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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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NASA NTRSDate not supplied

An Orbital Photogeologic Map of the Jezero Crater Rim: Diverse Targets for Mars 2020 Future Exploration.

The Perseverance rover on the Mars 2020 mission is currently collecting samples in Jezero crater for potential future return to Earth by the Mars Sample Return (MSR) mission. Jezero is a 45 km diameter mid- to late-Noachian-aged crater selected for its diverse geology and potential for preserving evidence of ancient life. The rover is approaching the crater rim, an area of interest for its potential to preserve diverse lithologies representative of a large period of geologic history. It has significant astrobiological potential, as it may preserve evidence of uplifted deep crust and ancient hydrothermal environments. Impact megabreccia in the crater rim may be exhumed pre-Noachian crust from the Isidis impact, which would likely be the oldest materials ever investigated by a rover on Mars. Additionally, the rim hosts outcrops of the regionally extensive and potentially volcanic olivine/carbonate unit and mafic capping unit, which could have implications for the evolution of Mars volcanism. Regional maps have delineated the lithologies present in and around Jezero as a whole. The largest scale that the crater rim geology has been mapped is 1:5000.

M C Deahn↗
NASA NTRSDate not supplied

Hourly Stream Heights – A Short-term Deep Learning Prediction Model

River flooding can have a detrimental impact on a community by causing loss of life, loss or damage to property, and damage to infrastructure. Having the capability to forecast flooding events can prevent the loss of life and mitigate damage to property. A programmatic, data-driven approach using deep learning to forecast a stream’s gauge height every 6 hours has been developed by NASA’s Short-term Prediction Research and Transition Center (SPoRT) and is currently in operation. Based on our end user engagement and feedback, this medium-term product has been successfully adopted by several National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC). SPoRT is currently researching and developing a short-term hourly deep learning model which will be useful in forecasting flash flood events.

Michael Antia↗
DOE OSTI2024

Accelerating CO2 Storage Site Characterization through a New Understanding of Favorable Formation Properties and the Impact of Core-Scale Heterogeneities

CO2 sequestration in deep geologic formations can permanently reduce atmospheric CO2 emissions and help to abate climate change. Target formations must undergo a time- and resource-intensive site evaluation process, assessing storage capacity, environmental safety, and suitability for CO2 trapping via reactive transport models based on data from a limited number of core samples. As such, simulations are often simplified and omit heterogeneities in formation properties that may be significant but are not well understood. To facilitate more rapid site assessment, this work first defines the aquifer properties of favorable storage formations through the analysis of promising and active storage sites. Data show quartz is the most prevalent formation mineral with carbonate minerals, highly reactive with injected CO2, present in over 75% of formations. Porosity and permeability data are highly clustered at 10–30% and 10–1000 mD. Field-scale reactive transport simulations are then constructed and used to analyze CO2 trapping efficiency. The models consider porosity and carbonate mineral heterogeneity as well as the impacts of typical temperature gradients. Simulated sequestration efficiencies are compared to results from a comparable homogenous model to understand the implications of aquifer non-uniformities. The results show a lower sequestration efficiency in the homogeneous model during the injection phase. During the post-injection phase, the homogenization of porosity and carbonate mineralogy results in a higher sequestration efficiency. Incorporating the temperature gradient also increases the sequestration efficiency. Importantly, the maximum deviation between the homogeneous and heterogeneous simulations at the end of the 50-year study period is only ~10%. Larger impacts may be incurred for properties outside the defined, promising ranges suggested here.

