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At least 487 records · Page 27

Symmetry dilemmas in quantum computing for chemistry: A comprehensive analysis

Symmetry adaptation, universality, and gate efficiency are central but often competing requirements in quantum algorithms for electronic structure and many-body physics. For example, fully symmetry-adapted universal operator pools typically generate long and deep quantum circuits; gate-efficient universal operator pools generally break symmetries; and gate-efficient, fully symmetry-adapted operator pools may not be universal. In this work, we analyze such symmetry dilemmas both theoretically and numerically. On the theory side, we prove that the popular, gate-efficient operator pool consisting of singlet spin-adapted singles and perfect-pairing doubles is not universal when spatial symmetry is enforced. To demonstrate the strengths and weaknesses of the three types of pools, we perform numerical simulations using an adaptive algorithm paired with operator pools that are (i) fully symmetry-adapted and universal, (ii) fully symmetry-adapted and non-universal, and (iii) breaking a single symmetry and universal. Our numerical simulations encompass three physically relevant scenarios in which the target state is (i) the global ground state, (ii) the ground state crossed by a state differing in multiple symmetry properties, and (iii) the ground state crossed by a state differing in a single symmetry property. Our results show when symmetry-breaking but universal pools can be used safely, when enforcing at least one distinguishing symmetry suffices, and when a particular symmetry must be rigorously preserved to avoid variational collapse. Together, the formal and numerical analyses provide a practical guide for designing and benchmarking symmetry-adapted operator pools that balance universality, resource requirements, and robust state targeting in quantum simulations for chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SAM Code Enhancements for Modeling of Liquid Metal-Cooled Fast Reactor Concepts

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. This report summarizes two major efforts in addressing the modeling gaps in SAM for liquid-metal-cooled fast reactor (LMFR) applications, i.e. thermal mixing and stratification phenomena in large pools and corrosion-oxidation of components in flowing lead. A new one-dimensional model for thermal mixing and stratification effects in large pools and enclosures is developed and implemented. Thermal mixing and stratification occur when fluid enters a pool at a temperature different than the bulk fluid itself, a scenario often encountered during transients in pool-type systems. These phenomena are critical for the safety of reactors, impacting phenomena like natural circulation, which is essential for passive cooling. The improved model in SAM addresses limitations of state-of-the-art approaches by combining one-dimensional (1D) channels, representing the coolant jet flow, with lumped-parameter zero-dimensional (0D) pools, representing the rest of coolant in the tank. Energy exchange between the 1D jet and the 0D pools is based on heat transfer correlations calibrated against 3D simulations. It is verified that this model can handle various flow configurations, including hot jets in colder pools, cold jets in hotter pools, and the presence of features like ceilings, free surfaces, and obstacles. Additionally, validation against experimental data demonstrates the ability of the model to capture mixing and stratification effects in a wide range of conditions. The flexibility and improved accuracy of the new model make it a valuable tool for reactor safety analysis, allowing for the simulation of different geometries encountered in advanced reactors. A system-level corrosion modeling capability is developed and implemented in SAM to support Lead Fast Reactor (LFR) development. Although the initial focus of this capability will be on LFR application, this can later be expanded to include other liquid metals such as Lead-Bismuth Eutectic (LBE) and PbLi. This report summarizes the common corrosion mitigation strategies and outlines the progress on implementing and validating a corrosion-oxidation model in SAM. Verification and validation of the corrosion-oxidation portion of the model was performed using analytical solution and measured data from samples tested in the non-isothermal pumped lead loop at IPPE Obninsk. The iron transport and corrosion/precipitation portion of the model was assessed using an analytical model and measured corrosion depths from a natural convection lead loop experiment performed at CEA. It is demonstrated that the model implemented in SAM performed well in these assessments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Thermal Behavior During the Selective Laser Melting Process of Ti-6Al-4V Powder in the Point Exposure Scan Pattern

