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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

U.S. Virgin Islands Wind Resources Update 2014

This report summarized the data collected from two 60-meter (m) meteorological towers (met masts or met towers) and three sonic detection and ranging (SODAR) units on St. Thomas and St. Croix in 2012 and 2013. These results are an update to the previous feasibility study; the collected data are critical to the successful development of a wind project at either site (Lantz et al. 2012). The wind maps for the territory were updated based on these improved data. The National Renewable Energy Laboratory (NREL) conducted measurements from met towers and SODAR units for several locations in the U.S. Virgin Islands (USVI). Both met masts were deployed for more than a year and produced high-quality data (standard industry practice in the wind industry). The Longford (St. Croix) and Bovoni (St. Thomas) sites are estimated to have long-term corrected wind speeds that exceed 7 meters per second (m/s), which may produce financially viable wind projects for both sites. The levelized cost of energy for both sites was estimated at $\$$0.08–$\$$0.14 per kilowatt-hour for typical utility-scale wind turbine with the uncertainty in the estimate driven by uncertainty in the installed capital costs of the proposed wind farms. These estimates assume that the wind production tax credit is not reinstated, but that accelerated depreciation is in place.

17 WIND ENERGY↗
DOE OSTI2023

Improving Tropical Cyclogenesis Forecasts of Hurricane Irma (2017) through the Assimilation of All-Sky Infrared Brightness Temperatures

The assimilation of satellite all-sky infrared (IR) brightness temperatures (BTs) has been shown in previous studies to improve intensity forecasts of tropical cyclones. Here, in this study, we examine whether assimilating all-sky IR BTs can also potentially improve tropical cyclogenesis forecasts by improving the pregenesis cloud and moisture fields. By using an ensemble-based data assimilation system, we show that the assimilation of upper-tropospheric water vapor channel BTs observed by the Meteosat-10 SEVIRI instrument two days before the formation of a tropical depression improves the genesis forecast of Hurricane Irma (2017), a classic Cape Verde storm, by up to 24 h while also capturing its later rapid intensification in deterministic forecasts. In an experiment that withholds the assimilation of all-sky IR BTs, the assimilation of conventional observations from the Global Telecommunications System (GTS) leads to the premature genesis of Hurricane Irma by at least 24 h. This premature genesis is shown to result from an overestimation of the spatial coverage of deep convection within the African easterly wave (AEW) from which Irma eventually forms. The gross overestimation of deep convection without all-sky IR BTs is accompanied by higher column saturation fraction, stronger low-level convergence, and the earlier spinup of a low-level meso- β -scale vortex within the AEW that ultimately becomes Hurricane Irma. Through its adjustment to the initial moisture and cloud conditions, the assimilation of all-sky IR BTs leads to a more realistic convective evolution in forecasts and ultimately a more realistic timing of genesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed at the East River, Colorado, Water: Dataset

This data package contains simulation results of daily evapotranspiration for 17 locations of meteorological stations with different precipitation, air temperature and vegetation within the East River Watershed, Colorado (CLMResult.csv). Daily precipitation data is included for reference. These are the main results of the paper Tran, 2019. Meteorological stations names, latitude and longitude coordinates of meteorological stations, types of lands from the National Land Cover Database, and a comparison with the community land model (CLM) data are also included (Met_LC.csv). The purpose of this data is to analyze the spatio-temporal variations of evapotranspiration at the East River Watershed and understand the factors that control these variations. More information regarding the study, methods, and findings can be found in the Related Reference paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Probable Maximum Precipitation in the U.S. Pacific Northwest in a Changing Climate

The safety of large and aging water infrastructures is gaining attention in water management given the accelerated rate of change in landscape, climate and society. In current engineering practice, such safety is ensured by the design of infrastructure for the Probable Maximum Precipitation (PMP). Recently, several physics-based numerical modeling approaches have been proposed to modernize the conventional and ad hoc PMP estimation approach. However, the underlying physics has not been investigated and thus differing PMP estimates are obtained without clarity on their interpretation. In this study, we present a hybrid approach that takes advantage of both traditional engineering wisdom and modern climate science to estimate PMP for current and future climate conditions. The traditional PMP approach is improved and applied to outputs from an ensemble of five CMIP5 models. This hybrid approach is applied in the Pacific Northwest (PNW) to produce ensemble PMP estimation for the historical (1970-2016) and future (2050-2099) time periods. The new historical PMP estimates are verified by comparing them with the traditional estimates. PMP in the PNW will increase by 50% of the current level by 2099 under the RCP8.5 scenario. Most of the increase is caused by warming, which mainly affects moisture availability, with minor contributions from changes in storm efficiency in the future. Moist track change tends to reduce the future PMP. Compared with extreme precipitation, ensemble PMP exhibits higher internal variation. Thus high-quality data of both precipitation and related meteorological fields (temperature, wind fields) are required to reduce uncertainties in the ensemble PMP estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Growth modeling to evaluate alternative cultivation strategies to enhance national microalgal biomass production

