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DOE OSTI2021

The WRF-Solar Ensemble Prediction System to Provide Solar Irradiance Probabilistic Forecasts

In this study, we introduce the recently developed WRF-solar ensemble prediction system and a calibration method. The performances of forecast models are evaluated using the National Solar Radiation Database observational analysis for day-ahead solar irradiance predictions. The results demonstrate that the ensemble forecast improves the quality of the forecasts by considering the uncertainty of each ensemble member. The analog ensemble calibration contributed to the reduction of positive bias and an overall improvement in the probabilistic attributes, such as reliability and statistical consistency.

14 SOLAR ENERGY↗

DOE OSTI2025

Hestia-SWIFL: hourly anthropogenic fossil fuel CO2 and heat on the 2km WRF grid, version 1.1

The Hestia-SWIFL version 1.1 anthropogenic heat (AH) and fossil fuel CO2 (FFCO2) emissions data product represent emissions due to the combustion of fossil fuel and cement production within the state of Arizona from 2019 to 2022. This product was developed as part of the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL) project, which aims to provide new knowledge and tools that address extreme heat, air quality, climate change and related urban environmental issues by integrating high-resolution observations, modeling, and civic engagement. The emissions are generated using a bottom-up/engineering approach and are tied to results generated by the Vulcan Project version 4, an effort to quantify space/time-resolved FFCO2 & AH emissions for the entire United States landscape. A large number of data sources are combined to best estimate the emissions at fine scales such as air quality emissions data, traffic flow data, building information, sociodemographic information, and fuel statistics. The AH product provides emissions for two emissions sources (transportation and point source emissions) in units of Watts per hour per square meter (W/m2) per year (annual files) or per hour (hourly files). The FFCO2 product provides emissions from nine individual emission sectors as well as the total, and in units of tons of carbon (tC) per grid cell per year or per hour. The output made available here places the native spatial resolution of the Hestia FFCO2 & AH emissions data product (points, lines, and polygons) into a regularized 2km x 2km grid at hourly and annual temporal resolutions, and stored in netCDF files. The exact spatial extent is defined by the ASU Weather Research Forecast (WRF) simulation grid. All data are processed using R/Python pm high-performance computing system. 2-27-2026 updates: Bugs in airport hourly profile (both AH and FFCO2) and building spatial patterns (FFCO2 only) were fixed. Hourly emissions are reprocessed for all years to reflect those changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Influences of Cloud Microphysics on the Components of Solar Irradiance in the WRF-Solar Model

An accurate forecast of Global Horizontal solar Irradiance (GHI) and Direct Normal Irradiance (DNI) in cloudy conditions remains a major challenge in the solar energy industry. This study focuses on the impact of cloud microphysics on GHI and its partition into DNI and Diffuse Horizontal Irradiance (DHI) using the Weather Research and Forecasting model specifically designed for solar radiation applications (WRF-Solar) and seven microphysical schemes. Three stratocumulus (Sc) and five shallow cumulus (Cu) cases are simulated and evaluated against measurements at the US Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, Southern Great Plains (SGP) site. Results show that different microphysical schemes lead to spreads in simulated solar irradiance components up to 75% and 350% from their ensemble means in the Cu and Sc cases, respectively. The Cu cases have smaller microphysical sensitivity due to a limited cloud fraction and smaller domain-averaged cloud water mixing ratio compared to Sc cases. Cloud properties also influence the partition of GHI into DNI and DHI, and the model simulates better GHI than DNI and DHI due to a non-physical error compensation between DNI and DHI. The microphysical schemes that produce more accurate liquid water paths and effective radii of cloud droplets have a better overall performance.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Quantifying the City-Scale Impacts of Impervious Surfaces on Groundwater Recharge Potential: An Urban Application of WRF–Hydro