Currently, there are two main scan patterns, including the continuous exposure scan pattern and the point exposure scan pattern, during the selective laser melting (SLM) process. The point exposure scan pattern allows a three-dimensional (3-D) printer to build finer detail features as a static molten pool that is more stable than a dynamic one. However, there has been limited theoretical research on the thermal behavior characteristics during the process in the point exposure scan pattern. Therefore, in this study, the simulation of thermal behavior during SLM of Ti-6Al-4V powder in the point exposure scan pattern was performed. The temperature evolution behavior of different positions and the effects of exposure time on the temperature evolution behavior of different positions, temperature distributions, and dimensions of the molten pool were investigated. The results showed that the direct exposure position and unexposed position had significantly different temperature evolution behaviors under a given condition, and the changed exposure time had the greatest influence on the direct exposure position compared with unexposed position. Moreover, the thermal accumulation effect of a former exposure point on a later one decreased with increasing exposure time. In addition, with the increase of exposure time, the maximum temperature of the molten pool was enhanced and the surface morphology of the molten pool changed from an approximate ellipse to an approximate circle. Besides, the molten pool dimensions were found to increase with exposure time, which indicated that the exposure time played an important role in the stability of the molten pool and the metallurgical bonding in the process. Furthermore, the dimensions of the molten pool and metallurgical bonding in the cross-sectional view were obtained through experiments. Good agreement was obtained when comparing the simulated results with the experimental ones.

36 MATERIALS SCIENCE↗

A dynamic volumetric heat source model for laser additive manufacturing

Melt pool scale models of laser powder bed fusion (LPBF) offer insights into the process-structure-property relationships in additive manufacturing (AM). These models often neglect physical phenomena such as vapor cavity formation and fluid mechanics to reduce computational demands. Instead, volumetric heat source models are used to represent the effects that these phenomena have on the predicted melt pool dimensions. Generally, the dimensions and effective absorption of the volumetric heat source are calibrated to reproduce melt pool dimensions observed in metallographic cross sections taken from single-track experiments on bare plate. However, the transient nature of LPBF often deviates the melt pool dimensions from the assumed steady-state conditions of single-track experiments, motivating the need for a volumetric heat source model that more generally considers the dynamic relationship between melt pool shape and laser-material interactions. Here, we introduce a two-parameter volumetric heat source model that integrates several existing models into a generalized mathematical expression, providing independent control over the radial heat distribution via the parameter k and the volumetric shape of the heat source via the parameter m. This parameterization enables the calibration of melt pool shape predictions through simultaneous adjustment of these parameters, while keeping the radial heat source dimensions consistent with the experimental spot size (D4σ) and constraining the heat source depth and absorption to physically derived expressions for cavities. Consequently, the proposed volumetric heat source model adapts to changes in the local melt pool conditions due to scanning strategy and part geometry by dynamically adjusting the heat source depth and absorption. We demonstrate the capabilities of the proposed model through comparisons with a collection of experiments from the Additive Manufacturing Benchmark (AMBench).

36 MATERIALS SCIENCE↗

Exploring Demographic Factors Behind the User Preferences in Ridesharing Services

Ridesharing is an increasingly prevalent form of transportation. Personal and pooled rideshare services are the two modes of ridesharing available on the market. While personal rideshare features higher time efficiency and better service experience, especially in terms of privacy, pooled rideshare has better energy efficiency and can reduce traffic congestion. To encourage users to utilize pooled rideshare, it is crucial to understand the factors behind preferences between pooled and personal rideshare services. This study conducted a survey study on a sample of 2,884 participants from the U.S. The stated-choice method was employed to collect the usage rate of pooled rideshare in designed scenarios. A detailed analysis of pooled rideshare usage rates among participants from different demographic backgrounds was performed. The results demonstrated demographic factors related to variations in pooled rideshare usage rates. Findings from this study explore the impacts of demographic factors on people's choices in ridesharing and provide important information for the modeling and optimization of ridesharing transportation systems.