Environmental Sciences & Ecology↗
NASA NTRS1999

Compaction as the Origin of the Unusual Craters on the Asteroid Mathilde

Asteroid Mathilde has been pummeled by at least five giant impacts (Figure 1). Previous experience with cratering suggests Mathilde's giant craters should each be surrounded by kilometer-deep blankets of ejecta, i.e. material excavated during the impact events. Curiously, there appears to be very little ejecta around Mathilde's craters; they show no evidence of filling by ejecta from adjacent large craters. A previous explanation for the missing ejecta, based on computer simulations, is that Mathilde's unusually high porosity (50 +/- 20%) confines the deposited impact kinetic energy to a localized volume, and produces excavation velocities so high (greater than approximately 20m/s) that nearly all ejecta escape Mathilde's gravitational field. Here we report on laboratory experiments in a highly porous material that give a different explanation. The crater is formed primarily by compaction, not excavation. The small amount of material that is lofted has velocities and ranges so small that nearly all of it is re-deposited within the crater bowl, thereby sparing neighboring craters from ejecta in-filling. This peculiar style of cratering implies that highly porous asteroids are minor contributors of meteorites, because essentially no ejecta escape these asteroids.

Housen, Kevin R.↗
NASA NTRS2013

Arcjet Testing of Micro-Meteoroid Impacted Thermal Protection Materials

There are several harsh space environments that could affect thermal protection systems and in turn pose risks to the atmospheric entry vehicles. These environments include micrometeoroid impact, extreme cold temperatures, and ionizing radiation during deep space cruise, all followed by atmospheric entry heating. To mitigate these risks, different thermal protection material samples were subjected to multiple tests, including hyper velocity impact, cold soak, irradiation, and arcjet testing, at various NASA facilities that simulated these environments. The materials included a variety of honeycomb packed ablative materials as well as carbon-based non-ablative thermal protection systems. The present paper describes the results of the multiple test campaign with a focus on arcjet testing of thermal protection materials. The tests showed promising results for ablative materials. However, the carbon-based non-ablative system presented some concerns regarding the potential risks to an entry vehicle. This study provides valuable information regarding the capability of various thermal protection materials to withstand harsh space environments, which is critical to sample return and planetary entry missions.

