SEARCH · Engineering Papers

Results for “variable importance”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,171 records · Page 65

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Causal Directions Matter: How Environmental Factors Drive Convective Cloud Detrainment Heights

This study investigates how environmental factors influence the level of maximum detrainment (LMD) in deep convective clouds. Through a novel application of the Linear Non‐Gaussian Acyclic Model (LiNGAM), we discover causal structures between environmental variables and LMD, observed at six tropical sites operated by the Atmospheric Radiation Measurement (ARM) user facility. LiNGAM effectively identifies causal directions among variables of interest, revealing robust relationships such as those among the lifting condensation level (LCL), level of free convection (LFC), and convective inhibition (CIN), aligning with prior knowledge. Relative humidity is shown to directly influence LMD; however, this relationship exhibits strong nonlinearity and becomes difficult to detect when the contrast between oceanic and continental environments is excluded from the analysis. This study highlights the importance of establishing causal relationships before performing statistical inference.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Eulerian finite element simulations of the drop weight impact test with a dislocation Density-based continuum model

During a drop weight impact test, the kinetic energy of the falling weight is transferred into the sample resting on the anvil. The plastic deformation in the sample is an important mechanism for the dissipation of the input kinetic energy. We use Eulerian finite element analysis to simulate the deformation and temperature evolution in a 1,3,5-trinitro-1,3,5-triazine (RDX) sample consisting of multiple crystals. In Eulerian finite element simulations, the mesh moves relative to the material. After every change of position between the mesh and the material, the state variables are interpolated to the new mesh position, i.e., advection. In an effort to reduce the advection errors, we use a rate form of a dislocation density-based continuum model by Luscher et al. Here, the simulations predict localization of plastic deformation, and plastic dissipation as a significant source of heat generation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Climatology of Linear Mesoscale Convective System Morphology in the United States based on Random Forests Method

This study uses machine learning methods, specifically the random forest (RF), on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004-2016. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, and reanalysis environmental information from 5-26yr manually identified nonlinear and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, in which half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (through March to October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus have higher potential in producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

Cui, Wenjun↗

DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

DOE OSTI2025

Phase-field modeling and experiments of dynamic fracture in single crystal quartz

Predicting the onset and characteristics of brittle fracture is important for a wide range of engineering and geological material applications. In this paper, we study important aspects of brittle fracture in α-quartz by phase-field modeling and experiments using a top-down approach. In the modeling framework, the work term in the Griffith energy balance is replaced with internal energy contributions that represent surface energy, thermal energy, and elastic strain energy stored in defects. This allows parametrization of individual energy contributions in terms of internal state variables and keeps track of energy partitioning after the onset of fracture. The path and history dependence of fracture is included in evolution laws for internal state variables, e.g., entropy evolution, while the energy remains a true potential. In the experimental part, dynamic compression experiments coupled with X-ray phase contrast imaging are performed on cube-like samples with a hole. In the top-down analysis, dynamic compression and three point bending experiments from the literature are simulated with the developed phase-field damage model. In conclusion, the fitted model highlights the strain rate, size, and stress state dependence of damage nucleation and evolution in single crystal α-quartz.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Comprehensive Analysis of Model Parameter Uncertainty Influence on Evaluation of HVAC Operation to Mitigate Indoor Virus: A Case Study for an Office Building in a Cold and Dry Climate

Simulation-based studies of HVAC operation to mitigate indoor virus have been conducted to understand tradeoffs between indoor air quality (IAQ) and energy consumption. However, the influence of model parameter uncertainty in these studies has not been systematically quantified, which is critical when providing guidance to building operators. To address this gap, we identify 20 model parameters for a typical medium office building system in a cold and dry climate that can influence IAQ and energy consumption for indoor virus scenarios. Next, the distributions of the parameter values are estimated from literature and a set of simulation samples for three representative days is generated that simultaneously sample all of the parameters from their distributions. Two HVAC virus mitigation strategies are studied: increased filtration using MERV 13 filters and increased ventilation, via supply of 100% outdoor air into buildings. The model parameter uncertainty leads to significant variability in the results, particularly for the IAQ because of the highly uncertain virus generation rate. Use of 100% outdoor air can be beneficial for some uncertain scenarios on the hot day, but shows less IAQ improvement and/or significant energy increases on the other days. The virus removal efficiency and pressure drop of the HVAC filter, fan efficiency, and internal heat gain are the most important parameters to determining the tradeoffs of the two strategies. Our results demonstrate how this model parameter uncertainty analysis methodology can provide practical guidance to building operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems

