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Abstract: —J. Blunden and T. Boyer In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. Anna Glacier in Switzerland and Ice Worm Glacier in the United States disappeared completely. In August, as a direct result of glacial thinning over the past 20 years, a glacial lake on a tributary of the Mendenhall Glacier in Alaska burst through its ice dam and caused unprecedented flooding on Mendenhall River near Juneau. Across the Arctic, the annual surface air temperature was the fourth highest in the 124-year record, and summer (July–September) was record warm. Smaller-than-normal snow cover extent in May and June contributed to the third-highest average peak tundra greenness in the 24-year record. In September, Arctic minimum sea ice extent was the fifth smallest in the 45-year satellite record. The 17 lowest September extents have all occurred in the last 17 years. In Antarctica, temperatures for much of the year were up to 6°C above average over the Weddell Sea and along coastal Dronning Maud Land. The Antarctic Peninsula also experienced well-above-average temperatures during the 2022/23 melt season, which contributed to its fourth consecutive summer of above-average surface melt. On 21 February, Antarctic sea ice extent and sea ice area both reached all-time lows, surpassing records set just a year earlier. Over the course of the year, new daily record-low sea ice extents were set on 278 days. In some instances, these daily records were set by a large margin, for example, the extent on 6 July was 1.8 million km2 lower than the previous record low for that day. Across the global oceans, the annual sea surface temperature was the highest in the 170-year record, far surpassing the previous record of 2016 by 0.13°C. Daily and monthly records were set from March onward, including an historic-high daily global mean sea surface temperature of 18.99°C recorded on 22 August. Approximately 94% of the ocean surface experienced at least one marine heatwave in 2023, while 27% experienced at least one cold spell. Globally averaged ocean heat content from the surface to 2000-m depth was record high in 2023, increasing at a rate equivalent to ∼0.7 Watts per square meter of energy applied over Earth’s surface. Global mean sea level was also record high for the 12th consecutive year, reaching 101.4 mm above the 1993 average when satellite measurements began, an increase of 8.1±1.5 mm over 2022 and the third highest year-over-year increase in the record. A total of 82 named tropical storms were observed during the Northern and Southern Hemispheres’ storm seasons, below the 1991–2020 average of 87. Hurricane Otis became the strongest landfalling hurricane on record for the west coast of Mexico at 140 kt (72 m s−1), causing at least 52 fatalities and $12–16 billion U.S. dollars in damage. Freddy became the world’s longest-lived tropical cyclones on record, developing into a tropical cyclone on 6 February and finally dissipating on 12 March. Freddy crossed the full width of the Indian Ocean and made one landfall in Madagascar and two in Mozambique. In the Mediterranean Sea—outside of traditional tropical cyclone basins—heavy rains and flooding from Storm Daniel killed more than 4300 people and left more than 8000 missing in Libya. The record-warm temperatures in 2023 created conditions that helped intensify the hydrological cycle. Measurements of total-column water vapor in the atmosphere were the highest on record, while the fraction of cloud area in the sky was the lowest since records began in 1980. The annual global mean precipitation total over land surfaces for 2023 was among the lowest since 1979, but global one-day maximum totals were close to average, indicating an increase in rainfall intensity. In July, record-high areas of land across the globe (7.9%) experienced extreme drought, breaking the previous record of 6.2% in July 2022. Overall, 29.7% of land experienced moderate or worse categories of drought during the year, also a record. Mexico reported its driest (and hottest) year since the start of its record in 1950. In alignment with hot and prolonged dry conditions, Canada experienced its worst national wildfire season on record. Approximately 15 million hectares burned across the country, which was more than double the previous record from 1989. Smoke from the fires were transported far into the United States and even to western European countries. August to October 2023 was the driest three-month period in Australia in the 104-year record. Millions of hectares of bushfires burned for weeks in the Northern Territory. In South America, extreme drought developed in the latter half of the year through the Amazon basin. By the end of October, the Rio Negro at Manaus, a major tributary of the Amazon River, fell to its lowest water level since records began in 1902. The transition from La Niña to El Niño helped bring relief to the prolonged drought conditions in equatorial eastern Africa. However, El Niño along with positive Indian Ocean dipole conditions also contributed to excessive rainfall that resulted in devastating floods over southeastern Ethiopia, Somalia, and Kenya during October to December that displaced around 1.5 million people. On 5 September, the town of Zagora, Greece, broke a national record for highest daily rainfall (754 mm in 21 hours, after which the station ceased reporting) due to Storm Daniel; this one-day accumulation was close to Zagora’s normal annual total.

