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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Atmospheric H 2 observations from the NOAA Cooperative Global Air Sampling Network

Abstract. The NOAA Global Monitoring Laboratory (GML) measures atmospheric hydrogen (H2) in grab samples collected weekly as flask pairs at over 50 sites in the Cooperative Global Air Sampling Network. Measurements representative of background air sampling show higher H2 in recent years at all latitudes. The marine boundary layer (MBL) global mean H2 was 552.8 ppb in 2021, 20.2 ± 0.2 ppb higher compared to 2010. A 10 ppb or more increase over the 2010–2021 average annual cycle was detected in 2016 for MBL zonal means in the tropics and in the Southern Hemisphere. Carbon monoxide measurements in the same-air samples suggest large biomass burning events in different regions likely contributed to the observed interannual variability at different latitudes. The NOAA H2 measurements from 2009 to 2021 are now based on the World Meteorological Organization Global Atmospheric Watch (WMO GAW) H2 mole fraction calibration scale, developed and maintained by the Max Planck Institute for Biogeochemistry (MPI-BGC), Jena, Germany. GML maintains eight H2 primary calibration standards to propagate the WMO scale. These are gravimetric hydrogen-in-air mixtures in electropolished stainless steel cylinders (Essex Industries, St. Louis, MO), which are stable for H2. These mixtures were calibrated at the MPI-BGC, the WMO Central Calibration Laboratory (CCL) for H2, in late 2020 and span the range 250–700 ppb. We have used the CCL assignments to propagate the WMO H2 calibration scale to NOAA air measurements performed using gas chromatography and helium pulse discharge detector instruments since 2009. To propagate the scale, NOAA uses a hierarchy of secondary and tertiary standards, which consist of high-pressure whole-air mixtures in aluminum cylinders, calibrated against the primary and secondary standards, respectively. Hydrogen at the parts per billion level has a tendency to increase in aluminum cylinders over time. We fit the calibration histories of these standards with zero-, first-, or second-order polynomial functions of time and use the time-dependent mole fraction assignments on the WMO scale to reprocess all tank air and flask air H2 measurement records. The robustness of the scale propagation over multiple years is evaluated with the regular analysis of target air cylinders and with long-term same-air measurement comparison efforts with WMO GAW partner laboratories. Long-term calibrated, globally distributed, and freely accessible measurements of H2 and other gases and isotopes continue to be essential to track and interpret regional and global changes in the atmosphere composition. The adoption of the WMO H2 calibration scale and subsequent reprocessing of NOAA atmospheric data constitute a significant improvement in the NOAA H2 measurement records.

Pétron, Gabrielle↗
DOE OSTI2026

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). This data record spans from 1981 to 2024 using data from NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18, -19 and S-NPP. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗
DOE OSTI2025

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5. This data record spans from 1981 to 2018 using data from eight NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18 and -19. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR Version 5 products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗
DOE OSTI2024

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY↗
DOE OSTI2025

NOAA PSL Microwave Radiometer Block Island / Thermodynamic retrievals TROPoe

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on the Block Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗
DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗
DOE OSTI2018

Contiguous US summer maximum temperature and heat stress trends in CRU and NOAA Climate Division data plus comparisons to reanalyses

Abstract Warming is a major climate change concern, but the impact of high maximum temperatures depends upon the air’s moisture content. Trends in maximum summertime temperature, moisture, and heat index are tracked over three time periods: 1900–2011, 1950–2011, and 1979–2011; these trends differ notably from annual temperature trends. Trends are emphasized from two CRU datasets (CRUTS3.25 and CRUTS4.01) and two reanalyses (ERA-20C and 20CRv2). Maximum temperature trends tend towards warming that is stronger over the Great Lakes, the interior western and the northeastern contiguous United States. A warming hole in the Midwest generally decreases in size and magnitude when heat stress trends are calculated because the region has increasing moisture. CRU and nearly all reanalyses find cooling in the northern high plains that is not found in NOAA Climate Division trends. These NOAA trends are captured better by CRUTS401. Moistening in the northeast amplifies the heat stress there. Elsewhere the moisture trends are less clear. Drying over northern Texas (after 1996) in CRUTS401 translates into decreasing heat stress there (less so in CRUTS325). Though other reanalyses are not intended for long-term trends, MERRA-2 and ERA-Interim match observed trends better than other reanalyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NOAA National Centers for Environmental Information Fisheries Acoustics Archive Network Deep Dive

