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Heuristics for Relevancy Ranking of Earth Dataset Search Results

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

science data management↗

Relevancy Ranking of Satellite Dataset Search Results

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

science data management↗

Publishing Variables Archived at GES DISC to Earth System Grid Federation (ESGF)

We present a straightforward and low-cost approach to publish variables archived at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) to the Earth System Grid Federation (ESGF). An ESGF publication requires a single standard-name variable aggregated over time to facilitate data inter-comparison. It also contains significant metadata to enable searching in ESGF. We look up standard names on high demand in ESGF search history, and using OPeNDAP and NcML technologies we aggregate the corresponding variables available in the GES DISC archive with augmented metadata required by CMIP6 and obs4MIPs Data Specification version 2.1. At this writing 10 variables from a standard product of the Atmospheric Infrared Sounder along with the Tech Notes are published in ESGF by NASA Center for Climate Simulation (NCCS). Users can view, analyze, and subset remotely, and download these aggregated variables via links in any ESGF node after searching. We plan to work on and publish more variables and data from different NASA missions and experiments in our archive.

Fan Fang↗

Parameterization-Induced Uncertainties and Impacts of Crop Management Harmonization in a Global Gridded Crop Model Ensemble

Global gridded crop models (GGCMs) combine agronomic or plant growth models with gridded spatial input data to estimate spatially explicit crop yields and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different biophysical models, setups, and input data. GGCM ensembles are frequently employed to bracket uncertainties in impact studies without investigating the causes of divergence in outputs. This study explores differences in maize yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison initiative. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, and selection of subroutines affecting crop yield estimates via cultivar distributions, soil attributes, and hydrology among others. The analyses reveal inter-annual yield variability and absolute yield levels in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. All GGCMs show an intermediate performance in reproducing reported yields with a higher skill if a static soil profile is assumed or sufficient plant nutrients are supplied. An in-depth comparison of setup domains for two EPIC-based GGCMs shows that GGCM performance and plant stress responses depend substantially on soil parameters and soil process parameterization, i.e. hydrology and nutrient turnover, indicating that these often neglected domains deserve more scrutiny. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions in setups appears the best solution for coping with uncertainties from lack of comprehensive global data on crop management, cultivar distributions and coefficients for agro-environmental processes. However, the underlying assumptions require systematic specifications to cover representative agricultural systems and environmental conditions. Furthermore, the interlinkage of parameter sensitivity from various domains such as soil parameters, nutrient turnover coefficients, and cultivar specifications highlights that global sensitivity analyses and calibration need to be performed in an integrated manner to avoid bias resulting from disregarded core model domains. Finally, relating evaluations of the EPIC-based GGCMs to a wider ensemble based on individual core models shows that structural differences outweigh in general differences in configurations of GGCMs based on the same model, and that the ensemble mean gains higher skill from the inclusion of structurally different GGCMs. Although the members of the wider ensemble herein do not consider crop-soil-management interactions, their sensitivity to nutrient supply indicates that findings for the EPIC-based sub-ensemble will likely become relevant for other GGCMs with the progressing inclusion of such processes.

Folberth, Christian↗

Global Ocean Phytoplankton

Marine phytoplankton are responsible for roughly half the net primary production (NPP) on Earth, fixing atmospheric CO2 into food that fuels global ocean ecosystems and drives the ocean's biogeochemical cycles. Phytoplankton growth is highly sensitive to variations in ocean physical properties, such as upper ocean stratification and light availability within this mixed layer. Satellite ocean color sensors, such as the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; McClain 2009) and Moderate Resolution Imaging Spectroradiometer (MODIS; Esaias 1998), provide observations of sufficient frequency and geographic coverage to globally monitor physically-driven changes in phytoplankton distributions. In practice, ocean color sensors retrieve the spectral distribution of visible solar radiation reflected upward from beneath the ocean surface, which can then be related to changes in the photosynthetic phytoplankton pigment, chlorophyll- a (Chla; measured in mg m-3). Here, global Chla data for 2013 are evaluated within the context of the 16-year continuous record provided through the combined observations of SeaWiFS (1997-2010) and MODIS on Aqua (MODISA; 2002-present). Ocean color measurements from the recently launched Visible and Infrared Imaging Radiometer Suite (VIIRS; 2011-present) are also considered, but results suggest that the temporal calibration of the VIIRS sensor is not yet sufficiently stable for quantitative global change studies. All MODISA (version 2013.1), SeaWiFS (version 2010.0), and VIIRS (version 2013.1) data presented here were produced by NASA using consistent Chla algorithms.

