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NASA NTRS2018

GMI-IPS: Processing & Visualization Software Used in ATom DC-8 Aircraft Studies

NASA's Atmospheric Tomography Mission (ATom) deployed in each of the four seasons during 2016-2018, the DC-8 aircraft in order to establish global-scale datasets intended to improve the representation of chemically reactive gases in global atmospheric chemistry models (ACMs). The Global Modeling Initiative (GMI) executed simulations for each ATom flight using the GMI Chemistry Transport Model (GMI-CTM) to provide species concentrations of chemical gases along the DC-8 flight transects. To solve the problem of translating the GMI-CTM simulation data to the unique spatial resolutions of each ATom flight, the GMI ICARTT Processing Software (GMI-IPS) was developed.The GMI-IPS is written in Python and provides data processing, flight extraction, and visualization support for aircraft research projects using ICARTT format, which is a standard format for airborne instrument data. Additionally, the GMI-IPS interpolates global gridded model data from Hierarchical Data Format (HDF) to ICARTT compatible flight transects. Software classes for instruments and collections provided by the ATom DC-8 aircraft such as MER10, MMS, etc. are derived from a common base class. Other functionality provided by the GMI-IPS are: deriving missing flight entries along a transect, reading ICARTT entries from file, and providing Python data structures for storing flight and model information, and more.The GMI-IPS is GIT source controlled, has approximately 30,000 lines of code, and supports parallelization across data collections. It delivered GMI-CTM data for more than forty distinct DC-8 aircraft flights that took place under ATom. The output ICARTT files adhere to format standard V1.1, and pass the scan utility provided by NASA LaRC Airborne Science Data for Atmospheric Composition. This presentation will include a software and methods overview, and results from ATom, including assessments using the GMI-CTM showing how well observations from ATom flight transects represent a broader region.

Damon, M. R.↗

NASA NTRS2012

The Influence of Pickup Protons, from Interstellar Neutral Hydrogen, on the Propagation of Interplanetary Shocks from the Halloween 2003 Solar Events to ACE and Ulysses: A 3-D MHD Modeling Study

We describe our 3-D, time ]dependent, MHD solar wind model that we recently modified to include the physics of pickup protons from interstellar neutral hydrogen. The model has a time-dependent lower boundary condition, at 0.1 AU, that is driven by source surface map files through an empirical interface module. We describe the empirical interface and its parameter tuning to maximize model agreement with background (quiet) solar wind observations at ACE. We then give results of a simulation study of the famous Halloween 2003 series of solar events. We began with shock inputs from the Fearless Forecast real ]time shock arrival prediction study, and then we iteratively adjusted input shock speeds to obtain agreement between observed and simulated shock arrival times at ACE. We then extended the model grid to 5.5 AU and compared those simulation results with Ulysses observations at 5.2 AU. Next we undertook the more difficult tuning of shock speeds and locations to get matching shock arrival times at both ACE and Ulysses. Then we ran this last case again with neutral hydrogen density set to zero, to identify the effect of pickup ions. We show that the speed of interplanetary shocks propagating from the Sun to Ulysses is reduced by the effects of pickup protons. We plan to make further improvements to the model as we continue our benchmarking process to 10 AU, comparing our results with Cassini observations, and eventually on to 100 AU, comparing our results with Voyager 1 and 2 observations.

Detman, T. R.↗

NASA NTRS2002

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

Fox-Rabinovitz, Michael S.↗

NASA NTRS2009

Forecasting Lightning Threat using Cloud-resolving Model Simulations

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\dgc\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

McCaul, E. W., Jr.↗

NASA NTRS2015

Improving the Timeliness of Winter Wheat Production Forecast in the United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day Information

Wheat is themost important cereal crop traded on international markets and winter wheat constitutes approximately 80% of global wheat production. Thus, accurate and timely production forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) developed an empirical generalized model for forecasting winter wheat production. Their approach combined BRDF-corrected daily surface reflectance from Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop typemasks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel (area within the CMG pixel occupied by wheat), and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. In this study, we include Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts while conserving the accuracy of the original model. We apply this modified model to three major wheat-producing countries: the Unites States (US), Ukraine and China from 2001 to 2012. We show that a reliable forecast can be made between one month to a month and a half prior to the peak NDVI (meaning two months to two and a half months prior to harvest), while conserving an accuracy of 10% in the production forecast.

