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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 73 records · Page 4Linked to original sources
USGS2016

The geomagnetic blitz of September 1941

Seventy-five years ago, on 18–19 September 1941, the Earth experienced a great magnetic storm, one of the most intense ever recorded. It arrived at a poignant moment in history, when radio and electrical technology was emerging as a central part of daily life and when much of the world was embroiled in World War II, which the United States had not yet officially entered. Auroras danced across the night sky as voltage surged in power grid lines. A radio blackout interrupted fan enjoyment of a baseball game, while another radio program was interrupted by private phone conversations. Citizens, already on edge, wondered if neon lights were some sort of antiaircraft signal. And far away in the North Atlantic, the illuminated night sky exposed an Allied convoy to German attack. These effects raised awareness within the scientific community and among the public of the societal significance of the effects that the Sun and outer space can have on the Earth—what we now call space weather .

Eos, Earth and Space Science News↗
USGS2017

Using strain rates to forecast seismic hazards

One essential component in forecasting seismic hazards is observing the gradual accumulation of tectonic strain accumulation along faults before this strain is suddenly released as earthquakes. Typically, seismic hazard models are based on geologic estimates of slip rates along faults and historical records of seismic activity, neither of which records actively accumulating strain. But this strain can be estimated by geodesy: the precise measurement of tiny position changes of Earth’s surface, obtained from GPS , interferometric synthetic aperture radar ( InSAR ), or a variety of other instruments.

Eos, Earth and Space Science News↗
USGS2017

Defining snow drought and why it matters

On 12 February, water resource managers at the Oroville Dam issued an evacuation warning that forced some 180,000 Californians to relocate to higher ground. The story of how conditions got to this point involves several factors, but two clearly stand out: the need to prevent water shortages during a record drought, followed by one of the wettest October–February periods in California history. The situation at Oroville Dam highlights difficulties that many reservoir managers face in managing flood risks while simultaneously storing water to mitigate severe droughts and smaller snowpacks. Central to this difficulty is the idea of “snow drought,” a term that’s gaining traction in both scientific and lay literature.

Eos, Earth and Space Science News↗
USGS2017

Aquatic ecosystems in a changing climate

Extreme climate events (ECEs) such as tropical storms and hurricanes, thunderstorms, heat waves, droughts, ice storms, and snow storms have increased and are projected to further increase in intensity and frequency across the world. These events are expected to have significant consequences for aquatic ecosystems with the potential for large changes in ecosystem processes, responses, and functions.

Eos, Earth and Space Science News↗
USGS2017

Probing magma reservoirs to improve volcano forecasts

When it comes to forecasting eruptions, volcano observatories rely mostly on real-time signals from earthquakes, ground deformation, and gas discharge, combined with probabilistic assessments based on past behavior [Sparks and Cashman, 2017] . There is comparatively less reliance on geophysical and petrological understanding of subsurface magma reservoirs.

Eos, Earth and Space Science News↗
USGS2018

Examining forest structure with terrestrial lidar: Suggestions and novel techniques based on comparisons between scanners and forest treatments

Terrestrial laser scanners (TLSs) provide a tool to assess and monitor forest structure across forest landscapes. We present TLS methods, suggestions, and mapped guidelines for planning TLS acquisitions at varying scales and forest densities. We examined rates of point‐density decline with distance from two TLS that acquire data at relatively high and low point density and found that the rates were nearly identical between scanners ( p value <0.01), suggesting that our findings are applicable to a range of TLS types. Using unique, TLS‐adapted processing methods, we determined the relative accuracy of TLS‐derived plot‐scale estimates of tree height, diameter‐at‐breast‐height, height‐to‐canopy, tree counts, as well as treatment‐scale tree density and patch metrics, using both high point density and low point density TLS among thinned and nonthinned forest treatments. The high‐density TLS consistently provides more accurate estimates of plot‐level metrics ( R 2 = 0.46 to 0.87) than the low‐density TLS (R 2 = −0.14 to 0.53). At treatment scales, tree density estimates are similar among scanners ( R 2 = 0.95 vs. 0.71), as are canopy cover and patch metrics. We develop and present the normalized density‐distance index (NDDI), which can account for up to 59% of the variance in estimate error and can be used to guide TLS‐data acquisition plans. This index indicates whether a given location has generally higher point density (higher NDDI) relative to the distance from the scanner and can be used as a proxy for uncertainty. Using NDDI as a guide for fair comparison between scanners, both plot‐ and treatment‐scale estimates improved.

Earth and Space Science↗
USGS2018

Planetary dune workshop expands to include subaqueous processes

Dune-like structures appear in the depths of Earth’s oceans, across its landscapes, and in the extremities of the solar system beyond. Dunes rise up under the thick dense atmosphere of Venus, and they have been found under the almost unimaginably ephemeral atmosphere of a comet.

Eos, Earth and Space Science News↗
USGS2018

Challenges of forecasting flooding on coral reef–lined coasts

Understanding wave-driven coastal flooding is a challenging scientific problem; the need for forecasts is becoming more urgent because of sea level rise, climate change, and ever-growing coastal populations. The tools developed for sandy shorelines are generally not applicable to coral reef–lined coasts with their complex bathymetry, hydrodynamically rough reef platforms, steep and poorly sorted beaches, and low coastal elevations. Advances in understanding and predicting flooding on coral reef–lined coasts thus require concerted efforts from a number of disciplines, including climatology, oceanography, geology, and ecology.

