Search NASA⌕ Search

SEARCH · Search NASA

Results for “CYCLONE”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tropical Cyclone Precipitation Response to Surface Warming in Aquaplanet Simulations With Uniform Thermal Forcing

While many modeling studies have attempted to estimate how tropical cyclone (TC) precipitation is impacted by climate change, the multitude of analysis techniques and methodologies have resulted in varying conclusions. Simplified models may be able to help overcome this problem. Radiative-convective equilibrium (RCE) model simulations have been used in various configurations to study fundamental aspects of Earth's climate. While many RCE modeling studies have focused on TC genesis, intensification, and size, limited work has been done using RCE to study TC precipitation. Here, in this study, the response of TC precipitation to sea surface temperature (SST) change is analyzed in global Community Atmosphere Model (CAM) aquaplanet simulations run with Radiative-Convective Equilibrium Model Intercomparison Project protocols, with the addition of planetary rotation. We expect that the insight gained about how TC precipitation responds to SST warming will help predict how TCs in the real world respond to climate change. In the CAM RCE simulations, the warmer SST simulations have less TCs on average, but the TCs tend to be larger in outer size and more intense. As simulation SST increases, more extreme precipitation rates occur within TCs, and more of the TC precipitation comes from these extreme rates. For extreme (99th percentile) TC precipitation, SST, and TC intensity increases dominate the 8.6% per K increase, while TC outer size changes have little impact. For accumulated TC precipitation, SST, and TC intensity contributions are still the majority, but TC outer size changes also contribute to the 6.6% per K increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of Rainfall on Tropical Cyclone-Induced Sea Surface Cooling

Tropical cyclones (TCs) are often accompanied by strong winds and torrential rains. While the winds associated with TCs tend to enhance mixing in the upper-ocean, the freshwater input from rain can stratify the water column and limit mixing. However, the extent to which the stabilizing effect of rainfall can compete with wind-induced mixing, and to what degree it modulates TC-induced sea surface cooling, remains unknown. Here we show, using a suite of observations, that heavy rains under weak TCs can significantly reduce the magnitude of cold wakes induced by them. Additionally, when compared to storms with low rain rates, the ocean surface under TCs with high rain rates freshens significantly and cools less. High-resolution climate model simulations and idealized experiments with an ocean mixed layer model support these results and reveal that oceanic mixing processes are primarily responsible for the reduced cooling under TCs, with a lesser role for surface fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Investigating the Physical Drivers for the Increasing Tropical Cyclone Rainfall Hazard in the United States

In this study, we investigate both the changes of tropical cyclone (TC) rainfall hazard in the United States under climate change and the relative importance of the factors that cause the changes. We find that under the SSP5 8.5 scenario, the 100-year TC rainfall level can increase by up to 320% along the U.S. coastline by the end of this century. The influence of TC rainfall-producing ability increase is more significant than the influence of TC frequency increase on the increase of the 100-year TC rainfall level (up to 180% vs. 60% increase). Among the different physical drivers for the increase in storm rainfall-producing ability, the increase of TC intensity is the leading factor, followed by changes in TC duration and atmospheric temperature. The projected increase of TC rainfall hazard is robust against the uncertainty in the TC frequency projection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Observed Increase in Tropical Cyclone‐Induced Sea Surface Cooling Near the U.S. Southeast Coast

Abstract Tropical cyclones (TCs) induce substantial upper‐ocean mixing and upwelling, leading to sea surface cooling. In this study, we explore changes in TC‐induced cold wakes along the United States (U.S.) Southeast and Gulf Coasts during 1982–2020. Our study shows a significant increase in TC‐induced sea surface temperature (SST) cooling of about 0.20°C near the U.S. Southeast Coast over this period. However, for the U.S. Gulf Coast, trends in TC‐induced SST cooling are insignificant. Analysis of the large‐scale oceanic environments indicate that the increasing TC‐induced cold wakes near the Southeast coast have been predominantly caused by the cooling of subsurface waters in that region. This upper‐ocean change is attributed to the enhancement of surface pressure gradient across land‐sea boundary and the associated increase in alongshore winds over there. Further analysis with climate models reveals the important role of anthropogenic forcings in driving these changes in the atmospheric circulation response along the U.S. Southeast Coast.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Understanding the Recent Increase in Landfalling Tropical Cyclones Over Florida's Gulf Coast

