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NASA NTRS2014

The Impact of Microphysics and Planetary Boundary Layer Physics on Model Simulation of U.S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics pararneterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRn Center to select NOAAlNWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boWldary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage oflightuing activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, Eugene W., Jr.↗

NASA NTRS2015

Impact of Asian Aerosols on Precipitation Over California: An Observational and Model Based Approach

Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF-Chem model simulations. After validating the capability of the WRF-Chem in realistically simulating the aerosol-cloud precipitation interactions, we conduct sensitivity studies where the AOD is doubled to diagnose whether an increasing concentration of Asian aerosols over the western United States will lead to further impacts on the cloud and precipitation processes over California. We also perform sensitivity studies where the aerosols will be partitioned into dust-only and pollution-only in order to separate the impacts of the differing Asian aerosol species. The results of our WRF-Chem model simulations aim to show that the trans-Pacific transport of Asian aerosols influence the precipitation associated with atmospheric river events that can ultimately impact the regional climate of the western United States. 1 University

Naeger, Aaron R.↗

NASA NTRS2015

A Module for Assimilating Hyperspectral Infrared Retrieved Profiles into the Gridpoint Statistical Interpolation System for Unique Forecasting Applications

Hyperspectral infrared sounder radiance data are assimilated into operational modeling systems however the process is computationally expensive and only approximately 1% of available data are assimilated due to data thinning as well as the fact that radiances are restricted to cloud-free fields of view. In contrast, the number of hyperspectral infrared profiles assimilated is much higher since the retrieved profiles can be assimilated in some partly cloudy scenes due to profile coupling other data, such as microwave or neural networks, as first guesses to the retrieval process. As the operational data assimilation community attempts to assimilate cloud-affected radiances, it is possible that the use of retrieved profiles might offer an alternative methodology that is less complex and more computationally efficient to solve this problem. The NASA Short-term Prediction Research and Transition (SPoRT) Center has assimilated hyperspectral infrared retrieved profiles into Weather Research and Forecasting Model (WRF) simulations using the Gridpoint Statistical Interpolation (GSI) System. Early research at SPoRT demonstrated improved initial conditions when assimilating Atmospheric Infrared Sounder (AIRS) thermodynamic profiles into WRF (using WRF-Var and assigning more appropriate error weighting to the profiles) to improve regional analysis and heavy precipitation forecasts. Successful early work has led to more recent research utilizing WRF and GSI for applications including the assimilation of AIRS profiles to improve WRF forecasts of atmospheric rivers and assimilation of AIRS, Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI) profiles to improve model representation of tropopause folds and associated non-convective wind events. Although more hyperspectral infrared retrieved profiles can be assimilated into model forecasts, one disadvantage is the retrieved profiles have traditionally been assigned the same error values as the rawinsonde observations when assimilated with GSI. Typically, satellitederived profile errors are larger and more difficult to quantify than traditional rawinsonde observations (especially in the boundary layer), so it is important to appropriately assign observation errors within GSI to eliminate potential spurious innovations and analysis increments that can sometimes arise when using retrieved profiles. The goal of this study is to describe modifications to the GSI source code to more appropriately assimilate hyperspectral infrared retrieved profiles and outline preliminary results that show the differences between a model simulation that assimilated the profiles as rawinsonde observations and one that assimilated the profiles in a module with the appropriate error values.

Berndt, Emily↗

DOE OSTI2020

Validating simulated mountain wave impacts on hub-height wind speed using SoDAR observations

The ascent of stably stratified air over a mountain barrier can trigger the generation of mountain waves. Mountain waves occur frequently over the Columbia River Gorge in western North America and can impact wind power generation over the area. Therefore, predicting the details of mountain waves events (e.g., dominant wavelength, timing, and duration) can be very valuable for the wind energy community. In this study, the ability of the Weather Research and Forecasting (WRF) model to simulate mountain waves and their impact on hub-height wind speed is investigated. Our results suggest that the WRF model has moderate skill in simulating observed mountain wave. Further, given WRF predictions of wavelength range and wave period, the Fast Fourier Transform can calculate the simulated mountain wave impact on hub-height wind speed. The resulting wind speeds agree well with SoDAR observations in terms of both magnitude and pattern. Finally, for the simulated cases, WRF consistently predicts impacts of significant mountain wave events about an hour earlier than the actual observations. Overall, in this work, the sensitivities as well as uncertainties associated with our methodology are discussed in detail.

