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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2019

Architecture and Dynamics of Kepler's Multi-Transiting Planet Systems.III. Comprehensive Investigation Using All Four Years of Kepler Mission Data

We study the orbital architectures of planetary systems orbiting within ∼1 AU of their stars by analyzing the ensemble of Kepler systems having two or more planet candidates. We use data from the entire Kepler mission, and in many cases we apply improved analysis techniques (e.g., replacing histograms by top-hat Kernel Density Estimators that avoid the loss of information resulting from choosing a particular phase for the bin boundaries) to extend and enhance the studies of Lissauer et al. (2011, ApJS 197, 8) and Fabrycky et al. (2014, ApJ 790, 146).These data show ~ 1700 transiting planet candidates in > 600 multiple-planet systems, far more than were available for our previous two studies. The increased numbers and better information about planetary radii and the properties of stellar hosts made possible by Gaia DR2 allow more statistically-robust analyses of the entire ensemble of Kepler multis as well as independent analyses of subsets of the population. We are thus able to contrast the dynamical configurations of small and large planets, short-period and longer-period planets, and planets orbiting various types of host stars. We reinforce our previous findings that most pairs of planets within the same system are neither in nor near low-order mean motion resonances and that there is a substantial excess of planets having period ratios slightly larger than those of first-order mean-motion resonances. However, neglecting three systems whose planets are locked in 3- body resonances and summing over all first-order mean motion resonances, the deficit of planet pairs with period ratios just narrow of resonance is as large as the excess of planets wide of resonance (within statistical uncertainties), suggesting that overall there is no overall excess of planet pairs in the vicinity of resonance. Other aspects of our study, including estimates of the typical relative inclinations of planetary orbits and their variations as functions of orbital period, planet sizes and stellar properties, are in progress, with results expected to be available for presentation by the time of the conference.

Lissauer, Jack↗
NASA NTRS2019

A New Look at Aubrites: Investigating 3D Modal Mineralogy with X-Ray Computed Tomography

The aubrites (approximately 30 known meteorites) are a unique group of differentiated meteorites that formed on asteroids with oxygen fugacities (ƒO2) from approximately 2 to approximately 6 log units below the iron-wustite buffer. At these highly reduced conditions, elements deviate from the geochemical behavior exhibited at terrestrial ƒO2, forming FeO-poor silicates and exotic sulfides. While previous studies have described the petrology and 2D modal abundances of aubrites, this work investigates the 3D modal mineralogies of silicate, metal, and sulfide phases in aubrite samples, which are then compared to the available 2D data. In addition to 3D modal mineralogies, we have examined the geochemistry of fourteen aubrites, including mineral major-element compositions, bulk-rock compositions, and oxygen isotopic compositions to understand their formation and evolution at extreme ƒO2 conditions. We utilize X-ray computed tomography (XCT) to non-destructively analyze the distribution and abundances of mineral phases in aubrites and locate composite clasts of sulfide grains for future analytical study. In order to better constrain elemental behavior under reduced conditions, we specifically target minerals phases that comprise moderately volatile elements (i.e. oldhamite [CaS], caswellsilverite [NaCrS2] and djerfisherite [K6Na(Fe,Cu,Ni)25S26Cl]) as it has been shown that their geochemical behavior changes as a function of ƒO2. Currently, we have produced 3D scans of the Norton County aubrite. The results of the XCT data have allowed for the determination of the abundances of silicate groundmass (i.e., enstatite, forsterite, albite, and diopside), light (based on electron density) sulfides (i.e. alabandite [MnS] and daubréelite [FeCr2S4]), heavy (based on electron density) sulfides (i.e., troilite [FeS]), and Fe,Ni metal by segmenting a density histogram in Volume Graphics Studio software. XCT scans of additional aubrites are underway. By combining the 3D representation of the exotic phases found in aubrites with existing 2D characterizations, we are able to better determine modal abundances. By integrating 3D and 2D modal abundances and geochemistry, we can ultimately better constrain aubrite petrogenesis and elemental partitioning under reduced conditions. Furthermore, application of this new 3D approach offers the opportunity to identify and select clasts for future study prior to cutting the sample, which will minimize sample loss of this precious material.