EPOC uses the Deep Dive process to discuss and analyze current and planned science use cases and anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Deep Dives help ensure that key stakeholders have a common understanding of the issues and the actions that a campus or regional network may need to undertake to offer solutions. The EPOC team leads the effort and relies on collaboration with the hosting site or network, and other affiliated entities that participate in the process. EPOC organizes, convenes, executes, and shares the outcomes of the review with all stakeholders. Between May 2021 and August 2021, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from the National Oceanic and Atmospheric Administration (NOAA)'s N-Wave (the Enterprise network that supports the NOAA mission) and National Centers for Environmental Information (NCEI)'s Fisheries Acoustics Archive for the purpose of a recording a Deep Dive into research drivers. The goal of these meetings was to help characterize the requirements for the research use case, and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Comparison of X1 (OLD) and X3 (NEW) Aerosol Observing Systems at the North Slope of Alaska NOAA Observatory

This report describes a comparison of the overlapping X1 and X3 Aerosol Observing Systems (AOS) at the North Slope of Alaska (NSA) observatory. Due to structural issues with the original observatory building, the National Oceanic and Atmospheric Administration (NOAA) funded the design and construction of a new observatory building. Construction began in 2019 and was completed in 2020. The now decommissioned old NOAA Barrow Observatory (BRW) housed the AOS referred to as an NSA external site X1 from October 1997 through August 2021. A new observatory building next door housed the AOS referred to as an NSA external site X3 starting in October 2020. In this document we will refer to the original observatory system measurements as 'OLD' and the measurements in the new building as 'NEW'.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Reanalysis of NOAA H 2 observations: implications for the H 2 budget

Abstract. Hydrogen (H2) is a promising low-carbon alternative to fossil fuels for many applications. However, significant gaps in our understanding of the atmospheric H2 budget limit our ability to predict the impacts of greater H2 usage. Here we use NOAA H2 dry air mole fraction observations from air samples collected from ground-based and ship platforms during 2010–2019 to evaluate the representation of H2 in the NOAA GFDL-AM4.1 atmospheric chemistry-climate model. We find that the base model configuration captures the observed interhemispheric gradient well but underestimates the surface concentration of H2 by about 10 ppb. Additionally, the model fails to reproduce the 1–2 ppb yr−1 mean increase in surface H2 observed at background stations. We show that the cause is most likely an underestimation of current anthropogenic emissions, including potential leakages from H2-producing facilities. We also show that changes in soil moisture, soil temperature, and snow cover have most likely caused an increase in the magnitude of the soil sink, the most important removal mechanism for atmospheric H2, especially in the Northern Hemisphere. However, there remains uncertainty due to fundamental gaps in our understanding of H2 soil removal, such as the minimum moisture required for H2 soil uptake, for which we performed extensive sensitivity analyses. Finally, we show that the observed meridional gradient of the H2 mixing ratio and its seasonality can provide important constraints to test and refine parameterizations of the H2 soil sink.

Paulot, Fabien (ORCID:0000000175344922)↗
DOE OSTI2018

NOAA Air Resources Laboratory Atmospheric Turbulence and Diffusion Division Contribution to LAFE Field Campaign Report

