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At least 181 records · Page 10

Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional Neural Networks

Summary Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, examine well stimulation efficacy, and estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture hits because hydraulic fractures propagate and create strain rate variations in the rock. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS poses the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate responses correlated with low-frequency DAS data. In this paper, “fracture hit” refers to a hydraulic fracture originating from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber-optic sensing data. Additionally, we use edge detection techniques to recognize fracture-hit event patterns in strain rate images. The fracture-hit location can be identified using recognized pixels in the image. The accuracy of edge detection-based location identification is also plausible, but edge detection is dependent on the assumption of pattern shape and image quality, hence it is less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber-optic sensing event detection.

Engineering↗

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the wind resource – particularly extreme events – is vital to the industry's success. Such understanding has been hindered by a lack of publicly available wind profile observations in offshore wind energy areas. However, the New York State Energy Research and Development Authority recently funded the deployment of two floating lidars within two current lease areas off the coast of New Jersey. These floating lidars provide publicly available wind speed data from 20 to 200 m height with a 20 m vertical resolution. In this study, we leverage a year of these lidar data to quantify and characterize the frequent occurrence of high-wind-shear and low-level-jet events, both of which will have a considerable impact on turbine operation. In designing a detection algorithm for these events, we find that the typical, non-dimensional power-law-based wind shear exponent is insufficient to identify many of these extreme, high-wind-speed events. Rather, we find that the simple vertical gradient of wind speed better captures the events. Based on this detection method, we find that almost 100 independent events occur throughout the year with mean wind speed at 100 m height and wind speed gradient of 16 m s -1 and 0.05 s -1 , respectively. The events have strong seasonal variability, with the highest number of events in summer and the lowest in winter. A detailed analysis reveals that these events are enabled by an induced stable stratification when warmer air from the south flows over the colder mid-Atlantic waters, leading to a positive air–sea temperature difference.

17 WIND ENERGY↗

A semi-supervised machine learning detector for physics events in tokamak discharges

Databases of physics events have been used in various fusion research applications, including the development of scaling laws and disruption avoidance algorithms, yet they can be time-consuming and tedious to construct. This paper presents a novel application of the label spreading semi-supervised learning algorithm to accelerate this process by detecting distinct events in a large dataset of discharges, given few manually labeled examples. A high detection accuracy (>85%) for H-L back transitions and initially rotating locked modes is demonstrated on a dataset of hundreds of discharges from DIII-D with manually identified events for which only 3 discharges are initially labeled by the user. Lower yet reasonable performance (~75%) is also demonstrated for the core radiative collapse, an event with a much lower prevalence in the dataset. Additionally, analysis of the performance sensitivity indicates that the same set of algorithmic parameters is optimal for each event. This suggests that the method can be applied to detect a variety of other events not included in this paper, given that the event is well described by a set of 0D signals robustly available on many discharges. Procedures for analysis of new events are demonstrated, showing automatic event detection with increasing fidelity as the user strategically adds manually labeled examples. Detections on Alcator C-Mod and EAST are also shown, demonstrating the potential for this to be used on a multi-tokamak dataset.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The He-3/He-4 ratios for solar energetic particle events during the Combined Release and Radiation Effects Satellite Mission

Helium data measured by the University of Chicago instrument, ONR-604, are employed to determine the ratio of He-3 to He-4 for solar energetic particle (SEP) events over an energy range 50-110 MeV/nucleon during the 1990/1991 Combined Release and Radiation Effects Satellite mission. The Sun in this period is extremely active. A total of 29 separate SEP events have been identified; among them 16 major events have been analyzed to obtain He-3/He-4 ratios, with a mass resolution of 0.10 amu. Thirteen events have a He-3/He-4 ratio larger than 0.005, one order of magnitude greater than the solar coronal value. The He-3/He-4 ratio at energies of 50-110 MeV/nucleon is independent of the size of the SEP event, for the moderately large flares analyzed here. The helium energy spectra are represented by power laws. During the 1991 June flare period, different large-particle injections associated with different solar flares, but occurring from the same active region, have a similar average spectral index and a similar He-3/He-4 ratio. The spectral index of He-4 varies from event to event, i.e., from as small as 1.5 to as large as 7.5. A correlation is found between the inferred spectral index from gamma-ray measurements and our measured spectral indices for the 1991 June 11 and June 15 events, suggesting that the high-energy SEPs may come from the same acceleration event as the particles that interact at the Sun and produce the gamma rays. The implications of these results for particle acceleration and propagation at the flare site and in the solar corona are discussed.

