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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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At least 91 records · Page 5

Constraining Clouds and Convective Parameterizations in A Climate Model Using Paleoclimate Data

Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.

cloud and convective parameterization↗

Global Assessment of the Capability of Satellite Precipitation Products to Retrieve Landslide-Triggering Extreme Rainfall Events

Rainfall-induced landsliding is a global and systemic hazard that is likely to increase with the projections of increased frequency of extreme precipitation with current climate change. However, our ability to understand and mitigate landslide risk is strongly limited by the availability of relevant rainfall measurements in many landslide prone areas. In the last decade, global satellite multisensor precipitation products (SMPP) have been proposed as a solution, but very few studies have assessed their ability to adequately characterize rainfall events triggering landsliding. Here, we address this issue by testing the rainfall pattern retrieved by two SMPPs (IMERG and GSMaP) and one hybrid product [Multi-Source Weighted-Ensemble Precipitation (MSWEP)] against a large, global database of 20 comprehensive landslide inventories associated with well-identified storm events. We found that, after converting total rainfall amounts to an anomaly relative to the 10-yr return rainfall R*, the three products do retrieve the largest anomaly (of the last 20 years) during the major landslide event for many cases. However, the degree of spatial collocation of R* and landsliding varies from case to case and across products, and we often retrieved R* > 1 in years without reported landsliding. In addition, the few (four) landslide events caused by short and localized storms are most often undetected. We also show that, in at least five cases, the SMPP’s spatial pattern of rainfall anomaly matches landsliding less well than does ground-based radar rainfall pattern or lightning maps, underlining the limited accuracy of the SMPPs. We conclude on some potential avenues to improve SMPPs’ retrieval and their relation to landsliding.

Extreme events↗

Leveraging the 2024 Solar Eclipse to Enhance Science Learning through Citizen Science

The solar eclipse on April 8, 2024, provided a rare and compelling opportunity for educators and students to engage in hands-on citizen science. Two NASA Science Activation projects GLOBE Mission Earth (GME) and NASA Earth Science Education Collaborative (NESEC) partnered together to provide a unique professional development experience for educators interested in the eclipse. They invited educators to participate in a specialized 5-week online workshop designed to engage the educators in Global Learning and Observations to Benefit the Environment (GLOBE) citizen science about the eclipse. The workshop was designed to support their certification as GLOBE educators and develop their knowledge, skills, and confidence in conducting a GLOBE investigation. Over 60 educators from across the United States took part in this workshop, which focused on investigating the eclipse by collecting and analyzing atmospheric data. The GLOBE Program promotes environmental and scientific literacy by enabling participants to collect Earth science data and contribute it to a global database accessible for research. The 2024 GLOBE Eclipse workshop trained educators in specific GLOBE protocols—Clouds, Air Temperature, and Surface Temperature—using the GLOBE Eclipse tool integrated into the GLOBE Observer app. This training was supplemented with guidance on engaging students in authentic scientific research and creating research posters to present their findings. The workshop aimed to enhance educators’ skills and confidence in integrating GLOBE protocols into their teaching practices. It addressed several key areas outlined in the National Academies' report on Learning through Citizen Science, including scientific context, nature of participation, and project infrastructure. Educators learned about the atmospheric effects of solar eclipses and were trained to use scientific tools and data analysis methods relevant to their research. They also engaged in live sessions and asynchronous activities, practicing data collection and analysis with real-time feedback. Survey results from the workshop highlighted that participants were primarily motivated by the desire to better use data in their classrooms and improve their proficiency with the GLOBE Observer app. Post-workshop evaluations showed significant increases in educators' confidence regarding their ability to conduct and guide scientific research. Participants reported feeling well-prepared to use the GLOBE Observer app for data collection and were successful in integrating their eclipse observations into classroom activities. Participants also valued the opportunity to contribute to authentic science through GLOBE, which involved observing atmospheric changes such as air temperature fluctuations and cloud cover alterations during the eclipse. The success of the workshop is evident in the increased confidence and skill levels of educators, as well as the publication of research posters on the GLOBE Mission Earth Student Research webpage.This session will discuss how the GLOBE Eclipse workshop series effectively utilized the unique context of the solar eclipse to enhance science education through citizen science. By adhering to the principles outlined in the Learning through Citizen Science framework, the workshop successfully engaged educators and students in meaningful scientific practices, demonstrating the potential of citizen science to enrich science education and foster a deeper understanding of Earth systems.

Jessica Taylor↗

Global Inter-Basin Hydrological Transfer Database

This document describes a global database of inter-basin hydrological transfers that has been used by the University of New Hampshire Water Balance Model for several years. The database has focussed primarily on large scale water transfers that are built, under-construction, or proposed.

