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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Synergy of Satellite Radiation, Precipitation, and Other Meteorological Variable Observations for Global Mean Sea Surface Turbulent Heat Flux Estimation

Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.

Bing Lin↗
NASA NTRSDate not supplied

Coherent Vorticity Meteorological Infrasound Sensing Flight Research

Under collaborative flight research project with NASA and, separately, Air Canada, the NRC has investigated meteorological infrasound sensing, using NASA-developed Infrasound sensing microphones. The project involved the installation of 1.5-inch NASA microphone in the nosebay of the NRC DHC-6 research aeroplane. The microphone was plumbed to a pitot-static tube line, connected to a research pitot-static tube on the starboard side of the aircraft nose. Microphone signals on the DHC-6 installation were validated during orbiting flight through its own wake vortices, and flight in the vicinity of wake vortices from Medium Category jets landing at Ottawa Airport. Thereafter, flights were undertaken, to measure the infrasound sensing of meteorological features. Possible acoustic ducting of infrasound energy was measured in stratified lower atmospheric conditions. Infrasound sensing was also accomplished, in the vicinity of meteorological flow-fields of relatively concentrated vorticity, notably line features of vorticity. An increase in sensed infrasound energy was recorded as distance to the line features reduced. Convective uplift infrasound signature sensing was also conducted, and indicated a similar result.

A P Brown↗
NASA NTRS2024

Long-Term Trends in Aerosols, Low Clouds, and Large-scale Meteorology over the Western North Atlantic from 2003 to 2020

A continuous decrease of aerosol over the western North Atlantic Ocean (WNAO) on decadal timescales provides a long-term experiment to evaluate how other natural and anthropogenic processes affect the manifestation of aerosol-cloud interactions in this region. Furthermore, the WNAO is a natural laboratory with diverse aerosol sources, marine boundary layer clouds that are more variable than marine stratocumulus deck regions, and unique flow regimes set up by the Gulf Stream and semi-permanent Bermuda High. We investigate how satellite-retrieved macrophysical and microphysical properties of low clouds and the surface shortwave irradiance changed from 2003 to 2020, in tandem with this aerosol decrease. The decadal changes in large-scale meteorology relating to the North Atlantic Oscillation (NAO) are also examined. We find no significant changes in low-cloud fraction but a widespread reduction in low-cloud optical depth attributed to fewer and larger cloud droplets with almost no change in cloud liquid water path. Despite robust signals in low-cloud optical properties together with aerosol decrease, a corresponding increase in the surface shortwave irradiance trends, also called surface brightening, is lacking. This absence of brightening is potentially due to concomitant changes found in large-scale meteorology associated with NAO— a Bermuda High strengthening, sea surface warming, and atmospheric moistening— as well as an increase in high cloud fraction that can counteract the surface brightening. Ultimately, our findings suggest that spatial patterns in the decadal meteorological variability, likely set up by NAO, contribute more to the surface cloud radiative effect over the WNAO than aerosol-cloud interactions.

J Minnie Park↗
DOE OSTI2024

Utah FORGE Project 3-2417: Meteorological Data During 2023 Completion/Circulation

This preliminary data archive includes meteorological data recorded at the Utah FORGE facility over the period of time including the completion/cementing of well 78-16B and the initial 2023 circulation test, largely occurring in June/July/August of 2023. This information may prove useful for understanding seismic and other instrumentation responses during these activities. The meteorological station was installed June 23rd, 2023 during drilling; the circulation test occurred in mid July of 2023 (July 4-19). The included files span this period. All sensors were installed at the 16 pad and hence reflect weather state at the site. This dataset was acquired by the FOGMORE R&D project (Fiber Optic MOnitoring for Reservoir Evolution), Utah FORGE R&D Project 3-2417.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Gap-filled meteorological data (2011-2020) and modeled potential evapotranspiration data from the KCOMTCRE2 WeatherUnderground weather station, from the East River Watershed, Colorado

