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At least 361 records · Page 20Linked to original sources
USGS2024

On-orbit calibration and performance of the EMIT imaging spectrometer

The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that has been operating onboard the International Space Station since July 2022. This article describes EMIT's on-orbit spectroradiometric calibration and validation. Accurate spectroscopy is vital to achieve consistent mapping results with orbital imaging spectrometers. EMIT takes a unique approach to this challenge, with just six optical elements, no shutter, and no onboard calibration systems. Its simple design focuses on uniformity and stability to enable vicarious spectroradiometric calibration. Our experiments demonstrate that this approach is successful, approaching the fidelity of manual field spectroscopy in some cases, and enabling new and more accurate products across diverse Earth science disciplines. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary solar-reflected surface signals. Its noise performance enables percent-level discrimination in the depths of mineral absorption features. In these aspects, EMIT satisfies the stringent performance needs for the next generation of VSWIR imaging spectrometers to observe the Earth's ecosystems, geology , and water resources.

Remote Sensing of Environment↗
USGS2007

Oahu: perspective from space

Satellite remote sensing provides us with a unique perspective from space. This perspective is synoptic in nature and provides regional views of most of the land areas of the earth. The orbital characteristics of the Landsat system are such that repetitive imagery of the same area may be obtained. Because of the permanent nature of the imagery, it may be retrieved for comparative analysis at any time. Comparisons of this image of Oahu with maps of the island (for example, the Oahu, Hawaii, 1:250,000-scale topographic map) will enable the reader to readily identify the place names discussed in this article and permit a more detailed interpretation of the image.

Hawaii↗
USGS2009

High-Resolution Seismic-Reflection and Marine Magnetic Data Along the Hosgri Fault Zone, Central California

The U.S. Geological Survey (USGS) collected high-resolution shallow seismic-reflection and marine magnetic data in June 2008 in the offshore areas between the towns of Cayucos and Pismo Beach, Calif., from the nearshore (~6-m depth) to just west of the Hosgri Fault Zone (~200-m depth). These data are in support of the California State Waters Mapping Program and the Cooperative Research and Development Agreement (CRADA) between the Pacific Gas & Electric Co. and the U.S. Geological Survey. Seismic-reflection and marine magnetic data were acquired aboard the R/V Parke Snavely, using a SIG 2Mille minisparker seismic source and a Geometrics G882 cesium-vapor marine magnetometer. More than 550 km of seismic and marine magnetic data was collected simultaneously along shore-perpendicular transects spaced 800 m apart, with an additional 220 km of marine magnetometer data collected across the Hosgri Fault Zone, resulting in spacing locally as smallas 400 m. This report includes maps of the seismic-survey sections, linked to Google Earth software, and digital data files showing images of each transect in SEG-Y, JPEG, and TIFF formats, as well as preliminary gridded marine-magnetic-anomaly and residual-magnetic-anomaly (shallow magnetic source) maps.

Open-File Report↗
USGS2003

What Became of the Water on Mars?

Focuses on several exploratory missions to the planet Mars to investigate the role of water within the planet. Facts about Mars that were gathered from two National Aeronautics and Space Administration orbiters, the Mars Global Surveyor and Mars Odyssey; Features of Mars that are similar with the planet Earth; Factors that contribute to the possible existence of water in Mars; Background on the geology of Mars.

Natural History↗
USGS2025

System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor

Executive Summary This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-3 sensor and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence since 2021. These reports present and detail the methodology and procedures for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 for continuity of data and improved temporal resolution. The Resourcesat-2 platform (which includes Resourcesat-2A) is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Linear Imaging Self Scanning-3 and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. To summarize the results, we have determined that this sensor provides an interior geometric performance with mean offsets in the range of 1.75 meters (m; 0.06 pixel) to 6.83 m (0.23 pixel) in easting and −1.83 m (−0.06 pixel) to 1.81 m (0.06 pixel) in northing in band-to-band registration and a root mean square error in the range of 3.81 m (0.13 pixel) to 8.19 m (0.27 pixel) in easting and 2.21 m (0.09 pixel) to 4.72 m (0.16 pixel) in northing. We have measured an exterior geometric error offset in the range of −21.29 to 6.88 m in easting and −7.35 to −2.63 m in northing, and the root mean square error is in the range of 7.19 to 21.43 m in easting and 3.64 to 8.19 m in northing in comparison to the Landsat 8 Operational Land Imager. The measured radiometric performance was in the range of −0.002 to 0.031 in offset and 0.701 to 0.940 in slope, and the spatial performance was in the range of 1.204 to 1.265 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.251 to 0.277.

