PMF source apportionment model dataset inputs and outputs for 9 northwest monitoring sites with data from 2007 to 2018. Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.

This dataset contains the CMAQ model data provided by EPA/ORD researchers for the Makar et al. (2025) paper. It includes CMAQ model data extracted at monitoring stations, CMAQ gridded annual deposition fields, and CMAQ gridded monthly median diurnal deposition diagnostics. The extracted data at monitoring stations is provided in csv text format while the gridded data is provided in netcdf files. This dataset is associated with the following publication: Makar, P., P. Cheung, C. Hogrefe, A. Akingunola, U. Alyuz, J. Bash, M. Bell, R. Bellasio, R. Bianconi, T. Butler, H. Cathcart, O. Clifton, A. Hodzic, I. Kioutsioukis, R. Kranenburg, A. Lupascu, J. Lynch, K. Momoh, J.L. Perez Camanyo, J. Pleim, Y. Ryu, R. San Jose, D. Schwede, T. Scheuschner, M. Shephard, R. Sokhi, and S. Galmarini. Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 25(5): 3049–3107, (2025).

This dataset is a combination of annual Probability of Streamflow Permanence (PROSPER) predictions, Northwest Stream Temperature (NorWeST) predictions of monthly mean stream temperatures for August of each year, and predicted monthly streamflow discharge for stream reaches in the Pacific Northwest from the USGS database of natural monthly streamflow estimates, U.S., 2004-2015. The PROSPER model provides predictions of the annual probability of a 30-meter stream segment maintaining year-round streamflow. The NorWeST model provides annual predictions of monthly mean stream temperature for August for 1-kilometer stream segments. Finally, predictions of natural monthly streamflow were combined with NorWeST and PROSPER to provide information on the volume of water in a given system. The data are merged using the Medium Resolution National Hydrography Dataset, which serves as the foundation for the stream lines that the data are represented with. The intent of this merged dataset is to analyze the availability of current and future aquatic habitat.

This dataset is a combination of annual Probability of Streamflow Permanence (PROSPER) predictions, Northwest Stream Temperature (NorWeST) predictions of monthly mean stream temperatures for August of each year, and predicted monthly streamflow discharge for stream reaches in the Pacific Northwest from the USGS database of natural monthly streamflow estimates, U.S., 2004-2015. The PROSPER model provides predictions of the annual probability of a 30-meter stream segment maintaining year-round streamflow. The NorWeST model provides annual predictions of monthly mean stream temperature for August for 1-kilometer stream segments. Finally, predictions of natural monthly streamflow were combined with NorWeST and PROSPER to provide information on the volume of water in a given system. The data are merged using the Medium Resolution National Hydrography Dataset, which serves as the foundation for the stream lines that the data are represented with. The intent of this merged dataset is to analyze the availability of current and future aquatic habitat.

A simple GIS soil-water balance model for the Amazon Basin, called RisQue (Risco de Queimadasa -- Fire Risk), was used to conduct an analysis of spatial and temporal patterns of drought in moist tropical forests and the complex relationships between patterns of drought and forest fire regimes from 1995 through 2001. The provided data products are the model output estimates of maximum plant-available soil water (PAWmax) at 10 m depth at 8 km resolution and model data inputs of monthly precipitation and evapotranspiration. RisQue estimates PAWmax at 10 m depth starting with a map of PAWmax (1-2 m depth) developed using 1,565 RADAMBRASIL soil texture profiles and empirical relationships between soil texture and critical soil water parameters and then interpolated to 8 km resolution. In RisQue, plant-available soil water (PAW) is depleted by monthly evapotranspiration estimated using the Penman Monteith equation and satellite-derived radiation and recharged by monthly precipitation.There are three data files with this data set, two *.zip, and one GeoTIFF image (.tif). The *.zip files expand to 83 *.asc files of evapotranspiration and 89 *.asc files for precipitation data. The image (.tif) is a map of maximum percent available water at 10 m depth. All the files in this data set are in standard arc/info asciigrid format at 8 km resolution.

This data release contains the model inputs, outputs, and source code (written in R) for a redeveloped PRObability of Streamflow PERmanence (PROSPER) model (version 2.1) that had previously been developed for the Pacific Northwest Region (PROSPER_PNW_2), and a raster data set which shows where influential predictor values were outside the range of calibration data. The PROSPER-PNW version 2.1 model, a random forest model, was redeveloped in the Ranger R package using all the original model inputs consistent with PROSPER_PNW_2 to produce annual streamflow permanence probabilities for calendar years 2004-2016 at a 30-meter stream grid resolution that approximately corresponds to flowlines consistent with the National Hydrography Dataset Medium Resolution (NHD MR). Updated streamflow permanence probabilities ranged from 0 to 1 and were adjusted for the spatial variability in threshold determination of membership of permanence class. The adjusted streamflow permanence probabilities also have an associated estimated standard error. Streamflow permanence class rasters are class determinations based on the adjusted streamflow permanence probability and standard error and replaces the streamflow permanence class from PROSPER_PNW_2.

The Annual Energy Outlook presents longterm annual projections of energy supply, demand, and prices focused on the U.S. through 2050, based on results from EIA's National Energy Modeling System (NEMS). NEMS enables EIA to make projections under alternative, internally-consistent sets of assumptions, the results of which are presented as cases. The analysis in AEO2014 focuses on five primary cases: a Reference case, Low and High Economic Growth cases, and Low and High Oil Price cases. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm