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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Autonomous monitoring of algal biomass: Success stories and lessons learned from long-term field deployment

Autonomous, high-frequency monitoring of outdoor algal ponds is needed to quantify biomass productivity and detect culture decline in environments prone to contamination, grazers, and variable operating conditions. We report successes and lessons learned in translating a laboratory spectroradiometric monitoring approach to a multi-year autonomous field deployment at the Arizona Center for Algae Technology and Innovation (AzCATI). The system measures spectrally resolved pond reflectance by ratioing upwelling radiance from each raceway to simultaneous downwelling sky irradiance using fiber-coupled spectrometers. A physics-based reflectance model (ASHARP) is fit to each spectrum pair to estimate optical parameters, including a biomass-proxy coefficient (C a ) which enables near-real-time tracking of biomass accumulation and culture state at 2–5 min intervals. From May 2022 through September 2025 the platform operated continuously while scaling from two to six raceway ponds. Several strains of algae were monitored successfully, including the high productivity Tetraselmis striata and Picochlorum celeri. Transitioning data acquisition from a Windows laptop to a Raspberry Pi improved uptime from 57% (2022) to ~89% (2024–2025) and enabled routine real-time analysis. Further, we converted relative biomass estimates to absolute ash-free dry weight (AFDW) using experimentally-derived calibrations, providing field-relevant biomass predictions with conservative confidence bounds. These results demonstrate the feasibility of long-term, autonomous optical monitoring for well-mixed open-raceway algal cultivation and provide practical guidance for reliable field operation and scaling.

Katinas, Christopher Michael [Sandia National Labo↗
NASA NTRS1997

Observation of a Long-Term Spin-up Trend in 4U 1538-52

The high-mass X-ray pulsar 4U 153 8-52 has been continually monitored by the Burst and Transient Source Experiment (BATSE) on Compton Gamma-Ray Observatory. These observations permit the construction of long-term pulse frequency and intensity histories. The frequency history reveals that a reversal of the long-term trend in the accretion torque, from spinning down to spinning up, has occurred, probably in 1988. This is the first time a long-term change is known to have occurred for this source, The magnitude of the average absolute value of (dot-nu / nu) is approximately 10(exp -11)/s over an interval of approximately 5 year is similar during spin-down and spin-up. Shorter term pulse frequency variations of either sign are also observed. The power density spectrum of fluctuations in angular acceleration is consistent with white noise on timescales from 16 to 1600 days. It can be well fit with a power law with a power-law index of 0.10 plus or minus 0.21 and white noise strength of (7.6 +/- 1.6) x 10(exp -21) (Hz/s(exp 2)/Hz). These observations are also used to set 95% confidence level lower and upper limits on the rate of orbital period change, -3.9< dot-P orb /P orb <2. 1, in units of 10(exp -6) yr(exp -1).

Rubin, B. C.↗
DOE OSTI2023

Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions

Machine learning (ML) models, and Long Short-Term Memory (LSTM) networks in particular, have demonstrated remarkable performance in streamflow prediction and are increasingly being used by the hydrological research community. However, most of these applications do not include uncertainty quantification (UQ). ML models are data driven and can suffer from large extrapolation errors when applied to changing climate/environmental conditions. UQ is required to quantify the influence of data noises on model predictions and avoid overconfident projections in extrapolation. In this work, we integrate a novel UQ method, called PI3NN, with LSTM networks for streamflow prediction. PI3NN calculates Prediction Intervals by training 3 Neural Networks. It can precisely quantify the predictive uncertainty caused by the data noise and identify out-of-distribution (OOD) data in a non-stationary condition to avoid overconfident predictions. We apply the PI3NN-LSTM method in the snow-dominant East River Watershed in the western US and in the rain-driven Walker Branch Watershed in the southeastern US. Results indicate that for the prediction data which have similar features as the training data, PI3NN precisely quantifies the predictive uncertainty with the desired confidence level; and for the OOD data where the LSTM network fails to make accurate predictions, PI3NN produces a reasonably large uncertainty indicating that the results are not trustworthy and should avoid overconfidence. PI3NN is computationally efficient, robust in performance, and generalizable to various network structures and data with no distributional assumptions. It can be broadly applied in ML-based hydrological simulations for credible prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Feature review of photovoltaic modeling software utilizing blind performance assessment

While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.

