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DOE OSTI2023

The Misrepresentation of the Southern African Easterly Jet in Models and Its Implications for Aerosol, Clouds, and Precipitation Distributions

The southern African easterly jet (AEJ-S) is an important midtropospheric feature critical to understanding the tropical convective system over central Africa and the aerosol–cloud interactions over the southeast Atlantic Ocean. However, it remains unclear how well models represent the AEJ-S and its influence on aerosol transport, clouds, and precipitation distribution. Here, in this work, we use ground- and satellite-based observations and reanalysis datasets to assess the representation of AEJ-S in the Coupled Model Intercomparison Project phase 6 (CMIP6) models between September and October during the peak of midtropospheric winds, aerosol transport, clouds, and precipitation. We find that most CMIP6 models have difficulty accurately simulating the strength, position, and spatial distribution of the AEJ-S. Specifically, the AEJ-S is relatively weaker and at a slightly lower altitude in the ensemble of CMIP6 models than represented by observation and reanalysis datasets. To assess the influence of the misrepresented the AEJ-S on CMIP6-simulated aerosol, clouds, and precipitation distributions, we performed composite analyses using models with low and high biases based on the estimates of their midtropospheric easterly wind speed. We find that the misrepresentation of the AEJ-S in CMIP6 models is associated with the overestimation of clouds and precipitation over central Africa, the underestimation of clouds over the southeast Atlantic Ocean, and the limitation of aerosol transport over the continent or the deviation of its spatial distribution from the typical zonal transport over the Atlantic Ocean. Because aerosols, clouds, and precipitation are important components of the regional climate system, we conclude that accurate representation of the AEJ-S is essential over central Africa and the southeast Atlantic Ocean.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

International Collaborations on Fluid Flows in Fractured Crystalline Rocks: FY15 Progress Report

Active participation in international R&D is crucial for achieving the UFD long-term goals of conducting “experiments to fill data needs and confirm advanced modeling approaches” (by 2015) and of having a “robust modeling and experimental basis for evaluation of multiple disposal system options” (by 2020). DOE’s Office of Nuclear Energy (NE) and its Office of Used Fuel Disposition Research and Development (UFD) have developed a strategic plan to advance cooperation with international partners. The international collaboration on the evaluation of crystalline disposal media at Sandia National Laboratories (SNL) in FY15 was focused on the following three activities: (1) thermal-hydrologic-mechanical-chemical modeling single fracture evolution; (2) simulations of flow and transport in Bedrichov Tunnel, Czech Republic, and (3) streaming potential testing at Korean Atomic Energy Research Institute (KAERI) Underground Research Tunnel (KURT). The first two activities are part of the Development of Coupled Models and their Validation against Experiments (DECOVALEX) project.

58 GEOSCIENCES↗

DOE OSTI2023

Insights on Simulating Summer Warming of the Great Lakes: Understanding the Behavior of a Newly Developed Coupled Lake-Atmosphere Modeling System

The Laurentian Great Lakes are the world's largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one-dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two-way coupled modeling system using the Weather Research and Forecasting model and a three-dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake-atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two-way coupled modeling system and our observation-driven modeling system, we find that coupled-lake atmosphere dynamics can lead to a higher LST during June-September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

A general nonlinear magnetomechanical model for ferromagnetic materials under a constant weak magnetic field

Weak magnetic nondestructive testing (e.g., metal magnetic memory method) concerns the magnetization variation of ferromagnetic materials due to its applied load and a weak magnetic surrounding them. One key issue on these nondestructive technologies is the magnetomechanical effect for quantitative evaluation of magnetization state from stress–strain condition. A representative phenomenological model has been proposed to explain the magnetomechanical effect by Jiles in 1995. However, the Jiles' model has some deficiencies in quantification, for instance, there is a visible difference between theoretical prediction and experimental measurements on stress–magnetization curve, especially in the compression case. Based on the thermodynamic relations and the approach law of irreversible magnetization, a nonlinear coupled model is proposed to improve the quantitative evaluation of the magnetomechanical effect. Excellent agreement has been achieved between the predictions from the present model and previous experimental results. In comparison with Jiles' model, the prediction accuracy is improved greatly by the present model, particularly for the compression case. A detailed study has also been performed to reveal the effects of initial magnetization status, cyclic loading, and demagnetization factor on the magnetomechanical effect. Our theoretical model reveals that the stable weak magnetic signals of nondestructive testing after multiple cyclic loads are attributed to the first few cycles eliminating most of the irreversible magnetization. Remarkably, the existence of demagnetization field can weaken magnetomechanical effect, therefore, significantly reduces the testing capability. This theoretical model can be adopted to quantitatively analyze magnetic memory signals, and then can be applied in weak magnetic nondestructive testing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Combined Effects of Temperature and Irradiation on Concrete Damage

