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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Genesis of Twin Tropical Cyclones as Revealed by a Global Mesoscale Model: The Role of Mixed Rossby Gravity Waves

In this study, it is proposed that twin tropical cyclones (TCs), Kesiny and 01A, in May 2002 formed in association with the scale interactions of three gyres that appeared as a convectively coupled mixed Rossby gravity (ccMRG) wave during an active phase of the Madden-Julian Oscillation (MJO). This is shown by analyzing observational data, including NCEP reanalysis data and METEOSAT 7 IR satellite imagery, and performing numerical simulations using a global mesoscale model. A 10-day control run is initialized at 0000 UTC 1 May 2002 with grid-scale condensation but no sub-grid cumulus parameterizations. The ccMRG wave was identified as encompassing two developing and one non-developing gyres, the first two of which intensified and evolved into the twin TCs. The control run is able to reproduce the evolution of the ccMRG wave and thus the formation of the twin TCs about two and five days in advance as well as their subsequent intensity evolution and movement within an 8-10 day period. Five additional 10-day sensitivity experiments with different model configurations are conducted to help understand the interaction of the three gyres, leading to the formation of the TCs. These experiments suggest the improved lead time in the control run may be attributed to the realistic simulation of the ccMRG wave with the following processes: (1) wave deepening (intensification) associated with a reduction in wavelength and/or the intensification of individual gyres, (2) poleward movement of gyres that may be associated with boundary layer processes, (3) realistic simulation of moist processes at regional scales in association with each of the gyres, and (4) the vertical phasing of low- and mid-level cyclonic circulations associated with a specific gyre.

forecast↗
NASA NTRS2018

Nasa GEOS Model for Sub-Seasonal to Seasonal Predictions: The Major Teleconnections, Tropical Cyclone Activity, and ENSO

Ability of the NASA GEOS seasonal prediction model system (the latest version) in predicting the large-scale teleconnections, tropical cyclone (TC) activity, and ENSO are validated. The major large-scale teleconnections include the North Atlantic Oscillation (NAO), the Arctic Oscillation (AO), and the Pacific North American (PNA) that span vast geographical area across the North Pacific/Atlantic and North America. Predictive skill of TC activity is assessed by Genesis potential index (GPI). Anomaly correlations are greater than 0.5 for winter teleconnections at up to 2 month lead and for the first four month (June- July-August-September) GPIs over the North Atlantic and the Western Pacific. Correlation for the long-range prediction of the ENSO (Nino3.4 SST) maturity reaches 0.9 at 6 month lead and 0.8 at 9 month lead.

Lim, Young-Kwon↗
NASA NTRS1980

Tropical cyclone intensities from satellite microwave data

Radial profiles of mean 1000 mb to 250 mb temperature from the Nimbus 6 scanning microwave spectrometer (SCAMS) were constructed around eight intensifying tropical storms in the western Pacific. Seven storms showed distinct inward temperature gradients required for intensification; the eighth displayed no inward gradient and was decaying 24 hours later. The possibility that satellite data might be used to forecast tropical cyclone turning motion was investigated using estimates obtained from Nimbus 6 SCAMS data tapes of the mean 1000 mb to 250 mb temperature field around eleven tropical storms in 1975. Analysis of these data show that for turning storms, in all but one case, the turn was signaled 24 hours in advance by a significant temperature gradient perpendicular to the storm's path, at a distance of 9 deg to 13 deg in front of the storm. A thresholding technique was applied to the North Central U.S. during the summer to estimate precipitation frequency. except

Vonderhaar, T. H.↗
NASA NTRS1978

The benefits of using short interval satellite images to derive winds for tropical cyclones

During the 1975, 1976, and 1977, NOAA's National Environmental Satellite Service and NASA's Goddard Space Flight Center conducted a cooperative program to determine the optimum resolution and frequency of satellite images for deriving winds to study and forecast tropical cyclones. Rapid scan images were obtained at 7.5 minute interval from SMS-2 for hurricane Eloise and cyclone Caroline, and at 3 minute intervals from GOES-1 for tropical storms Belle, Holly, and Anita. Cloud motions were derived from these images using the Atmospheric and Oceanographic Information Processing System. Winds that were derived from the movement of upper and lower tropospheric level clouds using rapid scan data were compared with the 15 and 30 minute interval data. Greater than 10 (5) times as many clouds could be tracked to obtain winds using 3 and 7.5 minute rapid scan images as when using 15 or 30 minute interval images. A few bright areas within the central dense overcast which appeared to be moving with the winds at low levels were tracked.