phytoplankton↗

Recalibration and Validation of the SMAP L-Band Radiometer

SMAP mission was launched on 31st January 2015 in a 6 AM 6 PM sun-synchronous orbit at 685 km altitude to measure soil moisture and freethaw globally. The passive instrument of SMAP is a fully polarimetric L-band radiometer (1.4GHz) operating with a bandwidth of 24MHz. The radiometer L1B data product version 3 has been released for public science activities. Post-launch calibration and validation activities are described in [4,5]. Validation results show that SMAP antenna temperature (TA) is 2.6 K warmer over galactic Cold Sky (CS), and land TB is 2.6 K colder comparing to SMOS land TB (compared at the top of the atmosphere) after the update of the reflectors thermal model. Due to the biases, the SMAP radiometer is under re-calibration for next data release in 2018.We present the updated calibration approaches for the SMAP radiometer product. We will discuss the various radiometer calibration parameters and part of the validation process and result.

SMAP↗

Four years of ground-based total ozone measurements by visible spectrometry in Antarctica

Visible spectrometers SAOZ have been developed at Service d'Aeronomie for permanent ground-based ozone monitoring at all latitudes up to the polar circle in winter. Observations are made by looking at the sunlight scattered at zenith in the visible range, twice a day, at sunrise and sunset. Compared to ozone observations in the UV generally in use, visible observations in the small Chappuis bands at twilight have the advantages of being independent of stratospheric temperature, little contaminated by tropospheric ozone and multiple scattering, and of permitting observations even in winter at the polar circle. SAOZ instruments have been installed since 1988 at several stations in the Antarctic and the Arctic. More than four years data at Dumont d'Urville in Terre Adelie (67 deg S) are now available. The station is generally located at the edge of the vortex in spring and therefore the ozone hole is seen there only occasionally. The lowest values (140 DU) were reported in early October 1991. According to these first regular observations throughout the whole winter ozone seems to increase in late autumn and winter. Its decay does not start before the end of August. Although of smaller amplitude than with the previous version five data, the ratio between the groundbased and satellite/TOMS measurements displays a systematic seasonal variation correlated partly to the sun zenith angle of observations from orbit and partly to the temperature of the stratosphere. Since ground-based measurements are always made at 90 deg SZA, the SZA dependence must come from the satellite data interpretation (TOMS observations are between 43 to 88 deg SZA). The temperature dependence could be partly due to variations of ozone absorption cross-sections in the ultraviolet used by the satellite spectrometer, and partly to a systematic seasonal cycle of the air mass factor use in the interpretation of the ground based observations. However, the last contribution appears to be too small to compensate the ozone increase in winter reported by SAOZ, which is then real.

Goutail, F.↗

The 1998-2000 SHADOZ (Southern Hemisphere ADditional OZonesondes) Tropical Ozone Climatology: Ozonesonde Precision, Accuracy and Station-to-Station Variability

As part of the SAFARI-2000 campaign, additional launches of ozonesondes were made at Irene, South Africa and at Lusaka, Zambia. These represent campaign augmentations to the SHADOZ database described in this paper. This network of 10 southern hemisphere tropical and subtropical stations, designated the Southern Hemisphere ADditional OZonesondes (SHADOZ) project and established from operational sites, provided over 1000 profiles from ozonesondes and radiosondes during the period 1998-2000. (Since that time, two more stations, one in southern Africa, have joined SHADOZ). Archived data are available at: http://code9l6.gsfc.nasa.gov/Data-services/shadoz>. Uncertainties and accuracies within the SHADOZ ozone data set are evaluated by analyzing: (1) imprecisions in stratospheric ozone profiles and in methods of extrapolating ozone above balloon burst; (2) comparisons of column-integrated total ozone from sondes with total ozone from the Earth-Probe/TOMS (Total Ozone Mapping Spectrometer) satellite and ground-based instruments; (3) possible biases from station-to-station due to variations in ozonesonde characteristics. The key results are: (1) Ozonesonde precision is 5%; (2) Integrated total ozone column amounts from the sondes are in good agreement (2-10%) with independent measurements from ground-based instruments at five SHADOZ sites and with overpass measurements from the TOMS satellite (version 7 data). (3) Systematic variations in TOMS-sonde offsets and in groundbased-sonde offsets from station to station reflect biases in sonde technique as well as in satellite retrieval. Discrepancies are present in both stratospheric and tropospheric ozone. (4) There is evidence for a zonal wave-one pattern in total and tropospheric ozone, but not in stratospheric ozone.