Open-File Report↗
USGS2007

Reducing loss of life and property from disasters: A societal benefit area of the strategic plan for U.S. Integrated Earth Observation System (IEOS)

Natural and technological disasters, such as hurricanes and other extreme weather events, earthquakes, volcanic eruptions, landslides and debris flows, wildland and urban-interface fires, floods, oil spills, and space-weather storms, impose a significant burden on society. Throughout the United States, disasters inflict many injuries and deaths, and cost the nation $20 billion each year (SDR, 2003). Disasters in other countries can affect U.S. assets and interests overseas (e.g. the eruption of Mt. Pinatubo in the Philippines, which effectively destroyed Clark Air Force Base). Also, because they have a disproportionate impact on developing countries, disasters are major barriers to sustainable development. Improving our ability to assess, predict, monitor, and respond to hazardous events is a key factor in reducing the occurrence and severity of disasters, and relies heavily on the use of information from well-designed and integrated Earth observation systems. To fully realize the benefits gained from the observation systems, the information derived must be disseminated through effective warning systems and networks, with products tailored to the needs of the end users and the general public.

Open-File Report↗
USGS1965

Terrain analysis of the lunar equatorial belt

The U. S. Geological Survey began, in November 1963, a terrain analysis of the lunar equatorial belt (10°N-10°S, 60° W15°E), on behalf of the National Aeronautics and Space Administration. The purpose of the study is to establish a quantitative classification system in terms of different degrees of relative resolvable roughness, using the best available earth based techniques, the resolution of which averages one kilometer. Those parts of the lunar surface that have the least resolvable roughness at this scale have the highest statistical probability of containing safe landing areas at the one to ten meter scale for both manned and unmanned spacecraft. This preliminary report is based on eight months work prior to July 1, 1964: an unreviewed manuscript was submitted initially to the National Aeronautics and Space Administration on July 27, 1964. The report does not include any data derived from Ranger VII, and manuscript review subsequent to Ranger VII has not revealed the need for any significant changes in the conclusions. The major results are: 1) a quantitative terrain classification of the equatorial belt, chiefly in the form of a map (Plate 1), but including slope frequency distribution curves for each unit; 2) four larger scale maps (1:1, 000, 000) of the central part of the belt showing the areal distribution pattern of approximately 30, 000 individual slope measurements; 3) a large scale terrain map of the Flamsteed area, studied visually at the Lick 36" refractor, to determine the relative surface roughness below the limit of photographic resolution: 4) a full discussion of all the major techniques employed in the study, i.e. photometric slope measurement, slope measurement by shadow variation high resolution photography, and visual study techniques; 5) an extrapolation of derived roughness information below the of photographic resolution. The extrapolation is based primarily on the behavior of the lunar slope data through a wide range of resolution and on information derived from studies of different terrestrial areas at varying degrees of resolution.

Open-File Report↗
USGS2021

System characterization report on Resourcesat-2 Advanced Wide Field Sensor

Executive Summary This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Advanced Wide Field Sensor (AWiFS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Resourcesat-2 is a medium-resolution satellite launched in 2011 on the Polar Satellite Launch Vehicle-C16. Resourcesat-2 carries the same sensing elements as Resourcesat-1 (launched in October 2003) and provides continuity for the mission. The objectives of the Resourcesat mission are to provide remote sensing data services to global users, focusing on data for integrated land and water resources management. Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 launch vehicle for continuity of data and improved temporal resolution. The two satellites operating in tandem improved the revisit capability from 5 days to 2–3 days. The Resourcesat-2 platform is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that AWiFS has an interior geometric performance in the range of −16.080 (−0.268 pixel) to 35.520 meters (m; 0.592 pixel) in easting and −25.680 (−0.428 pixel) to 23.400 m (0.390 pixel) in northing in band-to-band registration, an exterior geometric error of −64.262 (−1.071 pixels) to −19.059 m (−0.318 pixel) in easting and −29.028 (−0.484 pixel) to 41.249 m (0.687 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 2.29–2.36 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.030–0.035.

