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The synoptic low pressure systems (LPSs) formed over the downwind side of the Tibetan Plateau explain a substantial portion of summer rainfall extremes along their paths. Recent studies have found that the total extreme rainfall trend over the East Asian landmass, which features the “south flood–north drought” pattern, can be understood to a great extent by the changes in terrestrial LPSs. Yet, the energy sources fueling these storms and the environmental drivers of their long-term trends remain unclear. Utilizing a probabilistic clustering method, three clusters of terrestrial LPS tracks for the period 1979–2018 are identified. Besides the differences in trajectories that distinguish the clusters into northeastward-migrating and quasi-stationary types, prominent intercluster differences are found in the LPS evolution, energetics, and trends. The Lorenz energetics suggest that while condensational heating is indispensable for all three clusters, the migratory type, which has greater intensity and faster development, is more closely tied to baroclinicity. Nonetheless, the summer baroclinicity alone is not enough to sustain these LPSs as these storms dissipate quickly after propagating out of the humid monsoon region and into the drier extratropics. Over time, occurrences of migratory LPSs decrease, and those of quasi-stationary LPSs increase. Using a Poisson model that links the LPS genesis to local environmental conditions, the decreasing occurrence of migratory LPSs is shown to result from the weakened baroclinicity, whereas the increasing occurrence of quasi-stationary LPSs is primarily driven by enhanced relative humidity and reduced steering flow in the mid-to-lower troposphere over East Asia.

Purpose of Review: Knowledge of how monsoons will respond to external forcings through the twenty-first century has been confounded by incomplete theories of tropical climate and insufficient representation in climate models. This review highlights recent insights from past warm climates and historical trends that can inform our understanding of monsoon evolution in the context of an emerging energetic framework. Recent Findings: Projections consistent with paleoclimate evidence and theory indicate expanded/wetter monsoons in Africa and Asia, with continued uncertainty in the Americas. Twentieth century observations are not congruent with expectations of monsoon responses to radiative forcing from greenhouse gases, due to the confounding effect of aerosols. Lines of evidence from warm climate analogues indicate that while monsoons respond in globally coherent and predictable ways to orbital forcing and inter-hemispheric thermal gradients, there are differences in response to these forcings and also between land and ocean. Summary: Further understanding of monsoon responses to climate change will require refinement of the energetic framework to incorporate zonal asymmetries and the use of model hierarchies.

The intensity and spatial extent of tropical cyclone precipitation (TCP) often shapes the risk posed by landfalling storms. Here we provide a comprehensive climatology of landfalling TCP characteristics as a function of tropical cyclone strength, using daily precipitation station data and Atlantic U.S. landfalling tropical cyclone tracks from 1900 to 2017. We analyze the intensity and spatial extent of ≥1 mm/day TCP (Z1) and ≥50 mm/day TCP (Z50) over land. We show that the highest median intensity and largest median spatial extent of Z1 and Z50 occur for major hurricanes that have weakened to tropical storms, indicating greater flood risk despite weaker wind speeds. We also find some signs of TCP change in recent decades. In particular, for major hurricanes that have weakened to tropical storms, Z50 intensity has significantly increased, indicating possible increases in flood risk to coastal communities in more recent years.

The impact of volcanic aerosols on recent global tropical cyclone (TC) activity is examined in observations, reanalysis, and models (the Coupled Model Intercomparison Project phase 5 - CMIP5 multi-model, and one single model large ensemble). In observations, we find a reduction of TC activity only in the North Atlantic following the last three strong volcanic eruptions; that signal, however, cannot be clearly attributed to volcanoes, as all three eruptions were simultaneous with El Niño events. In reanalyses, we find no robust impact of volcanic eruptions on potential intensity (PI) and genesis indices. In models, we find a reduction in PI after volcanic eruptions in the historical simulations, but this effect is significantly reduced when differences between the model environment and observations are accounted for. Morever, the CMIP5 multi-model historical ensemble shows no effect of volcanic eruptions on a TC genesis index. Finally, there is no robust and consistent reduction in recent TC activity following recent volcanic eruptions in a large set of synthetic TCs downscaled from these simulations. Taken together, these results show that in recent eruptions volcanic aerosols did not reduce global TC activity.

