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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Environmental Forcing of Super Typhoon Paka's (1997) Latent Heat Structure

The distribution and intensity of total (i.e., combined stratified and convective processes) rainrate/latent heat release (LHR) were derived for tropical cyclone Paka during the period 9-21 December, 1997 from the F-10, F-11, F-13, and F-14 Defense Meteorological Satellite Special Sensor Microwave/Imager and the Tropical Rain Measurement Mission Microwave Imager observations. These observations were frequent enough to capture three episodes of inner core convective bursts that preceded periods of rapid intensification and a convective rainband (CRB) cycle. During these periods of convective bursts, satellite sensors revealed that the rainrates/LHR: 1) increased within the inner eye wall region; 2) were mainly convectively generated (nearly a 65% contribution), 3) propagated inwards; 4) extended upwards within the middle and upper-troposphere, and 5) became electrically charged. These factors may have caused the eye wall region to become more buoyant within the middle and upper-troposphere, creating greater cyclonic angular momentum, and, thereby, warming the center and intensifying the system. Radiosonde measurements from Kwajalein Atoll and Guam, sea surface temperature observations, and the European Center for Medium Range Forecast analyses were used to examine the necessary and sufficient condition for initiating and maintaining these inner core convective bursts. For example, the necessary conditions such as the atmospheric thermodynamics (i.e., cold tropopause temperatures, moist troposphere, and warm SSTs [greater than 26 deg]) suggested that the atmosphere was ideal for Paka's maximum potential intensity (MPI) to approach super-typhoon strength. Further, Paka encountered weak vertical wind shear (less than 15 m/s ) before interacting with the westerlies on 21 December. The sufficient conditions, on the other hand, appeared to have some influence on Paka's convective burst, but the horizontal moisture flux convergence values in the outer core were weaker than some of the previously examined tropical cyclones. Also, the upper tropospheric outflow generation of eddy relative angular momentum flux convergence was 4D much less than that found during moderate tropical cyclone/trough interaction. These results indicated how important the external necessary condition and the internal forcing (i.e., CRB cycle) were in generating Paka's convective bursts as compared to the external sufficient forcing mechanisms found in higher latitude tropical cyclones. Later, as Paka began to interact with the westerlies, both the necessary (i.e., strong vertical shear and colder SSTs) and sufficient (i.e., dry air intrusion) external forcing mechanisms helped to decrease Paka's rainrate.

Rodgers, Edward B.↗
NASA NTRS1983

Monitoring tropical cyclone evolution with NOAA satellite microwave observations

NOAA satellite microwave soundings, which penetrate high clouds, delineate the development and dissipation of the upper tropospheric warm core associated with a tropical cyclone. The storm's 'core" may be detected from microwave imagery. Vertical cross sections reveal the intensification of the upper tropospheric warm core as the storm develops, and the downward propagation of the warm core as the storm dissipates. Excellent correlation is found between the horizontal Laplacian of an upper tropospheric temperature field and the intensity of the storm, as categorized by its surface central pressure and maximum sustained wind speed at the eye wall. The microwave monitoring of tropical cyclones is achieved in real time at the University of Wisconsin's Space Science and Engineering Center through high-speed teleconnections to direct readout receiving systems at Wallops Island, Virginia and Redwood City, California.

Velden, C.↗
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

Evaluating the Simulation of CONUS Precipitation by Storm Type in E3SM

Abstract Conventional low‐resolution (LR) climate models, including the Energy Exascale Earth System Model (E3SMv1), have well‐known biases in simulating the frequency, intensity, and timing of precipitation. Approaches to next‐generation E3SM, whether the high‐resolution (HR) or multiscale modeling framework (MMF) configuration, improve the simulation of the intensity and frequency of precipitation, but regional and seasonal deficiencies still exist. Here we apply a methodology to assess the contribution of tropical cyclones (TCs), extratropical cyclones (ETCs), and mesoscale convective systems (MCSs) to simulated precipitation in E3SMv1‐HR and E3SMv1‐MMF relative to E3SMv1‐LR. Across the United States, E3SMv1‐MMF provides the best simulation in terms of precipitation accumulation, frequency and intensity from MCSs and TCs compared to E3SMv1‐LR and E3SMv1‐HR. All E3SMv1 configurations overestimate precipitation amounts from and the frequency of ETCs over CONUS, with conventional E3SMv1‐LR providing the best simulation compared to observations despite limitations in precipitation intensity within these events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stronger Tropical Cyclone–Induced Ocean Cooling in Near-Coastal Regions Compared to the Open Ocean

