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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Spread of Ocean Heat Uptake Efficiency Traced to Ocean Salinity

Abstract Ocean heat uptake (OHU) plays an important role in determining the rate of surface warming under CO 2 forcing. We examined the transient response to CO 2 forcing in a set of 30 climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6) and found that the intermodel spread in OHU efficiency largely depends on the base‐state ocean stratification, especially in the Southern Ocean. This dependence is primarily traced to ocean salinity rather than ocean temperature. Models with weaker ocean stratification primarily due to higher upper‐ocean salinity tend to sequester heat into the deeper ocean, leading to a lower rate of surface warming, a primary reason for higher OHU efficiency; the stratification impact on total OHU is secondary. We applied the relationship between salinity and OHU efficiency for an emergent constraint on OHU efficiency, suggesting an OHU efficiency higher than the CMIP6 multimodel average and arguing against models with extremely low efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Parameter Tuning and Calibration of RegCM3 with MIT-Emanuel Cumulus Parameterization Scheme over CORDEX East Asian Domain

In this study, we calibrated the performance of regional climate model RegCM3 with Massachusetts Institute of Technology (MIT)-Emanuel cumulus parameterization scheme over CORDEX East Asia domain by tuning the selected seven parameters through multiple very fast simulated annealing (MVFSA) sampling method. The seven parameters were selected based on previous studies, which customized the RegCM3 with MIT-Emanuel scheme through three different ways by using the sensitivity experiments. The responses of model results to the seven parameters were investigated. Since the monthly total rainfall is constrained, the simulated spatial pattern of rainfall and the probability density function (PDF) distribution of daily rainfall rates are significantly improved in the optimal simulation. Sensitivity analysis suggest that the parameter “relative humidity criteria” (RH), which has not been considered in the default simulation, has the largest effect on the model results. The responses of total rainfall over different regions to RH were examined. Positive responses of total rainfall to RH are found over northern equatorial western Pacific, which are contributed by the positive responses of explicit rainfall. Followed by an increase of RH, the increases of the low-level convergence and the associated increases in cloud water favor the increase of the explicit rainfall. The identified optimal parameters constrained by the total rainfall have positive effects on the low-level circulation and the surface air temperature. Furthermore, the optimized parameters based on the extreme case are suitable for a normal case and the model’s new version with mixed convection scheme.

emanual cumulus parameterization↗
DOE OSTI2023

Impact of Global Warming on U.S. Summertime Mesoscale Convective Systems: A Simple Lagrangian Parcel Model Perspective

Abstract Mesoscale convective systems (MCSs) are the dominant rainfall producer over the United States during the warm season, causing natural disasters and severe weather every year. Global climate models have large uncertainty in projecting precipitation changes in the future climate. Here, a simple Lagrangian parcel model is used to investigate the impact of global warming on MCS initiation and growth. The single-column parcel model projects a mean precipitation decrease over the central United States and an increase to its east, in agreement with the CMIP5 model projection. It also highlights the crucial role of current climate mean-state model bias in exaggerating the change in future mean precipitation projection by 25%. As for convective population, the model captures the decreased occurrence frequency of weak to moderate convection and increased frequency of strong convection due to the increased CAPE and CIN, in agreement with convection-permitting regional simulations. Novel parameterizations of gust-front propagation speed and subsidence strength are developed as guided by cloud-resolving simulations. The multicolumn parcel model employing those parameterizations captures readily the cold pool–induced upscale growth feature. It simulates smaller mesoscale clusters over the central United States under global warming due to gust-front slowdown and subsidence strength enhancement, which are further attributed to land aridity–induced weakening of initial accumulated precipitation and strengthening of updraft speed, respectively. That said, mesoscale clusters could become bigger under more favorable conditions in future climate, including boundary layer moistening, convection lifetime lengthening, and cold pool mechanical-lifting enhancement, which require further investigations to improve mechanistic understanding of future MCS changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Discussion on “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach”

Abstract We thank the authors for this interesting paper that highlights important ideas and concepts for the future of climate model ensembles and their storage, as well as future uses of stochastic emulators. Stochastic emulators are particularly relevant because of the statistical nature of climate model ensembles, as discussed in previous work of the authors (Castruccio et al. in J Clim 32:8511–8522, 2019; Hu and Castruccio in J Clim 34:8409–8418, 2021). We thank the authors for sharing of some of their data with us in order to illustrate this discussion. In the following, in Sect. 1 we discuss alternative techniques currently used and studied, namely lossy compression and ideas emerging from the climate modeling community, that could feed the discussion on ensemble and storage. In that section, we also present numerical results of compression performed on the data shared by the authors. In Sect. 2, we discuss the current statistical model proposed by the authors and its context. We discuss other potential uses of stochastic emulators in climate and Earth modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The Changing Character of the California Sierra Nevada as a Natural Reservoir