Rodgers, E.↗
NASA NTRS2000

Tropical Cyclone Lightning Distribution and Its Relationship to Convection and Intensity Change

The long distance National Lightning Detection Network (NLDN) was used to monitor the distribution of lightning strokes in various 1998 and 1999 western North Atlantic tropical cyclones. These ground-based lightning observations together with the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and the Tropical Rain Mapping Mission (TRMM) Microwave Instrument (TMI) derived convective rain rates were used to monitor the propagation of electrically charged convective rain bands aid to qualitatively estimate intensification. An example of the lightning analyses was performed on hurricane George between 25-28 September, 1998 when the system left Key West and moved towards the Louisiana coast. During this period of time, George's maximum winds increased from 38 to 45 meters per second on 25 September and then remained steady state until it made landfall. Time-radius displays of the lightning strokes indicated that the greatest number of lightning strokes occurred within the outer core region (greater than 165 km) with little or no lightning strokes at radii less than 165 km. The trend in these lightning strokes decreased as George move into the Gulf of Mexico and showed no inward propagation. The lack inward propagating lightning strokes with time indicated that there was no evidence that an eye wall replacement was occurring that could alter George's intensity. Since George was steady state at this time, this result is not surprising. Time-azimuth displays of lightning strokes in an annulus whose outer and inner radii were respectively, 222 and 333 km from George's center were also constructed. A result from this analysis indicated that the maximum number of strokes occurred in the forward and rear right quadrant when George was over the Gulf of Mexico. This result is, consistent with the aircraft and satellite observations of maximum rainfall.

Rodgers, Edward↗
NASA NTRS1986

Pattern recognition analysis of satellite data for tropical cyclone motion and intensity forecasts

An objective empirical analysis technique is employed to investigate the extent to which satellite-obtained measurements (GOES IR and TOVS data) of a tropical cyclone and its environment can be used to predict cyclone motion. The paper describes the procedure used to process the satellite derived data in order to optimize their possible predictive value, the technique used in developing the regression algorithms, and the results of testing these algorithms using the Lachenbrach and Mickey (1968) procedure. The data were examined alone and in conjunction with available nonsatellite climatological and persistence variables for each storm. These predictors are similar to those used in the National Hurricane Center (NHC) CLIPPER model. The performances obtained using the Nichols Research Corporation CLIPPER model and the NHC CLIPPER model are compared, using homogeneous data sets for the comparisons. Major differences in results were found to be related to differences in the models.

Hunter, Herbert↗
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 NTRS1986

The relationship between satellite measured convective bursts and tropical cyclone intensification

High temporal resolution satellite IR measurements are used to analyze the relationship between the mean temperature of cloud canopy tops and the future maximum winds of Atlantic Ocean tropical cyclones. The measurements showed that prolonged surges of intense convection developed in the rear region surrounding cyclone depression centers before the maximum winds initially increased. When surges lasted for 9 hr or more, and the cloud-top temperature within 222 km of the cyclone centers was 238 K or less, then 71 percent of the time the maximum winds increased by 5 m/s or more within 24 hr. When intense convection was not present, similar maximum wind increases occurred only 37 percent of the time.

Steranka, J.↗
NASA NTRS2001

AMSU-A Tropical Cyclone Maximum Sustained Winds and Web Site

The Advanced Microwave Sounding Unit (AMSU)-A instruments on the NOAA-15 and NOAA-16 satellites provide information on the warm cores of tropical cyclones from oxygen channel brightness temperature (Tb) measurements near 55 GHz. With appropriate assumptions, cyclone-scale Tb gradients can be directly related to middle-to-lower tropospheric height gradients. We have developed a method for diagnosis of maximum sustained winds (Vmax) from radially averaged Tb gradients in several of the AMSU channels. Calibration of the method with recon-based (or other in situ) winds results in better agreement than with Dvorak wind estimates. Gradient wind theory shows that the warm core Tb gradient signal increases non-linearly with wind speed, making microwave temperature sounders useful for diagnosing high wind speeds, but at the expense of a minimum useful detection limit of about 40 knots. It is found that accurate wind diagnoses depend upon (1) accounting for hydrometeor effects in the AMSU channels, and (2) maximizing signal-to-noise, since the 50 km resolution data cannot fully resolve the temperature gradients in the Vmax region, typically 10-20 km in scale. AMSU imagery and max diagnoses from specific hurricanes will be shown, including independent tests from the 2000 hurricane season.