Aggregate radiation-induced volumetric expansion (RIVE) is a predominant mechanism in the formation of mechanical damage in the hardened cement paste (hcp) of irradiated concrete under fast-neutron flux (Giorla et al. 2015). Among the operating conditions difference between test reactors and light water reactors (LWRs), the difference of irradiation flux and temperature is significant. While a temperature increase is quite generally associated with a direct, or indirect (e.g., by dehydration) loss of mechanical properties (Maruyama et al. 2014), we found that it causes a partial annealing of irradiation amorphization of α-quartz, hence, reducing RIVE rate. Based on data collected by Bykov et al. (1981), an incremental RIVE model coupling neutron fluence and temperature is developed. The elastic properties and coefficient of thermal expansion (CTE) of irradiated polycrystalline quartz are interpreted through analytical homogenization of experimental data on irradiated α-quartz published by Mayer and Lecomte (1960). Moreover, the proposed model, implemented in the meso-scale simulation code AMIE, is compared to experimental data obtained on ordinary concrete made of quartz/quartzite aggregate (Dubrovskii et al. 1967). Substantial discrepancy, in terms of damage and volumetric expansion developments, is found when comparing irradiation scenarios assuming constant flux and temperature, as opposed to more realistic test reactor operation conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2022

The Essential Role of Westerly Wind Bursts in ENSO Dynamics and Extreme Events Quantified in Model “Wind Stress Shaving” Experiments

Abstract Westerly wind bursts (WWBs)—brief but strong westerly wind anomalies in the equatorial Pacific—are believed to play an important role in El Niño–Southern Oscillation (ENSO) dynamics, but quantifying their effects is challenging. Here, we investigate the cumulative effects of WWBs on ENSO characteristics, including the occurrence of extreme El Niño events, via modified coupled model experiments within Community Earth System Model (CESM1) in which we progressively reduce the impacts of wind stress anomalies associated with model-generated WWBs. In these “wind stress shaving” experiments we limit momentum transfer from the atmosphere to the ocean above a preset threshold, thus “shaving off” wind bursts. To reduce the tropical Pacific mean state drift, both westerly and easterly wind bursts are removed, although the changes are dominated by WWB reduction. As we impose progressively stronger thresholds, both ENSO amplitude and the frequency of extreme El Niño decrease, and ENSO becomes less asymmetric. The warming center of El Niño shifts westward, indicating less frequent and weaker eastern Pacific (EP) El Niño events. Removing most wind burst–related wind stress anomalies reduces ENSO mean amplitude by 22%. The essential role of WWBs in the development of extreme El Niño events is highlighted by the suppressed eastward migration of the western Pacific warm pool and hence a weaker Bjerknes feedback under wind shaving. Overall, our results reaffirm the importance of WWBs in shaping the characteristics of ENSO and its extreme events and imply that WWB changes with global warming could influence future ENSO.

Meteorology & Atmospheric Sciences↗

DOE OSTI2015

The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations

Abstract Reconciling observations and simulations of tropical upper tropospheric temperature trends remains an important problem in climate science. Examining atmospheric models running over observed sea surface temperatures (SSTs), Flannaghan et al. (2014) show that this reconciliation is affected by the SST data set used and that a precipitation‐weighted SST (PSST) is valuable in explaining this result. Here we show that even for Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project (CMIP5 AMIP) simulations forced with identical SSTs, tropical upper tropospheric temperature trends across models (and between ensemble members) show a substantial spread (standard deviation ∼10% of the average trend). About 60% of this spread between ensemble means, as well as deviations from the ensemble means, can be explained by PSST calculated from the time‐evolving precipitation in each model run. Both PSST and atmospheric temperature trends show statistical evidence for systematic differences between models. We conclude that the response of precipitation patterns to changes in SST patterns is a significant source of uncertainty for tropical temperature trends.

