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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Systematically tracking the hourly progression of large wildfires using GOES satellite observations

Abstract. In the western United States, prolonged drought, a warming climate, and historical fuel buildup have contributed to larger and more intense wildfires as well as to longer fire seasons. As these costly wildfires become more common, new tools and methods are essential for improving our understanding of the evolution of fires and how extreme weather conditions, including heat waves, windstorms, droughts, and varying levels of active-fire suppression, influence fire spread. Here, we develop the Geostationary Operational Environmental Satellites (GOES)-Observed Fire Event Representation (GOFER) algorithm to derive the hourly fire progression of large wildfires and create a product of hourly fire perimeters, active-fire lines, and fire spread rates. Using GOES-East and GOES-West geostationary satellite detections of active fires, we test the GOFER algorithm on 28 large wildfires in California from 2019 to 2021. The GOFER algorithm includes parameter optimizations for defining the burned-to-unburned boundary and correcting for the parallax effect from elevated terrain. We evaluate GOFER perimeters using 12 h data from the Visible Infrared Imaging Radiometer Suite (VIIRS)-derived Fire Event Data Suite (FEDS) and final fire perimeters from the California's Fire and Resource Assessment Program (FRAP). Although the GOES imagery used to derive GOFER has a coarser resolution (2 km at the Equator), the final fire perimeters from GOFER correspond reasonably well to those obtained from FRAP, with a mean Intersection-over-Union (IoU) of 0.77, in comparison to 0.83 between FEDS and FRAP; the IoU indicates the area of overlap over the area of the union relative to the reference perimeters, in which 0 is no agreement and 1 is perfect agreement. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery, where perimeters are available at intervals of 12 h or longer or at ad hoc intervals from aircraft overflights. This is particularly relevant when a fire spreads rapidly, such as at maximum hourly spread rates of over 5 km h−1. Our GOFER algorithm for deriving the hourly fire progression using GOES can be applied to large wildfires across North and South America and reveals considerable variability in the rates of fire spread on diurnal timescales. The resulting GOFER product has a broad set of potential applications, including the development of predictive models for fire spread and the improvement of atmospheric transport models for surface smoke estimates. The resulting GOFER product has a broad set of potential applications, including the development of predictive models for fire spread and the improvement of atmospheric transport models for surface smoke estimates (https://doi.org/10.5281/zenodo.8327264, Liu et al., 2023).

Geology↗
DOE OSTI2024

Parallax-corrected VISST-derived pixel-level products from satellite GOES-16

The NASA Langley group led by William Smith produced GOES-16 satellite cloud retrievals over an approximate 10 by 10 degree region over the CACTI field campaign location. These retrievals are described here: https://www.arm.gov/capabilities/vaps/visst and are available for download here . They use algorithms historically called VISST that are now referred to as SatCORPS. More information can be found in Trepte et al. (2019), Minnis et al. (2021), and Yost et al. (2021). If using this dataset, please cite these references, the CACTI VISST dataset DOI found at the download link above, and this dataset’s DOI. The CACTI VISST pixel-level retrievals are on a 2 km spatial grid and available every 15 minutes (every 10 minutes late in the campaign), producing 21,765 files for the entire field campaign between October 2018 and April 2019. They are not corrected for parallax error, which is an offset in the actual geographical location of a cloud above the surface due to the satellite viewing the cloud partly from the side off nadir. This dataset applies a correction for parallax using the location relative to the satellite and the retrieved cloud top height above the surface, which allows the dataset to be geo-located with surface-based observations. The parallax correction for each location depends on the longitude, latitude and cloud top height above ground level (AGL) for that longitude and latitude in the original VISST files. The cloud top height AGL requires first computing the surface elevation at each VISST grid point. Data from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global Digital Elevation Map Version 3 at 30-m resolution is projected onto the VISST grid using conservative coarsening (conserving surface elevation) in the xESMF Python package. The surface elevation is then subtracted from the VISST-retrieved cloud top height above mean sea level. These cloud top heights AGL are then combined with longitude and latitude to estimate the latitude and longitude corrections. Due to variability in cloud top height, the parallax shifts produce an irregular grid of values since higher cloud tops are shifted further than lower cloud tops. A ball tree-based neighbor search with Haversine distance is performed using the Python-based scikit-learn library to find the nearest VISST grid point to each parallax correction-shifted point. The data value of the shifted point is then assigned to that VISST grid point. In this manner, the irregular geographical shifts to correct for parallax are projected back to the rectilinear VISST grid. Because relatively higher clouds should obscure lower clouds, the variable values for the highest cloud top are preferentially chosen if two or more values are assigned to a grid point. The parallax correction should be viewed as an improved but still imperfect estimation of the cloud top locations, largely because the cloud top height is an imperfect retrieval. Please see the attached README document for further information. Users are encouraged to contact the authors with any additional questions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Physics-Based GOES Satellite Product for Use in NREL's National Solar Radiation Database: Preprint

