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The rapport describes and compares various existing and new methods to estimate tropical cyclone surface wind structure from spaceborne sensors. We discuss scatterometers, L-band radiometers, C-band synthetic aperture radar, reflectometers, microwave sounders. We describe the TC wind structure analysis at the JTWC and the DAV technique for determining wind radii.
This paper analyzes the climatology, prediction skill, and predictability of tropical cyclones (TCs) in NASA’s Global Earth Observing System Subseasonal to Seasonal (GEOS-S2S) forecast system version 2. GEOS reasonably simulates the number and spatial distribution of TCs compared to observations except in the Atlantic where the model simulates too few TCs due to low genesis rates in the Caribbean Sea and Gulf of Mexico. The environmental conditions, diagnosed through a genesis potential index, do not clearly explain model biases in the genesis rates, especially in the Atlantic. At the storm-scale, GEOS reforecasts replicate several key aspects of the thermodynamic and dynamic structure of observed TCs, such as a warm core and the secondary circulation. The model, however, fails to simulate an off-center eyewall when evaluating vertical velocity, precipitation and moisture. The analysis of prediction skill of TC genesis and occurrence shows that GEOS has comparable skill to other global models in WMO S2S archive and that its skill could be further improved by increasing the ensemble size. After calibration, GEOS forecasts are skillful in the Western North Pacific and Southern Indian Ocean up to 20 days in advance. A model-based predictability analysis demonstrates the importance of the Madden-Julian Oscillation (MJO) as a source of predictability of TC occurrence beyond the 14 day lead-time. Forecasts initialized under strong MJO conditions show evidence of predictability beyond week 3. However, due to model biases in the forecast distribution there are notable gaps between MJO-related prediction skill and predictability which require further study.
A comprehensive analysis has been conducted of the cloud-to-ground lightning activity occurring within a landfalling tropical cyclone that produced an outbreak of strong and damaging tornadoes. Radar data indicate that 12 convective cells were responsible for 29 tornadoes, several of which received an F3 intensity rating, in the southeastern United States on 16 August 1994 within the remnants of Tropical Storm Beryl. Of these 12 tornadic storms, the most active cell produced 315 flashes over a 5.5 hour period, while the other storms were less active. Three tornadic storms failed to produce any CG lightning at all. In general, the tornadic storms were more active electrically than other non-tornadic cells within Beryl's remnants, although the flash rates were rather modest by comparison with significant midlatitude severe storm events. Very few positive polarity flashes were found in the Beryl outbreak. During some of the stronger tornadoes, CG flash rates in the parent storms showed sharp transient decreases. Doppler radar data suggest the stronger tornadic storms were small supercells, and the lightning data indicate these storms exhibited lightning characteristics similar to those found in heavy-precipitation supercell storms.
Not much is known about the evolution of lightning within extra-tropical cyclones traversing the mid-latitudes, especially its oceans. To facilitate such studies we combine a recently constructed precipitation features (PF) database obtained from the Global Precipitation Measurement (GPM) mission constellation of satellites with lightning observations from the Geostationary Lightning Mapper (GLM) onboard GOES-16 and the Lightning Imaging Sensor (LIS) onboard the International Space Station (ISS). The goal of this study is to provide a new observationally-based view of the tropical to extra-tropical transition and its impact on lightning production. Such data fusion approaches, as presented here, will also be important in future satellite studies of convective precipitation.
