Search NASA⌕ Search

SEARCH · Search NASA

Results for “Storms”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Plasmaspheric Mass Loss and Refilling as a Result of a Magnetic Storm

Using the sounding measurements from the radio plasma imager on IMAGE, and a plasma density inversion algorithm, we derive the plasma density profiles along the magnetic field in a few L-shells every 14 hours at magnetic local noon before, during, and after the March 31,2001 magnetic storm. An empirical model of the plasmaspheric plasma density distribution is derived as a reference using the measurements before the storm. During the storm, the equatorial plasma was substantially depleted in a range of L-shells. The flux tubes were refilled after the storm. The filling ratio, the equatorial plasma density normalized by its quiet-time value before the storm, is introduced to assess the time evolution of the depletion and refilling processes. The depletion, more than two thirds of the quiet time content, appeared to occur rather quickly after the storm onset, as determined by the limited temporal resolution of the measurements. The refilling proceeded, although more slowly than the depletion process, significantly faster than the theoretical prediction of a 3-day time scale. Dynamic structures are observed in situ and confirmed by the extreme ultraviolet imager (EUV) measurements.

Reinisch, B. W.↗
NASA NTRS1998

Pulsing Inertial Oscillation, Supercell Storms, and Surface Mesonetwork Data

The pulsing inertial oscillation (PIO) model is a nonlinear, time-dependent, translating vortex solution of the inviscid, compressible fluid dynamic equations in the middle troposphere. The translation of this vortex during a pulse is strikingly similar to that of a supercell storm -- a rotating thunderstorm that can generate tornadoes and hail. Two studies were performed to test the hypothesis that some supercell storms are manifestations of a PIO pulse. The first study applied the model to an intense interior draft whose buoyancy was bounded by a temperature excess of +/- 12 K. The peak updraft speed achieved was 41.5 m/ s and the peak Rossby number was 92.9. The study also pointed to an advanced concept for attaining higher values. The second study applied the PIO model to a supercell storm as a whole and succeeded in replicating its bulk properties, such as mesocyclonic circulation, net mass and moisture influxes, and time track. This study also identified a critical feature of the PIO model that could be tested against storm data: The average vertical draft is downward before the turn in the storm track and upward afterwards. In the conventional theory, the average vertical draft is upward from storm inception until dissipation. These differing draft predictions were compared with the best available data, which are surface mesonetwork data. These data were found to support the PIO model. However, surface data alone are not conclusive, and further measurements are warranted.

Costen, R. C.↗
NASA NTRS2005

Lightning Mapping and the Nowcasting of Severe Storms

This paper describes a successful research and operational collaboration between NASA scientists and NWS forecasters to improve severe stor m warnings using real-time data from a regional VHF total lightning mapping array (LMA). Key objectives of our research using LMA data ar e: a) Identification of intensifying and weakening storms using the time rate-of-change of total flash rate; b) Improved severe storm poten tial situational awareness; c) Evaluation of the potential of total f lash rate trend to improve severe storm probability of detection (POD ) and lead time; and d) Validation of mesoscale model forecasts of th understorm initiation. The LMA data are distributed for ingest and di splay in the WFO AWIPS decision support system, and archived at each WFO for case studies, event playbacks, and assessments using the NWS Warning Event Simulator. The Huntsville WFO has upgraded severe thund erstorm warnings to verified tornado warnings and avoided a false ala rm on a severe storm through the added information on storm growth, intensification, and decay that can be deduced from the magnitude and temporal trend of total flash rates. We present detailed case studies of the observed relationships between lightning activity and tornadi c storm development as determined by radar reflectivity and velocity fields, and thunderstorms forecast by the Weather Research and Foreca st (WRF) model. From these collaborative studies, forecasters can eva luate the added value of total lightning data within the forecast and warning decision-making process (http://weather.msfc.nasa.gov/sport) .

Goodman, S.↗
NASA NTRS2011

Use of Dual-Polarization Radar Variables to Assess Low-Level Wind Shear in Severe Thunderstorm Near-storm Environments in the Tennessee Valley

