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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ERF: Energy Research and Forecasting Model

High performance computing (HPC) architectures have undergone rapid development in recent years. As a result, established software suites face an ever increasing challenge to remain performant on and portable across modern systems. Many of the widely adopted atmospheric modeling codes cannot fully (or in some cases, at all) leverage the acceleration provided by General-Purpose Graphics Processing Units, leaving users of those codes constrained to increasingly limited HPC resources. Energy Research and Forecasting (ERF) is a regional atmospheric modeling code that leverages the latest HPC architectures, whether composed of only Central Processing Units (CPUs) or incorporating GPUs. ERF contains many of the standard discretizations and basic features needed to model general atmospheric dynamics. The modular design of ERF provides a flexible platform for exploring different physics parameterizations and numerical strategies. ERF is built on a state-of-the-art, well-supported, software framework (AMReX) that provides a performance portable interface and ensures ERF's long-term sustainability on next generation computing systems. This paper details the numerical methodology of ERF, presents results for a series of verification/validation cases, and documents ERF's performance on current HPC systems. The roughly 5× speed up of ERF (using GPUs) over Weather Research and Forecasting (CPUs only) for a 3D squall line test case highlights the significance of leveraging GPU acceleration.

17 WIND ENERGY↗
NASA NTRS1988

Applications products of aviation forecast models

A service called the Optimum Path Aircraft Routing System (OPARS) supplies products based on output data from the Naval Oceanographic Global Atmospheric Prediction System (NOGAPS), a model run on a Cyber-205 computer. Temperatures and winds are extracted from the surface to 100 mb, approximately 55,000 ft. Forecast winds are available in six-hour time steps.

Garthner, John P.↗
NASA NTRS1979

Effects of sounding temperature assimilation on weather forecasting - Model dependence studies

In comparing various methods for the assimilation of remote sounding information into numerical weather prediction (NWP) models, the problem of model dependence for the different results obtained becomes important. The paper investigates two aspects of the model dependence question: (1) the effect of increasing horizontal resolution within a given model on the assimilation of sounding data, and (2) the effect of using two entirely different models with the same assimilation method and sounding data. Tentative conclusions reached are: first, that model improvement as exemplified by increased resolution, can act in the same direction as judicious 4-D assimilation of remote sounding information, to improve 2-3 day numerical weather forecasts. Second, that the time continuous 4-D methods developed at GLAS have similar beneficial effects when used in the assimilation of remote sounding information into NWP models with very different numerical and physical characteristics.

Ghil, M.↗
NASA NTRS2010

Quantification of Juniperus Ashei Pollen Production for the Development of Forecasting Models

Juniperus ashei pollen is considered one of the most allergenic species of Cupressaceae in North America. Juniperus ashei is distributed throughout central Texas, Northern Mexico, the Arbuckle Mountains of south central Oklahoma, and the Ozark Mountains of northern Arkansas and southwestern Missouri. The large amount of airborne pollen that J. ashei produces affects inhabitants of cities and towns adjacent to juniper woodland areas and because juniper pollen can be transported over long distances, it affects populations that are far away. In order to create a dynamic forecast system for allergy and asthma sufferers, pollen production must be estimated. Estimation of pollen production requires the estimation of male cone production. Two locations in the Arbuckle Mountains of Oklahoma and 4 locations in the Edwards Plateau region of Texas were chosen as sampling sites. Trees were measured to determine approximate size. Male to female ratio was determined and pollen cone production was estimated using a qualitative scale from 0 to 2. Cones were counted from harvested 1/8 sections of representative trees. The representative trees were measured and approximate surface area of the tree was calculated. Using the representative tree data, the number of cones per square meter was calculated for medium production (1) and high production (2) trees. These numbers were extrapolated to calculate cone production in other trees sampled. Calibration was achieved within each location's sub-plot by counting cones on 5 branches collected from 5 sides of both high production and medium production trees. The total area sampled in each location was 0.06 hectare and total cone production varied greatly from location to location. The highest production area produced 5.8 million cones while the lowest production area produced 72,000 cones. A single representative high production tree in the Arbuckle Mountains produced 1.38 million cones. The number of trees per location was relatively uniform, but the number of high cone production trees varied greatly. Although there is great diversity in the locations making it difficult to determine which factors are most important, cone production was well correlated with certain stand characteristics including trunk diameter.

