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At least 343 records · Page 19
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DOE OSTI2025

ORBIT-2 Weather and Climate Downscaling Software Repository

ORBIT-2 is a scalable foundation model for global, hyper-resolution climate and weather downscaling. ORBIT-2 incorporates two key innovations: (1) Residual Slim ViT (Reslim), a lightweight architecture with residual learning and Bayesian regularization for efficient, robust prediction; and (2) TILES, a tile-wise sequence scaling algorithm that reduces self-attention complexity from quadratic to linear, enabling long-sequence processing and massive parallelism. ORBIT-2 scales to 10 billion parameters across 65,536 GPUs, achieving up to 4.1 ExaFLOPS sustained throughput and 74–98% strong scaling efficiency. It supports downscaling to 0.9 km global resolution and processes sequences up to 4.2 billion tokens. On 7 km resolution benchmarks, ORBIT-2 achieves high accuracy with 𝑅2 scores in range of 0.98–0.99 against observation data.

Wang, Xiao [Oak Ridge National Laboratory]↗
DOE OSTI2025

Machine learning methods for weather forecasting

SAND2025-14466O This repository contains code for developing, training, and evaluating machine learning models for weather and climate forecasting, including forecast skill assessment, feature importance analysis, and reproducible workflows for model comparison. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Holthuijzen, Maike [Sandia National Lab. (SNL-CA),↗
DOE OSTI2026

Adapt: A Weather Radar Data Analysis and Nowcasting Platform for Informed Adaptive Scanning

SF-26-021 Adapt is a data processing platform for real-time data analysis, short term prediction of targets convective cells and tracking for archived data. It provides tools for downloading, processing, segmenting, projecting, analyzing, and visualizing storm cell data from weather radar. The pipeline includes cell detection, motion estimation using optical flow, cell property extraction, and persistence to NetCDF and SQLite/Parquet for guiding adaptive scanning.

Raut, Bhupendra Ashokrao [Argonne National Laborat↗
DOE OSTI2023

Supporting Advancement in Weather and Water Prediction in the Upper Colorado River Basin: The SPLASH Campaign

Water is a critical resource that causes significant challenges to inhabitants of the western United States. These challenges are likely to intensify as the result of expanding population and climate-related changes that act to reduce runoff in areas of complex terrain. To better understand the physical processes that drive the transition of mountain precipitation to streamflow, the National Oceanic and Atmospheric Administration has deployed suites of environmental sensors throughout the East River watershed of Colorado as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). This includes surface-based sensors over a network of five different observing sites, airborne platforms, and sophisticated remote sensors to provide detailed information on spatiotemporal variability of key parameters. With a 2-yr deployment, these sensors offer detailed insight into precipitation, the lower atmosphere, and the surface, and support the development of datasets targeting improved prediction of weather and water. Initial datasets have been published and are laying a foundation for improved characterization of physical processes and their interactions driving mountain hydrology, evaluation and improvement of numerical prediction tools, and educational activities. SPLASH observations contain a depth and breadth of information that enables a variety of atmospheric and hydrological science analyses over the coming years that leverage collaborations between national laboratories, academia, and stakeholders, including industry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding Observed Precipitation Change and the New Climate Normal from the Perspective of Daily Weather Types in the Southeast United States

Abstract Observed precipitation changes in the Southeast United States (SEUS) are spatially heterogeneous. Most of the inland SEUS and eastern Gulf Coast become drier, and the East Coast north of Charleston, South Carolina, and southern Florida become wetter from the old 30-yr period of 1961–90 to the recent period of 1991–2020. The observed climate change is examined from the perspective of daily weather types (WTs). A k -means clustering analysis has been conducted using daily 850-hPa circulation for 1948–2021. The obtained 10 WTs peak in different seasons, respectively. The frequencies and precipitation intensity of the WTs have been analyzed. A winter WT characterized by a western Appalachian trough (WAT) and a summer WT featuring North Atlantic subtropical high (NASH) have a rising trend of annual frequency from 1948 to 2021. An Appalachian high in the autumn has a decreasing frequency but becomes drier and stronger. Some precipitation intensity change and small location shift have also been observed. The drying up on the eastern Gulf Coast and the inland area of the SEUS is mainly caused by the weakened southwesterly low-level jet (LLJ) on the western flank of the NASH that reduces rain in the spring, the less frequent but stronger and drier Appalachian high in the summer and autumn, and the weaker and more western located Plains trough (PT) in the winter, spring, and autumn. The precipitation increase in the East Coast and southern Florida is majorly due to more frequent, stronger, and rainier troughs along the western Appalachian as well as the East Coast.