This study uses experiments from the Energy Exascale Earth System Model (E3SM) to compare the influence on tropical cyclone (TC) activity of: (i) the atmospheric effect of aerosols under specified sea-surface temperatures (SSTs); and (ii) the net effect of greenhouse gases (GhGs) (including changes in SSTs). The experiments were performed using the CMIP6 Shared Socioeconomic Pathway SSP5-8.5 emissions scenario with GhG-induced SST warming specified and atmospheric aerosol effects simulated but without explicit ocean coupling. Insignificant changes in global TC frequency are found in response to the atmospheric effect of future aerosols and GhGs, as significant regional responses in TC frequency counteract each other. Future GhGs contribute to more frequent TCs in the North Atlantic, and reductions over the Northwestern Pacific and Southern Indian Ocean. The atmospheric effect of future aerosols drives more frequent TCs over the Northwestern Pacific and reductions over the Northeast Pacific and North Atlantic. Along with increases in TC intensity, global TC precipitation (TCP) is projected to increase by 52.8% (14.1%/K) due to the combined effect of future aerosols and GhGs. Although both forcings contribute to TCP increases (14.7–19.3% from reduced aerosols alone and 28.1–33.3% from increased GhGs alone), they lead to different responses in the spatial structure of TCP. TCP increases preferentially in the inner-core due to increased GhGs, whereas TCP decreases in the inner-core and increases in the outer-bands in response to the atmospheric effects of decreased aerosols. These changes are distinct from those caused by aerosol-induced SST changes, which have been considered in other studies.

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.

The authors describe a tropical cyclone risk model for the Philippines using open-source methods that can be straightforwardly generalized to other countries. Wind fields derived from historical observations, as well as those from an environmentally forced tropical cyclone hazard model, are combined with data representing exposed value and vulnerability to determine asset losses. Exposed value is represented by the LitPop dataset, which assumes total asset value is distributed across a country following population density and night-lights data. Vulnerability is assumed to follow a functional form previously proposed by Emanuel, with free parameters chosen by a sensitivity analysis in which simulated and historical reported damages are compared for different parameter values and further constrained by information from household surveys about regional building characteristics. Use of different vulnerability parameters for the region around Manila, Philippines, yields much better agreement between simulated and actually reported losses than does a single set of parameters for the entire country. Despite the improvements from regionally refined vulnerability, the model predicts no losses for a substantial number of destructive historical storms, a difference the authors hypothesize is due to the use of wind speed as the sole metric of tropical cyclone hazard, omitting explicit representation of storm surge and/or rainfall. Bearing these limitations in mind, this model can be used to estimate return levels for tropical cyclone-caused wind hazards and asset losses for regions across the Philippines, relevant to some disaster risk reduction and management tasks; this model also provides a platform for further development of open-source tropical cyclone risk modeling.

The authors describe a tropical cyclone risk model for the Philippines, using methods that are open-source and can be straightfor-wardly generalized to other countries. Wind fields derived from historical observations, as well as those from an environmentally forced tropical cyclone hazard model (using environmental forcing from the recent historical period) are combined with data representing exposed value and vulnerability to determine asset losses. Exposed value is represented by the LitPop dataset, which assumes total asset value is distributed across a country following population density and nightlights data. Vulnerability is assumed to follow a functional form previously proposed by Emanuel, with free parameters chosen by a sensitivity analysis in which simulated and historical reported damages are compared for different parameter values. Use of different vulnerability parameters for the region around Manila yields much better agreement between simulated and actually reported losses than does a single set of parameters for the entire country. Even then, however, the model predicts no losses for a substantial number of historical storms which did in fact produce them, a difference the authors hypothesize is at least in part due to the use of wind speed as the sole metric of TC hazard, omitting explicit representation of flooding due to storm surge and/or rainfall.

Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.

