Browsing by Author "Chakraborty, Shibaji"
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- Characterization and Modeling of Solar Flare Effects in the Ionosphere Observed by HF InstrumentsChakraborty, Shibaji (Virginia Tech, 2021-06-08)The ionosphere is the conducting part of the upper atmosphere that plays a significant role in trans-ionospheric high frequency (HF, 3-30 MHz) radiowave propagation. Solar activities, such as solar flares, radiation storms, coronal mass ejections (CMEs), alter the state of the ionosphere, a phenomenon known as Sudden Ionospheric Disturbance (SID), that can severely disrupt HF radio communication links by enhancing radiowave absorption and altering signal frequency and phase. The Super Dual Auroral Radar Network (SuperDARN) is an international network of low-power HF coherent scatter radars distributed across the globe to probe the ionosphere and its relation to solar activities. In this study, we used SuperDARN HF radar measurements with coordinated spacecraft and riometer observations to investigate statistical characteristics and the driving mechanisms of various manifestations of solar flare-driven SIDs in HF observations. We begin in Chapter 2 with a statistical characterization of various effects of solar flares on SuperDARN observations. Simultaneous observations from GOES spacecraft and SuperDARN radars confirmed flare-driven HF absorption depends on solar zenith angle, operating frequency, and intensity of the solar flare. The study found flare-driven SID also affects the SuperDARN backscatter signal frequency, which produces a sudden rise in Doppler velocity observation, referred to as the ``Doppler flash'', which occurs before the HF absorption effect. In Chapter 3, we further investigate the HF absorption effect during successive solar flares and those co-occurring with other geomagnetic disturbances during the 2017 solar storm. We found successive solar flares can extend the ionospheric relaxation time and the variation of HF absorption with latitude is different depending on the type of disturbance. In Chapter 4, we looked into an inertial property of the ionosphere, sluggishness, its variations with solar flare intensity, and made some inferences about D-region ion-chemistry using a simulation study. Specifically, we found solar flares alter the D-region chemistry by enhancing the electron detachment rate due to a sudden rise in molecular vibrational and rotational energy under the influence of enhanced solar radiation. In Chapter 5, we describe a model framework that reproduces HF absorption observed by riometers. This chapter compares different model formulations for estimating HF absorption and discusses different driving influences of HF absorption. In Chapter 6, we have investigated different driving mechanisms of the Doppler flash observed by SuperDARN radars. We note two particular findings: (i) the Doppler flash is predominantly driven by a change in the F-region refractive index and (ii) a combination of solar flare-driven enhancement in photoionization, and changes in the zonal electric field and(or) ionospheric conductivity reduces upward ion-drift, which produces a lowering effect in the F-region HF radiowave reflection height. Collectively, these research findings provide a statistical characterization of various solar flare effects on the ionosphere seen in the HF observations, and insights into their driving mechanisms and impacts on ionospheric dynamics.
- Conductance Model for Extreme Events: Impact of Auroral Conductance on Space Weather ForecastsMukhopadhyay, Agnit; Welling, Daniel T.; Liemohn, Michael W.; Ridley, Aaron J.; Chakraborty, Shibaji; Anderson, Brian J. (2020-09-27)Ionospheric conductance is a crucial factor in regulating the closure of magnetospheric field-aligned currents through the ionosphere as Hall and Pedersen currents. Despite its importance in predictive investigations of the magnetosphere-ionosphere coupling, the estimation of ionospheric conductance in the auroral region is precarious in most global first-principles-based models. This impreciseness in estimating the auroral conductance impedes both our understanding and predictive capabilities of the magnetosphere-ionosphere system during extreme space weather events. In this article, we address this concern, with the development of an advanced Conductance Model for Extreme Events (CMEE) that estimates the auroral conductance from field-aligned current values. CMEE has been developed using nonlinear regression over a year's worth of 1-min resolution output from assimilative maps, specifically including times of extreme driving of the solar wind-magnetosphere-ionosphere system. The model also includes provisions to enhance the conductance in the aurora using additional adjustments to refine the auroral oval. CMEE has been incorporated within the Ridley Ionosphere Model (RIM) of the Space Weather Modeling Framework (SWMF) for usage in space weather simulations. This paper compares performance of CMEE against the existing conductance model in RIM, through a validation process for six space weather events. The performance analysis indicates overall improvement in the ionospheric feedback to ground-based space weather forecasts. Specifically, the model is able to improve the prediction of ionospheric currents, which impact the simulated dB/dt and Delta B, resulting in substantial improvements in dB/dt predictive skill.
- Magnetic Microsphere-Based Mixers for MicrodropletsRoy, T.; Sinha, Ashok; Chakraborty, Shibaji; Ganguly, Ranjan; Puri, Ishwar K. (AIP Publishing, 2009-02-01)While droplet-based microfluidic systems have several advantages over traditional flow-through devices, achieving adequate mixing between reagents inside droplet-based reactors remains challenging. We describe an active mixing approach based on the magnetic stirring of self-assembled chains of magnetic microspheres within the droplet as these stirrers experience a rotating magnetic field. We measure the mixing of a water-soluble dye in the droplet in terms of a dimensional mixing parameter as the field-rpm, fluid viscosity, and microsphere loading are parametrically varied. These show that the mixing rate has a maximum value at a critical Mason number that depends upon the operating conditions.