Wilbur, Zoe↗
NASA NTRS2019

A Qualitative Review of Selected Infrared Flow Visualization Processing Techniques: Contrast Enhancement and Frequency Domain Analysis

The deployment and integration of high-sensitivity infrared cameras in a transonic wind tunnel test environment has resulted in a unique capability to image aerodynamic phenomena in real-time. Multi-camera infrared flow visualization data systems are now routinely utilized at the NASA Ames Unitary Plan Wind Tunnel. The small flow-induced temperature gradients on the surface of the wind tunnel test article coupled with the high bit-depth of the infrared camera sensor makes the processing of the image data critically important. An image processing routine must enhance features of interest with minimal artifacts. Additionally, the production wind tunnel test environment demands that these processed images are made available in a real-time, automatic fashion. Therefore, any image processing routine must be computationally economical and enhance the image data with minimal input from a human operator. The following seeks to qualitatively explore selected image processing techniques by assessing their effectiveness to resolve flow features on a wind tunnel test article. A multi-scale contrast enhancement technique is introduced as well as a new implementation of a multi-scale, non-interpolated adaptive histogram equalization. Finally, a novel method is introduced that demonstrates the ability to resolve flow features imaged on bare-steel test articles possessing low emissivity. This method merges frequency domain analysis with contrast enhancement and has the potential to extend the application of infrared flow-visualization within the wind tunnel test environment.

Infrared Imaging↗
NASA NTRS2017

Interactive Visualization of High-Dimensional Petascale Ocean Data

We describe an application for interactive visualization of 5 petabytes of time-varying multivariate data from a high-resolution global ocean circulation model. The input data are 10311 hourly (ocean time) time steps of various 2D and 3D fields from a 22-billion point 1/48- degree “lat-lon cap” configuration of the MIT General Circulation Model (MITgcm). We map the global horizontal model domain onto our 128-screen (8x16) tiled display wall to produce a canonical tiling with approximately one MITgcm grid point per display pixel, and using this tiling we encode the entire time series for multiple native and computed scalar quantities at a collection of ocean depths. We reduce disk bandwidth requirements by converting the model’s floating point data to 16-bit fixed point values, and compressing those values with a lossless video encoder, which together allow synchronized playback at 24 time steps per second across all 128 displays. The application allows dynamic assignment of any two encoded tiles to any display, and has multiple interfaces for quickly specifying various orderly arrangements of tiles. All subsequent rendering is done on the fly, with run time control of colormaps, transfer functions, histogram equalization, and labeling. The two data streams on each screen can be rendered independently and combined in various ways, including blending, differencing, horizontal/ vertical wipes, and checkerboarding. The two data streams on any screen can optionally be displayed as a scatterplot in their joint attribute space. All scatterplots and map-view plots from the same x/y location and depth are linked so they all show the current brushable selection. Ocean scientists have used the system, and have found previously unidentified features in the data.

Interactive↗
NASA NTRS2019

Simulation of AMVs for OSSEs

An algorithm to simulate locations of atmospheric motion vectors (AMVs) for use in observing system simulation experiments (OSSEs) is described and demonstrated. It is intended to obviate likely deficiencies in nature run data [standard meteorological parameters and aerosol tracers] if used to produce images for feature tracking. The algorithm employs probabilistic functions that are tuned based on distributions of real observations and histograms of nature run fields. For distinct observation types, the algorithm produces geographical and vertical distributions, time - mean counts, and typical spacings of simulated locations that are, at least, qualitatively similar to those of real observations and are associated with nature run cloud and water vapor fields. It thus appears suitable for generating realistic atmospheric motion vectors for use in observing system simulation experiments.