In this paper, we present a model-based assessment of alternative cultivation strategies on algal biomass production within the conterminous United States. Our assessment focuses on two basic cultivation strategies: 1) seasonal rotation of three representative freshwater algal strains that are well suited for warm weather, cold weather, and all-season diverse weather conditions, respectively; and 2) variation between three open pond water depths (15cm, 20cm, and 25cm). The enhanced Biomass Assessment Tool (BAT) is applied on a site-specific, hourly basis at 5,832 North American Land Data Assimilation System Phase 2 1/8° meteorological model grid cells over a 30-year period (1980-2009) to evaluate the operational strategies. Recognizing that resource management decisions may also consider scales beyond the individual site, we also conduct a regional assessment of focused on 7 representative climate zones in the conterminous United States. Results demonstrate that the spatial variability of algal productivity is largely affected by the strain-specific growth response to light and temperature that vary significantly by climate zone and latitude. Therefore, with a limited set of alternative cultivation strategies, the BAT identified the best performing combination of cultivation strategies on a site-specific basis that considerably enhances national annual biomass productivity. Specifically, the appropriate choice of seasonal strain rotation is able to significantly dampen climate-driven seasonal and spatial variability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

The dependence of ice microphysics on aerosol concentration in arctic mixed-phase stratus clouds during ISDAC and M-PACE

Cloud and aerosol data acquired by the National Research Council of Canada (NRC) Convair-580 aircraft in, above, and below single-layer arctic stratocumulus cloud during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in April 2008 were used to test three aerosol indirect effects hypothesized to act in mixed-phase clouds: the riming indirect effect, the glaciation indirect effect, and the cold second indirect effect. The data showed a correlation of R= 0.75 between liquid drop number concentration, Nliq, inside cloud and ambient aerosol number concentration NPCASP below cloud. This, combined with increasing liquid water content LWC with height above cloud base and the nearly constant profile of Nliq, suggested that liquid drops were nucleated from aerosol at cloud base. No strong evidence of a riming indirect effect was observed, but a strong correlation of R = 0.69 between ice crystal number concentration Ni and NPCASP above cloud was noted. Increases in ice nuclei (IN) concentration with NPCASP above cloud combined with the subadiabatic LWC profiles suggest possible mixing of IN from cloud top consistent with the glaciation indirect effect. The higher Nice and lower effective radius rel for the more polluted ISDAC cases compared to data collected in cleaner single-layer stratocumulus conditions during the Mixed-Phase Arctic Cloud Experiment is consistent with the operation of the cold second indirect effect. However, more data in a wider variety of meteorological and surface conditions, with greater variations in aerosol forcing, are required to identify the dominant aerosol forcing mechanisms in mixed-phase arctic clouds.

58 GEOSCIENCES↗
DOE OSTI2026

Constraining the Aerosol Effects on Deep Convective Clouds by Considering the Coupling Between Clouds and the Planetary Boundary Layer

Several mechanisms have been proposed for the aerosol invigoration effect. Although their principles are well established, their actual magnitudes and roles in cloud development remain uncertain and debatable. This uncertainty partly stems from observational-based studies, in which it has been challenging to separate the co-variability between aerosols and meteorology. Addressing this problem requires large data samples. To this end, this study employs the Atmospheric Radiation Measurement data set expanding to 16 years (some up to 17 years, compared to 10 years in previous work) in the U.S. Southern Great Plains. It also conducts a more careful and rigorous analysis to isolate the influences of convective available potential energy (CAPE) and synoptic patterns to address a previously raised concern. We incorporated a new key process affecting aerosol-cloud interaction: cloud-surface coupling. The state/degree of the coupling relationship turns out to play an important role in the invigoration effect. Our analysis reinforces earlier findings of a robust positive relationship between cloud thickness and aerosol loading across CAPE percentiles—but only under cloud-surface coupled conditions. The increase in cloud thickness with aerosol loading is most pronounced in coupled clouds with high CAPE and bases below 1 km. Coupled clouds with bases below 1 km thicken between 1 and 4 km, depending on the CAPE percentile. Decoupled clouds show no such systematic changes. Synoptic patterns also lead to different strengths of the invigoration effect. Clean and polluted air masses are predominantly associated with northerly and southerly winds, respectively, with a stronger invigoration effect in cleaner air masses.

