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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sensitivity of future liquid argon dark matter search experiments to core-collapse supernova neutrinos

Future liquid-argon DarkSide-20k and Argo detectors, designed for direct dark matter search, will be sensitive also to core-collapse supernova neutrinos, via coherent elastic neutrino-nucleus scattering. This interaction channel is flavor-insensitive with a high-cross section, enabling for a high-statistics neutrino detection with target masses of ~50 t and ~360 t for DarkSide-20k and Argo respectively. Thanks to the low-energy threshold of ~0.5 keVnr achievable by exploiting the ionization channel, DarkSide-20k and Argo have the potential to discover supernova bursts throughout our galaxy and up to the Small Magellanic Cloud, respectively, assuming a 11-M progenitor star. In this work, we report also on the sensitivity to the neutronization burst, whose electron neutrino flux is suppressed by oscillations when detected via charged current and elastic scattering. Finally, the accuracies in the reconstruction of the average and total neutrino energy in the different phases of the supernova burst, as well as its time profile, are also discussed, taking into account the expected background and the detector response.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Improving deep learning-based protein distance prediction in CASP14

Abstract Motivation Accurate prediction of residue–residue distances is important for protein structure prediction. We developed several protein distance predictors based on a deep learning distance prediction method and blindly tested them in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The prediction method uses deep residual neural networks with the channel-wise attention mechanism to classify the distance between every two residues into multiple distance intervals. The input features for the deep learning method include co-evolutionary features as well as other sequence-based features derived from multiple sequence alignments (MSAs). Three alignment methods are used with multiple protein sequence/profile databases to generate MSAs for input feature generation. Based on different configurations and training strategies of the deep learning method, five MULTICOM distance predictors were created to participate in the CASP14 experiment. Results Benchmarked on 37 hard CASP14 domains, the best performing MULTICOM predictor is ranked 5th out of 30 automated CASP14 distance prediction servers in terms of precision of top L/5 long-range contact predictions [i.e. classifying distances between two residues into two categories: in contact (<8 Angstrom) and not in contact otherwise] and performs better than the best CASP13 distance prediction method. The best performing MULTICOM predictor is also ranked 6th among automated server predictors in classifying inter-residue distances into 10 distance intervals defined by CASP14 according to the precision of distance classification. The results show that the quality and depth of MSAs depend on alignment methods and sequence databases and have a significant impact on the accuracy of distance prediction. Using larger training datasets and multiple complementary features improves prediction accuracy. However, the number of effective sequences in MSAs is only a weak indicator of the quality of MSAs and the accuracy of predicted distance maps. In contrast, there is a strong correlation between the accuracy of contact/distance predictions and the average probability of the predicted contacts, which can therefore be more effectively used to estimate the confidence of distance predictions and select predicted distance maps. Availability and implementation The software package, source code and data of DeepDist2 are freely available at https://github.com/multicom-toolbox/deepdist and https://zenodo.org/record/4712084#.YIIM13VKhQM. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Adapting In Situ Accelerators for Sparsity With Granular Matrix Reordering

Neural network (NN) inference is an essential part of modern systems and is found at the heart of numerous applications ranging from image recognition to natural language processing. In situ NN accelerators can efficiently perform NN inference using resistive crossbars, which makes them a promising solution to the data movement challenges faced by conventional architectures. Although such accelerators demonstrate significant potential for dense NNs, they often do not benefit from sparse NNs, which contain relatively few non-zero weights. Processing sparse NNs on in situ accelerators results in wasted energy to charge the entire crossbar where most elements are zeros. To address this limitation, this paper proposes Granular Matrix Reordering (GMR): a preprocessing technique that enables an energy-efficient computation of sparse NNs on in situ accelerators. GMR reorders the rows and columns of sparse weight matrices to maximize the crossbars' utilization and minimize the total number of crossbars needed to be charged. The reordering process does not rely on sparsity patterns and incurs no accuracy loss. Finally, GMR achieves an average of 28% and up to 34% reduction in energy consumption over seven pruned NNs across four different pruning methods and network architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Marine Hydrogen Demonstration

