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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Subtropical Eastern North Pacific SST bias in earth system models

Karthik Balaguru (PNNL), Luke Van Roekel (LLNL), L. Ruby Leung (PNNL) and Milena Veneziani (LLNL) Abstract: This study systematically evaluates the warm SST bias in the Subtropical Eastern North Pacific (SENP), a problem plaguing most CMIP6 models, using the Energy Exascale Earth System Model version 1 (E3SM). Compared to the model at its standard resolution (1o atmosphere, 30-60 km ocean), the SST bias improves in several regions at high resolution (0.25o atmosphere, 18-6 km ocean) except in subtropical eastern boundary regions, such as the SENP. A mixed layer heat budget analysis reveals that errors in the surface radiative fluxes and horizontal heat advection are primarily responsible for the bias. Analysis of HighResMIP models indicates that the lack of improvement in the SENP SST bias with resolution is not native to E3SM alone. A larger CMIP6 inter-model correlation of SST bias with biases in surface winds than radiation highlights the important role of large-scale circulation biases in the SENP SST bias in coupled models.

Balaguru, Karthik↗
DOE OSTI2021

Winter precipitation changes in California under global warming: Contributions of CO2, uniform SST warming, and SST change patterns

Climate models project a wetting winter over California, distinct from the drying in all other Mediterranean climate regions under warming. Dynamic effect via an eastward extension of the westerly jet stream over the North Pacific is the root cause for the wetting California. Utilizing four sets of prescribed-SST (sea surface temperature) simulations, the relative effects of direct CO2 radiative forcing, uniform SST warming, and SST change pattern are investigated. The wetting winter is dominated by uniform SST warming mainly through its effect on the jet extension. As a fundamental response to the enhanced upper-tropospheric warming in the tropics, the jet extension in coupled simulations is well reproduced under uniform SST warming and robust among models. An El Niño-like SST warming pattern has a secondary contribution to the jet extension via atmospheric teleconnection, but with large inter-model spread. Relative to the SST forcing, the direct CO2 radiative effect is negligible.

Dong, Lu↗
DOE OSTI2021

SST-GPU: A Scalable SST GPU Component for Performance Modeling and Profiling

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of unprecedented amounts of data have created a space for massively parallel accelerators capable of maintaining context for thousands of concurrent threads resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. One path for the design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. The SST framework has been proven to scale up to run simulations containing tens of thousands of nodes. A previous report described the initial integration of the open-source, execution-driven GPU simulator, GPGPU-Sim, into the SST framework. This report discusses the results of the integration and how to use the new GPU component in SST. It also provides examples of what it can be used to analyze and a correlation study showing how closely the execution matches that of a Nvidia V100 GPU when running kernels and mini-apps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

SST-TG-P1F4R3200: Decaying Stably-Stratified Turbulence (SST), Initialized Using Taylor-Green Vortices (TG) at Prandtl Number Pr=1, Froude Number Fr=4, Reynolds Number Re=3200

This dataset comprises direct numerical simulations (DNS) of decaying stably-stratified turbulence influenced by a linear background density gradient, initialized using an array of Taylor-Green vortices, as described in [Riley & de Bruyn Kops (2003)](https://doi.org/10.1063/1.1578077). The initial Prandtl, Froude, and Reynolds numbers are (Pr, Fr, Re) = (1, 4, 3200). A total of 15,000 snapshots are recorded at uniform time intervals, each with a spatial resolution of 512x512x256 grid points. Four flow variables are associated with each snapshot: the three velocity components (u,v,w) and the perturbed density field (rho) away from the background gradient. All fields are stored in binary format (32-bit little-endian), each with a size of 255 MB, yielding a total dataset size of 15.3 TB. Further details are referenced in the attached README file, and a current list of publications and associated analysis tools are provided at https://stratified-turbulence.github.io/web/.

42 ENGINEERING↗
DOE OSTI2025

SST-TG-P50F4R3200: Decaying Stably-Stratified Turbulence (SST), Initialized Using Taylor-Green Vortices (TG) at Prandtl Number Pr=50, Froude Number Fr=4, Reynolds Number Re=3200

This dataset comprises direct numerical simulations (DNS) of decaying stably-stratified turbulence influenced by a linear background density gradient, initialized using an array of Taylor-Green vortices, extending the Pr=1 simulations performed in [Riley and de Bruyn Kops (2003)](https://doi.org/10.1063/1.1578077). The initial Prandtl, Froude, and Reynolds numbers are (Pr, Fr, Re) = (50, 4, 3200). A total of 1,680 snapshots are recorded at uniform time intervals, each with a spatial resolution of 3584x3584x1792 grid points. Four flow variables are associated with each snapshot: the three velocity components (u,v,w) and the perturbed density field (rho) away from the background gradient. All fields are stored in binary format (32-bit little-endian), each with a size of 85.8 GB, yielding a total dataset size of 577 TB. Further details are referenced in the attached README file, and a current list of publications and associated analysis tools are provided at https://stratified-turbulence.github.io/web/.