Su, Haotian↗

Accuracy of Fukuoka and American Gastroenterological Association Guidelines for Predicting Advanced Neoplasia in Pancreatic Cyst Neoplasm: A Meta-Analysis

Background: A differential diagnosis of advanced pancreatic cystic neoplasms (PCNs) is critical to determine optimal treatment. The Fukuoka and American Gastroenterological Association (AGA) guidelines are the most widely accepted criteria for the management of PCNs. Objective: This study aimed to evaluate the diagnostic value of these guidelines in predicting advanced neoplasia (AN). Methods: A comprehensive electronic search of the PubMed, EMBASE, Web of Science, Cochrane Library, and Scopus databases was conducted to identify all relevant studies evaluating the Fukuoka and AGA guidelines in surgically resected and histologically confirmed PCNs. Pooled sensitivity, specificity, and diagnostic odds ratios (DORs) were calculated as compound measures of diagnostic accuracy using the random-effects model. Summary of receiver operating characteristic (SROC) curves and the area under the curve (AUC) were also performed. Results: A total of 21 studies with 3723 patients were included in this meta-analysis. Of these studies, 15, 4, and 2 evaluated the Fukuoka guidelines, the AGA guidelines, and both guidelines, respectively. For AN prediction, the Fukuoka guidelines had a pooled sensitivity of 0.67 (95% confidence interval [CI] 0.64–0.70), pooled specificity of 0.64 (95% CI 0.62–0.66), and pooled DOR of 6.28 (95% CI 4.38–9.01), with an AUC of the SROC of 0.78. AGA guidelines showed a pooled sensitivity of 0.59 (95% CI 0.52–0.65), pooled specificity of 0.77 (95% CI 0.74–0.80), and pooled DOR of 5.84 (95% CI 2.60–13.15), with an AUC of 0.79 (95% CI 0.70–0.88). Conclusion: When used alone, the Fukuoka and AGA guidelines showed similar but unsatisfactory diagnostic accuracy in the risk stratification of malignant potential of PCN. Thus, we recommend that they be applied only as a broad framework in clinical practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Avoiding symmetry roadblocks and minimizing the measurement overhead of adaptive variational quantum eigensolvers

Quantum simulation of strongly correlated systems is potentially the most feasible useful application of near-term quantum computers. Minimizing quantum computational resources is crucial to achieving this goal. A promising class of algorithms for this purpose consists of variational quantum eigensolvers (VQEs). Among these, problem-tailored versions such as ADAPT-VQE that build variational ansätze step by step from a predefined operator pool perform particularly well in terms of circuit depths and variational parameter counts. However, this improved performance comes at the expense of an additional measurement overhead compared to standard VQEs. Here, we show that this overhead can be reduced to an amount that grows only linearly with the number n of qubits, instead of quartically as in the original ADAPT-VQE. We do this by proving that operator pools of size 2 n − 2 can represent any state in Hilbert space if chosen appropriately. We prove that this is the minimal size of such "complete" pools, discuss their algebraic properties, and present necessary and sufficient conditions for their completeness that allow us to find such pools efficiently. We further show that, if the simulated problem possesses symmetries, then complete pools can fail to yield convergent results, unless the pool is chosen to obey certain symmetry rules. We demonstrate the performance of such symmetry-adapted complete pools by using them in classical simulations of ADAPT-VQE for several strongly correlated molecules. Our findings are relevant for any VQE that uses an ansatz based on Pauli strings.

Shkolnikov, V. O.↗

Influence of Thermophysical Property Variability on Thermal Predictions of Ti-6Al-4V