Fueglistaler, S.↗

DOE OSTI2018

Do CMIP5 Models Reproduce Observed Low‐Frequency North Atlantic Jet Variability?

Abstract The magnitude of observed multidecadal variations in the North Atlantic Oscillation (NAO) in winter is at the upper end of the range simulated by climate models and a clear explanation for this remains elusive. Recent research shows that observed multidecadal winter NAO variability is more strongly associated with North Atlantic (NA) jet strength than latitude, thus motivating a comprehensive comparison of NA jet and NAO variability across the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Our results show that the observed peak in multidecadal jet strength variability is even more unusual than NAO variability when compared to the model‐simulated range across 133 historical CMIP5 simulations. Some CMIP5 models appear capable of reproducing the observed low‐frequency peak in jet strength, but there are too few simulations of each model to clearly identify which. It is also found that an observed strong multidecadal correlation between jet strength and NAO since the mid‐nineteenth century may be specific to this period.

Bracegirdle, Thomas J.↗

DOE OSTI2026

Examining Cloud Feedback Components in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM)

Cloud feedback remains the main source of uncertainty in climate sensitivity estimated by global climate models (GCMs), largely because subgrid cloud responses are parameterized in GCMs due to their coarse resolution. Here, this study examines cloud feedback in the global 3.25-km Simple Cloud-Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM 3 km) through a pair of 1-yr atmosphere-only simulations with control and +4-K sea surface temperature perturbations. SCREAM 3 km produces a positive cloud feedback that falls within but at the upper end of the range of Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP phase 6 (CMIP6) models and expert judgment. The positive cloud feedback arises from positive contributions from both high- and low-level clouds, with increases in high-cloud altitude and decreases in low-cloud amount and optical depth playing key roles. The stronger-than-CMIP-average feedback is mainly attributable to the high-cloud altitude feedback, owing to cloud tops rising nearly isothermally in SCREAM 3 km. The positive low-cloud amount feedback is weaker in SCREAM than in GCMs because estimated inversion strength (EIS) increases more dramatically with warming. A coarser 12-km resolution version of SCREAM exhibits a weaker positive cloud feedback than SCREAM 3 km, mainly because its low-cloud-radiative flux is more sensitive to EIS, leading to a stronger negative low-cloud amount feedback. With this process-level assessment of cloud feedback, this study reveals where SCREAM aligns with and diverges from conventional GCMs and expert assessment, providing insights to inform further model improvement and future expert assessment.

Cloud radiative effects↗

DOE OSTI2013

Utilizing CLASIC observations and multiscale models to study the impact of improved Land surface representation on modeling cloud- convection

The CLASIC experiment was conducted over the US southern great plains (SGP) in June 2007 with an objective to lead an enhanced understanding of the cumulus convection particularly as it relates to land surface conditions. This project was design to help assist with understanding the overall improvement of land atmosphere convection initiation representation of which is important for global and regional models. The study helped address one of the critical documented deficiency in the models central to the ARM objectives for cumulus convection initiation and particularly under summer time conditions. This project was guided by the scientific question building on the CLASIC theme questions: What is the effect of improved land surface representation on the ability of coupled models to simulate cumulus and convection initiation? The focus was on the US Southern Great Plains region. Since the CLASIC period was anomalously wet the strategy has been to use other periods and domains to develop the comparative assessment for the CLASIC data period, and to understand the mechanisms of the anomalous wet conditions on the tropical systems and convection over land. The data periods include the IHOP 2002 field experiment that was over roughly same domain as the CLASIC in the SGP, and some of the DOE funded Ameriflux datasets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Used Nuclear Fuel Loading and Structural Performance Under Normal Conditions of Transport - Modeling, Simulation and Experimental Integration RD&D Plan