42 ENGINEERING↗
DOE OSTI2025

SST-TG-P7F4R3200: Decaying Stably-Stratified Turbulence (SST), Initialized Using Taylor-Green Vortices (TG) at Prandtl Number Pr=7, Froude Number Fr=4, Reynolds Number Re=3200

This dataset comprises direct numerical simulations (DNS) of decaying stably-stratified turbulence influenced by a linear background density gradient, initialized using an array of Taylor-Green vortices, extending the Pr=1 simulations performed in [Riley and de Bruyn Kops (2003)](https://doi.org/10.1063/1.1578077). The initial Prandtl, Froude, and Reynolds numbers are (Pr, Fr, Re) = (7, 4, 3200). A total of 15,250 snapshots are recorded at uniform time intervals, each with a spatial resolution of 1280x1280x640 grid points. Four flow variables are associated with each snapshot: the three velocity components (u,v,w) and the perturbed density field (rho) away from the background gradient. All fields are stored in binary format (32-bit little-endian), each with a size of 4 GB, yielding a total dataset size of 244 TB. Further details are referenced in the attached README file, and a current list of publications and associated analysis tools are provided at https://stratified-turbulence.github.io/web/.

42 ENGINEERING↗
DOE OSTI2020

Forced and Unforced Decadal Behavior of the Interhemispheric SST Contrast during the Instrumental Period (1881–2012): Contextualizing the Late 1960s–Early 1970s Shift

The sea surface temperature (SST) contrast between the Northern Hemisphere (NH) and Southern Hemisphere (SH) influences the location of the intertropical convergence zone (ITCZ) and the intensity of the monsoon systems. This study examines the contributions of external forcing and unforced internal variability to the interhemispheric SST contrast in HadSST3 and ERSSTv5 observations, and 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 1881 to 2012. Using multimodel mean fingerprints, a significant influence of anthropogenic, but not natural, forcing is detected in the interhemispheric SST contrast, with the observed response larger than that of the model mean in ERSSTv5. The forced response consists of asymmetric NH–SH SST cooling from the mid-twentieth century to around 1980, followed by opposite NH–SH SST warming. The remaining best-estimate residual or unforced component is marked by NH–SH SST maxima in the 1930s and mid-1960s, and a rapid NH–SH SST decrease around 1970. Examination of decadal shifts in the observed interhemispheric SST contrast highlights the shift around 1970 as the most prominent from 1881 to 2012. Both NH and SH SST variability contributed to the shift, which appears not to be attributable to external forcings. Most models examined fail to capture such large-magnitude shifts in their control simulations, although some models with high interhemispheric SST variability are able to produce them. Large-magnitude shifts produced by the control simulations feature disparate spatial SST patterns, some of which are consistent with changes typically associated with the Atlantic meridional overturning circulation (AMOC).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the oceanic origin for the enhanced seasonal cycle of SST in the midlatitudes under global warming

Climate models project an enhancement in SST seasonal cycle over the midlatitude oceans under global warming. However, the maintaining mechanism for this enhancement is still under debate. This study investigates the SST seasonal cycle enhancement under quadrupling CO2 using a set of partially coupled experiments, in which the contribution from direct CO2 forcing (without the effect of wind changes) and wind effects can be isolated. Results indicate that both the direct CO2 and total wind effects contribute to the enhancement in the SST seasonal cycle, with the former (latter) effect being more important in the Northern Hemisphere (Southern Hemisphere). Further decomposition of the wind effect into the wind stress feedback and wind-evaporation-SST (WES) feedback through the change of wind speed reveals the importance of the wind stress-driven ocean response in the change of SST seasonal cycle, a result in contrast to a previous study that ascribed the midlatitude SST seasonal cycle change to the thermodynamic WES feedback. The direct CO2 effect regulates SST seasonal cycle mainly through the mediating effects of the ocean mixed layer depth (MLD): i) the CO2 induced warming leads to MLD shoaling, thus reducing its effective heat capacity; ii) the climatological MLD is greater in winter than summer, given the same amount of energy flux from the surface, SST warming in winter should be smaller. Notably, the surface wind seasonal cycle change due solely to the direct CO2 effect is found to bear a great resemblance to the full wind response, implicating that the direct CO2 effect is the root source for the enhancement of the midlatitude SST seasonal cycle. This is further supported by an ocean-alone experiment that replicates the SST seasonal cycle enhancement under a spatially and temporally homogeneous surface thermal forcing into the ocean.