The National Renewable Energy Laboratory (NREL), University of Wisconsin, and National Oceanic Atmospheric Administration are collaborating to investigate the integration of the Satellite Algorithm for Shortwave Radiation Budget (SASRAB) products into future versions of NREL's 4-km by 4-km gridded National Solar Radiation Database (NSRDB). This paper describes a method to select an improved clear-sky model that could replace the current SASRAB global horizontal irradiance and direct normal irradiances reported during clear-sky conditions.

14 SOLAR ENERGY↗
DOE OSTI2021

Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ΔR. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Summertime Continental Shallow Cumulus Cloud Detection Using GOES‐16 Satellite and Ground‐Based Ceilometer at North Alabama

Abstract Accurate simulations of boundary layer cloud processes remain challenging in Earth system modeling. Observations are essential to evaluate and improve models of such processes. This study introduces a comprehensive validation framework for a satellite‐based detection algorithm of continental shallow cumulus (ShCu) clouds during the daytime, which was initially developed using ground‐based observations of stereo cameras at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site (J. Tian et al., 2021, https://doi.org/10.3390/rs13122309 , 2022, https://doi.org/10.1029/2021gl097070 ). To validate this algorithm, the framework employs ground‐based ceilometer measurements from North Alabama (NA) where ShCu populations are prevalent. This study first generates clear‐sky surface reflectance maps at NA and identifies ShCu pixels with a detection threshold using Geostationary Operational Environmental Satellite (GOES) reflectance data. The obtained cloud fractions (CFs) are then compared against CFs from a ground‐based ceilometer, considering factors such as observed area differences, satellite parallax issue, and systematic biases. We found that with a detection threshold (∆R) of 0.05, the ShCu detection algorithm is effective for NA, enabling the reproduction of hourly ShCu CFs using GOES. Our framework is straightforward and easily repeatable to evaluate the effectiveness of a ∆R threshold for detecting ShCu clouds in various geographic regions where ceilometers are deployed. This satellite detection of ShCu provides a crucial regional context for ground‐based measurements, facilitating the tracking of convection initiation and its coupling with land surface conditions. Integrating localized ground‐based and regional satellite data will enhance our ability to conduct thorough studies of cloud morphology and land‐atmosphere interactions in North Alabama.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

National Solar Radiation Database (NSRDB)

The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2023. The NSRDB is updated annually and provides foundational information to support U.S. Department of Energy programs, research, industry and the general public. The NSRDB provides time-series data at 30-minute resolution of resource averaged over surface cells of 0.038 degrees in both latitude and longitude, or nominally 4 km in size. Additionally time series data at 5 minutes for the US and 10 minutes for North, Central and South America at 2 km resolution are produced from the next generation of GOES satellites and made available from 2019. The solar radiation values represent the resource available to solar energy systems. The data was created using cloud properties which are generated using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms developed by the University of Wisconsin. Fast all-sky radiation model for solar applications (FARMS) in conjunction with the cloud properties, and aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary source are used to estimate solar irradiance (GHI, DNI, and DHI). The Global Horizontal Irradiance (GHI) is computed for clear skies using the REST2 model. For cloud scenes identified by the cloud mask, FARMS is used to compute GHI and FARMS DNI is used to compute the Direct Normal Irradiance (DNI). The PATMOS-X model uses radiance images in visible and infrared channels from the Geostationary Operational Environmental Satellite (GOES) series of geostationary weather satellites. Ancillary variables needed to run REST2 and FARMS (e.g., aerosol optical depth, precipitable water vapor, and albedo) are derived from NASA's Modern Era-Retrospective Analysis (MERRA-2) dataset. Temperature and wind speed data are also derived from MERRA-2 and provided for use in NREL's System Advisor Model (SAM) to compute PV generation.