17 WIND ENERGY↗

DOE OSTI2023

Efficient Super-Resolution of Near-Surface Climate Modeling Using the Fourier Neural Operator

Downscaling methods are critical in efficiently generating high-resolution atmospheric data. However, state-of-the-art statistical or dynamical downscaling techniques either suffer from the high computational cost of running a physical model or require high-resolution data to develop a downscaling tool. Here, we demonstrate a recently proposed zero-shot super-resolution method, the Fourier neural operator (FNO), to efficiently perform downscaling without the need for high-resolution data. Because the FNO learns dynamics in Fourier space, FNO is a resolution-invariant emulator; it can be trained at a coarse resolution and produces emulation at any high resolution. We applied FNO to downscale a 4-km resolution Weather Research and Forecasting (WRF) Model simulation of near-surface heat-related variables over the Great Lakes region. The FNO is driven by the atmospheric forcings, and topographic features used in the WRF model at the same resolution. We incorporated a physics-constrained loss in FNO by using the Clausius-Clapeyron relation to better constrain the relations among the emulated states. Trained on merely 600 WRF snapshots at 4-km resolution, the FNO shows comparable performance with a widely used convolutional network, U-Net, achieving averaged modified Kling-Gupta Efficiency of 0.88 and 0.94 on the test dataset for temperature and pressure, respectively. We then employed the FNO to produce 1-km emulations to reproduce the fine climate features. Further, by taking the WRF simulation as ground truth, we show consistent performances at the two resolutions, suggesting the reliability of FNO in producing high-resolution dynamics. Our study demonstrates the potential of using FNO for zero-shot super-resolution in generating first-order estimation on atmospheric modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Building heights and urban canopy parameters for urban modeling

GLObal Building heights for Urban Studies (UT-GLOBUS) is a random forest model based framework that provides a level-of-detail-1 (LoD-1) building height dataset. The primary objective of UT-GLOBUS is not to precisely predict the height and footprint of individual buildings, but rather to offer a functional framework for generating building level information using open-source datasets for modeling applications. Specifically, UT-GLOBUS is tailored to meet the requirements of deriving urban canopy parameters (UCPs) for the multi-layer model within the Weather Research and Forecasting (WRF) model and building heights for the SOLWEIG and SUEWS model. Building-level data is accessible in vector file format (GeoPackage: .gpkg), which can be converted into raster file format (geoTIFF). The vector files employ the Universal Transverse Mercator (UTM) projection. The vector files are compatible with GIS platforms like QGIS and ArcGIS, and can be imported for analysis using programming languages such as Python. We are also providing UCPs required by the multi-layer urban model in the urban WRF in binary file format. Additionally, we provide the urban fractions calculated using ESA world cover dataset (https://esa-worldcover.org/en) for WRF model in binary file format. These binary files can be directly incorporated into the WRF pre-processing system (WPS).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Urban Parameters Maricopa County 100m Grid Spacing

132 urban parameters for Maricopa County are provided in WRF-readable binary form at 100m grid spacing with index. These parameters allow regional weather modelers to account for the contribution of built structures in modeling the urban heat island. This data is also provided in CSV format. Data are generated using 2023 Model America Version 1 data (https://www.osti.gov/biblio/1774134) and will be used to represent the urban morphology in Maricopa County to the WRF model for experiments conducted for the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL). Three files associated with these parameters are included in this repository: index, binary file 00001-01549.00001-01796, Maricopa_Parameters_03072024.csv . To use the binary file with the Weather Research and Forecasting (WRF) model, the binary file and the index file must be placed in their own directory in WRF_GEOG and accessed in the same way the National Urban Database and Access Portal Tool data (NUDAPT44) would be accessed. The name of the binary file must be in the format: 00001-02715.00001-01803. If, upon download, the binary filename has additional or different characters, please change them to match this format.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Urban Parameters Los Angeles County 100m version 2

132 Urban parameters based on building physical dimensions and location were generated for the city of Los Angeles at 100m resolution using the NATURF model. To use the binary file with WRF, the binary file and the index file must be placed in their own directory in WRF_GEOG and accessed in the same way NUDAPT44 would be accessed. The kmz file can be visualized on Google Earth.

Sweet-Breu, Levi [Baylor University]↗

DOE OSTI2026

High-Resolution ESM Projections for Energy Applications Over the CONUS

Assessing energy resources under future scenarios requires high-resolution meteorological information that is physically consistent and suitable for regional-scale analysis. While Earth system model (ESM) projections provide valuable large-scale information, their coarse resolution and systematic biases limit direct applicability for energy system modeling and planning. In this study, we develop a high-resolution dynamical downscaling framework based on the Weather Research and Forecasting (WRF) model to translate global-scale ESM data into energy-relevant regional projections over the contiguous United States (CONUS). The framework identifies an optimized WRF configuration through numerical experiments and evaluates raw and bias-corrected ESM initial and boundary conditions, with soil moisture (SM) and soil temperature (ST) bias correction implemented as an integral part of the bias-corrected ESM forcing to improve land-atmosphere coupling prior to WRF dynamical downscaling. Using an optimized WRF configuration at 4-km resolution, we show that raw ESM forcing introduces systematic dry and cold soil biases that propagate into pronounced warm biases in near-surface air temperature and positive biases in solar irradiance, particularly during summer. Applying bias-corrected atmospheric forcing together with bias-corrected SM and ST substantially reduces these downstream biases and improves the surface energy balance and near-surface atmospheric fields. These results demonstrate that bias-aware treatment of initial conditions is critical for producing high-resolution downscaled projections suitable for energy system modeling and planning applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