This manuscript discusses the challenges in detecting and attributing recently observed trends in the Atlantic tropical cyclone (TC) and the epistemic uncertainty we face in assessing future risk. We use synthetic storms downscaled from five CMIP5 models by the Columbia HAZard model (CHAZ), and directly simulated storms from high-resolution climate models. We examine three aspects of recent TC activity: the upward trend and multi-decadal oscillation of the annual frequency, the increase in storm wind intensity, and the decrease in forward speed. Some data sets suggest that these trends and oscillation are forced while others suggest that they can be explained by natural variability. Projections under warming climate scenarios also show a wide range of possibilities, especially for the annual frequencies, which increase or decrease depending on the choice of moisture variable used in the CHAZ model and on the choice of climate model. The uncertainties in the annual frequency lead to epistemic uncertainties in TC risk assessment. Here, we investigate the potential for reduction of these epistemic uncertainties through a statistical practice, namely likelihood analysis. We find that historical observations are more consistent with the simulations with increasing frequency than those with decreasing frequency, but we are not able to rule out the latter. We argue that the most rational way to treat epistemic uncertainty is to consider all outcomes contained in the results. In the context of risk assessment, since the results contain possible outcomes in which TC risk is increasing, this view implies that the risk is increasing.
A selected group of 1973 North Pacific Ocean tropical cyclones was studied by using data from the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR), the Temperature-Humidity Infrared Radiometer (THIR), NOAA-2 and USAF DMSP imageries. From the unique combination of infrared, visible, and microwave data, it was possible during various stages of storm development to differentiate between dense cirrus outflow and rain areas, to identify centers of circulation and areas of low-level moisture, and by the use of a theoretical model to estimate semi-quantitatively areas of light, moderate, and heavy rainfall rates.
The eddy flux convergence of relative angular momentum (EFC) at 200 mb was calculated for the named tropical cyclones during the 1989-1991 Atlantic hurricane seasons. A period of enhanced EFC within 1500 km of the storm center occurred about every five days due to the interaction with upper-level troughs in the midlatitude westerlies or upper-level, cold lows in low latitudes. Twenty-six of the 32 storms had at least one period of enhanced EFC. In about one-third of the cases, the storm intensified just after the period of enhanced EFC. In most of the cases in which the storm did not intensify the vertical shear increased, the storm moved over cold water, or the storm became extratropical just after the period of enhanced EFC. A statistically significant relationship was found between the EFC within 600 km of the storm center and the intensity change during the next 48 h. The EFC was also examined for the ten storms from the 1989-1991 sample that had the largest intensification rates. Six of the ten periods of rapid intensification were associated with enhanced EFC. In the remaining four cases the storms were intensifying rapidly in a low shear environment without any obvious interaction with upper-level troughs.
An approach to the problem of deducing wind speed and pressure around tropical cyclones is presented. The technique, called the Surface Wind Inference from Microwave data (SWIM technique, uses satellites microwave sounder data to measure upper tropospheric temperature anomalies which may then be related to surface pressure anomalies through the hydrostatic and radiative transfer equations. Surface pressure gradients outside of the radius of maximum wind are estimated for the first time. Future instruments may be able to estimate central pressure with + or - 0/1 kPa accuracy.
Barrier Islands are the first line of defense against tropical storms and hurricanes for coastal areas. Historically, tropical cyclonic events have had a great impact on the transgression of barrier islands, especially the Chandeleur Island chain off the eastern coast of Louisiana. These islands are of great importance, aiding in the protection of southeastern Louisiana from major storms, providing habitat for nesting and migratory bird species, and are part of the second oldest wildlife refuge in the country. In 1998, Hurricane Georges caused severe damage to the chain, prompting restoration and monitoring efforts by both federal and state agencies. Since then, multiple storm events have steadily diminished the integrity of the islands. Hurricane Katrina in 2005 thwarted all previous restoration efforts, with Hurricane Gustav in 2008 exacerbating island erosion and vegetation loss. Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 2-4 Multispectral Scanner (MSS), and Landsat 5 Thematic Mapper (TM) will be utilized to detect land loss, island transgression, and vegetation change from 1979 to 2009. This study looks to create a more synoptic view of the transgression of the Chandeleur Islands and correlate weather and sea surface phenomena with erosion trends over the past 30 years, so that partnering organizations such as the Pontchartrain Institute for Environmental Sciences (PIES) can better monitor and address the continual change of the island chain.