aerosol↗
DOE OSTI2020

Synergetic Use of the WSR-88D Radars, GOES-R Satellites, and Lightning Networks to Study Microphysical Characteristics of Hurricanes

Abstract This study analyzes the microphysics and precipitation pattern of Hurricanes Harvey (2017) and Florence (2018) in both the eyewall and outer rainband regions. From the retrievals by a satellite red–green–blue scheme, the outer rainbands show a strong convective structure while the inner eyewall has less convective vigor (i.e., weaker upper-level reflectivities and electrification), which may be related to stronger vertical wind shear that hinders fast vertical motions. The WSR-88D column-vertical profiles further confirm that the outer rainband clouds have strong vertical motion and large ice-phase hydrometeor formation aloft, which correlates well with 3D Lightning Mapping Array source counts in height and time. From the results from this study, it is determined that the inner eyewall region is dominated by warm rain, whereas the external rainband region contains intense mixed-phase precipitation. External rainbands are defined here as those that reside outside of the main hurricane circulation, associated with surface tropical storm wind speeds. The synergy of satellite and radar dual-polarization parameters is instrumental in distinguishing between the key microphysical features of intense convective rainbands and the warm-rain-dominated eyewall regions within the hurricanes. Substantial amounts of ice aloft and intense updrafts in the external rainbands are indicative of heavy surface precipitation, which can have important implications for severe weather warnings and quantitative precipitation forecasts. The novel part of this study is to combine ground-based radar measurement with satellite observations to study hurricane microphysical structure from surface to cloud top so as to fill in the gaps between the two observational techniques.

Meteorology & Atmospheric Sciences↗
DOE OSTI2015

The source of multi spectral energy of solar energetic electron

We study the solar energetic electron distribution obtained from ACE and GOES satellites which have different altitudes and electron spectral energy during the year 1997 to 2011. The electron spectral energies were 0.038–0.315 MeV from EPAM instrument onboard ACE satellite and >2 MeV from GOES satellite. We found that the low electron energy has no correlation with high energy. In spite of we have corrected to the altitude differences. It implied that they originated from time dependent events with different sources and physical processes at the solar atmosphere. The sources of multi spectral energetic electron were related to flare and CME phenomena. However, we also found that high energetic electron comes from coronal hole.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

PREDICTION OF SOLAR FLARE SIZE AND TIME-TO-FLARE USING SUPPORT VECTOR MACHINE REGRESSION

We study the prediction of solar flare size and time-to-flare using 38 features describing magnetic complexity of the photospheric magnetic field. This work uses support vector regression to formulate a mapping from the 38-dimensional feature space to a continuous-valued label vector representing flare size or time-to-flare. When we consider flaring regions only, we find an average error in estimating flare size of approximately half a geostationary operational environmental satellite (GOES) class. When we additionally consider non-flaring regions, we find an increased average error of approximately three-fourths a GOES class. We also consider thresholding the regressed flare size for the experiment containing both flaring and non-flaring regions and find a true positive rate of 0.69 and a true negative rate of 0.86 for flare prediction. The results for both of these size regression experiments are consistent across a wide range of predictive time windows, indicating that the magnetic complexity features may be persistent in appearance long before flare activity. This is supported by our larger error rates of some 40 hr in the time-to-flare regression problem. The 38 magnetic complexity features considered here appear to have discriminative potential for flare size, but their persistence in time makes them less discriminative for the time-to-flare problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

