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Gregory R. Foltz
,
Karthik Balaguru
, and
Samson Hagos

ABSTRACT

Sea surface temperature (SST) is one of the most important parameters for tropical cyclone (TC) intensification. Here, it is shown that the relationship between SST and TC intensification varies considerably from basin to basin, with SST explaining less than 4% of the variance in TC intensification rates in the Atlantic, 12% in the western North Pacific, and 23% in the eastern Pacific. Several factors are shown to be responsible for these interbasin differences. First, variability of SST along TCs’ tracks is lower in the Atlantic. This is due to smaller horizontal SST gradients in the Atlantic, compared to the Pacific, and stronger damping of prestorm SST’s contribution to TC intensification by the storm-induced cold SST wake in the Atlantic. The damping occurs because SST tends to vary in phase with TC-induced SST cooling: in the Gulf of Mexico and northwestern Atlantic, where SSTs are highest, TCs tend to be strongest and their translations slowest, resulting in the strongest storm-induced cooling. The tendency for TCs to be more intense over the warmest SST in the Atlantic also limits the usefulness of SST as a predictor since stronger storms are less likely to experience intensification. Finally, SST tends to vary out of phase with vertical wind shear and outflow temperature in the western Pacific. This strengthens the relationship between SST and TC intensification more in the western Pacific than in the eastern Pacific or Atlantic. Combined, these factors explain why prestorm SST is such a poor predictor of TC intensification in the Atlantic, compared to the eastern and western North Pacific.

Full access
Nguyen Dac Da
,
Gregory R. Foltz
,
Karthik Balaguru
, and
Eleda Fernald

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.

Open access
Karthik Balaguru
,
Gregory R. Foltz
,
L. Ruby Leung
,
Samson M. Hagos
, and
David R. Judi

Abstract

Sea surface temperature (SST) and tropical cyclone heat potential (TCHP) are metrics used to incorporate the ocean’s influence on hurricane intensification into the National Hurricane Center’s Statistical Hurricane Intensity Prediction Scheme (SHIPS). While both SST and TCHP serve as useful measures of the upper-ocean heat content, they do not accurately represent ocean stratification effects. Here, it is shown that replacing SST within the SHIPS framework with a dynamic temperature T dy, which accounts for the oceanic negative feedback to the hurricane’s intensity arising from storm-induced vertical mixing and sea surface cooling, improves the model performance. While the model with SST and TCHP explains about 41% of the variance in 36-h intensity changes, replacing SST with T dy increases the variance explained to nearly 44%. These results suggest that representation of the oceanic feedback, even through relatively simple formulations such as T dy, may improve the performance of statistical hurricane intensity prediction models such as SHIPS.

Full access
Wenwei Xu
,
Karthik Balaguru
,
Andrew August
,
Nicholas Lalo
,
Nathan Hodas
,
Mark DeMaria
, and
David Judi

Abstract

Reducing tropical cyclone (TC) intensity forecast errors is a challenging task that has interested the operational forecasting and research community for decades. To address this, we developed a deep learning (DL)-based multilayer perceptron (MLP) TC intensity prediction model. The model was trained using the global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to forecast the change in TC maximum wind speed for the Atlantic basin. In the first experiment, a 24-h forecast period was considered. To overcome sample size limitations, we adopted a leave one year out (LOYO) testing scheme, where a model is trained using data from all years except one and then evaluated on the year that is left out. When tested on 2010–18 operational data using the LOYO scheme, the MLP outperformed other statistical–dynamical models by 9%–20%. Additional independent tests in 2019 and 2020 were conducted to simulate real-time operational forecasts, where the MLP model again outperformed the statistical–dynamical models by 5%–22% and achieved comparable results as HWFI. The MLP model also correctly predicted more rapid intensification events than all the four operational TC intensity models compared. In the second experiment, we developed a lightweight MLP for 6-h intensity predictions. When coupled with a synthetic TC track model, the lightweight MLP generated realistic TC intensity distribution in the Atlantic basin. Therefore, the MLP-based approach has the potential to improve operational TC intensity forecasts, and will also be a viable option for generating synthetic TCs for climate studies.

