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NASA NTRS2009

Integrating and Visualizing Tropical Cyclone Data Using the Real Time Mission Monitor

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the NASA Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM is extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, scientists, and managers appreciate the contributions that RTMM makes to their flight projects. A broad spectrum of interdisciplinary scientists used RTMM during field campaigns including the hurricane-focused 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 NOAA-NASA Aerosonde Hurricane Noel flight, 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), plus a soil moisture (SMAP-VEX) and two arctic research experiments (ARCTAS) in 2008. Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated "on the fly". The resultant flight plan is then immediately posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and subsequently compare it to the actual real time flight progress. We are planning additional capabilities to RTMM including collaborations with the Jet Propulsion Laboratory in the joint development of a Tropical Cyclone Integrated Data Exchange and Analysis System (TC IDEAS) which will serve as a web portal for access to tropical cyclone data, visualizations and model output.

Goodman, H. Michael↗

NASA NTRS2018

Tropical Cyclone Intensity Estimation Using Deep Convolutional Neural Networks

Estimating tropical cyclone intensity by just using satellite image is a challenging problem. With successful application of the Dvorak technique for more than 30 years along with some modifications and improvements, it is still used worldwide for tropical cyclone intensity estimation. A number of semi-automated techniques have been derived using the original Dvorak technique. However, these techniques suffer from subjective bias as evident from the most recent estimations on October 10, 2017 at 1500 UTC for Tropical Storm Ophelia: The Dvorak intensity estimates ranged from T2.3/33 kt (Tropical Cyclone Number 2.3/33 knots) from UW-CIMSS (University of Wisconsin-Madison - Cooperative Institute for Meteorological Satellite Studies) to T3.0/45 kt from TAFB (the National Hurricane Center's Tropical Analysis and Forecast Branch) to T4.0/65 kt from SAB (NOAA/NESDIS Satellite Analysis Branch). In this particular case, two human experts at TAFB and SAB differed by 20 knots in their Dvorak analyses, and the automated version at the University of Wisconsin was 12 knots lower than either of them. The National Hurricane Center (NHC) estimates about 10-20 percent uncertainty in its post analysis when only satellite based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to tropical cyclone intensity. This study aims to utilize deep learning, the current state of the art in pattern recognition and image recognition, to address the need for an automated and objective tropical cyclone intensity estimation. Deep learning is a multi-layer neural network consisting of several layers of simple computational units. It learns discriminative features without relying on a human expert to identify which features are important. Our study mainly focuses on convolutional neural network (CNN), a deep learning algorithm, to develop an objective tropical cyclone intensity estimation. CNN is a supervised learning algorithm requiring a large number of training data. Since the archives of intensity data and tropical cyclone centric satellite images is openly available for use, the training data is easily created by combining the two. Results, case studies, prototypes, and advantages of this approach will be discussed.

tropical cyclone intensity↗

NASA NTRS2003

Comparisons and Contrasts Between Mediterranean Flood-Producing Orographic Storms and Tropical Cyclones Modified by Complex Orography

Often, late-year, flood-producing storms in the Mediterranean Alps region arise from baroclinic disturbances developing on westerly longwaves, with the incipient storm circulations appearing well west of the flood zone. Regardless of the genesis locations and before the storms begin their flow interactions with the orography of the Mediterranean Alps, a process which can produce intense long-lived rainfall over the mountainous terrain of Italy and France, most of their moisture is drawn from warm Mediterranean waters while important elements of their thermodynamic structure are derived from airmass properties originating in north Africa and the Mediterranean basin itself. In fact, because of strong thermodynamic contrasts between the baroclinic zone producing the incipient disturbance and high potential temperature air from the south advecting into and wrapping around the storm center, a Mediterranean storm whose origins are from an evolving shortwave baroclinic perturbation, can become a quasi-warm core hybrid in term of its energetics composition, a process somewhat akin to the development of polar lows. This process begs the question of whether there are similarities between the autumn-winter season flood producing storms of the Mediterranean Alps and warm core tropical cyclones which become altered dynamically and thermodynamically by landfall over steep orographic terrain. This study investigates, from a comparison and contrast perspective, how the similarities and differences between the two types of storms manifest themselves over their respective life cycles. Before the orographically-induced precipitation-release stage in which both types of storm have evolved to the same hydrometeorlogical conclusion, the two storm categories are transforming from entirely distinctive origins, i.e., the classic eastward traveling, baroclinic mid-latitude cyclone forming in western Europe, and the classic eastward-traveling, warm core tropical cyclone developing in the western Pacific. The analyses use high resolution, nonhydrostatic model simulations, satellite data, and various types of ground data to conduct the study. The flood events of Piemonte- 2000 in northern Italy and Typhoon Rusa-2002 in South Korea are selected to focus the analysis on well documented meteorological events.

