relation however, forecasts Gaussian type speed profiles, as the CH rotates in and out of the meridional slice, causing some discrepancy in the timing between forecasted and observed solar wind speed. With adaptations to the ESWF 2.0 algorithm we improve the precision and accuracy of the ESWF speed profiles. For that we implement compression and rarefaction effects occurring between solar wind streams of different velocities in interplanetary space. By considering the propagation times for plasma parcels between the Sun and Earth and their interactions, we achieve the asymmetrical shape of the speed profile that is characteristic of highspeed streams (HSS). By further implementing CH segmentation, co-latitude information and dynamic thresholding, we find that the newly developed ESWF 3.2 performs significantly better than ESWF 2.0. For a sample of 294 different HSSs, we derive a relative increase in hits of the timing and peak velocity by 13.9%. The Pearson correlation coefficient increases by 14.3% from cc = 0.35 to cc = 0.40.

show abstract

Section: Dynamic Time Warpingmentioning

confidence: 99%

An inner boundary condition for solar wind models based on coronal density

Bunting¹,

Morgan²

2022

Preprint

View full text Add to dashboard Cite

Accurate forecasting of the solar wind has grown in importance as society becomes increasingly dependent on technology that is susceptible to space weather events. This work describes an inner boundary condition for ambient solar wind models based on tomography maps of the coronal plasma density gained from coronagraph observations, providing a novel alternative to magnetic extrapolations. The tomographical density maps provide a direct constraint of the coronal structure at heliocentric distances of 4 to 8R , thus avoiding the need to model the complex non-radial lower corona. An empirical inverse relationship converts densities to solar wind velocities which are used as an inner boundary condition by the Heliospheric Upwind Extrapolation (HUXt) model to give ambient solar wind velocity at Earth. The dynamic time warping (DTW) algorithm is used to quantify the agreement between tomography/HUXt output and in situ data. An exhaustive search method is then used to adjust the lower boundary velocity range in order to optimize the model. Early results show up to a 32% decrease in mean absolute error between the modelled and observed solar wind velocities compared to that of the coupled MAS/HUXt model. The use of density maps gained from tomography as an inner boundary constraint is thus a valid alternative to coronal magnetic models, and offers a significant advancement in the field given the availability of routine space-based coronagraph observations.

show abstract

Dynamic Time Warping as a Means of Assessing Solar Wind Time Series

Cited by 22 publications

References 45 publications

An inner boundary condition for solar wind models based on coronal density

An inner boundary condition for solar wind models based on coronal density

Improvements to the Empirical Solar Wind Forescast (ESWF)

An inner boundary condition for solar wind models based on coronal density

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