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At least 109 records · Page 6

Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States

The global energy system is undergoing significant changes, including a shift in energy generating technologies to more renewable energy sources. However, the dependence of renewable energy sources on local environmental conditions could also increase disruptions in service through exposures to compound, extreme weather events. By fusing three diverse datasets (operations and maintenance tickets, weather data, and production data), this analysis presents a novel methodology to identify and evaluate performance impacts arising from extreme weather events across diverse geographical regions. Text analysis of maintenance tickets identified snow, hurricanes, and storms as the leading extreme weather events affecting photovoltaic plants in the United States. Statistical techniques and machine learning were then implemented to identify the magnitude and variability of these extreme weather impacts on site performance. Impacts varied between event and non-event days, with snow events causing the greatest reductions in performance (54.5%), followed by hurricanes (12.6%) and storms (1.1%). Machine learning analysis identified key features in determining if a day is categorized as low performing, such as low irradiance, geographic location, weather features, and site size. The analysis improves our understanding of compound, extreme weather event impacts on photovoltaic systems, which can inform planning activities, especially as the industry continues to expand into new geographic and climatic regions around the world.

14 SOLAR ENERGY↗

Risk-Based Dynamic Contingency Analysis Applied to Puerto Rico Electric Infrastructure

The U.S. Department of Energy’s (DOE) Office of Electricity and Office of Energy Efficiency & Renewable Energy have funded DOE National Laboratories to perform modeling, analysis, and high-level design of resilience-enhancement options for the power grid of the Commonwealth of Puerto Rico. The Pacific Northwest National Laboratory (PNNL) is one of the national laboratories contributing to the DOE effort. Under this funding, PNNL completed Phase I of their analysis in 2018, which identified high-priority transmission enhancements derived from detailed dynamic cascading analysis of severe contingencies, including a hurricane scenario example. This report describes additional analysis completed under Phase II, which was performed over 2019. The PNNL team applied decades of experience making complex power systems more resilient, reliable, secure, flexible, affordable and sustainable, with partners in government and industry. In this report, PNNL presents the Phase II analysis, in which a risk-based dynamic contingency analysis approach to evaluate impact of several hurricane scenarios was developed. This approach was used to identify high-priority enhancements and test resilience mitigation actions, including the evaluation of high-solar scenarios developed as a result of the 2019 Puerto Rico Integrated Resource Plan (IRP).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Micromovements and discomfort associated with flight mission with helmet operation tasks with different levels of cognitive workload

When performing stationary tasks under elevated cognitive workload, individuals must perform continual muscle contractions to maintain stability of the body, resulting in fatigue of the postural muscles. When the muscles perform these contractions in a prolonged manner, the body potentially responds through small changes in body movements—micromovements that may lead to discomfort. The study purpose was to evaluate impact of cognitive load on micromovements. The micromovements were measured during three different cognitive workloads; low, medium, and high. The NASA-TLX score was used to evaluate the perceived mental workload and discomfort was assessed by visual analog scale. In total, 60 subjects (30 males and 30 females) were recruited and performed cognitive tasks that simulated flight operations such as changing the radio frequency based on air traffic control messages, balancing the fuel levels in simulated fuel tanks, and aiming a reticle in a designated moving target using the cyclic control. Cognitive load was defined by the frequency of events. Micromovements were defined by changes in the center of pressure (COP) of the seat pan and COP standard deviation. It was found that the high cognitive workloads had the highest NASA-TLX scores including mental demands, temporal demands, and effort. The neck area had the highest overall levels of discomfort followed by upper back. The highest standard deviation for COP shift and number of micromovements occurred for medium cognitive workloads. In conclusion, while there were some interesting trends, few trends reached a statistical significance due to high variability among subjects for the outcome variables.

60 APPLIED LIFE SCIENCES↗

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗

Long-Term Chemical Analyses in Biota Collected Upstream of the Pajarito Canyon Flood Retention Structure and Los Alamos Canyon Weir at Los Alamos National Laboratory

The Cerro Grande wildfire was a major disaster that burned during the summer of 2000 in the Jemez Mountains and parts of Los Alamos National Laboratory (LANL or Laboratory). As an immediate response to the fire, the United States Department of Energy generated a list of post-fire actions needed to mitigate the impacts of this disaster, including flooding and the potential for erosion. Two structures built post-fire include the Pajarito Canyon flood retention structure (FRS) and the Los Alamos Canyon weir. Environmental monitoring at these two structures has occurred since the early 2000s as part of ongoing efforts to evaluate impacts of the fire.