Open-File Report↗
USGS2026

ENSO and PDO drive shoreline position anomalies in the U.S. Pacific Northwest

Sandy beaches act as buffers against various coastal hazards but are vulnerable to episodic (seasonal) and chronic (interannual) erosion. Understanding the variation of shoreline position, a key metric in coastal morphology, over a spectrum of time scales is therefore crucial in assessing hazard vulnerability. Long-standing research has investigated the role of El Niño-Southern Oscillation (ENSO), the dominant mode of climate variability in the Pacific Basin, in seasonal shoreline variability. Yet, ENSO’s chronic influence—and that of another Pacific climate mode, the Pacific Decadal Oscillation (PDO)—on shoreline anomalies remains poorly understood. Here, we examine the variability of sandy beaches in the US Pacific Northwest, a ∼750 km long coastal region on the US West Coast. We leverage 40 years (1984–2024) of shoreline data from publicly available Earth-observing (Landsat) satellite imagery at a high spatial resolution (>10,000 shore-normal transects at 50-m alongshore spacing) and employ Convergent Cross Mapping (CCM), a methodology for inferring causality in dynamical systems. We discover that strong El Niño years are signified by erosion (75.1% of transects), and strong La Niña years exhibit accretional behavior (73.4% of transects). Furthermore, we establish, for the first time, that both ENSO and PDO exert a statistically significant control on interannual shoreline variability, particularly on the alongshore component (in 95 and 100% of littoral cells, respectively), with water level fluctuations playing a critical role. This effort advances our understanding of the seasonal-to-interannual interactions between Pacific Basin climate variability and the PNW’s coastal morphodynamics, with implications for sediment management and coastal adaptation.

California, Oregon, Washington↗
USGS2015

Pore-pressure sensitivities to dynamic strains: observations in active tectonic regions

Triggered seismicity arising from dynamic stresses is often explained by the Mohr-Coulomb failure criterion, where elevated pore pressures reduce the effective strength of faults in fluid-saturated rock. The seismic response of a fluid-rock system naturally depends on its hydro-mechanical properties, but accurately assessing how pore-fluid pressure responds to applied stress over large scales in situ remains a challenging task; hence, spatial variations in response are not well understood, especially around active faults. Here I analyze previously unutilized records of dynamic strain and pore-pressure from regional and teleseismic earthquakes at Plate Boundary Observatory (PBO) stations from 2006 through 2012 to investigate variations in response along the Pacific/North American tectonic plate boundary. I find robust scaling-response coefficients between excess pore pressure and dynamic strain at each station that are spatially correlated: around the San Andreas and San Jacinto fault systems, the response is lowest in regions of the crust undergoing the highest rates of secular shear strain. PBO stations in the Parkfield instrument cluster are at comparable distances to the San Andreas fault (SAF), and spatial variations there follow patterns in dextral creep rates along the fault, with the highest response in the actively creeping section, which is consistent with a narrowing zone of strain accumulation seen in geodetic velocity profiles. At stations in the San Juan Bautista (SJB) and Anza instrument clusters, the response depends non-linearly on the inverse fault-perpendicular distance, with the response decreasing towards the fault; the SJB cluster is at the northern transition from creeping-to-locked behavior along the SAF, where creep rates are at moderate to low levels, and the Anza cluster is around the San Jacinto fault, where to date there have been no statistically significant creep rates observed at the surface. These results suggest that the strength of the pore pressure response in fluid-saturated rock near active faults is controlled by shear strain accumulation associated with tectonic loading, which implies a strong feedback between fault strength and permeability: dynamic triggering susceptibilities may vary in space and also in time.

Journal of Geophysical Research B: Solid Earth↗
USGS2010

An overview of the Landsat Data Continuity Mission

The Landsat Data Continuity Mission (LDCM) is the follow-on mission to Landsat 7 and will be the eighth mission in the Landsat series. The mission is in development via an interagency partnership between the National Aeronautics and Space Administration (NASA) and the Department of Interior (DOI) / United States Geological Survey (USGS). The LDCM satellite will carry two earth-observing sensors, the Operational Land Imager (OLI) to collect image data for nine spectral bands in the reflective portion of the spectrum and the Thermal Infrared Sensor (TIRS) to collect coincident image data for two thermal spectral bands. The LDCM ground segment will control the satellite and will receive, process, archive, and distribute the science data collected by the OLI and TIRS instruments. The USGS Earth Resources Observation & Science Center (EROS) will distribute LDCM data products at no cost to requestors. The mission objective is to continues the Landsat program's collection, archive, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The LDCM launch readiness date is currently December, 2012.