The upgrade of the National Weather Service (NWS) network of S ]band dual-polarization radars is currently underway, and the incorporation of polarimetric information into the real ]time forecasting process will enhance the forecaster fs ability to assess thunderstorms and their near ]storm environments. Recent research has suggested that the combination of polarimetric variables differential reflectivity (ZDR) and specific differential phase (KDP) can be useful in the assessment of low level wind shear within a thunderstorm. In an environment with strong low ]level veering of the wind, ZDR values will be largest along the right inflow edge of the thunderstorm near a large gradient in horizontal reflectivity (indicative of large raindrops falling with a relative lack of smaller drops), and take the shape of an arc. Meanwhile, KDP values, which are proportional to liquid water content and indicative of a large number of smaller drops, are maximized deeper into the forward flank precipitation shield than the ZDR arc as the smaller drops are being advected further from the updraft core by the low level winds than the larger raindrops. Using findings from previous work, three severe weather events that occurred in North Alabama were examined in order to assess the utility of these signatures in determining the potential for tornadic activity. The first case is from October 26, 2010, where a large number of storms indicated tornadic potential from a standard reflectivity and velocity analysis but very few storms actually produced tornadoes. The second event is from February 28, 2011, where tornadic storms were present early on in the event, but as the day progressed, the tornado threat transitioned to a high wind threat. The third case is from April 27, 2011, where multiple rounds of tornadic storms ransacked the Tennessee Valley. This event provides a dataset including multiple modes of tornadic development, including QLCS and supercell structures. The overarching goal of examining these three events is to compare dual ]polarization features from this larger dataset to previous work and to determine if these signatures can be a useful indication of the potential for tornadic activity associated with the amount of low ]level wind shear in the near ]storm environment.

Crowe, Christina C.↗
NASA NTRS2013

Space Weather Monitoring for ISS Geomagnetic Storm Studies

The International Space Station (ISS) space environments community utilizes near real time space weather data to support a variety of ISS engineering and science activities. The team has operated the Floating Potential Measurement Unit (FPMU) suite of plasma instruments (two Langmuir probes, a floating potential probe, and a plasma impedance probe) on ISS since 2006 to obtain in-situ measurements of plasma density and temperature along the ISS orbit and variations in ISS frame potential due to electrostatic current collection from the plasma environment (spacecraft charging) and inductive (vxB) effects from the vehicle motion across the Earth s magnetic field. An ongoing effort is to use FPMU for measuring the ionospheric response to geomagnetic storms at ISS altitudes and investigate auroral charging of the vehicle as it passes through regions of precipitating auroral electrons. This work is challenged by restrictions on FPMU operations that limit observation time to less than about a third of a year. As a result, FPMU campaigns ranging in length from a few days to a few weeks are typically scheduled weeks in advance for ISS engineering and payload science activities. In order to capture geomagnetic storm data under these terms, we monitor near real time space weather data from NASA, NOAA, and ESA sources to determine solar wind disturbance arrival times at Earth likely to be geoeffective (including coronal mass ejections and high speed streams associated with coronal holes) and activate the FPMU ahead of the storm onset. Using this technique we have successfully captured FPMU data during a number of geomagnetic storm periods including periods with ISS auroral charging. This presentation will describe the strategies and challenges in capturing FPMU data during geomagnetic storms, the near real time space weather resources utilized for monitoring the space weather environment, and provide examples of auroral charging data obtained during storm operations.

Minow, Joseph I.↗
NASA NTRS2013

Space Weather Monitoring for ISS Geomagnetic Storm Studies

The International Space Station (ISS) space environments community utilizes near real time space weather data to support a variety of ISS engineering and science activities. The team has operated the Floating Potential Measurement Unit (FPMU) suite of plasma instruments (two Langmuir probes, a floating potential probe, and a plasma impedance probe) on ISS since 2006 to obtain in-situ measurements of plasma density and temperature along the ISS orbit and variations in ISS frame potential due to electrostatic current collection from the plasma environment (spacecraft charging) and inductive (vxB) effects from the vehicle motion across the Earth s magnetic field. An ongoing effort is to use FPMU for measuring the ionospheric response to geomagnetic storms at ISS altitudes and investigate auroral charging of the vehicle as it passes through regions of precipitating auroral electrons. This work is challenged by restrictions on FPMU operations that limit observation time to less than about a third of a year. As a result, FPMU campaigns ranging in length from a few days to a few weeks are typically scheduled weeks in advance for ISS engineering and payload science activities. In order to capture geomagnetic storm data under these terms, we monitor near real time space weather data from NASA, NOAA, and ESA sources to determine solar wind disturbance arrival times at Earth likely to be geoeffective (including coronal mass ejections and high speed streams associated with coronal holes) and activate the FPMU ahead of the storm onset. Using this technique we have successfully captured FPMU data during a number of geomagnetic storm periods including periods with ISS auroral charging. This presentation will describe the strategies and challenges in capturing FPMU data during geomagnetic storms, the near real time space weather resources utilized for monitoring the space weather environment, and provide examples of auroral charging data obtained during storm operations.

