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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Future Projection of Tropical Upper-Tropospheric Troughs and Implications for Tropical Cyclone Activity

Summertime tropical upper-tropospheric troughs (TUTTs) provide a unified framework to better understand how extratropical and tropical forcings jointly modulate basin-scale tropical cyclone (TC) activity. In this study, we examine future changes in TUTTs and their implications for TC activity. Multimodel ensemble-mean projections from 45 Coupled Model Intercomparison Project phase 6 (CMIP6) models suggest a contraction of the Pacific TUTT and an expansion of the Atlantic TUTT as the climate warms. Consistently, future changes in environment-based TC indices indicate that the large-scale conditions will become more favorable for TC genesis and intensification over the central North Pacific but less favorable over the tropical North Atlantic and Gulf of Mexico. Utilizing a TC-permitting large-ensemble dataset [i.e., the Database for Policy Decision-Making for Future Climate Change (d4PDF)] that adequately captures the observed interannual TUTT–TC relationships, we further confirm the impacts of projected TUTT changes on the TC activity in a warmer climate. In contrast, the TUTT–TC relationship is poorly represented in most CMIP6 High-Resolution Model Intercomparison Project (HighResMIP) models; such deficiencies call for caution when assessing future TC risk based on explicitly tracked TCs in these models. Additionally, CMIP6 projections show large intermodel spread in TUTT changes, implying uncertainty in projected TC activity, especially over the central-to-eastern Pacific and the North Atlantic. This intermodel spread is associated with interhemispheric sea surface temperature warming asymmetry, which leads to a meridional shift of the intertropical convergence zone (ITCZ) and the simultaneous weakening or strengthening of TUTTs in the North Pacific and North Atlantic. The potential contributions of anthropogenic aerosol forcing and oceanic circulation to this interhemispheric warming asymmetry are briefly examined.

Climate Change↗
DOE OSTI2020

Assessing Tropical Cyclones’ Contribution to Precipitation over the Eastern United States and Sensitivity to the Variable-Resolution Domain Extent

Tropical cyclones (TCs) can subject an area to heavy precipitation for many hours, or even days, worsening the risk of flooding, which creates dangerous conditions for residents of the U.S. East and Gulf Coasts. To study the representation of TC-related precipitation over the eastern United States in current-generation global climate models, a novel analysis methodology is developed to track TCs and extract their associated precipitation using an estimate of their dynamical outer size. This methodology is applied to three variable-resolution (VR) configurations of the Community Atmosphere Model, version 5 (CAM5), with high-resolution domains over the North Atlantic and one low-resolution conventional configuration, as well as to a combination of reanalysis and observational precipitation data. Metrics and diagnostics such as TC counts, intensities, outer storm sizes, and annual mean total and extreme precipitation are compared between the CAM5 simulations and reanalysis/observations. The high-resolution VR configurations outperform the global low-resolution configuration for all variables in the North Atlantic. Realistic TC intensities are produced by the VR configurations. The total North Atlantic TC counts are lower than observations but better than reanalysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep Learning Experiments for Tropical Cyclone Intensity Forecasts

Reducing tropical cyclone (TC) intensity forecast errors is a challenging task that has interested the operational forecasting and research community for decades. To address this, we developed a deep learning (DL)-based multilayer perceptron (MLP) TC intensity prediction model. The model was trained using the global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to forecast the change in TC maximum wind speed for the Atlantic basin. In the first experiment, a 24-h forecast period was considered. To overcome sample size limitations, we adopted a leave one year out (LOYO) testing scheme, where a model is trained using data from all years except one and then evaluated on the year that is left out. When tested on 2010–18 operational data using the LOYO scheme, the MLP outperformed other statistical–dynamical models by 9%–20%. Additional independent tests in 2019 and 2020 were conducted to simulate real-time operational forecasts, where the MLP model again outperformed the statistical–dynamical models by 5%–22% and achieved comparable results as HWFI. The MLP model also correctly predicted more rapid intensification events than all the four operational TC intensity models compared. In the second experiment, we developed a lightweight MLP for 6-h intensity predictions. When coupled with a synthetic TC track model, the lightweight MLP generated realistic TC intensity distribution in the Atlantic basin. Therefore, the MLP-based approach has the potential to improve operational TC intensity forecasts, and will also be a viable option for generating synthetic TCs for climate studies.