Chen, Jiasheng↗

A Flight/Ground/Test Event Logging Facility

The onboard control software for spacecraft such as Mars Pathfinder and Cassini is composed of many subsystems including executive control, navigation, attitude control, imaging, data management, and telecommunications. The software in all of these subsystems needs to be instrumented for several purposes: to report required telemetry data, to report warning and error events, to verify internal behavior during system testing, and to provide ground operators with detailed data when investigating in-flight anomalies. Events can range in importance from purely informational events to major errors. It is desirable to provide a uniform mechanism for reporting such events and controlling their subsequent processing. Since radiation-hardened flight processors are several years behind the speed and memory of their commercial cousins, and since most subsystems require real-time control, and since downlink rates to earth can be very low from deep space, there are limits to how much of the data can be saved and transmitted. Some kinds of events are more important than others and should therefore be preferentially retained when memory is low. Some faults can cause an event to recur at a high rate, but this must not be allowed to consume the memory pool. Some event occurrences may be of low importance when reported but suddenly become more important when a subsequent error event gets reported. Some events may be so low-level that they need not be saved and reported unless specifically requested by ground operators.

Dvorak, Daniel↗

Short- and Medium-term Atmospheric Effects of Very Large Solar Proton Events

Long-term variations in ozone have been caused by both natural and humankind related processes. In particular, the humankind or anthropogenic influence on ozone from chlorofluorocarbons and halons (chlorine and bromine) has led to international regulations greatly limiting the release of these substances. These anthropogenic effects on ozone are most important in polar regions and have been significant since the 1970s. Certain natural ozone influences are also important in polar regions and are caused by the impact of solar charged particles on the atmosphere. Such natural variations have been studied in order to better quantify the human influence on polar ozone. Large-scale explosions on the Sun near solar maximum lead to emissions of charged particles (mainly protons and electrons), some of which enter the Earth's magnetosphere and rain down on the polar regions. "Solar proton events" have been used to describe these phenomena since the protons associated with these solar events sometimes create a significant atmospheric disturbance. We have used the National Center for Atmospheric Research (NCAR) Whole Atmosphere Community Climate Model (WACCM) to study the short- and medium-term (days to a few months) influences of solar proton events between 1963 and 2005 on stratospheric ozone. The four largest events in the past 45 years (August 1972; October 1989; July 2000; and October-November 2003) caused very distinctive polar changes in layers of the Earth's atmosphere known as the stratosphere (12-50 km; -7-30 miles) and mesosphere (50-90 km; 30-55 miles). The solar protons connected with these events created hydrogen- and nitrogen- containing compounds, which led to the polar ozone destruction. The hydrogen-containing compounds have very short lifetimes and lasted for only a few days (typically the duration of the solar proton event). On the other hand, the nitrogen-containing compounds lasted much longer, especially in the Winter. The nitrogen oxides were predicted to increase substantially due to these solar events and led to mid- to upper polar stratospheric ozone decreases of over 20%. These WACCM results generally agreed with satellite measurements. Both WACCM and measurements showed enhancements of nitric acid, dinitrogen pentoxide, and chlorine nitrate, which were indirectly caused by these solar events. Solar proton events were shown to cause a significant change in the polar stratosphere and need to be considered in understanding variations during years of strong solar activity.

Jackman, Charles H.↗

Why Are Most Ground Level Events Associated with High Fe/O Ratios?