Qian, Jian-Hua↗
DOE OSTI2020

Mesoscale to Microscale Simulations over Complex Terrain with the Immersed Boundary Method in the Weather Research and Forecasting Model

Improvements to the Weather Research and Forecasting (WRF) Model are made to enable multiscale simulations over highly complex terrain with dynamically downscaled boundary conditions from the mesoscale to the microscale. Over steep terrain, the WRF Model develops numerical errors that are due to grid deformation of the terrain-following coordinates. An alternative coordinate system, the immersed boundary method (IBM), has been implemented into WRF, allowing for simulations over highly complex terrain; however, the new coordinate system precluded nesting within mesoscale simulations using WRF’s native terrain-following coordinates. Here, the immersed boundary method and WRF’s grid-nesting framework are modified to seamlessly work together. This improved framework for the first time allows for large-eddy simulation over complex (urban) terrain with IBM to be nested within a typical mesoscale WRF simulation. Simulations of the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma, are performed using a multiscale five-domain nested configuration, spanning horizontal grid resolutions from 6 km to 2 m. These are compared with microscale-only simulations with idealized lateral boundary conditions and with observations of wind speed/direction and SF 6 concentrations from a controlled release from intensive observation period 3. The multiscale simulation, which is configured independent of local observations, shows similar model skill predicting wind speed/direction and improved skill predicting SF 6 concentrations when compared with the idealized simulations, which require use of observations to set mean flow conditions. Use of this improved multiscale framework shows promise for enabling large-eddy simulation over highly complex terrain with dynamically downscaled boundary conditions from mesoscale models.

42 ENGINEERING↗
DOE OSTI2020

Evaluating Implementations of the Immersed Boundary Method in the Weather Research and Forecasting Model

The terrain-following coordinate system used by many atmospheric models can cause numerical instabilities due to discretization errors as resolved terrain slopes increase and the grid becomes highly skewed. The immersed boundary (IB) method, which does not require the grid to conform to the terrain, has been shown to alleviate these errors, and has been used successfully for high-resolution atmospheric simulations over steep terrain, including vertical building surfaces. Since many previous applications of IB methods to atmospheric models have used very fine grid resolution (5 m or less), the present study seeks to evaluate IB method performance over a range of grid resolutions and aspect ratios. Two classes of IB algorithms, velocity reconstruction and shear stress reconstruction, are tested within the common framework of the Weather Research and Forecasting (WRF) Model. Performance is evaluated in two test cases, one with flat terrain and the other with the topography of Askervein Hill, both under neutrally stratified conditions. WRF-IB results are compared to similarity theory, observations, and native WRF results. Despite sensitivity to the location at which the IB intersects the model grid, the velocity reconstruction IB method shows consistent performance when used with a hybrid RANS/LES surface scheme. The shear stress reconstruction IB method is not sensitive to the grid intersection, but is less consistent and near-surface velocity errors can occur at coarse resolutions. This study represents an initial investigation of IB method variability across grid resolutions in WRF. Future work will focus on improving IB method performance at intermediate to coarse resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data for: Competitive and Cooperative Effects of Chloride on Palladium(II) Adsorption to Iron (Oxyhydr)oxides: Implications for Mobility During Weathering

Data package for manuscript "Competitive and Cooperative Effects of Chloride on Palladium(II) Adsorption to Iron (Oxyhydr)oxides: Implications for Mobility During Weathering" by Emily G. Wright, Xicheng He, Elaine D. Flynn, Daniel E. Giammar, and Jeffrey G. Catalano. The manuscript will be submitted to Geochimica et Cosmochimica Acta. This dataset contains adsorption results from experiments designed to investigate the effect of chloride on Pd(II) adsorption to hematite and 2-line ferrihydrite. This includes lab experiments reacting suspensions of the minerals with various amounts of Pd and chloride at pH 4. We also characterized adsorbed Pd with X-ray absorption fine structure spectroscopy.

58 GEOSCIENCES↗
DOE OSTI2024

naturf: a package for generating urban parameters for numerical weather modeling

The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (NATURF) is a Python workflow that generates files readable by the Weather Research and Forecasting (WRF) model. NATURF uses geopandas and hamilton to calculate 132 building parameters from shapefiles with building footprint and height information. These parameters can be collected and used in many formats, and the primary output is a binary file configured for input to WRF. This workflow is a flexible adaptation of the National/World Urban Database and Access Portal Tool (NUDAPT/WUDAPT) that can be used with any study area at any spatial resolution. The climate modeling community and urban planners can identify the effects of building/neighborhood morphology on the microclimate using the urban parameters and WRF-readable files produced by NATURF. More information on the urban parameters calculated can be found in the documentation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