The mountains of the Western United States provide a vital natural service through the storage and release of mountain snowpack, lessening impacts of seasonal aridity and satiating summer water demand. Yet, climate change continues to undermine these important processes. To understand how snowpack may change in the headwaters of California's major reservoirs, the North American Coordinated Regional Climate Downscaling Experiment is analyzed to assess peak water volume, peak timing, accumulation rate, melt rate, and snow season length across both latitudinal and elevational gradients. Under a high-emissions scenario, end-of-century peak snowpack timing occurs 4 weeks earlier and peak water volume is 79.3% lower. The greatest reductions are above Shasta, Oroville, and Folsom and between 0- and 2,000-m elevations. Regional climate model and global forcing data set choice is important in determining historical snowpack character, yet by end century all models show a significant and similar decline in mountain snowpack.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Unified Entrainment and Detrainment Closures for Extended Eddy-Diffusivity Mass-Flux Schemes

The extended Eddy Diffusivity Mass Flux (EDMF) scheme is used as a unied parameterization that simulates subgrid-scale dynamics across a range of regimes.This work presents unied entrainment and detrainment closures that allow this scheme to simulate the dry convective boundary layer, shallow convection and deep convection , while adjacent works present other necessary closures for this unied scheme and test its performance for stable, stratocumulus topped and convective boundary layers. Entrainment and detrainment are modeled as a combination of turbulent and dynamical processes. The turbulent component is taken as downgradient diffusion between subdomains. The dynamical component is based on a ratio of buoyancy and vertical velocity that ensures consistent treatment of the ratio of mass-flux at vanishing area fraction. Dynamical detrainment is controlled by the difference in relative humidity between subdomains when liquid water is present. These closures are rst evaluated with entrainment and detrainment diagnosed from Large Eddy Simulations where decaying tracers are used to identify the different subdomains and mass exchanges between them. When implemented in a single column model (SCM), these closures are tested in simulations of several observationally motivated cases of dry convective boundary layer, shallow convection and deep convection. Results show good agreement between the SCM and Large Eddy Simulations in key properties for climate models and profiles of first, second and third moments. The development of diurnal cycles and the onset of and precipitation (with simplified microphysics) are well predicted by the SCM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Underestimated marine stratocumulus cloud feedback associated with overly active deep convection in models

Cloud feedback remains the largest source of uncertainty in equilibrium climate sensitivity (ECS). Many studies have attempted to narrow uncertainties in cloud feedback and ECS by proposing observable metrics with high skill at predicting future climate, referred to as emergent constraints. These constraints are often associated with clouds, convection, and circulation, and are interrelated. However, physical explanations for these connections remain unclear. Here, we propose a new mechanism relating convection and clouds across multiple climate models. Some models show overly active deep convection on daily timescales in the subtropical low cloud regions, which contributes to weaker subsidence inversion and smaller amounts of low-level clouds. Such models predict smaller shortwave (SW) cloud feedback. Using precipitation frequency in these regions as an emergent constraint, encapsulating this mechanism, models with lower SW cloud feedback (<0.50 W m -2 °C - 1) are found to exhibit erroneously frequent convection. Our results suggest that further improvements in understanding and better modeling of cloud and convective systems are necessary for accurate climate predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Atmospheric System Research Marine Low Clouds Workshop Report, January 27-29,2016

Marine low clouds are a major determinant of the Earth?s albedo and are a major source of uncertainty in how the climate responds to changing greenhouse gas levels and anthropogenic aerosol. Marine low clouds are particularly difficult to simulate accurately in climate models, and their remote locations present a significant observational challenge. A complex set of interacting controlling processes determine the coverage, condensate loading, and microphysical and radiative properties of marine low clouds. Marine low clouds are sensitive to atmospheric aerosol in several ways. Interactions at microphysical scales involve changes in the concentration of cloud droplets and precipitation, which induce cloud dynamical impacts including changes in entrainment and mesoscale organization. Marine low clouds are also impacted by atmospheric heating changes due to absorbing aerosols. The response of marine low clouds to aerosol perturbations depends strongly upon the unperturbed aerosol-cloud state, which necessitates greater understanding of processes controlling the budget of aerosol in the marine boundary layer. Entrainment and precipitation mediate the response of low clouds to aerosols but these processes also play leading roles in controlling the aerosol budget. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility and Atmospheric System Research (ASR) program are making major recent investments in observational data sets from fixed and mobile sites dominated by marine low clouds. This report provides specific action items for how these measurements can be used together with process modeling to make progress on understanding and quantifying the key cloud and aerosol controlling processes in the next 5-10 years. Measurements of aerosol composition and its variation with particle size are needed to advance a quantitative, process-level understanding of marine boundary-layer aerosol budget. Quantitative precipitation estimates that combine radar and lidar measurements are becoming available, and these could be used to test process models, quantify precipitation responses to aerosol, and constrain climate models. Models and observations can be used to constrain how clouds respond dynamically to changing precipitation. New measurements of turbulence from ground-based remote sensing could be used to attempt to relate entrainment to the vertical and horizontal structure of turbulence in the boundary layer. Cloud-top entrainment plays a major role in modulating how low clouds respond to both aerosols and to greenhouse gases, so investment in promising new observational estimates would be beneficial. Precipitation formation and radiative cooling both help marine low clouds to organize on the mesoscale. More work is needed to develop metrics to characterize mesoscale organization, to elucidate mechanisms that determine the type and spatial scale of mesoscale cellular convection, and to understand the role of mesoscale structures in the stratocumulus-to-cumulus transition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Internal variability of a dynamically downscaled climate over North America