58 GEOSCIENCES↗
DOE OSTI2022

Characterizing Long Island’s Extreme Precipitation and Its Relationship to Tropical Cyclones

Since extreme precipitation impacts society on small scales (i.e., a few kilometers and smaller, it is worthwhile to explore extreme precipitation trends in localized regions, such as Long Island (LI), New York. Its coastal location makes it vulnerable to various extreme events, such as tropical cyclones (TCs). This work aimed to quantify the extreme precipitation events on LI that are caused by TCs, as well as the percentage of TCs passing close to LI that cause extreme precipitation events. Both gauge-based and satellite-based precipitation datasets of varying resolutions (DAYMET, IMERG, and CPC) were used to understand the impact of dataset selection. Results are shown for the common time period of 2001–2020, as well as the full time periods of each dataset. DAYMET shows the highest percentage of extreme precipitation events linked to TCs for 2001–2020 (a maximum of 7.2%) and the highest number of TCs that caused extreme precipitation events (36.5%), with IMERG showing similar results. For the full and common time periods, the highest percentage of extreme precipitation events caused by TCs was found in eastern LI. TC-related extreme precipitation averaged over LI varied year to year, and amounts were dependent on the resolution of the observational dataset, but most datasets showed an increasing trend in the last 19 years that is larger than the trend in mean precipitation. Current infrastructure in the region is likely inadequately prepared for future impacts from TC-related extreme precipitation events in such a population-dense region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Classification Analysis of Southwest Pacific Tropical Cyclone Intensity Changes Prior to Landfall

This study evaluates the ability of a random forest classifier to identify tropical cyclone (TC) intensification or weakening prior to landfall over the western region of the Southwest Pacific Ocean (SWPO) basin. For both Australia mainland and SWPO island cases, when a TC first crosses land after spending ≥24 h over the ocean, the closest hour prior to the intersection is considered as the landfall hour. If the maximum wind speed (V max ) at the landfall hour increased or remained the same from the 24-h mark prior to landfall, the TC is labeled as intensifying and if the V max at the landfall hour decreases, the TC is labeled as weakening. Geophysical and aerosol variables closest to the 24 h before landfall hour were collected for each sample. The random forest model with leave-one-out cross validation and the random oversampling example technique was identified as the best-performing classifier for both mainland and island cases. The model identified longitude, initial intensity, and sea skin temperature as the most important variables for the mainland and island landfall classification decisions. Incorrectly classified cases from the test data were analyzed by sorting the cases by their initial intensity hour, landfall hour, monthly distribution, and 24-h intensity changes. TC intensity changes near land strongly impact coastal preparations such as wind damage and flood damage mitigations; hence, this study will contribute to improve identifying and prioritizing prediction of important variables contributing to TC intensity change before landfall.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Characteristics and trends of Atlantic tropical cyclones that do and do not develop from African easterly waves

Abstract Atlantic tropical cyclones (TCs) are known to develop from African easterly waves (AEWs) that propagate across North Africa and out over the Atlantic Ocean. The relationship between AEWs and TCs has been the subject of numerous previous studies. There are, however, many Atlantic TCs that do not have AEW origins. In this study, we provide a novel analysis of the characteristics and trends of Atlantic TCs both with and without AEW origins using 43 years of observational and reanalysis data. To conduct this research, we identified TCs with and without AEW origins from the observational record between 1980 and 2022, and ran objective tracking algorithms on reanalysis data to identify the AEWs and TCs during this time period. We found statistically significant differences in the characteristics and environments of TCs with and without AEW origins. TCs with AEW origins are stronger and costlier, experience more favorable environmental conditions, and are more likely to make landfall in the Gulf of Mexico and the Caribbean when compared to TCs without AEW origins. Additionally, the 43‐year increasing trend in Atlantic TC activity is primarily driven by an increase in TCs with AEW origins that is associated with increasing AEW frequency and strength, with anthropogenic aerosols potentially driving this trend. In contrast, we found no trend in TCs without AEW origins.