Unlike Florida's Atlantic Coast, the Gulf Coast of Florida has seen heightened tropical cyclone (TC) activity in recent decades with several destructive landfalls. Here, we attempt to understand this regional contrast using a suite of observations for the period 1979–2024. First, we demonstrate that while the El Niño Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO) can explain ~23% of the interannual variability in landfalls over the Gulf Coast, the variance explained by them for the Atlantic Coast is statistically insignificant. Next, we show that this striking difference may be attributed to the regional patterns of wind shear, steering flow and air-sea thermodynamic state excited by those modes of variability. The differential control exerted by ENSO, AMO, and NAO on landfalling Florida TCs, in combination with decadal trends in those modes, is likely responsible for the observed increases in landfalls over Florida's Gulf Coast.

Florida↗
DOE OSTI2026

The Role of Tropical Cyclone—Ocean Interactions in Future Changes in Hurricane Katrina

Tropical cyclone (TC) intensity and precipitation are projected to increase in the future. However, some projections are based on atmosphere‐only models in which sea surface temperatures are prescribed, whereas projections based on global atmosphere‐ocean coupled models can be subject to long‐term ocean biases. We investigated the role of TC‐ocean interactions in future changes in TC intensity and precipitation in Hurricane Katrina. We performed four‐member ensembles using convection‐permitting atmosphere‐only and atmosphere‐ocean regional models for the historical climate and four future climates. We found that although future TC intensity and precipitation increased regardless of ocean coupling, ocean coupling dampened the future minimum sea‐level pressure decrease by half and amplified future precipitation scaling. Compared to future changes in upper‐ocean temperature, changes in salinity contributed little to future changes in TC intensity. This study highlights the importance of considering TC‐ocean interactions to reduce uncertainty in the magnitude of future TC intensity and precipitation projections.

climate change↗
DOE OSTI2021

Climatological analysis of tropical cyclone impacts on hydrological extremes in the Mid-Atlantic region of the United States

Abstract Research efforts related to landfalling tropical cyclones (TCs) and their hydrological impacts have focused mostly on the continental or regional scales, whereas many coastal management and infrastructure decisions are made at much finer spatial scales. In this context, this study aims to provide local-scale understandings of the climatological characteristics and hydrological impacts of TCs (from 1950 to 2019) over the Mid-Atlantic region defined as the Delaware River Basin (DRB) and Susquehanna River Basin (SRB). The climatological analysis is based on analyzing long-term, spatially distributed observational datasets of hurricane tracks, precipitation, and streamflows. Results suggest that, despite limited contribution of TCs to regional precipitation (<9%), TC is the dominant driver for extreme floods in the southern part of DRB (e.g. tributaries of the Christina River and lower Schuylkill River) and the southwestern portions of SRB (e.g. tributaries of the Lower Susquehanna and Junita River), where TC’s effect on drought alleviation is also comparatively higher. At the basin level, SRB is more susceptible to flooding associated with TCs and prone to drought relative to DRB; however, strong spatial variability of TC’s impact on hydrological extremes is observed within and across the basins. While the TC effect on flood/drought is negligible for the high-elevation, northern part of the region, TC increases the magnitude of the 100 year flood by up to 19.6% in DRB and 53.0% in SRB; the duration of short-term extreme hydrological drought is reduced by TC by up to 25.0% in SRB and 24.7% in DRB, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning

Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is salinity, which is important for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model consisting of a variety of machine learning (ML) methods. For salinity data, we use satellite measurements of pre-storm sea surface salinity (SSS) as a proxy for the salinity stratification. We train and test the model on various ocean basins, including the Atlantic, eastern North Pacific and western North Pacific. A calibrator is trained on top of the ML models to correct and enhance probability forecasts. The calibrator significantly improves probability forecasts relative to recent works. The ML model performance is improved with the addition of SSS in the Eastern North Pacific, western North Pacific, and the Caribbean subregion of the North Atlantic, and the overall model performance is better than previous studies. SSS decreases model skill for a model trained on the full Atlantic basin. In the Indian Ocean, SSS is also notably correlated with RI occurrence, but the TC samples are not sufficient to train ML models.