Belowground autotrophic respiration (RAsoil) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but least understood components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RAsoil has not been fully examined at the global scale. To fill this knowledge gap, first, the spatio-temporal patterns of RAsoil from 1981 to 2017 were predicted by a Random Forest (RF) algorithm using the most updated Global Soil Respiration Database (v5) with global environmental variables; second, carbon allocation from photosynthesis to RAsoil (CAB), was calculated as the ratio of RAsoil to gross primary production; and its temporal and spatial patterns were assessed in global forest ecosystems. . Globally, mean RAsoil from forests was 8.9 ± 0.08 Pg C yr-1 (mean ± standard deviation) from 1981 to 2017 with strong spatial variabilities. Temporally, RAsoil increased at a rate of 0.0059 Pg C yr-2, paralleling broader soil respiration changes and indicating increasing carbon respired by roots. Mean CAB was 0.243 ± 0.016 and decreased over time. The temporal trend of CAB varied greatly in space, reflecting uneven responses of CAB to environmental changes. This study is the first attempt to predict global CAB and analyze its temporal and spatial patterns. With the linkage of carbon use efficiency, the developed CAB offers an completely independent approach to quantify global aboveground autotropic respiration spatially and temporally, which could provide crucial insights into carbon flux partition and global carbon cycling under climate change.

Tang, Xiaolu↗

DOE OSTI2021

Influence of intrinsic and extrinsic attributes on neonate survival in an invasive large mammal

Abstract Understanding factors influencing survival of neonates for wild species is important for successful management, particularly for determining drivers of population dynamics. Wild pigs ( Sus scrofa ) are invasive and populations are rapidly increasing in part due to high reproductive capacity. Survival of adults is generally high, however, survival of piglets, and particularly neonates, is largely unknown. We located neonates at the natal nest and quantified survival in relation to individual and maternal biological attributes, and environmental variables. During 2017–2020, we captured 50 neonates from 13 litters and documented 28 mortalities (56%) over six weeks. Survival was positively influenced by pelage coloration, likely as a form of camouflage from predators. Male neonates had higher survival. They were born larger than females, which could be beneficial for thermoregulation and competition for milk. Neonates born to larger sows had lower survival. Sow size was positively correlated with litter size, and this finding may reflect the increased nutritional demands of sustaining large litters, or difficulties in defending more neonates against predators. Neonates born in warmer months had higher survival than those born in cooler months. Neonates are inefficient thermoregulators, thus being born in warmer months could be beneficial for maintaining homeostasis as well as access to more food resources. These are the largest and most complete data for neonate wild pig survival and will inform population models for the development of management strategies to reduce negative impacts of this destructive invasive species on native ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

15-minute Parker River gap-filled tide height and salinity data, PIE LTER, Plum Island Sound, MA (2014–2023), for ELM PFLOTRAN modeling

This dataset contains 15-minute tide height and salinity data from the Typha site along the Parker River, part of the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site in Plum Island Sound, Massachusetts (MA) 2014-2023. Tide height (in NAVD88) was compiled from measurements conducted at the mouth of Plum Island Sound and corrected for time lags. Gap-filling of missing periods were done by fitting tidal constituents to the time series. Salinity was measured (and is stored on ESS DIVE ) in 2022 and 2023 using HOBO U24-002 conductivity loggers. River discharge is the most important control on tidal river water salinity at the location (Vallino & Hopkinson, 1998). An artificial neural network was trained to predict river water salinity at the location using Parker River discharge (USGS station 01101000, Parker River at Byfield, MA) and gap-filled salinity observations from a long-term monitoring station ca. 3km downstream from the Typha site (LTER station ‘Middle Road’) as input variables to create continuous time series information. The data set was used in the spin up and simulations of a land surface model coupled to a biogeochemical reaction network (ELM PFLOTRAN) assessing impacts of hydrology and salinity input on methane fluxes in 2022 and 2023 (Sulman et al., 2024). Metadata files ELMPFLOTRAN_tide_salinity_dd.csv and ELMPFLOTRAN_tide_salinity_flmd.csv provide details on site location, data variables, and QA/QC methods .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Identification and Characterization of ten Escherichia coli Strains Encoding Novel Shiga Toxin 2 Subtypes, Stx2n as Well as Stx2j, Stx2m, and Stx2o, in the United States