Agrawal, Parul↗
NASA NTRSDate not supplied

4.32 Billion Year Old Impact Melts at Apollo 14: Dating the Procellarum Basin?

Introduction: Recent work has improved our understanding of lunar crustal structure and basin evolution on the Moon, but its early impact history and implications for solar system dynamics remain poorly established [1,2]. In particular, there is a derth of absolute ages, especially for the period >4.0 Ga, that could be related to basin-forming events. Here we present U-Pb isotopic data for Zr-rich minerals found in impact-melt fragments from Apollo 14 soil sample 14163 that, when combined with previously published data, dates an impact event at 4324±15 Ma. The compositions and ages of these impact-melt fragments provide unique information about the timing of early impact events and the composition of the lunar crust. Results: Fourteen rocklets ranging in size from 1 to 3 mm were extracted from soil 14163. Most are impactmelt rocks with 10-30% clasts of mostly pyroxene and plagioclase (100 to 500 μm) in a crystalline matrix. Textures of the matrix vary from subophitic, formed by intergrowths of 10-20 μm plagioclase and pyroxene crystals, to poikilitic, with plagioclase and pyroxene reaching 20-50 μm size. Some fragments that contain no visible clasts have similar textures are also interpreted as impact-melt rocks. All fragments contain notably large proportions of euhedral to subhedral ilmenite, zircon, apatite/merrillite and less abundant zirconolite and baddeleyite in the melt matrices. These grains often form intricate intergrowths with each other and rock-forming minerals, indicating their crystallization from the melt (Fig. 1). However, some slightly larger (~50 μm) zircon and phosphate grains can be interpreted as relict clasts based on their granular textures and relationships with the surrounding phases (Fig. 1). This implies that zircon and phosphate minerals were present in the target rocks. Some of these grains were profoundly remelted during the impact, which resulted in an oversaturation of the melt in Zr and P and crystallization of new grains of Zrrich minerals and phosphates during melt solidification. The presence of zircon and phosphates indicates that the melts were significantly enriched in KREEP components and ties their provenance to the Procellarum- KREEP Terrane (PKT) [3]. Combined U-Pb zircon data obtained for all fragments form two main clusters on a concordia diagram (Fig. 2), between about 4.3 and 3.9 Ga. Phosphate data mostly concentrate on the younger end of this age range but some analyses are almost as old as the older zircon grains (Fig. 2). Figure 1: Zircon (Zr) and phosphate (Apt; Mer) grains in impact melt fragments from Apollo 14 soil 14161. A-zircon grains crystallized from impact melt; B-phosphate grain inherited from the target; C- granular zircon grains Our interpretation of these data is that all U-rich minerals experienced variable resetting of the U-Pb system, with phosphate, where closure temperature is significantly lower than that in zircon, affected more profoundly by Pb loss than zircon. Our best estimate of the time of formation of zircon and phosphate is based on statistically valid analysis of grains interpreted texturally as grown from the impact melt (Fig. 2). Ten of these analyses define an age of 4324±15 Ma (MSWD=3.0, probability of fit P=0.002). Our best estimate for the time of resetting is obtained by combining data from phosphates that are statistically indistinguishable from 3.9 Ga within the analytical uncertainties. This group is represented by 18 analyses of 15 phosphate grains from different fragments (Fig. 2) and defines an age of 3922±6 Ma (MSWD=1.2, P=0.23). Conversely, a minimum age of the target lithologies, remelted in the impact that produced the rocklets studied here (Fig. 2), can be determined from the five oldest analyses of zircon clasts at 4338±13 Ma (MSWD=1.5, P=0.2), which is indistinguishable from the age of the impact melt within the uncertainties. The obtained ages, combined with textural evidence, imply that the impact melt was formed at 4324±15 Ma, and that it occurred in a zircon-rich target with a minimum age of 4338±13 Ma. Further reworking occurred during a second impact event at 3922±6 Ma. Discussion: The younger age of 3922±6 Ma can be interpreted as the time of the Imbrium impact. The older age of 4324±15 Ma would then be the time of formation of the impact melt, which was then caught in the Imbrium ejecta either at the Apollo 14 landing site or within the target rocks of the Imbrium impact. The presence of abundant accessory phases such as zircons and phosphates is consistent with a substantial KREEP component in the analyzed particles. The current distribution of KREEP on the lunar surface appears to be strongly influenced by Imbrum ejecta [4] so interpretation of the 4.32 Ga age depends in part on assumed structure of the pre-impact crust and distribution of KREEP within the crust. If KREEP was present only in the deep crust at 4.32 Ga, then a basin-scale impact possibly analogous to Imbrium or larger may be necessary to excavate a KREEPy impact melt at this time. However, if KREEPy materials were present closer to the surface perhaps due to redistribution related to Mg-suite magmatism, then smaller impacts might be able to rework KREEPy compositions at shallower depths. The coherence of the data on the particles analysed here suggests a large volume of melt that has been preserved since 4.32 Ga, consistent with a large impact event. Relict zircons and mineral clasts suggests that the igneous crust in the vicinity of this impact was well developed by at least 4.34 Ga, similar to the model age of KREEP and older than the isochron ages of many Mg-suite cumulates [5]. A problem that confronts all lunar sample studies using the current collection is that the pre-Imbrium geology of the PKT (the source of these 4.32 Ga impact melts) is not well constrained. The South Pole-Aitken basin contains regions that are moderately enriched in Th, but its ejecta is Th-poor [6]; therefore these A14 fragments are probably not SPA ejecta. Alternatively, these fragments may represent formation of a hypothesized Procellarum basin [7] although the lack of a clearly defined basin ejecta signature is a potential problem with that interpretation. In any case, they provide a younger limit on the age of lunar differentiation and formation of KREEP within the lunar crust. Figure 2: U-Pb data for zircon and phosphate grains from impact melt fragments. A-all data; B-data used for age calculations. References: [1] Orgel C., Michael G., Fassett C. I., van der Bogert C. H., Riedel C., Kneissl T., and Hiesinger H. (2018) J. Geophys. Res. Planets 123, 748- 762. [2] Evans A. J., Andrews-Hanna J. C., Head J. W., Soderblom J. M., Solomon S. C., and Zuber M. T. (2018) J. Geophys. Planets. 123, 1596-1617. [3] Jolliff, B.L., Gillis, J.J., Haskin, L.A., Korotev, R.L. and Wieczorek, M.A. (2000) J. Geophys. Res: Planets 105, 4197-4216. [4] Haskin L. A. (1998) J. Geophys. Res. Planets 103, 1679-1689. [5] Borg L.E., Gaffney A.M., and Shearer C.K. (2015) MAPS 50, 715-732. [6] Moriarty, D.P., Watkins, R.N., Valencia, S.N., Kendall, J.D., Evans, A.J., Dygert, N. and Petro, N.E. (2021) J. Geophys. Res. Planets 126. [7] Zhu, M.H., Wünnemann, K., Potter, R.W., Kleine, T. and Morbidelli, A. (2019) J. Geophys. Res: Planets 124, 2117-2140

