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Results for “SURFACE RADIATIVE PROPERTIES”

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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Fundamentals of spacecraft thermal design.

The papers deal with and are grouped according to four major issues. These are: surface radiation properties, including synthesis and measurement, space flight effect, and contamination effects; thermal analysis, including reentry vehicle analysis, radiant heat transfer between surfaces, and thermal contact conductance of surfaces; heat pipes, including possible applications, operating characteristics, and design, fabrication and testing of heat pipes; and thermal design, including radiative, ablative, and active cooling thermal protection of the leading edge of a space-shuttle wing, and space station environmental thermal control. Individual items were previously announced in issues 06 and 11, 1971.

Lucas, J. W.↗
NASA NTRS1989

Global, seasonal cloud variations from satellite radiance measurements. I - Sensitivity of analysis

Global, daily, visible and IR radiance measurements from the NOAA-5 Scanning Radiometer (SR) are analyzed for the months of January, April, July and October, 1977 to infer cloud and surface radiative properties. In this paper, the data and analysis method are described. A unique feature of the method is that it utilizes radiative transfer models that simulate the SR measurements using explicit parameters representing the properties of the surface, atmosphere, and clouds. The accuracy of all the results depends primarily on the proper separation of the total radiance distribution into those parts representing clear and cloudy scenes.

Rossow, William B.↗
DOE OSTI2025

Search for a Cloud Phase Feedback in the Arctic Climate System

This project was motivated by a hypothesis involving the transition in lower troposphere temperatures across the freezing point of water. Specifically, at temperatures just below to about ten degrees below freezing, Arctic clouds should be in a mixed-phase, with strong influences from secondary ice production (e.g., the Hallett-Mossop process). At temperatures just above freezing, clouds should become entirely deglaciated. We hypothesized that, with multiple years of ARM data, a statistically significant change could be detected in cloud radiative properties and surface radiative fluxes that could be directly attributed to this phase change. Furthermore, in a gradually warming climate, these phase change-related responses in surface radiation would represent a cloud phase feedback as part of Arctic amplification. We designed this research project to coincide with a new ARM Arctic cloud radar product developed by Ed Luke and collaborators at BNL (Luke et al., 2021: PNAS, doi:10.1073/pnas.2021387118) that explicitly contains SIP cloud properties retrieved from radar data. This research project has successfully concluded after analysis of a much larger North Slope of Alaska (NSA) data sample than originally anticipated, and the results are quite different than originally hypothesized.

58 GEOSCIENCES↗
NASA NTRS2011

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗
NASA NTRS2012

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗
NASA NTRS1993

Spectral radiation analyses of the GOES solar illuminated hexagonal cell scan mirror back

A ray tracing analytical tool has been developed for the simulation of spectral radiation exchange in complex systems. Algorithms are used to account for heat source spectral energy, surface directional radiation properties, and surface spectral absorptivity properties. This tool has been used to calculate the effective solar absorptivity of the geostationary operational environmental satellites (GOES) scan mirror in the calibration position. The development and design of Sounder and Imager instruments on board GOES is reviewed and the problem of calculating the effective solar absorptivity associated with the GOES hexagonal cell configuration is presented. The analytical methodology based on the Monte Carlo ray tracing technique is described and results are presented and verified by experimental measurements for selected solar incidence angles.

Fantano, Louis G.↗
NASA NTRS1994

Arctic ocean radiative fluxes and cloud forcing estimated from the ISCCP C2 cloud dataset, 1983-1990