A 30-yr high-resolution weather research and forecasting model downscaling data over California and Nevada

This dataset presents a 30-year high resolution meteorological dataset obtained using the WRF model (Advanced version Research WRF version 4.4). We used WRF and European Centre for Medium-Range Weather Forecasts Reanalysis v5 as initial and boundary conditions to generate gridded meteorological variables. A large number of surface weather stations was used for model validation. A multi-physics analysis was first developed to identify a good physics suite extended from 6 November 00 UTC to 10 November 23 UTC, 2018, which included the Camp Fire in northern California. Based on the best physics suite, the downscaling dataset extends from 1 December to 28 February, 1990–2021 and the horizontal domain has 1.5 km grid spacing covering the entire states of California and Nevada in the United States. Comparisons between hourly surface observations and WRF simulations of air temperature, relative humidity and wind speeds show mean absolute errors on the order of (1.6-2.0 C), (10 %) and 1.2–1.5 m s -1 , respectively.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Examining the effects of soil entrainment during nuclear cloud rise on fallout predictions using a multiscale atmospheric modeling framework

Current operational models for nuclear cloud rise over land were developed and validated using observations from shallow-buried or surface detonations, where lofted soil quickly mixed with fission products from the detonation. These models poorly predict fallout from elevated detonations near the fallout-free height of burst (FFHOB), where interactions with the ground are limited and the mixing of fission products and lofted soil is incomplete. Fallout-free is a misnomer at this HOB, as fallout was observed in these cases, but was below the levels of concern, especially off-grounds of the nuclear test site. To correctly characterize and model fallout from detonations near the FFHOB, models must be developed which can capture the stratified nature of the particle and activity-size distributions within the cloud. Previously, it was shown that the Weather Research and Forecasting (WRF) model can accurately simulate nuclear cloud rise for airbursts with little to no ground interactions (Arthur et al., 2021). That work is expanded here by (1) using a radiation-hydrodynamics code to improve the fireball initialization in WRF, (2) further developing an aerosol package from WRF-Chem to simulate lofted soil, and (3) combining the WRF cloud rise simulations with the operational models used at the National Atmospheric Release Advisory Center (NARAC) for fallout modeling. Using this combination of codes, the Upshot-Knothole Grable detonation, which was just below the FFHOB, is simulated from seconds after detonation through cloud rise and fallout, and results are compared to historical test data. Here, the results show improved prediction of dose rate and highlight the need to correctly characterize the entrainment of material into the cloud and the subsequent mixing of fission products with entrained material.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

Effects of organized convection parameterization on the MJO and precipitation in E3SMv1. Part I: Mesoscale heating

Mesoscale organization of convection is typically not represented in global circulation models, and hence its influence on the global circulation is not accounted for. The heating component of a parameterization that represents the dynamical and physical effects of circulations associated with organized convection, referred to as the multiscale coherent structure parameterization (MCSP), is implemented in the Energy Exascale Earth System Model version 1 (E3SMv1). Numerical simulations are conducted to assess its impact on the simulated climate. Besides E3SMv1 simulations, we performed high-resolution (1 km) simulations using the Weather Research and Forecasting (WRF) Model to determine the temperature tendencies induced by mesoscale convective systems embedded in deep convection. We tuned the free parameters of the MCSP based on the WRF simulations. MCSP heating enhances Kevin wave spectra in E3SMv1, improves the representation of the Madden-Julian Oscillation, and impacts on mean precipitation that vary with locations and seasons, including a reduction of biases over the tropical Pacific.

Climate Modeling↗

DOE OSTI2023

The June 2012 North American Derecho: A Testbed for Evaluating Regional and Global Climate Modeling Systems at Cloud‐Resolving Scales

Abstract In this paper, we introduce a testbed for evaluating and comparing climate modeling systems at cloud resolving scales using hindcasts of the June 2012 North American derecho. To demonstrate its utility for model intercomparison, the testbed is applied to two models: the regionally‐refined Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) at 6.5, 3.25 and 1.625 km grid spacing and the Weather Research and Forecasting (WRF) model with 3.2 and 1.6 km grid spacing. We find the simulation results to be highly sensitive to the initial conditions (ICs), initialization time, and model configurations, with ICs from the Rapid Refresh producing the best simulation. Significant improvement is identified in both models as horizontal grid spacing is refined. While a propagation delay of approximately 2 hr is found in both models, SCREAM at 1.625 km simulates the observed bow echo structure of the derecho well and predicts strong surface gusts that exceed 30 m/s. In comparison, WRF has difficulty producing surface wind over 25 m/s, with wind gusts in WRF 42%–46% lower than in SCREAM. However, WRF has a lower bias in simulating cloud top temperature and extent, but overestimates precipitation intensity. Both models reproduce the observed outgoing longwave radiation spatial patterns well (Pearson correlation >0.88), but, compared with NEXRAD observations, simulate generally larger areas of composite radar reflectivity >40 dBZ and underestimate the precipitating area by ∼47%.