Witte, J. C.↗

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.

NLDAS-2↗

TPSAS-NF1676L-11678-DND

Cloud vertical profiles retrieved from CALIPSO and CloudSat data provide additional information that greatly improves the estimate of atmospheric radiative heating rates and potentially improves the estimate of the global surface radiation budget. To utilize CALIPSO and CloudSat cloud vertical profiles, we combined their profiles and generated merged profiles. Weused the merged cloud profiles and MODIS derived cloud profiles by the CERES cloud algorithm in irradiance computations. In this study, the improvement of the irradiance by CALIPSO and CloudSat derived merged cloud vertical profiles is evaluated by comparing modeled irradiances with and without merged cloud profiles. Because of lower cloud base heights provided by the merged profiles compared with cloud base heights derived from an empirical formula using the MODIS derived cloud top height and optical thickness, the global annual mean surface longwave downward irradiance increases approximately by 7 Wm-2. While CALIPSO version 3 data have not been incorporated in the irradiance computation and the effect of the new CALIPSO data needs to be assessed, a comparison with surface observations suggests an improvement of surface downward longwave irradiance computations. The surface downward longwave irradiance computed with CALIPSO and CloudSat merged clouds agrees better with surface observations than the irradiance computed with MODIS only does. The bias difference over ARM SGP sites with 2 years of data decreases from -5 W m-2to -2 Wm-2, and it decreases from -9 Wm-2to no bias over polar validation sites. The result suggests that CALIPSO CloudSat derived merged clouds significantly improve surface longwave irradiance estimates once they are combined with MODIS derived cloud properties and with temperature and humidity profiles from reanalysis.

Seiji Kato↗

Highlights from the 1998-2000 SHADOZ (Southern Hemisphere Additional Ozonesondes) Satellite Validation Project

There are three years of data (more than 1000 individual ozone profiles) available from a network of 10 southern hemisphere tropical and subtropical stations, designated the Southern Hemisphere ADditional OZonesondes (SHADOZ) project. Since late 1999, a tropical station in the northern hemisphere (Paramaribo, Surinam; lat/long) joined SHADOZ, providing coordinated weekly ozone and radiosonde data from the surface to approx. 7 hPa for satellite validation, process studies, and model evaluation. Profiles are also collected at: Ascension Island; Nairobi, Kenya; Irene, South Africa; R (union Island; Watukosek, Java; Fiji; Tahiti; American Samoa; San Cristobal, Galapagos; Natal, Brazil. The archive, station characteristics and photos are available at http://code9l6.gsfc.nasa.gov/Data_ services/shadoz>. SHADOZ ozone time-series and profiles in 1998-2000 display highly variable tropospheric ozone, a zonal wave-one pattern in total (and tropospheric) column ozone, and signatures of the Quasi-Biennial Oscillation (QBO) in stratospheric ozone. Total, stratospheric and tropospheric column ozone amounts peak between August and November and are lowest between March and May. Integrated total ozone column amounts from the sondes are lower than independent measurements from a ground-based network and from the TOMS (Total Ozone Mapping Spectrometer) satellite (version 7 data).