Minow, Joseph I.↗
NASA NTRS2016

Highly Relativistic Radiation Belt Electron Acceleration, Transport, and Loss: Large Solar Storm Events of March and June 2015

Two of the largest geomagnetic storms of the last decade were witnessed in 2015. On 17 March 2015, a coronal mass ejection-driven event occurred with a Dst (Disturbance Storm Time Ring Current Index) value reaching 223 nanoteslas. On 22 June 2015 another strong storm (Dst reaching 204 nanoteslas) was recorded. These two storms each produced almost total loss of radiation belt high-energy (E (Energy) greater than or approximately equal to 1 millielectronvolt) electron fluxes. Following the dropouts of radiation belt fluxes there were complex and rather remarkable recoveries of the electrons extending up to nearly 10 millielectronvolts in kinetic energy. The energized outer zone electrons showed a rich variety of pitch angle features including strong butterfly distributions with deep minima in flux at alpha equals 90 degrees. However, despite strong driving of outer zone earthward radial diffusion in these storms, the previously reported impenetrable barrier at L (L-shell magnetic field line value) approximately equal to 2.8 was pushed inward, but not significantly breached, and no E (Energy) greater than or approximately equal to 2.0 millielectronvolts electrons were seen to pass through the radiation belt slot region to reach the inner Van Allen zone. Overall, these intense storms show a wealth of novel features of acceleration, transport, and loss that are demonstrated in the present detailed analysis.

Baker, D. N.↗
NASA NTRS2016

Geomagnetically Induced Currents Around the World During the 17 March 2015 Storm

Geomagnetically induced currents (GICs) represent a significant space weather issue for power grid and pipeline infrastructure, particularly during severe geomagnetic storms. In this study, magnetometer data collected from around the world are analyzed to investigate the GICs caused by the 2015 St. Patricks Day storm. While significant GIC activity in the high-latitude regions due to storm time substorm activity is shown for this event, enhanced GIC activity was also measured at two equatorial stations in the American and Southeast Asian sectors. This equatorial GIC activity is closely examined, and it is shown that it is present both during the arrival of the interplanetary shock at the storm sudden commencement (SSC) in Southeast Asia and during the main phase of the storm approximately 10 h later in South America. The SSC caused magnetic field variations at the equator in Southeast Asia that were twice the magnitude of those observed only a few degrees to the north, strongly indicating that the equatorial electrojet (EEJ) played a significant role. The large equatorial magnetic field variations measured in South America are also examined, and the coincident solar wind data are used to investigate the causes of the sudden changes in the EEJ approximately 10 h into the storm. From this analysis it is concluded that sudden magnetopause current increases due to increases in the solarwind dynamic pressure, and the sudden changes in the resultant magnetospheric and ionospheric current systems, are the primary drivers of equatorial GICs.

Carter, B. A.↗
NASA NTRS2017

Observations of Deep Ionospheric F-Region Density Depletions with FPMU Instrumentation and Their Relationship with the Global Dynamics of the June 22-23, 2015 Geomagnetic Storm

The magnetic storm that commenced on June 22, 2015 was one of the largest storms in the current solar cycle. During this event, ionospheric F-region density measurements from the Floating Potential Measurement Unit (FPMU) on board the International Space Station (ISS) show dramatic depletions in the post-sunset (nighttime) local time sector at equatorial latitudes starting in the main phase of the storm and persisting on several subsequent orbits into the next day. Putting these low-latitude measurements in context with the global dynamics of the storm, we will present results from simulations and observations in our efforts to better understand the effects of this storm on the different regions of the coupled ionosphere-magnetosphere. The consequences of the magnetospheric penetration electric field and their role in the occurrence of these equatorial spread F observations will be investigated through the results of the SAMI3-RCM numerical model, a coupled ionosphere-magnetosphere model with self-consistent large-scale electrodynamics. Specifically, we will investigate the transient signatures of the interplanetary magnetic field component, Bz, and its role in driving the global convection electric field and ionospheric density redistribution. Lastly, measurements from the AMPERE Birkeland currents, DMSP drift velocities and the particle flux dropouts observed from the Magnetospheric Multiscale Mission (MMS) will be correlated with the FPMU density depletions and each other. Together these observations and simulation results will be assembled to provide each region’s context to the global dynamics and time evolution of the storm.