Bercos‐Hickey, Emily↗
DOE OSTI2020

A new method to construct a horizontal resolution-dependent wind speed adjustment factor for tropical cyclones in global climate model simulations

A new method to construct a horizontal resolution-dependent wind speed adjustment factor for evaluating tropical cyclones (TCs) in global climate models (GCMs) is presented here. In contrast to the previous studies that used idealized axisymmetric wind fields, this study analyzes 48 hours of 10-second surface wind fields from 1-km TC simulations. The adjustment factor is derived from filtering the simulated TC wind fields onto various horizontal grid spacings typical of those used in GCMs. The new adjustment factor leads to TCs with greater intensity than the existing adjustment factors for horizontal grid spacings smaller than 30 km. This difference is attributed to more realistic wind fields in the TC simulations that contain highly asymmetric, localized patches of higher wind speeds instead of axisymmetric wind fields. Applying the new adjustment factor to select GCM simulations suggests the common interpretation of low-intensity bias in GCM-simulated TCs might be slightly exaggerated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Latent Energy and Snow Fall Speed on a Wintertime Midlatitude Cyclone

This study aimed to understand the impacts of latent energy as well as snow fall speeds on precipitation properties and synoptic-scale storm characteristics of a wintertime midlatitude cyclone. Simulations of a potent winter storm that impacted the Rocky Mountains and northern Great Plains of the United States in February 2017 were performed using the Weather Research and Forecasting model with latent heating or cooling from individual microphysical processes systematically turned off and fall speeds adjusted by ±50%. Results indicated substantial impacts on the microphysical characteristics of the simulated storm to fall speed, cooling from sublimation, and warming from deposition. The impacts of cooling and warming were manifested as differences in accumulated snowfall. Increased (decreased) fall speeds led to smaller (larger) ice crystals and total mass, resulting in offsetting effects on the precipitation flux, and thus minimal impacts on snowfall and large-scale characteristics of the storm. Warming and cooling associated with deposition and sublimation, respectively, impacted the synoptic-scale dynamics, whereby removing warming from deposition resulted in an increased meridional temperature gradient near the jet stream, thus increasing the jet strength and causing it to be more westerly with less curvature aloft. This in turn limited upper-level divergence, creating a weaker surface low and shifting the precipitation shield southward. The opposite occurred with the removal of latent cooling due to sublimation. This study highlights the potential importance of latent energy associated with ice sublimation and deposition and fall speeds in the larger-scale characteristics of winter storms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Exploring Western North Pacific Tropical Cyclone Activity in the High‐Resolution Community Atmosphere Model

Abstract High‐resolution climate models (∼28 km grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus enabling their investigation in relation to the climate system. On the global scale, previous works have demonstrated that the Community Atmosphere Model (CAM) version 5 presents a reasonable TC climatology under prescribed present‐day (1980–2005) forcing. However, for the Western North Pacific (WNP) region, known biases in simulated TC genesis frequency and location under‐represent the basin's dominant share in observations. This study addresses these model biases in WNP by evaluating WNP TCs in a decadal simulation, and exploring potential improvements through nudging experiments. Among the major environmental controls of TC genesis, the lack of mid‐level moisture is identified as the leading cause of the deficit in simulated WNP TC genesis over the Pacific Warm Pool. Subsequent seasonal experiments explore the effect of constraining the large‐scale environment on TC development by nudging WNP temperature field toward reanalysis at various strengths. Temperature nudging elicits a significant response in TC genesis and intensity development, as well as in moisture and convection over the Warm Pool. These responses are sensitive to the choice of nudging timescale. Overall, the nudging experiments demonstrate that improvements in the large‐scale environment can lead to improvements in simulated TCs, suggesting future model developments in relation to model physics. In this way, the potential improvements in model fidelity will contribute to the understanding of how the mean state of current or future climates may give rise to extremes such as TCs.

58 GEOSCIENCES↗
DOE OSTI2021

The Influence of Ocean Coupling on Simulated and Projected Tropical Cyclone Precipitation in the HighResMIP–PRIMAVERA Simulations

This study aims to quantify the impacts of atmosphere–ocean coupling on simulated and projected tropical cyclone (TC) precipitation globally. We used global climate model (GCM) simulations over 1950–2050 from the High Resolution Model Intercomparison Project (HighResMIP) and compared its fully coupled atmosphere–ocean GCMs (AOGCMs) with atmosphere-only GCMs (AGCMs). We find that ocean coupling generally leads to decreased TC precipitation over ocean and land. Large-scale sea surface temperature (SST) biases are critical drivers of the precipitation difference, with secondary contributions from local TC–ocean feedbacks via SST cold wakes. The two driving factors, attributed to ocean coupling in the AOGCMs, influence TC precipitation in association with decreased TC intensity and specific humidity. The AOGCMs and AGCMs consistently project TC precipitation increases in 2015–2050 relative to 1950–2014 over ocean for all basins, and for landfalling TCs in the North Atlantic and western North Pacific.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Seasonality of Interbasin SST Contributions to Atlantic Tropical Cyclone Activity