54 ENVIRONMENTAL SCIENCES↗

Data from "The Influence of Climate Change on Flooding and Social Inequalities from Remnants of Hurricane Ida"

Previous research has demonstrated that tropical cyclone-related precipitation and flooding have been increased by anthropogenic global warming. Our work aims to quantify the contribution of climate change to the deadly flooding from the remnants of Hurricane Ida (2021) and its impact on human society. We developed an analysis framework that combines lessons from climate change attribution science, two-dimensional hydrodynamic modeling, and flood impact evaluation, including a social inequality index, to estimate remnants of Ida flooding and consequences responding to current (locally 1°C warmer) and future (another 1°C warmer) climate change. We find that an additional quarter to a half million people were exposed to flooding due to current and future climate change. The human influence on flood impacts was larger with deeper flood water depth (≥ 1 m) than with shallow depths. Socially vulnerable populations were found to be disproportionately more affected, and climate change exacerbates this inequality

Climate Change↗

Technical Evaluation of Accelerated Basin De-Inventory Material Addition to Sludge Batch 11

Savannah River Nuclear Solutions has a need to discard spent nuclear fuel (SNF), currently stored in L Basin, to the Defense Waste Processing Facility (DWPF) for vitrification. The Department of Energy (DOE) has approved the Accelerated Basin De-inventory (ABD) Program for discarding SNF via transfers from H-Canyon to the Savannah River Site (SRS) Liquid Waste (LW) system. The first ABD discards will occur during the preparation of Sludge Batch (SB) 11. An initial impact evaluation of the LW flowsheet was performed by the Savannah River National Laboratory (SRNL) prior to the approval of the ABD Program. This evaluation addressed the LW downstream facilities based on the current H-Canyon flowsheet sequence for the average ABD discard. The flowsheet evaluation only included aluminum-clad SNF, specifically Materials Test Reactor (MTR) fuel and High Flux Isotope Reactor (HFIR) fuel similar to the planned SB11 discard. Following this evaluation, the flowsheet has been slightly altered to address (i) new nuclear criticality safety controls for DWPF that credit a higher amount of gadolinium as a neutron poison for all of the enriched uranium contained in a SB and (ii) potential additions of the H-Canyon neutralized fuel stream prior to the Low Temperature Aluminum Dissolution (LTAD) process in Tank 51. The early introduction of ABD material into the SB assembly process is being investigated to provide flexibility regarding transfer opportunities for H-Canyon to Tank 51 for SB11 and future sludge batches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Benchmark of numerical modeling approaches on the systematic performance evaluation of wave energy converters

Different numerical modeling methods have been developed and applied to evaluate a variety of performance indicators of wave energy converters (WECs), including the power performance, structural loads, levelized cost of energy, etc. Based on the modeling fidelity, the commonly used numerical modeling approaches can be classified as linear modeling, weakly nonlinear modeling and fully nonlinear modeling approaches. Each method differs in accuracy and computational efficiency, making them suitable for different stages of WEC design. However, the selection of modeling approach could significantly impact evaluation outcomes. For instance, simplified linear models may underestimate structural loads or overestimate energy production in some operational conditions, potentially leading to less cost-effective designs. Given the widespread utilization of these models, it is essential to understand the uncertainties brought by them in performance evaluations. This work is dedicated to benchmarking different linear-potential-flow-based numerical models for evaluating the systematic performance of WECs. Three representative numerical modeling approaches are considered in this work, including linear frequency-domain modeling, statistically linearized spectral-domain modeling and Cummins equation-based nonlinear time-domain modeling. A generic point absorber WEC is considered as the research reference in this work, and different sea sites are taken into account. The numerical models are utilized to predict critical performance indicators, including power performance, the annual energy production, the capacity factor, the levelized cost of energy and the PTO fatigue loads. By comparing the results, this work identifies the uncertainties associated with different modeling approaches in evaluating WEC performance.

Fatigue↗

Reductions in wind farm main bearing rating lives resulting from wake impingement