The impact of ocean warming on tropical cyclone (TC) track over the western North Pacific is an open issue. Relatively little is known about possible changes in TC tracks under ocean warming conditions due to both inhomogeneous observation networks and large natural variability over a relatively short observational period. A suite of semiidealized numerical experiments on two TC cases is conducted to investigate the response of TC tracks to increases in sea surface temperature (SST). It is found that the simulated TC track is highly sensitive to underlying SST. Specifically, through its influence on the radial distribution of sea surface enthalpy, ocean warming can lead to changes in the tangential wind profile and thus increase the TC size in terms of the radius of gale force wind, which is attributed to the increase in maximum wind speed, the expansion of the radius of maximum wind, and the additional increase in outer winds. The increased TC size, as suggested by previous studies, further leads to the eastward withdrawal of the western Pacific subtropical high (WPSH) and thus a northward turning of the TC. Results of climate simulations in the present study provide further evidence for the aforementioned impact of ocean warming on TC size and thus the WPSH and TC track. Results of the present study also imply that the threat of storms to countries in East Asia may be reduced due to possible changes in TC tracks if ocean warming continues in the future.

During the second half of 2014, the tropical Pacific was in a state marginally consistent with El Niño. While oceanic indicators were indicative of a weak El Niño event, a number of atmospheric indicators were not, and a number of forecast centers did not declare an El Niño. Nonetheless, the most active tropical cyclone basins of the northern hemisphere—those of the North Atlantic and Pacific—showed tropical cyclone statistics that in some respects were consistent with El Niño. In particular, the numbers of relatively intense storms in the four basins considered—major hurricanes in the Eastern North Pacific and North Atlantic, super typhoons in the Western North Pacific, and hurricanes in the Central North Pacific—formed a pattern strongly consistent with El Niño.

An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño–Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño—namely, eastern Pacific (EP) and central Pacific (CP) El Niño—and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.

Recent assessments agree that tropical cyclone intensity should increase as the climate warms. Less agreement exists on the detection of recent historical trends in tropical cyclone intensity. We interpret future and recent historical trends by using the theory of potential intensity, which predicts the maximum intensity achievable by a tropical cyclone in a given local environment. Although greenhouse gas–driven warming increases potential intensity, climate model simulations suggest that aerosol cooling has largely canceled that effect over the historical record. Large natural variability complicates analysis of trends, as do poleward shifts in the latitude of maximum intensity. In the absence of strong reductions in greenhouse gas emissions, future greenhouse gas forcing of potential intensity will increasingly dominate over aerosol forcing, leading to substantially larger increases in tropical cyclone intensities.

Dynamical downscaling of simulations of the Last Glacial Maximum (LGM) and late twentieth century (20C) were conducted using the Weather Research and Forecasting (WRF) model with the aim of (1) understanding how the downscaled kinematic and thermodynamic variables influence simulated tropical cyclone (TC) activity over the western North Pacific during the LGM and the 20C periods and (2) to test the relevance of TC genesis factors for the colder LGM climate. The results show that, despite the lower temperatures during the LGM, the downscaled TC climatology over the western North Pacific in the LGM simulation does not differ significantly from that in the 20C simulation. Among the TC environmental factors, the TC potential intensity, mid‐tropospheric entropy deficit, and vertical wind shear during the LGM were consistent with previous analyses of TC genesis factors in LGM global climate model simulations. Changes in TC genesis density between the LGM and the 20C simulations seem to be well represented by the ventilation index, a nondimensional measure of the combined effects of vertical wind shear, and thermodynamic properties, suggesting the potential applicability of those factors for TC activity evaluation during the LGM and possibly other climates.

