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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 OSTI2023

Spatio–Temporal Coarse–Graining Decomposition of the Global Ocean Geostrophic Kinetic Energy

We expand on a recent determination of the first global energy spectrum of the ocean’s surface geostrophic circulation using a coarse-graining (CG) method. We compare spectra from CG to those from spherical harmonics by treating land in a manner consistent with the boundary conditions. While the two methods yield qualitatively consistent domain-averaged results, spherical harmonics spectra are too noisy at gyre-scales (> 1000 km). More importantly, spherical harmonics are inherently global and cannot provide local information connecting scales with currents geographically. CG shows that the extra-tropics mesoscales (100–500 km) have a root-mean-square (rms) velocity of ~15 cm/s, which increases to ~30–40 cm/s locally in the Gulf Stream and Kuroshio and to ~16–28 cm/s in the ACC. There is notable hemispheric asymmetry in mesoscale energy-per-area, which is higher in the north due to continental boundaries. We estimate that ≈25–50% of total geostrophic energy is at scales smaller than 100 km, and is un(der)-resolved by pre-SWOT satellite products. Spectra of the time-mean circulation show that most of its energy (up to 70%) resides in stationary eddies with characteristic scales smaller than (< 500 km). This highlights the preponderance of ‘standing’ small-scale structures in the global ocean due to the temporally coherent forcing by boundaries. By coarse-graining in space and time, we compute the first spatio-temporal global spectrum of geostrophic circulation from AVISO and NEMO. These spectra show that every length-scale evolves over a wide range of time-scales with a consistent peak at ≈200 km and ≈2–3 weeks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Geostrophic to magnetically-damped turbulence in liquid metal rotating magnetoconvection

Understanding planetary core convection dynamics requires the study of convective flows in which the Coriolis and Lorentz forces attain a leading-order, so-called magnetostrophic balance. Experimental investigations of rotating magnetoconvection (RMC) in the magnetostrophic regime are therefore essential to broadly characterize the properties of local-scale planetary core flow. Toward this end, we present here the first thermovelocimetric measurements of magnetostrophic, liquid metal convection, which are made using liquid gallium as the working fluid, at moderate rotation rates (Ekman numbers 10 -4 ≤ Ek ≤ 10 -5 ) and in the presence of dynamically strong magnetic fields (Elsasser number Λ = 1). Complementary rotating convection (RC) experiments are performed at the same rotation rates to serve as reference cases. Our RMC velocity measurements adequately follow a geostrophic turbulent scaling for cases in which local-scale convective inertial forces exceed the Lorentz forces in the fluid bulk. In cases where Lorentz forces exceed local-scale inertia (local or convective interaction parameter N ℓ or N C ≳ 3), the root-mean-square RMC velocities are magnetically damped, yielding values below the geostrophic turbulent RC scaling prediction. An enhancement in heat transfer is observed, which we attribute to the increased coherence of vertically aligned magnetostrophic convective flow. Finally, our results and comparisons to dynamo simulations suggest that the system is in the strong-field regime, where convection-scale flows are magnetically damped with N C ≳ 3).

Convective turbulence↗
DOE OSTI2020

Turbulent exchanges between near-inertial waves and balanced flows

Wind generated near-inertial waves are ubiquitous in the upper ocean. An improved understanding of near-inertial wave dynamics following their excitation in the ocean and their subsequent interaction with mesoscale geostrophic balanced flows is key to decoding oceanic energy flow pathways. In this regard, multiple oceanic data sets accumulated over the past few decades reveal that the relative strength of near-inertial waves and geostrophic balanced eddy fields is highly variable, both geographically and seasonally. Inspired by these observations, we investigate turbulent interactions and energy exchanges between near-inertial waves and balanced flows using freely evolving numerical simulations of the non-hydrostatic Boussinesq equations. Here, we find accelerated vertical propagation and dissipation of the waves in regimes where balanced and wave fields have comparable strengths. In such regimes we also find that near-inertial waves directly extract energy from balanced flows, with O(10%) being the amount of balanced energy loss. In contrast, we find that near-inertial waves transfer energy to balanced flows in regimes where balance-to-wave energy ratio is small, with the gain in balanced energy being dependent on the relative strength of waves. Furthermore, these regimes are characterized by relatively weaker vertical propagation and dissipation of the near-inertial wave field. One of the key outcomes of this study is the demonstration of the lack of a unique direction for near-inertial wave-balanced flow energy transfers. Depending on the balance-to-wave energy ratio, near-inertial waves can act as an energy sink or energy source for the geostrophic balanced flow.

