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Numerous recent tropical cyclones have caused extreme rainfall and flooding events in the CONUS. Climate change is contributing to heavier extreme rainfall around the world. Modeling studies have suggested that tropical cyclones may be particularly efficient engines for transferring the additional water vapor in the atmosphere into extreme rainfall. This paper develops a new indicator for climate change using the enhanced rainfall metric to evaluate how the frequency and/or intensity of extreme rainfall around tropical cyclones has changed. The enhanced rainfall metric relates the amount of rain from a storm over a given location to the 5-yr return period rainfall in that location to determine the severity of the event. The annual area exposed to tropical-cyclone-related 5-yr rainfall events is increasing, which makes it a compelling climate change indicator. Quantile regression illustrates that the distribution of tropical cyclone rainfall is also changing. For tropical storms, all quantiles are increasing. However, major hurricanes show large increases in their most extreme rainfall. This study does not attempt to make any detection claims (vs natural variability) or attribution of the observed trends to anthropogenic forcing. However, the sensitivity of the results to natural variability in tropical cyclone frequency was somewhat constrained by comparing 2 decades from the previous active era (1951–70) with two from the current era (2001–20). This comparison also shows that both the mean rainfall and the maximum rainfall associated with tropical cyclones are increasing over most areas of the eastern CONUS with the most significant increases from northern Alabama to the southern Appalachians. Significance Statement: The purpose of this study is to analyze the changes in frequency and magnitude of extreme precipitation events associated with tropical cyclones with the goal of developing a new indicator for climate change. This is important because heavy rainfall and associated flooding is one of the primary causes of tropical cyclone destruction and fatalities, especially in inland locations away from where storms initially make landfall. Our results show that both the frequency and magnitude of extreme rainfall events from tropical cyclones have increased over the CONUS. The strongest storms (major hurricanes) also show more of an increase in extreme rainfall than storms of weaker intensities. [ABSTRACT FROM AUTHOR]

Studying temperature probability distributions and the physical processes that shape them is important for understanding extreme temperature events. Previous work has used a conditional mean temperature framework to reveal whether horizontal temperature advection drives temperature to extreme or median values at a specific location as a method to dynamically interpret temperature probability distributions. In this paper, we generalize this method to study how other processes shape temperature probability distributions and explore the diverse effects of horizontal temperature advection on temperature probability distributions at different locations and different temperature percentiles. We apply this generalized method to several representative regions to demonstrate its use. We find that temperature advection drives temperatures toward more extreme values over most land in the midlatitudes (i.e., cold air advection occurs during cold anomalies and warm air advection occurs during warm anomalies). In contrast, we find that horizontal temperature advection dampens temperature anomalies in some coastal summer monsoon regions, where extreme temperatures result from other processes, such as horizontal humidity advection and vertical temperature advection. By calculating the mean of processes conditioned on the temperature percentile, this method enables composite analysis of processes that contribute to events for all percentiles and a range of processes. We show examples of composites at different percentiles for certain processes and regions to illustrate the conditional mean analysis. This general approach may benefit future studies related to temperature probability distributions and extreme events. [ABSTRACT FROM AUTHOR]

A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the early-twentieth-century Arctic warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and subdaily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from 10 individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days, day-to-day temperature variability, and the onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the contemporary Arctic warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7°C) and Canadian Arctic (1.9°C) regions. A shortening of winter and lengthening of summer were noted. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW. Significance Statement: It is well established that human activity (particularly increased greenhouse gas emissions) is the primary driving mechanism of the recent dramatic warming in the Arctic. However, the causes of a similar warming here in the first half of the twentieth century remain uncertain. The limited knowledge about the climate of that period—which mainly results from the low resolution of data—is a significant obstacle to a definitive determination of the forcing mechanisms. Therefore, the main aim of our paper is to improve our understanding of specific aspects of weather and climate (including extremes) using long-term series of daily and subdaily data that have rarely been applied for this purpose. This new, more comprehensive knowledge about the historical Arctic climate should allow the scientific community (particularly climate modelers) to better validate both climate models and reanalysis products and, consequently, to more precisely identify the causes of the early-twentieth-century Arctic warming. [ABSTRACT FROM AUTHOR]