Bunderson, L. D.↗
NASA NTRS1997

Initialization and Predictability of a Coupled ENSO Forecast Model

The skill of a coupled ocean-atmosphere model in predicting ENSO has recently been improved using a new initialization procedure in which initial conditions are obtained from the coupled model, nudged toward observations of wind stress. The previous procedure involved direct insertion of wind stress observations, ignoring model feedback from ocean to atmosphere. The success of the new scheme is attributed to its explicit consideration of ocean-atmosphere coupling and the associated reduction of "initialization shock" and random noise. The so-called spring predictability barrier is eliminated, suggesting that such a barrier is not intrinsic to the real climate system. Initial attempts to generalize the nudging procedure to include SST were not successful; possible explanations are offered. In all experiments forecast skill is found to be much higher for the 1980s than for the 1970s and 1990s, suggesting decadal variations in predictability.

Chen, Dake↗
NASA NTRS1990

Microwave (SSM/I) Estimates of the Precipitation Rate to Improve Numerical Atmospheric Model Forecasts

Delay in the spin-up of precipitation early in numerical atmospheric forecasts is a deficiency correctable by diabatic initialization combined with diabatic forcing. For either to be effective requires some knowledge of the magnitude and vertical placement of the latent heating fields. Until recently the best source of cloud and rain water data was the remotely sensed vertical integrated precipitation rate or liquid water content. Vertical placement of the condensation remains unknown. Some information about the vertical distribution of the heating rates and precipitating liquid water and ice can be obtained from retrieval techniques that use a physical model of precipitating clouds to refine and improve the interpretation of the remotely sensed data. A description of this procedure and an examination of its 3-D liquid water products, along with improved modeling methods that enhance or speed-up storm development is discussed.

Raymond, William H.↗
NASA NTRS2015

Modeled Forecasts of Dengue Fever in San Juan, PR Using NASA Satellite Enhanced Weather Forecasts

Dengue virus is transmitted between humans and mosquitoes of the genus Aedes and causes approximately 96 million cases of disease (dengue fever) each year (Bhatet al. 2013). Symptoms of dengue fever include fever, headache, nausea, vomiting, and eye, muscle and joint pain (CDC). More sever manifestations such as abdominal pain, bleeding from nose and gums, vomiting of blood, and clammy skin occur in rare cases of dengue hemorrhagic fever (CDC). Dengue fever occurs throughout tropical and sub-tropical regions worldwide, however, the geographical range and size of epidemics is increasing. Weather and climate are drivers of dengue virus transmission dynamics (Morin et al. 2013) by affecting mosquito proliferation and the virus extrinsic incubation period (i.e. required time for the virus to replicate and disseminate within the mosquito before it can retransmit the virus).

vector↗
DOE OSTI2025

Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model

Although most of our understanding of boundary layer cloudiness is based on idealized, subtropical, barotropic marine environments, boundary layer clouds exist across a range of conditions. In this study, we use the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and an automated cold-front-relative analysis framework to explore the boundary layer structure associated with low clouds across a transect through the cold front of a midlatitude synoptic cyclone. The model credibly captures boundary layer structure in line with conceptual models of midlatitude cyclones and ground-based observations at Graciosa Island in the Azores. The warm sector is conditionally unstable, with clouds that are too shallow and with too little liquid water, compared to cloud property retrievals from satellite and surface-based instruments. The cold-frontal region exhibits convection associated with weak stability and ascent. Northwest of the cold front, the boundary layer is well mixed, deeper, and capped by a strong inversion maintained by large-scale subsidence. Simulated clouds in frontal and post-frontal regions are mostly too thick, with too much liquid water and too little cloud base drizzle. The post-frontal clouds are associated with grid-scale updrafts, which appear to be the model's attempt to represent mesoscale organization of cellular convection typically observed in the cold sector of midlatitude cyclones. The deep, well-mixed post-frontal boundary layers and cloudiness are maintained by strong surface fluxes, as in cold air outbreaks. Our analysis framework serves as a unique approach to model verification, and our results offer insights into differences in boundary layer cloud behavior between subtropical and synoptic cold-sector regimes.