Eos, Earth and Space Science News↗
USGS2018

Seismic sensors record a hurricane’s roar

The instruments installed at Global Seismographic Network (GSN) stations were designed to record Earth’s vibrations, but they sometimes pick up sound waves from unexpected sources. For example, newly installed infrasound sensors at a station on Puerto Rico recorded the passage of Hurricane Maria on 20 September 2017.

Eos, Earth and Space Science News↗
USGS2019

Data sharing in magnetotellurics

Here, we introduce the first openly available comprehensive database of magnetotelluric (MT) and related electromagnetic data that we developed and matured over the past decade, explain how to access the data, and describe the challenges that had to be overcome to make MT data sharing possible. The database is a helpful tool for MT scientists, and is widely used by the international scientific community in teaching, planning future surveys, and then to leverage the value of new data at the inversion and interpretation stage. It has also turned into a primary resource for researchers in space weather, and for power grid industry. MT impedance, a transfer function that relates geoelectric fields to geomagnetic fields at the Earth’s surface, provides a critical missing component for estimation of geomagnetically induced currents: quasi-direct currents caused by geomagnetic storms that can destroy valuable equipment and cause extended blackouts. We envision that this database will also be useful for researchers in other areas of geophysics, such as seismology, who would like to use real MT data for hands-on learning and joint inversion analysis.

Eos, Earth and Space Science News↗
USGS2020

Planetary sensor models interoperability using the community sensor model specification

This paper presents the photogrammetric foundations upon which the Community Sensor Model specification depends, describes common coordinate system and reference frame transformations that support conversion between image sensor (charge‐coupled device) coordinates to some arbitrary body coordinate, and describes the U.S. Geological Survey Astrogeology Community Sensor Model implementation ( https://github.com/USGS-Astrogeology/usgscsm ). We present a new image support data specification that provides the position, pointing, timing, and metadata information necessary to properly locate a pixel or observations location on a body and describe a system architecture designed to explicitly identify the responsibilities of software components within a larger pipeline or analytical environment. This paper concludes with a set of experiments that illustrate positional and pointing error in the sensor location and the impact on the computed surface location.

Earth and Space Science↗
USGS2020

Aligning climate models with stakeholder needs: Advances in communicating future rainfall uncertainties for south Florida decision makers

Changes in future precipitation are of great importance to climate data users in South Florida. A recent U.S. Geological Survey workshop, “Increasing Confidence in Precipitation Projections for Everglades Restoration,” highlighted a gap between standard climate model outputs and the climate information needs of some key Florida natural resource managers. These natural resource managers (hereafter broadly defined as “climate data users”) need more tailored output than is commonly provided by the climate modeling community. This study responds to these user needs by outlining and testing an adaptable methodology to select output from ensemble climate‐model simulations based on user‐defined precipitation drivers, using statistical methods common across scientific disciplines. This methodology is developed to provide a “decision matrix” that guides climate data users to specify the subset of models most important to their work based on each user's season (winter, summer, and annual) and the condition (dry, wet, neutral, and no threshold events) of interest. The decision matrix is intended to better communicate the subset of models best representing precipitation drivers. This information could increase users' confidence in climate models as a resource for natural resource planning and can be used to direct future dynamical downscaling efforts. This methodology is based in dynamical processes controlling precipitation via remote and local teleconnections. We also suggest that future climate studies in South Florida include high‐resolution climate model runs (i.e., ocean eddy resolving) in conjunction with dynamical downscaling to adequately capture precipitation variability.

South Florida↗
USGS2021

Can modeling the geologic record contribute to constraining the tectonic source of the AD 1755 Great Lisbon earthquake?

The precise location of the seismic source of 1755 CE Great Lisbon earthquake is still uncertain. The aim of this work is to use an onland sedimentary record in southern Portugal to test and validate seismic sources for the earthquake. To achieve this, tsunami deposit thicknesses from over 150 cores collected at Salgados in southern Portugal were compared to the results of a tsunami sediment transport model (Delft3D-FLOW) that simulates tsunami propagation, inundation, erosion, and deposition. Five different hypothetical seismic sources were modeled with varying bed roughness coefficients to assess how well they reproduced observed patterns of tsunami deposit thicknesses and dune. Modeled and observed historical tsunami arrival times were also used to test different earthquake sources. Based on these comparisons, three modeled earthquake sources were able to reproduce the observed data, suggesting they should be regarded as somewhat more likely sources for the 1755 earthquake in contrast to four other modeled sources. The fault closest to shore (Marquês de Pombal) yielded the best correlations between model and observations.

Lisbon↗
USGS2020

Observations of an extreme atmospheric river storm with a diverse sensor network

Observational networks enhance real‐time situational awareness for emergency and water resource management during extreme weather events. We present examples of how a diverse, multitiered observational network in California provided insights into hydrometeorological processes and impacts during a 3‐day atmospheric river storm centered on 14 February 2019. This network, which has been developed over the past two decades, aims to improve understanding and mitigation of effects from extreme storms influencing water resources and natural hazards. We combine atmospheric reanalysis output and additional observations to show how the network allows: (1) the validation of record cool season precipitable water observations over southern California; (2) the identification of phenomena that produce natural hazards and present difficulties for short‐term weather forecast models, such as extreme precipitation amounts and snow level variability; (3) the use of soil moisture data to improve hydrologic model forecast skill in northern California's Russian River basin; and (4) the combination of meteorological data with seismic observations to identify when a large avalanche occurred on Mount Shasta. This case study highlights the value of investments in diverse observational assets and the importance of continued support and synthesis of these networks to characterize climatological context and advance understanding of processes modulating extreme weather.

California↗