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aerosol-Cloud Interactions From Aviation Soot Emissions

Current models estimate global aviation contributes approximately 5% to the total anthropogenic climate forcing, with aerosol-cloud interactions having the greatest effect. However, radiative forcing estimates from aviation aerosol-cloud interactions remain undetermined. There is an expected significant increase in aircraft emissions with aviation demand expected to rise by over 4% per year. Soot may play an important role in the ice nucleation of aircraft-induced cirrus formation due to a high emission rate, but the ice nucleating properties are poorly constrained. Understanding the microphysical processes leading to atmospheric ice crystal formation is crucial for the reliable parameterization of aerosol-cloud interactions in climate models due to their impact on precipitation and cloud radiative properties. Ice nucleation of aircraft-emitted soot is potentially affected by particle morphology with condensation of supercooled water occurring in pores followed by ice nucleation. However, soot has heterogeneous properties and undergoes atmospheric aging and oxidation that could change surface properties and contribute to complex ice nucleation processes. Further, this review synthesizes current knowledge of ice nucleation catalyzed by aviation in the cirrus regime and its effects on global radiative forcing. Further research is required to determine the ice nucleation and microphysical processes of cirrus cloud formation from aviation emissions in both controlled laboratory and field investigations to inform models for more accurate climate predictions and to provide efficient mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The relationship between interannual and long-term cloud feedbacks

The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual and long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Statistical Treatment of Convolutional Neural Network Superresolution of Inland Surface Wind for Subgrid-Scale Variability Quantification

Abstract Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over relatively small downscaling factors because of the challenge of recovering fine-scale information from coarse data. This limits their compatibility with many global climate model outputs, often available between ∼50- and 100-km resolution, to scales of interest such as cloud resolving or urban scales. This study systematically examines the capability of a type of superresolving convolutional neural network (SR-CNNs) to downscale surface wind speed data over land from different coarse resolutions (25-, 48-, and 100-km resolution) to 3 km. For each downscaling factor, we consider three convolutional neural network (CNN) configurations that generate superresolved predictions of fine-scale wind speed, which take between one and three input fields: coarse wind speed, fine-scale topography, and diurnal cycle. In addition to fine-scale wind speeds, probability density function parameters are generated through which sample wind speeds can be generated, accounting for the intrinsic stochasticity of wind speed. For assessing generalization to new data, CNN models are tested on regions with different topography and climate that are unseen during training. The evaluation of superresolved predictions focuses on subgrid-scale variability and the recovery of extremes. Models with coarse wind and fine topography as inputs exhibit the best performance when compared with other model configurations, operating across the same downscaling factor. Our diurnal cycle encoding results in lower out-of-sample generalizability when compared with other input configurations.

17 WIND ENERGY↗
DOE OSTI2018

Simulation of Hurricane Katrina at 3km resolution

A regional climate model simulation of Hurricane Katrina at 3 km resolution, part of a study published in Nature titled, “Anthropogenic Influences on Major Tropical Cyclone Events,” by Berkeley Lab researchers Christina Patricola and Michael Wehner. The study found that climate change intensified the amount of rainfall in recent hurricanes such as Katrina, Irma, and Maria by 5 to 10 percent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modes of Variability in E3SM and CESM Large Ensembles