This report summarizes Phase 1 of a project involving the design of a Floating Hydrogen Production and Dispensing Barge destined for the Port of San Francisco (SF). The H 2 Barge is designed to produce renewable H 2 at the rate of ~ 530 kg/day, storing 512 kg of hydrogen at 517-bar, allowing fast refueling of hydrogen fuel cell vessels and land-side hydrogen delivery trailers for distribution into the nascent SF hydrogen ecosystem. The broader considerations that impacted the H2 Barge design are also described. An account is given of a new review process formulated by the United States Coast Guard (USCG) to review this first-of-its-kind maritime implementation of hydrogen technology. The immediate goals of the H 2 Barge Project are to 1) demonstrate the feasibility, viability and methods of hydrogen production, storage and fueling in a maritime context, 2) help shape (where needed) and navigate the required local, state and federal regulatory gauntlet and 3) catalyze a “green hydrogen ecosystem” (both marine and landside) with locally produced renewable hydrogen at the San Francisco waterfront. A summary is also given of the modeling and experimental activity of Phase 1 directed to the development of science-based refueling protocols for large marine Type IV 250-bar hydrogen tanks. Combined modeling and experimental studies are reported of the filling of large (28 kg) 250-bar Type IV hydrogen tanks of the type being deployed on early hydrogen ferries, such as the MV Sea Change. The primary question was to determine how such tanks can be successfully filled (state of charge greater than 97%) within 45 minutes without exceeding the 82 °C temperature limit historically set for such tanks. The studies show that a gas injector is needed avoid thermal stratification during filling which can result in potential hot spots. Pre-cooling of the hydrogen was found to be essential in most cases, as ambient conditions greatly affect the need for a pre-cooling to achieve the 45-minute fill time. Pre-cooling cannot be supplied by nearby water, such as that found in nature (bays, lakes, rivers, etc.) because pre-cooling cooling below 0 °C was found to be necessary to avoid excessive compression heating. The experimental results afforded a calibration of the engineering model (SOFIL) for these large 250-bar tanks, which now enables using SOFIL to predict volume-averaged hydrogen filling temperatures to an accuracy of +/- 2.7°C for these tanks. The model can therefore be used to evaluate potential scenarios for development of a standardized fueling methodology for ferries utilizing large Type-IV tanks of the type examined here.

08 HYDROGEN↗
DOE OSTI2023

Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure

Fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. We hypothesized that predictive models for personal chemical exposure would be significantly improved by expanding beyond stationary PM2.5 AQI data or satellite HMS data to also include environmental and behavioral information. In Eugene, Oregon, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a seven-day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons (PAHs). Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.

Bramer, Lisa M↗
NASA NTRS1982

Surface wind analyses for Seasat

During the 99 days of Seasat operation, two large-scale experiments were conducted which established the satellite sensors' wind measuring capabilities: (1) the Gulf of Alaska Experiment (GOASEX), and (2) the Joint Air Sea Interaction Experiment (JASIN), which unlike GOASEX was independent of the Seasat program and undertook comprehensive air and sea investigations which furnished excellent comparison data for Seasat. Qualitative comparison windfields were also provided by several storms. The point measurements in GOASEX and JASIN were averaged in conjunction with Seasat scatterometer regions and, on the basis of comparisons between several anemometers on buoys and meteorological ships and the calculation of various averaging times, a 20-min average yields a scatterometer scale windfield accuracy of up to + or 1 m/sec and + or - 10 deg in well-behaved windfields.

Brown, R. A.↗
NASA NTRS1990

Multigrid solution of unsteady Navier-Stokes equations using a pressure method

A multigrid relaxation method is applied to a pressure-based implicit procedure to solve unseady, incompressible Navier-Stokes equations. The present multigrid method is a Correction Scheme according to Brandt. This method is used to solve the scalar matrices resulting from the finite-volume formulation and uses flux averaging as the restriction operator. The accuracy and computational efficiency are demonstrated with a steady state driven cavity flow and an unsteady flow over a circular cylinder case. The results are compared with single grid results using the OrthoMin conjugate gradient method and experimental data.