Abstract Tropical cyclones (TC) often induce strong mixing in the upper ocean that generates a trail of cooler sea surface temperature (Twake) in their wakes. The Twake can affect TC intensity, so its prediction is important, especially in coastal regions where TCs can make landfall. Coastal Twakes are often more complex than those in the open ocean due to the influences of coastline geometry, highly variable water depth, continental runoff, and shelf processes. Using observational data since 2002, here we show a significantly stronger global mean Twake in coastal regions compared to offshore regions. Temperature stratification is the main driver of stronger coastal Twakes in the North Atlantic and east Pacific. In the northwest Pacific and north Indian Ocean, the differences between coastal and offshore Twakes are smaller due to compensation between TC forcings and ocean stratification. The north Indian Ocean is unique in the Northern Hemisphere because salinity stratification plays a major role on the spatial distribution of Twake. In the South Pacific Ocean, TC intensity and translation speed are crucial for explaining coastal–offshore Twake differences, while ocean stratification and mixed layer depth are more important for the coastal–offshore Twake differences in the south Indian Ocean. These findings suggest that coastal–offshore differences in ocean stratification need to be properly represented in models in order to capture changes in TC-induced ocean cooling as storms approach landfall. Significance Statement Landfalling tropical cyclones (TCs) often cause considerable damage in coastal regions with dense human populations. Understanding TC–ocean interaction and how it differs between coastal and offshore regions can help predict TC intensity prior to landfall. Sea surface cooling after TC passage is an important proxy for TC–ocean interaction. A global evaluation of coastal TC-induced cooling has not been conducted. Using data covering two decades, we show significantly stronger TC-induced surface cooling in coastal regions compared to offshore regions at the global scale and in all basins except the northwest Pacific and north Indian Ocean. The difference is driven mainly by upper-ocean conditions in the North Atlantic, east Pacific, and south Indian Ocean, and by TC characteristics in the South Pacific.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Decadal Trends of Atlantic Basin Tropical Cyclones (1950-1999)

Ten-year moving averages of the seasonal rates for "named storms," tropical storms, hurricanes, and major (or intense) hurricanes in the Atlantic basin reveal that the present epoch is one of enhanced activity (i.e., having seasonal rates typically equal to or above respective long-term median rates). For example, the 10-year moving average of the seasonal rates for named storms is now higher than for any previous year over the past 50 years, measuring 10.65 in 1994, or 2.65 units higher than its median rate of 8. For tropical storms, its 10-year moving average has more than doubled over the past 50 years, from 2.15 in 1955 to 4.60 in 1992, with 16 of the past 20 years having a seasonal rate of 3 or more (the median rate). For hurricanes and major hurricanes, their 10-year moving averages turned upward, rising above long-term median rates (5.5 and 2, respectively) in 1992, following a 25-year lull in activity. Taken together, the outlook for this year and immediately succeeding years is for all categories of Atlantic basin tropical cyclones to have seasonal rates at levels equal to or above their long-term median rates, especially during non-El Nino-related seasons. Only during El Nino-related seasons does it appear that seasonal rates might be slightly diminished.

Wilson, Robert M.↗
NASA NTRS2001

Decadal Trends of Atlantic Basin Tropical Cyclones (1950-1999)

Ten-year moving averages of the seasonal rates for 'named storms,' tropical storms, hurricanes, and major (or intense) hurricanes in the Atlantic basin suggest that the present epoch is one of enhanced activity, marked by seasonal rates typically equal to or above respective long-term median rates. As an example, the 10-year moving average of the seasonal rates for named storms is now higher than for any previous year over the past 50 years, measuring 10.65 in 1994, or 2.65 units higher than its median rate of 8. Also, the 10-year moving average for tropical storms has more than doubled, from 2.15 in 1955 to 4.60 in 1992, with 16 of the past 20 years having a seasonal rate of three or more (the median rate). For hurricanes and major hurricanes, their respective 10-year moving averages turned upward, rising above long-term median rates (5.5 and 2, respectively) in 1992, a response to the abrupt increase in seasonal rates that occurred in 1995. Taken together, the outlook for future hurricane seasons is for all categories of Atlantic basin tropical cyclones to have seasonal rates at levels equal to or above long-term median rates, especially during non-El Nino-related seasons. Only during El Nino-related seasons does it appear likely that seasonal rates might be slightly diminished.