Errico, R. M.↗
NASA NTRS2019

IMERG Reaching for 20 Years

The new V06 IMERG is briefly reviewed, then key data visualizations are shown, including the zonal profile of calibration by GPCP, the long-term time series of ocean estimates for the Final Run (with comparison to TMPA and GPCP SG), the time series of tropical ocean rainrate histogram, diurnal cycle, and atoll validation at the monthly time scale.

Huffman, George J.↗
NASA NTRS2016

Low Frequency 1/f Noise on QWIPs, nBn, and Superlattice Focal Plane Array

Noise Equivalent Difference Temperature (NE△T) is a standard performance metric for most infrared focal plane array (FPA) systems. The frequency bandwidth and range associated with NE△T is at high frequency and it does not describe the long time noise behavior or the very low frequency noise of the FPA. Very low frequency noise measurement requires data capture that takes longer time duration and sampling interval. This study investigates low frequency noise in QWIP, nBn and LWIR n-type Complementary Barrier Infrared Detector (CBIRD) FPAs. The corner frequencies are extracted from the power spectral density (PSD) as function of frequency. The peak wavelength, quantum efficiency of QWIP detector are 6.2 µm and 2 %, respectively. QWIP FPA has a mean NE△T ~ 25 mK at an operating temperature of 65 K and an integration time of 16 msec. The mean QWIP PSD plot shows a corner frequency of < 0.5 mHz. The nBn FPA with 4 µm cut off and quantum efficiency of 67 % has NE△T ~ 15.6 mK at an integration time ~ 7.52 msec and an operating temperature of 120 K. The nBn has corner frequency of > 50 mHz. Lastly the n-type CBIRD FPA with a 50% cutoff at 8.8 µm and quantum efficiency of ~ 50 % has an NE△T ~ 18.6 mK at an integration time of 1.86 msec and operating temperature 120 K. The superlattice FPA has a corner frequency ~ 10 mHz. The investigation of the tail on the NE△T histogram reveals that its origin is not accounted for entirely by the high noise current, but also it needs the inclusion of lower responsivity for some pixels.

Pepper, B.↗
NASA NTRS2021

Post-test Inspection of NASA’s Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge Chamber

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014after demonstrating 51,184 hours of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for the discharge chamber as well as other miscellaneous components such as the high-voltage propellant isolators and electrical cabling. Comparison of magnetic field measurements taken during pretest and post-test inspections indicate that the field strength did not degrade, consistent with performance data obtained during the test. Inspection of discharge chamber mesh samples show a deposition coating primarily composed of grid material that is approximately 15 μm in thickness. This thickness is well within the retention capability of the mesh and is therefore not expected to present any issues. Approximately 3.1 grams of deposition flakes were found at the bottom of the discharge chamber, composed primarily of grid material and carbon. Calculated size histograms of these flakes indicate that 99% have a maximum dimension of 200 μm or smaller, which is significantly less than the ion optics grid gap. Larger flakes that are capable of causing a grid-to-grid short will be analyzed to determine if their formation will occur in flight or is a facility effect. The high-voltage propellant isolators as well as numerous other electrical insulators were inspected and no evidence of arcing or any other issues were found.

Rohit Shastry↗
NASA NTRS2021

Classifying planetary cloudiness with an updated set of MODIS Cloud Regimes

We present an updated Cloud Regime (CR) dataset based on Moderate resolution Imaging Spectroradiometer (MODIS) Collection 6.1 cloud products, specifically joint histograms that partition cloud fraction within distinct combinations of cloud top pressure and cloud optical thickness ranges. The paper focuses on an edition of the CR dataset derived from our own aggregation of MODIS pixel-level cloud retrievals on an equal area grid and pre-specified 3-hour UTC intervals that spatiotemporally match International Satellite Cloud Climatology Project (ISCCP) gridded cloud data. The other edition comes from the 1-degree daily aggregation provided by standard MODIS Level-3 data, as in previous versions of the MODIS CRs, for easier use with datasets mapped on equal angle grids. Both editions consist of 11 clusters whose centroids are nearly identical.We provide a physical interpretation of the new CRs and aspects of their climatology that have not been previously examined, such as seasonal and interannual variability of CR frequency of occurrence. We also examine the makeup and precipitation properties of the CRs assisted by independent datasets originating from active observations, and provide a first glimpse of how MODIS CRs relate to clouds as seen by ISCCP.