In a seminal paper about Ground Level Events (GLEs), Dietrich and Lopate (1999) reported on 24 GLEs from April, 1973 to May, 1998. They noted that alt but one of these GLEs, June 15, 1991, were associated with a Solar Energetic Particle (SEP) event with an enhanced Fe/O ratio. The Fe/O ratio observed for the June 15, 1991 event was only 0.03, well below the nominal coronal abundance of Fe/O = 0.134. For the remaining events, Fe/O ranged from 0.27 to over 3, welt over the nominal coronal value. During Solar Cycle 23, 14 more GLEs were observed, only one of which had very low Fe/O. This was the event of January 20, 2005, the largest ground-level neutron monitor event in 49 years. We will report on our efforts to find out whether the events of June 15, 1991 and January 20, 2005 have features in common, besides high Fe/O, that distinguish them from all other GLE events and may help determine the cause of elevated Fe/O in almost all GLE events. We will use energetic particle, magnetic field, and solar wind plasma data from NASA's IMP-8 Wind, and ACE spacecraft.

von Rosenvinge, Tycho T.↗

Response of the Antarctic Stratosphere to Warm Pool EI Nino Events in the GEOS CCM

A new type of EI Nino event has been identified in the last decade. During "warm pool" EI Nino (WPEN) events, sea surface temperatures (SSTs) in the central equatorial Pacific are warmer than average. The EI Nino signal propagates poleward and upward as large-scale atmospheric waves, causing unusual weather patterns and warming the polar stratosphere. In austral summer, observations show that the Antarctic lower stratosphere is several degrees (K) warmer during WPEN events than during the neutral phase of EI Nino/Southern Oscillation (ENSO). Furthermore, the stratospheric response to WPEN events depends of the direction of tropical stratospheric winds: the Antarctic warming is largest when WPEN events are coincident with westward winds in the tropical lower and middle stratosphere i.e., the westward phase of the quasi-biennial oscillation (QBO). Westward winds are associated with enhanced convection in the subtropics, and with increased poleward wave activity. In this paper, a new formulation of the Goddard Earth Observing System Chemistry-Climate Model, Version 2 (GEOS V2 CCM) is used to substantiate the observed stratospheric response to WPEN events. One simulation is driven by SSTs typical of a WPEN event, while another simulation is driven by ENSO neutral SSTs; both represent a present-day climate. Differences between the two simulations can be directly attributed to the anomalous WPEN SSTs. During WPEN events, relative to ENSO neutral, the model simulates the observed increase in poleward planetary wave activity in the South Pacific during austral spring, as well as the relative warming of the Antarctic lower stratosphere in austral summer. However, the modeled response to WPEN does not depend on the phase of the QBO. The modeled tropical wind oscillation does not extend far enough into the lower stratosphere and upper troposphere, likely explaining the model's insensitivity to the phase of the QBO during WPEN events.

Hurwitz, Margaret M.↗

Tool for Automated Retrieval of Generic Event Tracks (TARGET)