Jiang, Y.↗
NASA NTRS1992

Solar Doppler-shift measurements in the Ne VII 465 A emission line

Using a Dopplergram obtained with the Naval Research Laboratory extreme ultraviolet spectrograph on Skylab, we have searched for Doppler shifts in the Ne VII 465 A emission line, which is formed at a temperature of about 500,000 K. In the quiet sun we find no measurable average Doppler shift to a measurement accuracy of +/- 18 km/s. Small regions of the quiet sun do, however, display measurable Doppler shifts. In active regions, we measure Doppler shifts indicating downflow velocities of up to 70 km/s.

Mariska, John T.↗
NASA NTRS1994

Laboratory and in-flight experiments to evaluate 3-D audio display technology

Laboratory and in-flight experiments were conducted to evaluate 3-D audio display technology for cockpit applications. A 3-D audio display generator was developed which digitally encodes naturally occurring direction information onto any audio signal and presents the binaural sound over headphones. The acoustic image is stabilized for head movement by use of an electromagnetic head-tracking device. In the laboratory, a 3-D audio display generator was used to spatially separate competing speech messages to improve the intelligibility of each message. Up to a 25 percent improvement in intelligibility was measured for spatially separated speech at high ambient noise levels (115 dB SPL). During the in-flight experiments, pilots reported that spatial separation of speech communications provided a noticeable improvement in intelligibility. The use of 3-D audio for target acquisition was also investigated. In the laboratory, 3-D audio enabled the acquisition of visual targets in about two seconds average response time at 17 degrees accuracy. During the in-flight experiments, pilots correctly identified ground targets 50, 75, and 100 percent of the time at separation angles of 12, 20, and 35 degrees, respectively. In general, pilot performance in the field with the 3-D audio display generator was as expected, based on data from laboratory experiments.

Ericson, Mark↗
NASA NTRS1995

Vertical Scales of Turbulence at the Mount Wilson Observatory

The vertical scales of turbulence at the Mount Wilson Observatory are inferred from data from the University of California at Berkeley Infrared Spatial Interferometer (ISI), by modeling path length fluctuations observed in the interferometric paths to celestial objects and those in instrumental ground-based paths. The correlations between the stellar and ground-based path length fluctuations and the temporal statistics of those fluctuations are modeled on various timescales to constrain the vertical scales. A Kolmogorov-Taylor turbulence model with a finite outer scale was used to simulate ISI data. The simulation also included the white instrumental noise of the interferometer, aperture-filtering effects, and the data analysis algorithms. The simulations suggest that the path delay fluctuations observed in the 1992-1993 ISI data are largely consistent with being generated by refractivity fluctuations at two characteristic vertical scales: one extending to a height of 45 m above the ground, with a wind speed of about 1 m/ s, and another at a much higher altitude, with a wind speed of about 10 m/ s. The height of the lower layer is of the order of the dimensions of trees and other structures near the interferometer, which suggests that these objects, including elements of the interferometer, may play a role in generating the lower layer of turbulence. The modeling indicates that the high- attitude component contributes primarily to short-period (less than 10 s) fluctuations, while the lower component dominates the long-period (up to a few minutes) fluctuations. The lower component turbulent height, along with outer scales of the order of 10 m, suggest that the baseline dependence of long-term interferometric, atmospheric fluctuations should weaken for baselines greater than a few tens of meters. Simulations further show that there is the potential for improving the seeing or astrometric accuracy by about 30%-50% on average, if the path length fluctuations in the lower component are directly calibrated. Statistical and systematic effects induce an error of about 15 m in the estimate of the lower component turbulent altitude.