Spencer, Roy↗
NASA NTRSDate not supplied

Objectively Identifying Transverse Cirrus Bands in Tropical Cyclones using a Convolutional Neural Network

Transverse cirrus bands (TCBs) are bands of upper-level clouds that are regularly seen in mesoscale and synoptic-scale weather systems. In tropical cyclones, their appearance has been subjectively linked to intensification and the diurnal cycle, but these hypothesized relationships have not been rigorously tested due to the difficulty of objectively identifying TCBs in satellite images. This presentation describes a machine learning technique that successfully identifies TCBs in imagery from the GOES-16 Advanced Baseline Imager. The technique uses a convolutional neural network (CNN) that assigns a probability of each pixel in the image being associated with a TCB. Using the CNN, a database of TCBs from 2018 to 2022 was developed for the Atlantic basin. Statistics using this database will be presented, including the relationship between TCBs and deep-layer vertical wind shear, intensity change, and the TC diurnal cycle.

John Mark Mayhall↗
NASA NTRS2010

Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis(2008)

Very severe cyclonic storm Nargis devastated Burma (Myanmar) in May 2008, caused tremendous damage and numerous fatalities, and became one of the 10 deadliest tropical cyclones (TCs) of all time. To increase the warning time in order to save lives and reduce economic damage, it is important to extend the lead time in the prediction of TCs like Nargis. As recent advances in high-resolution global models and supercomputing technology have shown the potential for improving TC track and intensity forecasts, the ability of a global mesoscale model to predict TC genesis in the Indian Ocean is examined in this study with the aim of improving simulations of TC climate. High-resolution global simulations with real data show that the initial formation and intensity variations of TC Nargis can be realistically predicted up to 5 days in advance. Preliminary analysis suggests that improved representations of the following environmental conditions and their hierarchical multiscale interactions were the key to achieving this lead time: (1) a westerly wind burst and equatorial trough, (2) an enhanced monsoon circulation with a zero wind shear line, (3) good upper-level outflow with anti-cyclonic wind shear between 200 and 850 hPa, and (4) low-level moisture convergence.

Shen, B.-W.↗
NASA NTRS1995

Condensed Water in Tropical Cyclone "Oliver", 8 February 1993

On February 8, 1993, the NASA DC-8 aircraft profiled from 10,000 to 37,000 feet (3.1-11.3 km) pressure altitude in a stratified section of tropical cyclone "Oliver" over the Coral Sea northeast of Australia. Size, shape and phase of cloud and precipitation particles were measured with a 2-D Greyscale probe. Cloud/precipitation particles changed from liquid to ice as soon as the freezing level was reached near 17,000 feet (5.2 km) pressure altitude. The cloud was completely glaciated at -5 C. There was no correlation between ice particle habit and ambient temperature. In the liquid phase, the precipitation-cloud drop concentration was 4.0 x 10(exp 3)/cu m, the geometric mean diameter D(sub g) = 0.5-0.7 mm, and the liquid water content 0.7-1.9 g m(exp-3). The largest particles anywhere in the cloud, dominated by fused dendrites at concentrations similar to that of raindrops (2.5 x 10(exp 3) m(exp -3)) but a higher condensed water content(5.4 g/cu m estimated) were found in the mixed phase; condensed water is removed very effectively from the mixed layer due to high settling velocities of the large mixed particles. The highest number concentration (4.9 x 10(exp 4)/cu m, smallest size (D(sub g) = 0.3-0.4 mm), largest surface area (up to 2.6 x 10 (exp 2) sq cm/cu m at 0.4- 1.0 g/cu m of condensate) existed in the ice phase at the coldest temperature (- 40 C) at 35,000 feet ( 10.7 km). Each cloud contained aerosol (haze particles) in addition to cloud particles. The aerosol total surface area exceeded that of the cirrus particles at the coldest temperature. Thus, aerosols must play a significant role in the upscattering of solar radiation. Light extinction (6.2/km) and backscatter (0.8/sr/km) was highest in the coldest portion of the cirrus cloud at the highest altitude.