Wilson, Robert M.↗
NASA NTRS2015

Hazard Assessment from Storm Tides and Rainfall on a Tidal River Estuary

Here, we report on methods and results for a model-based flood hazard assessment we have conducted for the Hudson River from New York City to Troy/Albany at the head of tide. Our recent work showed that neglecting freshwater flows leads to underestimation of peak water levels at up-river sites and neglecting stratification (typical with two-dimensional modeling) leads to underestimation all along the Hudson. As a result, we use a three-dimensional hydrodynamic model and merge streamflows and storm tides from tropical and extratropical cyclones (TCs, ETCs), as well as wet extratropical cyclone (WETC) floods (e.g. freshets, rain-on-snow events). We validate the modeled flood levels and quantify error with comparisons to 76 historical events. A Bayesian statistical method is developed for tropical cyclone streamflows using historical data and consisting in the evaluation of (1) the peak discharge and its pdf as a function of TC characteristics, and (2) the temporal trend of the hydrograph as a function of temporal evolution of the cyclone track, its intensity and the response characteristics of the specific basin. A k-nearest-neighbors method is employed to determine the hydrograph shape. Out of sample validation tests demonstrate the effectiveness of the method. Thus, the combined effects of storm surge and runoff produced by tropical cyclones hitting the New York area can be included in flood hazard assessment. Results for the upper Hudson (Albany) suggest a dominance of WETCs, for the lower Hudson (at New York Harbor) a case where ETCs are dominant for shorter return periods and TCs are more important for longer return periods (over 150 years), and for the middle-Hudson (Poughkeepsie) a mix of all three flood events types is important. However, a possible low-bias for TC flood levels is inferred from a lower importance in the assessment results, versus historical event top-20 lists, and this will be further evaluated as these preliminary methods and results are finalized. Future funded work will quantify the influences of sea level rise and flood adaptation plans (e.g. surge barriers). It would also be valuable to examine how streamflows from tropical cyclones and wet cool-season storms will change, as this factor will dominate at upriver locations.

Hazard assessment↗
NASA NTRS2014

Statistical Aspects of North Atlantic Basin Tropical Cyclones During the Weather Satellite Era, 1960-2013: Part 1

A tropical cyclone is described as a warm-core, nonfrontal, synoptic-scale system that originates over tropical or subtropical waters, having organized deep convection and closed surface wind circulation (counterclockwise in the Northern Hemisphere) about a well defined center. When its sustained wind speed equals 34-63 kt, it is called a tropical (or subtropical) storm and is given a name (i.e., alternating male and female names, beginning in 1979); when its sustained wind speed equals 64-95 kt, it is called a hurricane (at least in the Eastern Pacific and North Atlantic basin); and when its sustained wind speed equals 96 kt or higher, it is called an intense or major hurricane (i.e., categories 3-5 on the Saffir-Simpson Hurricane Wind Scale). Although tropical cyclones have been reported and described since the voyages of Columbus, a detailed record of their occurrences extends only from 1851 to the present, with the most reliable portion extending only from about 1945 to the present, owing to the use of near-continuous routine reconnaissance aircraft monitoring flights and the use of satellite imagery (beginning in 1960; see Davis). Even so, the record may still be incomplete, possibly missing at least one tropical cyclone per yearly hurricane season, especially prior to the use of continuous satellite monitoring. In fact, often an unnamed tropical cyclone is included in the year-end listing of events at the conclusion of the season, following post-season analysis (e.g., as happened in 2011 and 2013, each having one unnamed event). In this two-part Technical Publication (TP), statistical aspects of the North Atlantic basin tropical cyclones are examined for the interval 1960-2013, the weather satellite era. Part 1 examines some 25 parameters of tropical cyclones (e.g., frequencies, peak wind speed (PWS), accumulated cyclone energy (ACE), etc.), while part 2 examines the relationship of these parameters against specific climate-related factors. These studies are a continuation of nearly two decades of previous tropical cyclone-related investigations.