Coffey, Victoria↗
NASA NTRS2017

Observations of Deep Ionospheric F-Region Density Depletions with FPMU Instrumentation and Their Relationship with the Global Dynamics of the June 22-23, 2015 Geomagnetic Storm

The magnetic storm that commenced on June 22, 2015 was one of the largest storms in the current solar cycle. During this event, ionospheric F-region density measurements from the Floating Potential Measurement Unit (FPMU) on board the International Space Station (ISS) show dramatic depletions in the post-sunset (nighttime) local time sector at equatorial latitudes starting in the main phase of the storm and persisting on several subsequent orbits into the next day. Putting these low-latitude measurements in context with the global dynamics of the storm, we will present results from simulations and observations in our efforts to better understand the effects of this storm on the different regions of the coupled ionosphere-magnetosphere. The consequences of the magnetospheric penetration electric field and their role in the occurrence of these equatorial spread F observations will be investigated through the results of the SAMI3-RCM numerical model, a coupled ionosphere-magnetosphere model with self-consistent large-scale electrodynamics. Specifically, we will investigate the transient signatures of the interplanetary magnetic field component, Bz, and its role in driving the global convection electric field and ionospheric density redistribution. Lastly, measurements from the AMPERE Birkeland currents, DMSP drift velocities and the particle flux dropouts observed from the Magnetospheric Multiscale Mission (MMS) will be correlated with the FPMU density depletions and each other. Together these observations and simulation results will be assembled to provide each region's context to the global dynamics and time evolution of the storm.

Coffey, Victoria↗
NASA NTRS2019

Thermospheric Heating and Cooling Times During Geomagnetic Storms, Including Extreme Events

We present the first quantitative calculations of thermospheric heating and cooling times for geomagnetic storms of different intensity, including extreme events. We utilize the neutral mass density database of the CHAllenging Mini‐satellite Payload and Gravity Recovery And Climate Experiment missions to produce thermospheric global system response to geomagnetic storms caused by coronal mass ejections via superposed epoch analysis during May 2001 to December 2015. Storm events are grouped in five different categories based on the minimum value of the SYM‐H index. We calculate the time from storm onset for the thermosphere to reach maximum intensification (heating time) and the time from onset for the thermosphere to recover (cooling time). We find that heating and cooling times decrease as storm intensity increases and the effect is more pronounced for the cooling times. For extreme storms, the thermospheric heating time is 9.5 hr, while the cooling time is 22 hr.

Zesta, Eftyhia↗
NASA NTRSDate not supplied

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗
NASA NTRS2024

Storm-Time Variability of Terrestrial Hydrogen Exosphere: Kinetic Simulation Results

Recent studies of TWINS Lyman-α observations have reported an increase in geocoronal column brightness during geomagnetic storms, indicating enhanced exospheric hydrogen atom density (NH). This suggests a complex role of exospheric neutrals in determining storm-time magnetosphere dynamics and their energy release through charge-exchange processes. We developed a Model for Analyzing Terrestrial Exosphere (MATE) to investigate storm-time exospheric behaviors and their physical drivers. MATE traces test hydrogen atoms backward in time from locations in the exosphere to a nominal exobase altitude of 500 km, employing Newtonian mechanics with gravitational force. The model then calculates the phase-space densities (PSDs) of test hydrogen atoms at the exobase using the Maxwellian distribution with physics-based exobase conditions from the TIMEGCM upper atmosphere model. MATE maps PSDs at the exobase to the exosphere using Liouville’s Theorem under collisionless assumptions and derives NH by integrating the PSDs across velocity space. We conducted MATE simulation before, during, and after a minor geomagnetic storm from 12 to 18 June 2008, and compared the model results with NH estimates from the TWINS geocorona data. MATE reproduces storm-time density enhancements soon after the minimum Dst is reached, matching well with a general trend of TWINS NH estimates. The results suggest that upper atmospheric heating during a geomagnetic storm increases the number of ballistic and escaping hydrogen atoms entering the exosphere from the exobase, thereby boosting NH. However, the magnitude of modeled NH mismatches the TWINS NH estimates. The potential mechanisms of this density discrepancy include the physics excluded in the MATE model — such as neutralneutral collisions, neutral-plasma charge exchange, solar radiation pressure, and photoionization — as well as the higher exobase hydrogen density of TIMEGCM compared to typical empirical values, which will be addressed in future.

