Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “tropical cyclones”

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.

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

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Recent Tropical Cyclone Outer Size Increases in the Western North Atlantic

The outer size of a tropical cyclone (TC) plays a pivotal role in its impact through a modulation of wind duration, rainfall extent and storm surge. While global and basin scale trends in TC size have been examined previously, whether there have been regional changes over time remains unclear. Here, using a suite of observations and reanalyses, we detect an increasing TC outer size over the western North Atlantic during 1979–2022. Over the western subtropical North Atlantic where the largest changes are found, the area-averaged increase in the radius of 17 ms -1 winds is about 7.5% over this period. Analysis of the large-scale environment reveals that the air-sea thermodynamic state has become more favorable for storm intensification, and thereby expansion, over that region. Further, numerical model simulations link changes in the environment with those in storm size, and suggest a combination of natural variability and external forcing in driving them.

Balaguru, Karthik [Pacific Northwest National Labo↗
NASA NTRS1976

Satellite-observed latent heat release in a tropical cyclone

Data from the Nimbus 5 electrically scanning microwave radiometer (ESMR) are used to make calculations of the latent heat release (L.H.R.) and the distribution of rainfall rate in a tropical cyclone as it grows from a tropical disturbance to a typhoon. The L.H.R. (calculated over a circular area of 4 deg latitude radius) increases during the development and intensification of the storm from a magnitude of 2.7 X 10 to the 21st power ergs/s (in the disturbance stage) to 8.8 X 10 to the 21st power ergs (typhoon stage). The latter value corresponds to a mean rainfall rate of 2.0 mm hr/s. The more intense the cyclone and the greater the L.H.R., the greater the percentage contribution of the larger rainfall rates to the L.H.R. In the disturbance stage the percentage contribution of rainfall rates less than or minus 6 mm hr/s is typically 8%; for the typhoon stage, the value is 38%. The distribution of rainfall rate as a function of radial distance from the center indicates that as the cyclone intensifies, the higher rainfall rates tend to concentrate toward the center of the circulation.

Adler, R. F.↗
DOE OSTI2025

Uncertainty in Synthetic Tropical Cyclone Hazard and Risk Estimates: Insights from RAFT, CHAZ, MIT, STORM, and CLIMADA

We synthesize five complementary tropical cyclone (TC) hazard frameworks—RAFT (physics-based machine learning), CHAZ and MIT (statistical–dynamical), STORM (fully statistical), and CLIMADA (observation-driven resampling)—to characterize uncertainty in wind-related TC metrics relevant to energy applications. All datasets and the IBTrACS observational record are harmonized to a common 6-hourly, 2.5° grid. We compare basin-wide and coastal properties using consistent definitions for TC frequency, mean and maximum intensity, 24-hour intensification, and 6-hour translation speed, and quantify agreement with Pearson r, RMSE, and Kling–Gupta efficiency (KGE) alongside resampling-based confidence intervals. CLIMADA is included for basin context but excluded from coastal skill scoring because it resamples historical IBTrACS; if supplied with projected future tracks from an external hazard model, CLIMADA can be used to simulate future TC scenarios. Results show robust, cross-model signals: (i) a corridor of activity from the tropical Atlantic through the Caribbean into the Bahamas and western subtropical Atlantic; (ii) a meridional dipole in 24-hour intensification (low-latitude strengthening, subtropical weakening); and (iii) a transition from slower tropical motion to faster midlatitude translation. Coastal winds (mean and maximum) consistently cluster from the eastern Gulf into the Bahamas–western Atlantic transition. The largest structural spread occurs in the amplitude and footprint of lifetime maximum intensity and, secondarily, in translation speed; intensification exhibits similar central behavior across frameworks with variability in extremes. Translation speed shows the most uniform coastal agreement. These findings provide a decision envelope for wind-focused risk screening and clarify where uncertainty should be carried forward; wind-only results represent a lower bound on total hazard, motivating integration of surge and rainfall modules and a companion, asset-level damage analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

The effect of African Easterly Wave suppression by periodicity on Atlantic tropical cyclones

Research has shown that suppressing African Easterly Waves (AEWs) does not reduce basin-wide North Atlantic tropical cyclone (TC) frequency but can enhance TC environmental favorability. We investigated the AEW-TC relationship further by examining the effects of suppressing the two AEW periodicities individually on TC activity. Using regional model simulations, AEWs were prescribed or suppressed in the 2–6 d or 6–10 d ranges through the lateral boundary conditions. Seasonal TC frequency increased significantly when either AEW periodicity was suppressed, with a larger increase when the 2–6 d waves were suppressed. We also found that suppressing the 2–6 d waves increased mid-tropospheric moisture by up to 8%, as well as overall atmospheric instability, near the western coast of northern Africa. Furthermore, the convective disturbances that developed into TCs exhibited stronger rotation, increased ascending motion, and higher rainfall. Our results suggest that reduced 2–6 d AEW activity may trigger a more active TC season.