Wilson, Robert M.↗
DOE OSTI2021

Multi-cyclone analysis and machine learning model implications of cyclone effects on forests

Past studies of cyclones (hurricanes, typhoons, tropical cyclones) disturbance showed that meteorological, topographical, and biological factors affect the patterns of forest disturbance intensity but left open the extent to which these findings were representative across different global cyclone regions. Using remote sensing data and machine learning models, we examined how these factors change over spatial scales and assessed their consistency across four major cyclones: Katrina (August 2005), Rita (September 2005), Yasi (February 2011), and María (September 2017). Our results revealed that the factors which best explained forest disturbance intensity pattern varied across these regions. Wind speed and precipitation were the dominant factors contributing to the variation in impacts of Katrina; terrain features, especially elevation, explained most of the variation in disturbance intensity of Rita; pre-disturbance vegetation condition was significant predictors of effects of Yasi; these factors played equal roles in explaining the disturbance intensity variation of María. A 40 m/s (144 km/h) wind speed threshold was proposed to split low- and high-level forest disturbance intensity. Other than wind speed, few generalizations can be made on features across multiple regions. We built several generalized hurricane impact models, which worked well with the test data from cyclones used for model development (R 2 = 0.89). However, these models did not have good predictions on other cyclones, such as Michael (October 2018) and Laura (August 2020). This study showed that each cyclone interacted with the landscape in a unique way and the challenges remained in building a generalized cyclone impact model.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Application of the Global Precipitation Forecast dataset for Global Landslide Forecasting System

Landslides are extremely damaging, pervasive and cause fatalities and economic impacts. Extreme rainfall events, coupled with inopportune surface conditions, are the primary triggers of landslides around the world. Forecasting landslide events represent an area of open research. A global Landslide Hazard Assessment for Situational Awareness (LHASA) model has been created that provides near real-time dynamic landslide characterization using Integrated Multi-Satellite Retrievals for Global Precipitation Mission (IMERG). However, it does not provide information on prediction of landslides into future. This study considers how global precipitation forecast data compares to satellite rainfall at different spatiotemporal scales and outlines the potential for its use in landslide hazard prediction/forecasting system. NASA Goddard Earth Observing System (GEOS)-Forecast model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The GEOS-Forecast model is initialized at 00 UTC and is evaluated with IMERG Early, using Multi-Radar Multi-Sensor gauge corrected (MRMS-GC) precipitation product as a reference over contiguous United States (CONUS). Categorical and continuous statistics along with probability density functions and cumulative distribution functions are considered to assess the performance of the precipitation products, with a focus on landslide hotspots. Seasonality appears to influence the performance of both the GEOS-Forecast and IMERG Early product. Moreover, the global comparison between the GEOS-Forecast and IMERG Early is carried out in terms of percentile difference, correlation, and bias maps. For extreme rainfall events in regions such as Mekong, Colombia, and Tajikistan, GEOS-Forecast appears to resolve high rainfall relative to IMERG Early more frequently. Validation over landslide points reveal that for 24hr rainfall accumulations > 100mm, GEOS-Forecast and IMERG coincide. GEOS-Forecast and IMERG Early precipitation matches more closely for tropical cyclones than other types of storms. Overall, the performance varies with respect to location, rainfall intensities, and type of precipitation events.

Sana Khan↗
NASA NTRS2012

The Impact of Dry Midlevel Air on Hurricane Intensity in Idealized Simulations with No Mean Flow

This study examines the potential negative influences of dry midlevel air on the development of tropical cyclones (specifically, its role in enhancing cold downdraft activity and suppressing storm development). The Weather Research and Forecasting model is used to construct two sets of idealized simulations of hurricane development in environments with different configurations of dry air. The first set of simulations begins with dry air located north of the vortex center by distances ranging from 0 to 270 km, whereas the second set of simulations begins with dry air completely surrounding the vortex, but with moist envelopes in the vortex core ranging in size from 0 to 150 km in radius. No impact of the dry air is seen for dry layers located more than 270 km north of the initial vortex center (approximately 3 times the initial radius of maximum wind). When the dry air is initially closer to the vortex center, it suppresses convective development where it entrains into the storm circulation, leading to increasingly asymmetric convection and slower storm development. The presence of dry air throughout the domain, including the vortex center, substantially slows storm development. However, the presence of a moist envelope around the vortex center eliminates the deleterious impact on storm intensity. Instead, storm size is significantly reduced. The simulations suggest that dry air slows intensification only when it is located very close to the vortex core at early times. When it does slow storm development, it does so primarily by inducing outward- moving convective asymmetries that temporarily shift latent heating radially outward away from the high-vorticity inner core.

