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At least 343 records · Page 19

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NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗

NASA NTRS2023

Assessment of the Performance of the Atmospheric Correction Algorithm MAJA for Sentinel-2 Surface Reflectance Estimates

The correction of atmospheric effects on optical remote sensing products is an essential component of Analysis Ready Data (ARD) production lines. The MAJA processor aims at providing accurate time series of surface reflectances over land for satellite missions, such as Sentinel-2, Venμs, and Landsat 8. The Centre d’Études Spatiales de la Biosphère (CESBIO) and the Centre National d’Études Spatiales (CNES) share a common effort to maintain, validate, and improve the MAJA processor, using state-of-the-art ground measurement sites, and participating in processor inter-comparisons, such as the Atmospheric Correction Intercomparison Exercise (ACIX). While contributing to the second ACIX-II Land validation exercise, it was found that the candidate MAJA dataset could not adequately be compared to the main reference dataset. MAJA reflectances were corrected for adjacency and topography effects while the reference dataset was not, excluding MAJA from a part of the performance metrics of the exercise. The first part of the following study aims at providing complementary performance assessment to ACIX-II by reprocessing MAJA surface reflectances without adjacency nor topographic correction, allowing for an un-biased full resolution comparison with the reference Sentinel-2 dataset. The second part of the study consists of validating MAJA against surface reflectance measurements time series of up to five years acquired at three automated stations. Both approaches provide extensive insights on the quality of MAJA Sentinel-2 Level 2 products.

ROSAS↗

NASA NTRS1996

(abstract) Role of Long Equatorial Wave Reflection in the Low-Frequency Variability Observed During the TOPEX/POSEIDON Period: Data Analysis and Coupled Model Study

The analysis of TOPEX/POSEIDON sea level and ERS-1 zonal wind stress data gives evidence that first mode meridonal long Rossby waves fully reflected into Kelvin waves at the equatorial western Pacific boundary at different periods including the January-June 1994 period. The evolution of the conditions (zonal wind stress, sea surface temperature and sea level anomalies) in the central Pacific suggests that this reflection may have played a role in the reversal of cold to warm anomalies observed in the central Pacific in June-July 1994. To investigate the actual role of reflected Kelvin waves observed by TOPEX/POSEIDON, a simple ocean-atmosphere coupled model is designed. Starting from these initial conditions, several simulations are run for testing the role western bundary reflection evidenced in TOPEX/POSEIDON data. Coupled mechanisms are suggested to explain the low-frequency variability observed during this period.

Rossby waves Kelvin waves zonal wind stress TOPEX/↗

NASA NTRS2005

Voltage-induced broad-spectrum reflectivity change with surface-plasmon waves

Voltage-induced broad-spectrum reflectivity change with surface-plasmon waves is reported. When white light is incident at a metal/electro-optical material interface, surface-plasmon waves can be excited under phase match conditions. This surface-plasmon resonance depends on the dielectric constants of both the metal and the electro-optical material. Photons in the surface-plasmon resonance wavelength range are absorbed by the interface. Since metals have large imaginary parts of their dielectric constants, the surface-plasmon resonances are broad and may cover all visible wavelengths. Applying voltage to the electro-optical material to change its dielectric constant can result in a change in the reflectivity at the interface. Experimental results showed a reflectivity change from almost 0% to about 40% under an applied voltage using a liquid-crystal and nickel film structure, and the results had good agreement with theoretical calculations. The theoretical calculations also predicted a 90% reflectivity recovery by exciting surface-plasmon waves at a Rh-Al/electro-optical material interface. These results demonstrate that a high efficiency white light modulator can be built using surface-plasmon excitations.

white light modulator↗

NASA NTRS2011

Daytime Water Detection Based on Sky Reflections

Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide-open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies. One of the properties of water useful for detecting it is that its surface acts as a horizontal mirror at large incidence angles. Water bodies can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. The Jet Propulsion Laboratory (JPL) has implemented a water detector based on sky reflections that geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground and predicts if the ground pixel is water based on color similarity and local terrain features. This software detects water bodies in wide-open areas on cross-country terrain at mid- to far-range using imagery acquired from a forward-looking stereo pair of color cameras mounted on a terrestrial UGV. In three test sequences approaching a pond under a clear, overcast, and cloudy sky, the true positive detection rate was 100% when the UGV was beyond 7 meters of the water's leading edge and the largest false positive detection rate was 0.58%. The sky reflection based water detector has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA, USA.

sky reflections↗

NASA NTRS2014

Validation of the Two-Layer Model for Correcting Clear Sky Reflectance Near Clouds