The additive manufacturing (AM) industry has experienced rapid growth in recent decades as industrial interest in the process has grown. Because of this, there are many groups interested in simulations of the AM process. However, the influence of thermophysical property variability on the melt pool geometry during processing of various AM alloys is unclear. The goal of my work at NASA Langley Research Center (LaRC) was to characterize this influence on Ti-6Al-4V during AM processing alongside developing a tool to enable equivalent studies on other AM materials. To facilitate this process, a database tool was developed to contain and organize thermophysical data previously reported by primary sources. The specific thermophysical properties of interest for this study were density, specific heat capacity, and conductivity. Thermal diffusivity was calculated using the other three properties. This data was then fit with a Gaussian distribution and then randomly sampled from using Monte Carlo random value sampling. Using the Rosenthal equation, this sample data was used to simulate the temperature field during additive manufacturing and extract the melt pool geometry. Specifically, the melt pool’s length, width, and depth. This process was repeated an arbitrary number of times, with the default being 1000. Once this information was obtained, histograms were made showing the distributions of the sizes of the melt pool’s length, width, and depth. Representative statistical metrics of the distributions were calculated (mean, standard deviation, and coefficient of variance). This work found that at the simulated processing values, the melt pool’s width and depth had a 5.7% variation while the length had a 3.2% variation. Additionally, a tool was constructed to graph a thermal color map representation of the melt pool for specific, arbitrary values of density, specific heat, and conductivity. This tool allowed for more efficient plotting of individual queries of the thermophysical properties. The results that were observed in the research were that values reported in literature vary and this variance can have a significant impact on the simulation. Predictions of the melt pool’s dimensions show that length has a standard deviation of approximately 6 μm, width has a standard deviation of approximately 5 μm, and depth can vary by approximately 3 μm. Considering the mean sizes of length, width, and depth are 185 μm, 88 μm, and 44 μm respectively, such a deviation is significant. This shows that depth, for example, could be more than 10% larger or smaller than expected. This demonstrates that variability in the reported thermophysical properties are not negligible and should be expected to have an influence on the results of the laser powder bed fusion additive manufacturing process. When simulating this process in the future, measures should be taken to account for this discrepancy and the uncertainty involved

Justin Martin↗

Which way does the dendrite grow? Competition among epitaxy, preferred growth direction, and thermal gradients in powder bed fusion additive manufacturing

The as-processed microstructure of metal alloy parts manufactured through laser powder bed fusion (LPBF) is heavily derived from the cellular dendritic solidification. The growth direction of dendrites within the melt pool is determined through competition among epitaxial growth, preferred growth directions, and maximum thermal gradients. However, the dominant factor and the specific role of each in developing melt pool microstructures remain unknown. Here, in this study, we performed single laser track scans on an SS316L single crystal substrate and combined experimental characterization of microstructure and crystal orientations with Computational Fluid Dynamics simulations of thermal gradients to evaluate the role of each factor in determining dendritic growth direction and evolution. Our results reveal that epitaxial growth dominates microstructure development by preferentially growing along a single 〈100〉 variant of the single crystal substrate adjacent to the melt pool boundary. Under LPBF’s highly curved and rapidly evolving thermal field, this preferential dendrite variant selection and its continued growth from the melt pool boundary to the centerline are governed by the local temperature gradient magnitude at the solid-liquid interface, rather than by the instantaneous maximum temperature gradient direction alone. Using these findings, we successfully predict changes in the dendrite growth direction with changing laser scan direction on a single crystal substrate, and show that the geometric melt pool centerline can deviate from the microstructural centerline because asymmetric local temperature gradient magnitudes transiently limit growth, resulting in different dendrite travel distances on each side of the melt pool.

36 MATERIALS SCIENCE↗

An in situ imaging investigation of the effect of gas flow rates on directed energy deposition

Gas flow rates in Directed Energy Deposition (DED) Additive Manufacturing (AM) can significantly affect the quality of built parts by altering melt pool geometry. Using a DED process replicator and in situ synchrotron radiography, together with analogous experiments in an industrial DED machine, we investigate the impact of carrier gas and shield gas flow rates on build quality. The results reveal that there is a critical shield gas flow rate above which melt pools are flattened, tracks widen, and thus layer thickness decreases. The reduction in layer thickness is most prominent in conditions with low carrier gas flow rate, as the highly turbulent shield gas flow may divert slow moving powder particles away from the melt pool, decreasing capture efficiency. Very high flow rates increase internal porosity, as fast-moving particles impacting the melt pool surface can entrain chamber gas behind them. High gas flow rates also cool the melt pool, creating shallower melt pools with increased thermal gradients near the solidification front, increasing pore entrapment in the solidified track.