This dataset is a gap-filled meteorological dataset (years 2011-2020) that includes modeled potential evapotranspiration from a station near the pumphouse on the East River (KCOMTCRE2 WeatherUnderground ) near the top of the ridge at the Pumphouse PLM wells. These datasets are useful as model inputs. The KOMTCRE2 station is located on Mt. Crested Butte in Colorado. More information can be found at: https://www.wunderground.com/dashboard/pws/KCOMTCRE2/table/2020-12-7/2020-12-7/daily. The purpose of this dataset is to use as input to hydrological and flow-reactive transport models as meteorological forcing. One attached file includes metadata files with definitions for all variables and units. Subsequent files include the same time series dataset, but aggregated and gap-filled at different time-stamp intervals. These include 5 minute time-series, 15 minute time-series, 30 minute time-series, 1 hour time-series, daily time-series, and hourly and daily modeled evapotranspiration.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1946

Lightning Discharges to Aircraft and Associated Meteorological Conditions

A summary is given of information on atmospheric electrical discharges to aircraft and associated meteorological conditions. Information is given that is designed to give a fairly comprehensive view of the underlying principles of meteorology and atmospheric electricity. Of special interest to pilots are lists of procedures of flight conduct and aircraft maintenance recommended foe avoiding or minimizing the hazards of disruptive electrical discharges and other severe conditions near thunderstorms.

MEDICAL PROBLEMS OF FLIGHT - LIGHTNING↗
NASA NTRS2023

Spatially-Coordinated Airborne Data and Complementary Products for Aerosol, Gas, Cloud, and Meteorological Studies: the Nasa Activate Dataset

The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions, with applications extending from process-based studies to multi-scale model intercomparison and improvement as well as to remote-sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean, resulting in 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the HU-25 Falcon and King Air, respectively. The HU-25 Falcon conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. Under cloud-free conditions, the HU-25 Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flying aircraft) flew at approximately ∼ 9 km and conducted remote sensing with a lidar and polarimeter while also launching dropsondes (785 in total). Collectively, simultaneous data from both aircraft help to characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the HU-25 Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product's start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes. The data are publicly accessible through https://doi.org/10.5067/SUBORBITAL/ACTIVATE/DATA001 (ACTIVATE Science Team, 2020).

Aerosol Cloud meTeorology Interactions oVer the we↗
DOE OSTI2023

Contrasting changes in ozone during 2019–2021 between eastern and the other regions of China attributed to anthropogenic emissions and meteorological conditions

Ozone pollution is one of the most severe air quality issues in China that poses a serious threat to human health and ecosystems. During 2019–2021, the maximum daily 8-h average ozone concentrations in eastern China (110–122.5°E, 26–42°N) and the rest of China (ROC) show different decreasing patterns, with ozone concentrations in eastern China decreasing by 14.9 μg/m 3 , which is much larger than 4.8 μg/m 3 in ROC. Here, based on two independent methods, the atmospheric chemical transport model (GEOS-Chem) simulations and the machine learning (ML) model (LightGBM) predictions, the reasons for the differences in ozone changes between eastern China and ROC during the warm season (April to September) are investigated. According to the GEOS-Chem (LightGBM) results, changes in the meteorological conditions contributed to an ozone decrease by 7.3 (6.8) μg/m 3 in eastern China due to decreased chemical production and an ozone decrease by 6.8 (7.0) μg/m 3 in ROC attributed to the weakened horizontal and vertical advection. With the influence of meteorological factors excluded, the observations show that changes in anthropogenic emissions resulted in an ozone decrease by 7.6 (8.1) μg/m 3 in eastern China and an ozone increase by 2.0 (2.2) μg/m 3 in ROC, which is primarily induced by the changes in NO x emissions. The surface measurements and satellite retrievals also indicate that the reduction in NO x emissions in ROC is less efficient than that in the more developed eastern China, leading to contrasting changes in ozone concentrations between eastern China and ROC during 2019–2021. In conclusion, our results highlight the critical need to reduce ozone precursor emissions in the rest regions of China apart from eastern China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Meteorological Drivers of North American Monsoon Extreme Precipitation Events