Methods have been developed to identify and track tornado-producing mesoscale convective systems (MCSs) automatically over the continental United States, in order to facilitate systematic studies of these powerful and often destructive events. Several data sources were combined to ensure event identification accuracy. Records of watches and warnings issued by National Weather Service (NWS), and tornado locations and tracks from the Tornado History Project (THP) were used to locate MCSs in high-resolution precipitation observations and GOES infrared (11-micron) Rapid Scan Operation (RSO) imagery. Thresholds are then applied to the latter two data sets to define MCS events and track their developments. MCSs produce a broad range of severe convective weather events that are significantly affecting the living conditions of the populations exposed to them. Understanding how MCSs grow and develop could help scientists improve their weather prediction models, and also provide tools to decision-makers whose goals are to protect populations and their property. Associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Any storm-tracking method should include the following processes: storm identification, storm tracking, and quantification of storm intensity and activity. The spatiotemporal coordinates of the tracks will enable researchers to obtain other coincident observations to conduct more thorough studies of these events. In addition to their tracked locations, their areal extents, precipitation intensities, and accumulations all as functions of their evolutions in time were also obtained and recorded for these events. All parameters so derived can be catalogued into a moving object database (MODB) for custom queries. The purpose of this software is to provide a generalized, cross-platform, pluggable tool for identifying events within a set of scientific data based upon specified criteria with the possibility of storing identified events into a searchable database. The core of the application uses an implementation of the connected component labeling (CCL) algorithm to identify areas of interest, then uses a set of criteria to establish spatial and temporal relationships between identified components. The CCL algorithm is used for identifying objects within images for computer vision. This application applies it to scientific data sets using arbitrary criteria. The most novel concept was applying a generalized CCL implementation to scientific data sets for establishing events both spatially and temporally. The combination of several existing concepts (pluggable components, generalized CCL algorithm, etc.) into one application is also novel. In addition, how the system is designed, i.e., its extensibility with pluggable components, and its configurability with a simple configuration file, is innovative. This allows the system to be applied to new scenarios with ease.

Clune, Thomas↗

Properties of Ground Level Enhancement Events and the Associated Solar Eruptions During Solar Cycle 23

Solar cycle 23 witnessed the most complete set of observations of coronal mass ejections (CMEs) associated with the Ground Level Enhancement (GLE) events. We present an overview of the observed properties of the GLEs and those of the two associated phenomena, viz., flares and CMEs, both being potential sources of particle acceleration. Although we do not find a striking correlation between the GLE intensity and the parameters of flares and CMEs, the solar eruptions are very intense involving X-class flares and extreme CME speeds (average approx. 2000 km/s). An M7.1 flare and a 1200 km/s CME are the weakest events in the list of 16 GLE events. Most (80 %) of the CMEs are full halos with the three non-halos having widths in the range 167 to 212 degrees. The active regions in which the GLE events originate are generally large: 1290 msh (median 1010 msh) compared to 934 msh (median: 790 msh) for SEP-producing active regions. For accurate estimation of the CME height at the time of metric type II onset and GLE particle release, we estimated the initial acceleration of the CMEs using flare and CME observations. The initial acceleration of GLE-associated CMEs is much larger (by a factor of 2) than that of ordinary CMEs (2.3 km/sq s vs. 1 km/sq s). We confirmed the initial acceleration for two events for which CME measurements are available in the inner corona. The GLE particle release is delayed with respect to the onset of all electromagnetic signatures of the eruptions: type II bursts, low frequency type III bursts, soft X-ray flares and CMEs. The presence of metric type II radio bursts some 17 min (median: 16 min; range: 3 to 48 min) before the GLE onset indicates shock formation well before the particle release. The release of GLE particles occurs when the CMEs reach an average height of approx 3.09 R(sub s) (median: 3.18 R (sub s) ; range: 1.71 to 4.01 R (sub s) ) for well-connected events (source longitude in the range W20–W90). For poorly connected events, the average CME height at GLE particle release is ∼66 % larger (mean: 5.18 R (sub s) ; median: 4.61 R (sub s) ; range: 2.75–8.49 R (sub s) ). The longitudinal dependence is consistent with shock accelerations because the shocks from poorly connected events need to expand more to cross the field lines connecting to an Earth observer. On the other hand, the CME height at metric type II burst onset has no longitudinal dependence because electromagnetic signals do not require magnetic connectivity to the observer. For several events, the GLE particle release is very close to the time of first appearance of the CME in the coronagraphic field of view, so we independently confirmed the CME height at particle release. The CME height at metric type II burst onset is in the narrow range 1.29 to 1.8 R(sub s), with mean and median values of 1.53 and 1.47 R(sub s). The CME heights at metric type II burst onset and GLE particle release correspond to the minimum and maximum in the Alfven speed profile. The increase in CME speed between these two heights suggests an increase in Alfvenic Mach number from 2 to 3. The CME heights at GLE particle release are in good agreement with those obtained from the velocity dispersion analysis, including the source longitude dependence. We also discuss the implications of the delay of GLE particle release with respect to complex type III bursts by approx 18 min (median: 16 in; range: 2 to 44 min) for the flare acceleration mechanism. A similar analysis is also performed on the delay of particle release relative to the hard X-ray emission.