In previous work the authors demonstrated an empirical relation, in the form of an index, between U.S. monthly tornado activity and monthly averaged environmental parameters. Here a detailed comparison is made between the index and reported tornado activity. The index is a function of two environmental parameters taken from the North American Regional Reanalysis: convective precipitation (cPrcp) and storm relative helicity (SRH). Additional environmental parameters are considered for inclusion in the index, among them convective available potential energy, but their inclusion does not significantly improve the overall climatological performance of the index. The aggregate climatological dependence of reported monthly U.S. tornado numbers on cPrcp and SRH is well described by the index, although it fails to capture nonsupercell and cool season tornadoes. The contributions of the two environmental parameters to the index annual cycle and spatial distribution are examined with the seasonality of cPrcp (maximum during summer) relative to SRH (maximum in winter) accounting for the index peak value in May. The spatial distribution of SRH establishes the central U.S. “tornado alley” of the index, while the spatial distribution of cPrcp enhances index values in the South and Southeast and suppresses them west of the Rockies and over elevation. At the scale of the NOAA climate regions, the largest deficiency of the index climatology occurs over the central region where the index peak in spring is too low and where the late summer drop-off in the reported number of tornadoes is poorly captured. This index deficiency is related to its sensitivity to SRH, and increasing the index sensitivity to SRH improves the representation of the annual cycle in this region. The ability of the index to represent the interannual variability of the monthly number of U.S. tornadoes can be ascribed during most times of the year to interannual variations of cPrcp rather than of SRH. However, both factors are important during the peak spring period. The index shows some skill in representing the interannual variability of monthly tornado numbers at the scale of NOAA climate regions.

The ventilation index serves as a theoretically based metric to assess possible changes in the statistics of tropical cyclones to combined changes in vertical wind shear, midlevel entropy deficit, and potential intensity in climate models. Model output from eight Coupled Model Intercomparison Project 5 models is used to calculate the ventilation index. The ventilation index and its relationship to tropical cyclone activity between two 20 year periods are compared: the historical experiment from 1981 to 2000 and the RCP8.5 experiment from 2081 to 2100. The general tendency is for an increase in the seasonal ventilation index in the majority of the tropical cyclone basins, with exception of the North Indian basin. All the models project an increase in the midlevel entropy deficit in the tropics, although the effects of this increase on the ventilation index itself are tempered by a compensating increase in the potential intensity and a decrease in the vertical wind shear in most tropical cyclone basins. The nonlinear combination of the terms in the ventilation index results in large regional and intermodel variability. Basin changes in the ventilation index are well correlated with changes in the frequency of tropical cyclone formation and rapid intensification in the climate models. However, there is large uncertainty in the projections of the ventilation index and the corresponding effects on changes in the statistics of tropical cyclone activity.

Using the historical Atlantic tropical cyclone record, this study examines the empirical relationships between climate state variables and Atlantic tropical cyclone counts. The state variables considered as predictors include indices of the El Niño/Southern Oscillation and Northern Atlantic Oscillation, and both “local” and “relative” measures of Main Development Region sea surface temperature. Other predictors considered include indices measuring the Atlantic Meridional Mode and the West African monsoon. Using all of the potential predictors in a forward stepwise Poisson regression, we examine the relationships between tropical cyclone counts and climate state variables. As a further extension on past studies, both basin-wide named storm counts and cluster analysis time series representing distinct flavors of tropical cyclones, are modeled. A wide variety of cross validation metrics reveal that basin-wide counts or sums over appropriately chosen clusters may be more skillfully modeled than the individual cluster series. Ultimately, the most skillful models typically share three predictors: indices for the main development region sea surface temperatures, the El Niño/Southern Oscillation, and the North Atlantic Oscillation.

Monthly U.S. tornado numbers are here related to observation-based monthly averaged atmospheric parameters. Poisson regression is used to form an index which captures the climatological spatial distribution and seasonal variation of tornado occurrence, as well as year-to-year variability, and provides a framework for extended range forecasts of tornado activity. Computing the same index with predicted atmospheric parameters from a comprehensive forecast model gives some evidence of the predictability of monthly tornado activity.

The tropical subseasonal variability simulated by the Goddard Institute for Space Studies general circulation model, Model E2, is examined. Several versions of Model E2 were developed with changes to the convective parameterization in order to improve the simulation of the Madden–Julian oscillation (MJO). When the convective scheme is modified to have a greater fractional entrainment rate, Model E2 is able to simulate MJO-like disturbances with proper spatial and temporal scales. Increasing the rate of rain reevaporation has additional positive impacts on the simulated MJO. The improvement in MJO simulation comes at the cost of increased biases in the mean state, consistent in structure and amplitude with those found in other GCMs when tuned to have a stronger MJO. By reinitializing a relatively poor-MJO version with restart files from a relatively better-MJO version, a series of 30-day integrations is constructed to examine the impacts of the parameterization changes on the organization of tropical convection. The poor-MJO version with smaller entrainment rate has a tendency to allow convection to be activated over a broader area and to reduce the contrast between dry and wet regimes so that tropical convection becomes less organized. Besides the MJO, the number of tropical-cyclone-like vortices simulated by the model is also affected by changes in the convection scheme. The model simulates a smaller number of such storms globally with a larger entrainment rate, while the number increases significantly with a greater rain reevaporation rate.