Liu, Fukai↗
DOE OSTI2023

The Role of Atmospheric Noise in Decadal SST Variability

Abstract A substantial role for atmospheric noise in simulations of decadal internal variability of SST is demonstrated by a comparison of a multicentury climate model control and a corresponding interactive ensemble (IE) simulation. The IE is designed to reduce atmospheric noise in the heat flux, wind stress, and freshwater flux at the air–sea interface. This comparison suggests that nearly all SST variability on decadal time scales is forced by internal atmospheric variability. The results are examined to determine the relative roles of atmospheric surface heat flux noise and ocean dynamics in the decadal volume-averaged heat budget of the upper ocean. The regional heat budgets in two regions, the South Pacific and the midlatitude North Atlantic, show the net atmospheric surface heat flux to be approximately in equilibrium with the ocean dynamics forcing. The IE and control results are used in the equilibrium heat budget approximation to infer the atmospheric heat flux response to SST, as well as the time series of the control atmospheric noise surface heat flux and ocean dynamics forcings for several regions. The South Pacific region SST is found to be primarily forced by the atmospheric noise surface heat flux and the North Atlantic region SST is forced by the ocean dynamics. Similar strengths for the atmospheric heat flux noise and ocean dynamics forcing, with an interdecadal atmospheric heat flux noise time scale and a centennial ocean dynamics time scale, are found for an Atlantic multidecadal variability region SST.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

The Shortwave Cloud-SST Feedback Amplifies Multi-Decadal Pacific Sea Surface Temperature Trends: Implications for Observed Cooling

Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud-SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi-decadal SST variability. A heat-budget analysis reveals coupling between cloud-radiative effects, circulation, and SST gradients in driving multi-decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ~56% on average. If models underestimate climate “noise,” as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate.

58 GEOSCIENCES↗
DOE OSTI2025

Evaluating switch lifetime in soft-switched single-stage differential-mode SST

The reliability of semiconductor switches in single-stage differential-mode solid-state transformers (DM-SSTs) has not been systematically evaluated under soft-switching operation and realistic grid conditions. This paper presents a switch-level reliability analysis for soft-switched and hard-switched DM-SST configurations by integrating converter-specific power loss modeling with empirical lifetime prediction. Analytical derivation of device current profiles specific to the DM-SST is used to characterize electrothermal stress, which is then mapped to lifetime using degradation models obtained from power cycling tests (PCTs). Applied to realistic SST load profiles and grid voltage variations, this approach provides a probabilistic prediction of switch lifetime for the DM-SST. Lifetime estimates for both SiC MOSFETs and Si IGBTs are presented, offering insight into device degradation under converter operating conditions. The results quantify the reliability benefits of soft switching in single-stage SSTs, highlighting how switching dynamics influence long-term switch degradation.

14 SOLAR ENERGY↗
DOE OSTI2021

Evolving CO 2 rather than SST leads to a factor of ten decrease in GCM convergence time

The high computational cost of Global Climate Models (GCMs) is a problem that limits their use in many areas. Recently an inverse climate modeling (InvCM) method, which fixes the global mean sea surface temperature (SST) and evolves the CO 2 mixing ratio to equilibrate climate, has been implemented in a cloud resolving model. In this paper, we apply InvCM to ExoCAM GCM aquaplanet simulations, allowing the SST pattern to evolve while maintaining a fixed global-mean SST. We find that InvCM produces the same climate as normal slab-ocean simulations but converges an order of magnitude faster. We then use InvCM to calculate the equilibrium CO 2 for SSTs ranging from 290 K to 340 K at 1 K intervals and reproduce the large increase in climate sensitivity at an SST of about 315 K at much higher temperature resolution. The speedup provided by InvCM could be used to equilibrate GCMs at higher spatial resolution or to perform broader parameter space exploration in order to gain new insight into the climate system. Additionally, InvCM could be used to find unstable and hidden climate states, and to find climate states close to bifurcations such as the runaway greenhouse transition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