This paper studies the impacts of wake impingement on main bearing rating lives predicted during the wind turbine design stage. A computational tool chain was developed to explore and quantify these effects across a wind farm populated by 10 MW wind turbines. Wind field and turbine load modelling was undertaken using the Dynamiks Python package, including application of a dynamic wake meandering model. The ISO 281 basic bearing rating life formulation was subsequently applied in order to evaluate impacts from wake effects. Analyses included a two-turbine parametric analysis, followed by a full wind farm analysis undertaken for the TotalControl 32-turbine reference wind farm, including full wind rose simulations across all operational wind speeds. Site conditions were accounted for using a Weibull wind speed distribution and a range of parametric wind direction rose models. Results indicate that wind farm main bearing rating lives are negatively impacted by the effects of wake impingement, resulting in rating life reductions for the analysed wind farm of the order of 16 % on average and as much as 20 %–25 %, both for the locating main bearing. Despite these high sensitivities, it is important to note that these resultant rating lives (i.e. the predicted lives) still far exceed the standard wind turbine operational lifetimes of 20–30 years. Wake impacts were also found to be asymmetrically related to the side on which the rotor is impinged, suggesting that, for the main bearing, there may be a “better” side for wake impingement to occur. Rating life sensitivities to wind rose shape were also observed. While these findings must be interpreted with due consideration for the various methodological limitations present, they provide compelling evidence that wake effects at the wind farm level should necessarily be included when undertaking main bearing operational load modelling, rating life assessment, or other load-related analyses.

17 WIND ENERGY↗

Potential Impacts of the Inflation Reduction Act on Domestic Manufacturing and Deployment for Land-Based Wind Turbines

The land-based wind energy industry in the United States has matured over the past several decades, representing 10% of the country's total electricity generation in 2022. It has experienced periods of rapid growth and decline in recent years, in large part because of supply chain disruptions at a global and domestic level. With the recent passing of the 2022 Inflation Reduction Act, the industry faces unprecedented opportunities to strengthen domestic manufacturing and enable greater deployment over the next decade. To better understand the opportunities and challenges, the authors explore the value of relevant IRA provisions and provide a set of scenarios evaluating impacts on domestic component demand and manufacturing.

17 WIND ENERGY↗

Ecological Benchmark for Radionuclides

The Ecological Benchmark Tool for radionuclides dataset serves as a comprehensive repository of benchmarks designed to assess ecological risks at contaminated sites. This tool facilitates the evaluation of various environmental media and contaminants, supporting regulatory compliance and ecological protection. Benchmarks are available for sediment, soil, and surface water. The dataset also provides species-specific benchmarks for fish, plants, birds, mammals, and invertebrates. Users can select benchmark sources, media, individual radionuclides, and retrieve results in tabular or spreadsheet formats for analysis. Benchmarks are derived from authoritative sources, including government agencies, scientific councils, and academic publications. The dataset supports ecological risk assessments, regulatory decision-making, and environmental planning, with tools for benchmarking against radiological thresholds, sensitive species protection, and habitat impact evaluations. This structured approach ensures a robust evaluation of ecological risks tailored to site-specific and regulatory needs.

Stewart, Debra [Oak Ridge National Laboratory (ORN↗

Ecological Benchmark for Chemicals

The Ecological Benchmark Tool dataset serves as a comprehensive repository of benchmarks designed to assess ecological risks at contaminated sites. This tool facilitates the evaluation of various environmental media and contaminants, supporting regulatory compliance and ecological protection. Benchmarks are available for air, biota, sediment, soil, and surface water. The dataset also provides species-specific benchmarks for fish, plants, birds, mammals, and invertebrates. Users can select benchmark sources, media, individual chemicals, and retrieve results in tabular or spreadsheet formats for analysis. Benchmarks are derived from authoritative sources, including government agencies, scientific councils, and academic publications. The dataset supports ecological risk assessments, regulatory decision-making, and environmental planning, with tools for benchmarking against chemical thresholds, sensitive species protection, and habitat impact evaluations. This structured approach ensures a robust evaluation of ecological risks tailored to site-specific and regulatory needs.

Stewart, Debra [Oak Ridge National Laboratory (ORN↗

LA100 Equity Strategies. Chapter 6: Universal Access to Safe and Comfortable Home Temperatures

The LA100 Equity Strategies project integrates community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. This chapter focuses on housing weatherization and cooling technologies as means to increase access to safe and comfortable home temperatures. Lack of cooling access and use can have severe health impacts on building occupants during heat waves. Specifically, NREL developed and used a residential building stock model to simulate the energy use of 50,000 dwellings representing the diversity of housing types, appliances, climate zones, and household incomes across Los Angeles. We compared a baseline scenario with seven upgrade scenarios. Five scenarios cooled the entire household and featured cooling systems at varying efficiency levels with various improvements to the envelope, roof, and shading, and two scenarios cooled a single room in a household with no prior cooling using either a room air-conditioning or a heat pump system. For each scenario, we evaluated impacts on utility bills, payback periods, and changes in energy burdens, as well as ability to achieve safe and comfortable temperatures. We also examined the effects of building types (multifamily vs. single-family) on indoor air temperatures. Based on the results of modeling, analysis, and community guidance, we identified six short-term and two long-term strategies for improving access to building envelope upgrades and cooling strategies that could save lives and maintain safe home temperatures for Los Angeles' low-income households during heat waves. Research was guided by input from the community engagement process, and associated equity strategies are presented in alignment with that guidance.