M D Norman↗
NASA NTRS1994

Mirages and the nature of Pluto's atmosphere

We present model occultation lightcurves demonstrating that a strong thermal inversion layer at the base of Pluto's stratosphere can reproduce the minimum flux measured by the Kuiper Airborne Observatory (KAO) during the 1988 occultation of a star by Pluto. The inversion layer also forms the occultation equivalent of a mirage at a radius of 1198 km, which is capable of hiding tropospheres of significant depth. Pluto's surface lies below 1198 km, its radius depending on the depth of the troposphere. We begin by computing plausible temperature structures for Pluto's lower atmosphere, constrained by a calculation of the temperature of the atmosphere near the surface. We then trace rays from the occulted star through the model atmosphere, computing the resultant bending of the ray. Model light curves are obtained by summing the contribution of individual rays within the shadow of Pluto on Earth. We find that we can reproduce the KAO lightcurve using model atmospheres with a temperature inversion and no haze. We have explored models with tropospheres as deep as 40 km (implying a Pluto radius of 1158 km) that reproduce the suite of occultation data. Deeper tropospheres can be fitted to the data, but the mutual event radius of 1150 km probably provides a lower bound. If Pluto has a shallow or nonexistent troposphere, its density is consistent with formation in the solar nebula with modest water loss due to impact ejection. If the troposhere is relatively deep, implying a smaller radius and larger density, significant amounts of water loss are required.

Stansberry, J. A.↗
NASA NTRS2004

Numerical Modeling of the South Pole-Aitkin Impact

The South Pole-Aitkin (SPA) basin, on the far side of the Moon, is the largest and oldest impact structure still preserved in the solar system. The crater is about 2500 km in diameter and formed in the Pre-Nectarian era of lunar history, over 4 Gyr ago. At this time, the thermal state of the Moon was much hotter than it is today. Accretional energy from the rapidly forming Moon melted the outermost few hundred kilometers of the Moon. As this magma ocean differentiated and cooled a 60 100-km thick low-density crust formed at the surface; below this the residual melt, with a higher density, cooled to form the lunar mantle. The giant SPA impact event punctured the Moon some time during the cooling of the magma ocean and thus provides a unique window for studying the lunar interior and the early formative processes of the Moon. The impact excavated otherwise inaccessible samples of the deep crust and (possibly) upper mantle, which has inspired proposed sample return missions. Furthermore, the thermal and rheologic state of the early Moon played a role in shaping the final structure of the basin. To aid in site selection for future sample return missions to the SPA basin, and to investigate the effect of thermal state on final crater structure, we performed some numerical simulations of the SPA impact event.