Global Historical Climate Network (GHCN) data are used to characterize changes in large-scale fall extreme precipitation in the mid-Atlantic and the northeast United States. Days with the highest regional extreme precipitation total [extreme precipitation (EP) days] are sorted into weather types based on tropical cyclone (TC), atmospheric river (AR), and extreme integrated water vapor transport (IVT) influences. Increased cumulative precipitation from EP days is attributed primarily to three sources. First, over the mid-Atlantic states, Pennsylvania, and eastern New England, large increasing trends are found in precipitation occurring on EP days attributed to TC-related weather types. These increases are due to a late-1990s increase in TC frequency, which manifests primarily as increased TC remnants in the mid-Atlantic area. Second, over New York State and central and northern New England, there are increasing trends in EP day precipitation from AR-related weather types. Finally, there is evidence of increasing extreme IVT-related precipitation in the absence of ARs and TCs. However, when taking into account prior TC influences, it is found that a combination of TC-related weather types accounts for much of the increasing EP day precipitation trend. These trends are then compared to EP day synoptic changes relating to atmospheric moisture content and transport. Results indicate that fall EP days have become warmer and moister, but that this does not necessarily translate to higher IVT because wind speeds have stayed the same or slowed. This is consistent with fall climatological changes during the 1979–2019 analysis period, including higher atmospheric water content and slowed westerlies in the vicinity of the mid-Atlantic. Significance Statement: This paper sorts days with high extreme precipitation totals in the mid-Atlantic and northeast United States fall into categories based on the presence of factors such as tropical cyclones (TCs), atmospheric rivers (ARs), and other extreme moisture transport. These days have become more frequent between 1979 and 2019, in part due to events with TC influences. However, the synoptic environment on extreme days has also changed, becoming warmer and moister. Many of the most extreme events involve combined AR and TC influences. This is important because it shows that 1) large-scale extreme precipitation has become more common and has changed synoptically and 2) interactions between tropical and non-tropical systems are a key factor for extreme events in this part of the country. Future work might investigate how changes in TC frequency, moisture transport, and jet stream patterns will affect these events in a future climate. [ABSTRACT FROM AUTHOR]

This paper provides an updated analysis of observed changes in extreme precipitation using high-quality station data up to 2018. We examine changes in extreme precipitation represented by annual maxima of 1-day (Rx1day) and 5-day (Rx5day) precipitation accumulations at different spatial scales and attempt to address whether the signal in extreme precipitation has strengthened with several years of additional observations. Extreme precipitation has increased at about two-thirds of stations and the percentage of stations with significantly increasing trends is significantly larger than that can be expected by chance for the globe, continents including Asia, Europe, and North America, and regions including central North America, eastern North America, northern Central America, northern Europe, the Russian Far East, eastern central Asia, and East Asia. The percentage of stations with significantly decreasing trends is not different from that expected by chance. Fitting extreme precipitation to generalized extreme value distributions with global mean surface temperature (GMST) as a covariate reaffirms the statistically significant connections between extreme precipitation and temperature. The global median sensitivity, percentage change in extreme precipitation per 1 K increase in GMST is 6.6% (5.1% to 8.2%; 5%–95% confidence interval) for Rx1day and is slightly smaller at 5.7% (5.0% to 8.0%) for Rx5day. The comparison of results based on observations ending in 2018 with those from data ending in 2000–09 shows a consistent median rate of increase, but a larger percentage of stations with statistically significant increasing trends, indicating an increase in the detectability of extreme precipitation intensification, likely due to the use of longer records. [ABSTRACT FROM AUTHOR]

This paper presents a global picture of the dynamic processes and synoptic characteristics of extratropical extreme precipitation events (EPEs), defined as annual maximum daily precipitation averaged over 7.58 3 7.58 regional boxes. Based on the quasigeostrophic omega equation, extreme precipitation can be decomposed into components forced by large-scale adiabatic disturbances and amplified by diabatic heating feedback. The spatial distribution of the diabatic feedback parameter is largely controlled by atmospheric precipitable water and captured by a simple model. Most spatial heterogeneities of EPEs in the middle and high latitudes are due to the spatial variations of large-scale adiabatic forcing. The adiabatic component includes the processes of vorticity advection, in which the synoptic vorticity advection by background wind dominates; temperature advection, in which the total meridional temperature advection by synoptic wind dominates; and boundary forcing. The synoptic patterns of EPEs in all extratropical regions can be classified into six clusters using the self-organizing map method: two clusters in low latitudes and four clusters in middle and high latitudes. Synoptic disturbances are characterized by strong pressure anomalies throughout the troposphere over the coastal regions and oceans and feature upper-level shortwave disturbances and a large westward tilt with height over land. Synoptic configurations favor moisture transport from ocean to land over coastal regions. [ABSTRACT FROM AUTHOR]