air conditioning↗

Online and Offline Analytical Techniques to Quantify Chloride Salts

This report serves as the deliverable for Milestone- M3FT-26AN080502017: Summary of Accomplishments for Online and Offline Analytical Qualification of Chloride Fuel Salts. The qualification of chloride fuel salts is a critical challenge for the development and deployment of molten salt reactors (MSRs), requiring precise control and verification of chemical and isotopic composition to ensure predictable neutronics, manageable radiological behavior, and safe plant operation. Currently, there is no universally accepted standard for fuel salt qualification, particularly for chloride-based systems, which underscores the need for robust, science-based analytical methodologies. This report presents a comprehensive evaluation of both online and offline techniques for quantifying chloride fuel salts, including multielectrode array voltammetry, differential thermal analysis (DTA) probes, inert gas fusion (IGF) analyzers, and gamma spectrometry using the Mirion NAIS-2x2 NaI(Tl) detector. The integration of these methods enables real-time monitoring of actinide concentrations, redox state, and thermophysical properties, as well as high-precision measurement of impurities and isotopic composition. The acquisition of advanced instruments such as the Bruker Leonardo G6 for IGF and the Mirion NaI detector enhances analytical capabilities, supporting the establishment of operational envelopes and impurity thresholds. These approaches provide essential data for neutronic impact evaluation, feedstock documentation, and compliance with nuclear safety standards. The methodologies developed and validated in this report lay the groundwork for future standardized protocols, bridging the gap between laboratory research and commercial reactor operation, and advancing the safe and efficient deployment of chloride-fueled MSRs.

Polke, Amber↗

Sensor impacts on building and HVAC controls: A critical review for building energy performance

Building operations rely heavily on control systems and sensors. This paper provides a sophisticated literature review on sensor systems in building/HVAC systems, particularly in the context of controls, and their impacts on energy efficiency and thermal comfort. This study aims to understand the previous and current research and identify future research opportunities on this subject. The reviewed sensor systems were used for heuristic rule-based controls, local controls, and advanced optimal controls for existing and emerging technologies. Five major aspects of sensors are reviewed here: control loops for sensors, sensor types, sensor locations, sensor data, and a sensor impact evaluation framework. To augment the literature review, comprehensive standardized interviews were also conducted with relevant industry experts and practitioners. These interviews were designed and performed to (1) identify significant factors for selecting sensor sets and current undergoing issues, (2) identify potential improvements in sensor configuration/deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experiences to develop structured use-case scenarios. Researchers collected and analyzed 31 interview responses for this paper.

Building control↗

Stakeholder-Engaged Structured Decision Making for the Los Alamos Legacy Cleanup Mission - 20501

