Search NASA⌕ Search

SEARCH · Search NASA

Results for “Meteorologic data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21

Panama Land Model (CLM/ELM) Site Drivers

This data package contains meteorological and surface data at the Barro Colorado Island (BCI) and Bosque Protector San Lorenzo (Fort Sherman) NGEE Tropics sites in Panama. Data has been converted into formats usable by the land-models driving the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES). Surface datasets are model release dependent and may have to be re-processed for later versions of the model. Current surface datasets based off of "<>_16pfts_Irrig_CMIP6_simyr2000_c170824.nc" See the README_ngeet_lm_driver text file in the attached zip file for detailed descriptions of the included data files.

54 ENVIRONMENTAL SCIENCES↗

Ground-based All-sky Mid-infrared and Visible Imagery for Purposes of Characterizing Cloud Properties

This paper describes the All Sky Infrared Visible Analyzer (ASIVA), a multi-purpose visible and infrared sky imaging and analysis instrument whose primary functionality is to provide radiometrically calibrated imagery in the mid-infrared (mid-IR) atmospheric window. This functionality enables the determination of diurnal hemispherical cloud fraction (HCF) and estimates of sky/cloud temperature from which one can derive estimates of cloud emissivity and cloud height. This paper describes the calibration methods and performance of the ASIVA instrument with particular emphasis on data products being developed for the meteorological community. Data presented here were collected during a field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Climate Research Facility from May 21 to July 27, 2009. The purpose of this campaign was to determine the efficacy of IR technology in providing reliable nighttime HCF data. Significant progress has been made in the analysis of the campaign data over the past several years and the ASIVA has proven to be an excellent instrument for determining HCF as well as several other important cloud properties.

analyzer↗

Maximum Photovoltaic Penetration Levels on Typical Distribution Feeders: Preprint

This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder,clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Simulations were run inGridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the cases simulated, maximum PV penetration was at least 30% of peak load.

14 SOLAR ENERGY↗

Enhancing Streamflow Reanalysis Across the Conterminous US Leveraging Multiple Gridded Precipitation Data Sets

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly affect the accuracy of hydrologic predictions. This challenge intensifies across regions characterized by diverse hydro-climatological and geographical conditions, such as in the conterminous US (CONUS) where a single precipitation product struggles to consistently replicate observed hydrographs, particularly peak flow dynamics. To enhance streamflow predictions, we utilize a VIC-RAPID hydrologic modeling framework driven by multiple commonly used meteorological forcing data sets, such as Daymet, PRISM, ST4, AORC, and their hybrids and create multiple sets of 40-year (1980–2019) hourly, daily, and monthly streamflow reanalysis, Dayflow Version 2, for 2.7 million river reaches across the CONUS. Most forcings lead to skillful streamflow performance, except for ST4 in the mountainous west, where severe radar blockage adversely affects the accuracy. The evaluation using over 6,000 hourly stream gauges shows that hourly AORC and ST4 lead to improved annual peak flow performance over Daymet—driven streamflow (Dayflow V1), particularly in smaller basins, highlighting the value of high temporal resolution forcings in hydrologic predictions. Compared with other benchmark data sets like National Water Model V3.0, AORC-driven VIC-RAPID exhibits improved regional streamflow performance, with comparable peak flow representation. We envision that multi-forcing streamflow reanalysis data can inform regions in need of forcing data enhancement, diagnose hydrologic model performance, and benefit diverse water resource applications.

54 ENVIRONMENTAL SCIENCES↗

Investigating Building Energy Consumption and CO2 Emission in Phoenix Using AutoBEM and Future Typical Meteorological Year (fTMY) Weather Data

This research investigates the energy performance and CO2 emissions of each building stock across the Phoenix metropolitan area using the Automatic Building Energy Modeling (AutoBEM) framework and Model America v2 (MAv2) dataset from Oak Ridge National Laboratory (ORNL). Typical Meteorological Year (TMY) and Future Typical Meteorological Year (fTMY) files were used for AutoBEM simulation. The simulation results from TMY and fTMY were compared. It was found that a projected 10.28% increase in total CO2 emissions and a 9.30% rise in total energy consumption by 2080–2099 relative to current typical conditions. The results highlight the disparities in emissions among different building stocks and the influence of climate change on future energy demand. The findings underscore the necessity of targeted policy interventions and retrofitting strategies (eg. advanced HVAC systems, improved insulation, reflective roofing) to mitigate emissions in high-energy-use and emission-intensed buildings, particularly as climate conditions evolve. This study contributes to the growing understanding of building-sector emissions and their long-term implications under future climate scenarios.

Li, Hang [ORNL] (ORCID:0000000306001920)↗

Achieving Realistic Runoff in the Western United States with a Land Surface Model Forced by Dynamically Downscaled Meteorology

Abstract In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM’s ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method. Significance Statement This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model’s reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately.