hurricane↗
DOE OSTI2025

Projected increases in tropical cyclone-induced U.S. electric power outage risk

Abstract While power outages caused by tropical cyclones (TCs) already pose a great threat to coastal communities, how—and why—these risks will change in a warming climate is poorly understood. To address this need, we develop a robust machine learning model to capture TC-induced power outage risk. When applied to 900 000 synthetic TCs downscaled from simulated historical and future climate conditions under a strong warming scenario, we find outage risk in the United States and Puerto Rico is expected to increase broadly by the end of the century, with some states seeing increases of 60% and higher. Further, we discover that rising rainfall rates will play an increasingly important role in TC-induced power outage risk as the climate changes, explaining more than 50% of the projected change in risk in some regions. These insights are important for guiding decision-makers in their future outage risk investment and mitigation plans.

Grid Resilience↗
DOE OSTI2023

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

Abstract This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical cyclone–driven (TC-driven) storm tide and inundation with limited time and resources. Forecasts of TC track, intensity, and size are perturbed according to quasi-random Korobov sequences of historical forecast errors with assumed Gaussian and uniform statistical distributions. These perturbations are run in an ensemble of hydrodynamic storm tide model simulations. The resulting set of maximum water surface elevations are dimensionality reduced using Karhunen–Loève expansions and then used as a training set to develop a polynomial chaos (PC) surrogate model from which global sensitivities and probabilistic predictions can be extracted. The maximum water surface elevation is extrapolated over dry points incorporating energy head loss with distance to properly train the surrogate for predicting inundation. We find that the surrogate constructed with third-order PCs using elastic net penalized regression with leave-one-out cross validation provides the most robust fit across training and test sets. Probabilistic predictions of maximum water surface elevation and inundation area by the surrogate model at 48-h lead time for three past U.S. landfalling hurricanes (Irma in 2017, Florence in 2018, and Laura in 2020) are found to be reliable when compared to best track hindcast simulation results, even when trained with as few as 19 samples. The maximum water surface elevation is most sensitive to perpendicular track-offset errors for all three storms. Laura is also highly sensitive to storm size and has the least reliable prediction. Significance Statement The purpose of this study is to develop and evaluate a methodology that can be used to provide high-quality probabilistic predictions of hurricane-induced storm tide and inundation with limited time and resources. This is important for emergency management purposes during or after the landfall of hurricanes. Our results show that sampling forecast errors using quasi-random sequences combined with machine learning techniques that fit polynomial functions to the data are well suited to this task. The polynomial functions also have the benefit of producing exact sensitivity indices of storm tide and inundation to the forecasted hurricane properties such as path, intensity, and size, which can be used for uncertainty estimation. The code implementing the presented methodology is publicly available on GitHub.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Diurnal MCSs Precede the Genesis of Tropical Cyclone Mora (2017): The Role of Convectively Forced Gravity Waves

In this work, a novel high-resolution regional reanalysis is used to investigate the mesoscale processes that preceded the formation of Tropical Cyclone (TC) Mora (2017). Both satellite observations and the regional reanalysis show early morning mesoscale convective systems (MCSs) persistently initiated and organized in the downshear quadrant of the preexisting tropical disturbance a few days prior to the genesis of TC Mora. The diurnal MCSs gradually enhanced the meso-α-scale vortex near the center of the preexisting tropical disturbance through vortex stretching, providing a vorticity-rich and moist environment for the following burst of deep convection and enhancement of the meso-β-scale vortex. The regional reanalysis shows that the gravity waves that radiated from afternoon convection over the northern coast of the Bay of Bengal might play an important role in modulating the diurnal cycle of pregenesis MCSs. The diurnal convectively forced gravity waves increased the tropospheric stability, reduced the column saturation fraction, and suppressed deep convection within the preexisting tropical disturbance from noon to evening. A similar quasi-diurnal cycle of organized deep convection prior to TC genesis has also been observed over other basins. However, modeling studies are needed to conclusively demonstrate the relationships between the gravity waves and pregenesis diurnal MCSs. Also, whether diurnal gravity waves play a similar role in modulating the pregenesis deep convection in other TCs is worth future investigations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Azimuthally averaged wind and thermodynamic structures of tropical cyclones in global climate models and their sensitivity to horizontal resolution