The sharing of genome sequences in online data repositories allows for large scale analyses of specific genes or gene families. This can result in the detection of novel gene subtypes as well as the development of improved detection methods. Here, we used publicly available WGS data to detect a novel Stx subtype, Stx2n in two clinical E. coli strains isolated in the USA. During this process, additional Stx2 subtypes were detected; six Stx2j, one Stx2m strain, and one Stx2o, were all analyzed for variability from the originally described subtypes. Complete genome sequences were assembled from short- or long-read sequencing and analyzed for serotype, and ST types. The WGS data from Stx2n- and Stx2o-producing STEC strains were further analyzed for virulence genes pro-phage analysis and phage insertion sites. Nucleotide and amino acid maximum parsimony trees showed expected clustering of the previously described subtypes and a clear separation of the novel Stx2n subtype. WGS data were used to design OMNI PCR primers for the detection of all known stx1 (283 bp amplicon), stx2 (400 bp amplicon), intimin encoded by eae (221 bp amplicon), and stx2f (438 bp amplicon) subtypes. These primers were tested in three different laboratories, using standard reference strains. An analysis of the complete genome sequence showed variability in serogroup, virulence genes, and ST type, and Stx2 pro-phages showed variability in size, gene composition, and phage insertion sites. The strains with Stx2j, Stx2m, Stx2n, and Stx2o showed toxicity to Vero cells. Stx2j carrying strain, 2012C-4221, was induced when grown with sub-inhibitory concentrations of ciprofloxacin, and toxicity was detected. Taken together, these data highlight the need to reinforce genomic surveillance to identify the emergence of potential new Stx2 or Stx1 variants. The importance of this surveillance has a paramount impact on public health. Per our description in this study, we suggest that 2017C-4317 be designated as the Stx2n type-strain.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗

DOE OSTI2023

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗

DOE OSTI2023

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Pidaparti, Sandeep↗

DOE OSTI2021

Oxygen isotope ratios in zircon and garnet: A record of assimilation and fractional crystallization in the Dinkey Dome peraluminous granite, Sierra Nevada, California

Abstract The 119 Ma Dinkey Dome pluton in the central Sierra Nevada Batholith is a peraluminous granite and contains magmatic garnet and zircon that are complexly zoned with respect to oxygen isotope ratios. Intracrystalline SIMS analysis tests the relative importance of magmatic differentiation processes vs. partial melting of metasedimentary rocks. Whereas δ18O values of bulk zircon concentrates are uniform across the entire pluton (7.7‰ VSMOW), zircon crystals are zoned in δ18O by up to 1.8‰, and when compared to late garnet, show evidence of changing magma chemistry during multiple interactions of the magma with wall rock during crustal transit. The evolution from an early high-δ18O magma [δ18O(WR) = 9.8‰] toward lower values is shown by high-δ18O zircon cores (7.8‰) and lower δ 18O rims (6.8‰). Garnets from the northwest side of the pluton show a final increase in δ18O with rims reaching 8.1‰. In situ REE measurements show zircon is magmatic and grew before garnets. Additionally, δ18O in garnets from the western side of the pluton are consistently higher (avg = 7.3‰) relative to the west (avg = 5.9‰). These δ18O variations in zircon and garnet record different stages of assimilation and fractional crystallization whereby an initially high-δ18O magma partially melted low-δ18O wallrock and was subsequently contaminated near the current level of emplacement by higher δ18O melts. Collectively, the comparison of δ18O zoning in garnet and zircon shows how a peraluminous pluton can be constructed from multiple batches of variably contaminated melts, especially in early stages of arc magmatism where magmas encounter significant heterogeneity of wall-rock assemblages. Collectively, peraluminous magmas in the Sierran arc are limited to small <100 km2 plutons that are intimately associated with metasedimentary wall rocks and often surrounded by later and larger metaluminous tonalite and granodiorite plutons. The general associations suggest that early-stage arc magmas sample crustal heterogeneities in small melt batches, but that with progressive invigoration of the arc, such compositions are more effectively blended with mantle melts in source regions. Thus, peraluminous magmas provide important details of the nascent Sierran arc and pre-batholithic crustal structure.