14 SOLAR ENERGY↗
NASA NTRS1983

Spectral observation of the soft X-ray background and of the North Polar Spur with solid state spectrometers

Soft X-ray diffuse background observations in the 0.3-1.5 keV interval of two sky regions, near the north galactic pole and the North Polar Spur (NPS) are reported. Data were taken with a solid-state spectrometer carried by a rocket. The near-polar region exhibited O VII ion emissions at 530 eV. A second component was not identified but was attributed to the Galactic Halo. Fe XVIII, Ne IX, and O VIII contributions were detected in the NPS, along with an enhancement at 1.35 keV from Mg XI lines. A two-temperature contour was fit to the spectra and chi-square confidence levels of 90 and 68 percent were obtained.

Rocchia, R.↗
NASA NTRS1996

Prelude to Cycle 23: The Case for a Fast-Rising, Large Amplitude Cycle

For the common data-available interval of cycles 12 to 22, we show that annual averages of sunspot number for minimum years (R(min)) and maximum years (R(max)) and of the minimum value of the aa geomagnetic index in the vicinity of sunspot minimum (aa(min)) are consistent with the notion that each has embedded within its respective record a long-term, linear, secular increase. Extrapolating each of these fits to cycle 23, we infer that it will have R(min) = 12.7 +/- 5.7, R(max) = 176.7 +/- 61.8, and aa(min) = 21.0 +/- 5.0 (at the 95-percent level of confidence), suggesting that cycle 23 will have R(min) greater than 7.0, R(max) greater than 114.9, and aa(min) greater than 16.0 (at the 97.5-percent level of confidence). Such values imply that cycle 23 will be larger than average in size and, consequently (by the Waidmeier effect), will be a fast riser. We also infer from the R(max) and aa(min) records the existence of an even- odd cycle effect, one in which the odd-following cycle is numerically larger in value than the even-leading cycle. For cycle 23, the even-odd cycle effect suggests that R(max) greater than 157.6 and aa(min) greater than 19.0, values that were recorded for cycle 22, the even-leading cycle of the current even-odd cycle pair (cycles 22 and 23). For 1995, the annual average of the aa index measured about 22, while for sunspot number, it was about 18. Because aa(min) usually lags R(min) by 1 year (true for 8 of 11 cycles) and 1996 seems destined to be the year of R(min) for cycle 23, it may be that aa(min) will occur in 1997, although it could occur in 1996 in conjunction with R(min) (true for 3 of 11 cycles). Because of this ambiguity in determining aa(min), no formal prediction based on the correlation of R(max) against aa(min), having r = 0.90, or of R(max) against the combined effects of R(min) and aa(min)-the bivariate technique-having r = 0.99, is possible until 1997, at the earliest.

Wilson, Robert M.↗
DOE OSTI2023

Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3

We report on the population properties of compact binary mergers inferred from gravitational-wave observations of these systems during the first three LIGO-Virgo observing runs. The Gravitational-Wave Transient Catalog 3 (GWTC-3) contains signals consistent with three classes of binary mergers: binary black hole, binary neutron star, and neutron star–black hole mergers. We infer the binary neutron star merger rate to be between 10 and 1700 Gpc − 3 yr − 1 and the neutron star–black hole merger rate to be between 7.8 and 140 Gpc − 3 yr − 1 , assuming a constant rate density in the comoving frame and taking the union of 90% credible intervals for methods used in this work. We infer the binary black hole merger rate, allowing for evolution with redshift, to be between 17.9 and 44 Gpc − 3 yr − 1 at a fiducial redshift ( z = 0.2 ). The rate of binary black hole mergers is observed to increase with redshift at a rate proportional to ( 1 + z ) κ with κ = 2. 9 − 1.8 + 1.7 for z ≲ 1 . Using both binary neutron star and neutron star–black hole binaries, we obtain a broad, relatively flat neutron star mass distribution extending from 1.2 − 0.2 + 0.1 to 2.0 − 0.3 + 0.3 M ⊙ . We confidently determine that the merger rate as a function of mass sharply declines after the expected maximum neutron star mass, but cannot yet confirm or rule out the existence of a lower mass gap between neutron stars and black holes. We also find the binary black hole mass distribution has localized over- and underdensities relative to a power-law distribution, with peaks emerging at chirp masses of 8.3 − 0.5 + 0.3 and 27.9 − 1.8 + 1.9 M ⊙ . While we continue to find that the mass distribution of a binary’s more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above approximately 60 M ⊙ , which would indicate the presence of a upper mass gap. Observed black hole spins are small, with half of spin magnitudes below χ i ≈ 0.25 . While the majority of spins are preferentially aligned with the orbital angular momentum, we infer evidence of antialigned spins among the binary population. We observe an increase in spin magnitude for systems with more unequal-mass ratio. We also observe evidence of misalignment of spins relative to the orbital angular momentum. Published by the American Physical Society 2023