Production↗

NASA NTRS2003

Using Satellite-derived Ice Concentration to Represent Antarctic Coastal Polynyas in Ocean Climate Models

The focus of this paper is on the representation of Antarctic coastal polynyas in global ice-ocean general circulation models (OGCMs), in particular their local, regional, and high-frequency behavior. This is verified with the aid of daily ice concentration derived from satellite passive microwave data using the NASATeam 2 (NT2) and the bootstrap (BS) algorithms. Large systematic regional and temporal discrepancies arise, some of which are related to the type of convection parameterization used in the model. An attempt is made to improve the fresh-water flux associated with melting and freezing in Antarctic coastal polynyas by ingesting (assimilating) satellite ice concentration where it comes to determining the thermodynamics of the open-water fraction of a model grid cell. Since the NT2 coastal open-water fraction (polynyas) tends to be less extensive than the simulated one in the decisive season and region, assimilating NT2 coastal ice concentration yields overall reduced net freezing rates, smaller formation rates of Antarctic Bottom Water, and a stronger southward flow of North Atlantic Deep Water across 30 S. Enhanced net freezing rates occur regionally when NT2 coastal ice concentration is assimilated, concomitant with a more realistic ice thickness distribution and accumulation of High-Salinity Shelf Water. Assimilating BS rather than NT2 coastal ice concentration, the differences to the non-assimilated simulation are generally smaller and of opposite sign. This suggests that the model reproduces coastal ice concentration in closer agreement with the BS data than with the NT2 data, while more realistic features emerge when NT2 data are assimilated.

Stoessel, Achim↗

DOE OSTI2026

Scaled Implementation of Smart Charge Management for Electric Vehicles

Smart charge management (SCM) has become a critical strategy for mitigating potential grid impacts and reducing electricity costs for all customers. This study will evaluate the economics of implementing light-duty EV SCM at scale across the United States. This work will enhance distribution system analysis by estimating SCM implementation costs, exploring viable business cases, and developing a framework for national-level applications. The primary methodology involves leveraging detailed grid modeling from a specific service territory and using spatial extrapolation techniques to generalize findings to other regions. The analysis will develop key metrics to quantify the costs and benefits of SCM, including implementation costs relative to strategy and scale, the cost of distribution system upgrades with and without SCM, and the percentage of peak-load reduction. The objective is to produce a comprehensive report and a parameterized framework that enables utilities to self-assess the value of SCM in their own service territories. This will support the development of cost-effective charging strategies, accelerate the energization of new EV chargers, and facilitate the seamless integration of EVs into the nation's power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2008

Forecasting Lightning Threat using Cloud-Resolving Model Simulations

Two new approaches are proposed and developed for making time and space dependent, quantitative short-term forecasts of lightning threat, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the WRF model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed phase region at the-15 C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash rate proxy fields against domain-wide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. Our blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Exploratory tests for selected North Alabama cases show that, because WRF can distinguish the general character of most convective events, our methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models,the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of forecasts become available.

McCaul, Eugene W., Jr.↗

NASA NTRS2000

Operational Assimilation of GOES Data into a Mesoscale Model

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite- observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the Global Hydrology and Climate Center (GHCC) within the Penn State/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) since 1 November 1998. We performed the assimilation on a model grid centered over the Southeastern US. In addition, a control run without assimilation was performed to provide insight into the performance of the assimilation technique. Bulk verification statistics (BIAS and RMSE) of surface air temperature and relative humidity of more than 250 case days has been performed to date. Results show that assimilation of the satellite data results reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. We are working with forecasters at the National Weather Service Forecast Office located in Birmingham, AL to evaluate the impact of the assimilation on precipitation forecasts. In addition, work is currently underway to determine the ability of both the assimilation technique and Early Eta to sense the significant changes that occur in both leaf expansion and soil moisture conditions during the Spring-Summer of 1999. This will be accomplished via examination of the simulated surface energy budgets from both modeling systems.

Lapenta, William↗

NASA NTRS2007

Generating a Long-Term Land Data Record from the AVHRR and MODIS Instruments

The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments for land climate studies. The project will create daily surface reflectance and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for MODIS products from EOS Terra and Aqua. Higher order products such as burned area, land surface temperature, albedo, bidirectional reflectance distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA satellites by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in MODIS processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface reflectance product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for MODIS land product quality assessment. The land surface reflectance products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at http://ltdr.nascom.nasa.gov/ltdr/ltdr.html.

