11 research outputs found

    Attributing Tropical Cyclogenesis to Equatorial Waves in the Western North Pacific

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    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

    Role of equatorial waves in tropical cyclogenesis

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    Tropical cyclones typically form within preexisting wavelike disturbances that couple with convection. Using Tropical Rainfall Measuring Mission (TRMM) multisatellite rainfall estimates, this study determines the relative number of tropical cyclones that can be attributed to various wave types, including the Madden–Julian oscillation (MJO), Kelvin waves, equatorial Rossby (ER) waves, mixed Rossby–gravity (MRG) waves, and tropical depression (TD)-type disturbances. Tropical cyclogenesis is attributed to an equatorial wave’s convection when the filtered rainfall anomaly exceeds a threshold value at the genesis location. More storms are attributed to TD-type disturbances than to any other wave type in all of the Northern Hemisphere basins. In the Southern Hemisphere, however, ER waves and TD-type disturbances are equally important as precursors. Fewer storms are attributed to MRG waves, Kelvin waves, and the MJO in every basin. Although relatively few storms are attributed to the MJO, tropical cyclogenesis is 2.6 times more likely in its convective phase compared with its suppressed phase. This modulation arises in part because each equatorial wave type is amplified within MJO’s convective phase. The amplification significantly increases the probability that these waves will act as tropical cyclone precursors. A case study from June 2002 illustrates the effects of a series of Kelvin waves on two tropical cyclone formations. These waves were embedded in the convective phase of the MJO. Together, the MJO and the Kelvin waves preconditioned the low-level environment for cyclogenesis. The first Kelvin wave weakened the trade easterlies, while the subsequent waves created monsoon westerlies near the equator. These westerlies provided the background cyclonic vorticity within which both storms developed. The effects of tropical cyclone-related rainfall anomalies are also investigated. In the wavenumber–frequency spectrum for rainfall, tropical cyclones can inflate the power for shorter wavelength westward propagating waves by up to 27%. This spectrum contains signals from all longitudes, but the greatest contamination occurs in regions like the Philippines where tropical cyclones are most frequent. Here, tropical cyclones contribute more than 40% of the rainfall variance in each filter band. To mitigate these effects, tropical cyclone-related anomalies were removed before filtering in this study

    Hurricane Ida (2021): Rapid Intensification Followed by Slow Inland Decay

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    Hurricane Ida recently became one of the strongest hurricanes to hit Louisiana on record, with an estimated landfalling maximum sustained wind of 130 kt. Although Hurricane Ida made landfall at a similar time of year and landfall location as Hurricane Katrina (2005), Ida’s postlandfall decay rate was much weaker than Hurricane Katrina. This manuscript includes a comparative analysis of pre- and post-landfall synoptic conditions for Hurricane Ida and other historical major landfalling hurricanes (Category 3+ on the Saffir-Simpson Hurricane Wind Scale) along the Gulf Coast since 1983, with a particular focus on Hurricane Katrina. Abundant precipitation in southeastern Louisiana prior to Ida’s landfall increased soil moisture. This increased soil moisture along with extremely weak overland steering flow likely slowed the storm’s weakening rate post-landfall. Offshore environmental factors also played an important role, particularly anomalously high nearshore sea surface temperatures and weak vertical wind shear that fueled the rapid intensification of Ida just before landfall. Strong nearshore vertical wind shear weakened Hurricane Katrina before landfall, and moderate northward steering flow caused Katrina to move inland relatively quickly, aiding in its relatively fast weakening rate following landfall. The results of this study improve our understanding of critical factors influencing the evolution of the nearshore intensity of major landfalling hurricanes in the Gulf of Mexico. This study can help facilitate forecasting and preparation for inland hazards resulting from landfalling hurricanes with nearshore intensification and weak post-landfall decay

    Large-Scale Atmospheric and Oceanic Conditions during the 2011–12 DYNAMO Field Campaign

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    Abstract An international field campaign, Dynamics of the Madden Julian Oscillation (DYNAMO), took place in the Indian Ocean during October 2011–March 2012 to collect observations for the Madden–Julian oscillation (MJO), especially its convective initiation processes. The large-scale atmospheric and oceanic conditions during the campaign are documented here. The ENSO and the Indian Ocean dipole (IOD) states, the monthly mean monsoon circulation and its associated precipitation, humidity, vertical and meridional/zonal overturning cells, and ocean surface currents are discussed. The evolution of MJO events is described using various fields and indices that have been used to subdivide the campaign into three periods. These periods were 1) 17 September–8 December 2011 (period 1), which featured two robust MJO events that circumnavigated the global tropics with a period of less than 45 days; 2) 9 December 2011–31 January 2012, which contained less coherent activity (period 2); and 3) 1 February–12 April 2012, a period that featured the strongest and most slowly propagating MJO event of the campaign (period 3). Activities of convectively coupled atmospheric Kelvin and equatorial Rossby (ER) waves and their interaction with the MJO are discussed. The overview of the atmospheric and oceanic variability during the field campaign raises several scientific issues pertaining to our understanding of the MJO, or lack thereof. Among others, roles of Kelvin and ER waves in MJO convective initiation, convection-circulation decoupling on the MJO scale, applications of MJO filtering methods and indices, and ocean–atmosphere coupling need further research attention