Decades of urbanization have created sprawling, complex, and vulnerable cities, half of which are located in water-scarce areas. With the looming effects of climate change, including increasing droughts and water shortages, there is an urgent need to better understand how urbanization impacts the water cycle at city scale. Impervious surfaces disrupt the natural flow of water, affecting groundwater recharge in water-scarce cities, such as Los Angeles, looking to harness local water resources. In the face of growing water demand, informing on opportunities to maximize potential groundwater recharge can help increase cities’ resilience. WRF–Hydro, a physics-based hydrological modeling system, capable of resolving atmospheric, land surface, and hydrological processes at city scale, is adapted to represent urban impervious surfaces. The modified model is used to assess the hydrological implications of historical urbanization. Pre- and post-urban scenarios are used to quantify the impacts of impervious surfaces on the local water budget. Our results show that urbanization in LA has vastly decreased the potential for groundwater recharge, with up to half of the water inflow being redirected from infiltration in highly urbanized watersheds, while doubling surface runoff’s share of the city’s water budget, from ~15% to 30%. This study not only sheds light on the role of imperviousness on groundwater recharge in water-scarce cities, but also offers a robust and transferable tool for the management of urban land and water resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

WRF Simulation Data for LASSO-CACTI Overview Paper

A portion of the LASSO-CACTI simulation output was used in writing the LASSO-CACTI overview paper, which has been submitted to Geoscientific Model Development as of November 2025 by Gustafson et al. This product contains YAML files to be used in conjunction with the LASSO-CACTI Bundle Browser to download the specific WRF data used with each figure in the paper. This reduces the overall data downloaded so that the entire 2 PB data set is not needed.

{WRF,LASSO-CACTI}↗

NASA NTRS2020

An Examination of the Impact of Grid Spacing on WRF Simulations of Wintertime Precipitation in the Mid-Atlantic United States

A large set of deterministic and ensemble forecasts was produced to identify the optimal spacing for forecasting U.S. East Coast snowstorms. WRF forecasts were produced on cloud-allowing (~1-km grid spacing) and convection-allowing (3–4 km) grids, and compared against forecasts with parameterized convection (>~10 km). Performance diagrams were used to evaluate 19 deterministic forecasts from the winter of 2013–14. Ensemble forecasts of five disruptive snowstorms spanning the years 2015–18 were evaluated using various methods to evaluate probabilistic forecasts. While deterministic forecasts using cloud-allowing grids were not better than convection-allowing forecasts, both had lower bias and higher success ratios than forecasts with parameterized convection. All forecasts were underdispersive. Nevertheless, forecasts on the higher-resolution grids were more reliable than those with parameterized convection. Forecasts on the cloud-allowing grid were best able to discriminate areas that received heavy snow and those that did not, while the forecasts with parameterized convection were least able to do so. It is recommended to use convection-resolving and (if computationally possible) to use cloud-allowing forecast grids when predicting East Coast winter storms.

Snowstorms↗

NASA NTRSDate not supplied

Joint Assimilation of Surface, GEO, and LEO CO, NO2, and O3 In Situ and Partial Column/Profile Retrievals with WRF-Chem/DART

Low earth orbiting (LEO) satellites like OMI or TROPOMI and geostationary satellites like TEMPO (to be launched January 2023) provide ozone (O3) retrieval profiles that extend into the stratosphere. Regional models like WRF-Chem generally do not include the stratosphere and have vertical grids that end near the tropopause. This causes difficulties when assimilating O3 retrievals (both column and profile retrievals) because the respective observation forward operators require model O3 profiles that extend into the stratosphere. In this presentation, we look at results from assimilating O3 observation from surface (in situ measurements), multiple LEO (profile retrievals), and GEO (proxy profile retrievals) platforms in as regional model where we use a global chemical transport model (GCTM) to provide O3 upper boundary conditions (BCs) to enable application of the O3 observation forward operators. We will also present results from assimilating O3 retrievals together with carbon monoxide (CO) observations from surface (in situ measurements) and multiple LEO platforms (column and profile retrievals), and nitrogen dioxide (NO2) observations from surface (in situ measurements), multiple LEO (column retrievals), and GEO (proxy column retrievals) platforms. Our joint assimilation experiments show that sometimes the observations complement each, e.g., when assimilating surface and satellite CO or NO2 observations, and sometimes the observations conflict with each other, e.g., when assimilating observations that are biased with respect to other observations (e.g., CO retrievals), or when the assimilation increments conflict due to their chemical interaction (e.g., surface O3 and NO2 retrievals). Results from assimilation of O3 retrieval profiles in regional model are preliminary and will also be discussed in our presentation. Our expectation is that using GCTM O3 as upper BCs in the regional model for evaluation of the O3 forward operator will improve our O3 forecasts. In summary, we will present results from jointly assimilating surface, LEO, and GEO CO, NO2, and O3 in situ and satellite observations in a regional model with dynamic emissions estimation. This study uses proxy GEO observations as a prelude to actual observations because the GEO platform will not be launched until after our presentation.