Abstract Recent studies have demonstrated that the difference in sea surface temperature anomalies (SSTAs) between the tropical Atlantic main development region (MDR) and the tropical Pacific (Niño 3) modulates Atlantic tropical cyclone activity. This study further explores the seasonality of Pacific and Atlantic contributions to Atlantic hurricane activity. Our analysis shows that while MDR and Niño 3 SSTAs are equally important for late‐season (September–November) activity, early‐season (June‐August) activity is largely modulated by MDR SSTAs. This reflects the increased (reduced) variance of MDR (Niño 3) SSTAs in the early‐season due to their phase locking to the seasonal cycle. Further analysis yields skillful forecasts using an MDR‐Niño 3 interbasin index derived from hindcasts of the North American Multi‐Model Ensemble with May initial conditions. However, the prediction skill for MDR SSTAs is lower than that of Niño 3 SSTAs, suggesting that increasing the prediction skill for MDR SSTAs is key to improving seasonal outlooks.

West, Robert↗
DOE OSTI2022

Influence of African Easterly Wave Suppression on Atlantic Tropical Cyclone Activity in a Convection-Permitting Model

African easterly waves (AEWs) are strongly linked to Atlantic tropical cyclones (TCs) on the synoptic timescale by serving as seedling disturbances for TC genesis. However, it is unclear whether climatological TC frequency is limited by AEWs. We investigated the impact of suppressing AEWs using a 3-member ensemble of convection-permitting regional model simulations, in which AEWs were either retained or removed through the lateral boundary conditions. Suppressing AEWs did not substantially change seasonal TC number, but did influence TC intensity, genesis time and location. Suppressing AEWs produced stronger TCs, shifted peak TC genesis from September to August, and reduced (increased) TC genesis in the eastern Atlantic (Gulf of Mexico). Without AEWs, TCs generated under more favorable large-scale atmospheric conditions. Furthermore, these results indicate that AEWs may not be reliable predictors of basin-wide seasonal TC frequency. However, simulations provide evidence that AEWs could influence the large-scale environment that is important for TCs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Role of Tropical Cyclones in Determining ENSO Characteristics

El Niño-Southern Oscillation (ENSO) can effectively modulate global tropical cyclone (TC) activity, but the role TCs may play in determining ENSO characteristics remains unclear. Here we investigate the impact of TC winds on ENSO using a suite of Earth system model experiments where we insert TC winds, extracted from a TC-permitting high-resolution simulation, into a low-resolution model configuration with nearly no intrinsic TCs. The presence of TC winds in the model increases ENSO power and shifts ENSO frequency closer to what we observe. TCs lead to an increase of strong to extreme El Niño events seen in observations and not simulated in the low-resolution model without intrinsic TCs, mainly through enhanced zonal advection feedback and thermocline feedback. Our results indicate that TCs play a fundamental role in producing the ENSO characteristics we experience today in the climate system and point to a two-way climatological interaction between TCs and ENSO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Changes in Tropical Cyclones Undergoing Extratropical Transition in a Warming Climate: Quasi-Idealized Numerical Experiments of North Atlantic Landfalling Events

The current study extends earlier work that demonstrated future extratropical transition (ET) events will feature greater intensity and heavier precipitation to specifically consider potential changes in the impacts of landfalling ET events in a warming climate. A quasi-idealized modeling framework allows comparison of highly similar present-day and future event simulations; the model initial conditions are based on observational composites, increasing representativeness of the results. The future composite ET event features substantially more impactful weather conditions in coastal areas, with heavier precipitation and greater storm intensity. Specifically, a Category 2 present-day storm attained Category 4 Saffir-Simpson intensity in the future simulation and maintained greater intensity throughout the entire life cycle, although the storm undergoes less reintensification during the post-ET process, a result of reduced baroclinic conversion. These findings suggest increased potential for coastal hazards due to stronger tropical cyclone winds and heavier rainfall, leading to more severe coastal flooding and storm surge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Revisiting the Definition of Rapid Intensification of Tropical Cyclones by Clustering the Initial Intensity and Inner‐Core Size