The Los Alamos National Laboratory (LANL) environmental legacy cleanup program requires decisions to be made for environmental remediation, decommissioning and disposal or management of radioactive waste. This legacy cleanup program was established to address groundwater contamination, material disposal areas (MDAs) that have been used to dispose of radioactive and other waste material, and 'aggregate areas' that might produce radioactive or other chemical waste as a result of remediation activities. The LANL site is regulated for environmental concerns under the Resource Conservation and Recovery Act (RCRA). However, some parts of LANL, such as material disposal area G (MDA G), have disposed of radioactive waste under DOE Order 435.1, and are subject to other regulations. For example, decommissioning the remote-handled TRU material stored in 33 shafts at MDA G falls under EPA's 40 CFR 191. Collectively, the regulations are all aimed in the same direction of finding the best solution, either through constructs such as 'as low as reasonably achievable' (ALARA), considering balancing factors as opposed to only cost and human health risk, and, under EPA regulations such as RCRA and NEPA, evaluating impact from all chemicals and both human health and ecological endpoints. Despite the basic goals and objectives of the regulations or their guidance, the main challenge is in their implementation. Arguably perhaps, but really in principle, all of these (and similar) regulations are asking for a decision analysis to be performed. Implementation challenges encountered have included lack of understanding of decision analysis in the industry, lack of effective stakeholder engagement in the decision analysis process, and lack of appreciation of the need to separate value judgments from science, the latter leading to developing conservative, or protective, science-based models. Conservative models lead to poor solutions, lack of effective stakeholder engagement leads to long drawn out protracted approaches to finding a solution (which also might never be found with this approach), and lack of understanding of decision analysis and Bayesian statistics causes poor models to be built, which creates unfortunate situations of 'garbage in, garbage out' becoming the basis for decision making. Stakeholder-engaged structured decision making (SDM) is an approach to solving problems that relies on the theory of decision science to involve stakeholders in the decision-making process. This approach incorporates stakeholder values using a scientifically rigorous methodology that separates value judgments from science in a way that helps avoid the pitfalls of biased, protective, or conservative modeling. This approach has its foundation in Keeney's 1992 treatise on value-focused thinking [1]. Keeney advocated a paradigm shift in decision making based on the idea that the standard way of thinking about decisions is backwards. The standard approach of focusing first on identifying alternatives rather than on articulating values results in a reactive approach with the emphasis on mechanics and fixed choices instead of the core values that have meaning to stakeholders. This paradigm shift effectively engages all stakeholders in the decision-making process while using a values focused thinking approach that can lead to the identification of decision opportunities and the creation of better alternatives. The intent is to be proactive and generate solutions that are related directly to values and objectives as identified by stakeholders. There are, perhaps, two overarching reasons why SDM can be used to benefit LANL's environmental legacy cleanup. Some of LANL's remaining waste management and environmental management problems are challenging and complex (for example, the Cr and RDX plumes, and MDAs) and while the traditional approach has, arguably, worked well for relatively simple risk-based problems, it cannot, or should not, be applied to more complex problems if the most effective and efficient solutions are desired. The second reason is cost. This has perhaps become more critical since publication of the Government Accountability Office (GAO) reports that DoE's environmental liability is considered a high-risk concern for the nation [2]. The focus of SDM is on structuring solutions to decision risk problems by first addressing stakeholder and decision maker values and subsequently developing decision objectives and ways to measure those objectives, preference weighting across objectives, identifying decision alternatives that best achieve those values, and characterizing uncertainty in predictions of the measures. Because a complete decision model is created using SDM, it can be evaluated to find the main elements of the model that drive, or predict, the best solution. This approach creates complete decision models that are transparent, traceable, reproducible and technically defensible. The science behind SDM, or decision analysis, is well founded, yet it is not unusual to see ad hoc approaches to decision making implemented under various environmental regulations that are pertinent to the LANL site, including NEPA, RCRA and DOE Order 435.1. Such ad hoc approaches are often not transparent or traceable, and lack reproducibility and technical defensibility. The LANL legacy cleanup program has embarked on using SDM to address the complex problems that remain. Stakeholder meetings have been held, and a prototype version of the stakeholder value system has been developed. Further meetings are expected in the future to address specific project needs. This is a long-term endeavor considering the complex environmental problems faced by DOE EM in Los Alamos (EM-LA), and careful planning, consideration of stakeholder value systems, and engagement with stakeholders throughout the SDM process is expected to lead to a successful endpoint. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrated U.S. nationwide corridor charging infrastructure planning for mass electrification of inter-city trips

This study introduces an integrated modeling framework to evaluate long-term national corridor charging infrastructure requirements in the United States to support the growing inter-city charging demand with the rapid growth in the battery electric vehicle (BEV) market. The core model is an optimization model that considers spatial and temporal dimensions and models heterogeneous behaviors between travelers. The model also introduces the travelers’ inconvenience cost function by linking travelers’ acceptance of the charging infrastructure with exogenous technology and social factors. The inconvenience cost function simulates mode choice between BEVs and alternative modes by heterogenous travelers. We applied the framework to assess the inter-regional charging infrastructure requirements for the entire U.S. mainland interstate highway network. We evaluated impacts on the infrastructure design and its public acceptance with changes in policy, technology, and demographic characteristics, and we also quantified the importance of modeling full-scale inter-regional charging infrastructure requirements compared to the conventional regional level analyses.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Global Atmosphere‐aerosol Model ICON‐A‐HAM2.3–Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness

Abstract The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3‐HAM2.3 global atmosphere‐aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON‐A (icon‐aes‐1.3.00) global atmosphere model to yield the new ICON‐A‐HAM2.3 atmosphere‐aerosol model. The ICON‐A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub‐grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6‐HAM2.3 two‐moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON‐A‐HAM2.3 and ECHAM6.3‐HAM2.3, but the bias is larger in ICON‐A‐HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub‐tropical oceans. ICON‐A‐HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON‐A‐HAM2.3 compared to standard ICON‐A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON‐A‐HAM2.3 and in ECHAM6.3‐HAM2.3. In the extra‐tropics, a smaller multivariable bias is found for ICON‐A‐HAM2.3 than for ECHAM6.3‐HAM2.3.

54 ENVIRONMENTAL SCIENCES↗