A two-layer model was developed in our earlier studies to estimate the clear sky reflectance enhancement near clouds. This simple model accounts for the radiative interaction between boundary layer clouds and molecular layer above, the major contribution to the reflectance enhancement near clouds for short wavelengths. We use LES/SHDOM simulated 3D radiation fields to valid the two-layer model for reflectance enhancement at 0.47 micrometer. We find: (a) The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; and (b) The magnitude of the 2-layer modeled enhancement agree reasonably well with the "truth" with some expected underestimation. We further extend our model to include cloud-surface interaction using the Poisson model for broken clouds. We found that including cloud-surface interaction improves the correction, though it can introduced some over corrections for large cloud albedo, large cloud optical depth, large cloud fraction, large cloud aspect ratio. This over correction can be reduced by excluding scenes (10 km x 10km) with large cloud fraction for which the Poisson model is not designed for. Further research is underway to account for the contribution of cloud-aerosol radiative interaction to the enhancement.

two-layer model↗

NASA NTRS2014

Early Evaluation of the VIIRS Calibration, Cloud Mask and Surface Reflectance Earth Data Records

Surface reflectance is one of the key products fromVIIRS and as withMODIS, is used in developing several higherorder land products. The VIIRS Surface Reflectance (SR) Intermediate Product (IP) is based on the heritageMODIS Collection 5 product (Vermote, El Saleous, & Justice, 2002). The quality and character of surface reflectance depend on the accuracy of the VIIRS Cloud Mask (VCM), the aerosol algorithms and the adequate calibration of the sensor. The focus of this paper is the early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system, the Interface Data Processing System (IDPS). After a brief introduction, the paper presents the calibration performance and the role of the surface reflectance in calibration monitoring. The analysis of the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions) shows typical problems over bright surfaces and high elevation sites. Also discussed is the performance of the aerosol input used in the atmospheric correction and in particular the artifacts generated by the use of the Navy Aerosol Analysis and Prediction System. Early quantitative results of the performance of the SR product over the AERONET sites showthatwith the fewadjustments recommended, the accuracy iswithin the threshold specifications. The analysis of the adequacy of the SR product (Land PEATE adjusted version) in applications of societal benefits is then presented. We conclude with a set of recommendations to ensure consistency and continuity of the JPSS mission with the MODIS Land Climate Data Record.

Surface reflectance↗

NASA NTRS2015

High Ice Water Content at Low Radar Reflectivity near Deep Convection: Consistency of In Situ and Remote-Sensing Observations with Stratiform Rain Column Simulations - Part I

Occurrences of jet engine power loss and damage have been associated with flight through fully glaciated deep convection at -10 to -50 degrees Centigrade. Power loss events commonly occur during flight through radar reflectivity (Zeta (sub e)) less than 20-30 decibels relative to Zeta (dBZ - radar returns) and no more than moderate turbulence, often overlying moderate to heavy rain near the surface. During 2010-2012, Airbus carried out flight tests seeking to characterize the highest ice water content (IWC) in such low-radar-reflectivity regions of large, cold-topped storm systems in the vicinity of Cayenne, Darwin, and Santiago. Within the highest IWC regions encountered, at typical sampling elevations (circa 11 kilometers), the measured ice size distributions exhibit a notably narrow concentration of mass over area-equivalent diameters of 100-500 micrometers. Given substantial and poorly quantified measurement uncertainties, here we evaluate the consistency of the Airbus in situ measurements with ground-based profiling radar observations obtained under quasi-steady, heavy stratiform rain conditions in one of the Airbus-sampled locations. We find that profiler-observed radar reflectivities and mean Doppler velocities at Airbus sampling temperatures are generally consistent with those calculated from in situ size-distribution measurements. We also find that column simulations using the in situ size distributions as an upper boundary condition are generally consistent with observed profiles of radar reflectivity (Ze), mean Doppler velocity (MDV), and retrieved rain rate. The results of these consistency checks motivate an examination of the microphysical pathways that could be responsible for the observed size-distribution features in Ackerman et al. (2015).