Twenty-first century climate model projections show an amplification of the annual cycle in tropical precipitation with increased strength in both wet and dry seasons, but uncertainty is large and few studies have examined transition seasons. Here we analyze coupled climate model projections of global land monsoons and show a redistribution of precipitation from spring to summer in northern (North America, West Africa and Southeast Asia) and southern (South America, Southern Africa) regions. The annual cycle changes are global in scale. Two mechanisms, remote (based on tropospheric stability) and local (based on low level and surface moisture), are evaluated through the annual cycle. Increases in tropospheric stability persist from winter into spring and are reinforced by a reduction in surface moisture conditions, suggesting that in spring both remote and local mechanisms act to inhibit convection. This enhanced spring convective barrier leads to reduced early season rainfall; however, once sufficient increases in moisture (by transport) are achieved, decreases in tropospheric stability result in increased precipitation during the late rainy season. Further examination of this mechanism is needed in observations and models, as the projected changes would have substantial implications for agriculture, water management, and disaster preparedness.

An observational study covering the period 1950–2002 examines a seasonal reversal in the ENSO rainfall signal in the north-central Philippines. In boreal Summer of El Niño (La Niña) events, above (below) average rainfall typically occurs in this area. Rainfall anomalies of opposite sign develop across the country in the subsequent fall. This study investigates the seasonal evolution of the anomalous atmospheric circulation over the western North Pacific (WNP) during both El Niño and La Niña and places these features in the context of the large-scale evolution of ENSO events, including an analysis of changes in tropical cyclone activity affecting the Philippines. The results show that during boreal summer of El Niño (La Niña) events, a relatively narrow, zonally elongated band of enhanced (reduced) low-level westerlies develops across the WNP which serves to increase (decrease) the summer monsoon flow and moisture flux over the north-central Philippines and is associated with an increase (decrease) in the strength of the WNP monsoon trough via the anomalous relative vorticity. Tropical cyclone activity is shown to be enhanced (reduced) in the study region during boreal summer of El Niño (La Niña) events, which is related to the increase (decrease) of mid-level atmospheric moisture, as diagnosed using a genesis potential index. The subsequent evolution shows development of an anomalous anticyclone (cyclone) over the WNP in El Niño (La Niña) and the well-known tendency for below (above) average rainfall in the fall. Prolonged ENSO events also exhibit seasonal rainfall sign reversals in the Philippines with a similar evolution in atmospheric circulation.

The International Research Institute for Climate and Society has been issuing experimental seasonal tropical cyclone activity forecasts for several ocean basins since early 2003. In this paper we describe the method used to obtain these forecasts, and evaluate their performance. The forecasts are based on tropical cyclone-like features detected and tracked in a low-resolution climate model, namely ECHAM4.5. The simulation skill of the model using historical observed sea surface temperatures (SSTs) over several decades, as well as with SST anomalies persisted from the month ending at the forecast start time, is discussed. These simulation skills are compared with skills of purely statistically based hindcasts using as predictors observed SSTs preceding the forecast start time. For the recent 6-year period during which real-time forecasts have been made, the skill of the raw model output is compared with that of the subjectively modified probabilistic forecasts actually issued. Despite variations from one basin to another, the hindcast skills of the dynamical and statistical forecast approaches are found, overall, to be approximately equivalent. The dynamical forecasts require statistical post-prossessing (calibration) to be competitive with, and in some circumstances superior to, the statistical models. Hence, during the recent period of real-time forecasts, the subjective forecasts are found to have resulted in probabilistic skill better than that of the raw model output, primarily because of the forecasters' elimination of the systematic bias of "overconfidence" in the model's forecasts. Prospects for the future improvement of dynamical tropical cyclone prediction are considered.