Witte, J. C.↗

GeneLab: A Systems Biology Platform for Spaceflight Omics Data

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. Resources to support large numbers of spaceflight investigations are limited. NASA's GeneLab project is maximizing the science output from these experiments by: (1) developing a unique public bioinformatics database that includes space bioscience relevant "omics" data (genomics, transcriptomics, proteomics, and metabolomics) and experimental metadata; (2) partnering with NASA-funded flight experiments through bio-sample sharing or sample augmentation to expedite omics data input to the GeneLab database; and (3) developing community-driven reference flight experiments. The first database, GeneLab Data System Version 1.0, went online in April 2015. V1.0 contains numerous flight datasets and has search and download capabilities. Version 2.0 will be released in 2016 and will link to analytic tools. In 2015 Genelab partnered with two Biological Research in Canisters experiments (BBRIC-19 and BRIC-20) which examine responses of Arabidopsis thaliana to spaceflight. GeneLab also partnered with Rodent Research-1 (RR1), the maiden flight to test the newly developed rodent habitat. GeneLab developed protocols for maxiumum yield of RNA, DNA and protein from precious RR-1 tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected. GeneLab is establishing partnerships with at least three planned flights for 2016. Organism-specific nationwide Science Definition Teams (SDTs) will define future GeneLab dedicated missions and ensure the broader scientific impact of the GeneLab missions. GeneLab ensures prompt release and open access to all high-throughput omics data from spaceflight and ground-based simulations of microgravity and radiation. Overall, GeneLab will facilitate the generation and query of parallel multi-omics data, and deep curation of metadata for integrative analysis, allowing researchers to uncover cellular networks as observed in systems biology platforms. Consequently, the scientific community will have access to a more complete picture of functional and regulatory networks responsive to the spaceflight environment.. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and enable emerging terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space. As a result, open access to the data will foster new hypothesis-driven research for future spaceflight studies spanning basic science to translational science.

proteomics↗

Exchange of Standardized Flight Dynamics Data

Spacecraft operations require the knowledge of the vehicle trajectory and attitude and also that of other spacecraft or natural bodies. This knowledge is normally provided by the Flight Dynamics teams of the different space organizations and, as very often spacecraft operations involve more than one organization, this information needs to be exchanged between Agencies. This is why the Navigation Working Group within the CCSDS (Consultative Committee for Space Data Systems), has been instituted with the task of establishing standards for the exchange of Flight Dynamics data. This exchange encompasses trajectory data, attitude data, and tracking data. The Navigation Working Group includes regular members and observers representing the participating Space Agencies. Currently the group includes representatives from CNES, DLR, ESA, NASA and JAXA. This Working Group meets twice per year in order to devise standardized language, methods, and formats for the description and exchange of Navigation data. Early versions of some of these standards have been used to support mutual tracking of ESA and NASA interplanetary spacecraft, especially during the arrival of the 2003 missions to Mars. This paper provides a summary of the activities carried out by the group, briefly outlines the current and envisioned standards, describes the tests and operational activities that have been performed using the standards, and lists and discusses the lessons learned from these activities.

standards↗

Validation of UARS Microwave Limb Sounder Temperature and Pressure Measurements

The accuracy and precision of the Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS) atmospheric temperature and tangent-point pressure measurements are described. Temperatures and tangent- point pressure (atmospheric pressure at the tangent height of the field of view boresight) are retrieved from a 15-channel 63-GHz radiometer measuring O2 microwave emissions from the stratosphere and mesosphere. The Version 3 data (first public release) contains scientifically useful temperatures from 22 to 0.46 hPa. Accuracy estimates are based on instrument performance, spectroscopic uncertainty and retrieval numerics, and range from 2.1 K at 22 hPa to 4.8 K at 0.46 hPa for temperature and from 200 m (equivalent log pressure) at 10 hPa to 300 m at 0.1 hPa. Temperature accuracy is limited mainly by uncertainty in instrument characterization, and tangent-point pressure accuracy is limited mainly by the accuracy of spectroscopic parameters. Precisions are around 1 K and 100 m. Comparisons are presented among temperatures from MLS, the National Meteorological Center (NMC) stratospheric analysis and lidar stations at Table Mountain, California, Observatory of Haute Provence (OHP), France, and Goddard Spaceflight Center, Maryland. MLS temperatures tend to be 1-2 K lower than NMC and lidar, but MLS is often 5 - 10 K lower than NMC in the winter at high latitudes, especially within the northern hemisphere vortex. Winter MLS and OHP (44 deg N) lidar temperatures generally agree and tend to be lower than NMC. Problems with Version 3 MLS temperatures and tangent-point pressures are identified, but the high precision of MLS radiances will allow improvements with better algorithms planned for the future.