    The Extremely Active 2017 North Atlantic Hurricane Season

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    The 2017 North Atlantic hurricane season was extremely active, with 17 named storms (1981–2010 median is 12.0), 10 hurricanes (median is 6.5), 6 major hurricanes (median is 2.0), and 245% of median accumulated cyclone energy (ACE) occurring. September 2017 generated more Atlantic named storm days, hurricane days, major hurricane days, and ACE than any other calendar month on record. The season was destructive, with Harvey and Irma devastating portions of the continental United States, while Irma and Maria brought catastrophic damage to Puerto Rico, Cuba, and many other Caribbean islands. Seasonal forecasts increased from calling for a slightly below-normal season in April to an above-normal season in August as large-scale environmental conditions became more favorable for an active hurricane season. During that time, the tropical Atlantic warmed anomalously while a potential El Niño decayed in the Pacific. Anomalously high SSTs prevailed across the tropical Atlantic, and vertical wind shear was anomalously weak, especially in the central tropical Atlantic, from late August to late September when several major hurricanes formed. Late-season hurricane activity was likely reduced by a convectively suppressed phase of the Madden–Julian oscillation. The large-scale steering flow was different from the average over the past decade with a strong subtropical high guiding hurricanes farther west across the Atlantic. The anomalously high tropical Atlantic SSTs and low vertical wind shear were comparable to other very active seasons since 1982

    A Hyperactive End to the Atlantic Hurricane Season October–November 2020

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    The active 2020 Atlantic hurricane season produced 30 named storms, 14 hurricanes, and 7 major hurricanes (category 3+ on the Saffir–Simpson hurricane wind scale). Though the season was active overall, the final two months (October–November) raised 2020 into the upper echelon of Atlantic hurricane activity for integrated metrics such as accumulated cyclone energy (ACE). This study focuses on October–November 2020, when 7 named storms, 6 hurricanes, and 5 major hurricanes formed and produced ACE of 74 × 104 kt2 (1 kt ≈ 0.51 m s−1). Since 1950, October–November 2020 ranks tied for third for named storms, first for hurricanes and major hurricanes, and second for ACE. Six named storms also underwent rapid intensification (≥30 kt intensification in ≤24 h) in October–November 2020—the most on record. This manuscript includes a climatological analysis of October–November tropical cyclones (TCs) and their primary formation regions. In 2020, anomalously low wind shear in the western Caribbean and Gulf of Mexico, likely driven by a moderate-intensity La Niña event and anomalously high sea surface temperatures (SSTs) in the Caribbean, provided dynamic and thermodynamic conditions that were much more conducive than normal for late-season TC formation and rapid intensification. This study also highlights October–November 2020 landfalls, including Hurricanes Delta and Zeta in Louisiana and in Mexico and Hurricanes Eta and Iota in Nicaragua. The active late season in the Caribbean would have been anticipated by a statistical model using the July–September-averaged ENSO longitude index and Atlantic warm pool SSTs as predictors

    Cyclone Center: Can Citizen Scientists Improve Tropical Cyclone Intensity Records?

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    The global tropical cyclone (TC) intensity record, even in modern times, is uncertain because the vast majority of storms are only observed remotely. Forecasters determine the maximum wind speed using a patchwork of sporadic observations and remotely sensed data. A popular tool that aids forecasters is the Dvorak technique—a procedural system that estimates the maximum wind based on cloud features in IR and/or visible satellite imagery. Inherently, the application of the Dvorak procedure is open to subjectivity. Heterogeneities are also introduced into the historical record with the evolution of operational procedures, personnel, and observing platforms. These uncertainties impede our ability to identify the relationship between tropical cyclone intensities and, for example, recent climate change. A global reanalysis of TC intensity using experts is difficult because of the large number of storms. We will show that it is possible to effectively reanalyze the global record using crowdsourcing. Through modifying the Dvorak technique into a series of simple questions that amateurs (“citizen scientists”) can answer on a website, we are working toward developing a new TC dataset that resolves intensity discrepancies in several recent TCs. Preliminary results suggest that the performance of human classifiers in some cases exceeds that of an automated Dvorak technique applied to the same data for times when the storm is transitioning into a hurricane

    Advances in tropical cyclone prediction on subseasonal time scales during 2019–2022

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    This review describes advances in understanding and forecasting tropical cyclone (TC) subseasonal variability during the past four years. A large effort by the scientific community has been in understanding the sources of predictability at subseasonal timescales beyond the well-known modulation of TC activity by the Madden-Julian Oscillation (MJO). In particular, the strong modulation of TC activity over the western North Pacific by the Boreal Summer Intra-Seasonal Oscillation (BSISO) has been documented. Progress has also been realized in understanding the role of tropical-extratropical interactions in improving subseasonal forecasts. In addition, several recent publications have shown that extratropical wave breaking may have a role in the genesis and development of TCs. Analyses of multi-model ensemble data sets such as the Subseasonal to Seasonal (S2S) and Subseasonal Experiment (SubX) have shown that the skill of S2S models in predicting the genesis of TCs varies strongly among models and regions but is often tied to their ability to simulate the MJO and its impacts. The skill in select models has led to an increase over the past four years in the number of forecasting centers issuing subseasonal TC forecasts using various techniques (statistical, statistical-dynamical and dynamical). More extensive verification studies have been published over the last four years, but often only for the North Atlantic and eastern North Pacific
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