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Utah FORGE: Well 16B(78)-32 Drill Core Fracture Analysis Images and Data

This dataset contains drilling core data from well 16B(78)-32, including PDF documents with flattened core images annotated by feature type and core interval, as well as spreadsheets detailing feature morphologies by depth, planar feature measurements, and planar feature orientations rotated to in situ conditions. Core was recovered from three intervals, one per stimulation stage, in the crystalline rocks affected by the stimulation of well 16A(78)-32. Seven core runs were conducted, yielding 135.8 feet of recovered core. Features in the core were categorized into planar fractures, semi-planar fractures, unbroken mineralized fractures, rough fractures, curviplanar fractures, concave-convex surfaces, and planar compositional features such as mylonite or dike-like structures. Planar features were measured while the core was positioned horizontally, with the core axis aligned to a downhole azimuth of 42 degrees. Planar core measurements from stimulations 2 and 3 that could be confidently correlated with FMI data were rotated to in situ orientations. This was done by rotating the planes along vertical and horizontal axes to match the azimuth and inclination data recorded in the directional survey of well 16B(78)-32, as well as applying an axial rotation to resemble the fracture orientations observed in the FMI log at corresponding depths. Coherent sets of planar fracture measurements were made by aligning the core within each 3-foot section of the dissected core barrel, and between adjacent 3-foot sections within a core run by matching rock fabrics, saw cuts and/or tool marks. Where coherent fracture measurements could not be made within a core run, data sets are denoted by a subscript (i.e. 2-Ta and 2-Tb both come from tangent core run number 2).

15 GEOTHERMAL ENERGY↗
NASA NTRS1995

Gamma-Ray Burst Precursor Activity as Observed with BATSE

Gamma-ray burst time histories often consist of multiple episodes of emission with the count rate dropping to the background level between adjacent episodes. We define precursor activity as any case in which the first episode (referred to as the precursor episode) has a lower peak intensity than that of the remaining emission (referred to as the main episode) and is separated from the remaining burst emission by a background interval that is at least as long as the remaining emission. We find that approx. 3% of the bursts observed with the Burst and Transient Source Experiment (BATSE) on Compton Gamma Ray Observatory (CGRO) satisfy this definition. We present the results of a study of the properties of these events. The spatial distribution of these sources is consistent with that of the larger set of all BATSE gamma-ray bursts: inhomogeneous and isotropic. A correlation between the duration of the precursor emission and the duration of the main episode emission is observed at about the 3 sigma confidence level. We find no meaningful significant correlations between or among any of the other characteristics of the precursor or main episode emission. It appears that the characteristics of the main episode emission are independent of the existence of the precursor emission.

Koshut, Thomas M.↗
NASA NTRS1996

Observations of the Solar Irradiance in the 200-350 nm Interval During the ATLAS-1 Mission: A Comparison Among Three Sets of Measurements-SSBUV, SOLSPEC and SUSIM

The SOLSPEC, SSBUV, and SUSIM spectrometers simultaneously observed the solar spectral irradiance during the ATLAS-1 mission flown on board the Space Shuttle Atlantis in March 1992. The three instruments use different methods and means of absolute calibration and were each calibrated preflight and postflight. The three data sets are reported from 200 to 350 nm at 1.1 nm resolution. The method of comparing the three independent data sets is discussed. The importance of a common, precise wavelength scale is shown when comparing the data in wavelength regions of strong Fraunhofer lines. The agreement among the solar irradiance measurements is better than plus or minus 5%. The fact that the calibrations of the three instruments were based on three independent standards provides confidence that the absolute solar spectral irradiance in the range 200-350 nm is now known with an accuracy better than plus or minus 5%. The mean ATLAS-I solar spectrum is compared with simultaneous solar observations from the UARS SOLSTICE and UARS SUSIM instruments. The two mean solar spectra agree to within plus or minus 3%.