Pedelty, Jeffrey↗

DOE OSTI2024

Empowering Rural Electrification in Honduras: An Integrated Assessment of PV/BESS and Productive Uses of Electricity in Gracias a Dios

Honduras faces significant challenges in its energy sector, particularly in rural areas where access to reliable and affordable electricity remains limited. The flagship rural electrification initiative for Honduras Secretary of Energy (SEN) is the Politica de Acceso Universal a la Electricidad (PAUEH - Universal Electricity Access Policy), a key solution for addressing this energy poverty is the deployment of more than 1700 distributed solar and hybrid mini-grid solutions. In late 2023 as a first step towards supporting SEN's electrification efforts, the National Renewable Energy Laboratory (NREL) developed a literature review of SEN electrification policy documents and conducted a series of technical capacity-building workshops with SEN and other energy sector stakeholders in Honduras focused on using NREL's open-source REopt tool to conduct techno-economic assessments and develop least-cost optimizations for potential solar + storage mini-grid systems. Building on some initial capacity building on mini-grid modeling, the National Renewable Energy Laboratory (NREL) worked with SEN to develop a detailed techno-economic assessment for electrifying two schools, a healthcare clinic, and a hospital in a hypothetical community within the department of Gracias a Dios. The analysis also evaluates the business case for cold storage productive use of energy (PUE) applications for the fisheries value chain and how the incorporation of these PUE loads potentially impacts both the viability of the PV+BESS solutions as well as local economic development. By assessing the potential for deployment of integrated PV/BESS systems to both support critical community services like education and healthcare, as well as potential for downstream enterprise and economic development, this analysis represents a first step that can help to inform specific strategies for development of pilot PV+BESS projects aligned with national priorities and sector level planning under PAUEH.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Early Exploration of a Flexible Framework for Efficient Quantum Linear Solvers in Power Systems

The rapid integration of renewable energy resources presents formidable challenges in managing power grids. While advanced computing and machine learning techniques offer some solutions for accelerating grid modeling and simulation, there remain complex problems that classical computers cannot effectively address. Quantum computing, a promising technology, has the potential to fundamentally transform how we manage power systems, especially in scenarios with a higher proportion of renewable energy sources. One critical aspect is solving linear systems of equations, crucial for power system applications like power flow analysis, for which the Harrow-Hassidim-Lloyd (HHL) algorithm is a well-known quantum solution. However, HHL quantum circuits often exhibit excessive depth, making them impractical for current Noisy-Intermediate-Scale-Quantum (NISQ) devices. In this paper, we introduce a versatile framework, powered by NWQSim, that bridges the gap between power system applications and quantum linear solvers available in Qiskit. This framework empowers researchers to efficiently explore power system applications using quantum linear solvers. Through innovative gate fusion strategies, reduced circuit depth, and GPU acceleration, our simulator significantly enhances resource efficiency. Power flow case studies have demonstrated up to a eight-fold speedup compared to Qiskit Aer, all while maintaining comparable levels of accuracy.

quantum computing, Harrow-Hassidim-Lloyd, high-per↗

DOE OSTI2024

Fortalecimiento de la Electrificación Rural en Honduras: Una Evaluación Integrada de PV+BESS y Usos Productivos de la Electricidad en Gracias a Dios, Honduras [Empowering Rural Electrification in Honduras: An Integrated Assessment of PV/BESS and Productive Uses of Electricity in Gracias a Dios] (Spanish Translation)

14 SOLAR ENERGY↗

DOE OSTI2024

Equivalent-Circuit Models of Grid-Forming IBRs for Electromagnetic-Transient Simulations

We derive equivalent-circuit models of control- and physical-layer subsystems of grid-forming (GFM) inverter-based resources (IBRs) for electromagnetic-transient (EMT) simulations. Three different primary controllers are considered: Droop, Virtual Synchronous Machine (VSM), and dispatchable Virtual Oscillator Control (dVOC). In addition, the models include cascaded voltage- and current-control loops, and LCL output filters. Simulations for a single-inverter setup and for a network of five inverters in a modified IEEE 14-bus topology are presented. The equivalent-circuit models simulated with analog electronic circuit-simulator software (in our case, LTspice) offer the same accuracy, and with no explicit tuning of the solver, lower computational burden compared to block-diagram-based implementations in commercial off-the-shelf EMT software (in our case, MATLAB-Simulink).