Collins, G. S.↗
NASA NTRS2017

Detection of Hail Storms in Radar Imagery Using Deep Learning

In 2016, hail was responsible for 3.5 billion and 23 million dollars in damage to property and crops, respectively, making it the second costliest weather phenomenon in the United States. In an effort to improve hail-prediction techniques and reduce the societal impacts associated with hail storms, we propose a deep learning technique that leverages radar imagery for automatic detection of hail storms. The technique is applied to radar imagery from 2011 to 2016 for the contiguous United States and achieved a precision of 0.848. Hail storms are primarily detected through the visual interpretation of radar imagery (Mrozet al., 2017). With radars providing data every two minutes, the detection of hail storms has become a big data task. As a result, scientists have turned to neural networks that employ computer vision to identify hail-bearing storms (Marzbanet al., 2001). In this study, we propose a deep Convolutional Neural Network (ConvNet) to understand the spatial features and patterns of radar echoes for detecting hailstorms.

natural hazard↗
DOE OSTI2022

Large-Eddy Simulations of Convection Initiation over Heterogeneous, Low Terrain

Abstract Large-eddy simulations are conducted to investigate and physically interpret the impacts of heterogeneous, low terrain on deep-convection initiation (CI). The simulations are based on a case of shallow-to-deep convective transition over the Amazon River basin, and use idealized terrains with varying levels of ruggedness. The terrain is designed by specifying its power-spectral shape in wavenumber space, inverting to physical space assuming random phases for all wave modes, and scaling the terrain to have a peak height of 200 m. For the case in question, these modest terrain fields expedite CI by up to 2–3 h, largely due to the impacts of the terrain on the size of, and subcloud support for, incipient cumuli. Terrain-induced circulations enhance subcloud kinetic energy on the mesoscale, which is realized as wider and longer-lived subcloud circulations. When the updraft branches of these circulations breach the level of free convection, they initiate wider and more persistent cumuli that subsequently undergo less entrainment-induced cloud dilution and detrainment-induced mass loss. As a result, the clouds become more vigorous and penetrate deeper into the troposphere. Larger-scale terrains are more effective than smaller-scale terrains in promoting CI because they induce larger enhancements in both the width and the persistence of subcloud updrafts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

The Stardust Mission

The primary goal of the Stardust Mission is to collect >1000 particles >15 micron in diameter from comet Wild2 and return them to Earth in January 2006. The main samples will be captured by 6.1 km/s impact into low density silica aerogel and additional particles will crater into approx. 150 sq cm of 100 micron thick pure aluminum foil that covers the aerogel holding grid. It is expected that the impacts into the aerogel will produce tracks that range from deep narrow cones for non-fragmenting particles to shallower more complex tracks for particles that fragment. The impacts into aluminum foil will produce craters but a significant amount of projectile residue is expected to line the crater walls.

Brownlee, D. E.↗
NASA NTRS2017

Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

atmospheric dust↗
DOE OSTI2022

Impact of heavy-quark production measurements in the CT18 global QCD analysis of PDFs

We discuss the impact of heavy-flavor production measurements in semi-inclusive deep inelastic scattering at HERA on the CTEQ-TEA PDFs. In particular, we study the impact of the latest charm and bottom production measurements from the H1 and ZEUS collaborations on the gluon, and the interplay of these measurements with the data ensemble of the recent CT18 global QCD analysis.

Guzzi, Marco↗
NASA NTRS2013

Radiation Engineering Analysis of Shielding Materials to Assess Their Ability to Protect Astronauts in Deep Space From Energetic Particle Radiation

An analysis is performed on four typical materials (aluminum, liquid hydrogen, polyethylene, and water) to assess their impact on the length of time an astronaut can stay in deep space and not exceed a design basis radiation exposure of 150 mSv. A large number of heavy lift launches of pure shielding mass are needed to enable long duration, deep space missions to keep astronauts at or below the exposure value with shielding provided by the vehicle. Therefore, vehicle mass using the assumptions in the paper cannot be the sole shielding mechanism for long duration, deep space missions. As an example, to enable the Mars Design Reference Mission 5.0 with a 400 day transit to and from Mars, not including the 500 day stay on the surface, a minimum of 24 heavy lift launches of polyethylene at 89,375 lbm (40.54 tonnes) each are needed for the 1977 galactic cosmic ray environment. With the assumptions used in this paper, a single heavy lift launch of water or polyethylene can protect astronauts for a 130 day mission before exceeding the exposure value. Liquid hydrogen can only protect the astronauts for 160 days. Even a single launch of pure shielding material cannot protect an astronaut in deep space for more than 180 days using the assumptions adopted in the analysis. It is shown that liquid hydrogen is not the best shielding material for the same mass as polyethylene for missions that last longer than 225 days.