Weather Research and Forecasting model↗
DOE OSTI2022

Evaluating the Influence of CAM5 Aerosol Configuration on Simulated Tropical Cyclones in the North Atlantic

This study examines the influence of prescribed and prognostic aerosol model configurations on the formation of tropical cyclones (TCs) in the North Atlantic Ocean in Community Atmosphere Model version 5 (CAM5). The impact of aerosol parameterization is examined by investigating storm track density, genesis density, potential intensity, and genesis potential index. This work shows that both CAM5 configurations simulate reduced storm frequency when compared to observations and that differences in TC climatology between the model configurations can be explained by differences in the large-scale environment. The analysis shows that simulation with the prognostic aerosol parameterization scheme reasonably captures the observed interannual variability in tropical cyclones and aerosols (i.e., dust) in the North Atlantic, while simulation with the prescribed configuration (climatology) is less favorable. The correlation between dust and TCs in observations (i.e., reanalysis and satellite datasets) is shown to be negative, and this relationship was also found for the prognostic aerosol configuration despite an overall decrease in the frequency of TCs. This indicates that, to accurately replicate certain aspects of TC interannual variability, the aerosol configuration within CAM5 needs to account for the appropriate dust variability.

Huff, J. Jacob A. (ORCID:0000000329143817)↗
DOE OSTI2025

Simulating Hurricane Katrina in the Simple Cloud‐Resolving E3SM Atmosphere Model v1

Climate models are important tools for advancing understanding and prediction of tropical cyclones (TCs). Traditional global climate models, however, do not have the ability to properly simulate TC intensity due to their coarse horizontal resolution. Regional models can be run at convection‐permitting resolutions, but these models are often strongly influenced by the data used in the lateral boundary forcing, and domain choice can have a large impact on the simulation. Cloud‐resolving global climate models have demonstrated great potential for realism in TC simulations, and in this study we focus specifically on the Simple Cloud‐Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM) v1 configuration. We evaluate SCREAMv1 against the observational record and the Weather Research and Forecasting (WRF) model run at a convection‐permitting resolution with Hurricane Katrina as our case study. We found that both models produced realistic simulations of Hurricane Katrina. SCREAMv1 demonstrated skill in simulating TC track, size, and intensity, while the model produced an excessive amount of precipitation. In comparison, WRF more accurately simulated TC precipitation and intensity, although the TC wind extent was smaller than the observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Life Cycle Cost Analysis of Prestressed Concrete Poles Subjected to Wind, Surges, and Waves

Prestressed concrete (PC) poles are becoming popular choices to support coastal power transmission systems. However, the existing literature does not offer a detailed analysis of the effectiveness of PC poles in terms of long-term vulnerabilities and the direct and indirect costs. This is due to (1) lack of fragility models for PC poles and (2) lack of probabilistic wind, storm surge, and wave models in coastal settings. In this study, we address these gaps through a series of Monte Carlo simulations to estimate fragility of PC poles as a function of age and hazard (wind, surges, and waves) intensity, and the development of a probabilistic hazard model based on 10,000 years of synthetic tropical cyclone data. The probabilistic hazard model is used in conjunction with high-resolution hydrodynamic models to generate realizations of coastal wind, storm surges, and waves for the Louisiana and Mississippi coasts. A comprehensive life cycle cost analysis for a service life of 70 years considering direct and indirect losses is conducted to compare the performance of a transmission line located in Pascagoula, Mississippi, when wood poles are replaced by PC poles. Results showed that aging has a minor effect on the reliability of PC poles, highlighting the advantages of replacing wood poles with PC poles, especially in coastal areas. In addition, PC poles are significantly more cost-effective compared with wood poles over their life cycle, leading to an estimated saving of $11.55 million (68.17% reduction). The results of this study provide key insight to inform decision-making processes to keep the coastal power grids resilient and cost-effective against future storm hazards.