Treuhaft, Robert N.↗
NASA NTRS2000

Leonardo-BRDF: A New Generation Satellite Constellation

Instantaneous net radiation flux at the top of the atmosphere is one of the primary drivers of climate and global change. Since the dawn of the satellite era, great efforts and expense have gone into measuring this flux from single satellites and even (for a several-year period) from a constellation of three satellites called ERBE. However, the reflected solar flux is an angular and spectral integral over the so-called "BRDF" or Bidirectional Reflectance Distribution Function, which is the angular distribution of reflected solar radiation for each solar zenith angle and each wavelength. Previous radiation flux satellites could not measure instantaneous BRDF, so scientists have had to fall back on models or composites. Because their range of observed solar zenith angles was very limited due to sunsynchronous orbits, the resultant flux maps are too inaccurate to see the dynamics of radiation flux or to reliably correlate it with specific phenomena (hurricanes, biomass fires, urban pollution, dust outbreaks, etc.). Accuracy only becomes acceptable after monthly averaging, but this washes out almost all cause-and-effect information, further exacerbated by the lack of spectral resolution. Leonardo-BRDF is a satellite system designed to measure the instantaneous spectral BRDF using a formation of highly coordinated satellites, all pointing at the same Earth targets at the same time. It will allow scientists for the first time to assess the radiative forcing of climate due to specific phenomena, which is bound to be important in the ongoing debate about global warming and what is causing it. The formation is composed of two satellite types having, as instrument payloads, single highly-integrated miniature imaging spectrometers or radiometers. Two nearby "keystone" satellites anchor the formation and fly in static orbits. They employ wide field of view imaging spectrometers that are extremely light and compact. The keystone satellites are identical and can operate in alongtrack or cross-track mode, or anything in between, at ground command. This provides inherent system redundancy and cross-calibration capability. Several "wing-man" satellites in non-static orbits fly in formation up to 1000 km out from the keystone satellites to provide additional along- and cross-track angular sampling. They view the target(s) observed by the keystone satellites from different zenith and azimuth angles and are maneuverable within a limited range of zenith angle using thrusters, and within a large range of azimuth angle using clever orbit design. The wing-man satellites carry single miniature imaging radiometers with just a few wavelength bands in order to be lighter and more agile.

Esper, Jaime↗
NASA NTRS2000

Structure and Dynamics of the Polar Regions of Mars from MGS Topography and Gravity

The Mars Global Surveyor (MGS) spacecraft has been engaged in systematic mapping of Mars since insertion into Mars orbit in September, 1997. The objectives of the MGS mission are to globally map Mars as well as to quantify seasonal changes on the planet. MGS geophysical/geodetic observations of topography from the Mars Orbiter Laser Altimeter (MOLA) and gravity from the Radio Science investigation are providing significant new insights on both static and time-varying aspects of the polar regions of Mars. These observations have implications for polar processes on diurnal seasonal and climatic timescales. Thus far, MOLA has collected over 300 million precise measurements of Martian topography and cloud heights. The instrument has also provided measurements of the width of the backscattered optical pulse and of the 1064 nm reflectivity of the Martian surface and atmosphere. The along-track resolution of MOLA ground shots is approx. 300 m and the across-track spacing in the polar regions is a maximum of about four kilometers. The vertical accuracy of the topography is determined by the precision recovery of spacecraft orbits from the Radio Science investigation, which includes MOLA altimetry in the form of crossovers. This accuracy is currently approx. one meter. The gravity field is derived from X-band Doppler tracking with typical accuracy of 0.03 to 0.05 mm/s averaged over ten seconds. Current Mars gravity fields are to approximately degree and order 80 but are interpretable to the approximate degree and order 60 (spatial resolution < 180 km), which represents an estimate of the approximate coefficient limit of a field that can be produced without a power law constraint on the gravitational field inversion, which is commonly imposed for solution stability. Additional information is contained in the original extended abstract.