Geosciences↗
DOE OSTI2021

Antarctic Water Masses and Ice Shelves: Visualizing the Physics

High-resolution simulation of global climate physics enables us to model how the climate may change under a variety of future scenarios. Such simulations produce vast amounts of information and dense datasets. If interrogated in tandem, these datasets can provide holistic, vital information on Earth’s many integrated systems by revealing the manifold interrelated properties of the atmosphere, ocean, and polar ice, framed by real-world terrain in three-dimensional space as they vary over time. To accomplish this, climate scientists have joined with computer scientists and an artist to develop techniques enabling scientists to see these relationships. Finally, the impact of ocean water properties on Antarctic ice shelves illustrates the benefit of this analysis in understanding land ice melt rates and thus sea-level rise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Estimating Subhourly Inverter Clipping Loss From Satellite-Derived Irradiance Data

Photovoltaic system production simulations are conventionally run using hourly weather datasets. Hourly simulations are sufficiently accurate to predict the majority of long-term system behavior but cannot resolve high-frequency effects like inverter clipping caused by short-duration irradiance variability. Direct modeling of this subhourly clipping error is only possible for the few locations with high-resolution irradiance datasets. This paper describes a method of predicting the magnitude of this error using a machine learning regressor ensemble model, comprised of a random forest and an XGBoost model, and 30-minute satellite irradiance data. The method predicts a correction for each 30-minute interval with the potential to roll up into 60-minute corrections to match an hourly energy model. The model is trained and validated at locations where the error can be directly simulated from 1-minute ground data. The validation shows low bias at most ground station locations. The model is also applied to gridded satellite irradiance to produce a heatmap of the estimated clipping error across the United States. Finally, the relative importance of each predictor satellite variable is retrieved from the model and discussed.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2011

A computational framework for uncertainty quantification and stochastic optimization in unit commitment with wind power generation.

We present a computational framework for integrating a state-of-the-art numerical weather prediction (NWP) model in stochastic unit commitment/economic dispatch formulations that account for wind power uncertainty. We first enhance the NWP model with an ensemble-based uncertainty quantification strategy implemented in a distributed-memory parallel computing architecture. We discuss computational issues arising in the implementation of the framework and validate the model using real wind-speed data obtained from a set of meteorological stations. We build a simulated power system to demonstrate the developments.

17 WIND ENERGY↗
DOE OSTI2023

Synchronization of Alternative Models in a Supermodel and the Learning of Critical Behavior

“Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, interscale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the midlatitudes and a pair of ECHAM5 models of the tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with intermodel connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. In conclusion, for supermodels of both types, power spectra indicate enhanced interscale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Water balance in the Amazon basin from a land surface model ensemble

Despite recent advances in modeling and remote sensing of land surfaces, estimates of the global water budget are still fairly uncertain. The objective of this study is to evaluate the water budget of the Amazon basin based on several state-of-the-art land surface model (LSM) outputs. Water budget variables [total water storage (TWS), evapotranspiration (ET), surface runoff (R) and baseflow (B)] are evaluated at the basin scale using both remote sensing and in situ data. Fourteen LSMs were run using meteorological forcings at a 3-hourly time step and 1-degree spatial resolution. Three experiments are performed using precipitation which has been rescaled to match monthly global GPCP and GPCC datasets and the daily HYBAM dataset for the Amazon basin. R and B are used to force the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration, and GRACE TWS estimates in different catchments. At the basin scale, simulated ET ranges from 2.39mm.d-1 to 3.26mm.d-1 and a low spatial correlation between ET and P indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget variables vary significantly as a function of both the LSM and precipitation used, but simulated TWS generally agree at the basin scale. The best water budget simulations resulted from experiments using the HYBAM dataset, mostly explained by a denser rainfall gauge network the daily rescaling.

water balance, Amazon, land surface models↗
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 OSTI2023

Capturing plume behavior in complex terrain: an overview of the Nevada National Security Site Meteorological Experiment (METEX21)