An adequate characterization of internal modes of climate variability (MoV) is a prerequisite for both accurate seasonal predictions and climate change detection and attribution. Assessing the fidelity of climate models in simulating MoV is therefore essential; however, doing so is complicated by the large intrinsic variations in MoV and the limited span of the observational record. Large ensembles (LEs) provide a unique opportunity to assess model fidelity in simulating MoV and quantify intermodel contrasts. Here, in this work, these goals are pursued in four recently produced LEs: the Energy Exascale Earth System Model (E3SM) versions 1 and 2 LEs, and the Community Earth System Model (CESM) versions 1 and 2 LEs. In general, the representation of global coupled modes is found to improve across successive E3SM and CESM versions in conjunction with the fidelity of the base state climate while the patterns of extratropical modes are well simulated across the ensembles. Various persistent shortcomings for all MoV are however identified and discussed. The results both demonstrate the successes of these recent model versions and suggest the potential for continued improvement in the representation of MoV with advances in model physics.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2020

Global Teleconnections: Atmospheric Interactions Across Scales [Slides]

This project aims at an improved understanding of non-hydrostatic dynamics in atmospheric modeling using the DOE’s next generation climate model. One aspect that we have been focusing on is baroclinic instability which is closely related to mid-latitude cyclone genesis. The other aspect that we recently developed is E3SM simulations under Radiative-Convective Equilibrium (RCE), a prototype of tropical climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Laboratory Experiments and Instrument Intercomparison Studies of Carbonaceous Aerosol Particles

Aerosols containing black carbon (and some specific types of organic particulate matter) directly absorb incoming light, heating the atmosphere. In addition, all aerosol particles backscatter solar light, leading to a net-cooling effect. Indirect effects involve hydrophilic aerosols, which serve as cloud condensation nuclei (CCN) that affect cloud cover and cloud stability, impacting both atmospheric radiation balance and precipitation patterns. At night, all clouds produce local warming, but overall clouds exert a net-cooling effect on the Earth. The effect of aerosol radiative forcing on climate may be as large as that of the greenhouse gases, but predominantly opposite in sign and much more uncertain. The uncertainties in the representation of aerosol interactions in climate models makes it problematic to use model projections to guide energy policy. The objective of our program is to reduce the uncertainties in the aerosol radiative forcing in the two areas highlighted in the ASR Science and Program Plan. That is, (1) addressing the direct effect by correlating particle chemistry and morphology with particle optical properties (i.e. absorption, scattering, extinction), and (2) addressing the indirect effect by correlating particle hygroscopicity and CCN activity with particle size, chemistry, and morphology. In this connection we are systematically studying particle formation, oxidation, and the effects of particle coating. The work is specifically focused on carbonaceous particles where the uncertainties in the climate relevant properties are the highest. The ongoing work consists of laboratory experiments and related instrument inter-comparison studies both coordinated with field and modeling studies, with the aim of providing reliable data to represent aerosol processes in climate models. The work is performed in the aerosol laboratory at Boston College. At the center of our laboratory setup are two main sources for the production of aerosol particles: (a) two well-characterized source of soot particles and (b) a flow reactor for controlled OH and/or O3 oxidation of relevant gas phase species to produce well-characterized SOA particles. After formation, the aerosol particles are subjected to physical and chemical processes that simulate aerosol growth and aging. A suite of instruments in our laboratory is used to characterize the physical and chemical properties of aerosol particles before and after processing. The Time of Flight Aerosol Mass Spectrometer (ToF-AMS) together with a Scanning Mobility Particle Sizer (SMPS) measures particle mass, volume, density, composition (including black carbon content), dynamic shape factor, and fractal dimension. The–ToF-AMS was developed at ARI with Boston College participation. About 120 AMS instruments are now in service (including 5 built for DOE laboratories) performing field and laboratory studies world-wide. Other major instruments include a thermal denuder, two Differential Mobility Analyzers (DMA), a Cloud Condensation Nuclei Counter (CCN), a Thermal desorption Aerosol GC/MS (TAG) and the new Soot Particle Aerosol Mass Spectrometer (SP-AMS). Optical instrumentation required for the studies have been brought to our laboratory as part of ongoing and planned collaborative projects with colleagues from DOE, NOAA and university laboratories. Optical instruments that will be utilized include a Photoacoustic Spectrometer (PAS), a Cavity Ring Down Aerosol Extinction Spectrometer (CRD-AES), a Photo Thermal Interferometer (PTI), a new 7-wavelength Aethalometer and a Cavity Attenuated Phase Shift Extinction Monitor (CAPS). These instruments are providing aerosol absorption, extinction and scattering coefficients at a range of atmospherically relevant wavelengths. During the past two years our work has continued along the lines of our original proposal. We report on 12 completed and/or continuing projects conducted during the period 08/14 to 0814/2015. These projects are described in 17 manuscripts published in refereed journals.

54 ENVIRONMENTAL SCIENCES↗