Rain↗

NASA NTRS2015

OSOAA: A Vector Radiative Transfer Model of Coupled Atmosphere-Ocean System for a Rough Sea Surface Application to the Estimates of the Directional Variations of the Water Leaving Reflectance to Better Process Multi-angular Satellite Sensors Data Over the Ocean

In this study, we present a radiative transfer model, so-called OSOAA, that is able to predict the radiance and degree of polarization within the coupled atmosphere-ocean system in the presence of a rough sea surface. The OSOAA model solves the radiative transfer equation using the successive orders of scattering method. Comparisons with another operational radiative transfer model showed a satisfactory agreement within 0.8%. The OSOAA model has been designed with a graphical user interface to make it user friendly for the community. The radiance and degree of polarization are provided at any level, from the top of atmosphere to the ocean bottom. An application of the OSOAA model is carried out to quantify the directional variations of the water leaving reflectance and degree of polarization for phytoplankton and mineral-like dominated waters. The difference between the water leaving reflectance at a given geometry and that obtained for the nadir direction could reach 40%, thus questioning the Lambertian assumption of the sea surface that is used by inverse satellite algorithms dedicated to multi-angular sensors. It is shown as well that the directional features of the water leaving reflectance are weakly dependent on wind speed. The quantification of the directional variations of the water leaving reflectance obtained in this study should help to correctly exploit the satellite data that will be acquired by the current or forthcoming multi-angular satellite sensors.

Ocean surface↗

NASA NTRS2017

A Framework for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method.

The so-called bi-spectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

reflectance↗

NASA NTRS2017

Assessment of Satellite-Derived Surface Reflectances by NASA's CAR Airborne Radiometer over Railroad Valley, Nevada

CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada (38.504 deg N, 115.692 deg W).The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CARs land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol effects in the EO derived reflectances.

calibration↗

NASA NTRS2018

The Harmonized Landsat and Sentinel-2 Surface Reflectance Data Set

The Harmonized Landsat and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a VirtualConstellation (VC) of surface reflectance (SR) data acquired by the Operational Land Imager (OLI) and MultiSpectral Instrument (MSI) aboard Landsat 8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, bidirectional reflectance distribution function normalization and spectral bandpass adjustment. Three products are derivedfrom the HLS processing chain: (i) S10: full resolution MSI SR at 10 m, 20 m and 60 m spatial resolutions; (ii)S30: a 30 m MSI Nadir BRDF (Bidirectional Reflectance Distribution Function)-Adjusted Reflectance (NBAR);(iii) L30: a 30 m OLI NBAR. All three products are processed for every Level-1 input products from Landsat 8/OLI (L1T) and Sentinel-2/MSI (L1C). As of version 1.3, the HLS data set covers 10.35 million km2 and spans from first Landsat 8 data (2013); Sentinel-2 data spans from October 2015. The L30 and S30 show a good consistency with coarse spatial resolution products, in particular MODIS Collection 6 MCD09CMG products (overall deviations do not exceed 11%) that are used as a reference for quality assurance. The spatial co-registration of the HLS is improved compared to original Landsat 8 L1T and Sentinel 2A L1C products, for which misregistration issues between multi-temporal data are known. In particular, the resulting computed circular errors at 90% for the HLS product are 6.2 m and 18.8 m, for S10 and L30 products, respectively. The main known issue of the current data set remains the Sentinel-2 cloud mask with many cloud detection omissions. The cross-comparison with MODIS was used to flag products with most evident non-detected clouds. A time series outlier filtering approach is suggested to detect remaining clouds. Finally, several time series are presented to highlight the high potential of the HLS data set for crop monitoring.

Landsat Sentinel-2↗

NASA NTRS2018

Directional Reflectance Studies in Support of the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley

The Radiometric Calibration Test Site (RadCaTS) is a suite of commercial and custom instruments used to make measurements of the surface reflectance and atmosphere throughout the day at Railroad Valley, Nevada. It was developed in response to the need for daily radiometric calibration data for the vast array of Earth-observing sensors on orbit, which is continuously increasing as more nations and private companies launch individual environmental satellites as well as large constellations. The current suite of instruments at RadCaTS includes five ground-viewing radiometers (GVRs), four of which view the surface in a nadir-viewing configuration. Many sensors such as those on Landsat-7 and Landsat-8 view Railroad Valley within 3° of nadir, while others such as those on Sentinel-2A and -2B, RapidEye, Aqua, Suomi NPP, and Terra can view Railroad Valley at off-nadir angles. Past efforts have shown that the surface bidirectional reflectance distribution function (BRDF) has minimal impact on vicarious calibration uncertainties for views <10°, but the desire to use larger view angles has prompted the effort to develop a BRDF correction for data from RadCaTS. The current work investigates the application of Railroad Valley BRDF data derived from a BRF camera developed at the University of Arizona in the 1990s (but is no longer in use) to the current RadCaTS surface reflectance measurements. Also investigated are early results from directional reflectance studies using a mobile spectro-goniometer system during a round-robin field campaign in 2018. This work describes the preliminary results, the effects on current measurements, and the approach for future measurements.