METEX21 was an atmospheric tracer release experiment executed at the Department of Energy’s Nevada National Security Site (NNSS) in the southwestern U.S to study terrain-induced wind and thermodynamic conditions that influence local-scale (<5-km) plume transport under varying atmospheric forcing conditions. Meteorological observations were collected using 10-m tall meteorological towers, 2-m tall tripods with 3-d sonic anemometers, a 3-m tall eddy covariance flux tower, Doppler profiling lidars, Doppler scanning lidars, weather-balloon launched radiosondes, and a tethered balloon equipped with wind, temperature, and aerosol sensors at heights up to 800 m. A smoke tracer was released along three transects in the horizontal and vertical directions and observed with video cameras, aerosol sensors and lidars (via aerosol backscatter). The observations showed evidence of large-scale/synoptic transience as well as local-scale upslope and downslope flows, along-axis valley flows, recirculation eddies on leeward slopes, and periods of strong shear and veer aloft. The release days were classified as either synoptically-driven or locally-driven, and a single case day is presented in detail for each. Synoptically-forced days show relatively narrow smoke plumes traveling down the valley from north to south (with the predominant wind direction), with little deviation in transport direction regardless of the elevation or ground locations of the smoke releases, except near the presence of leeside recirculation eddies. Locally-forced days exhibit a wider range of plume behavior due to the combination of thermally-induced valley and slope flows, which are often flowing in different cardinal directions, and wind shear found aloft at higher altitudes and elevations. We saw evidence of smoke lofting on top of the mesas due to strong upslope flows on these days. A major finding of this experiment was the effectiveness of scanning lidars to measure 2-dimensional plume transport out to a 2–3 km distance; much farther than could be visibly observed. METEX21 was the first of three planned tracer experiments at NNSS, and future experiments will incorporate multiple tracers to improve individual plume identification so that finer resolution flow details can be attained from these measurements, as well as deploy a larger suite of meteorological instrumentation, including more temperature profiling data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Optical properties and composition of viscous organic particles found in the Southern Great Plains

Abstract. Atmospheric high-viscosity organic particles (HVOPs) were observed in samples of ambient aerosols collected in April and May 2016 in the Southern Great Plains of the United States. These particles were apportioned as either airborne soil organic particles (ASOPs) or tar balls (TBs) from biomass burning based on spetro-microscopic imaging and assessments of meteorological records of smoke and precipitation data. Regardless of their apportionment, the number fractions of HVOPs were positively correlated (R2=0.85) with increased values of absorption Ångström exponent (AAE) measured in situ for ambient aerosol at the site. Extending this correlation to 100 % HVOPs yields an AAE of 2.6, similar to previous literature reports of the class of light-absorbing organic particles known as brown carbon (BrC). One out of the three samples investigated had a significant number of ASOPs, while the other two samples contained TBs. Although there are chemical similarities between ASOPs and TBs, they can be distinguished based on composition inferred from near-edge absorption X-ray fine structure (NEXAFS) spectroscopy. ASOPs were distinguished from TBs based on their average -COOH/C=C and -COOH/COH peak ratios, with ASOPs having lower ratios. NEXAFS spectra of filtered soil organic brine particles nebulized from field samples of standing water deposited after rain were consistent with ASOPs when laboratory particles were generated by bubble bursting at the air–organic brine interface. However, particles generated by nebulizing the bulk volume of soil organic brine had a particle composition different from ASOPs. These observations are consistent with the raindrop generation mechanism responsible for ASOP emissions in the area of study. In contrast, nebulized samples carry with them higher fractions of soil inorganics dissolved in the bulk volume of soil brine, which are not aerosolized by the raindrop mechanism. Our results support the bubble bursting mechanism of particle generation during rainfall resulting in the ejection of soil organics into the atmosphere. In addition, our results show that ASOPs may only be atmospherically relevant during times when suitable emission conditions are met.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Meteodrone data

The University of Nebraska-Lincoln (UNL) Meteodrone (model SSE MM-641) is a small (1.1 kg GTOW, ~40 cm across) hexcopter UAS manufactured by Meteomatics. Maximum endurance is approximately 30 min and estimated maximum operating altitude of 1500 m. Profiles can be executed at ascent/descent rates up to 10 m/s. The Meteodrone is capable of measuring temperature, relative humidity, wind velocity and GPS position time-stamped with GPS time. Temperature and dual relative humidity sensors are shielded from solar exposure by a housing with a vertically oriented air intake and hoirizontal exhaust. Sensor aspiration is driven by rotorwash across the horizontal exhaust. In its current configuration data are recorded only when executing vertical profiles. Attitude and position are updated at a data rate of 20 Hz while meteorological observations are updated at 10 Hz.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Turbulent Parameters by airborne measurements over BNF in March 2025

The original data were collected during the AAF Engineering Flights (AEF2025) in the vicinity of the ARM Bankhead National Forest (BNF) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/bnf ) in northwestern Alabama in March 2025. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at the public-use airport of Posey Field, Alabama (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from March 10 through March 24, 2025. The ArcticShark UAS performed nine flights, including eight research flights over the AMF3 (BNF Main Site) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Atmosphere↗