Eissner, Jordan M. [Univ. of Kansas, Lawrence, KS ↗
NASA NTRS1975

A study of application of remote sensing to river forecasting. Volume 2: Detailed technical report, NASA-IBM streamflow forecast model user's guide

The Model is described along with data preparation, determining model parameters, initializing and optimizing parameters (calibration) selecting control options and interpreting results. Some background information is included, and appendices contain a dictionary of variables, a source program listing, and flow charts. The model was operated on an IBM System/360 Model 44, using a model 2250 keyboard/graphics terminal for interactive operation. The model can be set up and operated in a batch processing mode on any System/360 or 370 that has the memory capacity. The model requires 210K bytes of core storage, and the optimization program, OPSET (which was used previous to but not in this study), requires 240K bytes. The data band for one small watershed requires approximately 32 tracks of disk storage.

Source record↗
NASA NTRS1976

PECHCV, PECHFV, PEFHCV and PEFHFV: A set of atmospheric, primitive equation forecast models for the Northern Hemisphere, volume 3

As part of the SEASAT program of NASA, a set of four hemispheric, atmospheric prediction models were developed. The models, which use a polar stereographic grid in the horizontal and a sigma coordinate in the vertical, are: (1) PECHCV - five sigma layers and a 63 x 63 horizontal grid, (2) PECHFV - ten sigma layers and a 63 x 63 horizontal grid, (3) PEFHCV - five sigma layers and a 187 x 187 horizontal grid, and (4) PEFHFV - ten sigma layers and a 187 x 187 horizontal grid. The models and associated computer programs are described.

Wellck, R. E.↗
NASA NTRS1983

The impact of Seasat-A scatterometer data on GLAS model forecasts

The effect of SASS (Seasat-A Satellite Scatterometer) data on the GLAS analysis and forecast system is assessed. After discussing the objective analysis and assimilation of SASS winds, consideration is given to a scheme developed to objectively dealias the SASS data. Results are then presented from analysis and forecast experiments. The evaluation finds a negligible effect of the SASS data in the Northern Hemisphere. In the Southern Hemisphere, the impact is larger and for the most part beneficial when the VTPR (vertical temperature profile radiometer) is excluded. However, the inclusion of VTPR data effectively eliminates this positive impact, suggesting some redundancy between the two data sets.

Atlas, R.↗
NASA NTRS1987

The effect of increased horizontal resolution on GLA Fourth Order model forecasts

A benchmark series of ten-day weather forecasts has been run with the GLA Fourth Order GCM with both a 4 deg latitude by 5 deg longitude resolution and a 2 deg latitude by 2.5 deg longitude resolution. Ensemble statistics of forecast skill and maps of systematic error fields have been generated for both resolutions. The enhanced resolution added 24 hours of useful predictive skill to the sea level pressure forecasts and 6 hours to the 500 mb height forecasts, but 5 to 6 days into the forecasts the advantage of the finer resolution was lost. The systematic error fields showed that by 8 days the 'climate drift' of the 2 x 2.5 deg forecasts had become pronounced and had caused the loss of predictive skill relative to the 4 x 5 deg forecasts. Additional results indicate that a gravity wave drag parameterization scheme might alleviate the climate drift problem.

Helfand, H. M.↗