58 GEOSCIENCES↗
DOE OSTI2025

Oceanic mixing and waves in the presence of a suspended canopy

Large-eddy simulations are analysed to determine the influence of suspended canopies, such as those formed in macroalgal farms, on ocean mixed layer (OML) deepening and internal wave generation. In the absence of a canopy, we show that Langmuir turbulence, when compared with wind-driven shear turbulence, results in a deeper OML and more pronounced internal waves beneath the OML. Subsequently, we examine simulations with suspended canopies of varying densities located in the OML, in the presence of a background geostrophic current. Intensified turbulence occurs in the shear layer at the canopy’s bottom edge, arising from the interaction between the geostrophic current and canopy drag. Structures resembling Kelvin–Helmholtz (KH) instability emerge as the canopy shear layer interacts with the underlying stratification, radiating internal waves beneath the OML. Both intensified turbulence and lower-frequency motions associated with KH-type structures are critical factors in enhancing mixing. Consequently, the OML depth increases by up to a factor of two compared with cases without a canopy. Denser canopies and stronger geostrophic currents lead to more pronounced KH-type structures and internal waves, stronger turbulence and greater OML deepening. Additionally, vertical nutrient transport is enhanced as the OML deepens due to the presence of the canopy. Considering that the canopy density investigated in this study closely represents offshore macroalgal farms, these findings suggest a mechanism for passive nutrient entrainment conducive to sustainable farming. Overall, this study reveals the intricate interactions between the suspended canopy, turbulent mixing and stratification, underscoring their importance in reshaping OML characteristics.

Bo, Tong (ORCID:0000000260300561)↗
DOE OSTI2020

Big-Data-Driven Geo-Spatiotemporal Correlation Analysis between Precursor Pollen and Influenza and its Implication to Novel Coronavirus Outbreak

Although studies of many respiratory viruses and pollens are often framed by both seasonal and health related perspectives, pollen has yet to be extensively examined as an important covariate to seasonal respiratory viruses (SRVs) in any context, including a causal one. This study contributes to those goals through an investigation of SRVs and pollen counts at selected regions across the Western Hemisphere. Two complementary decadal-scaled geospatial profiles were developed. One laterally spanned the US and was anchored by detailed pollen information for Albuquerque, New Mexico. The other straddled the equator to include Fortaleza, Brazil. We found that the geospatial and climatological patterns of pollen advancement and decline across the US every year presented a statistically significant correlation to the subsequent emergence and decline of SRVs. Other significant covariates included winds, temperatures, and atmospheric moisture. Our study indicates that areas of the US with lower geostrophic wind baselines are typically areas of persistently higher and earlier influenza like illness (ILI) cases. In addition to that continental- scaled contrast, many sites indicated seasonal highs of geostrophic winds and ILI which were closely aligned. These observations suggest extensive scale-dependent connectivity of viruses to geostrophic circulation. Pollen emergence and its own scale-dependent circulation may contribute to the geospatial and seasonal patterns of ILI. We explore some uncertainties associated with this investigation, and consider the possibility that in a temperate climate, following a Spring pollen emergence, a resulting increase in pollen triggered human Immunoglobulin E (IgE) antibodies may suppress ILIs for several months.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Seasonal variation of the surface cross-shelf exchange in the northern South China Sea: a Lagrangian perspective

Previous studies on cross-shelf exchange, predominantly adopted an Eulerian perspective, struggled to identify water sources and pathways. Using a high-resolution regional ocean modeling system (ROMS) and Lagrangian particle tracking, this study systematically investigates the seasonal variation and dynamics of surface cross-shelf exchange in the northern South China Sea (NSCS) from a Lagrangian perspective. Based on daily released 30-day drifter trajectories we identify the key pathways, source regions for surface cross-shelf exchange, revealing pronounced seasonal variability. Results show the surface cross-shelf exchange generally following monsoon-driven Ekman transport. However, local dynamics, especially topographic modulation, can outweigh the expected Ekman-driven transport, producing surface exchange patterns opposite to that predicted from the prevailing winds. Topographic effects vary across different scales. In the coastal waters of western Guangdong during winter, despite downwelling-favorable winds, the modulation of alongshore currents by island topography induces an eastward pressure gradient. This gradient, through geostrophic balance, drives offshore flows opposite to wind-driven Ekman onshore transport. Furthermore, the eastern widened shelf exhibits a distinct seasonal variation of cross-shelf exchange, with strong offshore transport (opposite to the direction of Ekman transport) in winter and exceedingly weak exchange in summer. Analysis of the underlying mechanisms reveals that this winter offshore transport is primarily attributed to geostrophic flows driven by surface pressure gradient that is jointly modulated by the Kuroshio intrusion and local widened shelf topography, and enhanced by cumulative submesoscale processes. In summer, a persistent and strong along-isobath jet acts as a dynamic barrier, effectively suppressing the exchange. These findings highlight the important role of topography in regulating surface material transport, and have important implications for predicting the advection and dispersion of plankton or oil spills over the continental shelf influenced by monsoon.

