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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Guide to Handle Electronic and Physical Records Requests for Service Innovation-Records Management Services (SI-RMS) Staff

The Electronic Records Management System (ERMS) is Los Alamos National Laboratory’s method for consolidating, tracking, and preserving valuable records according to National Archives and Records Administration (NARA) requirements. Like an online library catalog, the ERMS stores unclassified electronic records that are retrievable from a remote computer system, and the ERMS contains a list of unclassified physical record holdings (paper documents, audiovisual materials, photographs, etc.) that are stored in the LANL Records Center and may be checked out. This guide covers new processes that affect both physical and electronic records. Each process begins when an employee (referred to as the requester) submits a request through the AskIT ticketing system (askit.lanl.gov). A request may include submitting a record, retrieving a record, or destroying a record.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Distributed Order Recording Techniques for Efficient Record-and-Replay of Multi-threaded Programs

After all these years and all these other shared memory programming frameworks, OpenMP is still the most popular one. However, its greater levels of non-deterministic execution makes debugging and testing more challenging. The ability to record and deterministically replay the program execution is key to address this challenge. However, scalably replaying OpenMP programs is still an unresolved problem. In this paper, we propose two novel techniques that use Distributed Clock (DC) and Distributed Epoch (DE) recording schemes to eliminate excessive thread synchronization for OpenMP record and replay. Our evaluation on representative HPC applications with ReOMP, which we used to realize DC and DE recording, shows that our approach is 2-5x more efficient than traditional approaches that synchronize on every shared-memory access. Furthermore, we demonstrate that our approach can be easily combined with MPI-level replay tools to replay non-trivial MPI+OpenMP applications. We achieve this by integrating ReOMP into ReMPI, an existing scalable MPI record-and-replay tool, with only a small MPI-scale-independent runtime overhead.

Fu, Xiang↗
DOE OSTI2019

Physical similarity of the processes of laser thermochemical recording on thin metal films and modeling the recording of submicron structures

Laser thermochemical recording is a flexible method for direct writing the binary planar structures (for instance, diffractive optical elements) by a local laser-induced oxidation of thin metal films. Unfortunately, due to excess of influencing parameters, search for regimes of high-resoluted recording could be complicated. The presented article proposes the way to analyze the hard-to-reach regimes of laser recording by modeling them with more convenient regimes (with different geometric and/or thermochemical parameters) based on their physical similarity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Three phase spectral interferometry for recording high dynamic range optical waveforms with <1 ps resolution over >2 ns records applied to closed-loop pulse shaping

Herein we demonstrate, to our knowledge, a novel spectral interferometry technique that simultaneously captures three spectral interferograms of a signal waveform with a reference pulse. The measured performance is robust to nonidealities and ambient drifts by implementing a precisely calibrated 3 × 3 polarization maintaining (PM) splitter that provides three phase shift differences nominally spaced 120° apart. The system can achieve long record length by implementing three, high resolution, virtually imaged phase array (VIPA) spectrometers. Here, we experimentally implement this technique and demonstrate the measurement of waveforms with >2ns of record while maintaining <1ps resolution.

42 ENGINEERING↗
DOE OSTI2021

Black Carbon Deposited in Hariqin Glacier of the Central Tibetan Plateau Record Changes in the Emission from Eurasia

Black carbon (BC), by the combustion of fossil fuels and biomass, has profound effects on climate change and glacier retreat in industrial eras. In the present study, we report refractory BC (rBC) in an ice core spanning 1850–2014, retrieved from the Hariqin Glacier of the Tanggula Mountains in the central Tibetan Plateau, measured using a single particle soot photometer (SP2). The rBC concentration shows a three-fold increase since the 1950s. The mean rBC concentration was 0.71±0.52 ng mL-1 during 1850s–1940s and 2.11±1.60 ng mL-1 during 1950s–2010s. The substantial increase in rBC since the 1950s is consistent with rBC ice core records from the Tibetan Plateau and Eastern Europe. According to the predominant atmospheric circulation patterns over the glacier and timing of changes in regional emissions, the post-1950 amplification of rBC concentration in the central Tibetan Plateau most likely reflects increases in emissions in Eastern Europe, former USSR, the Middle East, and South Asia. Despite the low-level background rBC concentrations in the ice cores from the Tibetan Plateau, the present study highlights a remarkable increase in anthropogenic BC emissions in recent decades and the consequent influence on glaciers in the Tibetan Plateau.