A new method to construct a horizontal resolution-dependent wind speed adjustment factor for evaluating tropical cyclones (TCs) in global climate models (GCMs) is presented here. In contrast to the previous studies that used idealized axisymmetric wind fields, this study analyzes 48 hours of 10-second surface wind fields from 1-km TC simulations. The adjustment factor is derived from filtering the simulated TC wind fields onto various horizontal grid spacings typical of those used in GCMs. The new adjustment factor leads to TCs with greater intensity than the existing adjustment factors for horizontal grid spacings smaller than 30 km. This difference is attributed to more realistic wind fields in the TC simulations that contain highly asymmetric, localized patches of higher wind speeds instead of axisymmetric wind fields. Applying the new adjustment factor to select GCM simulations suggests the common interpretation of low-intensity bias in GCM-simulated TCs might be slightly exaggerated.
This study aims to quantify the impacts of atmosphere–ocean coupling on simulated and projected tropical cyclone (TC) precipitation globally. We used global climate model (GCM) simulations over 1950–2050 from the High Resolution Model Intercomparison Project (HighResMIP) and compared its fully coupled atmosphere–ocean GCMs (AOGCMs) with atmosphere-only GCMs (AGCMs). We find that ocean coupling generally leads to decreased TC precipitation over ocean and land. Large-scale sea surface temperature (SST) biases are critical drivers of the precipitation difference, with secondary contributions from local TC–ocean feedbacks via SST cold wakes. The two driving factors, attributed to ocean coupling in the AOGCMs, influence TC precipitation in association with decreased TC intensity and specific humidity. The AOGCMs and AGCMs consistently project TC precipitation increases in 2015–2050 relative to 1950–2014 over ocean for all basins, and for landfalling TCs in the North Atlantic and western North Pacific.
Abstract A vertically resolved moist static energy (MSE) variance budget framework is used to diagnose processes associated with the development of tropical cyclones (TCs) in a general circulation model (GCM) under realistic boundary conditions. Previous studies have shown that interactions between radiation and MSE promote TC development. Here, we examine the vertical contributions of radiation and its interactions with MSE by performing several mechanism-denial experiments in which synoptic-scale radiative interactions are suppressed either in the boundary layer or in the free troposphere. Partly suppressing radiative interactions results in a reduction in global TC frequency. However, the magnitude of reduction and structure of the feedback depend on the intensity and structure of the TCs in these mechanism-denial experiments, indicating that both the magnitude and the vertical location of radiative interactions can impact global TC frequency. Using instantaneous 6-hourly outputs, an explicit computation reveals distinct spatial patterns of the advection term: the vertical component is positive in the mid- to upper troposphere, which reflects an upward transport of MSE by deep convection, whereas the horizontal component is positive in the boundary layer. These results illustrate the impact of the vertical distribution of radiative interactions and vertically varied contribution of the advection term in the development of TCs.
The Chandeleur Islands are the first line of defense against tropical storms and hurricanes for coastal Louisiana. They provide habitats for birds species and are a wildlife refuge; however, distressingly, they are eroding and transgressing at an alarming rate. In 1998, Hurricane Georges caused severe damage to the chain, prompting restoration and monitoring efforts by both Federal and State agencies. Since then, storm events have steadily diminished the condition of the islands. Quantification of shoreline erosion, vegetation, and land loss, from 1979 to 2009, was achieved through the analysis of imagery from Landsat 2-4 Multispectral Scanner, Landsat 4 & 5 Thematic Mapper, and Advanced Spaceborne Thermal Emission and Reflection Radiometer sensors. QuickBird imagery was used to validate the accuracy of these results. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer data to assist in tracking the transgression of the Chandeleur Islands. The use of near infrared reflectance calculated from MOD09 surface reflectance data from 2000 to 2009 was analyzed using the Time Series Product Tool. The scope of this project includes not only assessments of the tropical cyclonic events during this time period, but also the effects of tides, winds, and cold fronts on the spatial extent of the islands. Partnering organizations, such as the Pontchartrain Institute for Environmental Research, will utilize those results in an effort to better monitor and address the continual change of the island chain.