Additive manufacturing↗

Effects of Wind Shear and Aerosol Conditions on the Organization of Precipitating Marine Stratocumulus Clouds

Here this study examines how wind shear affects precipitating marine stratocumulus clouds under different cloud droplet number concentrations (N d ). We performed a series of large eddy simulations (LES) of nocturnal marine stratocumulus clouds using Cloud Model 1 (CM1). The simulations show that N d is the dominant factor for cloud cellular organization in this cloud regime rather than wind shear. Low N d characterizes the open cellular structure with a high in-cloud liquid water path (LWP). When wind shear is increased, the cloud fraction tends to decrease along with LWP, suggesting the cloud top region is significantly influenced by the entrainment and mixing of dry air from the free troposphere. We also examine cold pools in open and closed cellular clouds. Open-cell clouds produce larger and deeper cold pools compared to closed-cell clouds. Interestingly, cold pools can exist without surface precipitation and are produced by evaporation of light precipitation (drizzle) below the cloud base with weak downdrafts. The evaporation of raindrops and drizzle play an important role in initiating new convection, particularly where colliding outflows occur downstream of the cloud. This secondary convection contributes to the development and maintenance of the cloud cellular organization and formation.

54 ENVIRONMENTAL SCIENCES↗

Emergent temperature sensitivity of soil organic carbon driven by mineral associations

Abstract Soil organic matter decomposition and its interactions with climate depend on whether the organic matter is associated with soil minerals. However, data limitations have hindered global-scale analyses of mineral-associated and particulate soil organic carbon pools and their benchmarking in Earth system models used to estimate carbon cycle–climate feedbacks. Here we analyse observationally derived global estimates of soil carbon pools to quantify their relative proportions and compute their climatological temperature sensitivities as the decline in carbon with increasing temperature. We find that the climatological temperature sensitivity of particulate carbon is on average 28% higher than that of mineral-associated carbon, and up to 53% higher in cool climates. Moreover, the distribution of carbon between these underlying soil carbon pools drives the emergent climatological temperature sensitivity of bulk soil carbon stocks. However, global models vary widely in their predictions of soil carbon pool distributions. We show that the global proportion of model pools that are conceptually similar to mineral-protected carbon ranges from 16 to 85% across Earth system models from the Coupled Model Intercomparison Project Phase 6 and offline land models, with implications for bulk soil carbon ages and ecosystem responsiveness. To improve projections of carbon cycle–climate feedbacks, it is imperative to assess underlying soil carbon pools to accurately predict the distribution and vulnerability of soil carbon.

54 ENVIRONMENTAL SCIENCES↗

MOSIQS: Persistent Memory Object Storage With Metadata Indexing and Querying for Scientific Computing

Scientific applications often require high-bandwidth shared storage to perform joint simulations and collaborative data analytics. Shared memory pools provide a chance to satisfy such needs. Recently, a high-speed network such as Gen-Z utilizing persistent memory (PM) offers an opportunity to create a shared memory pool connected to compute nodes. However, there are several challenges to use scientific applications on the shared memory pool directly such as scalability, failure-atomicity, and lack of scientific metadata-based search and query. In this paper, we propose MOSIQS, a persistent memory object storage framework with metadata indexing and querying for scientific computing. We design MOSIQS based on the key idea that memory objects on PM pool can live beyond the application lifetime and can become the sharing currency for applications and scientists. MOSIQS provides an aggregate memory pool atop an array of persistent memory devices to store and access memory objects to accelerate scientific computing. MOSIQS uses a lightweight persistent memory key-value store to manage the metadata of memory objects, which enables memory object sharing. To facilitate metadata search and query over millions of memory objects resident on memory pool, we introduce Group Split and Merge (GSM), a novel persistent index data structure designed primarily for scientific datasets. GSM splits and merges dynamically to minimize the query search space and maintains low query processing time while overcoming the index storage overhead. MOSIQS is implemented on top of PMDK. We evaluate the proposed approach on many-core server with an array of real PM devices. Experimental results show that MOSIQS gains a 100% write performance improvement and executes multi-attribute queries efficiently with 2.7× less index storage overhead offering significant potential to speed up scientific computing applications.