Characteristics of tropical cyclones (TCs) in global climate models (GCMs) are known to be influenced by details of the model configurations, including horizontal resolution and parameterization schemes. Understanding model-to-model differences in TC characteristics is a prerequisite for reducing uncertainty in future TC activity projections by GCMs. This study performs a process-level examination of TC structures in eight GCM simulations that span a range of horizontal resolutions from 1° to 0.25°. A recently developed set of process-oriented diagnostics is used to examine the azimuthally averaged wind and thermodynamic structures of the GCM-simulated TCs. Results indicate that the inner-core wind structures of simulated TCs are more strongly constrained by the horizontal resolutions of the models than are the thermodynamic structures of those TCs. As expected, the structures of TC circulations become more realistic with smaller horizontal grid spacing, such that the radii of maximum wind (RMW) become smaller, and the maximum vertical velocities occur off the center. However, the RMWs are still too large, especially at higher intensities, and there are rising motions occurring at the storm centers, inconsistently with observations. The distributions of precipitation, moisture, radiative and surface turbulent heat fluxes around TCs are diverse, even across models with similar horizontal resolutions. At the same horizontal resolution, models that produce greater rainfall in the inner-core regions tend to simulate stronger TCs. Further, when TCs are weak, the radial gradient of net column radiative flux convergence is comparable to that of surface turbulent heat fluxes, emphasizing the importance of cloud-radiative feedbacks during the early developmental phases of TCs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

An Evaluation of Tropical Cyclone Rainfall Structures in the HighResMIP Simulations against Satellite Observations

This study evaluates tropical cyclone (TC) rainfall structures in the CMIP6 HighResMIP global climate model (GCM) simulations against satellite rainfall retrievals. Here, we specifically focus on TCs within the deep tropics (25°S–25°N). Analysis of TC rain rate composites indicates that in comparison to the satellite observations at the same intensity, many HighResMIP simulations tend to overproduce rain rates around TCs, in terms of both maximum rain rate magnitude and area-averaged rain rates. In addition, as model horizontal resolution increases, the magnitude of the peak rain rate appears to increase. However, the area-averaged rain rates decrease with increasing horizontal resolution, partly due to the TC eyewall being located closer to the TC center, thus occupying a smaller area and contributing less to the area-averaged rain rates. The effect of ocean coupling is to lower the TC rain rates, bringing them closer to the satellite observations, due to reduced horizontal moisture flux convergence and surface latent heat flux beneath TCs. Examination of horizontal rain rate distributions indicates that vertical wind shear–induced rainfall asymmetries in HighResMIP-simulated TCs are qualitatively consistent with the observations. In addition, a positive relationship is observed between the area-averaged inner-core rainfall and TC intensification likelihoods across the HighResMIP simulations, as GCM simulations producing stronger TCs more frequently have the greater rainfall close to the center, in agreement with previous theoretical and GCM simulation results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Analyzing Relationships between Tropical Cyclone Intensity and Rain Rate over the Ocean Using Numerical Simulations

In this study, the relationship between tropical cyclone (TC) intensity and rain rate over the ocean is investigated using a full-physics numerical model (WRF) and a physics-based TC rainfall model (TCR). TC intensity is found to be nearly linearly correlated with the average rain rate in the inner core [~0.97 (mm h –1 m –2 )/(m s –1 )], while the correlation is weak at outer radii. This difference is induced because TC intensity is significantly correlated with both the vertical velocity and specific humidity in the inner core but is not significantly correlated with the vertical velocity in the outer radii. Further investigation shows that the intensity–rain-rate relationship at the outer radii is influenced by the TC evolution stage. The rain rate for the outer radii is positively correlated with TC intensity for nondecaying TCs, while this correlation is reduced for decaying TCs due to systematic downdrafts in the outer radii. In the context of climate change, the sensitivity of the TC rain rate to sea surface temperature (SST) is found to be +9% per 1 K increase of SST, roughly the product of the sensitivity of TC intensity to SST (+3%) and the Clausius-Clapeyron scaling (+7%). Coupled with synthetic storms, evolution of the TC rain rate over the twenty-first century under the SSP5-8.5 scenario is projected by the TCR (calibrated with the WRF simulations). The annual increase rates of averaged TC rain rate are 0.17% and 0.20% for the inner core and outer radii, respectively, larger than the annual increase rate of TC intensity (0.046%) but comparable to that of cube of intensity (0.18%).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of Tropical Cyclone Wind Forcing on the Global Climate in a Fully Coupled Climate Model