Smith, Eric A.↗

NASA NTRSDate not supplied

Estimating Tropical Cyclone Threats to Floating Rigs in the Gulf of Mexico

Offshore drilling operations in the Gulf of Mexico are particularly vulnerable during hurricane season. When a weather threat arises, a decision to evacuate the rig and/or move to a safe location may need to be made. Depending on the activities in progress at the time of the threat, securing the well, evacuating, and/or moving to a safe location can take a considerable amount of time. This transition time is called T-time. T-time is not only rig dependent, but also depends on the activity being performed at the time of the threat. For these reasons it is important to assess tropical cyclone threats and the time it takes for them to reach the rig location. The objective of this study is to use the available 50 years of past cyclone history to estimate cyclone threats at any location in the Gulf of Mexico. The cyclone threat is estimated based on the rig location as well as the start date and duration of the offshore activity. By threat, it is meant the likelihood that a specific location with an associated offshore activity would be exposed to an upcoming cyclone whose forecasted track cone and storm size lies within that location. Three representative rig locations in the Gulf of Mexico were selected as assessment sites to evaluate the threat of incoming cyclones for different T-times. To conduct this tropical cyclone study, an Excel spreadsheet tool was developed to automate the analysis of the tropical cyclone data from the Best Track Archive for Climate Stewardship (IBTrACS) Version 4. The spreadsheet tool allows the user to input any location (i.e., longitude and latitude) in the Gulf of Mexico and displays a list of historical cyclones that have passed within 150 nautical miles of that location during the activity period selected by the user. Also, the tool allows the user to input a T-time to assess the threat of cyclones that would not provide adequate time to secure the well, evacuate, and/or move to a safe location.

Risk↗

NASA NTRS2022

Estimating Tropical Cyclone Threats to Floating Rigs in the Gulf of Mexico

Offshore drilling operations in the Gulf of Mexico are particularly vulnerable during hurricane season. When a weather threat arises, a decision to evacuate the rig and/or move to a safe location may need to be made. Securing the well, evacuating, and/or moving to a safe location can take a considerable amount of time. This transition time is called T-time. T-time is not only rig dependent, but also depends on the activity being performed at the time of the threat. For these reasons, it is important to assess tropical cyclone threats and the estimated time it will take the storm to reach the rig location from the time it is first detected. The objective of this study is to use 50 years of cyclone history from a National Oceanic and Atmospheric Administration’s (NOAA) database, the International Best Track Archive for Climate Stewardship (IBTrACS) to estimate cyclone threats at any location in the Gulf of Mexico. The cyclone threat is estimated based on the rig location as well as the start date and duration of the offshore activity. By threat, it is meant the likelihood that a specific location with an associated offshore activity lies within the forecasted track cone and storm size of the upcoming cyclone. Three representative rig locations in the Gulf of Mexico were selected as assessment sites to evaluate the threat of incoming cyclones for different T-times. To conduct this tropical cyclone study, an Excel spreadsheet tool was developed to automate the analysis of the tropical cyclone data. The spreadsheet tool allows the user to input any location (i.e., longitude and latitude) in the Gulf of Mexico and displays a list of historical cyclones that have passed within 150 nautical miles of that location during the activity period selected by the user. In addition, the tool allows the user to input any T-time to assess the threat of cyclones that would not provide adequate time to secure the well, evacuate, and/or move to a safe location.