Hydrological Infrastructure↗

Energy Storage Policy Summaries for the Global Energy Storage Database

This report includes energy storage policy analysis from six states: Arizona, California, Massachusetts, Nevada, New Mexico, and New York. These summaries offer prototypes for summaries that will subsequently be prepared for all 50 states (and territories). There is presently a shortage of comprehensive energy storage policy analysis that public utility regulators can call upon to inform policymaking in their own jurisdictions. The state policy summaries that will be offered publicly on the Global Energy Storage Database (GESDB) will include analysis on the executive directives, legislation, regulations pertaining to energy storage that have been adopted by an individual state, along with perspective on the remaining policy issues pertaining to storage that a state will be likely to address in the future. It is anticipated that public utility regulators in particular will find the database to be a useful resource in benchmarking policy approaches critical to the continued development of an energy storage marketplace in the U.S., including policy approaches specific to storage and renewables procurement targets, interconnection standards, valuation of energy storage, rate reform and tariff design specific to energy storage, consideration of multiple uses for storage at the distribution level, and potential revisions to existing state net metering programs to accommodate an expected growth of energy storage technologies.

25 ENERGY STORAGE↗

Global Carbon Consumption Database for Wildland Fire

Fire significantly impacts both human-altered and wild landscapes on national and global scales. Though often devastating, wildland fires naturally reduce fuels, preventing larger wildfires. However, their smoke can harm human health locally and globally. To understand its impact on air quality and health, quantifying the emissions released into the atmosphere is crucial. To accurately model fire emissions, understanding fuel characteristics and burning conditions is crucial, as they vary with the fuelbed type and fire weather. For example, savanna fires have lower carbon loading and intensity but spread quickly, while boreal forest fires burn longer and release more carbon due to higher loading. Hotter, drier conditions increase fuel consumption and smoke plume height. Fire weather and available fuel are the key drivers of emissions.

Emily Gargulinski↗

Evaluation of Global Fire Weather Database Reanalysis and Short-Term Forecast Products

Daily Fire Weather Index (FWI) System components calculated from the NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), are compared to FWI calculations from a global network of weather stations over 2004–2018, and short-term, experimental (8 d) daily FWI forecasts are evaluated for their skill across the Terrestrial Ecoregions of the World for 2018. FWI components from MERRA-2 were, in general, biased low compared to station data, but this reflects a mix of coherent low and high biases of different magnitudes. Biases in different MERRA-2 FWI components were related to different biases in weather input variables for different regions, but temperature and relative humidity biases were the most important overall. FWI forecasts had high skill for 1–2 d lead times for most of the world. For longer lead times, forecast skill decreased most quickly at high latitudes and was most closely related to decreasing skill of relative humidity forecasts. These results provide a baseline for the evaluation and use of fire weather products calculated from global analysis and forecast fields.

Global Fire Weather Database↗

A Global Building Occupant Behavior Database

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 4.

To address the need for a centralized root trait database, we compiled the Fine-Root Ecology Database (FRED) from published and unpublished data sources. We have continued to add to the FRED database since the release of FRED 1.0 in 2017, followed by 2.0 in 2018, and 3.0 in 2021. This new release of FRED 4.0 now has 213,941 observations of 238 root traits, for a combined total of roughly 3.4 million data fields for root traits and ancillary data together. FRED 4.0 has 39.8% more root trait observations than FRED 3.0 and a 34.4% increase in unique data sources. This release of FRED 4.0 also includes significant increases in geographic regions that have long been underrepresented in global datasets, notably in the tropical low latitudes. Ancillary data on associated site, vegetation, edaphic, and climatic conditions from across the globe have also increased concurrently with root trait observations. FRED is focused on fine roots (traditionally defined as roots less than 2 mm in diameter), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations. Despite this fine-root focus, FRED accepts data collected from roots of all sizes and contains observations of many root classes including coarse roots. Data collection will continue for the foreseeable future. The FRED4_Entire_Database_2026.csv file is the flat csv data file for FRED 4.0, and the FRED4_dd.csv file is the data dictionary of all columns available in FRED, including column IDs, column names, definitions, and unit (where applicable).

54 ENVIRONMENTAL SCIENCES↗

Global Oil & Gas Features Database

This submission contains a zip file with the developed Global Oil & Gas Features Database (as an ArcGIS geodatabase). Access the technical report describing how this database was produced using the following link: https://edx.netl.doe.gov/dataset/development-of-an-open-global-oil-and-gas-infrastructure-inventory-and-geodatabase This data can be viewed as a web map application at the following link: https://edx.netl.doe.gov/dataset/global-oil-gas-infrastructure-features-database-edx-spatial-webmap Acknowledgements: This work was performed under a CRADA between NETL and EDF, and was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.

Database↗

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 2.