RadCalNet↗

NASA NTRSDate not supplied

Reduction of Spectral Radiance Reflectance During the Annular Solar Eclipse of 21 June 2020 from DSCOVR/EPIC

We have analyzed three EPIC images during the annular solar eclipse on June 21, 2020 when centers of the eclipse were in the Arabian Peninsula (mostly desert), the Himalayas (mostly barren land), and China (mostly cloudy over vegetation) and compared with two images for 2017 American solar eclipse over Casper, WY and Columbia, MO (vegetated surface for both). We found that the global average reductions of spectral reflectance for the three images during 2020 solar eclipse are quite different while the reductions of spectral reflectance for the two images for 2017 solar eclipse are similar. Radiative transfer model simulations suggest that different surface spectral albedo and cloud fraction attribute to the different reduction of spectral reflectance for three images during 2020 eclipse while similar spectral albedo of vegetated surface around Casper and Columbia are the main cause for the similar spectral reflectance reduction for the two images during 2017 solar eclipse.

solar eclipse↗

NASA NTRSDate not supplied

Using the Diurnal Variability in GeoNEX TOA Reflectances for Earth Monitoring

Observations from the third-generation geostationary satellite instruments (GOES 16/17 ABI, Himawari 8/9 AHI, and etc.) have spatial resolution and spectral band configurations comparable to flagship LEO sensors (e.g., MODIS/VIIRS). More importantly, these data are acquired at very high temporal resolution, faithfully recording the variations of the full disk of Earth at every 5-10 minutes. They thus provide unique information about Earth’s atmosphere and surface. In order to explore the unique information content of geostationary data, this study systematically analyzes the diurnal variability in the GeoNEX L1G TOA reflectance products and compares them to simulated results by state-of-the-art radiative transfer codes. Our results show that • The smoothness of the TOA reflectance diurnal cycle provides a convenient and reliable way to identify stable atmospheric conditions and filter out passing clouds/shadows. • The diurnal variability of the blue band (0.47µm) reflectance is regulated mainly by atmospheric optical conditions over a majority of land cover types. As such, the diurnal variability of the blue band data allows us to retrieve AOD without invoking the use of spectral band ratios (SRC) as in previous algorithms. • In comparison, the diurnal variability of the short-wave infrared band (2.2µm) BRFs is mainly regulated by surface reflectance and the sun-target-satellite geometry. This information allows us to test and, if suitable, retrieve surface BRDF parameters. • Spectral band ratios, especially those between the 2.2µm and 0.47µm bands, are not constant but vary by locations and sun-target-satellite geometries. Our analysis clearly demonstrates that the information provided in high-frequent geostationary observations is unique and complementary to LEO sensors. Therefore, a synergy of GEO and LEO (and other) sensors has the great potential to improve existing remote sensing models and algorithms for better Earth monitoring.

Diurnal Variability↗

DOE OSTI2025

All the light we cannot see: Climate manipulations leave short and long‐term imprints in spectral reflectance of trees

Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change.

Stefanski, Artur [Department of Forest Resources U↗

DOE OSTI2026

Improvements in Mirror Surface Measurement with Reflected Computer Vision Targets

Over the last several years, NREL has been developing a system to measure large optical surfaces of heliostat mirrors by reflecting computer vision targets. An advantage of this system, called Reflected Target Nonintrusive Assessment (ReTNA), is that it lends itself well to stitching together many images, each reflecting only part of a larger heliostat. In the last few months, this was taken to a new extreme, with a small target (<5m2) being used to measure a >25m2 long focal length heliostat. These measurements were compared with traditional fringe deflectometry methods, which require a >50m2 target, and photogrammetry. The strengths, weaknesses and limitations of ReTNA are discussed. An estimated uncertainty in this new measurement is presented, along with software improvements and a new wireless data collection system. A bill of materials for this measurement system is presented, which has been designed to use all low-cost, off-the-shelf components. Finally, the next steps for future ReTNA development are presented. Overall, ReTNA can be a valuable optics measurement system, complimentary to existing measurement techniques available for large reflective surfaces.

14 SOLAR ENERGY↗

NASA NTRS1972

Reflectance of evaporated rhenium and tungsten films in the vacuum ultraviolet from 300 to 2000 A.

Discussion of the dependence of the reflectance of Re and W on the substrate temperature during deposition, film thickness, and aging during exposure to air. Re and W of 99.99% purity were evaporated with a 6-kW fine-focused electron gun and deposited on glass and fused quartz plates of various temperatures ranging from 40 to 500 C. With Re, films of highest reflectance were obtained by evaporation onto unheated substrates, whereas with W, heating of the substrate greatly increased the reflectance of the deposited films. For both metals, the reflectance losses during extended exposure to air remained rather small, indicating that the oxide films formed on both film materials at room temperature were very thin.

Cox, J. T.↗