On behalf of the journal, AGU, and the scientific community, the editors would like to sincerely thank those who reviewed the manuscripts for Geophysical Research Letters in 2019. The hours reading and commenting on manuscripts not only improve the manuscripts but also increase the scientific rigor of future research in the field. We particularly appreciate the timely reviews in light of the demands imposed by the rapid review process at Geophysical Research Letters. With the revival of the “major revisions” decisions, we appreciate the reviewers' efforts on multiple versions of some manuscripts. With the advent of AGU's data policy, many reviewers have helped immensely to evaluate the accessibility and availability of data associated with the papers they have reviewed, and many have provided insightful comments that helped to improve the data presentation and quality. We greatly appreciate the assistance of the reviewers in advancing open science, which is a key objective of AGU's data policy. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics.

On behalf of the journal, AGU, and the scientific community, the Editors would like to sincerely thank those who reviewed manuscripts for Geophysical Research Letters in 2018. The hours reading and commenting on manuscripts not only improves the manuscripts but also increases the scientific rigor of future research in the field. We particularly appreciate the timely reviews, in light of the demands imposed by the rapid review process at Geophysical Research Letters. With the revival of the “major revisions” decisions, we appreciate the reviewers' efforts on multiple versions of some manuscripts. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics. In total, 4,484 referees contributed to 7,557 individual reviews in journal. Thank you again. We look forward to the coming year of exciting advances in the field and communicating those advances to our community and to the broader public.

Tropical cyclone intensification processes are explored in six high-resolution climate models. The analysis framework employs process-oriented diagnostics that focus on how convection, moisture, clouds, and related processes are coupled. These diagnostics include budgets of column moist static energy and the spatial variance of column moist static energy, where the column integral is performed between fixed pressure levels. The latter allows for the quantification of the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclone spinup, including surface flux feedbacks and cloud-radiative feedbacks. Tropical cyclones (TCs) are tracked in the climate model simulations and the analysis is applied along the individual tracks and composited over many TCs. Two methods of compositing are employed: a composite over all TC snapshots in a given intensity range, and a composite over all TC snapshots at the same stage in the TC life cycle (same time relative to the time of lifetime maximum intensity for each storm). The radiative feedback contributes to TC development in all models, especially in storms of weaker intensity or earlier stages of development. Notably, the surface flux feedback is stronger in models that simulate more intense TCs. This indicates that the representation of the interaction between spatially varying surface fluxes and the developing TC is responsible for at least part of the intermodel spread in TC simulation.

El Niño-Southern Oscillation (ENSO) is a major source of seasonal western North Pacific (WNP) tropical cyclone (TC) predictability. However, the spatial characteristics of ENSO have changed in recent decades, from warming more typically in the eastern equatorial Pacific during canonical or cold tongue El Niño to warming more typically in the central equatorial Pacific during noncanonical or warm pool El Niño. We investigated the response in basinwide WNP TC activity and spatial clustering of TC tracks to the location and magnitude of El Niño using observations, TC-permitting tropical channel model simulations, and a TC track clustering methodology. We found that simulated western North Pacific TC activity, including accumulated cyclone energy (ACE) and the number of typhoons and intense typhoons, is more effectively enhanced by sea surface temperature warming of the central, compared to the eastern, equatorial Pacific. El Niño also considerably influenced simulated TC tracks regionally, with a decrease in TCs that were generated near the Asian continent and an increase in clusters that were dominated by TC genesis in the southeastern WNP. This response corresponds with the spatial pattern of reduced vertical wind shear and is most effectively driven by central Pacific SST warming. Finally, internal atmospheric variability generated a substantial range in the simulated season total ACE (±25% of the median). However, extremely active WNP seasons were linked with El Niño, rather than internal atmospheric variability, in both observations and climate model simulations.

Western North Pacific tropical cyclone (TC) model tracks are analyzed in two large multimodel ensembles, spanning a large variety of models and multiple future climate scenarios. Two methodologies are used to synthesize the properties of TC tracks in this large data set: cluster analysis and mass moment ellipses. First, the models' TC tracks are compared to observed TC tracks' characteristics, and a subset of the models is chosen for analysis, based on the tracks' similarity to observations and sample size. Potential changes in track types in a warming climate are identified by comparing the kernel smoothed probability distributions of various track variables in historical and future scenarios using a Kolmogorov-Smirnov significance test. Two track changes are identified. The first is a statistically significant increase in the north-south expansion, which can also be viewed as a poleward shift, as TC tracks are prevented from expanding equatorward due to the weak Coriolis force near the equator. The second change is an eastward shift in the storm tracks that occur near the central Pacific in one of the multimodel ensembles, indicating a possible increase in the occurrence of storms near Hawaii in a warming climate. The dependence of the results on which model and future scenario are considered emphasizes the necessity of including multiple models and scenarios when considering future changes in TC characteristics.