The second version of the Fine-Root Ecology Database is available for download! Download the full FRED 2.0 data set, user guidance document, map, and list of data sources here. Prior to downloading the data, please read and follow the Data Use Guidelines, and it's worth checking out some tips for using FRED before you begin your analyses. Also, see here for an updating list of corrections to FRED 2.0.

54 ENVIRONMENTAL SCIENCES↗

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 3.

To address the need for a centralized root trait database, we compiled the Fine-Root Ecology Database (FRED) from published and unpublished data sources. We have continued to add to the FRED database since the release of FRED 2.0 in 2018, and a new version of FRED is now available. FRED 3.0 has more than 150,000 observations of more than 330 root traits, with data collected from more than 1400 data sources. FRED 3.0 has 45% more root trait observations than FRED 2.0, particularly in the categories of root anatomy, morphology, and microbial associations; ancillary data on associated site, vegetation, edaphic, and climatic conditions from across the globe have also increased concurrently. FRED is focused on fine roots (traditionally defined as roots less than 2 mm in diameter), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations. However, FRED accepts data collected from roots of all sizes, and already contains several observations of coarse roots. Data collection will continue for the foreseeable future.

54 ENVIRONMENTAL SCIENCES↗

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 1

To address the need for a centralized root trait database, we are compiling the Fine-Root Ecology Database (FRED) from published literature and unpublished data. FRED Version 1 (FRED 1.0) currently houses more than 70,000 observations of root traits and their associated site, vegetation, edaphic, and climatic conditions from across the globe (see image below, which shows the more than 1000 distinct locations associated with observations in FRED 1.0). Data collection is ongoing and will continue for the foreseeable future. The more than 300 root traits currently housed in FRED 1.0 are described in detail here. FRED is focused on fine roots (less than 2 mm), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations.

54 ENVIRONMENTAL SCIENCES↗

Optimal stomatal behaviour around the world

Stomatal conductance (g s ) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model 1 and the leaf and wood economics spectrum 2,3 . We also demonstrate a global relationship with climate. In conclusion, these findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.

54 ENVIRONMENTAL SCIENCES↗

Defending our public biological databases as a global critical infrastructure

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world’s primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly “retrofitted” mitigations. Furthermore this Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Lightning Enriched Global Precipitation Feature Database

The Tropical Rainfall Measurement Mission (TRMM) has provided a wealth of insight about lightning and precipitation in the tropics. However TRMM did not provide coverage outside the tropics and sub-tropics (i.e., beyond ±38°latitude), and hence it was unable to sample the lightning activity and precipitation features over a large fraction of mid-latitude continents and oceans, including extratropical cyclone storm tracks. The Global Precipitation Measurement (GPM) mission picks up where TRMM left off in that it provides information on precipitation features in the mid-and high latitudes (up to 65°N/S). However, GPM lacks a lightning instrument that can provide additional insights into mid-latitude thunderstorm activity and distribution. Hence we integrate observations from coincident the ISS Lightning Imaging Sensor (LIS) and the World Wide Lightning Location Network (WWLLN) observations with measurements from the GPM constellation of satellites, in particular to extend the existing GPM Precipitation Feature (PF) database so its data parameters are similar to that of the TRMM PF database (i.e., precipitation + lighting). Currently, WWLLN and ISS-LIS lightning have been collocated into precipitation features defined from GPM core satellite and constellation satellites observations.

Precipitation↗

A New Global River Network Database for Macroscale Hydrologic modeling

Coarse resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical Dominant River Tracing (DRT) algorithm for automated extraction and spatial upscaling of basin flow directions and river networks using fine-scale hydrography inputs (e.g., flow direction, river networks, and flow accumulation). The DRT was initially applied using HYDRO1K baseline fine-scale hydrography inputs and the resulting upscaled global hydrography maps were produced at several spatial scales, and verified against other available regional and global datasets. New baseline fine-scale hydrography data from HydroSHEDS are now available for many regions and provide superior scale and quality relative to HYDRO1K. However, HydroSHEDS does not cover regions above 60°N. In this study, we applied the DRT algorithms using combined HydroSHEDS and HYDRO1K global fine-scale hydrography inputs, and produced a new series of upscaled global river network data at multiple (1/16° to 2°) spatial resolutions in a consistent (WGS84) projection. The new upscaled river networks are internally consistent and congruent with the baseline fine-scale inputs. The DRT results preserve baseline fine-scale river networks independent of spatial scales, with consistency in river network, basin shape, basin area, river length, and basin internal drainage structure between upscaled and baseline fine-scale hydrography. These digital data are available online for public access (ftp://ftp.ntsg.umt.edu/pub/data/DRT/) and should facilitate improved regional to global scale hydrological simulations, including runoff routing and river discharge calculations.

macroscale hydrological modeling↗