Pueschel, R. F.↗
NASA NTRS2019

Assimilation of Microwave Observations in the Rainbands of Tropical Cyclones

We propose a novel Bayesian Monte Carlo Integration (BMCI) technique to retrieve the profiles of temperature, water vapor, and cloud liquid/ice water content from microwave cloudy measurements in the presence of tropical cyclones (TC). These retrievals then can either be directly used by meteorologists to analyze the structure of TCs or be assimilated into numerical models to provide accurate initial conditions for the NWP (Numerical Weather Prediction) models. The BMCI technique is applied to the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and Global Precipitation Measurement (GPM) Microwave Imager (GMI). The retrieved profiles are then assimilated into Hurricane WRF (Weather Research and Forecasting) using the GSI (Gridpoint Statistical Interpolation) data assimilation system.

Moradi, Isaac↗
NASA NTRS2016

Surface Stress in Tropical Cyclone Observed by Scatterometer

Ocean surface wind (U) is air in motion and stress (τ) is the turbulent transport of momentum between the ocean and the atmosphere. While the strong wind of a tropical cyclone (TC) causes destruction at landfall, it is the surface stress that drags down the TC. There was almost no stress measurement except in dedicated field campaigns and the stress we used was almost entirely derived from wind through a drag coefficient (C(sub D)), as defined by C(sub D) = τ / ( ρ U(exp 2)). In TC, there is difficulty in measuring strong wind and large uncertainty in the drag coefficient.

Liu, W. Timothy↗
NASA NTRSDate not supplied

Machine-Learning-Based Adaptive Thinning of CrIS Radiances to Improve Global Tropical Cyclone Analysis and Forecasts

This work is focused on optimizing the assimilation of hyperspectral infrared (IR) radiances from the Cross-track Infrared Sounder (CrIS) with the goal of improving the representation of tropical cyclones (TCs) in global analyses and forecasts. Current operational assimilation systems rely on subsampling IR radiances on a regular thinning grid. A new and improved adaptive methodology based on machine learning (ML) recognizes TCs from geostationary satellite imagery and is implemented in the Goddard Earth Observing System (GEOS) model and data assimilation framework. The ML methodology is extensively trained on existing TC data sets and creates for each TC a dynamic mask, based on the evolving shape and life cycle of that specific event. Once a TC mask is created, a switch is then activated in the data assimilation system to alter the thinning, ingesting more CrIS radiances within the moving mask, thus increasing the TC sampling. After the TC dissipates, the assimilation of CrIS radiances reverts to normal data density. Results of TC segmentation provided by a state-of-the-art generative machine learning model known as the Denoising Diffusion Probabilistic Model (DDPM) are compared to the previously used U-Net model. The new approach surpasses the performance of the previously developed one. The methodology is applied to both clear-sky and cloud-cleared radiances. Benefits from the latter methodology, particularly in improving the structure of TCs and the intensity forecasts, are presented.

Oreste Reale↗
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 OSTI2022

Declining tropical cyclone frequency under global warming

Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Assessing the Sensitivity of the Tropical Cyclone Boundary Layer to the Parameterization of Momentum Flux in the Community Earth System Model

Recent studies have demonstrated that high-resolution (~25 km) Earth System Models (ESMs) have the potential to skillfully predict tropical cyclone (TC) occurrence and intensity. However, biases in ESM TCs still exist, largely due to the need to parameterize processes such as boundary layer (PBL) turbulence. Building on past studies, we hypothesize that the depiction of the TC PBL in ESMs is sensitive to the configuration of the PBL parameterization scheme, and that the targeted perturbation of tunable parameters can reduce biases. The Morris one-at-a-time (MOAT) method is implemented to assess the sensitivity of the TC PBL to tunable parameters in the PBL scheme in an idealized configuration of the Community Atmosphere Model, version 6 (CAM6). The MOAT method objectively identifies several parameters in an experimental version of the Cloud Layers Unified by Binormals (CLUBB) scheme that appreciably influence the structure of the TC PBL. We then perturb the parameters identified by the MOAT method within a suite of CAM6 ensemble simulations and find a reduction in model biases compared to observations and a high-resolution, cloud-resolving model. Importantly, we demonstrate that the high-sensitivity parameters are tied to PBL processes that reduce turbulent mixing and effective eddy diffusivity, and that in CAM6 these parameters alter the TC PBL in a manner consistent with past modeling studies. In this way, we provide an initial identification of process-based input parameters that, when altered, have the potential to improve TC predictions by ESMs.

54 ENVIRONMENTAL SCIENCES↗