Radiative fluxes and cloud forcings for the ocean areas of the Arctic are computed from the monthly cloud product of the International Satellite Cloud Climatology Project (ISCCP) for 1983-90. Spatially averaged short-wave fluxes are compared well with climatological values, while downwelling longwave fluxes are significantly lower. This is probably due to the fact that the ISCCP cloud amounts are underestimates. Top-of-the-atmosphere radiative fluxes are in excellent agreement with measurements from the Earth Radiation Budget Experiment (ERBE). Computed cloud forcings indicate that clouds have a warming effect at the surface and at the top of the atmosphere during winter and a cooling effect during summer. The net radiative effect of clouds is larger at the surface during winter but greater at the top of the atmosphere during summer. Overall the net radiative effect of clouds at the top of the atmosphere is one of cooling. This is in contrast to a previous result from ERBE data showing arctic cloud forcings have a net warming effect. Sensitivities to errors in input parameters are generally greater during winter with cloud amount being the most important paarameter. During summer the surface radiation balance is most sensitive to errors in the measurements of surface reflectance. The results are encouraging, but the estimated error of 20 W/sq m in surface net radiative fluxes is too large, given that estimates of the net radiative warming effect due to a doubling of CO2 are on the order of 4 W/sq m. Because it is difficult to determine the accuracy of results with existing in situ observations, it is recommended that the development of improved algorithms for the retrieval of surface radiative properties be accompanied by the simultaneous assembly of validation datasets.

Schweiger, Axel J.↗
DOE OSTI2023

Drone flight visible images, digital elevation maps, and geotiffs, Council, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along each flight path. This package includes data from four flight paths over the NGEE Arctic Council Road Site near mile marker 71 in the Seward Peninsula, Alaska in July 2017. Derived image products for each flight include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Drone flight visible images, digital elevation maps, and geotiffs, Teller, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along the flight path. This package includes data from a flight path over the NGEE Arctic Teller Site, west of mile marker 27 Bob Blodgett Highway in the Seward Peninsula, Alaska in July 2017. Derived image products include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Drone flight visible images, digital elevation maps, and geotiffs, Kougarok, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along each flight path. This package includes data from four flight paths over the NGEE Arctic Kougarok Site, west of mile marker 64 on Kuzitrin Road in the Seward Peninsula, Alaska in July 2017. Derived image products include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Maps of Arctic vegetation leaf nitrogen concentration, albedo and plant functional type (PFT) derived from imaging spectroscopy data, Council watershed, Seward Peninsula, Alaska, 2019

Remote sensing maps of surface albedo, leaf nitrogen content, and plant functional types (PFTs) derived from NASA's Airborne Visible / Infrared Imaging Spectrometer Next Generation (AVIRIS-NG) by the Terrestrial Ecosystem Science & Technology (TEST) group at Brookhaven National Laboratory. The AVIRIS-NG imaging spectroscopy data (380 ~ 2510 nm) was collected as a part of the collaboration between NASA's Arctic-Boreal Vulnerability Experiment (ABoVE; Miller et al., 2019) and DOE's Next Generation Ecosystem Experiment in the Arctic (NGEE-Arctic). This package includes maps for the NGEE-Arctic Council watershed created using AVIRIS-NG imagery collected on July 9th, 2019. The map data and metadata are provided as image (ENVI, *.png) and text (*.txt, *hdr) formats. Additional supporting map quicklooks are provided as *.png files and GIS *.kml files. Detailed description of the methods for each map are provided in this document. These datasets are provided in support of Figure 6 in Nelson et al., (2022), "Remote Sensing of Tundra Ecosystems using High Spectral Resolution Reflectance: Opportunities and Challenges". The full citation can be found within the references section. Note that the AVIRIS-NG leaf nitrogen product included in this dataset is a preliminary product and is provided for demonstration purposes only. It is not recommended that the map be used for scientific applications. For future updates on these products, please contact the authors.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Measurement of surface physical properties and radiation balance for KUREX-91 study

Biophysical properties and radiation balance components were measured at the Streletskaya Steppe Reserve of the Russian Republic in July 1991. Steppe vegetation parameters characterized include leaf area index (LAI), leaf angle distribution, mean tilt angle, canopy height, leaf spectral properties, leaf water potential, fraction of absorbed photosynthetically active radiation (APAR), and incoming and outgoing shortwave and longwave radiation. Research results, biophysical parameters, radiation balance estimates, and sun-view geometry effects on estimating APAR are discussed. Incoming and outgoing radiation streams are estimated using bidirectional spectral reflectances and bidirectional thermal emittances. Good agreement between measured and modeled estimates of the radiation balance were obtained.