National Weather Service Radiosonde Evaluation Field Campaign Report

The purpose of the campaign was to perform a full evaluation of participating vendor’s radiosondes to qualify for potential use in the National Weather Service (NWS) upper air field operations. The NWS has specific requirements that vendors systems were evaluated against to determine if the vendor’s radiosonde performs within specifications. For this evaluation, the NWS was pursuing commercial off-the-shelf (COTS) ground/tracking systems in the 403 MHz frequency band over the previously used Telemetry Receiving System (TRS) and house-built software using the 1680 MHz frequency. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory served as the warm and dry test region. The radiosondes were assessed for precision of the radiosonde (unit under test versus itself) and accuracy of the radiosonde’s humidity measurements (unit under test versus a cryogenic frostpoint hygrometer [CFH]).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Background Data and Statistics on Low-Income Energy Use and Burden for the Weatherization Assistance Program: Update for Fiscal Year 2020

This report provides updated estimates of the energy consumptions, energy expenditures, and energy burdens of the population eligible to be served through the US Department of Energy (DOE) Weatherization Assistance Program (WAP) and by proxy, those clients actually served by the program. WAP continues to serve a population with an energy burden that is much greater than the rest of the county. The mean energy burden for the WAP-eligible population across the United States for FY 2020 is estimated to be 13.9% compared to 3.0% for households living above the 200% poverty threshold. The mean energy burden for households living below the 100% federal poverty line was estimated to be 30.9%. These energy burdens for the WAP-eligible population have remained steady at this high level over the last decade.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Historic Significance and Current Condition Assessment of Building 06-CP-170, the Yucca Flat Weather Station, Area 6, Nevada National Security Site, Nye County, Nevada

This report was produced in partial fulfillment of the mitigation of adverse effects to Building 06-CP-170, the Yucca Flat Weather Station on the Nevada National Security Site (NNSS), and is intended to comply with the 2021 Memorandum of Agreement DE-GM58-21NA25543 Between the U.S. Department of Energy and the Nevada State Historic Preservation Officer Regarding Demolition of Fourteen Buildings and Structures in Area 6 of the Nevada National Security Site, Nye County, Nevada (hereafter referred to as the MOA). This MOA was executed to resolve adverse effects from the U.S. Department of Energy (DOE) plan to demolish 14 architectural resources at the Control Point and in the vicinity in Area 6 of the NNSS. The management and operations contractor for the NNSS identified these 14 architectural resources as environmental hazards unsafe for human occupation due to deterioration and rodent infestation. Building 06-CP-170 is scheduled for demolition as part of this undertaking. Building 06-CP-170 was originally recorded in 2018 during a Section 106 cultural resources inventory for a proposed installation of a 138-kilovolt transmission line on the NNSS. The building was determined individually eligible by the DOE, in consultation with the Nevada State Historic Preservation Office, for inclusion in the National Register of Historic Places under the Secretary of the Interior’s Significance Criterion A because of its association with nuclear testing. Pursuant to Stipulation III.D.3 of the MOA, this report provides a summary of the historic significance of Building 06-CP-170 and a description of its current condition and accessory resources. In addition, an updated Architectural Resource Assessment (ARA) form with new information and photographs is included in the appendix in fulfillment of Stipulation III.D.2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Framework for Incorporating Social Cost of Carbon in Weatherization

This document provides a framework for incorporating [avoided] social cost of carbon (SCC) when calculating cost effectiveness of energy measures under the U.S. Department of Energy Weatherization Assistance Program (WAP). The framework describes the relevant metrics, calculation methodology, and implementation approach that can be adopted by any energy audit software for use under the WAP.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Wind Resource Data for Southeast Asia Using a Hybrid Numerical Weather Prediction with Machine Learning Super Resolution Approach

In this work we develop and present a machine learning based downscaling approach using generative adversarial networks (GANs). GANs learn to distinguish the relationships between low-resolution and high-resolution simulations and generate accurate high-resolution output from low-resolution input (Stengel, Glaws, Hettinger, & King, 2020). Low-resolution numerical weather prediction (NWP) simulations at 9-km spatial and 60-minute temporal resolution were executed over Southeast Asia to provide input to the GANs model. GANs for wind, temperature, and pressure were trained on coarsened WIND Toolkit data with a diverse sampling of terrain and meteorological conditions. After training, the NWP simulations over Southeast Asia were enhanced by 3x along each horizontal spatial dimension and 4x along the temporal dimension. This novel downscaling approach generated 15-year high-resolution wind, temperature, and pressure data from January 2007 through December 2021 at multiple hub heights over Southeast Asia at 3-km spatial and 15-minute temporal resolution with a 16x reduction in compute time over standard dynamical downscaling.

17 WIND ENERGY↗