MODIS↗
NASA NTRSDate not supplied

Influence of Thermophysical Property Variability on Thermal Predictions of Ti-6Al-4V

The additive manufacturing (AM) industry has experienced rapid growth in recent decades as industrial interest in the process has grown. Because of this, there are many groups interested in simulations of the AM process. However, the influence of thermophysical property variability on the melt pool geometry during processing of various AM alloys is unclear. The goal of my work at NASA Langley Research Center (LaRC) was to characterize this influence on Ti-6Al-4V during AM processing alongside developing a tool to enable equivalent studies on other AM materials. To facilitate this process, a database tool was developed to contain and organize thermophysical data previously reported by primary sources. The specific thermophysical properties of interest for this study were density, specific heat capacity, and conductivity. Thermal diffusivity was calculated using the other three properties. This data was then fit with a Gaussian distribution and then randomly sampled from using Monte Carlo random value sampling. Using the Rosenthal equation, this sample data was used to simulate the temperature field during additive manufacturing and extract the melt pool geometry. Specifically, the melt pool’s length, width, and depth. This process was repeated an arbitrary number of times, with the default being 1000. Once this information was obtained, histograms were made showing the distributions of the sizes of the melt pool’s length, width, and depth. Representative statistical metrics of the distributions were calculated (mean, standard deviation, and coefficient of variance). This work found that at the simulated processing values, the melt pool’s width and depth had a 5.7% variation while the length had a 3.2% variation. Additionally, a tool was constructed to graph a thermal color map representation of the melt pool for specific, arbitrary values of density, specific heat, and conductivity. This tool allowed for more efficient plotting of individual queries of the thermophysical properties. The results that were observed in the research were that values reported in literature vary and this variance can have a significant impact on the simulation. Predictions of the melt pool’s dimensions show that length has a standard deviation of approximately 6 μm, width has a standard deviation of approximately 5 μm, and depth can vary by approximately 3 μm. Considering the mean sizes of length, width, and depth are 185 μm, 88 μm, and 44 μm respectively, such a deviation is significant. This shows that depth, for example, could be more than 10% larger or smaller than expected. This demonstrates that variability in the reported thermophysical properties are not negligible and should be expected to have an influence on the results of the laser powder bed fusion additive manufacturing process. When simulating this process in the future, measures should be taken to account for this discrepancy and the uncertainty involved

Justin Martin↗
NASA NTRSDate not supplied

Calculation of top-of-atmosphere, surface and atmospheric cloud radiative kernels and feedbacks based on ISCCP-H datasets

This study aims to create observation-based cloud radiative kernel (CRK) datasets and evaluate them by direct comparison of CRK and the CRK-derived cloud feedback datasets. Based on the International Satellite Cloud Climatology Project (ISCCP) H datasets, we calculate CRKs (called FH CRKs) as 2D joint function/histogram of cloud optical depth and cloud top pressure for shortwave, longwave, and their sum, Net, at the top of atmosphere (TOA), as well as, for the first time, at the surface (SFC) and in the atmosphere (ATM). The direct comparison shows that FH agrees reasonably well with three other TOA CRK datasets. With cloud fraction change (CFC) datasets of the same histogram for doubled-CO2 simulation from 10 CFMIP1 models, we derive all the TOA, SFC and ATM cloud feedback using the FH CRKs. Our TOA cloud feedback is highly similar to the previous counterparts. Based on the comparison for the 4 CRK datasets and the 10 CFC datasets, we estimate the uncertainty budget for the CRK-derived cloud feedback and show that the CFC-associated uncertainty contributes > 98.5% of the total cloud feedback uncertainty while CRK’s is very small. Our preliminary evaluation shows that some near-zero/small cloud feedback in the TOA-alone feedback indeed results from the compensation of sizable cloud feedback of the SFC and ATM feedback, demonstrating that they help reveal some significant surface and atmospheric cloud feedback whose sum appears insignificant in TOA-alone feedback