Hao, Dongliang↗
DOE OSTI2021

Sea Surface Salinity Reemergence in an Updated North Atlantic In Situ Salinity Dataset

Monthly sea surface salinity (SSS) fields are constructed from observations, using objective mapping on a 1° x 1° grid in the Atlantic between 30°S and 50°N in the 1970-2016 period in an update of the dataset of Reverdin et al. Data coverage is heterogeneous, with increased density in 2002 when Argo floats become available, high density along Voluntary Observing Ship lines, and low density south of 10°S. Using lag correlation, the seasonal reemergence of SSS anomalies is investigated between 20° and 50°N in 5° x 5° boxes during the 1993-2016 period, both locally and remotely following the displacements of the deep mixed-layer waters estimated from virtual float trajectories derived from the daily AVISO surface geostrophic currents. Although SSS data are noisy, local SSS reemergence is detected in about half of the boxes, notably in the northeast and southeast, while little reemergence is seen in the central and part of the eastern subtropical gyre. In the same period, sea surface temperature (SST) reemergence is found only slightly more frequently, reflecting the short data duration. However, taking geostrophic advection into account degrades the detection of remote SSS and even SST reemergence. When anomalies are averaged over broader areas, robust evidence of a second and third SSS reemergence peak is found in the northeastern and southeastern parts of the domain, indicating long cold-season persistence of large-scale SSS anomalies, while only a first SST reemergence is seen. Finally, an oceanic reanalysis is used to confirm that the correlation analysis indeed reflects the reemergence of subsurface salinity anomalies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Characterizing Spatial and Temporal Variability of California’s Coastal Upwelling Using a Satellite-Derived CUTI Index

Ocean upwelling off California is a wind-driven coastal process with complex interactions between spatial wind patterns and sea surface temperatures. Large-scale spatial and temporal upwelling characterizations are traditionally based on numerical models, while quantifying upwelling with direct observations is not straightforward. To complement model-based upwelling characterizations, here we use satellite estimates of winds, sea surface temperatures, and ocean currents along the California coast to calculate the coastal upwelling transport index (CUTI), originally calculated from a numerical ocean model. The CUTI framework accounts for both Ekman and geostrophic offshore-directed ocean transport, the latter of which is often neglected in satellite-based upwelling assessments. The approach yields the CUTI over a 30-yr period at a daily temporal and 0.25° spatial resolution to analyze upwelling patterns, with focus on potential Morro Bay and Humboldt wind energy areas. Morro Bay (CUTI median of 0.63 m 2 s −1 ) exhibits stronger, more consistent upwelling throughout the year, whereas Humboldt (CUTI median of 0.45 m 2 s −1 ) exhibits a pronounced seasonal cycle with strongest upwelling in the summer and occasional downwelling in winter. The cluster analysis of 1993–2022 satellite maps of CUTI identifies four characteristic spatial upwelling patterns along the coast, corresponding to distinct spatial distributions of sea surface temperature anomalies, Ekman transport, and geostrophic ocean water transport. This dataset provides an observation-based foundation for characterizing natural coastal upwelling off the California coast, showing good agreement with the original model CUTI while being based on satellite data and offering increased spatial resolution.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Environmental sensitivities of shallow-cumulus dilution – Part 2: Vertical wind profile