Black carbon, Ice core, Tibetan Plateau, Industria↗
DOE OSTI2020

Development of Lipid-Coated Semiconductor Nanosensors for Recording of Membrane Potential in Neurons

In the past decade, optical imaging methods have significantly improved our understanding of the information processing principles in the brain. Although many promising tools have been designed, sensors of membrane potential are lagging behind the rest. Semiconductor nanoparticles are an attractive alternative to classical voltage indicators, such as voltage-sensitive dyes and proteins. Such nanoparticles exhibit high sensitivity to external electric fields via the quantum-confine Stark effect. Here we report the development of semiconductor voltage-sensitive nanorods (vsNRs) that self-insert into the neuronal membrane. To facilitate interaction of the nanorods with the membrane, we functionalized their surface with the lipid mixture derived from brain extract. We describe a workflow to detect and process the photoluminescent signal of vsNRs after widefield time-lapse recordings. We also present data indicating that vsNRs are feasible for sensing membrane potential in neurons at a single-particle level. This shows the potential of vsNRs for the detection of neuronal activity with unprecedentedly high spatial and temporal resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Closed Bay-Breeze Circulation and Its Lifecycle From TRACER With a New Orienteering Tape Recorder Diagram

A closed bay-breeze circulation (BBC) followed by a gulf-breeze front (GBF) was observed on 10 September 2022 during the Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) TRACER campaign. Using high-resolution X-band Scanning Cloud Radar (XSACR) and a newly developed orienteering tape recorder diagram, the study analyzed radar reflectivity and Doppler velocity to identify anomalies and track the evolution of these circulations. The BBC, a mesoscale system approximately 30-km long, 30-km wide, and 2-km deep, formed from enhanced horizontal convective rolls along the Galveston Bay coast, progressing northwestward under a 6 m s−1 onshore flow anomaly and reaching 1.5 km depth with return flow aloft. The inland penetration speed was 2 m s−1, driven by an observed 6-9 K land-water temperature contrast. The GBF, coupled to the BBC, intensified with additional southerly flow, penetrating further inland after the BBC collapsed. Passing over the TRACER field site, both fronts significantly impacted boundary layer thermodynamics, dynamics, and aerosol concentration. The BBC event exhibited four lifecycle stages-formation, development, maturation, and dissipation-driven by solar heating, wind field rotation, and interactions with convective eddies and the GBF. This study provides insights into the inland evolution of coastal breeze circulations and their interactions with environmental processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Search for Higgs boson pair production in the γγWW* channel using $pp$ collision data recorded at $\sqrt{s}$ $=13$ TeV with the ATLAS detector

Searches for non-resonant and resonant Higgs boson pair production are performed in the γγWW* channel with the final state of γγℓνjj using 36.1 fb -1 of proton–proton collision data recorded at a centre-of-mass energy of √s= 13 TeV by the ATLAS detector at the Large Hadron Collider. No significant deviation from the Standard Model prediction is observed. A 95% confidence-level observed upper limit of 7.7 pb is set on the cross section for non-resonant production, while the expected limit is 5.4 pb. A search for a narrow-width resonance X decaying to a pair of Standard Model Higgs bosons HH is performed with the same set of data, and the observed upper limits on σ(pp→X) × B(X→HH) range between 40.0 and 6.1 pb for masses of the resonance between 260 and 500 GeV, while the expected limits range between 17.6 and 4.4 pb. When deriving the limits above, the Standard Model branching ratios of the H→γγ and H→WW* are assumed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Record High Hydrogen Storage Capacity in the Metal–Organic Framework Ni 2 ( m -dobdc) at Near-Ambient Temperatures