Geomagnetic Storms↗

Large Solar Energetic Particle Events Associated With Filament Eruptions Outside Active Regions

We report on four large filament eruptions (FEs) from solar cycles 23 and 24 that were associated with large solar energetic particle (SEP) events and interplanetary type II radio bursts. The post-eruption arcades corresponded mostly to C-class soft X-ray enhancements, but an M1.0 flare was associated with one event. However, the associated coronal mass ejections (CMEs) were fast (speeds approx. 1000 km/s) and appeared as halo CMEs in the coronagraph field of view. The interplanetary type II radio bursts occurred over a wide wavelength range, indicating the existence of strong shocks throughout the inner heliosphere. No metric type II bursts were present in three events, indicating that the shocks formed beyond 2-3 Rs. In one case, there was a metric type II burst with low starting frequency, indicating a shock formation height of approx.2 Rs. The FE-associated SEP events did have softer spectra (spectral index >4) in the 10-100 MeV range, but there were other low-intensity SEP events with spectral indices ⩾4. Some of these events are likely FE-SEP events, but were not classified as such in the literature because they occurred close to active regions. Some were definitely associated with large active region flares, but the shock formation height was large. We definitely find a diminished role for flares and complex type III burst durations in these large SEP events. Fast CMEs and shock formation at larger distances from the Sun seem to be the primary characteristics of the FE-associated SEP events.

filaments↗

Classification of Meteorological Influences Surrounding Extreme Precipitation Events in the United States using the MERRA-2 Reanalysis

Extreme precipitation events can have a large impact on society through flooding that can result in property destruction, crop losses, economic losses, the spread of water-borne diseases, and fatalities. Observations indicate there has been a statistically significant increase in extreme precipitation events over the past 15 years in the Northeastern United States and other localized regions of the country have become crippled with record flooding events, for example, the flooding that occurred in the Southeast United States associated with Hurricane Matthew in October 2016. Extreme precipitation events in the United States can be caused by various meteorological influences such as extratropical cyclones, tropical cyclones, mesoscale convective complexes, general air mass thunderstorms, upslope flow, fronts, and the North American Monsoon. Reanalyses, such as the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), have become a pivotal tool to study the meteorology surrounding extreme precipitation events. Using days classified as an extreme precipitation events based on a combination of observational gauge and radar data, two techniques for the classification of these events are used to gather additional information that can be used to determine how events have changed over time using atmospheric data from MERRA-2. The first is self organizing maps, which is an artificial neural network that uses unsupervised learning to cluster like patterns and the second is an automated detection technique that searches for characteristics in the atmosphere that define a meteorological phenomena. For example, the automated detection for tropical cycles searches for a defined area of suppressed sea level pressure, alongside thickness anomalies aloft, indicating the presence of a warm core. These techniques are employed for extreme precipitation events in preselected regions that were chosen based an analysis of the climatology of precipitation.