Geochemistry & Geophysics↗

DOE OSTI2020

Iodate interactions with calcite: implications for natural attenuation

Solid-phase interactions and speciation are important to radioiodine transport in groundwater. At the Hanford Site in Southeastern Washington State, iodate (IO 3 - ) is the main aqueous species in dilute radioiodine groundwater plumes. Like other oxyanions, IO 3 - may be incorporated into and/or adsorbed onto calcite, a common mineral at Hanford, decreasing its mobility in the environment. A series of macroscale batch experiments combined with solid phase characterization were conducted to identify variables impacting time-dependent aqueous IO 3 - removal via calcite precipitation and determine the location of IO 3 - within the calcite crystal structure. Results demonstrated 11.5-97% aqueous IO 3 - removal during initial rapid calcite precipitation. Incorporation was apparently the main removal mechanism, although later slower precipitation and/or adsorption may have also contributed to IO 3 - removal. Using a higher concentration of the calcite forming solutions (i.e., using 1M vs. 0.1M concentrations) resulted in an increase in the amount of precipitated calcite and a greater percentage of IO 3 - removed; however, calcite formed with lower molarity solutions resulted in higher IO 3 - mass (µg/g) removal. Solubility testing of laboratory produced calcites showed only small differences in solubility for calcite with and without IO 3 - incorporated into the structure. Evidence collected from SEM/FIB and TEM/SAED suggested that the IO 3 - incorporated into calcite was present in regions close to surface (implying potential easy release upon calcite dissolution).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Target mass corrections in lepton–nucleus DIS: Theory and applications to nuclear PDFs

Motivated by the wide range of kinematics covered by current and planned deep-inelastic scattering (DIS) facilities, we revisit the formalism, practical implementation, and numerical impact of target mass corrections (TMCs) for DIS on unpolarized nuclear targets. An important aspect is that we only use nuclear and later partonic degrees of freedom, carefully avoiding a picture of the nucleus in terms of nucleons. After establishing that formulae used for individual nucleon targets (p,n), derived in the Operator Product Expansion (OPE) formalism, are indeed applicable to nuclear targets, here we rewrite expressions for nuclear TMCs in terms of re-scaled (or averaged) kinematic variables. As a consequence, we find a representation for nuclear TMCs that is approximately independent of the nuclear target. We go on to construct a single-parameter fit for all nuclear targets that is in good numerical agreement with full computations of TMCs. We discuss in detail qualitative and quantitative differences between nuclear TMCs built in the OPE and the parton model formalisms, as well as give numerical predictions for current and future facilities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Observations and Modeling of Ocean Circulation in the Seychelles Plateau Region

The ocean circulation around and over the Seychelles Plateau is characterized using 35 months of temperature and velocity measurements along with a numerical model. The results here provide the first documented description of the ocean circulation atop the Seychelles Plateau. The Seychelles Plateau is an unusually broad (~200 km), shallow (~50 m) plateau, dropping off steeply to the abyss. It is situated in a dynamic location (3.5-5.5S, 54-57E) in the south-western tropical Indian Ocean where northwesterly winds are present during austral summer and become southeasterly in austral winter, following the reversal of the western Indian Ocean monsoon winds. Measurements around the Inner Islands, on the Seychelles Plateau, have been carried out since 2015. Velocity measurements show that most of the depth-averaged current variance on the Seychelles Plateau arises from near-inertial oscillations and lower-frequency variability. Lower-frequency variability encompasses seasonal and intraseasonal variability, the latter of which includes the effects of mixed Rossby-gravity waves and mesoscale eddies. Here, a global 0.1-degree numerical ocean simulation is used in conjunction with these observations to describe the regional circulation around the Seychelles Plateau. Atop the Seychelles Plateau, circulation is dominated by ageostrophic processes consistent with Ekman dynamics, while around the Seychelles Plateau, both geostrophic and ageostrophic processes are important and vary seasonally. Stratification responds to the sea surface height semi-annual signal which is due to Ekman pumping-driven upwelling (related to the Seychelles-Chagos Thermocline Ridge) and the arrival of an annual downwelling Rossby wave.

58 GEOSCIENCES↗