This second part of a numerical study on shallow-cumulus dilution focuses on the sensitivity of cloud dilution to changes in the vertical wind profile. Insights are obtained through large-eddy simulations of maritime and continental cloud fields. In these simulations, the speed of the initially uniform geostrophic wind and the strength of geostrophic vertical wind shear in the cloud and subcloud layer are varied. Increases in the cloud-layer vertical wind shear (up to 9 ms -1 km -1 ) lead to 40%–50% larger cloud-core dilution rates compared to their respective unsheared counterparts. When the background wind speed, on the other hand, is enhanced by up to 10 ms -1 and subcloud-layer vertical wind shear develops or is initially prescribed, the dilution rate decreases by up to 25%. The sensitivities of the dilution rate are linked to the updraft strength and the properties of the entrained air. Increases in the wind speed or vertical wind shear result in lower vertical velocities across all sets of experiments with stronger reductions in the cloud-layer wind shear simulation (27%–47%). Weaker updrafts are exposed to mixing with the drier surrounding air for a longer time period, allowing more entrainment to occur (i.e., the “core-exposure effect”). However, reduced vertical velocities, in concert with increased cloud-layer turbulence, also assist in widening the humid shell surrounding the cloud cores, leading to entrainment of more humid air (i.e., the “core–shell dilution effect”). In the experiments with cloud-layer vertical wind shear, the core-exposure effect dominates and the cloud-core dilution increases with increasing shear. Conversely, when the wind speed is increased and subcloud-layer vertical wind shear develops or is imposed, the core–shell dilution effect dominates to induce a buffering effect. The sensitivities are generally stronger in the maritime simulations, where weaker sensible heat fluxes lead to narrower, more tilted, and, therefore, more suppressed cumuli when cloud-layer shear is imposed. Moreover, in the experiments with subcloud wind shear, the weaker baseline turbulence in the maritime case allows for a larger turbulence enhancement, resulting in a widening of the transition zones between the cores and their environment, leading to the entrainment of more humid air.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Robustness of the Ensemble Score Filter to the Type of Assimilated Observation Networks

Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it remains unclear how the performance of these advanced methods depends on the observation network characteristics. In this study, we present initial experiments with the surface quasi‐geostrophic model, in which we compare a recently developed ensemble filter using score‐based diffusion models with the standard Local Ensemble Transform Kalman Filter (LETKF). Our results show that the analysis solutions respond differently to the number, spatial distribution, and nonlinear fraction of assimilated observations. We also find notable changes in the multiscale characteristics of the analysis errors. Given that standard DA techniques will eventually be replaced by more advanced methods, we hope this study sets the ground for future efforts to reassess the value of Earth observing systems in the context of newly emerging algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Conservative Numerical Schemes with Optimal Dispersive Wave Relations: Part II. Numerical Evaluations

A new energy and enstrophy conserving scheme (EEC) for the shallow water equations is proposed and evaluated using a suite of test cases over the global spherical or bounded domain. The evaluation is organized around a set of pre-defined properties: accuracy of individual operators, accuracy of the whole scheme, conservation of key quantities, control of the divergence variable, representation of the energy and enstrophy spectra, and simulation of nonlinear dynamics. The results confirm that the scheme is between the first and second order accurate, and conserves the total energy and potential enstrophy up to the time truncation errors. Here, the scheme is capable of producing more physically realistic energy and enstrophy spectra, indicating that it can help prevent the unphysical energy cascade towards the finest resolvable scales. With an optimal representation of the dispersive wave relations, the scheme is able to keep the flow close to being non-divergent, and maintain the geostrophically balanced structures with large-scale geophysical flows over long-term simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Operator inference with roll outs for learning reduced models from scarce and low-quality data

Data-driven modeling has become a key building block in computational science and engineering. However, data that are available in science and engineering are typically scarce, often polluted with noise and affected by measurement errors and other perturbations, which makes learning the dynamics of systems challenging. Here, in this work, we propose to combine data-driven modeling via operator inference with the dynamic training via roll outs of neural ordinary differential equations. Operator inference with roll outs inherits interpretability, scalability, and structure preservation of traditional operator inference while leveraging the dynamic training via roll outs over multiple time steps to increase stability and robustness for learning from low-quality and noisy data. Numerical experiments with data describing shallow water waves and surface quasi-geostrophic dynamics demonstrate that operator inference with roll outs provides predictive models from training trajectories even if data are sampled sparsely in time and polluted with noise of up to 10%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Data-driven variational multiscale reduced order models