Offshore Oil Drilling↗

NASA NTRS2010

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

Putman, William M.↗

NASA NTRS2013

The Evolution and Role of the Saharan Air Layer During Hurricane Helene (2006)

The Saharan air layer (SAL) has received considerable attention in recent years as a potential negative influence on the formation and development of Atlantic tropical cyclones. Observations of substantial Saharan dust in the near environment of Hurricane Helene (2006) during the National Aeronautics and Space Administration (NASA) African Monsoon Multidisciplinary Activities (AMMA) Experiment (NAMMA) field campaign led to suggestions about the suppressing influence of the SAL in this case. In this study, a suite of satellite remote sensing data, global meteorological analyses, and airborne data are used to characterize the evolution of the SAL in the environment of Helene and assess its possible impact on the intensity of the storm. The influence of the SAL on Helene appears to be limited to the earliest stages of development, although the magnitude of that impact is difficult to determine observationally. Saharan dust was observed on the periphery of the storm during the first two days of development after genesis when intensification was slow. Much of the dust was observed to move well westward of the storm thereafter, with little SAL air present during the remainder of the storm's lifetime and with the storm gradually becoming a category-3 strength storm four days later. Dry air observed to wrap around the periphery of Helene was diagnosed to be primarily non-Saharan in origin (the result of subsidence) and appeared to have little impact on storm intensity. The eventual weakening of the storm is suggested to result from an eyewall replacement cycle and substantial reduction of the sea surface temperatures beneath the hurricane as its forward motion decreased.

Hurricane Helene↗

NASA NTRS2020

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗

NASA NTRS2015

Tropical Cyclone Diurnal Cycle as Observed by TRMM

Using infrared satellite data, previous work has shown a consistent diurnal cycle in the pattern of cold cloud tops around mature tropical cyclones. In particular, an increase in the coverage by cold cloud tops often occurs in the inner core of the storm around the time of sunset and subsequently propagates outward to several hundred kilometers over the course of the following day. This consistent cycle may have important implications for structure and intensity changes of tropical cyclones and the forecasting of such changes. Because infrared satellite measurements are primarily sensitive to cloud top, the goal of this study is to use passive and active microwave measurements from the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR), respectively, to examine and better understand the tropical cyclone diurnal cycle throughout a larger depth of the storm's clouds. The National Hurricane Center's best track dataset was used to extract all PR and TMI pixels within 1000 km of each tropical cyclone that occurred in the Atlantic basin between 1998-2011. Then the data was composited according to radius (100-km bins from 0-1000 km) and local standard time (LST; 3-hr bins). Specifically, PR composites involved finding the percentage of pixels with reflectivity greater than or equal to 20 dBZ at various heights (i.e., 2-14 km in increments of 2 km) as a function of radius and time. The 37- and 85- GHz TMI channels are especially sensitive to scattering by precipitation-sized ice in the mid to upper portions of clouds. Hence, the percentage of 37- and 85-GHz polarization corrected temperatures less than various thresholds were calculated using data from all storms as a function of radius and time. For 37 GHz, thresholds of 260 K, 265 K, 270 K, and 275 K were used, and for 85 GHz, thresholds of 200-270 K in increments of 10 K were utilized. Note that convection forced by the interactions of a tropical cyclone with land (e.g., due to frictional convergence) may disrupt the natural convective cycle of a cyclone. Hence, only data pertaining to storms whose centers were greater than 300 km from land were included in the composites. Early results suggest the presence of a diurnal cycle in the PR composites of all Atlantic basin tropical cyclones from a height of 2-12 km from approximately 0-400 km radius, but the cycle is most apparent above 6 km. At a height of 8 km, there is a peak (minimum) in the percentage of PR pixels greater than or equal to 20 dBZ near 0 (21) LST in the inner core with some indication that this signal propagates outward with time. In contrast, the 37- and 85-GHz composites show little indication of a diurnal cycle at any radii, regardless of the threshold used. Ongoing work with this project will involve sub-setting the composites according to storm intensity to see if the diurnal cycle varies with storm strength. Moderate to strong vertical wind shear often leads to asymmetries in tropical cyclone convection and may disrupt the cyclone's natural diurnal cycle. Therefore, wind shear thresholds will be applied to the composites to determine if the diurnal cycle becomes more apparent in a low shear environment. Finally, other work to be completed will involve developing composites for other tropical cyclone basins, including the East Pacific, Northwest Pacific, South Pacific, and Indian Ocean.