97 MATHEMATICS AND COMPUTING↗

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗

The effect of repeated hurricanes on the age of organic carbon in humid tropical forest soil

Abstract Increasing hurricane frequency and intensity with climate change is likely to affect soil organic carbon (C) stocks in tropical forests. We examined the cycling of C between soil pools and with depth at the Luquillo Experimental Forest in Puerto Rico in soils over a 30‐year period that spanned repeated hurricanes. We used a nonlinear matrix model of soil C pools and fluxes (“soilR”) and constrained the parameters with soil and litter survey data. Soil chemistry and stable and radiocarbon isotopes were measured from three soil depths across a topographic gradient in 1988 and 2018. Our results suggest that pulses and subsequent reduction of inputs caused by severe hurricanes in 1989, 1998, and two in 2017 led to faster mean transit times of soil C in 0–10 cm and 35–60 cm depths relative to a modeled control soil with constant inputs over the 30‐year period. Between 1988 and 2018, the occluded C stock increased and δ 13 C in all pools decreased, while changes in particulate and mineral‐associated C were undetectable. The differences between 1988 and 2018 suggest that hurricane disturbance results in a dilution of the occluded light C pool with an influx of young, debris‐deposited C, and possible microbial scavenging of old and young C in the particulate and mineral‐associated pools. These effects led to a younger total soil C pool with faster mean transit times. Our results suggest that the increasing frequency of intense hurricanes will speed up rates of C cycling in tropical forests, making soil C more sensitive to future tropical forest stressors.

14C↗

Real-Time and Rapid Respiratory Response of the Soil Microbiome to Moisture Shifts

Microbial response to changing environmental factors influences the fate of soil organic carbon, and drought has been shown to affect microbial metabolism and respiration. We hypothesized that the access of microbes to different carbon pools in response to dry–rewet events occurs sequentially at different rates. We amended desiccated soils with 13 C-labeled glucose and measured the rates of 12 CO 2 and 13 CO 2 respiration in real time after rewetting. Using these differentiated 12 CO 2 and 13 CO 2 respiration rate soils after rewetting, we were able to deduce when microbes are accessing different pools of carbon. Immediately upon rewetting, respiration of 12 CO 2 occurred first, with negligible 13 CO 2 respiration. Appreciable metabolism and respiration of the added 13 C glucose did not occur until 15 min after rewetting. We conclude that, while all carbon pools are being accessed in the first 9 h after rewetting, the rate and timing at which new and existing carbon pools are being accessed varies. Within this study, using stable isotope-labeled substrates to discern which carbon pools are metabolized first uniquely illustrates how microorganisms access different carbon pools which has implications into understanding how carbon metabolism can further affect climate, carbon sequestration, and soil health.

59 BASIC BIOLOGICAL SCIENCES↗

Determination and impact of surface radiative processes for TOGA COARE

Experiments using atmospheric general circulation models have shown that the atmospheric circulation is very sensitive to small changes in sea surface temperature in the tropical western Pacific Ocean warm pool region. The mutual sensitivity of the ocean and the atmosphere in the warm pool region places stringent requirements on models of the coupled ocean atmosphere system. At present, the situation is such that diagnostic studies using available data sets have been unable to balance the surface energy budget in the warm pool region to better than 50 to 80 W/sq m. The Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE) is an observation and modelling program that aims specifically at the elucidation of the physical process which determine the mean and transient state of the warm pool region and the manner in which the warm pool interacts with the global ocean and atmosphere. This project focuses on one very important aspect of the ocean atmosphere interface component of TOGA COARE, namely the temporal and spatial variability of surface radiative fluxes in the warm pool region.

Curry, Judith A.↗