natural disasters↗
NASA NTRS1986

Hurricane structure and wind fields from stereoscopic and infrared satellite observations and radar data

Hurricane cloud and precipitation structure have been studied by means of IR and stereoscopic visual satellite data from synchronized scanning GOES-East and -West, in combination with ground-based radar data for Hurricane Frederico and time-composited airborne radar data for Hurricane Allen. It is noted that stereoscopically measured cloudtop height in these hurricanes is not as closely correlated to radar reflectivity at lower levels as it is in intense thunderstorms over land. This and other results obtained imply that satellite precipitation estimation techniques for tropical cyclones that are based on cloudtop measurements will not be accurate with respect to time and place scales that are less than several hours and a few hundred km, respectively.

Hasler, A. F.↗
NASA NTRS2008

Simulation of the Impact of New Aircraft and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses

Accurate observations of surface ocean vector winds (OVW) with high spatial and temporal resolution are required for understanding and predicting tropical cyclones. As NASA's QuikSCAT and Navy's WindSat operate beyond their design life, many members of the weather and climate science communities recognize the importance of developing new observational technologies and strategies to meet the essential need for OVW information to improve hurricane intensity and location forecasts. The Hurricane Imaging Radiometer (HIRAD) is an innovative technology development which offers new and unique remotely sensed satellite observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR), which is the only proven remote sensing technique for observing tropical cyclone (TC) ocean surface wind speeds and rain rates. The proposed HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology. This sensor will operate over 4-7 GHz (C-band frequencies) where the required TC remote sensing physics has been validated by both SFMR and WindSat radiometers. The instrument is described in more detail in a paper by Jones et al. presented to the Tropical Meteorology Special Symposium at this AMS Annual Meeting. Simulated HIRAD passes through a simulation of hurricane Frances are being developed to demonstrate HIRAD estimation of surface wind speed over a wide swath in the presence of heavy rain. These are currently being used in "quick" OSSEs (Observing System Simulation Experiments) with H'Wind analyses as the discriminating tool. The H'Wind analysis, a product of the Hurricane Research Division of NOAA's Atlantic , Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa._ov/hrd/data sub/wind.html. Observations have been simulated from both aircraft altitudes and space. The simulated flight patterns for the aircraft platform cases have been designed to duplicate the timing and flight patterns used in routine NOAA and USAF hurricane surveillance flights, and the spaceborne case simulates a TRMM orbit and altitude.

Miller, TImothy L.↗
DOE OSTI2022

Unveiling four decades of intensifying precipitation from tropical cyclones using satellite measurements

Increases in precipitation rates and volumes from tropical cyclones (TCs) caused by anthropogenic warming are predicted by climate modeling studies and have been identified in several high intensity storms occurring over the last half decade. However, it has been difficult to detect historical trends in TC precipitation at time scales long enough to overcome natural climate variability because of limitations in existing precipitation observations. We introduce an experimental global high-resolution climate data record of precipitation produced using infrared satellite imagery and corrected at the monthly scale by a gauge-derived product that shows generally good performance during two hurricane case studies but estimates higher mean precipitation rates in the tropics than the evaluation datasets. General increases in mean and extreme rainfall rates during the study period of 1980–2019 are identified, culminating in a 12–18%/40-year increase in global rainfall rates. Overall, all basins have experienced intensification in precipitation rates. Increases in rainfall rates have boosted the mean precipitation volume of global TCs by 7–15% over 40 years, with the starkest rises seen in the North Atlantic, South Indian, and South Pacific basins (maximum 59–64% over 40 years). In terms of inland rainfall totals, year-by-year trends are generally positive due to increasing TC frequency, slower decay over land, and more intense rainfall, with an alarming increase of 81–85% seen from the strongest global TCs. As the global trend in precipitation rates follows expectations from warming sea surface temperatures (11.1%/°C), we hypothesize that the observed trends could be a result of anthropogenic warming creating greater concentrations of water vapor in the atmosphere, though retrospective studies of TC dynamics over the period are needed to confirm.

54 ENVIRONMENTAL SCIENCES↗