Cebula, R. P.↗
NASA NTRS1983

The relative abundances of Sn, Te, Xe, Ba and Ce

Elements with even atomic number (Z) in the interval 50 or = Z or = 58 were resolved in the cosmic radiation using the Heavy Nuclei Experiment on the HEAO-3 satellite. Their relative abundances were compared with the results expected from pure r-process material, pure s-process material, and solar system material, both with and without a modification due to possible first ionization potential effects. Such effects may be the result of the preferential acceleration, and hence enhancement in the cosmic rays, of those elements having low first ionization potentials. Measurements were found to be inconsistent with pure r-process material at the greater than 98% confidence level whether or not the first ionization potential adjustments are made.

Krombel, K. E.↗
NASA NTRS1995

Block distributions on the lunar surface: A comparison between measurements obtained from surface and orbital photography

Among the hazards that must be negotiated by lunar-landing spacecraft are blocks on the surface of the Moon. Unfortunately, few data exist that can be used to evaluate the threat posed by such blocks to landing spacecraft. Perhaps the best information is that obtained from Surveyor photographs, but those data do not extend to the dimensions of the large blocks that would pose the greatest hazards. Block distributions in the vicinities of the Surveyor 1, 3, 6, and 7 sites have been determined from Lunar Orbiter photography and are presented here. Only large (i.e., greater than or equal to 2.5 m) blocks are measurable in these pictures, resulting in a size gap between the Surveyor and Lunar Orbiter distributions. Nevertheless, the orbital data are self-consistent, a claim supported by the similarity in behavior between the subsets of data from the Surveyor 1, 3, and 6 sites and by the good agreement in position (if not slopes) between the data obtained from the Surveyor 3 photography and those derived from the Lunar Orbiter photographs. Confidence in the results is also justified by the well-behaved distribution of large blocks at the surveyor site. Comparisons between the Surveyor distributions and those derived from the orbital photography permit these observations: (1) in all cases but that for Surveyor 3, the density of large blocks is overestimated by extrapolation of the Surveyor-derived trends; (2) the slopes of the Surveyor-derived distributions are consistently lower than those determined for the large blocks; and (3) these apparent disagreements could be mitigated if the overall shapes of the cumulative lunar block populations were nonlinear, allowing for different slopes over different size intervals. The relatively large gaps between the Surveyor-derived and Orbiter-derived data sets, however, do not permit a determination of those shapes.

Cintala, Mark J.↗
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↗
NASA NTRS1994

Redshift data and statistical inference

Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.

Newman, William I.↗
DOE OSTI2024

Search for photons above 10 18 eV by simultaneously measuring the atmospheric depth and the muon content of air showers at the Pierre Auger Observatory

The Pierre Auger Observatory is the most sensitive instrument to detect photons with energies above 1 0 17 eV . It measures extensive air showers generated by ultrahigh energy cosmic rays using a hybrid technique that exploits the combination of a fluorescence detector with a ground array of particle detectors. The signatures of a photon-induced air shower are a larger atmospheric depth of the shower maximum ( X max ) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced cascades. In this work, a new analysis technique in the energy interval between 1 and 30 EeV ( 1 EeV = 1 0 18 eV ) has been developed by combining the fluorescence detector-based measurement of X max with the specific features of the surface detector signal through a parameter related to the air shower muon content, derived from the universality of the air shower development. No evidence of a statistically significant signal due to photon primaries was found using data collected in about 12 years of operation. Thus, upper bounds to the integral photon flux have been set using a detailed calculation of the detector exposure, in combination with a data-driven background estimation. The derived 95% confidence level upper limits are 0.0403, 0.01113, 0.0035, 0.0023, and 0.0021 km − 2 sr − 1 yr − 1 above 1, 2, 3, 5, and 10 EeV, respectively, leading to the most stringent upper limits on the photon flux in the EeV range. Compared with past results, the upper limits were improved by about 40% for the lowest energy threshold and by a factor 3 above 3 EeV, where no candidates were found and the expected background is negligible. The presented limits can be used to probe the assumptions on chemical composition of ultrahigh energy cosmic rays and allow for the constraint of the mass and lifetime phase space of super-heavy dark matter particles. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Flight service evaluation of composite helicopter components