Conference Paper↗
USGS2014

Centralized mission planning and scheduling system for the Landsat Data Continuity Mission

Satellites in Low Earth Orbit provide missions with closer range for studying aspects such as geography and topography, but often require efficient utilization of space and ground assets. Optimizing schedules for these satellites amounts to a complex planning puzzle since it requires operators to face issues such as discontinuous ground contacts, limited onboard memory storage, constrained downlink margin, and shared ground antenna resources. To solve this issue for the Landsat Data Continuity Mission (LDCM, Landsat 8), all the scheduling exchanges for science data request, ground/space station contact, and spacecraft maintenance and control will be coordinated through a centralized Mission Planning and Scheduling (MPS) engine, based upon GMV’s scheduling system flexplan9 . The synchronization between all operational functions must be strictly maintained to ensure efficient mission utilization of ground and spacecraft activities while working within the bounds of the space and ground resources, such as Solid State Recorder (SSR) and available antennas. This paper outlines the functionalities that the centralized planning and scheduling system has in its operational control and management of the Landsat 8 spacecraft.

Conference Paper↗
USGS2002

Houston-Galveston Bay area, Texas, from space; a new tool for mapping land subsidence

Interferometric Synthetic Aperture Radar (InSAR) is a powerful new tool that uses radar signals to measure displacement (subsidence and uplift) of the Earth's crust at an unprecedented level of spatial detail and high degree of measurement resolution. The Houston-Galveston Bay area, possibly more than any other metropolitan area in the United States, has been adversely affected by land subsidence. Extensive subsidence, caused mainly by ground-water pumping but also by oil and gas extraction, has increased the frequency of flooding, caused extensive damage to industrial and transportation infrastructure, motivated major investments in levees, reservoirs, and surfacewater distribution facilities, and caused substantial loss of wetland habitat. Ongoing patterns of subsidence in the Houston area have been carefully monitored using borehole extensometers, Global Positioning System (GPS) and conventional spirit-leveling surveys, and more recently, an emerging technology—Interferometric Synthetic Aperture Radar (InSAR)—which enables development of spatially-detailed maps of land-surface displacement over broad areas. This report, prepared by the U.S. Geological Survey (USGS) in cooperation with the U.S. Fish and Wildlife Service, briefly summarizes the history of subsidence in the area and the local consequences of subsidence and describes the use of InSAR as one of several tools in an integrated subsidence-monitoring program in the area.

Texas↗
USGS2021

System characterization report on Resourcesat-2 Linear Imaging Self Scanning-3 (LISS–3) sensor

Executive Summary This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Linear Imaging Self Scanning-3 (LISS–3) sensor and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Resourcesat-2 is a medium-resolution satellite launched in 2011 on the Polar Satellite Launch Vehicle-C16 launch vehicle. Resourcesat-2 carries the same sensing elements as Resourcesat-1 (launched in October 2003) and provides continuity for the mission. The objectives of the Resourcesat mission are to provide remote sensing data services to global users, focusing on data for integrated land and water resources management. Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 launch vehicle for continuity of data and improved temporal resolution. The two satellites operating in tandem improved the revisit capability from 5 days to 2–3 days. The Resourcesat-2 platform is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Advanced Wide Field Sensor and LISS–3, as well as the Linear Imaging Self Scanning-4 for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that LISS–3 has an interior geometric performance in the range of −4.620 (−0.154 pixel) to 13.230 meters (m; 0.441 pixel) in easting and −12.360 (−0.412 pixel) to 1.500 m (0.050 pixel) in northing in band-to-band registration, an exterior geometric error of −27.805 (−0.927 pixel) to 26.578 m (0.886 pixel) in easting and −35.341 (−1.178 pixel) to −6.286 m (−0.210 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.096 to 0.036 in offset and 0.585–0.946 in slope, and a spatial performance in the range of 1.87–1.95 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.045–0.070.