We propose a new data-driven reduced order model (ROM) framework that centers around the hierarchical structure of the variational multiscale (VMS) methodology and utilizes data to increase the ROM accuracy at a modest computational cost. The VMS methodology is a natural fit for the hierarchical structure of the ROM basis: In the first step, we use the ROM projection to separate the scales into three categories: (i) resolved large scales, (ii) resolved small scales, and (iii) unresolved scales. In the second step, we explicitly identify the VMS–ROM closure terms, i.e., the terms representing the interactions among the three types of scales. In the third step, we use available data to model the VMS–ROM closure terms. Thus, instead of phenomenological models used in VMS for standard numerical discretizations (e.g., eddy viscosity models), we utilize available data to construct new structural VMS–ROM closure models. Specifically, we build ROM operators (vectors, matrices, and tensors) that are closest to the true ROM closure terms evaluated with the available data. We test the new data-driven VMS–ROM in the numerical simulation of four test cases: (i) the 1D Burgers equation with viscosity coefficient v = 10 -3 ; (ii) a 2D flow past a circular cylinder at Reynolds numbers, Re = 100, Re = 500, and Re= 1000; (iii) the quasi-geostrophic equations at Reynolds number Re = 450 and Rossby number Ro = 0.0036; and (iv) a 2D flow over a backward facing step at Reynolds number Re = 1000. The numerical results show that the data-driven VMS–ROM is significantly more accurate than standard ROMs.

42 ENGINEERING↗
DOE OSTI2024

Ensemble variational Fokker-Planck methods for data assimilation

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Itˆo process. This work introduces the Variational Fokker-Planck (VFP) framework for data assimilation, a general approach that includes previously known particle flow filters as special cases. The McKean-Vlasov-Itˆo process that transforms particles is defined via an optimal drift that depends on the selected diffusion term. It is established that the underlying probability density - sampled by the ensemble of particles - converges to the Bayesian posterior probability density. For a finite number of particles the optimal drift contains a regularization term that nudges particles toward becoming independent random variables. Based on this analysis, we derive computationally-feasible approximate regularization approaches that penalize the mutual information between pairs of particles, and avoid particle collapse. Moreover, the diffusion plays a role akin to a particle rejuvenation approach that aims to alleviate particle collapse. The VFP framework is very flexible. Different assumptions on prior and intermediate probability distributions can be used to implement the optimal drift, and localization and covariance shrinkage can be applied to alleviate the curse of dimensionality. A robust implicit-explicit method is discussed for the efficient integration of stiff McKean- Vlasov-Itˆo processes. Here, the effectiveness of the VFP framework is demonstrated on three progressively more challenging test problems, namely the Lorenz ’63, Lorenz ’96 and the quasi-geostrophic equations.

97 MATHEMATICS AND COMPUTING↗
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↗
DOE OSTI2020

Assessing Historical Variability of South Asian Monsoon Lows and Depressions With an Optimized Tracking Algorithm

Abstract Cyclonic low‐pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS and uses it to assess interannual variability and trends in reanalyses. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS data set while minimizing disagreement between four reanalyses in a training period. The stream function of 850 hPa horizontal wind is found to be optimal in this sense; it is less noisy than vorticity and represents the complete nondivergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55‐year Reanalysis (JRA‐55) and the IMD data set show a step‐like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982, respectively; the 1958–2018 linear trend in JRA‐55, however, is smaller than in the IMD data set, and its error bar includes 0. There are more LPS in seasons with above‐average monsoon rainfall and in La Niña years, but few other large‐scale modes of interannual variability are found to modulate LPS counts, lifetimes, or track length consistently across reanalyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Upper-Tropospheric Troughs and North American Monsoon Rainfall in a Long-Term Track Dataset

The North American monsoon is frequently affected by transient, propagating upper tropospheric vorticity anomalies. Sometimes called Tropical Upper-Tropospheric Troughs (TUTTs), these features have been claimed to episodically enhance monsoon rainfall. Here, we track long-lived TUTTs in 40 years of reanalysis data, producing composites and case studies from 340 TUTTs which last, on average, 7 days as they move westward across the North American monsoon region. TUTTs are thought to form from midlatitude Rossby wave breaking; case studies from our dataset support this theory. TUTTs move westward within the easterly upper-level flow in which they are embedded. In vortex-centered composites along the full tracks of long-lived TUTTs, here, we find no detectable increase in rainfall within the main TUTT circulation. Instead, negative precipitation anomalies lie within about 500 km of the TUTT center. Quasi-geostrophic ascent occurs in the southeast quadrant of TUTTs but is confined to the upper troposphere and does not appear to interact with precipitation. Positive anomalies of ascent and rainfall occur south and southeast of TUTTs but lie outside the main TUTT vortex, perhaps indicating concurrent variations in nearby climatological precipitation maxima. In contrast with previous case studies and subjective analyses that showed TUTTs enhance precipitation in parts of northwestern Mexico, our composites along the tracks of long-lived TUTTs portray these systems, to first order, as strong vorticity anomalies trapped in the upper troposphere that interact only weakly and indirectly with precipitation.

54 ENVIRONMENTAL SCIENCES↗