Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userDomain of Influence analysis: implications for Data Assimilation in space weather forecasting
89
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Solar activity, ranging from the background solar wind to energetic coronal mass ejections (CMEs), is the main driver of the conditions in the interplanetary space and in the terrestrial space environment, known as space weather. A better understanding of the Sun-Earth connection carries enormous potential to mitigate negative space weather effects with economic and social benefits. Effective space weather forecasting relies on data and models. In this paper, we discuss some of the most used space weather models, and propose suitable locations for data gathering with space weather purposes. We report on the application of textit{Representer analysis (RA)} and textit{Domain of Influence (DOI) analysis} to three models simulating different stages of the Sun-Earth connection: the OpenGGCM and Tsyganenko models, focusing on solar wind - magnetosphere interaction, and the PLUTO model, used to simulate CME propagation in interplanetary space. Our analysis is promising for space weather purposes for several reasons. First, we obtain quantitative information about the most useful locations of observation points, such as solar wind monitors. For example, we find that the absolute values of the DOI are extremely low in the magnetospheric plasma sheet. Since knowledge of that particular sub-system is crucial for space weather, enhanced monitoring of the region would be most beneficial. Second, we are able to better characterize the models. Although the current analysis focuses on spatial rather than temporal correlations, we find that time-independent models are less useful for Data Assimilation activities than time-dependent models. Third, we take the first steps towards the ambitious goal of identifying the most relevant heliospheric parameters for modelling CME propagation in the heliosphere, their arrival time, and their geoeffectiveness at Earth.
rate research
Read More
Space weather indices are commonly used to drive operational forecasts of various geospace systems, including the thermosphere for mass density and satellite drag. The drivers serve as proxies for various processes that cause energy flow and deposition in the geospace system. Forecasts of neutral mass density is a major uncertainty in operational orbit prediction and collision avoidance for objects in low earth orbit (LEO). For the strongly driven system, accuracy of space weather driver forecasts is crucial for operations. The High Accuracy Satellite Drag Model (HASDM) currently employed by the United States Air Force in an operational environment is driven by four (4) solar and two (2) geomagnetic proxies. Space Environment Technologies (SET) is contracted by the space command to provide forecasts for the drivers. This work performs a comprehensive assessment for the performance of the driver forecast models. The goal is to provide a benchmark for future improvements of the forecast models. Using an archived data set spanning six (6) years and 15,000 forecasts across solar cycle 24, we quantify the temporal statistics of the model performance.
The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in space weather. The purpose is twofold. On one hand, we will discuss previous works that use ML for space weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the space weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics-based and machine learning approaches, known as gray-box.
Given the infrequency of extreme geomagnetic storms, it is significant to note the concentration of three extreme geomagnetic storms in 1941, whose intensities ranked fourth, twelfth, and fifth within the aa index between 1868-2010. Among them, the geomagnetic storm on 1 March 1941 was so intense that three of the four Dst station magnetograms went off scale. Herein, we reconstruct its time series and measure the storm intensity with an alternative Dst estimate (Dst*). The source solar eruption at 09:29 - 09:38 GMT on 28 February was located at RGO AR 13814 and its significant intensity is confirmed by large magnetic crochets of 35 nT measured at Abinger. This solar eruption most likely released a fast interplanetary coronal mass ejection with estimated speed 2260 km/s. After its impact at 03:57 - 03:59 GMT on 1 March, an extreme magnetic storm was recorded worldwide. Comparative analyses on the contemporary magnetograms show the storm peak intensity of minimum Dst* < -464 nT at 16 GMT, comparable to the most and the second most extreme magnetic storms within the standard Dst index since 1957. This storm triggered significant low-latitude aurorae in the East Asian sector and their equatorward boundary has been reconstructed as 38.5{deg} in invariant latitude. This result agrees with British magnetograms which indicate auroral oval moving above Abinger at 53.0{deg} in magnetic latitude. The storm amplitude was even more enhanced in equatorial stations and consequently casts caveats on their usage for measurements of the storm intensity in Dst estimates.
The Mexican Space Weather Service (SCiESMEX in Spanish) and National Space Weather Laboratory (LANCE in Spanish) were organized in 2014 and in 2016 respectively to provide space weather monitoring and alerts, as well as scientific research in Mexico. In this work, we present the results of the first joint observations of two events (22 June, 2015, and 29 September, 2015) with our local network of instruments and their related products. This network includes the MEXART radio telescope (solar flare and radio burst), the Compact Astronomical Low-frequency, Low-cost Instrument for Spectroscopy in Transportable Observatories (CALLISTO) at MEXART station (solar radio burst), the Mexico City Cosmic Ray Observatory (cosmics ray fluxes), GPS receiver networks (ionospheric disturbances), and the Geomagnetic Observatory of Teoloyucan (geomagnetic field). The observations show that we detected significant space weather effects over the Mexican territory: geomagnetic and ionospheric disturbances (22 June, 2015), variations in cosmic rays fluxes, and also radio communications interferences (29 September, 2015). The effects of these perturbations were registered, for the first time, using space weather products by SCiESMEX: TEC maps, regional geomagnetic index K mex , radio spectrographs of low frequency, and cosmic rays fluxes. These results prove the importance of monitoring space weather phenomena in the region and the need to strengthening the instrumentation network.
The study of historical great geomagnetic storms is crucial for assessing the possible risks to the technological infrastructure of a modern society, caused by extreme space-weather events. The normal benchmark has been the great geomagnetic storm of September 1859, the so-called Carrington Event. However, there are numerous records of another great geomagnetic storm in February 1872. This storm, about 12 years after the Carrington Event, resulted in comparable magnetic disturbances and auroral displays over large areas of the Earth. We have revisited this great geomagnetic storm in terms of the auroral and sunspot records in the historical documents from East Asia. In particular, we have surveyed the auroral records from East Asia and estimated the equatorward boundary of the auroral oval to be near 24.3 deg invariant latitude (ILAT), on the basis that the aurora was seen near the zenith at Shanghai (20 deg magnetic latitude, MLAT). These results confirm that this geomagnetic storm of February 1872 was as extreme as the Carrington Event, at least in terms of the equatorward motion of the auroral oval. Indeed, our results support the interpretation of the simultaneous auroral observations made at Bombay (10 deg MLAT). The East Asian auroral records have indicated extreme brightness, suggesting unusual precipitation of high-intensity, low-energy electrons during this geomagnetic storm. We have compared the duration of the East Asian auroral displays with magnetic observations in Bombay and found that the auroral displays occurred in the initial phase, main phase, and early recovery phase of the magnetic storm.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