Monsoon↗

A Statistical Study of Solar Particle Events in Flux and Dose

The high-energy protons from solar energetic particle (SEP) events present a hazard to space systems: damage to science instruments/electronics/materials or to astronauts. A reliable estimate of the high-energy proton environment is critical to assure mission success. Important characteristics of an SEP event are fluence, peak flux, energy spectrum, time to reach the peak flux, time to reach peak dose, and properties of the cumulative dose profile after an event starts. All of these characteristics are important to understand in order to design space missions properly for both robotic and human missions. Because of the unpredictable and sporadic nature of SEP events, statistical models are often used to represent the SEP parameters described above. In a study by Jun et al. (2007), the statistics of event fluences, durations, and time intervals between events were investigated using the then available historical SEP dataset obtained from the instruments onboard the IMP-8 spacecraft. Since then, a more comprehensive SEP dataset based off of IMP-8 and GOES called Reference Data Set Version 2.0 (RDSv2.0) has become available covering the SEP events up to Year 2015 under a framework of the European Space Agency's (ESA's) Solar Energetic Particle Environment Modelling (SEPEM) project (Jiggens et al., 2018). The main objectives of this statistical study of SEP events are two-fold: First, the statistics of peak fluxes, event fluences, durations, and time intervals will be re-visited by using RDSv2.0; Second, the statistical analyses of flux and dose timing will be performed using the same dataset RDSv2.0. The results of this study will address the statistical properties of all key parameters for designing a spacecraft or a human mission where the SEP environment is an important consideration.

Whitman, K.↗

Effect of volcanic emissions on clouds during the 2008 and 2018 Kilauea degassing events

Volcanic eruptions in otherwise clean environments are “natural experiments” wherein the effects of aerosol emissions on clouds and climate can be partitioned from meteorological variability and anthropogenic activities. In this work, we combined satellite retrievals, reanalysis products, and atmospheric modeling to analyze the mechanisms of aerosol–cloud interactions during two degassing events at the Kilauea volcano in 2008 and 2018. The eruptive nature of the 2008 and 2018 degassing events was distinct from long-term volcanic activity for Kilauea. Although previous studies assessed the modulation of cloud properties from the 2008 event, this is the first time such an analysis has been reported for the 2018 event and that multiple degassing events have been analyzed and compared at this location. Both events resulted in significant changes in cloud effective radius and cloud droplet number concentration that were decoupled from local meteorology and in line with an enhanced cloud albedo. However, it is likely that the effects of volcanic emissions on liquid water path and cloud fraction were largely offset by meteorological variability. Comparison of cloud anomalies between the two events suggested a threshold response of aerosol–cloud interactions to overcome meteorological effects, largely controlled by aerosol loading. In both events, the ingestion of aerosols within convective parcels enhanced the detrainment of condensate in the upper troposphere, resulting in deeper clouds than observed under pristine conditions. Accounting for ice nucleation on ash particles led to enhanced ice crystal concentrations at cirrus levels and a slight decrease in ice water content, improving the correlation of the model results with the satellite retrievals. Overall, aerosol loading, plume characteristics, and meteorology contributed to changes in cloud properties during the Kilauea degassing events.

Katherine H. Breen↗

On-Board Deployment Event Verification for GOES-R Spacecraft

As is common with many spacecraft designs, the GOES-R vehicles require a series of deployment events to transition from the launch configuration to the operational configuration. Rather than implementing additional sensors to verify various deployments, the GOES-R program developed an alternate approach that uses existing gyro rate sensing. The approach includes two pieces: the first is a new onboard shock detection capability to confirm initiation of individual deployment events, and the second is a ground-based dynamics verification step to confirm completion of deployment events. We first present the algorithm that detects shock events for various deployment devices along with the parameter tuning performed during ground tests. We then show inflight performance of the shock detection algorithm. While shock detection is useful for observing initiation of deployment events, completion of some deployment events cannot be determined by shock detection alone. For these events, such as solar panel latch-up and deployable boom extension, the program developed dynamics models for the deployment transient responses. High-rate gyro data were recorded for these events, which allow the ground team to verify that the appendages were fully deployed. We show the predictive models for these events and corresponding flight results.