Tropical cyclones (TCs) alter upper-ocean temperature and influence ocean heat content via enhanced turbulent mixing. A better understanding of the role of TCs within the climate system requires a fully coupled modeling framework, where TC-induced ocean responses feed back to the atmosphere and subsequently to the climate mean state and variability. Here, we investigate the impacts of TC wind forcing on the global ocean and the associated feedbacks within the climate system using the fully coupled Community Earth System Model version 1.3 (CESM1.3). Using the low-resolution version of CESM1.3 (1° atmosphere and ocean grid spacing) with no intrinsic TCs, we conduct a suite of sensitivity experiments by inserting TC winds extracted from a high-resolution (0.25° atmosphere grid spacing) TC-permitting simulation into the low-resolution model. Results from the low-resolution TC experiment are compared to a low-resolution control simulation to diagnose TCs’ impact. We found that the added TC winds can increase ocean heat content by affecting ocean vertical mixing, air–sea enthalpy fluxes, and cloud amount. Here, the added TCs can influence mean SST, precipitation, ocean subsurface temperature, and ocean mixed layer depth. We found a strengthening of the wind-driven subtropical cells and a weakening of the Atlantic meridional overturning circulation due to the changes of surface buoyancy fluxes. TCs in the model cause anomalous equatorward ocean heat convergence in the deep tropics and an increase of poleward ocean heat transport out of the subtropics. Our modeling results provide new insights into the multiscale interactions between TCs and the coupled climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Influence of ENSO Diversity on Future Atlantic Tropical Cyclone Activity

El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting Model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly varying climatology, eastern Pacific El Niño, central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during eastern Pacific El Niño compared to central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during eastern Pacific El Niño compared to central Pacific El Niño. In addition, we found a decrease in the Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific sea surface temperature (SST) gradient, corresponding to a more El Niño–like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Are North Atlantic Tropical Cyclones Modulated by the Madden–Julian Oscillation in HighResMIP AGCMs?

This study assesses the representation of the observed relationship between Atlantic tropical cyclones (TCs) and the Madden–Julian oscillation (MJO) across nine models participating in CMIP6 High Resolution Model Intercomparison Project (HighResMIP). Most models struggle to faithfully reproduce the observed impacts of the MJO on Atlantic TCs, with the primary issue being the underestimated TC activity over the Atlantic main development region (MDR). The negative biases in genesis frequency within the MDR can be further attributed to weaker-than-observed African easterly wave (AEW) activity south of ∼12°N. Errors in the diabatic heating profile within the Atlantic intertropical convergence zone lead to insufficient potential vorticity production in the lower troposphere and constrain the amplification of AEWs. In addition to the biased TC climatology, the eastward-propagating power of the MJO is consistently underestimated across all models. Nevertheless, in models with a higher eastward–westward power ratio, the simulated MJO demonstrates a stronger capacity to modulate subseasonal TC activity. Models with relatively realistic eastward propagation of the MJO also exhibit greater variance in tropical intraseasonal convection. Stronger contrasts in convective heating over the North Atlantic between phases 2–3 and phases 6–7 drive larger fluctuations in MDR shear and AEW activity over the Gulf of Mexico and West Africa, resulting in a more pronounced TC response to the MJO. Overall, our findings suggest that improved MDR TC climatology and MJO propagation are essential for models to accurately capture the observed modulations of Atlantic TCs by the MJO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