This paper examines the possible influence of external forcings on observed changes in precipitation extremes in the mid-to-high latitudes of Asia during 1958–2012 and attempts to identify particular extreme precipitation indices on which there are better chances to detect the influence of external forcings. We compare a recently compiled dataset of observed extreme indices with those from phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations using an optimal fingerprinting method. We consider six indices that characterize different aspects of extreme precipitation, including annual maximum amount of precipitation falling in 1 day (Rx1day) or 5 days (Rx5day), the total amount of precipitation from the top 5% or top 1% daily amount on wet days, and the fraction of the annual total precipitation from these events. For single-signal analysis, the fingerprints of external forcings including anthropogenic agents are robustly detected in most studied extreme indices over all Asia and for midlatitude Asia but not for high-latitude Asia. For two-signal analysis, anthropogenic influence is detectable in these indices over Asia at 5% or slightly less than 5% significance level, whereas natural influence is not detectable. In high-latitude Asia, anthropogenic influence is detected only in a fractional index, representing a stark contrast to the midlatitude and full Asia results. We find relatively smaller internal variability and thus higher signal-to-noise ratio in the fractional indices when compared with the other ones. Our results point to the need for studying precipitation extreme indices that are less affected by internal variability while still representing the relevant nature of precipitation extremes to improve the possibility of detecting a forced signal if one is present in the data. [ABSTRACT FROM AUTHOR]

In the U.S. Great Plains (GP), diagnosing precipitation variability is key in developing an understanding of the present and future availability of water in the region. Building on previous work investigating U.S. GP pluvial years, this study uses ERA twentieth century (ERA-20C) reanalysis data to investigate key circulation anomalies driving GP precipitation anomalies during a subset of GP pluvial years (called in this paper Pattern pluvial years). With previous research showing links between tropical Pacific sea surface temperature (SST) anomalies and GP climate variability, this study diagnoses the key circulation anomalies through an analysis of SSTs and their influence on the atmosphere. Results show that during Pattern southern Great Plains (SGP) pluvial years, central tropical Pacific SST anomalies are coincident with key atmospheric anomalies across the Pacific basin and North America. During northern Great Plains (NGP) Pattern pluvial years, no specific pattern of oceanic anomalies emerges that forces the circulation anomaly feature inherent in specific NGP pluvial years. Utilizing the results for SGP pluvial years, a conceptual model is developed detailing the identified pathway for the occurrence of circulation patterns that are favorable for pluvial years over the SGP. Overall, results from this study show the importance of the identified SGP atmospheric anomaly signal and the potential for predictability of such events. [ABSTRACT FROM AUTHOR]

Although it is critical to assess the accuracy of attribution studies, the fraction of attributable risk (FAR) cannot be directly assessed from observations since it involves the probability of an event in a world that did not happen, the 'natural' world where there was no human influence on climate. Instead, reliability diagrams (usually used to compare probabilistic forecasts to the observed frequencies of events) have been used to assess climate simulations employed for attribution and by inference to evaluate the attribution study itself. The Brier score summarizes this assessment of a model by the reliability diagram. By constructing a modeling framework where the true FAR is already known, this paper shows that Brier scores are correlated to the accuracy of a climate model ensemble's calculation of FAR, although only weakly. This weakness exists because the diagram does not account for accuracy of simulations of the natural world. This is better represented by two reliability diagrams from early and late in the period of study, which would have, respectively, less and greater anthropogenic climate forcing. Two new methods are therefore proposed for assessing the accuracy of FAR, based on using the earlier observational period as a proxy for observations of the natural world. It is found that errors from model-based estimates of these observable quantities are strongly correlated with errors in the FAR estimated in the model framework. These methods thereby provide new observational estimates of the accuracy in FAR. [ABSTRACT FROM AUTHOR]

Given the reality of anthropogenic global warming, it is tempting to seek an anthropogenic component in any recent change in the statistics of extreme weather. This paper cautions that such efforts may, however, lead to wrong conclusions if the distinctively skewed and heavy-tailed aspects of the probability distributions of daily weather anomalies are ignored or misrepresented. Departures of several standard deviations from the mean, although rare, are far more common in such a distinctively non-Gaussian world than they are in a Gaussian world. This further complicates the problem of detecting changes in tail probabilities from historical records of limited length and accuracy. A possible solution is to exploit the fact that the salient non-Gaussian features of the observed distributions are captured by so-called stochastically generated skewed (SGS) distributions that include Gaussian distributions as special cases. SGS distributions are associated with damped linear Markov processes perturbed by asymmetric stochastic noise and as such represent the simplest physically based prototypes of the observed distributions. The tails of SGS distributions can also be directly linked to generalized extreme value (GEV) and generalized Pareto (GP) distributions. The Markov process model can be used to provide rigorous confidence intervals and to investigate temporal persistence statistics. The procedure is illustrated for assessing changes in the observed distributions of daily wintertime indices of large-scale atmospheric variability in the North Atlantic and North Pacific sectors over the period 1872-2011. No significant changes in these indices are found from the first to the second half of the period. [ABSTRACT FROM AUTHOR]