WRF-Chem/DART↗

NASA NTRSDate not supplied

Assimilation of GEO and LEO Satellite Retrievals in WRF-Chem (15 km and 4 km) with ‘Top-Down’ Emissions Estimation

We are constraining concentrations and emissions for all criteria pollutants (CO, O3, NO2, SO2, PM10, and PM2.5) with WRF-Chem/DART in applications for FRAPPE (15-km grid) and COLORADO (4-km grid). Our results show that: (i) dynamic emissions estimation at medium resolutions (15 km) improves forecast skill; (ii) At high resolutions, the results look good, but we do not have validation data; (iii) for what may be the first time, we assimilate O3 retrieval profiles in a regional model. The problem is that the averaging kernels generally extend above the upper boundary of regional models. We use O3 upper boundary conditions from the global model to solve that problem; and (iv) In the high resolution experiments, we document the potential benefits of assimilating TEMPO O3 profile and NO2 tropospheric column retrievals. Here, we assimilate proxy TEMPO retrievals from a GEOS-Chem nature run, so there’s a conceptual problem due to the potential bias of the proxy retrievals, but the point is to demonstrate our ability to assimilate TEMPO and identify its potential impacts.

Chemical data assimilation↗

DOE OSTI2023

Projected changes in extreme streamflow and inland flooding in the mid-21st century over Northeastern United States using ensemble WRF-Hydro simulations

Study region: Northeastern United States (NEUS). Study focus: We investigate the potential impacts of climate change on precipitation, streamflow, and inland flooding in the NEUS during the mid-21st century. Dynamically downscaled climate projections from three global climate models for historical (1995-2004) and future (2045-2054) periods under business-as-usual scenarios were used to force the hydrologic model WRF-Hydro at 200-meter resolution and create ensemble hydrologic simulations. Additionally, an extreme value model was developed to project the risks associated with low-frequency hydrologic events. New hydrological insights for the region: Results from four major watersheds indicate a significantly wetter regime in winter months and potential drier conditions during late spring to early summer. Discharges in fall are projected to decrease in the northern watersheds and increase toward the south. Extreme flow and water depths resulting from extreme inland flooding are projected to increase by 5-20% and > 100%, respectively. The extent of the total flooded area is likely to be 20% greater by the mid-century. These increased risks can be attributed to (i) an approximate 25% increase in decadal mean and > 40% increase in decadal extreme precipitation intensity, (ii) up to 30% lower snow availability and 5-25% higher evapotranspiration throughout the year, and (iii) a projected 5% increase in soil moisture in all seasons except summer. Furthermore, rapid snow melting in winter will likely cause an earlier peak flow in the rivers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Amazonian Moisture Recycling Revisited Using WRF With Water Vapor Tracers

Previous studies have estimated that 25%–35% of Amazonian precipitation comes from evapotranspiration (ET) within the basin. However, due to simplifying assumptions of traditional models, these studies primarily focus on large spatial and temporal scales. This study is the first to analyze the moisture of Amazonian origin at the annual to daily timescale in four different subregions of the Amazon. We analyze the sources, sinks and stores of moisture that originates as Amazonian ET. To do this, we use the Weather Research and Forecast (WRF) regional meteorological model with the added capability of water vapor tracers to track this moisture. Moisture of Amazonian origin shows strong annual and semi-annual signals, with contrasting behavior between the northern and southern parts of the basin. The tracers reveal a strong diurnal cycle of Amazonian water vapor which had not been previously reported. This signal is related to the diurnal cycle of ET, convective precipitation and advected moisture. ET's contribution to atmospheric moisture increases from early morning into the afternoon. Some of this moisture is rained out through convective storms in the early evening. Later in the night and following morning, strong winds associated with the South American Low Level Jet advect moisture downwind. Overall, the beating pattern becomes apparent when visualizing the Amazonian water vapor as an animation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Evaluating the performance of WRF urban schemes and PBL schemes over Dallas-Fort Worth during a dry summer and a wet summer