GeoXO↗

The 17 April 2021 Widespread Solar Energetic Particle Event

A complex and long-lasting solar eruption on 17 April 2021 produced a widespread solar energetic particle (SEP) event that was observed by five longitudinally well-separated observers in the inner heliosphere that covered distances to the Sun from 0.42 to 1 au: BepiColombo, Parker Solar Probe, Solar Orbiter, STEREO A, and near-Earth spacecraft. The event was the second widespread SEP event detected in solar cycle 25, and it produced relativistic electrons and protons. It was associated with a long-lasting solar hard X-ray flare that showed multiple hard X-ray peaks over a duration of one hour. The event was further accompanied by a medium-fast coronal mass ejection (CME) with a speed of 880 km s -1 that drove a shock, an extreme ultraviolet wave, and long-lasting and complex radio burst activity that showed four distinct type III burst groups over a period of 40 min. We aim to understand the reason for the wide spread of elevated SEP intensities in the inner heliosphere as well as identify the underlying source regions of the observed energetic electrons and protons. We applied a comprehensive multi-spacecraft analysis of remote-sensing observations and in situ measurements of the energetic particles and interplanetary context to attribute the SEP observations at the different locations to the various potential source regions at the Sun. We used an ENLIL simulation to characterize the complex interplanetary state and its role in the energetic particle transport. The magnetic connection between each spacecraft and the Sun was determined using ballistic backmapping in combination with potential field source surface extrapolations in the lower corona. Using also a reconstruction of the coronal shock front, we then determined the times when the shock establishes magnetic connections with the different observers. Radio observations were used to characterize the directivity of the four main injection episodes, which were then employed in a 2D SEP transport simulation to test the importance of these different injection episodes. A comprehensive timing analysis of the inferred solar injection times of the SEPs observed at each spacecraft suggests different source processes being important for the electron and proton events. Comparison among the characteristics and timing of the potential particle sources, such as the CME-driven shock or the flare, suggests a stronger shock contribution for the proton event and a more likely flare-related source for the electron event. In contrast to earlier studies on widespread SEP events, we find that in this event an important ingredient for the wide SEP spread was the wide longitudinal range of about 110 o covered by distinct SEP injections, which is also supported by our SEP transport modeling.

sun↗

Evaluating Precipitation Events Using GPM IMERG 30-Minute Near Real-Time Precipitation Estimates

Accurately detecting and estimating precipitation at near–real time (NRT) is of utmost importance for the early detection and monitoring of hydrometeorological hazards. The precipitation product, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), provides NRT 0.1° and 30-min precipitation estimates across the globe with only a 4-h latency. This study was an evaluation of the GPM IMERG version 6 level-3 early run 30-min precipitation product for precipitation events from 2014 through 2020. The purpose of this research was to identify when, where, and why GPM IMERG misidentified and failed to detect precipitation events in California, Nevada, Arizona, and Utah in the United States. Precipitation events were identified based on 15-min precipitation from gauges and 30-min precipitation from the IMERG multisatellite constellation. False-positive and false-negative precipitation events were identified and analyzed to determine their characteristics. Precipitation events identified by gauges had longer duration and had higher cumulative precipitation than those identified by GPM IMERG. GPM IMERG had many false event detections during the summer months, suggesting possible virga event detection, which is when precipitation falls from a cloud but evaporates before it reaches the ground. The frequency and timing of the merged passive microwave (PMW) product and forward propagation were responsible for IMERG overestimating cumulative precipitation during some precipitation events and underestimating others. This work can inform experts that are using the GPM IMERG NRT product to be mindful of situations where GPM IMERG–estimated precipitation events may not fully resolve the hydrometeorological conditions driving these hazards.

Jessica R P Sutton↗

Extreme Weather Events and the Impact on PV Time Series Data

The impact of extreme weather events on PV performance was studied by comparing the National Oceanic and Atmospheric Administration database on severe weather with the PV Fleet database on continuous PV performance. We identified 170 systems that were immediately impacted by weather events. These severe weather events lead to a median loss of only 1% of annual production. However, flooding and high wind events were found to have an extremely long tail extending to 60 % loss showing that these discrete events can pose a substantial risk to PV systems. Besides the short-term impact of lost production due to outages, we also found a statistically significant increased performance loss rate (PLR) for high wind events comparing PLR before and after these weather events. In addition, hail events caused a higher PLR for 2 out of 3 systems. More data are required to better quantify the impact, but these first results illustrate the substantial risk these events pose short-and long-term.

degradation↗