The Tropics

H. J. Diamond NOAA/OAR Air Resources Laboratory, College Park, Maryland

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C. J. Schreck Cooperative Institute for Satellite Earth System Studies, North Carolina State University, Asheville, North Carolina

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Adam Allgood NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center, College Park, Maryland

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Emily J. Becker Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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Eric S. Blake NOAA/NWS National Hurricane Center, Miami, Florida

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Francis G. Bringas NOAA/OAR Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

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Suzana J. Camargo Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York

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Randall Cerveny Department of Geography, Arizona State University, Tempe, Arizona

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Lin Chen Institute for Climate and Application Research (ICAR)/KLME/ILCEC/CIC-FEMD, Nanjing University of Information Science and Technology, Nanjing, China

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Caio A.S. Coelho Centro de Previsão do Tempo e Estudos Climáticos/National Institute for Space Research, Center for Weather Forecasts and Climate Studies, Cachoeira Paulista, Brazil

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Howard J. Diamond NOAA/OAR Air Resources Laboratory, College Park, Maryland

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Craig Earl-Spurr Bureau of Meteorology, Perth, Australia

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Nicolas Fauchereau National Institute of Water and Atmospheric Research, Ltd., Auckland, New Zealand

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Chris Fogarty Canadian Hurricane Centre, Dartmouth, Canada

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Stanley B. Goldenberg NOAA/OAR Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

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Daniel S. Harnos NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center, College Park, Maryland

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Qiong He Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing, China

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Zeng-Zhen Hu NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center, College Park, Maryland

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Philip J. Klotzbach Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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John A. Knaff NOAA/NESDIS Center for Satellite Applications and Research, Fort Collins, Colorado

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Arun Kumar NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center, College Park, Maryland

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Michelle L’Heureux NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center, College Park, Maryland

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Chris W. Landsea NOAA/NWS National Hurricane Center, Miami, Florida

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I-I Lin National Taiwan University, Taipei, Taiwan

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Hosmay Lopez NOAA/OAR Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

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Andrew M. Lorrey National Institute of Water and Atmospheric Research, Ltd., Auckland, New Zealand

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Jing-Jia Luo Institute for Climate and Application Research, Nanjing University of Information Science and Technology, Nanjing, China

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Andrew D. Magee Centre for Water, Climate and Land, School of Environmental and Life Sciences, University of Newcastle, Callaghan, Australia

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Richard J. Pasch NOAA/NWS National Hurricane Center, Miami, Florida

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Linda Paterson Bureau of Meteorology, Perth, Australia

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Alexandre B. Pezza Greater Wellington Regional Council, Wellington, New Zealand

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Matthew Rosencrans NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center, College Park, Maryland

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Carl J. Schreck Cooperative Institute for Satellite Earth System Studies, North Carolina State University, Asheville, North Carolina

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Blair C. Trewin Bureau of Meteorology, Melbourne, Australia

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Ryan E. Truchelut WeatherTiger, Tallahassee, Florida

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John Uehling Cooperative Institute for Satellite Earth System Studies, North Carolina State University, Asheville, North Carolina

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Bin Wang School of Ocean and Earth Science and Technology, Department of Meteorology, University of Hawaii at Manoa, Honolulu, Hawaii; International Pacific Research Center, Honolulu, Hawaii

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Hui Wang NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center, College Park, Maryland

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Kimberly M. Wood Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, Arizona

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Open access

© 2024 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Howard J. Diamond / howard.diamond@noaa.gov

© 2024 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Howard J. Diamond / howard.diamond@noaa.gov

a. Overview

—H. J. Diamond and C. J. Schreck

In 2023, the El Niño–Southern Oscillation (ENSO) transitioned to El Niño after three years of La Niña conditions. ENSO-neutral conditions were briefly present in the tropical Pacific between January–March and March–May, before El Niño conditions emerged in April–June. El Niño strengthened steadily through the second half of 2023, with the Oceanic Niño Index reaching a value of +1.9°C in October–December.

For the global tropics (defined here as 20°S–20°N), the NOAA Merged Land Ocean Global Surface Temperature Analysis (NOAA GlobalTemp; Vose et al. 2021) indicates that the combined average land and ocean surface temperature was 0.5°C above the 1991–2020 average, the warmest year for the tropics in the 174-year data record. The six warmest years in the tropics since 1850 have all occurred since 2015. Data from the Global Precipitation Climatology Project indicate a mean annual total precipitation value of 1318 mm across the tropics (20°S–20°N latitude band) over land. This is 86 mm below the 1991–2020 average and was the third lowest for the 1979–2023 period of record.