Meteorology & Atmospheric Sciences↗

Feedbacks Between Surface Deformation and Permafrost Degradation in Ice Wedge Polygons: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "Feedbacks between surface deformation and permafrost degradation in ice wedge polygons," submitted for review to the Journal of Geophysical Research: Earth Surface. The goals of the study were: 1) to determine how variability in microtopographic conditions (i.e., rim height, trough width, and trough depth) and hydrologic conditions in the trough (i.e., inundated or well-drained) of an ice wedge polygon impact active layer thickness above an ice wedge; and 2) to determine how microtopographic and hydrologic controls on active layer thickness may influence thermokarst trajectories in ice wedge polygon terrain. Toward these objectives, an ensemble of fine-scale simulations of the hydrologic and thermal regimes in ice wedge polygons of variable microtopography was conducted, each polygon being subjected to identical meteorological forcing data, characteristic of the last twenty years near Prudhoe Bay, Alaska. Simulations incorporated solutions of conservation of water and mass at the surface, in the subsurface, and in the snowpack. Active layer thickness in the trough (i.e., above the ice wedge) was extracted from each simulation at the end of a 19 year spin-up, and at the end of a markedly warm summer which followed the spin-up. This archive includes mesh files, meteorological forcing data, and input files needed to reproduce the analysis described in the paper. Due to the large file sizes, raw model output has been omitted. However, post-processing scripts and time series of several variables extracted from the raw output have been included. All data are included in one zipped file with a user guide as a pdf. All simulations were conducted using Amanzi-ATS, v 0.86 (https://doi.org/10.11578/dc.20190911.1).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. Our paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

17 WIND ENERGY↗

Downscaled precipitation and mean air temperature datasets; East-Taylor subbasin; 2008-2019; daily temporal resolution; 400 m spatial resolution

This dataset provides gridded meteorological forcing data (specifically, daily precipitation and daily mean air temperature). The dataset has been generated by downscaling the Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset from a spatial resolution of 800 m to 400 m. The time period is 2008-2019, and the mapped area is East Taylor subbasin in Upper Colorado. The data are in the form of NetCDF files, arranged by year. Compared to the PRISM dataset, the dates of the downscaled dataset are shifted backwards by one (e.g., downscaled data for May 25 corresponds to PRISM data for May 26). This temporal shifting makes the meteorological forcing correspond more closely to the prescribed date. The NetCDF format is a standard raster format that can be read using any Geographic Information System (GIS) software; plenty of modules exist in popular scripting languages (such as Python, R and Matlab) that can also be used to read NetCDF files.East_Taylor_Tavg_PRISM400 corresponds to mean air temperature.East_Taylor_Precip_PRISM400.zip corresponds to precipitation.The proprietary PRISM data (800 m resolution) were purchased with funding from the Watershed Function Scientific Focus Area supported by U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under award no. DE-AC02-05CH11231.Dataset update on March 9, 2022:Uploaded new data files that are identical to the earlier files but are now in the NetCDF format, arranged by year. Earlier, the files were in the GeoTiff format, arranged by date.

54 ENVIRONMENTAL SCIENCES↗

PLUSWIND Hourly Plant-Level Power

These data contain the hourly plant-level power time series from PLUSWIND. The time series is derived from the HRRR model and corrected for density and losses. The PLUSWIND dataset hosted on the Wind Data Hub here (https://a2e.energy.gov/project/pluswind) contains additional versions with meteorological corrections. Data are provided for years 2018 - 2021. The data hosted at this location include conversion from capacity factor output (normalized output) to total hourly production (units of MW).

17 WIND ENERGY↗

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗

Wind Integration National Dataset (WIND) Toolkit; NREL (National Renewable Energy Laboratory)

A webinar about the Wind Integration National Dataset (WIND) Toolkit was presented by Bri-Mathias Hodge and Caroline Draxl on July 14, 2015. It was hosted by the Southern Alliance for Clean Energy. The toolkit is a grid integration data set that contains meteorological and power data at a 5-minute resolution across the continental United States for 7 years and hourly power forecasts.

17 WIND ENERGY↗

Oak Ridge Reservation Meteorological Overview Report, Oak Ridge, TN

This report is purposed to provide a summary of the local climate and data from meteorological (Met) towers and wind profilers at the East Tennessee Technology Park (ETTP), the Y-12 National Security Complex Site (Y-12), the Oak Ridge National Laboratory (ORNL), as well as other federal, state, or local agencies as necessary to support the natural phenomena hazards (NPH) analysis 10-year update required by Department of Energy (DOE)- STD-1020-2016, Natural Phenomena Hazards Analysis and Design Criteria for DOE Facilities. The data from this report will be used to support high wind analyses, precipitation analysis, flood analysis, lightning analysis, and other severe weather phenomena for the ETTP, the ORNL, and Y-12.

54 ENVIRONMENTAL SCIENCES↗

LANL Meteorological Program Improvements to Continue Meeting Annual 90 Percent Data Recovery Requirements

Recently, the Los Alamos National Laboratory (LANL) Environmental Protection and Compliance (EPC) and Safety Basis (SB) Divisions have collaborated on the latter’s use of the meteorological data as input into dispersion analysis used to determine receptor dose consequences as a result of an accidental release of radioactive material from a LANL nuclear facility. The dose consequence calculations are part of the Department of Energy (DOE) approved Documented Safety Analysis (DSA), which describes the processes, hazards, and controls of nuclear operations within certain facilities at LANL. The DOE approved DSA is required according to Title 10 of the Code of Federal Regulations Part 830 (10CFR830), “Nuclear Safety Management” and is developed in accordance with the 10CFR830, Subpart B “Safety Basis” safe harbor methodology identified as DOE Standard 3009-94, or successor document (DOE STD 3009-94).

54 ENVIRONMENTAL SCIENCES↗