Zuber, Maria T.↗
NASA NTRS2010

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Sandford, Stephen P.↗
NASA NTRS2011

Aquarius Instrument and Salinity Retrieval

Aquarius has been designed to map the surface salinity field of the global ocean from space a parameter important for understanding ocean circulation and its relationship to climate and the global water cycle. Salinity is measured remotely from space by measuring the thermal emission from the ocean surface. This is done at the low frequency end of the microwave spectrum (e.g. 1.4 GHz) where the emission is sufficiently sensitive to changes in salinity to be detected with sophisticated radiometers. The goal is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean by providing maps on a monthly basis with a spatial resolution of 150 km and an accuracy of 0.2 psu. These are challenging requirements that have led to some unique features of the instrument. These include: a) The addition of a co-located scatterometer to help provide a correction for roughness; b) The addition of a polarimetric channel (third Stokes parameter) to the radiometer to help correct for Faraday rotation; c) Asun-synchronous orbit with a 6 pm ascending equatorial crossing to minimize Faraday rotation and with the antennas looking away from the sun toward the nighttime side to minimize contamination by radiation from the sun; and d) An antenna designed to limit side lobes in the direction of rays from the sun. In addition, achieving the accuracy goal of 0.2 psu requires averaging over one month and to do this requires a highly stable radiometer. Aquarius has three separate radiometers that image in pushbroom fashion with the three antenna beams looking across track. The antenna is a 2.5-m diameter, offset parabolic reflector with three feed horns and the three beams are arranged to image with the boresight aligned to look across track, roughly perpendicular to the spacecraft heading and pointing away from the Sun. The three beams point at angles of theta = 25.8 deg., 33.8 deg. and 40.3 deg. with respect to the spacecraft nadir which correspond to local incidence angles at the surface of 28.7 deg., 37.8 deg. and 45.6 deg., respectively. The resolution of the three radiometer beams (axes of the 3dB ellipse) is: 76 x 94 km for the inner beam, 84 x 120 km for the middle beam to 96 x 156 km for the outer beam. Together they cover a swath of about 390 km. Aquarius will map the global ice-free ocean every 7-days from which monthly average composites will be derived. This will provide a snapshot of the mean field, as well as resolving the seasonal to interannual variations over the three-year baseline of the mission.

Le Vine, D. M.↗
NASA NTRS2016

Assessment of the SMAP Passive Soil Moisture Product

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

passive↗
DOE OSTI2020

Sensitivity of future liquid argon dark matter search experiments to core-collapse supernova neutrinos

Future liquid-argon DarkSide-20k and ARGO detectors, designed for direct dark matter search, will be sensitive also to core-collapse supernova neutrinos, via coherent elastic neutrino-nucleus scattering. This interaction channel is flavor-insensitive with a high-cross section, enabling for a high-statistics neutrino detection with target masses of $\sim$50~t and $\sim$360~t for DarkSide-20k and ARGO, respectively. Thanks to the low-energy threshold of $\sim$0.5~keV$_{nr}$ achievable by exploiting the ionization channel, DarkSide-20k and ARGO have the potential to discover supernova bursts throughout our galaxy and up to the Small Magellanic Cloud, respectively, assuming a 11-M$_{\odot}$ progenitor star. We report also on the sensitivity to the neutronization burst, whose electron neutrino flux is suppressed by oscillations when detected via charged current and elastic scattering. Finally, the accuracies in the reconstruction of the average and total neutrino energy in the different phases of the supernova burst, as well as its time profile, are also discussed, taking into account the expected background and the detector response.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1999

Cross-Sensor Validation of the Optical Transient Detector (OTD)

Lightning data from the U.S. National Lightning Detection Network (NLDN) is used to perform preliminary validation of the satellite-based Optical Transient Detector (OTD). Sensor precision, accuracy, detection efficiency and biases of the deployed instrument are considered. We estimate the sensor to have, on average, better than 30 km spatial and 100 ms temporal accuracy. The detection efficiency for cloud-to-ground lightning is about 45-70%, slightly higher for intracloud lightning. There are only marginal day/night biases in the dataset, although 55 day averaging is required to remove sampling-based diurnal lightning cycle biases. The sensor detects statistically significant differences in the optical characteristics of intracloud, negative cloud-to-ground and positive cloud-to-ground lightning, although it cannot a priori determine flash types.

Boccippio, D. J.↗
NASA NTRS2013

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

Aqua↗