Under current U.S. Nuclear Regulatory Commission regulation, it is not sufficient for used nuclear fuel (UNF) to simply maintain its integrity during the storage period, it must maintain its integrity in such a way that it can withstand the physical forces of handling and transportation associated with restaging the fuel and moving it to treatment or recycling facilities, or a geologic repository. Hence it is necessary to understand the performance characteristics of aged UNF cladding and ancillary components under loadings stemming from transport initiatives. Researchers would like to demonstrate that enough information, including experimental support and modeling and simulation capabilities, exists to establish a preliminary determination of UNF structural performance under normal conditions of transport (NCT). This research, development and demonstration (RD&D) plan describes a methodology, including development and use of analytical models, to evaluate loading and associated mechanical responses of UNF rods and key structural components. This methodology will be used to provide a preliminary assessment of the performance characteristics of UNF cladding and ancillary components under rail-related NCT loading. The methodology couples modeling and simulation and experimental efforts currently under way within the Used Fuel Disposition Campaign (UFDC). The methodology will involve limited uncertainty quantification in the form of sensitivity evaluations focused around available fuel and ancillary fuel structure properties exclusively. The work includes collecting information via literature review, soliciting input/guidance from subject matter experts, performing computational analyses, planning experimental measurement and possible execution (depending on timing), and preparing a variety of supporting documents that will feed into and provide the basis for future initiatives. The methodology demonstration will focus on structural performance evaluation of Westinghouse WE 17×17 pressurized water reactor fuel assemblies with a discharge burnup range of 30-58 GWd/MTU (assembly average), loaded in a representative high-capacity (≥32 fuel rod assemblies) transportation package. Evaluations will be performed for representative normal conditions of rail transport involving a rail conveyance capable of meeting the Association of American Railroads (AAR) S-2043 specification. UNF modeling is anticipated to be defined to the pellet-cladding level and take in to account influences associated with spacer grids, intermediate fluid mixers, and control components. The influence of common degradation issues such as ductile-to-brittle-transition will also be accounted for. All model development and analysis will be performed with commercially available software packages exclusively. Inputs and analyses will be completely documented, all supporting information will be traceable, and bases will be defendable so as to be most useful to the U.S. Department of Energy community and mission. The expected completion date is the end of fiscal year (FY) 2013.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Sharp decline of dust events induces regional wetting over arid and semi-arid Northwest China in the NCAR Community atmosphere model

Abstract Multiple lines of observational evidence have indicated a significant wetting over the arid and semi-arid Northwest China (NWC) during recent decades, coinciding with a simultaneous sharp decline of dust events. Although recent studies have attributed NWC wetting to different anthropogenic and natural forcings, the mechanisms are not definitive and the regional wetting has been greatly underestimated in the Coupled Model Intercomparison Project historical simulations. Based on sensitivity experiments with different dust emission amounts using the NCAR Community Atmospheric Model version 5 (CAM5), here we find that decreasing dusts exert significant impacts on mixed-phase clouds through reducing the concentration of ice nucleating particles, increase the NWC precipitation and thus induce regional wetting through enhancing convection precipitation. A possible convection invigoration mechanism whereby the atmospheric vertical temperature gradient and convective instability are strengthened by reduced dusts, leading to convection invigoration and increased precipitation. These results are reinforced by simulations over the dust region in North Africa where mixed-phase and ice clouds are rare and reduced dusts do not increase precipitation. This study highlights the possible mechanism of dust-ice cloud interactions in recent NWC wetting and future regional climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Resolution Dependence and Rossby Wave Modulation of Atmospheric Rivers in an Aquaplanet Model