ESTIMATE OF SOLAR MAXIMUM USING THE 1-8 Å GEOSTATIONARY OPERATIONAL ENVIRONMENTAL SATELLITES X-RAY MEASUREMENTS

We present an alternate method of determining the progression of the solar cycle through an analysis of the solar X-ray background. Our results are based on the NOAA Geostationary Operational Environmental Satellites (GOES) X-ray data in the 1-8 Å band from 1986 to the present, covering solar cycles 22, 23, and 24. The X-ray background level tracks the progression of the solar cycle through its maximum and minimum. Using the X-ray data, we can therefore make estimates of the solar cycle progression and the date of solar maximum. Based upon our analysis, we conclude that the Sun reached its hemisphere-averaged maximum in solar cycle 24 in late 2013. This is within six months of the NOAA prediction of a maximum in spring 2013.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A LARGE-SCALE SEARCH FOR EVIDENCE OF QUASI-PERIODIC PULSATIONS IN SOLAR FLARES

The nature of quasi-periodic pulsations (QPP) in solar flares is poorly constrained, and critically the general prevalence of such signals in solar flares is unknown. Therefore, we perform a large-scale search for evidence of signals consistent with QPP in solar flares, focusing on the 1–300 s timescale. We analyze 675 M- and X-class flares observed by the Geostationary Operational Environmental Satellite (GOES) series in 1–8 Å soft X-rays between 2011 February 1 and 2015 December 31. Additionally, over the same era we analyze Fermi /Gamma-ray Burst Monitor (GBM) 15–25 keV X-ray data for each of these flares associated with a Fermi /GBM solar flare trigger, a total of 261 events. Using a model comparison method, we determine whether there is evidence for a substantial enhancement in the Fourier power spectrum that may be consistent with a QPP signature, based on three tested models; a power-law plus a constant, a broken power-law plus constant, and a power-law-plus-constant with an additional QPP signature component. From this, we determine that ∼30% of GOES events and ∼8% of Fermi /GBM events show strong signatures consistent with classical interpretations of QPP. For the remaining events either two or more tested models cannot be strongly distinguished from each other, or the events are well-described by single power-law or broken power-law Fourier power spectra. For both instruments, a preferred characteristic timescale of ∼5–30 s was found in the QPP-like events, with no dependence on flare magnitude in either GOES or GBM data. We also show that individual events in the sample show similar characteristic timescales in both GBM and GOES data sets. We discuss the implications of these results for our understanding of solar flares and possible QPP mechanisms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

New Solar Irradiance Measurements from the Miniature X-Ray Solar Spectrometer Cubesat

The goal of the Miniature X-ray Solar Spectrometer ( MinXSS ) CubeSat is to explore the energy distribution of soft X-ray (SXR) emissions from the quiescent Sun, active regions, and during solar flares and to model the impact on Earth's ionosphere and thermosphere. The energy emitted in the SXR range (0.1–10 keV) can vary by more than a factor of 100, yet we have limited spectral measurements in the SXRs to accurately quantify the spectral dependence of this variability. The MinXSS primary science instrument is an Amptek, Inc. X123 X-ray spectrometer that has an energy range of 0.5–30 keV with a nominal 0.15 keV energy resolution. Two flight models have been built. The first, MinXSS -1, has been making science observations since 2016 June 9 and has observed numerous flares, including more than 40 C-class and 7 M-class flares. These SXR spectral measurements have advantages over broadband SXR observations, such as providing the capability to derive multiple-temperature components and elemental abundances of coronal plasma, improved irradiance accuracy, and higher resolution spectral irradiance as input to planetary ionosphere simulations. MinXSS spectra obtained during the M5.0 flare on 2016 July 23 highlight these advantages and indicate how the elemental abundance appears to change from primarily coronal to more photospheric during the flare. MinXSS -1 observations are compared to the Geostationary Operational Environmental Satellite ( GOES ) X-ray Sensor (XRS) measurements of SXR irradiance and estimated corona temperature. Additionally, a suggested improvement to the calibration of the GOES XRS data is presented.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Onset of a Large Ejective Solar Eruption from a Typical Coronal-jet-base Field Configuration