Walter-Shea, Elizabeth A.↗
NASA NTRS2001

Arctic Stratus Cloud Properties and Their Effect on the Surface Radiation Budget: Selected Cases from FIRE ACE

To study Arctic stratus cloud properties and their effect on the surface radiation balance during the spring transition season, analyses are performed using data taken during three cloudy and two clear days in May 1998 as part of the First ISCCP Regional Experiment (FIRE) Arctic Cloud Experiment (ACE). Radiative transfer models are used in conjunction with surface- and satellite-based measurements to retrieve the layer-averaged microphysical and shortwave radiative properties. The surface-retrieved cloud properties in Cases 1 and 2 agree well with the in situ and satellite retrievals. Discrepancies in Case 3 are due to spatial mismatches between the aircraft and the surface measurements in a highly variable cloud field. Also, the vertical structure in the cloud layer is not fully characterized by the aircraft measurements. Satellite data are critical for understanding some of the observed discrepancies. The satellite-derived particle sizes agree well with the coincident surface retrievals and with the aircraft data when they were collocated. Optical depths derived from visible-channel data over snow backgrounds were overestimated in all three cases, suggesting that methods currently used in satellite cloud climatologies derive optical depths that are too large. Use of a near-infrared channel with a solar infrared channel to simultaneously derive optical depth and particle size appears to alleviate this overestimation problem. Further study of the optical depth retrieval is needed. The surface-based radiometer data reveal that the Arctic stratus clouds produce a net warming of 20 W m(exp -2) in the surface layer during the transition season suggesting that these clouds may accelerate the spring time melting of the ice pack. This surface warming contrasts with the net cooling at the top of the atmosphere (TOA) during the same period. All analysis of the complete FIRE ACE data sets will be valuable for understanding the role of clouds during the entire melting and refreezing process that occurs annually in the Arctic.

Doug, Xiquan↗
NASA NTRSDate not supplied

Surface Radiation Budget (SRB) Release 2.5 Longwave cloud props 3 hourly Data in Native Format (SRB_REL2.5_LW_CLDPROPS_3HRLY)

The Surface Radiation Budget (SRB) data set contain 47 surface and cloud properties including cloud fraction, cloud visible optical depth, cloud top temperature, cloud top pressure, cloud base pressure, and cloud water and ice content for each of 5 cloud types and in total. In addition to these cloud properties, the parameters also include surface pressure, total column ozone, day/night flag, and precipitable water. All perameters were measured at three hourly intervals for each day for the entire globe between 07/01/1983 and 06/30/2005 and serve as inputs to the Global Energy and Water-Cycle Experiment (GEWEX) longwave algorithm (GLW). [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3 hourly; Temporal_Resolution_Range=3 hourly].

CLOUD TOP TEMPERATURE↗
NASA NTRS2000

Radiative Properties of Smoke and Aerosol Over Land Surfaces

This talk discusses smoke and aerosol's radiative properties with particular attention to distinguishing the measurement over clear sky from clouds over land, sea, snow, etc. surfaces, using MODIS Airborne Simulator data from (Brazil, arctic sea ice and tundra and southern Africa, west Africa, and other ecosystems. This talk also discusses the surface bidirectional reflectance using Cloud Absorption Radiometer, BRDF measurements of Saudi Arabian desert, Persian Gulf, cerrado and rain forests in Brazil, sea ice, tundra, Atlantic Ocean, Great Dismal Swamp, Kuwait oil fire smoke. Recent upgrades to instrument (new TOMS UVA channels at 340 and 380 planned use in Africa (SAFARI 2000) and possibly for MEIDEX will also be discussed. This talk also plans to discuss the spectral variation of surface reflectance over land and the sensitivity of off-nadir view angles to correlation between visible near-infrared reflectance for use in remote sensing of aerosol over land.