Open-File Report↗
USGS2020

Simultaneous observations of geoelectric and geomagnetic fields produced by magnetospheric ULF waves

Geomagnetic perturbations ( B G E O ) related to magnetospheric ultralow frequency (ULF) waves induce electric fields within the conductive Earth—geoelectric fields ( E G E O )—that in turn drive geomagnetically induced currents. Though numerous past studies have examined ULF wave B G E O from a space weather perspective, few studies have linked ULF waves with E G E O . Using recently available magnetotelluric impedance and E G E O measurements in the contiguous United States, we explore the relationship between ULF waves and E G E O . We use satellite, ground‐based radar, B G E O , and E G E O measurements in a case study of a plasmaspheric virtual resonance (PVR), demonstrating that the PVR E G E O has significant spatial variation in contrast to a relatively uniform B G E O , consistent with spatially varying Earth conductivity. We further show ULF wave E G E O measurements during two moderate storms of ∼ 1 V/km. We use both results to highlight the need for more research characterizing ULF wave E G E O .

Geophysical Research Letters↗
USGS2011

Feasibility of waveform inversion of Rayleigh waves for shallow shear-wave velocity using a genetic algorithm

Conventional surface wave inversion for shallow shear (S)-wave velocity relies on the generation of dispersion curves of Rayleigh waves. This constrains the method to only laterally homogeneous (or very smooth laterally heterogeneous) earth models. Waveform inversion directly fits waveforms on seismograms, hence, does not have such a limitation. Waveforms of Rayleigh waves are highly related to S-wave velocities. By inverting the waveforms of Rayleigh waves on a near-surface seismogram, shallow S-wave velocities can be estimated for earth models with strong lateral heterogeneity. We employ genetic algorithm (GA) to perform waveform inversion of Rayleigh waves for S-wave velocities. The forward problem is solved by finite-difference modeling in the time domain. The model space is updated by generating offspring models using GA. Final solutions can be found through an iterative waveform-fitting scheme. Inversions based on synthetic records show that the S-wave velocities can be recovered successfully with errors no more than 10% for several typical near-surface earth models. For layered earth models, the proposed method can generate one-dimensional S-wave velocity profiles without the knowledge of initial models. For earth models containing lateral heterogeneity in which case conventional dispersion-curve-based inversion methods are challenging, it is feasible to produce high-resolution S-wave velocity sections by GA waveform inversion with appropriate priori information. The synthetic tests indicate that the GA waveform inversion of Rayleigh waves has the great potential for shallow S-wave velocity imaging with the existence of strong lateral heterogeneity.

Journal of Applied Geophysics↗
USGS2025

Planning considerations related to contamination control for the return and analysis of Martian samples

The joint National Aeronautics and Space Administration and European Space Agency Mars Sample Return (MSR) Campaign is a proposed multi-mission effort to bring selected geological samples from Mars to Earth for the purpose of scientific investigation. Significant parts of these investigations could be affected by Earth-sourced contamination that is either misinterpreted as having a martian origin or that masks a martian signal. The Mars 2020 Perseverance rover implemented strict contamination control requirements to limit contamination of the samples during sample collection. Contamination control and contamination knowledge requirements have not yet been established for the samples after they arrive on Earth. The MSR Sample Receiving Facility (SRF) Contamination Panel (SCP) was tasked with defining the terrestrial biological, organic, and inorganic contamination limits for martian samples during their residence inside the SRF. To reach our recommendations, the SCP studied (i) the previously proposed limits and rationale of the Organic Contamination Panel, (ii) cleanliness levels achieved for sampling hardware by the M2020 mission, (iii) recent improvements in analytical technology and detection limits, (iv) updated information regarding the organic content of martian samples ( e.g. , from the Sample Analysis at Mars instrument on the Curiosity rover and laboratory analyses of martian meteorites), and (v) information about the composition and geologic context of samples being collected by the Perseverance rover for return to Earth.

Astrobiology↗
USGS2019

On the intensity of the magnetic superstorm of September 1909

Analysis is made of solar observations and ground‐based magnetometer data recording space weather before and during the magnetic superstorm of 25 September 1909. From these data, it is inferred that the storm was initiated by an interplanetary coronal‐mass ejection having a mean Sun‐to‐Earth velocity of ~1,679 km/s. The commencement pressure on the magnetopause was ~32.4 nPa, sufficient to compress the subsolar magnetopause radius to ~5.9 Earth radii. Early on in the evolution of the storm, low‐latitude geomagnetic disturbance exhibited extreme longitudinal asymmetry, something that can be attributed to substorm activity extending to low latitudes. For this storm, Dst attained a minimum of −595 nT, comparable to that of the great magnetic storm of March 1989 (−589 nT; the most intense storm in terms of Dst of the space age). These results inform projects focused on understanding and mitigating the deleterious effects of extreme space‐weather events.

Space Weather↗