2012 North American derecho↗

DOE OSTI2023

Toward Improved Regional Hydrological Model Performance Using State-Of-The-Science Data-Informed Soil Parameters

Accurate soil moisture and streamflow data are an aspirational need of many hydrologically relevant fields. Model simulated soil moisture and streamflow hold promise but models require validation prior to application. Calibration methods are commonly used to improve model fidelity but misrepresentation of the true dynamics remains a challenge. In this study, we leverage soil parameter estimates from the Soil Survey Geographic (SSURGO) database and the probability mapping of SSURGO (POLARIS) to improve the representation of hydrologic processes in the Weather Research and Forecasting Hydrological modeling system (WRF-Hydro) over a central California domain. Our results show WRF-Hydro soil moisture exhibits increased correlation coefficients ( r ), reduced biases, and increased Kling-Gupta Efficiencies (KGEs) across seven in situ soil moisture observing stations after updating the model's soil parameters according to POLARIS. Compared to four well-established soil moisture data sets including Soil Moisture Active Passive data and three Phase 2 North American Land Data Assimilation System land surface models, our POLARIS-adjusted WRF-Hydro simulations produce the highest mean KGE (0.69) across the seven stations. More importantly, WRF-Hydro streamflow fidelity also increases, especially in the case where the model domain is set up with SSURGO-informed total soil thickness. The magnitude and timing of peak flow events are better captured, r increases across nine United States Geological Survey stream gages, and the mean KGE across seven of the nine gages increases from 0.12 to 0.66. Our pre-calibration parameter estimate approach, which is transferable to other spatially distributed hydrological models, can substantially improve a model's performance, helping reduce calibration efforts and computational costs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗

DOE OSTI2025

A compact x-ray spectrometer for measurements of electron temperature distributions in inertial confinement fusion implosions at OMEGA

The Wedge Range Filter (WRF), commonly used for proton spectroscopy at the OMEGA Laser Facility and National Ignition Facility, is adapted to measure the x-ray continuum spectrum through transmission measurement using a continuous-gradient filter. Continuum x rays emitted from the hotspot of an implosion contain information about the plasma composition and electron temperature. The WRF data are leveraged to probe this distribution, specifically the electron temperature distribution. In this work, the data recorded with the WRF are forward modeled using a temperature distribution model folded with the WRF response function. An uncertainty analysis is conducted through a Bayesian regression algorithm using a Hamiltonian Monte Carlo sampler. This analysis enables the uncertainties in the instrument response to be folded into the uncertainty estimation of the electron temperature and absolute x-ray emission. Data analysis for a series of OMEGA implosions is presented and compared with radiation hydrodynamic simulations.

Lasers↗

DOE OSTI2020

Impact of Lateral Groundwater Flow and Subsurface Lower Boundary Conditions on Atmospheric Boundary Layer Development over Complex Terrain

Credible soil moisture redistribution schemes are essential to meteorological models, as lower boundary moisture influences the balance of surface turbulent fluxes and atmospheric boundary layer (ABL) development. While land surface models (LSMs) have vastly improved in their hydrologic representation, several commonly held assumptions, such as free-draining lower boundary, one-dimensional moisture flux, and lack of groundwater representation, can bias the terrestrial water balance. This study explores the impact of LSM hydrology representation on ABL development in the Weather Research and Forecasting (WRF) meteorological model. The results of summertime WRF simulations with Noah LSM, characterized by 2-m-thick soil and one-dimensional flow, are shown for a domain in the Colorado Rocky Mountain headwaters region. A reference WRF simulation is compared to 1) the same model with soil moisture initialized by the hydrologic model ParFlow; 2) a deep, free-draining simulation; and 3) WRF coupled to ParFlow, a three-dimensional, integrated groundwater-surface water model. Results show that both lateral transport of groundwater and the rate of drainage from the lower soil layer can weaken or reverse the coupling strength between evaporative fraction and ABL over a 5-month summer period. The resulting shifts in low-level moist convection in river valleys and thermally driven airflows yield strengthened anabatic upslope winds and perturbations to regional precipitation.

Forrester, Mary M.↗

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↗