The Land-Atmosphere Feedback Experiment (LAFE) was conducted between 1 and 31 August, 2017 at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory. The main scientific goal of LAFE was to investigate feedbacks occurring between different land surface types and the overlying atmosphere to improve turbulence parameterizations in numerical weather prediction models. LAFE collaborators included scientists from the following institutions: Cleveland State University Cooperative Institute for Meteorological Satellite Studies (CIMSS) Cooperative Institute for Research in Environmental Sciences (CIRES) Leibniz University Institute of Meteorology and Climatology Marquette University NASA Goddard Space Flight Center National Center for Atmospheric Research (NCAR) National Severe Storms Laboratory (NSSL) NOAA Earth System Research Laboratory (ESRL) Pacific Northwest National Laboratories (PNNL) University of Hohenheim Institute of Physics and Meteorology University of Tennessee Space Institute (UTSI). In addition to helping plan the scientific objectives of LAFE, collaborators deployed several lidars (i.e., temperature, water, vapor, and wind) and remote-sensing instruments (e.g., microwave radiometers, atmospheric emitted radiance interferometers [AERIs], etc.) to complement the suite of instrument platforms already present at the SGP site. The measurement platforms, as well as scientific objectives of LAFE, are summarized in Wulfmeyer et al. (2018). To complement these platforms, the NOAA Atmospheric Turbulence and Diffusion Division (ATDD) installed micrometeorological towers to continuously measure fluxes of momentum, sensible heat, latent heat, and CO 2 at 2 m and 10 m above ground level (AGL) at three sites during LAFE. Tower measurements also included temperature, humidity, wind speed and direction, pressure, rainfall, soil temperature, and soil moisture. The three micrometeorological towers were installed between 9 and 13 July, 2017 and were removed between 12 and 14 September, 2017. During the experiment, the footprint of Tower 1 included a mixture of soybean and grassland that transitioned to mature soybean crop during the second half of the experiment. Tower 2’s footprint encompassed a field of grazed pasture, and Tower 3’s footprint was a mature soybean crop. The meteorological and flux measurements from these towers were/are being used to: Increase the spatial density of measurement platforms that were already available at the ARM facility and that were deployed during LAFE Improve the characterization of surface fluxes around the SGP site Explore the validity of applying Monin-Obukhov Similarity Theory (MOST) over different land surface types and improve knowledge of flux-gradient relationships Provide initial conditions and be used for verification for large-eddy simulations (LES) Evaluate numerical weather prediction models, e.g., the High-Resolution Rapid Refresh (HRRR), to identify and correct for biases within these models Evaluate the role of low-level advection at each site, which would be present in the flux-divergence data sets obtained from the three towers.

Southern Great Plains, unmanned aerial systems, su↗
DOE OSTI2026

Post-processed surface meteorological, air-sea flux, SST, wave, and ship navigation/position merged data from NOAA Ship Pisces

These are post-processed surface data from the NOAA Ship Pisces, merged from several instruments. They consist of meteorological, ocean, ship navigation/position, and surface air-sea flux quantities calculated at three different time frequencies. Because the averaging of directions can be complex, they are provided as a courtesy. R1 in the filename indicates "revision 1" or version 1. R2 will include surface waves (TBD).

17 WIND ENERGY↗
DOE OSTI2022

Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar Data

Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter D m from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. Here, this estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

An Analysis of Coordinated Observations from NOAA’s Ronald H. Brown Ship and G-IV Aircraft in a Landfalling Atmospheric River over the North Pacific during CalWater-2015

Using a diverse suite of mobile observing platforms deployed on NOAA’s Ronald H. Brown (RHB) research vessel and G-IV research aircraft during the CalWater-2015 field campaign, this study describes the structure and evolution of a long-lived atmospheric river (AR) modulated by six frontal waves over the northeastern Pacific on 20-25 January 2015. Satellite observations and reanalysis diagnostics provided synoptic-scale context, illustrating the warm, moist southwesterly airstream within the quasi-stationary AR situated between an upper-level trough and ridge. The AR remained offshore of the U.S. West Coast but made landfall across British Columbia where heavy precipitation and high melting levels occurred, resulting in flooding. Forty-seven rawinsondes launched from the RHB provided a comprehensive thermodynamic and kinematic depiction of the AR, including an upward intrusion of strong water-vapor transport in the low-level moist southwesterly flow during the passage of frontal waves 2 through 6. A collocated 1290-MHz wind profiler showed an abrupt frontal transition from southwesterly to northerly flow below 1 km MSL coinciding with the tail-end of AR conditions. Shipborne radar and disdrometer observations in the AR uniquely captured key microphysical characteristics of shallow warm rain, convection, and deep mixed-phase precipitation. Continuous and novel observations of sea-surface fluxes documented persistent ocean-surface evaporation into the AR and sensible-heat transfer from the AR into the ocean. The G-IV aircraft coordinated with the RHB and flew directly over the ship. Dropsonde and radar spatial analyses complemented the temporal depictions of the AR from the RHB. The AR characteristics varied, depending on the location of the cross section through the frontal waves.

54 ENVIRONMENTAL SCIENCES↗