Hydrogen holds promise as a clean alternative automobile fuel, but its on-board storage presents significant challenges due to the low temperatures and/or high pressures required to achieve a sufficient energy density. The opportunity to significantly reduce the required pressure for high density H 2 storage persists for metal-organic frameworks due to their modular structures and large internal surface areas. The measurement of H 2 adsorption in such materials under conditions most relevant to on-board storage is crucial to understanding how these materials would perform in actual applications, although such data have to date been lacking. In the present work, the metal-organic frameworks M 2 (m-dobdc) (M = Co, Ni; m-dobdc 4- = 4,6-dioxido-1,3-benzenedicarboxylate) and the isomeric frameworks M 2 (dobdc) (M = Co, Ni; dobdc 4- = 1,4-dioxido-1,3-benzenedicarboxylate), which are known to have open metal cation sites that strongly interact with H 2 , were evaluated for their usable volumetric H 2 storage capacities over a range of near-ambient temperatures relevant to on-board storage. Based upon adsorption isotherm data, Ni 2 (m-dobdc) was found to be the top-performing physisorptive storage material with a usable volumetric capacity between 100 and 5 bar of 11.0 g/L at 25 °C and 23.0 g/L with a temperature swing between -75 and 25 °C. Additional neutron diffraction and infrared spectroscopy experiments performed with in situ dosing of D 2 or H 2 were used to probe the hydrogen storage properties of these materials under the relevant conditions. Finally, the results provide benchmark characteristics for comparison with future attempts to achieve improved adsorbents for mobile hydrogen storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Challenges in Long-Term Records Preservation and Access - 19549

The US Department of Energy Office of Legacy Management (LM) mission includes preserving records and information about the nation's Cold War-era weapons projects and making that information available for years to come. As LM assumes responsibility for each project, records documenting operations and cleanup activities are absorbed into a central recordkeeping system. Each record category is governed by a federal retention requirement. Routine administrative records are kept just a few years, while the most important records have 'permanent' retention requirements and are transferred to the National Archives typically within 25 years of creation. It is relatively easy for LM to meet retention requirements for these routine and permanent records. LM's big preservation challenge is with records with tremendously long retention requirements. Records with 75-year retention requirements are common, and a small subset of LM records pertaining to waste disposal requires 150-year retention periods. LM must consider the best format for maintaining each of its records collections. Should physical records be boxed up for long-term storage, or should they be digitized? Each option has associated benefits, costs, and risks. Keeping records in paper format avoids digitizing expense and preserves the original media, but the paper must be maintained in a certified storage facility. A vermin infestation or sprinkler malfunction at a certified facility may be rare but could easily destroy records. Keeping the paper and making reference or backup electronic copies reduces the risk of loss but requires diligence and resources to keep the physical records and electronic versions synchronized. This becomes an overwhelming task in a database with millions of records. Entirely replacing paper records with digitized versions as electronic records introduces the risk that records could be lost due to a cybersecurity incident or made inaccessible by evolving technology. LM's early electronic records management efforts were limited to documents saved to PDF format. More recently, LM has embraced the benefits of maintaining records in native formats. (A spreadsheet includes formulas and other details lost when converted to a PDF file.) But whether the file is saved as a Microsoft Excel spreadsheet or PDF document, how do we ensure the file is readable in 75 or 150 years when these records meet their retention requirement? We have no way of knowing for sure from our 2019 vantage point-no more than we would expect to get good technology advice from someone 150 years ago. We cannot predict the technological future, but we can make sure our current electronic records environment is healthy and future ready. This includes making sure the electronic recordkeeping system is built on a modern platform and ensuring that each record in the system is saved in a current format. Quality standards are critical for electronic records to be future ready. Implementing quality involves an organization-wide approach to having consistently formatted file names and complete and descriptive metadata. Quality PDF documents are scanned to settings that ensure characters are machine-readable (with optical character recognition, or OCR). LM is currently replacing its electronic recordkeeping system and simultaneously modernizing its organizational approach to data management; it is replacing a traditional electronic records repository with a system that also manages records stored anywhere across the computer network. This new records management approach will require new thinking in how LM manages a dramatically increased volume of information across the network while not losing focus on its responsibility for long-term records preservation and access. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