Abstract In this paper the meteorological drivers of North American Monsoon (NAM) extreme precipitation events (EPEs) are identified and analyzed. First, the NAM area and its subregions are distinguished using self‐organizing maps applied to the Climate Prediction Center global precipitation data set. This reveals distinct subregions, shaped by the inhomogeneous geographic features of the NAM area, with distinct extreme precipitation character and drivers. Next, defining EPEs as days when subregion‐mean precipitation exceeds the 95th percentile of rainy days, five synoptic features and one mesoscale feature are investigated as potential drivers of EPEs. Essentially all EPEs can be associated with at least one selected driver, with only one event remaining unclassified. This analysis shows the dominant role of Gulf of California moisture surges, mesoscale convective systems and frontal systems in generating NAM extreme precipitation. Finally, a frequency and probability analysis is conducted to contrast precipitation distributions conditioned on the associated meteorological drivers. The findings demonstrate that the co‐occurrence of multiple features does not necessarily enhance the EPE probability.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Diurnal Trends and Meteorological Factors Influencing the Variability of Fluorescent Bioaerosol in Mt. Crested Butte, Colorado During SAIL

Abstract Despite the crucial role of bioaerosol particles (BAP) in our climate system, local ecosystems, and human health, our grasp on their atmospheric interactions is hampered by a lack of high‐resolution and long‐term data, which is essential for understanding their abundance and variability in response to meteorological conditions. To discern these relationships in a high‐altitude mountainous terrain is even less well‐studied. Therefore, we deployed a Wideband Integrated Bioaerosol Sensor (WIBS‐Neo) for three months during the first biologically active season of the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in summer 2022 on Mt. Crested Butte in Colorado (elevation 3,140 m ASL). Here, we report real‐time fluorescent BAP (FBAP) data collected from 15 June to 13 September 2022, sampled from within the ARM Aerosol Observing System (AOS). To our knowledge, these are the first high altitude (>3,000 m ASL) continuous measurements of FBAP made in North America. During this deployment, we observed on average 21% and as many as 48% (hourly maximum) of particles within the detection size range ( to ) of the WIBS as FBAP. Our analysis presents the diurnal cycles for seven distinct types of FBAP, showing unique patterns and, in some cases, correlations with temperature and solar radiation cycles. Abundance and composition of FBAP varied with relative humidity and precipitation. Precipitation events appeared to both cause emission and removal of FBAP, whereas dust and smoke events had no significant effect, highlighting the critical role of meteorology on FBAP at high altitudes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dynamically Downscaled (WRF) 1km, Hourly Meteorological Conditions 1987-2020. East/Taylor Watersheds

This dataset contains meteorological output from the Weather Research and Forecasting (WRF) version 3.8.1. This dataset has been created to 1) investigate hydrometeorological processes impacting the East River and water-delivery to the Critical Zone, and 2) provide meteorological forcing data for distributed Earth-science modeling applications in the East River watershed. Variables have a 1 kilometer spatial resolution and hourly temporal resolution and encompass a rectangular region encompassing the East and Taylor River watersheds, Colorado, near the town of Crested Butte. WRF was forced using Climate Forecast System Reanalysis (CFSR) lateral boundary conditions. Each .zip file contains one "water year" of data (October 1 -- September 30; i.e. water year 2017 starts October 1, 2016 and ends September 30, 2017). Each zip folder contains 12 netcdf (.nc) files containing one month of hourly data each and are approximately 250mb. Model timestamps are in UTC time.The files contain the following data variables:EAST_MASK: binary mask of the watershed regionTAYLOR_MASK: binary mask of the watershed regionGLW downwelling longwave radiation (w/m2)HR_PRCP: Hourly Precipitation Rate (mm/hr). Includes all hydrometeors (solid+liquid). HFX NoahMP LSM total grid-cell modelled sensible heat flux (w/m2) [positive towards atmosphere]LH NoahMP LSM total grid-cell modelled latent heat flux (w/m2) [positive towards atmosphere; can be converted to ET]PSFC Surface Barometric Pressure (hPa)Q2 Two-meter specific humidity (kg/kg)SWDOWN Downwelling shortwave solar radiation (w/m2)SWNORM Terrain-normal downwelling shortwave radiation (w/m2)T2 Two-meter air temperature (deg K)U10 10-m U-component of wind velocity (m/s)V10 10m V-component of wind velocity (m/s)XLAT Latitude of grid-center point XLONG Longitude of grid-center point XTIME Model timestamp, **in UTC**