On behalf of the journal, AGU, and the scientific community, the editors of Geophysical Research Letters would like to sincerely thank those who reviewed manuscripts for us in 2023. The hours reading and commenting on manuscripts not only improve the manuscripts, but also increase the scientific rigor of future research in the field. With the advent of AGU's data policy, many reviewers have also helped immensely to evaluate the accessibility and availability of data, and many have provided insightful comments that helped to improve the data presentation and quality. We greatly appreciate the assistance of the reviewers in advancing open science, which is a key objective of AGU's data policy. We particularly appreciate the timely reviews in light of the demands imposed by the rapid review process at Geophysical Research Letters. We received 4,512 submissions in 2023 and 5,112 reviewers contributed to their evaluation by providing 8,587 reviews in total. We deeply appreciate their contributions. Plain Language Summary: Individuals in italics provided three or more reviews for GRL in 2023. Key Points: The editors thank the 2023 peer‐reviewers [ABSTRACT FROM AUTHOR]

Synoptic-scale monsoon disturbances produce the majority of continental rainfall in the monsoon regions of South Asia and Australia, yet there is little understanding of the conditions that foster development of these low pressure systems. Here a genesis index is used to associate monsoon disturbance genesis in a global domain with monthly mean, climatological environmental variables. This monsoon disturbance genesis index (MDGI) is based on four objectively selected variables: Total column water vapor, low-level absolute vorticity, an approximate measure of convective available potential energy, and midtropospheric relative humidity. A Poisson regression is used to estimate the index coefficients. Unlike existing tropical cyclone genesis indices, the MDGI is defined over both land and ocean, consistent with the fact that monsoon disturbance genesis can occur over land. The index coefficients change little from their global values when estimated separately for the Asian-Australian monsoon region or the Indian monsoon region, suggesting that the conditions favorable for monsoon disturbance genesis, and perhaps the dynamics of genesis itself, are common across multiple monsoon regions. Vertical wind shear is found to be a useful predictor in some regional subdomains; although previous studies suggested that baroclinicity may foster monsoon disturbance genesis, here genesis frequency is shown to be reduced in regions of strong climatological vertical shear. The coefficients of the MDGI suggest that monsoon disturbance genesis is fostered by humid, convectively unstable environments that are rich in vorticity. Similarities with indices used to describe the distribution of tropical cyclone genesis are discussed.

Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate.

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models. Key Points: Multimodel comparison of tropical cyclone activity in global climate models Geographic distribution of the TC activity is similar to observed Most models produce tropical cyclones weaker than observed

This is the second part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the twentieth-century simulations of intraseasonal to multidecadal variability and teleconnections with North American climate. Overall, the multimodel ensemble does reasonably well at reproducing observed variability in several aspects, but it does less well at capturing observed teleconnections, with implications for future projections examined in part three of this paper. In terms of intraseasonal variability, almost half of the models examined can reproduce observed variability in the eastern Pacific and most models capture the midsummer drought over Central America. The multimodel mean replicates the density of traveling tropical synoptic-scale disturbances but with large spread among the models. On the other hand, the coarse resolution of the models means that tropical cyclone frequencies are underpredicted in the Atlantic and eastern North Pacific. The frequency and mean amplitude of ENSO are generally well reproduced, although teleconnections with North American climate are widely varying among models and only a few models can reproduce the east and central Pacific types of ENSO and connections with U.S. winter temperatures. The models capture the spatial pattern of Pacific decadal oscillation (PDO) variability and its influence on continental temperature and West Coast precipitation but less well for the wintertime precipitation. The spatial representation of the Atlantic multidecadal oscillation (AMO) is reasonable, but the magnitude of SST anomalies and teleconnections are poorly reproduced. Multidecadal trends such as the warming hole over the central-southeastern United States and precipitation increases are not replicated by the models, suggesting that observed changes are linked to natural variability. © 2013 American Meteorological Society.