- Modeling geomagnetic induction in submarine cablesChakraborty, Shibaji; Boteler, David H.; Shi, Xueling; Murphy, Benjamin S.; Hartinger, Michael D.; Wang, Xuan; Lucas, Greg; Baker, Joseph B. H. (Frontiers, 2022-10)Submarine cables have become a vital component of modern infrastructure, but past submarine cable natural hazard studies have mostly focused on potential cable damage from landslides and tsunamis. A handful of studies examine the possibility of space weather effects in submarine cables. The main purpose of this study is to develop a computational model, using Python, of geomagnetic induction on submarine cables. The model is used to estimate the induced voltage in the submarine cables in response to geomagnetic disturbances. It also utilizes newly acquired knowledge from magnetotelluric studies and associated investigations of geomagnetically induced currents in power systems. We describe the Python-based software, its working principle, inputs/outputs based on synthetic geomagnetic field data, and compare its operational capabilities against analytical solutions. We present the results for different model inputs, and find: 1) the seawater layer acts as a shield in the induction process: the greater the ocean depth, the smaller the seafloor geoelectric field; and 2) the model is sensitive to the Ocean-Earth layered conductivity structure.
- Multi-instrument observations of polar cap patches and traveling ionospheric disturbances generated by solar wind Alfven waves coupling to the dayside magnetospherePrikryl, Paul; Gillies, Robert G.; Themens, David R.; Weygand, James M.; Thomas, Evan G.; Chakraborty, Shibaji (Copernicus, 2022-11)During minor to moderate geomagnetic storms, caused by corotating interaction regions (CIRs) at the leading edge of high-speed streams (HSSs), solar wind Alfven waves modulated the magnetic reconnection at the dayside magnetopause. The Resolute Bay Incoherent Scatter Radars (RISR-C and RISR-N), measuring plasma parameters in the cusp and polar cap, observed ionospheric signatures of flux transfer events (FTEs) that resulted in the formation of polar cap patches. The patches were observed as they moved over the RISR, and the Canadian High-Arctic Ionospheric Network (CHAIN) ionosondes and GPS receivers. The coupling process modulated the ionospheric convection and the intensity of ionospheric currents, including the auroral electrojets. The horizontal equivalent ionospheric currents (EICs) are estimated from ground-based magnetometer data using an inversion technique. Pulses of ionospheric currents that are a source of Joule heating in the lower thermosphere launched atmospheric gravity waves, causing traveling ionospheric disturbances (TIDs) that propagated equatorward. The TIDs were observed in the SuperDual Auroral Radar Network (SuperDARN) high-frequency (HF) radar ground scatter and the detrended total electron content (TEC) measured by globally distributed Global Navigation Satellite System (GNSS) receivers.
- Probabilistic prediction of geomagnetic storms and the Kp indexChakraborty, Shibaji; Morley, Steven Karl (2020-07-30)Geomagnetic activity is often described using summary indices to summarize the likelihood of space weather impacts, as well as when parameterizing space weather models. The geomagnetic indexK(p)in particular, is widely used for these purposes. Current state-of-the-art forecast models provide deterministicK(p)predictions using a variety of methods - including empirically-derived functions, physics-based models, and neural networks - but do not provide uncertainty estimates associated with the forecast. This paper provides a sample methodology to generate a 3-hour-aheadK(p)prediction with uncertainty bounds and from this provide a probabilistic geomagnetic storm forecast. Specifically, we have used a two-layered architecture to separately predict storm (K-p >= 5(-)) and non-storm cases. As solar wind-driven models are limited in their ability to predict the onset of transient-driven activity we also introduce a model variant using solar X-ray flux to assess whether simple models including proxies for solar activity can improve the predictions of geomagnetic storm activity with lead times longer than the L1-to-Earth propagation time. By comparing the performance of these models we show that including operationally-available information about solar irradiance enhances the ability of predictive models to capture the onset of geomagnetic storms and that this can be achieved while also enabling probabilistic forecasts.
- pyDARN: A Python software for visualizing SuperDARN radar dataShi, Xueling; Schmidt, Marina; Martin, Carley J.; Billett, Daniel D.; Bland, Emma; Tholley, Francis H.; Frissell, Nathaniel A.; Khanal, Krishna; Coyle, Shane; Chakraborty, Shibaji; Detwiller, Marci; Kunduri, Bharat; McWilliams, Kathryn (Frontiers, 2022-12)The Super Dual Auroral Radar Network (SuperDARN) is an international network of high frequency coherent scatter radars that are used for monitoring the electrodynamics of the Earth's upper atmosphere at middle, high, and polar latitudes in both hemispheres. pyDARN is an open-source Python-based library developed specifically for visualizing SuperDARN radar data products. It provides various plotting functions of different types of SuperDARN data, including time series plot, range-time parameter plot, fields of view, full scan, and global convection map plots. In this paper, we review the different types of SuperDARN data products, pyDARN's development history and goals, the current implementation of pyDARN, and various plotting and analysis functionalities. We also discuss applications of pyDARN, how it can be combined with other existing Python software for scientific analysis, challenges for pyDARN development and future plans. Examples showing how to read, visualize, and interpret different SuperDARN data products using pyDARN are provided as a Jupyter notebook.