Atmospheric rivers (ARs) are examined in a set of aquaplanet simulations using the Model for Prediction Across Scales dynamical core run at multiple horizontal resolutions, namely, 240, 120, and 60 km. As the resolution is increased, there is an increase in the occurrence of long—lasting ARs. At the same time there is also an increase in the local finite–amplitude wave activity (LWA) of upper–tropospheric absolute vorticity, a measure for Rossby wave phase and amplitude that is closely linked with wave breaking. Consistent with the notion that changes in ARs are driven by midlatitude dynamics, a strong relationship is identified between ARs and the equatorward component of LWA. Here, a logistic regression model is used to quantify the probability of AR occurrence based solely on LWA and explains most of the change in AR frequency with resolution. LWA is a diagnostic that may be easily applied to the broadly available output of phase 6 of the Coupled Model Intercomparison project and other model simulations, thus enabling scientists to infer AR and Rossby wave characteristics. AR characteristics, in particular, require higher–resolution moisture and winds at multiple levels that are not always easily available.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Systematic Benchmarking of Climate Models: Methodologies, Applications, and New Directions

As climate models become increasingly complex, there is a growing need to comprehensively and systematically assess model performance with respect to observations. Given the increasing number and diversity of climate model simulations in use, the community has moved beyond simple model intercomparison and toward developing methods capable of benchmarking a large number of simulations against a suite of climate metrics. Here, we present a detailed review of evaluation and benchmarking methods and approaches developed in the last decade, focusing primarily on scientific implications for Coupled Model Intercomparison Project (CMIP) simulations and CMIP6 results that contributed to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Based on this review, we explain the resulting contemporary philosophy of model benchmarking, and provide clear distinctions and definitions of the terms model verification, process validation, evaluation, and benchmarking. While significant progress has been made in model development based on systematic evaluation and benchmarking efforts, some climate system biases still remain. The development of open‐source community software packages has played a fundamental role in identifying areas of significant model improvement and bias reduction. We review the key features of several software packages that have been commonly used over the past decade to evaluate and benchmark global and regional climate models. Additionally, we discuss best practices for the selection of evaluation and benchmarking metrics and for interpreting the obtained results, the importance of selecting suitable sources of reference data and accurate uncertainty quantification.

Environmental sciences↗

DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

DOE OSTI2013

One-way coupling of an integrated assessment model and a water resources model: evaluation and implications of future changes over the US Midwest

An integrated model is being developed to advance our understanding of the interactions between human activities, terrestrial system and water cycle, and how system interactions will be affected by a changing climate at the regional scale. As a first step towards that goal, a global integrated assessment model including a waterdemand model is coupled offline with a land surface hydrology – routing – water resources management model. A spatial and temporal disaggregation approach is developed to project the annual regional water demand simulations into a daily time step and subbasin representation. The model demonstrated reasonable ability to represent the historical flow regulation and water supply over the Midwest (Missouri, Upper Mississippi and Ohio). Implications for the future flow regulation, water supply and supply deficit are investigated using a climate change projection with the B1 emission scenario which affects both natural flow and water demand. Over the Midwest, changes in flow regulation are mostly driven by the change in natural flow due to the limited storage capacity over the Ohio and Upper Mississippi river basins. The changes in flow and demand have a combined effect on the Missouri Summer regulated flow. The supply deficit tends to be driven by the change in flow over the region. Spatial analysis demonstrates the relationship between the supply deficit and the change in demand over urban areas not along a main river or with limited storage, and over areas upstream of groundwater dependent fields with therefore overestimated demand.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2021

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗

DOE OSTI2015

An alternate approach to ensemble ENSO forecast spread: Application to the 2014 forecast

Abstract Evaluating the 2014 El Niño forecast as a “bust” may be tapping into a bigger issue, namely that forecast “overconfidence” from single‐model ensembles could affect the retrospective assessment of El Niño–Southern Oscillation (ENSO) predictions. The present study proposes a new approach to quantifying an “expected” spread and uncertainty from noise‐driven processes and supplementing these measures with actual ENSO forecasts. Expanding on a previously developed coupled model framework that isolates noise‐driven ENSO‐like errors, an experimental design is implemented to generate an expected December Niño‐3.4 spread from March initial condition sea surface temperature errors that have similar structure to the 2014 and 2015 observed. Results reveal that the 2014 ENSO forecast falls within the expected uncertainty generated by ENSO‐independent, forecast‐independent, noise‐driven errors.

Larson, Sarah M.↗