Globally, 82 named tropical cyclones (TCs; ≥34 kt; or ≥17 m s−1) were observed during the 2023 Northern Hemisphere season (January–December 2023) and the 2022/23 Southern Hemisphere season (July–June 2022/23; see Table 4.2), as documented by the National Hurricane Center and the Joint Typhoon Warning Center in International Best Track Archive for Climate Stewardship Version 4 (Knapp et al. 2010). Overall, this number was below the 1991–2020 global average of 87 TCs and also below the 85 TCs reported during the 2022 season (Diamond and Schreck 2023). The record for most named storms in a single TC season is 104 in 1992.

Of the 82 named storms, 45 reached hurricane strength (one-minute maximum sustained winds ≥64 kt) and 30 reached major hurricane strength (one-minute maximum winds ≥96 kt). Both of these counts were below their 1991–2020 averages. The accumulated cyclone energy (ACE; an integrated metric of the strength, frequency, and duration of tropical storms and hurricanes; Bell et al. 2000) rebounded from the lowest on record in 2022 (since reliable data began in 1981) to an above-normal level in 2023. Four of the seven TC basins were above normal in 2023 in contrast to zero in 2022. The North Indian Ocean had its second highest ACE on record behind 2019, and the North Atlantic had its seventh above-normal season in the last eight years. The western North Pacific had its fourth consecutive season with below-normal activity. A total of seven storms reached Category 5 intensity on the Saffir-Simpson Hurricane Wind Scale (one-minute maximum sustained winds ≥137 kt) during 2023, compared with only three in 2022. All of the basins, except for the Australian and southwest Pacific, had at least one Category 5 storm.

The 20 named storms in the North Atlantic during 2023 was equal with 1933 for the fourth-highest total in the HURDAT2 database (Landsea and Franklin 2013). In contrast, the number of hurricanes and major hurricanes were at their long-term (1991–2020) average of seven and three, respectively. The 2023 hurricane season was classified by NOAA as an above-normal season. NOAA uses 1951–2020 terciles of ACE to delineate below-normal, normal, and above-normal seasons, and 2023’s ACE of 146 × 104 kt2 places it in the upper tercile. Two storms of particular note this season were Hurricane Otis, which was the strongest landfalling hurricane on record for the west coast of Mexico (see Sidebar 4.1), and Cyclone Freddy in the Southern Hemisphere (see Sidebar 4.2). Freddy is now recognized as the world's longest-lived TC (Earl-Spur et al. 2024), crossing the full width of the Indian Ocean. Freddy is the first TC since 2000 to form in the Australian region and make landfall on the mainland African coast. Freddy made a total of three landfalls: one in Madagascar and two in Mozambique.

b. ENSO and the tropical Pacific

—E. Becker, M. L’Heureux, Z.-Z. Hu, and A. Kumar

The El Niño–Southern Oscillation (ENSO) is an ocean and atmosphere-coupled climate phenomenon across the tropical Pacific Ocean, with its warm (cold) phases called El Niño (La Niña). NOAA’s Climate Prediction Center classifies and assesses the strength and duration of El Niño and La Niña events using the Oceanic Niño Index (ONI, shown for mid-2022 through 2023 in Fig. 4.1). The ONI is the three-month (seasonal) running average of sea-surface temperature (SST) anomalies in the Niño-3.4 region (5°S–5°N, 170°W–120°W), currently calculated as the departure from the 1991–2020 base period mean1. El Niño is classified when the ONI is at or greater than +0.5°C for at least five consecutive, overlapping seasons, while La Niña is classified when the ONI is at or less than −0.5°C for at least five consecutive, overlapping seasons.

Fig. 4.1.
Fig. 4.1.

Time series of the Oceanic Niño Index (ONI, °C) from mid-2022 through 2023. Overlapping three-month seasons are labeled on the x-axis, with initials indicating the first letter of each month in the season. Blue bars indicate negative values that are less than −0.5°C. Black bars indicate values between −0.5°C and 0.5°C, while red bars indicate positive values greater than 0.5°C. ONI values are derived from the ERSSTv5 dataset and are based on departures from the 1991–2020 period monthly means (Huang et al. 2017).