USACE FUSRAP Records Management Challenges in the Digital Age - 20242

In late 2016, the U.S. Army Corps of Engineers (USACE) implemented a Headquarters-supported nationwide records management initiative managed by the USACE-New England District to address the digitization and organization of Formerly Utilized Sites Remedial Action Program (FUSRAP) project files. This initiative will prepare USACE FUSRAP for moving toward a fully electronic system of records management. Additionally, the records management initiative streamlines the process and prepares the Administrative Record (AR) and Permanent Record (PR) file for transfer from USACE to the U.S. Department of Energy (DOE)-Office of Legacy Management (LM) following project closeout. Over the past couple of years, USACE and DOE-LM have been working to finalize a joint guidance document to assist in the FUSRAP records transition process. However, there remain key records management topics that require further discussion and development. Specifically, these topics include the implementation, process, and procedure for the capture of social media records and compliance with Section 508 of the Rehabilitation Act of 1973 (29 USC 794d), as amended. Due to advances in technology and the ease of communication it provides, USACE is using social media more often to interface with the public than 5, 10 or 15 years ago. The identification and capture of these records are challenging because it requires each USACE district or producer of a record to track what has been released through social media so that it can be captured as part of the AR or PR. USACE is currently evaluating processes and procedures for social media records capture. This paper explores how social media is being used by USACE across FUSRAP projects and best practices for the capture of social media records. Public accessibility to the project AR is required under the Comprehensive Environmental Response, Compensation, and Liability Act, which USACE FUSRAP must follow. As USACE FUSRAP ARs are converted to a digital format, greater accessibility to the files can be provided through web sites or other electronic media. However, Section 508 of the Rehabilitation Act must be considered when releasing electronic files to the public. Under Section 508, government agencies must ensure that information is made available to the public in a format that provides equal access to persons with disabilities. This paper discusses the electronic records requirements under Section 508 and addresses broad implementation of compliance across large digital records sets. Records management challenges are presented in the context of the FUSRAP records management program; however, these records management considerations and best practices are applicable across all Federal agency records management programs. Examples presented will further aid in understanding electronic records requirements that may be included on new USACE FUSRAP contracts as well as upcoming National Archives Records Administration requirements that will move us toward an electronic government. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on data sourced from WestDAAT - Changed using a Site ID column to identify unique records to using aa combination of Site ID and Allocation ID - Removed the Water Management Area (WMA) column from the harmonized records. The replacement is a separate file which stores the relationship between allocations and WMAs. This allows for allocations to contribute to water right amounts to multiple WMAs during the subsequent cumulative process. - Added a column describing a water rights legal status - Added "Unspecified" was a water source category - Added an acre-foot (AF) column - Added a column for the classification of the right's owner v1.02 - Added a .RData file to the dataset as a convenience for anyone exploring our code. This is an internal file, and the one referenced in analysis scripts as the data objects are already in R data objects. v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description Here we present an updated database of Western U.S. water right records. This database provides consistent unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of seven broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of inter-sectoral water allocation changes though water markets (Grogan et al., *in review*). Specifically, the data were formatted for use as input to a process-based hydrologic model, Water Balance Model (WBM), with a water rights module (Grogan et al., *in review*). While this specific study motivated the development of the database presented here, water management in the U.S. West is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al., 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. West. We produced the water rights