On the Effect of Historical SST Patterns on Radiative Feedback

Here, we investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in fourteen Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with long term climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt 4xCO2 simulations). Post 1980 however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) and cooling in the Southern Ocean that drove climate feedback to be uncorrelated with – and indicating much lower climate sensitivity than – that expected for long-term CO 2 increase. We show that these conclusions are not strongly dependent on the AMIP II SST dataset used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in nine AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a ‘pattern effect’ (defined as the difference between historical and longterm CO 2 feedback) equal to 0.48 ± 0.47 [5-95%] W m -2 K -1 for the time-period 1871-2010 when the AGCMs are forced with HadISST1 SSTs, or 0.70 ± 0.47 [5-95%] W m -2 K -1 when forced with AMIP II SSTs. Assessed changes in the Earth’s historical energy budget agree with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades but may be waning post 2014.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Attribution of the record-high 2023 SST using a deep-learning framework

Abstract The global-mean sea surface temperature (SST) reached a record high in 2023, exceeding the 2016 record by 0.14 °C. This unprecedented change in global-mean SST has major implications for our understanding of internal variability and the forced response in our changing climate. In this work, we use neural networks trained on simulated climate data to separate the contributions of internal variability and the forced response within observations. Performing attribution reveals that internal variability was responsible for +0.07 °C of the 2023 global mean SST, due to anomalously warm conditions in the Pacific, Atlantic, and Indian Ocean basins. Furthermore, these results provide a line of evidence for accelerated forced warming in recent years. Continued monitoring of the climate will be critical for understanding the drivers behind this unprecedented SST record.

Rader, Jamin K. (ORCID:0000000222045977)↗
DOE OSTI2021

Structural Simluation Toolkit (SST) v.11.0

The SST provides a parallel framework to perform system simulation of computer architectures to determine their performance and power consumption. Additionally, the SST contains basic models of a computer processor, and interconnect and can connect to an external memory simulator (DRAMSim II). The SST framework provides a simple interface by which other computer simulation models can be combined under a common parallel discrete event-based simulation environment. This allows design exploration of future architectures, analysis of how current computer programs will function on future architectures. The SST provides a parallel discrete event simulation framework, including partitioning and object distribution over MPI. It also provides a mechanism by which components can report their power consumption for analysis.

Rodrigues, ArunF.↗
DOE OSTI2023

The QBO–MJO Connection: A Possible Role for the SST and ENSO

We examine the hypothesis that the observed connection between the stratospheric quasi-biennial oscillation (QBO) and the strength of the Madden–Julian oscillation (MJO) is modulated by the sea surface temperature (SST)—for example, by El Niño–Southern Oscillation (ENSO). A composite analysis shows that, globally, La Niña SSTs are remarkably similar to those that occur during the easterly phase of the QBO. A maximum covariance analysis suggests that MJO power and SST are strongly linked on both the ENSO time scale and the QBO time scale. We analyze simulations with a modified configuration of version 2 of the Community Earth System Model, with a high top and fine vertical resolution. The model is able to simulate ENSO, the QBO, and the MJO. The ocean-coupled version of the model simulates the QBO, ENSO, and MJO, but does not simulate the observed QBO–MJO connection. When driven with prescribed observed SST anomalies based on composites for QBO east and QBO west (QBOE and QBOW), however, the same atmospheric model produces a modest enhancement of MJO power during QBOE relative to QBOW, as observed. We explore the possibility that the SST anomalies are forced by the QBO itself. Indeed, composite Hovmöller diagrams based on observations show the propagation of QBO zonal wind anomalies all the way from the upper stratosphere to the surface. Also, subsurface ocean temperature composites reveal a similarity between the western Pacific and Indian Ocean subsurface signal between La Niña and QBOE.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

SST ..kappa..-..omega.. Simulations of the Atmospheric Boundary Layer Including the Coriolis Effect

For large-scale structures in the atmospheric boundary layer (ABL), the Coriolis effect and near-wall behavior can have a meaningful impact. For example, both the Coriolis effect and blade boundary layer impact how muchpower wind farms produce. RANS simulations of the ABL typically use the ..kappa..-epsilon turbulence model, which has been developed to accurately capture the Coriolis effect but typically does not perform well near walls. The SST ..kappa..-..omega.. turbulence model performs well near walls but does not accurately capture the Coriolis effect. This work modifies SST ..kappa..-..omega.. to accurately model the Coriolis effect. We discuss the similarities and differences in how to modify ..kappa..-epsilon and SST ..kappa..-..omega.. for the Coriolis effect. Finally, we compare ..kappa..-epsilon and SST ..kappa..-..omega.. simulations of the ABL, including the Coriolis effect, with large eddy simulations and measurements.

atmospheric boundary layer↗