Citation: Bulletin of the American Meteorological Society 105, 8; 10.1175/BAMS-D-24-0098.1

The time series of the ONI (Fig. 4.1) shows a transition from 2022’s La Niña conditions—the third La Niña year in a row—to strong El Niño in 2023, where strong El Niño is defined in this chapter as ONI ≥1.5°C. La Niña developed in July–September 2020 and lasted nearly continuously through December–February (DJF) 2022/23, with a brief period of ENSO-neutral conditions in the summer of 2021. ENSO-neutral conditions were briefly present in the tropical Pacific in 2023, between January–March and March–May (MAM), before El Niño emerged in April–June. El Niño strengthened steadily through the second half of 2023, with the ONI reaching a value of +1.9°C in October–December.

1. OCEANIC CONDITIONS

Figure 4.2 displays the mean SST (left column) and SST anomalies (right column) during DJF 2022/23 through September–November (SON) 2023. During DJF, below-average SST anomalies were on the order of −0.5°C to −1.0°C across the central equatorial Pacific (approximately 170°E–260°E), reflecting a weak and waning La Niña (Fig. 4.2b). During MAM, a small region of SST anomalies exceeding +2.5°C developed off the coast of Peru and Ecuador, while most of the tropical Pacific was near average, with a slight positive anomaly (+0.5°C to +1.0°C) in the western Pacific (Fig. 4.2d). By June–August (JJA), positive anomalies spread westward along the equator, with western Pacific SSTs closer to average (Fig. 4.2f). The SST pattern in SON reflects a strong El Niño, with equatorial Pacific anomalies in excess of +1.0°C extending from the dateline to the coast of South America (Fig. 4.2h). Some weak off-equatorial negative SST anomalies in the eastern half of the tropical basin were present from MAM through SON (Figs. 4.2d,f,h). Also of note in SON 2023 was the positive phase of the Indian Ocean dipole (IOD), with negative SST anomalies in the east and positive SST anomalies in the west (Fig. 4.2h).

Fig. 4.2.
Fig. 4.2.

Mean sea-surface temperatures (SSTs; left) and SST anomalies (right) for (a),(b) Dec–Feb (DJF) 2022/23, (c),(d) Mar−May (MAM) 2023, (e),(f) Jun–Aug (JJA) 2023, and (g),(h) Sep−Nov (SON) 2023. The bold contour for SST is for 30°C. Anomalies are departures from the 1991–2020 seasonal adjusted OIv2.1 climatology (Huang et al. 2021).

Citation: Bulletin of the American Meteorological Society 105, 8; 10.1175/BAMS-D-24-0098.1

The weakening La Niña of DJF 2022/23 is also reflected in the subsurface temperature anomalies (Fig. 4.3a). The subsurface temperatures in the eastern Pacific were slightly below average, with a slightly shoaled thermocline. Warm anomalies in the west contributed to a deeper-than-average thermocline, leading to a slightly deeper-than-average west–east thermocline slope (Fig. 4.3a). During the transition from La Niña to El Niño in MAM, the thermocline across the entire basin was deeper than average (Fig, 4.3b). As El Niño strengthened into JJA and SON 2023, the depth of the thermocline in the western Pacific returned to near-average. In the central and eastern equatorial Pacific, the thermocline deepened as warm subsurface anomalies expanded in the central and eastern equatorial Pacific. The slope of the thermocline across the equatorial Pacific was shallower than average during the last half of the year (Figs. 4.3c,d). Overall, the subsurface SST in the western Pacific was warmer than would be expected during strong El Niño events (e.g., Kumar and Hu 2014).

Fig. 4.3.
Fig. 4.3.

Equatorial depth–longitude section of Pacific Ocean temperature anomalies (°C) averaged between 5°S and 5°N during (a) Dec–Feb (DJF) 2022/23, (b) Mar–May (MAM) 2023, (c) Jun–Aug (JJA) 2023, and (d) Sep–Nov (SON) 2023. The 20°C isotherm (thick solid line) approximates the center of the oceanic thermocline. The gray dashed line shows the climatology of the 20°C isotherm based on the 1991–2020 mean. The data are derived from a reanalysis system that assimilates oceanic observations into an oceanic general circulation model (Behringer 2007). Anomalies are departures from the 1991–2020 period monthly means.

Citation: Bulletin of the American Meteorological Society 105, 8; 10.1175/BAMS-D-24-0098.1

2. ATMOSPHERIC