database presented here in four main steps: (1) data collection, (2) data quality control, (3) data harmonization, and (4) generation of cumulative water rights curves. Each of steps (1)-(3) had to be completed in order to produce (4), the final product that was used in the modeling exercise in Grogan et al. (*in review*). All data in each step is associated with a spatial unit called a Water Management Area (WMA), which is the unit of water right administration utilized by the state in which the right came from. Steps (2) and (3) required use to make assumptions and interpretation, and to remove records from the raw data collection. We describe each of these assumptions and interpretations below so that other researchers can choose to implement alternative assumptions an interpretation as fits their research aims. Motivation for Changing Data Sources The most significant change has been a switch from collecting the raw water rights directly from each state to using the water rights records presented in WestDAAT, a product of the Water Data Exchange (WaDE) Program under the Western States Water Council (WSWC). One of the main reasons for this is that each state of interest is a member of the WSWC, meaning that WaDE is partially funded by these states, as well as many universities. As WestDAAT is also a database with consistent categorization, it has allowed us to spend less time on data collection and quality control and more time on answering research questions. This has included records from water right sources we had previously not known about when creating v1.0 of this database. The only major downside to utilizing the WestDAAT records as our raw data is that further updates are tied to when WestDAAT is updated, as some states update their public water right records daily. However, as our focus is on cumulative water amounts at the regional scale, it is unlikely most records updates would have a significant effect on our results. The structure of WestDAAT led to several important changes to how HarWR is formatted. The most significant change is that WaDE has calculated a field known as `SiteUUID`, which is a unique identifier for the Point of Diversion (POD), or where the water is drawn from. This separate from `AllocationNativeID`, which is the identifier for the allocation of water, or the amount of water associated with the water right. It should be noted that it is possible for a single site to have multiple allocations associated with it and for an allocation to be able to be extracted from multiple sites. The site-allocation structure has allowed us to adapt a more consistent, and hopefully more realistic, approach in organizing the water right records than we had with HarDWR v1.0. This was incredibly helpful as the raw data from many states had multiple water uses within a single field within a single row of their raw data, and it was not always clear if the first water use was the most important, or simply first alphabetically. WestDAAT has already addressed this data quality issue. Furthermore, with v1.0, when there were multiple records with the same water right ID, we selected the largest volume or flow amount and disregarded the rest. As WestDAAT was already a common structure for disparate data formats, we were better able to identify sites with multiple allocations and, perhaps more importantly, allocations with multiple sites. This is particularly helpful when an allocation has sites which cross WMA boundaries, instead of just assigning the full water amount to a single WMA we are now able to divide the amount of water between the number of relevant WMAs. As it is now possible to identify allocations with water used in multiple WMAs, it is no longer practical to store this information within a single column. Instead the stAllocationToWMATab.csv file was created, which is an allocation by WMA matrix containing the percent Place of Use area overlap with each WMA. We then use this percentage to divide the allocation's flow amount between the given WMAs during the cumulation process to hopefully provide more realistic totals of water use in each area. However, not every state provides areas of water use, so like HarDWR v1.0, a hierarchical decision tree was used to assign each allocation to a WMA. First, if a WMA could be identified based on the allocation ID, then that WMA was used; typically, when available, this applied to the entire state and no further steps were needed. Second was the spatial analysis of Place of Use to WMAs. Third was a spatial analysis of the POD locations to WMAs, with the assumption that allocation's POD is within the WMA it should belong to; if an allocation still had multiple WMAs based on its POD locations, then the allocation's flow amount would be divided equally between all WMAs. The fourth, and final, process