This study evaluated the Weather Research and Forecasting (WRF) model sensitivity to different planetary boundary layer (PBL) schemes (the YSU and MYJ schemes) and urban schemes including the bulk scheme (BULK), single-layer urban canopy model (UCM), multi-layer building environment parameterization (BEP) model, and multi-layer building energy model (BEM). Daily reinitialization simulations were conducted over Dallas-Fort Worth during a dry summer month (July 2011) and a wet summer month (July 2015) with weaker (stronger) daytime (nocturnal) UHI in 2011 than 2015. All urban schemes overestimated the urban daytime 2m temperature in both summers, but BEP and BEM still reproduced the daytime urban cool island in dry summer. All urban schemes reproduced the nocturnal urban heat island, with BEP producing the weakest one due to its unrealistic urban cooling. BULK and UCM overestimated the urban canopy wind speed, while BEP and BEM underestimated it. The urban schemes showed prominent impact on daytime PBL profiles. UCM+MYJ showed a superior performance than other configurations. The relatively large (small) aspect ratio between building height and road width in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy temperature. The relatively low (high) building height in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy wind speed. Improving urban schemes and providing realistic urban parameters were critical for improving urban canopy simulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A Moving-Wave Implementation in WRF to Study the Impact of Surface Water Waves on the Atmospheric Boundary Layer

Abstract While numerous modeling studies have focused on the interaction of ocean surface waves with the atmospheric boundary layer, most employ idealized waves that are either monochromatic or synthetically generated from a theoretical wave spectrum, and the atmospheric solvers are typically incompressible. To study wind–wave coupling in real-world scenarios, a model that can simulate both realistic meteorological and wave conditions is necessary. In this paper we describe the implementation of a moving bottom boundary condition into the Weather Research and Forecasting Model for large-eddy simulation applications. We first describe the moving bottom boundary conditions within WRF’s pressure-based vertical coordinate system. We then validate our code with idealized test cases that have analytical solutions, including flow over a monochromatic wave with and without viscosity. Finally, we present results from turbulent flows over a moving monochromatic wave with different wave ages, and demonstrate satisfactory agreement of the wave growth rate with results from the literature. We also compare atmospheric stress and wind parameters from two physically equivalent cases. The first specifies a wind moving in the same direction as a propagating wave, while the second involves a stationary wave with the wind adjusted such that the wind relative to the wave is the same as in the first case. Results indicate that the velocity and Reynolds stress profiles for the two cases match, further validating the moving bottom implementation.

17 WIND ENERGY↗

DOE OSTI2025

A Large-Eddy Simulation Study in WRF on Wind over Broadband Waves of Different Directions and Spreading Widths

We use the Weather Research and Forecasting (WRF) Model coupled with moving waves to conduct large-eddy simulations (LESs) of wind over broadband waves with different propagating directions and spreading widths. Our results show that wind-opposing waves can double the form drag, and the wave propagating direction affects the mean wind velocity, velocity variances, and pressure stress. On the other hand, waves with wider spread tend to reduce the form drag in the streamwise direction. Results further indicate that the wave direction can impact the bulk drag coefficient by as much as 25%, while the wave directional spreading width can change it by 5%. Based on our wave-phase-resolved simulations, we demonstrate that the parameterization of sea surface roughness is significantly influenced by the direction of wave propagation relative to the wind, a factor that the commonly used Charnock relation does not account for.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Five-day track forecast skills of WRF model for the western North Pacific tropical cyclones