International audience; A probabilistic clustering technique is used to describe tropical cyclone tracks in the eastern North Pacific, on the basis of their shape and location. The best track data set is decomposed in terms of three clusters; these clusters are analyzed in terms of genesis location, trajectory, landfall, intensity, seasonality, and their relationships with the El Niño-Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO). Longitudinal track location plays a strong discriminating role in the regression mixture model's solution, with the average track orientation becoming more zonal toward the west. This progression encapsulates well the relationship between tropical cyclones over the eastern tropical Pacific and the MJO or ENSO. Two of the clusters describe tropical cyclones (TCs) with tracks that lie near the coast of Mexico and Central America. The most frequent cluster contains tracks that trend west-northwestward, while the second most frequent one has genesis locations that lie slightly to the southeast of those in the most frequent cluster and tracks that run typically parallel to the Central American coast. This second cluster is shown to be significantly associated with the westerly phase of the MJO. The third, least frequent cluster contains TCs with westward trajectories over the central and eastern equatorial Pacific; some of these TCs have an impact on Hawaii and other islands, as far as the central and western North Pacific regions. The least frequent cluster is strongly related to ENSO, while the others are not; it occurs significantly more frequently during El Niño conditions. Examination of the large-scale patterns of atmospheric circulation and sea surface temperature associated with each of our three clusters are consistent with previous studies. Anomalous low-level westerly zonal winds from the monsoon trough and MJO meet anomalous easterlies near the region of genesis in each cluster.

[1] The thermodynamic theory for the physics of a mature tropical cyclone (TC) tells us that the cyclone's intensity cannot exceed an upper bound, the potential intensity (PI). This combined with an empirical result due to Emanuel leads to a prediction of average TC intensity change, given the change in PI. The slope of the predicted relationship between percentagewise variations in PI and those in intensity can vary between 0.5 and 1, depending on the mean PI and on what threshold is applied to the intensity data. For the Atlantic and Pacific, typical values are around 0.65 when tropical storms are excluded and 0.8 when they are included. The authors use best track data for the North Atlantic and western North Pacific, combined with PI computed from reanalysis data sets, to test these predictions. The results show that observed interannual variations of maximum TC intensity are consistent with the predictions of PI theory. Modest fractions of the variance in actual intensity are explained by PI variations. Much of the interannual variation in PI experienced by the storms comes from variation in TC tracks, so that the storms in different years are more or less likely to sample regions of high PI, rather than from variations in PI at a fixed location.

To enable downscaling of seasonal prediction and climate change scenarios, long-term baseline regional climatologies which employ global model forcing are needed for South America. As a first step in this process, this work examines climatological integrations with a regional climate model using a continental scale domain nested in both reanalysis data and multiple realizations of an atmospheric general circulation model (GCM). The analysis presents an evaluation of the nested model simulated large scale circulation, mean annual cycle and interannual variability which is compared against observational estimates and also with the driving GCM for the Northeast, Amazon, Monsoon and Southeast regions of South America. Results indicate that the regional climate model simulates the annual cycle of precipitation well in the Northeast region and Monsoon regions; it exhibits a dry bias during winter (July–September) in the Southeast, and simulates a semi-annual cycle with a dry bias in summer (December–February) in the Amazon region. There is little difference in the annual cycle between the GCM and renalyses driven simulations, however, substantial differences are seen in the interannual variability. Despite the biases in the annual cycle, the regional model captures much of the interannual variability observed in the Northeast, Southeast and Amazon regions. In the Monsoon region, where remote influences are weak, the regional model improves upon the GCM, though neither show substantial predictability. We conclude that in regions where remote influences are strong and the global model performs well it is difficult for the regional model to improve the large scale climatological features, indeed the regional model may degrade the simulation. Where remote forcing is weak and local processes dominate, there is some potential for the regional model to add value. This, however, will require improvments in physical parameterizations for high resolution tropical simulations.

In March 2006, the International Research Institute for Climate and Society (IRI) hosted a two and a half day workshop on "Tropical Cyclones and Climate". The centerpiece of the workshop was a set of invited lectures, with a modest number of contributed oral presentations and a small poster session. Relatively lengthy discussion periods were built into the schedule, allowing in-depth discussion of the presentations and related issues.