Singleterry, R. C.↗
NASA NTRS2017

Results of Simulated Galactic Cosmic Radiation (GCR) and Solar Particle Events (SPE) on Spectra Restraint Fabric

Spectra or similar Ultra-high-molecular-weight polyethylene (UHMWPE) fabric is the likely choice for future structural space suit restraint materials due to its high strength-to-weight ratio, abrasion resistance, and dimensional stability. During long duration space missions, space suits will be subjected to significant amounts of high-energy radiation from several different sources. To insure that pressure garment designs properly account for effects of radiation, it is important to characterize the mechanical changes to structural materials after they have been irradiated. White Sands Test Facility (WSFTF) collaborated with the Crew and Thermal Systems Division at the Johnson Space Center (JSC) to irradiate and test various space suit materials by examining their tensile properties through blunt probe puncture testing and single fiber tensile testing after the materials had been dosed at various levels of simulated GCR and SPE Iron and Proton beams at Brookhaven National Laboratories. The dosages were chosen based on a simulation developed by the Structural Engineering Division at JSC for the expected radiation dosages seen by space suit softgoods seen on a Mars reference mission. Spectra fabric tested in the effort saw equivalent dosages at 2x, 10x, and 20x the predicted dose as well as a simulated 50 year exposure to examine the range of effects on the material and examine whether any degradation due to GCR would be present if the suit softgoods were stored in deep space for a long period of time. This paper presents the results of this work and outlines the impact on space suit pressure garment design for long duration deep space missions.

Peters, Benjamin↗
DOE OSTI2026

Marine Aerosol to Refinery Emissions: Transport and Evolution of CCN in the Houston Metropolitan Area and Their Impact on Cloud Formation

The Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) campaign aimed to untangle the impacts of contrasting aerosol sources on cloud microphysical properties within deep convective cells using airborne observations with the National Research Council Canada (NRC) Convair CV‐580 research aircraft. Horizontal and vertical gradients of aerosol number size distributions, total aerosol concentrations and cloud condensation nuclei (CCN) spectra were measured in the lower troposphere to quantify the impact of different aerosol sources on aerosol‐cloud interactions. This study focuses on a research flight dedicated to characterizing the aerosol and CCN properties in the Houston Metropolitan region and identifies five main categories of aerosols based on characteristics of aerosol number size distributions, their CCN properties and meteorological conditions. These categories encompassed more than two orders of magnitude differences in aerosol and CCN concentrations, yet their hygroscopic properties remained similar. Aerosol number size distributions and effective hygroscopicity parameters are used to generate continuous CCN spectra to represent the major aerosol types. The different CCN spectra are then incorporated into a 1‐D aerosol‐cloud parcel model using a large range of updrafts selected in the range of those observed during the ESCAPE campaign to assess the impact of the major aerosol sources in Houston on deep convective cloud microphysical properties.

aerosol-cloud interactions↗
NASA NTRSDate not supplied

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗
DOE OSTI2023

Construction of deep-learning based WWBs parameterization for ENSO prediction

Westerly wind bursts (WWBs) significantly impact the occurrence and development of the El Niño-Southern Oscillation (ENSO). Current dynamical models, however, face significant challenges in representing WWBs. In this study, deep learning techniques were used to develop a new parameterization scheme for WWBs and further compared against two widely used schemes. Further, the results show that the scheme developed in this study has greater capability than previous schemes in reproducing WWBs characteristics, particularly in terms of occurrence probability, location, and duration. This improvement was mainly reflected in El Niño years, especially in strong events when the deep-learning-based scheme much realistically captures the location and strength of WWBs. It is expected that the new parameterization scheme will further improve ENSO prediction in dynamical models.

54 ENVIRONMENTAL SCIENCES↗