King, Michael D.↗
DOE OSTI2021

Enhanced radiative and thermal properties from surface encapsulation of InAs nanowires

In this work, photoluminescence (PL), quantum efficiency and carrier dynamics are investigated in indium arsenide (InAs) nanowires (NWs) with various surface treatments, including a molecular beam epitaxy (MBE)-grown semiconductor shell passivation, sulfur-passivation, alumina (Al 2 O 3 ) coating by atomic layer deposition (ALD) and polydimethylsiloxane (PDMS) spin-coating. The ALD-dielectric layer-coated InAs core-shell NWs show a maximum 13-fold increase in PL intensity. In contrast to the previous reports, this enhancement is found to be due to increased radiative rate from an enhanced Purcell factor, better thermal conductance and higher carrier injection within the NWs instead of improved surface quality. Numeric simulations confirm the experimentally observed increased radiative rate. Further improvements are suggested with even thicker capped InAs NWs. Carrier lifetime in surface-treated NWs is extended and shows long-term stability, critical for practical devices.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

A Machine Learning Approach to Determine Surface Radiative Fluxes based on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) projects provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. An alternative data product, Fast Longwave and Shortwave radiative Flux (FLASHFlux), was created to provide data to the applied sciences and educational users. FLASHFlux provides Top-of-Atmosphere radiative fluxes, Clouds properties, and parameterized surface radiative fluxes within four days for footprint (Level 2) data. We investigate the use of Artificial Neural Network (ANN) using MODerate resolution Imaging Spectroradiometer (MODIS) derived clouds properties and meteorology from the Global Assimilation and Meteorology Office (GMAO) scaled to the CERES footprint from the CERES Clouds Radiative Swath (CRS) data product to compute surface radiative fluxes. We test ANN produce fluxes against surface fluxes produced from the Fu-Liou model used in CRS and the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) used in FLASHFlux. We also validated each model with ground-based observations. Furthermore, we investigate Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training and provide insight for future models. Advances in machine learning, along with increases in computational capabilities and available data allow us to estimate effects of unresolved processes in our climate without direct modeling. This work evaluates the ability to create accurate data-driven models to supplement or replace current models that estimate surface radiative fluxes.

Climatology↗
DOE OSTI2023

ESS-DIVE Unoccupied Aerial Systems (UAS) Reporting Format v1

Here we present documentation of the ESS-DIVE reporting format for Unoccupied Aerial System (UAS) data and metadata. This reporting format provides guidance to data contributors on how to store data to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format provides templates and guidance for the reporting of metadata for UAS experimental campaigns, individual flights, platform and sensor description. To improve data access and discoverability, the reporting format proposes a data description scheme of Levels based on the degree of processing, where Level 0 includes raw data, through to Level 3 being derived data end products. A range of examples of data types for each Level are given, with suggested file naming schemes. The reporting format presented here is intended to form a foundation for future development that will accommodate new UAS technologies and approaches to data access and use in the future. The reporting format documentation is maintained and updated on the ESS-DIVE Community Space GitHub at https://github.com/ess-dive-community/essdive-uas. This data package is the first published version of this reporting format, and comprises a zip file of the complete content of https://github.com/ess-dive-community/essdive-uas v1.0. The zip contains the reporting format description, instructions and variable definitions in GitHub markdown language (*.md) and metadata templates in csv format. The reporting format is designed to be compatible with other ESS-DIVE formats, and it is specifically recommended that this reporting format be used in conjunction with the File-level metadata (FLMD) and comma separated values (csv) reporting formats for submission to the ESS-DIVE repository.

54 ENVIRONMENTAL SCIENCES↗