tropical cyclones↗

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 regularly seen in mesoscale and synoptic-scale weather systems. In tropical cyclones, their appearance has been subjectively linked to intensification and the diurnal cycle. However, these hypothesized relationships have not been rigorously tested due to the subjective nature of TCBs in satellite images. A machine learning technique that successfully identifies TCBs objectively in imagery from the GOES-16 Advanced Baseline Imager (ABI) has been developed to solve this problem. The technique uses a U-Net convolutional neural network (CNN) that assigns a probability to each pixel in an image based on the likelihood of the pixel being associated with a TCB. Using the U-Net CNN, a database of TCBs from 2019 to 2022 was developed for the Atlantic tropical cyclone basin by defining an appropriate probability threshold that defines the difference between TCB and non-TCB pixels. This threshold is where the Jaccard score, calculated using manually identified TCBs and model identified TCBs, is maximized. Statistics for TCB occurrence will also be presented, including the relationships between TCBs and storm relative motion, shear relative direction, cardinal direction, tropical cyclone intensity, tropical cyclone intensification rates, and time of day.

John Mark Mayhall↗

NASA NTRS2009

Attributing Tropical Cyclogenesis to Equatorial Waves in the Western North Pacific

The direct influences of equatorial waves on the genesis of tropical cyclones are evaluated. Tropical cyclogenesis is attributed to an equatorial wave when the filtered rainfall anomaly exceeds a threshold value at the genesis location. For an attribution threshold of 3 mm/day, 51% of warm season western North Pacific tropical cyclones are attributed to tropical depression (TD)-type disturbances, 29% to equatorial Rossby waves, 26% to mixed Rossby-Gravity waves, 23% to Kelvin waves, 13% to the Madden-Julian oscillation (MJO), and 19% are not attributed to any equatorial wave. The fraction of tropical cyclones attributed to TD-type disturbances is consistent with previous findings. Past studies have also demonstrated that the MJO significantly modulates tropical cyclogenesis, but fewer storms are attributed to the MJO than any other wave type. This disparity arises from the difference between attribution and modulation. The MJO produces broad regions of favorable conditions for cyclogenesis, but the MJO alone might not determine when and where a storm will develop within these regions. Tropical cyclones contribute less than 17% of the power in any portion of the equatorial wave spectrum because tropical cyclones are relatively uncommon equatorward of 15deg latitude. In regions where they are active, however, tropical cyclones can contribute more than 20% of the warm season rainfall and up to 50% of the total variance. Tropical cyclone-related anomalies can significantly contaminate wave-filtered precipitation at the location of genesis. To mitigate this effect, the tropical cyclone-related rainfall anomalies were removed before filtering in this study.

Schreck, Carl J., III↗

NASA NTRS2018

Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Assessment Using Dropsondes

The Hurricane Imaging Radiometer (HIRAD) is an experimental C-band passive microwave radiometer designed to map the horizontal structure of surface wind speed fields in hurricanes. New data processing and customized retrieval approaches were developed after the 2015 Tropical Cyclone Intensity (TCI) experiment, which featured flights over Hurricanes Patricia, Joaquin, Marty, and the remnants of Tropical Storm Erika. These new approaches produced maps of surface wind speed that looked more realistic than those from previous campaigns. Dropsondes from the High Definition Sounding System (HDSS) that was flown with HIRAD on a WB-57 high altitude aircraft in TCI were used to assess the quality of the HIRAD wind speed retrievals. The root mean square difference between HIRAD-retrieved surface wind speeds and dropsonde-estimated surface wind speeds was 6.0 meters per second. The largest differences between HIRAD and dropsonde winds were from data points where storm motion during dropsonde descent compromised the validity of the comparisons. Accounting for this and for uncertainty in the dropsonde measurements themselves, we estimate the root mean square error for the HIRAD retrievals as around 4.7 meters per second. Prior to the 2015 TCI experiment, HIRAD had previously flown on the WB-57 for missions across Hurricanes Gonzalo (2014), Earl (2010), and Karl (2010). Configuration of the instrument was not identical to the 2015 flights, but the methods devised after the 2015 flights may be applied to that previous data in an attempt to improve retrievals from those cases.

wind retrieval↗

NASA NTRS2010

Coarse, Intermediate and High Resolution Numerical Simulations of the Transition of a Tropical Wave Critical Layer to a Tropical Storm