A statistical-stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones (TCs) is used to examine the relationship between climate and landfall rates along the North American Atlantic and Gulf Coasts. The model draws on archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and one of two different measures of sea surface temperature (SST): 1) SST averaged over the NA subtropics and the hurricane season and 2) this SST relative to the seasonal global subtropical mean SST (termed relSST). Here, the authors focus on SST by holding ENSO to a neutral state. Jackknife uncertainty tests are employed to test the significance of SST and relSST landfall relationships. There are more TC and major hurricane landfalls overall in warm years than cold, using either SST or relSST, primarily due to a basinwide increase in the number of storms. The signal along the coast, however, is complex. Some regions have large and significant sensitivity (e.g., an approximate doubling of annual major hurricane landfall probability on Texas from -2 to +2 standard deviations in relSST), while other regions have no significant sensitivity (e.g., the U.S. mid-Atlantic and Northeast coasts). This geographic structure is due to both shifts in the regions of primary TC genesis and shifts in TC propagation.
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.
Since extreme precipitation impacts society on small scales (i.e., a few kilometers and smaller, it is worthwhile to explore extreme precipitation trends in localized regions, such as Long Island (LI), New York. Its coastal location makes it vulnerable to various extreme events, such as tropical cyclones (TCs). This work aimed to quantify the extreme precipitation events on LI that are caused by TCs, as well as the percentage of TCs passing close to LI that cause extreme precipitation events. Both gauge-based and satellite-based precipitation datasets of varying resolutions (DAYMET, IMERG, and CPC) were used to understand the impact of dataset selection. Results are shown for the common time period of 2001–2020, as well as the full time periods of each dataset. DAYMET shows the highest percentage of extreme precipitation events linked to TCs for 2001–2020 (a maximum of 7.2%) and the highest number of TCs that caused extreme precipitation events (36.5%), with IMERG showing similar results. For the full and common time periods, the highest percentage of extreme precipitation events caused by TCs was found in eastern LI. TC-related extreme precipitation averaged over LI varied year to year, and amounts were dependent on the resolution of the observational dataset, but most datasets showed an increasing trend in the last 19 years that is larger than the trend in mean precipitation. Current infrastructure in the region is likely inadequately prepared for future impacts from TC-related extreme precipitation events in such a population-dense region.
Abstract High‐resolution climate models (∼28 km grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus enabling their investigation in relation to the climate system. On the global scale, previous works have demonstrated that the Community Atmosphere Model (CAM) version 5 presents a reasonable TC climatology under prescribed present‐day (1980–2005) forcing. However, for the Western North Pacific (WNP) region, known biases in simulated TC genesis frequency and location under‐represent the basin's dominant share in observations. This study addresses these model biases in WNP by evaluating WNP TCs in a decadal simulation, and exploring potential improvements through nudging experiments. Among the major environmental controls of TC genesis, the lack of mid‐level moisture is identified as the leading cause of the deficit in simulated WNP TC genesis over the Pacific Warm Pool. Subsequent seasonal experiments explore the effect of constraining the large‐scale environment on TC development by nudging WNP temperature field toward reanalysis at various strengths. Temperature nudging elicits a significant response in TC genesis and intensity development, as well as in moisture and convection over the Warm Pool. These responses are sensitive to the choice of nudging timescale. Overall, the nudging experiments demonstrate that improvements in the large‐scale environment can lead to improvements in simulated TCs, suggesting future model developments in relation to model physics. In this way, the potential improvements in model fidelity will contribute to the understanding of how the mean state of current or future climates may give rise to extremes such as TCs.
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 and performing 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 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 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. 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: (I) wave deepening associated with wave shortening and/or the intensification of individual gyres, (2) poleward movement of gyres that may be associated with bOlll1dary 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.