Hyunju K Connor↗
DOE OSTI2020

Integrative investigation of dust emissions by dust storms and dust devils in North Africa

Dust aerosols in North Africa account for >50% of the global total; however dust emission areas are still unclear. Based on the analysis of dust storms simulated with the numerical Weather Research and Forecast (WRF) model, satellite aerosol index (AI), and the dust data observed at 300 meteorological stations over 20 years, the spatio-temporal distribution characteristics of dust storm, dust devil and AI are compared and analyzed. From this study, the results show that: 1) There are two dust emission mechanisms: the dynamically-dominated dust storm and thermally-dominated dust devil; 2) Dust storms occur most frequently in Spring and are concentrated in the areas of Grand Erg Occidental Desert to the Erg Chech-Adrar Desert, the northern part of Grand Erg Oriental, the Atouila Desert to the Ouarane Desert, the Mediterranean coast, the eastern side of Nubian Desert and Bodélé Depression; 3) Dust devils occur most frequently from April to August and are mainly concentrated in the central part of North Africa, especially in the southwest of Hoggar Mountains to the west of Air Mountains, the border area of Egypt - Sudan - Libya and the vicinity of Tibesti Plateau; 4) The spatio-temporal distribution of AI is correlated more with the dust devils emission whereas the annual average contributions by dust storms and dust devils are 61.3% and 38.7%, respectively. This study discovers a new area of dust emissions by dust devils, and provides a better explanation for the spatio-temporal distribution of AI in North Africa.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Assimilation of X-band Phased-Array Radar Data with EnKF for the Analysis and Warning Forecast of a Tornadic storm

The impact of assimilating China's operational X-band Phased-Array radar's (X-PAR) data on the analysis and warning forecast of the vortex structure and intensity of the June 8, 2018 Foshan, Guangdong province, tornadic storm was investigated for the first time using an Ensemble Kalman Filter (EnKF) data assimilation system. Both radar radial velocity (Vr) and reflectivity (Z) from two S-band operational radars and one X-PAR were assimilated. Deterministic forecasts were launched every 6 min from 05:42 UTC (20 min before the tornado touched down) to 06:00 UTC from the EnKF mean analysis field. Five experiments were conducted to examine the added capability of Z assimilation of the EnKF system, and to investigate the impact of assimilating X-PAR data on the analysis and prediction of the tornadic storm. Compared to the experiment without Z assimilation, the assimilation of Z reduced the analysis error and greatly reduced the forecast error of Z. Furthermore, the assimilation of X-PAR data greatly improved the vortex structure of the tornadic storm at low levels, and improved the intensity of the rear inflow of the tornadic storm, especially with a higher assimilation frequency. Compared to the experiments without X-PAR data assimilation, assimilating X-PAR data improved the predictability of tornadic storm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Role of Intense Arctic Storm in Accelerating Summer Sea Ice Melt: An In Situ Observational Study

Abstract Intense storms have been more frequently observed in the Arctic during recent years, in coincidence with extreme sea ice loss events. However, it is still not fully understood how storms drive such events due to deficient observations and modeling discrepancies. Here we address this problem by analyzing in situ observations acquired during an Arctic expedition, which uniquely captured an intense storm in summer 2016. The result shows a pronounced acceleration of sea ice loss during the storm process. Diagnostic analysis indicates a net energy loss at the ice surface, not supporting the accelerated melting. Although the open water surface gained net heat energy, it was insufficient to increase the mixed‐layer temperature to the observed values. Dynamic analysis suggests that storm‐driven increase in ocean mixing and upward Ekman pumping of the Pacific‐origin warm water tremendously increased oceanic heat flux. The thermal advection by the Ekman pumping led to a warmed mixed layer by 0.05°C–0.12°C and, in consequence, an increased basal sea ice melt rate by 0.1–1.7 cm day −1 .

58 GEOSCIENCES↗
DOE OSTI2020

Probabilistic Prediction of Geomagnetic Storms and the K p index

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 index K p in particular, is widely used for these purposes. Current state-of-the-art forecast models provide deterministic K 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-ahead K 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.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Energy Transport in the Thermosphere During the Solar Storms of April 2002

The dramatic solar storm events of April 2002 deposited a large amount of energy into the Earth's upper atmosphere, substantially altering the thermal structure, the chemical composition, the dynamics, and the radiative environment. We examine the flow of energy within the thermosphere during this storm period from the perspective of infrared radiation transport and heat conduction. Observations from the SABER instrument on the TIMED satellite are coupled with computations based on the ASPEN thermospheric general circulation model to assess the energy flow. The dominant radiative response is associated with dramatically enhanced infrared emission from nitric oxide at 5.3 microns from which a total of approx. 7.7 x 10(exp 23) ergs of energy are radiated during the storm. Energy loss rates due to NO emission exceed 2200 Kelvin per day. In contrast, energy loss from carbon dioxide emission at 15 microns is only approx. 2.3% that of nitric oxide. Atomic oxygen emission at 63 microns is essentially constant during the storm. Energy loss from molecular heat conduction may be as large as 3.8% of the NO emission. These results confirm the "natural thermostat" effect of nitric oxide emission as the primary mechanism by which storm energy is lost from the thermosphere below 210 km.

SOLAR STORMS↗