electromagnetic transient simulation↗

NASA NTRS2013

Photoionization Modeling of Oxygen K Absorption in the Interstellar Medium:

We present detailed analyses of oxygen K absorption in the interstellar medium (ISM) using four high-resolution Chandra spectra toward the X-ray low-mass binary XTE J1817-330. The 11-25 Angstrom broadband is described with a simple absorption model that takes into account the pile-up effect and results in an estimate of the hydrogen column density. The oxygen K-edge region (21-25 Angstroms) is fitted with the physical warmabs model, which is based on a photoionization model grid generated with the xstar code with the most up-to-date atomic database. This approach allows a benchmark of the atomic data which involves wavelength shifts of both the K lines and photoionization cross sections in order to fit the observed spectra accurately. As a result we obtain a column density of N(sub H) = 1.38 +/- 0.01 × 10(exp 21) cm(exp −2); an ionization parameter of log xi = −2.70 +/- 0.023; an oxygen abundance of A(sub O) = 0.689 (+0.015/−0.010); and ionization fractions of O(sub I)/O = 0.911, O(sub II)/O = 0.077, and O(sub III)/O = 0.012 that are in good agreement with results from previous studies. Since the oxygen abundance in warmabs is given relative to the solar standard of Grevesse & Sauval, a rescaling with the revision by Asplund et al. yields A(sub O) = 0.952(+0.020/−0.013), a value close to solar that reinforces the new standard.We identify several atomic absorption lines-K(alpha), K(beta), and K(gamma) in O(sub I) and O(sub II) and K(alpha) in O(sub III), O(sub VI), and O(sub VII)-the last two probably residing in the neighborhood of the source rather than in the ISM. This is the first firm detection of oxygen K resonances with principal quantum numbers n greater than 2 associated with ISM cold absorption.

oxygen↗

DOE OSTI2025

Characterization of Gulf Stream energy resources: A 30-year high-resolution simulation study

The strength and proximity of the Gulf Stream (GS) along the U.S. coast offers opportunities for marine energy extraction. Leveraging high-resolution (up to 400 m) long-term (30-year) hindcasts based on an unstructured grid model, this study characterizes the energy potential of the GS in two viable locations: the Florida Straits (FS) and Cape Hatteras (CH). Results reveal distinct characteristics in the kinetic energy flux (KEF) and kinetic energy density (KED) for the two regions. The 30-year mean KEF at CH is 27.50 GW, surpassing the 19.74 GW estimated for the FS, which is attributed to the wider cross-section of the GS in CH. Additionally, CH exhibits higher KEF variability due to GS’s larger path shifts and meanders. Estimated KEDs at ADCP site locations reach up to 2,908 W/m 2 in the FS and 1,512 W/m 2 in the CH at a depth of 20 m. High-energy zones are closer to shore in the FS, whereas energy-rich areas at CH are located further offshore. A depth-based KED analysis shows significant decreases across typical energy extraction depths (20 to 100 m), with reductions up to 44%. Finally, this study provides high-resolution resource characterization, forming a foundation for optimized site selection and marine hydrokinetic system design.

16 TIDAL AND WAVE POWER↗

DOE OSTI2026

Hybrid Grid-Renewable Strategies for Green Steel Production under Electricity Market Uncertainty

Volatility in grid spot prices is expected to rise with climate change-driven demand pressures and the intermittency of renewable generation. This volatility poses financial risks for green hydrogen-based steel production. The Direct Reduced Iron− Electric Arc Furnace (H 2 -DRI-EAF) is a promising pathway to decarbonize steel, which accounts for ∼8% of global GHG emissions. This study assesses how increased grid spot price volatility influences the optimal sizing and operation of H2-DRIEAF plants under three operational scenarios: grid-connected, fully behind-the-meter (islanded), and mixed-mode (semi-islanded). Our analysis identifies the semi-islanded configuration as the most cost-effective solution, achieving a Levelized Cost of Steel (LCOS) 10−35% lower than sourcing energy solely from the grid. Modeling also shows hydrogen storage or selective electricity purchases at high prices (>$1000/MWh) generally outperform battery storage, except under extreme volatility. Additionally, the study explores cost reduction strategies to strengthen the economic viability and sustainability of green steel production.

Batteries↗

DOE OSTI2025

Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement

The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NO x emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NO x to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate.

54 ENVIRONMENTAL SCIENCES↗