This paper presents the results of a NASA funded contract and Sikorsky research and development programs to evaluate structural composite components in flight service on Sikorsky Model S-76 helicopters. Selected components were removed and tested at prescribed intervals over a nine year time frame. Four horizontal stabilizers and thirteen tail rotor spars were returned from commercial service in West Palm Beach, Florida and in the Gulf Coast region of Louisiana to determine the long term effects of operations in hot and humid climates on component performance. Concurrent with the flight component evaluation, panels of materials used in their fabrication were exposed to the environment in ground racks. Selected panels were tested annually to determine the effects of exposure on physical and mechanical properties. The results of 55,741 component flight hours and 911 months of field exposure are reported and compared with initial Federal Aviation Administration (FAA) certification data. The findings of this program have provided increased confidence in the long term durability of advanced composite materials used in helicopter structural applications.

Mardoian, George H.↗
NASA NTRS1997

A Sequence of Outbursts from the Transient X-Ray Pulsar GS 0834-430

GS 0834-430, a 12.3 s accretion-powered pulsar, has been observed in seven outbursts with the BATSE large-area detectors on the Compton Gamma Ray Observatory. The first five outbursts observed by BATSE occurred at intervals of about 107 days, while the final two outbursts were separated by about 140 days. The photon energy spectrum, measured by Earth occultation in the 20 100 keV band, can be fitted by a power law with photon index alpha approximately equals -3.7 or by an exponential spectrum with temperature kT approximately equals 15 keV, with some variations within outbursts. The source has a low pulse fraction, less than or equal to 0.15 in the 20-50 keV band. We have observed significant temporal and energy-dependent variations in epoch folded pulse profiles. Because the intrinsic torque effects for this system are at least comparable to orbital effects, pulse timing analysis did not produce a unique orbital solution. However, confidence regions for the orbital elements yielded the following 1 sigma limits: orbital period P(sub orb) = 105.8 +/- 0.4 days and eccentricity 0.10 less than or approximately equals epsilon less than or approximately equals 0.17. GS 0834-430 is most likely a Be/X-ray binary.

Wilson, Colleen A.↗
NASA NTRS2013

Multitemporal Snow Cover Mapping in Mountainous Terrain for Landsat Climate Data Record Development

A multitemporal method to map snow cover in mountainous terrain is proposed to guide Landsat climate data record (CDR) development. The Landsat image archive including MSS, TM, and ETM+ imagery was used to construct a prototype Landsat snow cover CDR for the interior northwestern United States. Landsat snow cover CDRs are designed to capture snow-covered area (SCA) variability at discrete bi-monthly intervals that correspond to ground-based snow telemetry (SNOTEL) snow-water-equivalent (SWE) measurements. The June 1 bi-monthly interval was selected for initial CDR development, and was based on peak snowmelt timing for this mountainous region. Fifty-four Landsat images from 1975 to 2011 were preprocessed that included image registration, top-of-the-atmosphere (TOA) reflectance conversion, cloud and shadow masking, and topographic normalization. Snow covered pixels were retrieved using the normalized difference snow index (NDSI) and unsupervised classification, and pixels having greater (less) than 50% snow cover were classified presence (absence). A normalized SCA equation was derived to independently estimate SCA given missing image coverage and cloud-shadow contamination. Relative frequency maps of missing pixels were assembled to assess whether systematic biases were embedded within this Landsat CDR. Our results suggest that it is possible to confidently estimate historical bi-monthly SCA from partially cloudy Landsat images. This multitemporal method is intended to guide Landsat CDR development for freshwaterscarce regions of the western US to monitor climate-driven changes in mountain snowpack extent.

Landsat↗