was to include water allocations which spatially fell outside of the state WMA boundaries. This could be due to several reasons, such as coordinate errors / imprecision in the POD location, imprecision in the WMA boundaries, or rights attached with features, such as a reservoir, which crosses state boundaries. To include these records, we decided for any POD which was within one kilometer of the state's edge would be assigned to the nearest WMA. Other Changes WestDAAT has Allowed In addition to a more nuanced and consistent method of assigning water right's data to WMAs, there are other benefits gained from using the WestDAAT dataset. Among those is a consistent categorization of a water right's legal status. In HarDWR v1.0, legal status was effectively ignored, which led to many valid concerns about the quality of the database related to the amounts of water the rights allowed to be claimed. The main issue was that rights with legal status' such as "application withdrawn", "non-active", or "cancelled" were included within HarDWR v1.0. These, and other water rights status' which were deemed to not be in use have been removed from this version of the database. Another major change has been the addition of the "unspecified water source category. This is water that can come from either surface water or groundwater, or the source of which is unknown. The addition of this source category brings the total number of categories to three. Due to reviewer feedback, we decided to add the acre-foot (AF) column so that the data may be more applicable to a wider audience. We added the ownerClassification column so that the data may be more applicable to a wider audience. File Descriptions The dataset is a series of various files organized by state sub-directories. In addition, each file begins with the state's name, in case the file is separate from its sub-directory for some reason. After the state name is the text which describes the contents of the file. Here is each file described in detail. Note that st is a placeholder for the state's name. stFullRecords_HarmonizedRights.csv: A file of the complete water records for each state. The column headers for each of this type of file are: state - The name of the state to which the allocations belong to. FIPS - The two digit numeric state ID code. siteID - The site location ID for POD locations. A site may have multiple allocations, which are the actual amount of water which can be drawn. In a simplified hypothetical, a farm stead may have an allocation for "irrigation" and an allocation for "domestic" water use, but the water is drawn from the same pumping equipment. It should be noted that many of the site ID appear to have been added by WaDE, and therefore may not be recognized by a given state's water rights database. allocationID - The allocation ID for the water right. For most states this is the water right ID, and what is recommended to use should a right be looked up on a given state's water rights database. The water amounts associated with these IDs tend to be finer scaled than those associated with siteID. It should be noted that some allocations may be extracted from multiple sites, particularly for larger Places of Use. ownerClassification - A classification of the types of owners for water rights. The most common is `Private` which incorporates a wide range of entities. Several classifications would be grouped into a government category, most of which are for the U.S. Federal Government. These allocations could be listed as "Federal", "United States of America", or as the names of any number of federal agencies. The last major grouping of entities is for "Native American"s. priorityDate - The date we use as the water right priority date for our modeling analysis. This is the legal priority date when it is available. However, for some rights, specifically from California and New Mexico, we used a pseudo priority date (e.g. well completion date or start of well drilling date) when a legal priority date was not available. The most questionable dates come from New Mexico, where the only date associated with certain water right records was the date the allocation was recorded in the database. As the allocation record creation tended to be within a few months of the filing of the application of the water right, from manually double checking the water rights, and our analysis focuses on aggregating water rights on the timescale of years, we determined it was acceptable to use such dates to include as many records as possible. primaryBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories WestDAAT. This column is the original WaDE category for the primary water use at the PoD site. allocationBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories for WestDAAT. This column is the original WaDE category

