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تسجيل مستخدم جديدDrag-based model (DBM) tools for forecast of coronal mass ejection arrival time and speed
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Forecasting the arrival time of CMEs and their associated shocks is one of the key aspects of space weather research. One of the commonly used models is, due to its simplicity and calculation speed, the analytical drag-based model (DBM) for heliospheric propagation of CMEs. DBM relies on the observational fact that slow CMEs accelerate whereas fast CMEs decelerate, and is based on the concept of MHD drag, which acts to adjust the CME speed to the ambient solar wind. Although physically DBM is applicable only to the CME magnetic structure, it is often used as a proxy for the shock arrival. In recent years, the DBM equation has been used in many studies to describe the propagation of CMEs and shocks with different geometries and assumptions. Here we give an overview of the five D
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The drag-based model (DBM) for heliospheric propagation of coronal mass ejections (CMEs) is a widely used analytical model which can predict CME arrival time and speed at a given heliospheric location. It is based on the assumption that the propagati
on of CMEs in interplanetary space is solely under the influence of magnetohydrodynamical drag, where CME propagation is determined based on CME initial properties as well as the properties of the ambient solar wind. We present an upgraded version, covering ensemble modelling to produce a distribution of possible ICME arrival times and speeds, the drag-based ensemble model (DBEM). Multiple runs using uncertainty ranges for the input values can be performed in almost real-time, within a few minutes. This allows us to define the most likely ICME arrival times and speeds, quantify prediction uncertainties and determine forecast confidence. The performance of the DBEM is evaluated and compared to that of ensemble WSA-ENLIL+Cone model (ENLIL) using the same sample of events. It is found that the mean error is $ME=-9.7$ hours, mean absolute error $MAE=14.3$ hours and root mean square error $RMSE=16.7$ hours, which is somewhat higher than, but comparable to ENLIL errors ($ME=-6.1$ hours, $MAE=12.8$ hours and $RMSE=14.4$ hours). Overall, DBEM and ENLIL show a similar performance. Furthermore, we find that in both models fast CMEs are predicted to arrive earlier than observed, most probably owing to the physical limitations of models, but possibly also related to an overestimation of the CME initial speed for fast CMEs.
Coronal mass ejections (CMEs) cause various disturbances of the space environment; therefore, forecasting their arrival time is very important. However, forecasting accuracy is hindered by limited CME observations in interplanetary space. This study
investigates the accuracy of CME arrival times at the Earth forecasted by three-dimensional (3D) magnetohydrodynamic (MHD) simulations based on interplanetary scintillation (IPS) observations. In this system, CMEs are approximated as spheromaks with various initial speeds. Ten MHD simulations with different CME initial speed are tested, and the density distributions derived from each simulation run are compared with IPS data observed by the Institute for Space-Earth Environmental Research (ISEE), Nagoya University. The CME arrival time of the simulation run that most closely agrees with the IPS data is selected as the forecasted time. We then validate the accuracy of this forecast using 12 halo CME events. The average absolute arrival-time error of the IPS-based MHD forecast is approximately 5.0 h, which is one of the most accurate predictions that ever been validated, whereas that of MHD simulations without IPS data, in which the initial CME speed is derived from white-light coronagraph images, is approximately 6.7 h. This suggests that the assimilation of IPS data into MHD simulations can improve the accuracy of CME arrival-time forecasts. The average predicted arrival times are earlier than the actual arrival times. These early predictions may be due to overestimation of the magnetic field included in the spheromak and/or underestimation of the drag force from the background solar wind, the latter of which could be related to underestimation of CME size or background solar wind density.
Coronal mass ejections (CMEs) cause disturbances in the environment of the Earth when they arrive at the Earth. However, the prediction of the arrival of CMEs still remains a challenge. We have developed an interplanetary scintillation (IPS) estimati
on system based on a global magnetohydrodynamic (MHD) simulation of the inner heliosphere to predict the arrival time of CMEs. In this system, the initial speed of a CME is roughly derived from white light coronagraph observations. Then, the propagation of the CME is calculated by a global MHD simulation. The IPS response is estimated by the three-dimensional density distribution of the inner heliosphere derived from the MHD simulation. The simulated IPS response is compared with the actual IPS observations made by the Institute for Space-Earth Environmental Research, Nagoya University, and shows good agreement with that observed. We demonstrated how the simulation system works using a halo CME event generated by a X9.3 flare observed on September 5, 2017. We find that the CME simulation that best estimates the IPS observation can more accurately predict the time of arrival of the CME at the Earth. These results suggest that the accuracy of the CME arrival time can be improved if our current MHD simulations include IPS data.
White light images of Coronal Mass Ejections (CMEs) are projections on the plane-of-sky (POS). As a result, CME kinematics are subject to projection effects. The error in the true (deprojected) speed of CMEs is one of the main causes of uncertainty t
o Space Weather forecasts, since all estimates of the CME Time-of-Arrival (ToA) at a certain location within the heliosphere require, as input, the CME speed. We use single viewpoint observations for 1037 flare-CME events between 1996-2017 and propose a new approach for the correction of the CME speed assuming radial propagation from the flare site. Our method is uniquely capable to produce physically reasonable deprojected speeds across the full range of source longitudes. We bound the uncertainty in the deprojected speed estimates via limits in the true angular width of a CME based on multiview-point observations. Our corrections range up to 1.37-2.86 for CMEs originating from the center of the disk. On average, the deprojected speeds are 12.8% greater than their POS speeds. For slow CMEs (VPOS < 400 km/s) the full ice-cream cone model performs better while for fast and very fast CMEs (VPOS > 700 km/s) the shallow ice-cream model gives much better results. CMEs with 691-878 km/s POS speeds have a minimum ToA mean absolute error (MAE) of 11.6 hours. This method, is robust, easy to use, and has immediate applicability to Space Weather forecasting applications. Moreover, regarding the speed of CMEs, our work suggests that single viewpoint observations are generally reliable.
We investigate the relationship between the monthly averaged maximal speeds of coronal mass ejections (CMEs), international sunspot number (ISSN), and the geomagnetic Dst and Ap indices covering the 1996-2008 time interval (solar cycle 23). Our new f
indings are as follows. (1) There is a noteworthy relationship between monthly averaged maximum CME speeds and sunspot numbers, Ap and Dst indices. Various peculiarities in the monthly Dst index are correlated better with the fine structures in the CME speed profile than that in the ISSN data. (2) Unlike the sunspot numbers, the CME speed index does not exhibit a double peak maximum. Instead, the CME speed profile peaks during the declining phase of solar cycle 23. Similar to the Ap index, both CME speed and the Dst indices lag behind the sunspot numbers by several months. (3) The CME number shows a double peak similar to that seen in the sunspot numbers. The CME occurrence rate remained very high even near the minimum of the solar cycle 23, when both the sunspot number and the CME average maximum speed were reaching their minimum values. (4) A well-defined peak of the Ap index between 2002 May and 2004 August was co-temporal with the excess of the mid-latitude coronal holes during solar cycle 23. The above findings suggest that the CME speed index may be a useful indicator of both solar and geomagnetic activities. It may have advantages over the sunspot numbers, because it better reflects the intensity of Earth-directed solar eruptions.
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