Danso, Derrick K↗
DOE OSTI2025

Effects of Atmosphere and Ocean Horizontal Model Resolution on Tropical Cyclone and Upper-Ocean Response Forecasts in Four Major Hurricanes

A coupled atmosphere–ocean model is necessary for tropical cyclone (TC) prediction to accurately characterize ocean feedback on atmospheric processes within the TC environment. Here, the ECMWF coupled global model is run at horizontal resolutions from 9 to 1.4 km in the atmosphere, as well as 25 and 8 km in the ocean, to identify how resolution impacts forecast accuracy of four observed major TCs in the Atlantic: Irma, Florence, Teddy, and Ida. Most of the resolutions used here are unprecedented for global models. GOES-16 and synthetic aperture radar (SAR) satellite images and best track data are used for atmospheric validation. Salinity and temperature observations from Air-Launched Autonomous Micro-Observer (ALAMO) floats are used to validate modeled upper-ocean response, including mixed layer deepening, sea surface cooling, and near-inertial waves in the wakes of TCs. Increasing atmospheric resolution leads to more realistic TC structure and stronger winds, significantly improving TC intensity forecasts and modestly improving track errors. Ocean resolution impacts the upper-ocean response but does not influence atmospheric forecasts for the fast-moving TCs considered here. Stronger mixing, sea surface cooling, and near-inertial oscillations are found for both higher atmosphere and ocean resolutions, provided the initial upper-ocean state is the same for the two ocean resolutions. Whether this agrees better with the ALAMO observations also depends on the realism of the initial upper-ocean state in the model, emphasizing the importance of ocean initialization for the accurate upper-ocean response. Overall, the model at all resolutions correctly predicts stronger mixing, surface cooling, and near-inertial oscillation amplitudes to the right of a TC center, as observed by ALAMO floats.

Atmosphere-ocean interaction↗
NASA NTRS1974

Tropical cyclone rainfall as measured by the Nimbus 5 electrically scanning microwave radiometer

A selected group of 1973 North Pacific Ocean tropical cyclones was studied by using data from the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR), the Temperature-Humidity Infrared Radiometer (THIR), NOAA-2 and USAF DMSP imageries. From the unique combination of infrared, visible, and microwave data, it was possible during various stages of storm development to differentiate between dense cirrus outflow and rain areas, to identify centers of circulation and areas of low-level moisture, and by the use of a theoretical model to estimate semi-quantitatively areas of light, moderate, and heavy rainfall rates.

Allison, L. J.↗
DOE OSTI2025

Toward Understanding the Differences between Mesoscale and Large-Eddy Simulations of Tropical Cyclones

In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from categories 1 to 5 on the Saffir–Simpson scale and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10–500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary layer parameterization may be needed.

17 WIND ENERGY↗
NASA NTRS1977

Latent heat calculations and their relationship to tropical cyclone intensity

Data from the Nimbus-5 electrically scanning microwave radiometer (ESMR) were used to calculate total storm latent heat release (LHR) and other precipitation parameters for over 100 satellite observations of Pacific Ocean tropical cyclones. The data are useful in determining the rainfall characteristics of these storms and appear to be potentially useful in monitoring them.

Adler, R. F.↗
DOE OSTI2025

pyTCR: A tropical cyclone rainfall model for python

pyTCR is a climatology software package developed in the Python programming language. It integrates the capabilities of several legacy physical models and increases computational efficiency to allow rapid estimation of tropical cyclone (TC) rainfall consistent with the large-scale environment. Specifically, pyTCR implements a horizontally distributed and vertically integrated model [Zhu et al., 2013] for simulating rainfall driven by TCs. Along storm tracks, rainfall is estimated by computing the cross-boundary-layer, upward water vapor transport caused by different mechanisms including frictional convergence, vortex stretching, large-scale baroclinic effect (i.e., wind shear), topographic forcing, and radiative cooling [Lu et al., 2018]. The package provides essential functionalities for modeling and interpreting spatio-temporal TC rainfall data. pyTCR requires a limited number of model input parameters, making it a convenient and useful tool for analyzing rainfall mechanisms driven by TCs. To sample rare (most intense) rainfall events that are often of great societal interest, pyTCR adapts and leverages outputs from a statistical-dynamical TC downscaling model [Lin et al., 2023] capable of rapidly generating a large number of synthetic TCs given a certain climate. As a result, pyTCR significantly reduces computational effort and improves the efficiency in capturing extreme TC rainfall events at the tail of the distributions from limited datasets. Furthermore, the TC downscaling model is forced entirely by large-scale environmental conditions from reanalysis data or coupled General Circulation Models (GCMs), simplifying the projection of TC-induced rainfall and wind speed under future climate using pyTCR. Finally, pyTCR can be coupled with hydrological and wind models to assess risks associated with independent and compound events (e.g., storm surges and freshwater flooding).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Tropical Cyclone Wind Speeds

The RAFT TC model is used to simulate storms for historical and future climates using CMIP6 environmental conditions.

17 WIND ENERGY↗