Economics↗
DOE OSTI2023

Reassessing long-standing meteorological records: an example using the national hottest day in Ireland

This analysis highlights the potential value in reanalysing early national meteorological records from around the world. These were oftentimes measured via techniques that preceded standardisation of instrumentation and methods of observation and thus could be subject to considerable biases and uncertainties. This analysis uses the techniques pioneered by WMO record assessment teams. The highest currently recognised air temperature (33.3 °C) ever recorded in the Republic of Ireland was logged at Kilkenny Castle in 1887. The original observational record however no longer exists. Given that Ireland is now the only country in Europe to have a national heat record that was set in the 19th century, a reassessment of the verity of this record is both timely and valuable. The present analysis undertakes a fundamental reassessment of the plausibility of the 1887 temperature record using methods similar to those used to assess various weather extremes under WMO auspices over recent years. Specifically, we undertake an inter-station reassessment using sparse available records and make recourse to the new and improved 20CRv3 sparse-input reanalysis product. Neither surrounding available stations nor the reanalysis offer substantive support for the Kilkenny record of 33.3 °C being correct. Moreover, recent data rescue efforts have uncovered several earlier extreme values, one of which exceeds the Kilkenny value (33.5 °C on 16 July 1876 recorded at the Phoenix Park). However, the sparsity of early observational networks, a distinct lack of synoptic support from 20CRv3 for many of the extreme heat values, and the fact that these measurements were obtained using non-standard exposures lead us to conclude that there is grossly insufficient evidence to support any of these 19th century extremes as robust national heat record candidates. Data from the early 20th century onwards benefit from a denser network of stations undertaking measurements in a more standardised manner, many under the direct auspices of Met Éireann and its predecessors, adhering to WMO guidance and protocols. This enables more robust cross-checking of records. We argue that the Met Éireann-recognised 20th century heat record from Boora in 1976 is verified as the most plausible robust national temperature record based upon the synoptic situation and comparisons with nearby neighbouring stations. This measurement of 32.5°C thus likely constitutes the highest reliably recorded temperature measurement in the Republic of Ireland. Ultimately, the formal decision on any reassessment and reassignment of the national record rests with the national meteorological service, Met Éireann.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two-digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use(s) from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to include within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state. For those whom may be interested in exploring our code more in depth, we are also making available an internal data file for convenience. The file is in .RData format and contains everything described above as well as some minor additional objects used within the code calculating the cumulative curves. For completeness, here is a detailed description of the various objects which can be found within the .RData file: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. This object holds the the data that is exported to created the xxGroundwaterHarmonizedRights.csv files. rightsByState_surface: A list of data frames with the cleaned surface water rights collected from each state. This object holds the the data that is exported to created the xxSurfaceWaterHarmonizedRights.csv files. fullRightsRecs: A list of the combined groundwater and surface water records for each state. This object holds the the data that is exported to created the xxFullHarmonizedRights.csv files. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page. The code related to the creation of this dataset can be viewed within HarDWR GitHub Repository/dataHarmonization.

Economics↗
DOE OSTI2023

DATASET RELEASE AND QUALITY CONTROL REVIEW OF LIVERMORE NEVADA NETWORK (LNN) RECORDINGS OF A SUBSET OF NEVADA NUCLEAR SECURITY SITE NUCLEAR EXPLOSIONS FROM 1979 TO 1992.

Geophysical research on historical nuclear tests is an important aspect of future monitoring capabilities in seismic research. This research is challenging due to the limited number of digital seismic recordings during the peak of nuclear testing (1945-1992). These limited records are unique and non-reproducible data with potential high research impact. Releasing available nuclear explosion seismic records to the explosion monitoring community is thus of high value and is the motivation for this dataset release. The target of this effort was on compilation and quality control of regional seismic records of nuclear explosions recorded on Lawrence Livermore National Laboratory stations ELK, KNB, LAC, and MNV, known collectively as the Livermore National Network (LNN) (Figure 1). LNN was established in the early 1960s for the primary purpose of monitoring underground nuclear testing at the former Nevada Test Site (NTS), now known as the Nevada Nuclear Security Site (NNSS) following the signing of the Limited Test Ban Treaty (LTBT). LNN consisted initially of short-period vertical component Benioff’s recorded on film located at Mina, NV (MNV) and Kanab, Utah (KNB). LNN added two additional stations at Landers, CA (LAC) and Elko, NV (ELK) in 1967 and upgraded equipment to broadband seismometers recorded on frequency modulation (FM) tapes from 1967-1979, followed by digital recordings after 1979 (Jarpe, 1989). The digital recordings were on a variety of now obsolete media, including 9-track, Exabyte, and DAT tapes. Jarpe (1989) describes the seismic station instrumentation details over the period of deployment. LNN recorded valuable non-repeatable unique data of several hundreds of nuclear explosions at NNSS, as well as earthquakes and chemical and mining explosions (Walter, 2020). The details of these nuclear tests are provided in the Department of Energy Report NV-209 Rev 16 (DOE, 2015).

58 GEOSCIENCES↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to included within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state.

Economics↗