In this study, the characteristics of simulated tropical cyclones (TCs) over the western North Pacific by a regional model (the WRF Model) are verified. We utilize 12-km horizontal grid spacing, and simulations are integrated for 5 days from model initialization. A total of 125 forecasts are divided into five clusters through the k-means clustering method. The TCs in the cluster 1 and 2 (group 1), which includes many TCs moving northward in the subtropical region, generally have larger track errors than for TCs in cluster 3 and 4 (group 2). The optimal steering vector is used to examine the difference in the track forecast skill between these two groups. The bias in the steering vector between the model and analysis data is found to be more substantial for group 1 TCs than group 2 TCs. The larger steering vector difference for group 1 TCs indicates that environmental fields tend to be poorly simulated in group 1 TC cases. Furthermore, the residual terms, including the storm-scale process, asymmetric convection distribution, or beta-related effect, are also larger for group 1 TCs than group 2 TCs. Therefore, it is probable that the large track forecast error for group 1 TCs is a result of unreasonable simulations of environmental wind fields and residual processes in the midlatitudes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

AmeriFlux CA-WRF White River Fen

This is the AmeriFlux version of the carbon flux data for the site CA-WRF White River Fen. Site Description - This flux tower is installed in a 10 ha natural boreal intermediate fen dominated by sedges.

Barreto, Carlos [Ontario Ministry of Natural Resou↗

DOE OSTI2022

Studying Cloud and Radiative Impacts Through an Improved Physically Based Representation of Organic Aerosol in a Large-Scale Model (WRF-Chem) (Final Report)

The work performed under this award resulted in the development of a computationally-efficient kinetic model to simulate the chemistry, thermodynamics, and microphysics of organic aerosol. Versions of the kinetic model were used to study a suite of aerosol processes including, multigenerational gas-phase chemistry, phase-state influenced gas/particle partitioning, heterogeneous oxidation, oligomerization reactions, and experimental artifacts. The kinetic model has now been implemented into a regional chemistry-climate model (WRF-Chem) to further study the formation, evolution, properties, and spatiotemporal distribution of organic aerosol at urban, regional, and global scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

5-minute Wind Power Data based on WFIP2 WRF Simulation

The second Wind Forecast Improvement Project (WFIP2) was a public-private partnership funded by the U.S. Department of Energy and NOAA, aimed at enhancing the forecast skill of numerical weather prediction models for turbine-height winds in regions with complex terrain. An 18-month Weather Research and Forecasting (WRF) model simulation was conducted over the Pacific Northwest, with model outputs validated against observational data collected during WFIP2. Simulated wind speeds were used to estimate wind power generation using reV (the Renewable Energy Potential Model developed by NREL) at ten wind project sites. Two sets of results were produced: one using wind speeds extracted from the model grid cell at the project centroid, and another using wind speeds from the actual turbine locations. For each dataset, power output was calculated using both actual turbine-specific power curves and nine generic power curves to convert wind speed into power.

17 WIND ENERGY↗

DOE OSTI2020

Dataset for "FLEXPART-WRF simulations to assess dust transport in the convective boundary layer at the Southern Great Plains site"

Soil dusts are an important source of aerosol in agricultural regions and can affect the Earth’s radiation budget through the modification of cloud properties, and in particular, through their ability to act as ice nucleating particles. In order to impact cloud properties, agricultural soil dusts need to be transported from the point of emission to cloud-relevant altitudes. Vertical transport within the planetary boundary layer is strongly controlled by turbulence and is challenging to represent accurately in regional and global models. Large-eddy simulations (LES) are run at resolutions capable of resolving most of the turbulent energy directly and can thus better simulate vertical transport. In this study, we leverage the LES ARM Symbiotic Simulation and Observation (LASSO) large-eddy simulations to simulate vertical transport of agricultural dust within the turbulent boundary layer using a modified version of the stochastic dispersion model FLEXPART-WRF. We find that the modified model is better capable of simulating particle transport due to turbulence, and that particle size was the greatest factor in determining particle lifetime. Individual meteorology and particle density had intermediate effects upon particle transport, while release height had little effect upon simulation results. Finally, we utilize a quasi-single column model (QSCM) approach to determine how our results compare to a parameterized treatment of turbulence. The QSCM simulations led to greater tracer transport out of the boundary layer, with ramifications for any studies utilizing a Lagrangian stochastic model to understand tracer dispersion. These results highlight the importance of accurately simulating turbulence for understanding particle transport.

54 ENVIRONMENTAL SCIENCES↗