cloud radiative kernel (CRK) datasets↗
NASA NTRS2021

SHARPEN: A Scheme to Restore the Distribution of Averaged Precipitation Fields

A key strategy in obtaining complete global coverage of high-resolution precipitation is to combine observations from multiple fields, such as the intermittent passive microwave observations, precipitation propagated in time using motion vectors, and geosynchronous infrared observations. These separate precipitation fields can be combined through weighted averaging, which produces estimates that are generally superior to the individual parent fields. However, the process of averaging changes the distribution of the precipitation values, leading to an increase in precipitating area and a decrease in the values of high precipitation rates, a phenomenon observed in IMERG. To mitigate this issue, we introduce a new scheme called SHARPEN (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood), which recovers the distribution of the averaged precipitation field based on the idea of quantile mapping applied to the local environment. When implemented in IMERG, precipitation estimates from SHARPEN exhibit a distribution that resembles that of the original instantaneous observations, with matching precipitating area and peak precipitation rates. Case studies demonstrate its improved ability in bridging between the parent precipitation fields. Evaluation against ground observations reveals a distinct improvement in precipitation detection skill, but also a slightly reduced correlation likely because of a sharper precipitation field. The increased computational demand of SHARPEN can be mitigated by striding over multiple grid boxes, which has only marginal impacts on the accuracy of the estimates. SHARPEN can be applied to any precipitation algorithm that produces an average from multiple input precipitation fields and is being considered for implementation in IMERG V07.

Jackson Tan↗
NASA NTRSDate not supplied

NASA/GEWEX SRB Surface Radiation Budget Fluxes Through the Prism of Weather States

The NASA/GEWEX Surface Radiation Budget Version 4 (SRB Rel4) product is now publicly available, covering the period from July 1983 through June 2017. This supersedes the SRB Rel3 (Stackhouse et al., 2011) product which has been used in the community for a wide variety of applications, including climate model validation, agriculture, solar energy, and architecture. SRB Rel4 uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Rel3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters. Rel4 incorporates several important algorithm improvements. These include recalculated shortwave (SW) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both shortwave and longwave (LW) now also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MACv1). LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added. Here we evaluate the SRB Rel4 top of atmosphere (TOA) and surface fluxes in the context of weather states and oceanic regions. Weather states (Tselioudis et al., 2013, Tselioudis et al., 2021) are defined by K-means clustering 2-D histograms of satellite-retrieved cloud optical depths and cloud top pressures. The most recent (Tselioudis et al., 2021) weather states derived from the International Satellite Cloud Climatology Project (ISCCP) H-series data results in eight cloud weather states and one clear sky weather state, for a total of nine weather states. We examine the statistics of SRB Rel4 fluxes for each weather state and a variety of relevant land and ocean regions. We compare to similar analyses performed on CERES EBAF and SYN1Deg flux products, and validate against Baseline Surface Radiometer Network (BSRN) land stations and Pacific Marine Environmental Laboratory (PMEL) ocean buoy data. It is demonstrated that the weather state concept is valuable when examining the comparative strengths and weaknesses of satellite radiative flux algorithms.

Atmospheric Radiation↗
NASA NTRS2023

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally-distributed single-catchment locations for a 10-year experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF systematically increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results also demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Soil moisture↗
NASA NTRS2021

Comparisons of IMERG Version 06 Precipitation at and between Passive Microwave Overpasses in the Tropics