Abstract Rapid intensification (RI) of tropical cyclones (TCs) provides a great challenge in operational forecasting and contributes significantly to the development of major TCs. RI is commonly defined as an increase in the maximum sustained surface wind speed of at least a certain threshold within 24 hr. The most widely used threshold is 30 kt (15.4 m/s), which was determined statistically. Here we propose a new definition for RI by objectively clustering TCs using the intensification rate, initial intensity, and radius of the maximum wind speed (RMW). A group of 770 samples is separated at a threshold of 45 kt (23.2 m/s). The threshold is 40 kt (20.6 m/s) for the western North Atlantic, where TC size measurements are more reliable. Monte Carlo experiments demonstrate that the proposed threshold is robust even considering the uncertainty in RMW of as high as 30 km. We show that, when a TC undergoes RI, its maximum wind speed is approximately 60 ± 15 kt (30.9 ± 7.7 m/s) and the RMW is 45 ± 20 km. The new threshold outperforms the conventional threshold of 30 kt/24 hr in describing the bimodal distribution of lifetime maximum intensity and explaining the annual count of Category 5 TCs. This new definition provides a more physically based threshold and describes a more reliable representation of extreme events. Although more comparisons are needed for operational application, it is likely to be desirable for case‐based process studies and could provide a more valuable metric for TC intensification classification and research.

Li, Yi↗
DOE OSTI2023

The Relationship Between African Easterly Waves and Tropical Cyclones in Historical and Future Climates in the HighResMIP‐PRIMAVERA Simulations

Abstract The deadly and destructive nature of tropical cyclones (TCs) makes understanding their response to future climate change of the utmost importance. TC genesis hinges on multiple factors, including an initial disturbance. African easterly waves (AEWs) have been shown to serve as such disturbances for TCs developing in the North Atlantic. It is therefore crucial to understand the relationship between AEWs and TCs and how this relationship may be affected by climate change. In this study, we examine the AEW‐TC relationship in historical and future climates using three models from the HighResMIP PRIMAVERA simulations. The AEWs and TCs were tracked in the model data using objective tracking algorithms, and AEW and TC tracks were then matched together if they were close to each other in space and time. The strength of the AEWs was measured using the eddy kinetic energy and the curvature vorticity of the waves. TC strength and intensity were measured using potential intensity and lifetime maximum 10 m windspeed. We found that future changes in the frequency of AEWs are not a good indicator of future TC activity. However, AEW strength, as well as environmental conditions conducive to strong TCs, are good indicators of AEWs that develop into TCs in both historical and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

An Energetic Diagnostic of Tropical Cyclone Size in f –Plane Simulations

As a major feature of tropical cyclones (TCs), controlling factors of TC outer size or size scaling remains a fundamental scientific question. The Rossby deformation radius and a natural extent associated with potential intensity have been proposed as two scalings of TC size. But neither of them satisfactorily captures the sensitivity of TC size to sea surface temperature (SST) in idealized f-plane simulations. Inspired by the studies of the Hadley circulation, here we proposed a new TC scaling based on an energetic diagnostic scaling. TC size is primarily a ratio of the secondary circulation strength to subsidence velocity, further determined by the total atmospheric heating in the ascending area, the gross moist stability, the diabatic cooling, and the dry static stability. The former two is based on the moist energetic budget applied to the whole storm structure, while the latter two is based on the dry thermodynamic budget applied to the subsidence areas. The new scaling well captured the sensitivity of TC size to SST in idealized f-plane simulations, partly resulted from expanded ascending area, increased surface moisture deficit, and weakened subsidence with increased SST.

58 GEOSCIENCES↗
DOE OSTI2023

Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity

Abstract It has been widely recognized that tropical cyclone (TC) genesis requires favorable large‐scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large‐scale environmental favorability in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relationship between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer‐learning technique to train ensemble of CNNs first on suites of high‐resolution climate model simulations with realistic seasonal TC activities and large‐scale environmental conditions, and then on a state‐of‐the‐art reanalysis from 1950 to 2019. The trained CNNs can well reproduce the historical TC records and yields significant seasonal prediction skills when the large‐scale environmental inputs are provided by operational climate forecasts. Furthermore, by inputting the ensemble CNNs with 20th century reanalysis products and Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we investigated TC variability and its changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our future projections using high‐resolution climate model.

Meteorology & Atmospheric Sciences↗