Fishbein, E. F.↗

CHESS 2025: Spectrometer orthorectified at-sensor radiance from NEON AOP imaging spectroscopy surveys

This dataset provides Level 1 (L1) orthorectified at-sensor radiance derived from measurements collected by the Imaging Spectrometer-1 (NIS-1) onboard the NEON (National Ecological Observatory Network) Airborne Observation Platform (AOP) for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). NIS-1 captures light reflected from the Earth’s surface in 426 discrete wavelength bands as raw digital numbers (DNs; Level 0). These data are then calibrated to physical units (uW/cm²·sr·nm) following the processing steps described in the NEON Imaging Spectrometer Level 1B Calibrated Radiance Algorithm Theoretical Basis Document (ATBD; Gallery 2022). The data delivered here are the primary inputs for the surface reflectance product in “Custom surface reflectance, shade masks, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study” (Carroll et al. 2026). For intertemporal comparison, the radiance data here are most directly relatable to the v2 radiance data in “NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset” (Goulden et al. 2018), to which the same processing methodology was applied. Together, the radiance and reflectance data enable users to exploit the unique reflection signatures of different surface objects for land cover classification, foliar trait mapping, plant vigor assessment, water content estimation, trace-element identification, and other scientific applications. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. Within each domain, data are delivered by flightline as orthorectified and calibrated hyperspectral rasters in Hierarchical Data Format version 5 (HDF5) format, with radiance values provided in uW/cm²·sr·nm on a fixed, uniform Universal Transverse Mercator (UTM) grid at 1 meter spatial resolution. The radiance rasters include all 426 NIS-1 spectral bands, along with associated quality-assurance (QA) and diagnostic and ancillary layers needed for atmospheric correction workflows. Orthorectified radiance is produced from pushbroom spectrometer observations by applying NEON’s radiometric calibration (including bad pixel masking, dark subtract, dark pedestal shift correction, electronic panel ghost correction, grating ghost correction, deblur correction and flat-fielding) and spectral calibration (using spectral response function band centers and full-width at half-maximum intensity), followed by geolocation and regridding to the fixed grid. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

DFAT: A web-based toolkit for estimating demand flexibility in building-to-grid integration

Demand Flexibility Assessment Tool (DFAT) is an open source web-based tool that estimates the demand flexibility potential of common control strategies in commercial buildings. The toolkit features a demand flexibility estimation tool that contains two calculators, basic and advanced, based on the level of input of customer data. The basic version calculates demand shed metrics for the control strategy “global temperature adjustment” and “cycle on/off compressors” using customer building information, local weather data, and electrical meter data. The advanced version, which uses detailed HVAC equipment data, calculates demand flexibility metrics for control strategies such as static pressure reset, global temperature adjustment, and cycle on/off compressors. In addition to the demand flexibility estimation tool, this toolkit offers a benchmarking tool that helps facility operators, aggregators, and utility resource managers assess demand flexibility opportunities, quantify/verify performance, and compare their performance against that of their peers.

Leong, Michael↗

Westcott g factors extended to arbitrary neutron energy spectra

Westcott 𝑔 factors are used in Neutron Activation Analysis (NAA) and Prompt Gamma-ray Activation Analysis (PGAA) to evaluate the impact of non-1∕𝑣 behavior in the neutron-capture cross sections of certain nuclei on activation product yields. This non-1∕𝑣 behavior arises from the presence of neutron resonances in the neutron- capture cross sections that overlap with the source neutron spectrum at low (< 5 eV) energies. Historically, Westcott 𝑔 factors that have been cataloged for NAA and PGAA applications are the result of calculations that assume a Maxwellian neutron flux distribution with a given temperature. In this work, we use this approach with updated neutron-capture cross sections from the Evaluated Nuclear Data File, version VIII.1 (ENDF/B-VIII.1) to tabulate Westcott 𝑔 factor values for a broad range of Maxwellian distribution temperatures, comparing the results against currently-available 𝑔 factors from International Atomic Energy Agency tables and other sources. Here, it was discovered during this analysis that the use of guided thermal and cold-neutron beams at certain facilities necessitates an approach for evaluating Westcott 𝑔 factors based on arbitrary non-Maxwellian spectra. In this paper, we present an approach for calculating 𝑔 factors with user-specified neutron spectra, and we demonstrate these methods to obtain Westcott 𝑔-factors for guided- and cold-neutron beams at the Budapest Research Reactor and the Forschungsreaktor München II reactor. As part of this work, open-source software has been developed that can be used to perform these calculations for applications in PGAA and NAA experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Planetary data analysis and display system: A version of PC-McIDAS

We propose to develop a system for access and analysis of planetary data from past and future space missions based on an existing system, the PC-McIDAS workstation. This system is now in use in the atmospheric science community for access to meteorological satellite and conventional weather data. The proposed system would be usable by not only planetary atmospheric researchers but also by the planetary geologic community. By providing the critical tools of an efficient system architecture, newer applications and customized user interfaces can be added by the end user within such a system.

Limaye, Sanjay S.↗