Utilizing multiwavelength observations and magnetic field data from the Solar Dynamics Observatory ( SDO )/Atmospheric Imaging Assembly (AIA), SDO /Helioseismic and Magnetic Imager (HMI), the Geostationary Operational Environmental Satellite ( GOES ), and RHESSI , we investigate a large-scale ejective solar eruption of 2014 December 18 from active region NOAA 12241. This event produced a distinctive “three-ribbon” flare, having two parallel ribbons corresponding to the ribbons of a standard two-ribbon flare, and a larger-scale third quasi-circular ribbon offset from the other two. There are two components to this eruptive event. First, a flux rope forms above a strong-field polarity inversion line and erupts and grows as the parallel ribbons turn on, grow, and spread apart from that polarity inversion line; this evolution is consistent with the mechanism of tether-cutting reconnection for eruptions. Second, the eruption of the arcade that has the erupting flux rope in its core undergoes magnetic reconnection at the null point of a fan dome that envelops the erupting arcade, resulting in formation of the quasi-circular ribbon; this is consistent with the breakout reconnection mechanism for eruptions. We find that the parallel ribbons begin well before (∼12 minutes) the onset of the circular ribbon, indicating that tether-cutting reconnection (or a non-ideal MHD instability) initiated this event, rather than breakout reconnection. The overall setup for this large-scale eruption (diameter of the circular ribbon ∼10{sup 5} km) is analogous to that of coronal jets (base size ∼10{sup 4} km), many of which, according to recent findings, result from eruptions of small-scale “minifilaments.” Thus these findings confirm that eruptions of sheared-core magnetic arcades seated in fan–spine null-point magnetic topology happen on a wide range of size scales on the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

GLOBAL SAUSAGE OSCILLATION OF SOLAR FLARE LOOPS DETECTED BY THE INTERFACE REGION IMAGING SPECTROGRAPH

An observation from the Interface Region Imaging Spectrograph reveals coherent oscillations in the loops of an M1.6 flare on 2015 March 12. Both the intensity and Doppler shift of Fe xxi 1354.08 Å show clear oscillations with a period of ∼25 s. Remarkably similar oscillations were also detected in the soft X-ray flux recorded by the Geostationary Operational Environmental Satellites ( GOES ). With an estimated phase speed of ∼2420 km s{sup −1} and a derived electron density of at least 5.4 × 10{sup 10} cm{sup −3}, the observed short-period oscillation is most likely the global fast sausage mode of a hot flare loop. We find a phase shift of ∼ π /2 (1/4 period) between the Doppler shift oscillation and the intensity/ GOES oscillations, which is consistent with a recent forward modeling study of the sausage mode. The observed oscillation requires a density contrast between the flare loop and coronal background of a factor ≥42. The estimated phase speed of the global mode provides a lower limit of the Alfvén speed outside the flare loop. We also find an increase of the oscillation period, which might be caused by the separation of the loop footpoints with time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF- ARW Using Synthetic and Observed GOES-13 Imagery

Synthetic satellite imagery can be employed to evaluate simulated cloud fields. Past studies have revealed that the Weather Research and Forecasting (WRF) WRF Single-Moment 6-class (WSM6) microphysics in WRF-ARW produces less upper level ice clouds within synthetic images compared to observations. Synthetic Geostationary Operational Environmental Satellite (GOES)-13 imagery at 10.7 μm of simulated cloud fields from the 4 km National Severe Storms Laboratory (NSSL) WRF-ARW is compared to observed GOES-13 imagery. Histograms suggest that too few points contain upper level simulated ice clouds. In particular, side-by-side examples are shown of synthetic and observed convective anvils. Such images illustrate the lack of anvil cloud associated with convection produced by the NSSL WRF-ARW. A vertical profile of simulated hydrometeors suggests that too much cloud water mass may be converted into graupel mass, effectively reducing the main source of ice mass in a simulated anvil. Further, excessive accretion of ice by snow removes ice from an anvil by precipitation settling. Idealized sensitivity tests reveal that a 50% reduction of the conversion of cloud water mass to graupel and a 50% reduction of the accretion rate of ice by snow results in a significant increase in anvil ice of a simulated storm. Such results provide guidance as to which conversions could be reformulated, in a more physical manner, to increase simulated ice mass in the upper troposphere.

GOES-13 imagery↗