The Integrated Multisatellite Retrievals for Global Precipitation Measurement Mission (IMERG) is a global precipitation product that uses precipitation retrievals from the virtual constellation of satellites with passive microwave (PMW) sensors, as available. In the absence of PMW observations, IMERG uses a Kalman filter scheme to morph precipitation from one PMW observation to the next. In this study, an analysis of convective systems observed during the Convective Process Experiment (CPEX) suggests that IMERG precipitation depends more strongly on the availability of PMW observations than previously suspected. Following this evidence, we explore systematic biases in IMERG through bulk statistics. In two CPEX case studies, cloud photographs, pilot’s radar, and infrared imagery suggest that IMERG represents the spatial extent of precipitation relatively well when there is a PMW observation but sometimes produces spurious precipitation areas in the absence of PMW observations. Also, considering an observed convective system as a precipitation object in IMERG, the maximum rain rate peaked during PMW overpasses, with lower values between them. Bulk statistics reveal that these biases occur throughout IMERG Version 06. We find that locations and times without PMW observations have a higher frequency of light precipitation rates and a lower frequency of heavy precipitation rates due to retrieval artifacts. These results reveal deficiencies in the IMERG Kalman filter scheme, which have led to the development of the Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood (SHARPEN; described in a companion paper) that will be applied in the next version of IMERG.

Manikandan Rajagopal↗
NASA NTRSDate not supplied

Newly Released GPCP Version 3.2 Global Precipitation Datasets at NASA GES DISC

The Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set of (mainly) satellite-based global products dealing with the Earth's water and energy cycles, under the auspices of the Global Water and Energy Experiment (GEWEX) Data and Assessment Panel (GDAP) of the World Climate Research Program. As the follow-on to the GPCP Version 2.X products, GPCP Version 3 (GPCP V3.2) seeks to continue the production of long, homogeneous precipitation record using modern input and calibration datasets. The GPCP V3.2 provides globally complete analyses of surface precipitation on a 0.5°x 0.5° latitude/longitude grid at both monthly and daily intervals, respectively covering 1983 to the present and June 2000 to the present. New data fields have been introduced to better characterize the precipitation, particularly including an estimate of the fraction of the precipitation that is liquid (rain) in both the Monthly and Daily, and a Quality Index for the Monthly. Compared to the operational GPCP V2.3 Monthly, the V3.2 Monthly provides a more reasonable climatology in the Southern Ocean, and increases the global average precipitation by about 4.46%, which is in line with recommendations of recent assessments. However, the two versions have comparable global and regional trends for 1983-2020. Compared to the operational One-Degree Daily (Version 1.3) product, the V3.2 Daily better represents the histogram of precipitation rates, particularly at high values. In this presentation, we will present the latest GPCP V3.2 daily and monthly datasets archived and distributed at NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) along with examples from NASA Giovanni.

Precipitation↗
NASA NTRSDate not supplied

Generative Framework Approach to Match Landsat and Sentinel-2 Data

Linear regression and histogram matching based techniques have been widely used to minimize the surface reflectance difference between two similar satellite observations such as Landsat-8/9 and Sentinel-2A/B products [1]. However, regionally or globally derived conversion factors may not be suitable for all land cover types and locations, resulting in noticeable residual differences between the sensors. Generative Adversarial Network (GAN) has shown promise in the field of image processing for domain or style transfer[2]. In this work we aim to minimize the surface reflectance difference between Landsat and Sentinel-2 products based on GAN.

Sujit Roy↗
NASA NTRS2023

Updated Observations of Clouds By MODIS for Global Model Assessment

This paper describes a new global dataset of cloud properties observed by MODIS relying on the current (collection 6.1) processing of MODIS data and produced to facilitate comparison with results from the MODIS observational proxy used in climate models. The dataset merges observations from the two MODIS instruments into a single netCDF file. Statistics (mean, standard deviation, and number of observations) are accumulated over daily and monthly timescales on an equal-angle grid for viewing and illumination geometry, cloud detection, cloud-top pressure, and cloud properties (optical thickness, effective particle size, and water path) partitioned by thermodynamic phase and an assessment as to whether the underlying observations come from fully or partly cloudy pixels. Similarly partitioned joint histograms are available for (1) optical thickness and cloud-top pressure, (2) optical thickness and particle size, and (3) cloud water path and particle size. Differences with standard data products, caveats for data use, and guidelines for comparison to the MODIS simulator are described.

Robert Pincus↗