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗
DOE OSTI2022

Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using Machine Learning Algorithm to Detect Blowing Snow and Fog in Antarctica Based on Ceilometer and Surface Meteorology Systems

Blowing snow is a common weather phenomenon in Antarctica and plays an important role in the water vapor cycle and ice sheet mass balance. Although it has a significant impact on the climate of Antarctica, people do not know much about this process. Fog events are difficult to distinguish from blowing snow events using existing detection algorithms by a ceilometer. In this study, based on ceilometer, the meteorological parameters observed by surface meteorology systems are further combined to detect blowing snow and fog using the AdaBoost algorithm. The weather phenomena recorded by human observers are ‘true’. The dataset is collected from 1 January 2016 to 31 December 2016 at the AWARE site. Among them, three-quarters of the data are used as the training set and the rest of the data as the testing set. The classification accuracy of the proposed algorithm for the testing set is about 94%. Compared with the Loeb method, the proposed algorithm can detect 89.12% of blowing snow events and 76.10% of fog events, while the Loeb method can only identify 64.29% of blowing snow events and 31.87% of fog events.

54 ENVIRONMENTAL SCIENCES↗
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↗
NASA NTRS2008

Surface Meteorology and Solar Energy (SSE) Data Release 5.1

The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].

Arctic heating↗
NASA NTRS2005

Diagnostic Comparison of Meteorological Analyses during the 2002 Antarctic Winter

Several meteorological datasets, including U.K. Met Office (MetO), European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and NASA's Goddard Earth Observation System (GEOS-4) analyses, are being used in studies of the 2002 Southern Hemisphere (SH) stratospheric winter and Antarctic major warming. Diagnostics are compared to assess how these studies may be affected by the meteorological data used. While the overall structure and evolution of temperatures, winds, and wave diagnostics in the different analyses provide a consistent picture of the large-scale dynamics of the SH 2002 winter, several significant differences may affect detailed studies. The NCEP-NCAR reanalysis (REAN) and NCEP-Department of Energy (DOE) reanalysis-2 (REAN-2) datasets are not recommended for detailed studies, especially those related to polar processing, because of lower-stratospheric temperature biases that result in underestimates of polar processing potential, and because their winds and wave diagnostics show increasing differences from other analyses between similar to 30 and 10 hPa (their top level). Southern Hemisphere polar stratospheric temperatures in the ECMWF 40-Yr Re-analysis (ERA-40) show unrealistic vertical structure, so this long-term reanalysis is also unsuited for quantitative studies. The NCEP/Climate Prediction Center (CPC) objective analyses give an inferior representation of the upper-stratospheric vortex. Polar vortex transport barriers are similar in all analyses, but there is large variation in the amount, patterns, and timing of mixing, even among the operational assimilated datasets (ECMWF, MetO, and GEOS-4). The higher-resolution GEOS-4 and ECMWF assimilations provide significantly better representation of filamentation and small-scale structure than the other analyses, even when fields gridded at reduced resolution are studied. The choice of which analysis to use is most critical for detailed transport studies (including polar process modeling) and studies involving synoptic evolution in the upper stratosphere. The operational assimilated datasets are better suited for most applications than the NCEP/CPC objective analyses and the reanalysis datasets.

stratosphere↗