The authors investigate the influence of western North Pacific (WNP) tropical cyclones (TCs) on their large-scale environment by lag regressing various large-scale climate variables [atmospheric temperature, winds, relative vorticity, outgoing longwave radiation (OLR), column water vapor, and sea surface temperature (SST)] on an index of TC activity [accumulated cyclone energy (ACE)] on a weekly time scale. At all leads and lags out to several months, persistent, slowly evolving signals indicative of the El Niño–Southern Oscillation (ENSO) phenomenon are seen in all the variables, reflecting the known seasonal relationship of TCs in the WNP to ENSO. Superimposed on this are more rapidly evolving signals, at leads and lags of one or two weeks, directly associated with the TCs themselves. These include anomalies of positive low-level vorticity, negative OLR, and high column water vapor associated with anomalously positive ACE, found in the region where TCs most commonly form and develop. In the same region, lagging ACE by a week or two and so presumably reflecting the influence of TCs on the local environment, signals are found that might be expected to negatively influence the environment for later cyclogenesis. These signals include an SST reduction in the primary region of TC activity, and a reduction in column water vapor and increase in OLR that may or may not be a result of the SST reduction. On the same short time scale, an increase in equatorial SST near and east of the date line is seen, presumably associated with equatorial surface westerly anomalies that are also found. This, combined with the correlation between ACE and ENSO indices on the seasonal time scale, suggests the possibility that TCs may play an active role in ENSO dynamics.

The properties of tropical cyclones in three atmospheric general circulation models (AGCMs) with low-resolution are discussed. The models are analysed for a period of 40 years. Characteristics of the tropical cyclones in the models are analysed and compared with those of observations, such as genesis position, number of cyclones, accumulated cyclone activity, number of storm days, tracks, and others. The three AGCMs have different levels of skill in simulating the different aspects of tropical cyclone activity in different regions. Some of the weak and strong features in simulating tropical cyclone activity variables are common for the three models, others are unique for each model and basin. The relation between model tropical cyclones and ENSO is analyzed in a paper currently in preparation.

"Tropical cyclogenesis" in a low-resolution Atmospheric General Circulation model is studied, focusing on the Western North Pacific region during the June-October typhoon season. Time-dependent composites of the cyclones are formed and analyzed, with a focus on the temporal evolution of quantities averaged in space around the storm centers. Day zero of each composite corresponds to the time at which the cyclone passes the criteria for detection. Some variables whose magnitude is related to cyclone intensity (such as low-level vorticity and surface wind speed) show similar temporal evolution, with a slight decrease up to a few days before day zero, a weak local minimum at that point, and a strong increase after that for a week or more. The relative humidity at low levels has its minimum somewhat later, at about day zero. The mean composite environmental vertical wind shear lacks a minimum and increases monotonically through the entire genesis period until a week after day zero. This variation is mostly due to the mean cyclone track's moving through regions of different climatological shear, which varies monotonically from easterly to westerly, crossing zero shortly after day zero, and would be consistent with a controlling role of the shear on model cyclogenesis. A signal in the skewness of the lower-level relative humidity distribution over the ensemble suggests that a dry lower troposphere can prevent development of a model cyclone. The local minimum in many variables' time series suggests the presence of an initial disturbance that is suddenly enhanced, becoming a model tropical cyclone, as has been noted in observations.

The main features of three atmospheric general circulation models forced with monthly-mean, observed sea surface temperature for the 1979-1995 period are analyzed and compared with observational data. The ensemble means and intra-ensemble standard deviations of several variables were investigated for the two seasons December-January-February and June-July-August. Correlations of the ensemble mean anomalies with observational data and with the indices Nino-3 and the Atlantic Dipole were also calculated. The probability distribution function of the precipitation at different regions was also examined, as well as the internal and external variance of the precipitation in the three models. No model has uniformly better characteristics than the others. On the contrary, each model has strengths and weaknesses that depend on the region and season.

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.

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in U.S. landfalling systems. Here, the authors present a tentative study that examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1°–0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and subtropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity, and power dissipation index in each cluster are documented for both configurations. The authors’ results show that, except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. The authors also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, the authors examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.

Volcanic eruptions can inject a large amount of aerosol particles, which interact with solar radiation and consequently can affect the climate worldwide, hence the intensity and frequency of extreme events for a few years following the eruption. However, only a handful of studies have investigated the impacts of volcanic eruptions on tropical cyclone activity. Through a set of sensitivity modeling experiments, our study demonstrates that volcanic eruptions by shifting the Intertropical convergence zone can impact tropical cyclone activity up to 4 years following the eruption. These results will prove valuable to society, allowing us to better prepare for the consequences of changes in tropical cyclone activity following large volcanic eruptions.