Recent work has hypothesized that tropical cyclones in the deep Atlantic and eastern Pacific basins develop from within the cyclonic Kelvin cat's eye of a tropical easterly wave critical layer located equatorward of the easterly jet axis. The cyclonic critical layer is thought to be important to tropical cyclogenesis because its cat's eye provides (i) a region of cyclonic vorticity and weak deformation by the resolved flow, (ii) containment of moisture entrained by the developing flow and/or lofted by deep convection therein, (iii) confinement of mesoscale vortex aggregation, (iv) a predominantly convective type of heating profile, and (v) maintenance or enhancement of the parent wave until the developing proto-vortex becomes a self-sustaining entity and emerges from the wave as a tropical depression. This genesis sequence and the overarching framework for describing how such hybrid wave-vortex structures become tropical depressions/storms is likened to the development of a marsupial infant in its mother's pouch, and for this reason has been dubbed the "marsupial paradigm". Here we conduct the first multi-scale test of the marsupial paradigm in an idealized setting by revisiting the Kurihara and Tuleya problem examining the transformation of an easterly wave-like disturbance into a tropical storm vortex using the WRF model. An analysis of the evolving winds, equivalent potential temperature, and relative vertical vorticity is presented from coarse (28 km), intermediate (9 km) and high resolution (3.1 km) simulations. The results are found to support key elements of the marsupial paradigm by demonstrating the existence of rotationally dominant region with minimal strain/shear deformation near the center of the critical layer pouch that contains strong cyclonic vorticity and high saturation fraction. This localized region within the pouch serves as the "attractor" for an upscale "bottom up" development process while the wave pouch and proto-vortex move together.

Montgomery, M. T.↗

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.↗

NASA NTRS2020

Quantification of the Land Surface and Brown Ocean Influence on Tropical Cyclone Intensification Over Land

An investigation of TC Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the Brown Ocean effect (BOE), and to develop a comprehensive analysis framework for landfalling tropical cyclones (TCs) in the process. NASA’s Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e. all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs.

Brown Ocean Effect↗

DOE OSTI2024

Can we mitigate tropical cyclone formation using aerosols? A review of cyclogenesis and aerosol effects as a theoretical basis

Tropical cyclogenesis is a complex phenomenon, involving processes across multiple scales, with various theories proposed to explain its mechanisms. This paper provides an up-to-date summary of the established physical mechanisms and controlling factors of cyclogenesis. Understanding the nature of tropical cyclone formation is necessary to improve tropical cyclone forecasts and inform tropical cyclone mitigation strategies targeting early-stage intervention. Despite the disparities among theories, the critical role of persistent, intensified convection in tropical cyclone initiation is universally acknowledged. Therefore, our hypothesis is that interrupting convective development using aerosol injection is a potential strategy for mitigating tropical cyclone formation. Targetted injection of coarse and fine aerosols at the formation stage are two proposed potential approaches for mitigating tropical cyclones. These methods have completely different microphysical effects but each may ultimately interfere with the formation of the nascent cyclone. In conclusion, these potential interventions open new areas of further research, which are important and necessary to establish a solid scientific foundation for cyclogenesis mitigation.

Tropical cyclone formation↗

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↗

NASA NTRS2003

The Structural Changes of Tropical Cyclones Upon Interaction with Vertical Wind Shear

The Fourth Convection and Moisture Experiment (CAMEX-4) provided a unique opportunity to observe the distributions and document the roles of important atmospheric factors that impact the development of the core asymmetries and core structural changes of tropical cyclones embedded in vertical wind shear. The state-of-the-art instruments flown on the NASA DC-8 and ER-2, in addition to those on the NOAA aircraft, provided a unique set of observations that documented the core structure throughout the depth of the tropical cyclone. These data have been used to conduct a combined observational and modeling study using a state-of-the-art, high- resolution mesoscale model to examine the role of the environmental vertical wind shear in producing tropical cyclone core asymmetries, and the effects on the structure and intensity of tropical cyclones.The scientific objectives of this study were to obtain in situ measurements that would allow documentation of the physical mechanisms that influence the development of the asymmetric convection and its effect on the core structure of the tropical cyclone.

Ritchie, Elizabeth A.↗