Open access
Chuan-Chieh Chang
,
Sandro W. Lubis
,
Karthik Balaguru
,
L. Ruby Leung
,
Samson M. Hagos
, and
Philip J. Klotzbach

Abstract

This study investigates the combined impacts of the Madden–Julian oscillation (MJO) and extratropical anticyclonic Rossby wave breaking (AWB) on subseasonal Atlantic tropical cyclone (TC) activity and their physical connections. Our results show that during MJO phases 2–3 (enhanced Indian Ocean convection) and 6–7 (enhanced tropical Pacific convection), there are significant changes in basinwide TC activity. The MJO and AWB collaborate to suppress basinwide TC activity during phases 6–7 but not during phases 2–3. During phases 6–7, when AWB occurs, various TC metrics including hurricanes, accumulated cyclone energy, and rapid intensification probability decrease by ∼50%–80%. Simultaneously, large-scale environmental variables, like vertical wind shear, precipitable water, and sea surface temperatures become extremely unfavorable for TC formation and intensification, compared to periods characterized by suppressed AWB activity during the same MJO phases. Further investigation reveals that AWB events during phases 6–7 occur in concert with the development of a stronger anticyclone in the lower troposphere, which transports more dry, stable extratropical air equatorward, and drives enhanced tropical SST cooling. As a result, individual AWB events in phases 6–7 can disturb the development of surrounding TCs to a greater extent than their phases 2–3 counterparts. The influence of the MJO on AWB over the western subtropical Atlantic can be attributed to the modulation of the convectively forced Rossby wave source over the tropical eastern Pacific. A significant number of Rossby waves initiating from this region during phases 5–6 propagate into the subtropical North Atlantic, preceding the occurrence of AWB events in phases 6–7.

Open access
Karthik Balaguru
,
Gregory R. Foltz
,
L. Ruby Leung
,
John Kaplan
,
Wenwei Xu
,
Nicolas Reul
, and
Bertrand Chapron

Abstract

Tropical cyclone (TC) rapid intensification (RI) is difficult to predict and poses a formidable threat to coastal populations. A warm upper ocean is well known to favor RI, but the role of ocean salinity is less clear. This study shows a strong inverse relationship between salinity and TC RI in the eastern Caribbean and western tropical Atlantic due to near-surface freshening from the Amazon–Orinoco River system. In this region, rapidly intensifying TCs induce a much stronger surface enthalpy flux compared to more weakly intensifying storms, in part due to a reduction in SST cooling caused by salinity stratification. This reduction has a noticeable positive impact on TCs undergoing RI, but the impact of salinity on more weakly intensifying storms is insignificant. These statistical results are confirmed through experiments with an ocean mixed layer model, which show that the salinity-induced reduction in SST cold wakes increases significantly as the storm’s intensification rate increases. Currently, operational statistical–dynamical RI models do not use salinity as a predictor. Through experiments with a statistical RI prediction scheme, it is found that the inclusion of surface salinity significantly improves the RI detection skill, offering promise for improved operational RI prediction. Satellite surface salinity may be valuable for this purpose, given its global coverage and availability in near–real time.

Free access
Karthik Balaguru
,
Gregory R. Foltz
,
L. Ruby Leung
,
John Kaplan
,
Wenwei Xu
,
Nicolas Reul
, and
Bertrand Chapron
Full access
Effy B. John
,
Karthik Balaguru
,
L. Ruby Leung
,
Gregory R. Foltz
,
Robert D. Hetland
, and
Samson M. Hagos

Abstract

Tropical Cyclone (TC) Sally formed on 11 September 2020, traveled through the Gulf of Mexico (GMX), and intensified rapidly before making landfall on the Alabama coast as a devastating category-2 TC with extensive coastal and inland flooding. In this study, using a combination of observations and idealized numerical model experiments, we demonstrate that the Mississippi River plume played a key role in the intensification of Sally near the northern Gulf Coast. As the storm intensified and its translation slowed before landfall, sea surface cooling was reduced along its track, coincident with a pronounced increase in SSS. Further analysis reveals that TC Sally encountered a warm Loop Current eddy in the northern GMX close to the Mississippi River plume. Besides deepening the thermocline, the eddy advected low-salinity Mississippi River plume water into the storm’s path. This resulted in the development of strong upper-ocean salinity stratification, with a shallow layer of freshwater lying above a deep, warm “barrier layer.” Consequently, TC-induced mixing and the associated sea surface cooling were reduced, aiding Sally’s intensification. These results suggest that the Mississippi River plume and freshwater advection by the Loop Current eddies can play an important role in TC intensification near the U.S. Gulf Coast.

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