In this review, we provide a historical overview of the simulation of tropical cyclones (TCs) in climate models, from the first attempts in the 1970s to the current state-of-the-art models. We discuss the status of TC simulation across multiple time scales, from intraseasonal, seasonal, and decadal, to climate change. One of the limitations on the simulation of TCs in climate models has been, and continues to be, balancing the high resolution necessary to accurately simulate TCs themselves with the need to run simulations for many years and using many ensemble members. Several approaches to inferring TC activity indirectly, rather than relying on the models own under-resolved TCs, are reviewed, including the use of TC genesis indices based on the large-scale environment and downscaling methods such as the use of regional climate models and statistical–dynamical techniques. We also provide an update on the status of climate change projections from the current class of models, where it is feasible to directly track the model's TCs. While there has been great progress in the capability of climate models to simulate TCs and provide useful forecasts and projections across multiple time scales, there remains much work to be done. We list some of the sources of uncertainty and model sensitivity, describe where improvements are necessary, and provide a few suggestions for promising research directions.

We analyze, using Poisson regressions, the main climate influences on North Atlantic tropical cyclone activity. The analysis is performed using not only various time series of basin‐wide storm counts but also various series of regional clusters, taking into account shortcomings of the hurricane database through estimates of missing storms. The analysis confirms that tropical cyclones forming in different regions of the Atlantic are susceptible to different climate influences. We also investigate the presence of trends in these various time series, both at the basin‐wide and cluster levels, and show that, even after accounting for possible missing storms, there remains an upward trend in the eastern part of the basin and a downward trend in the western part. Using model selection algorithms, we show that the best model of Atlantic tropical cyclone activity for the recent past is constructed using Atlantic sea surface temperature and upper tropospheric temperature, while for the 1878–2015 period, the chosen covariates are Atlantic sea surface temperature and El Niño–Southern Oscillation. We also note that the presence of these artificial trends can impact the selection of the best covariates. If the underlying series shows an upward trend, then the mean Atlantic sea surface temperature captures both interannual variability and the upward trend, artificial or not. The relative sea surface temperature is chosen instead for stationary counts. Finally, we show that the predictive capability of the statistical models investigated is low for U.S. landfalling hurricanes but can be considerably improved when forecasting combinations of clusters whose hurricanes are most likely to make landfall.

Two years of drought in Southeast Brazil have led to water shortages in São Paulo, the country's most populous city. We examine the observed drought during austral summers of 2013/2014 and 2014/2015 and the related large-scale dynamics. The 2013–2014 precipitation deficits were more concentrated in the state of São Paulo, while in 2014–2015 moderate deficits were seen throughout the region. We find that a persistent warm sea surface temperature (SST) anomaly in the western tropical Pacific Ocean was an important driver of drought via atmospheric teleconnection in the two December–February seasons. The warm SST and associated convective heating initiated a wave train across the South Pacific. The resulting anticyclonic geopotential height anomaly over the southwest Atlantic expanded the westward margin of the South Atlantic high and prevented low-pressure systems from entering southeast Brazil from midlatitudes. This mechanism suggests a hemispheric symmetry to that proposed for the recent California drought.

The authors describe the characteristics of tropical cyclone (TC) activity in the GISS general circulation ModelE2 with a horizontal resolution 1°×1°. Four model simulations are analysed. In the first, the model is forced with sea surface temperature (SST) from the recent historical climatology. The other three have different idealised climate change simulations, namely (1) a uniform increase of SST by 2 degrees, (2) doubling of the CO2 concentration and (3) a combination of the two. These simulations were performed as part of the US Climate Variability and Predictability Program Hurricane Working Group. Diagnostics of standard measures of TC activity are computed from the recent historical climatological SST simulation and compared with the same measures computed from observations. The changes in TC activity in the three idealised climate change simulations, by comparison with that in the historical climatological SST simulation, are also described. Similar to previous results in the literature, the changes in TC frequency in the simulation with a doubling CO2 and an increase in SST are approximately the linear sum of the TC frequency in the other two simulations. However, in contrast with previous results, in these simulations the effects of CO2 and SST on TC frequency oppose each other. Large-scale environmental variables associated with TC activity are then analysed for the present and future simulations. Model biases in the large-scale fields are identified through a comparison with ERA-Interim reanalysis. Changes in the environmental fields in the future climate simulations are shown and their association with changes in TC activity discussed.