The physical mechanisms and predictability associated with extreme daily rainfall in southeastern South America (SESA) are investigated for the December-February season in a two-part study. Through a k-mean analysis, this first paper identifies a robust set of daily circulation regimes that are used to link the frequency of rainfall extreme events with large-scale potential predictors at subseasonal-to-seasonal scales. This represents a basic set of daily circulation regimes related to the continental and oceanic phases of the South Atlantic convergence zone (SACZ) and wave train patterns superimposed on the Southern Hemisphere polar jet. Some of these recurrent synoptic circulation types are conducive to extreme rainfall events in the region through synoptic control of different mesoscale physical features and, at the same time, are influenced by climate phenomena that could be used as sources of potential predictability. Extremely high rainfall (as measured by the 95th and 99th percentiles) is associated with two of these weather types (WTs), which are characterized by moisture advection intrusions from lower latitudes and the Pacific Ocean; another three WTs, characterized by above-normal moisture advection toward lower latitudes or the Andes, are associated with dry days (days with no rain). The analysis permits the identification of several subseasonal-to-seasonal scale potential predictors that modulate the occurrence of circulation regimes conducive to extreme rainfall events in SESA. It is conjectured that a cross-time scale interaction between the different climate drivers improves the predictive skill of extreme precipitation in the region. [ABSTRACT FROM AUTHOR]

Transient Rossby wave packets (RWPs) are a prominent feature of the synoptic to planetary upper-tropospheric flow at the midlatitudes. Their demonstrated role in various aspects of weather and climate prompts the investigation of characteristic properties like their amplitude, phase speed, and group velocity. Traditional frameworks for the diagnosis of the two latter have so far remained nonlocal in space or time, thus preventing a detailed view on the spatiotemporal evolution of RWPs. The present work proposes a method for the diagnosis of horizontal Rossby wave phase speed and group velocity locally in space and time. The approach is based on the analytic signal of upper-tropospheric meridional wind velocity and RWP amplitude, respectively. The new diagnostics are first applied to illustrative examples from a barotropic model simulation and the real atmosphere. The main seasonal and interregional variability features of RWP amplitude, phase speed, and group velocity are then explored using ERA5 reanalysis data for the time period 1979-2018. Apparent differences and similarities in these respects between the Northern and Southern Hemispheres are also discussed. Finally, the role of RWP amplitude and phase speed during central European short-lived and persistent temperature extremes is investigated based on changes of their distribution compared to the climatology of the region. The proposed diagnostics offer insight into the spatiotemporal variability of RWP properties and allow the evaluation of their implications at low computational demands. [ABSTRACT FROM AUTHOR]

Sudden stratospheric warmings (SSWs) are characterized by a pronounced increase of the stratospheric polar temperature during the winter season. Different definitions have been used in the literature to diagnose the occurrence of SSWs, yielding discrepancies in the detected events. The aim of this paper is to compare the SSW climatologies obtained by different methods using reanalysis data. The occurrences of Northern Hemisphere SSWs during the extended-winter season and the 1958-2014 period have been identified for a suite of eight representative definitions and three different reanalyses. Overall, and despite the differences in the number and exact dates of occurrence of SSWs, the main climatological signatures of SSWs are not sensitive to the considered reanalysis. The mean frequency of SSWs is 6.7 events decade−1, but it ranges from 4 to 10 events, depending on the method. The seasonal cycle of events is statistically indistinguishable across definitions, with a common peak in January. However, the multidecadal variability is method dependent, with only two definitions displaying minimum frequencies in the 1990s. An analysis of the mean signatures of SSWs in the stratosphere revealed negligible differences among methods compared to the large case-to-case variability within a given definition. The stronger and more coherent tropospheric signals before and after SSWs are associated with major events, which are detected by most methods. The tropospheric signals of minor SSWs are less robust, representing the largest source of discrepancy across definitions. Therefore, to obtain robust results, future studies on stratosphere-troposphere coupling should aim to minimize the detection of minor warmings. [ABSTRACT FROM AUTHOR]

The frequent occurrence of extreme cold waves under climate change has attracted widespread attention. Based on the Japanese 55-year Reanalysis daily dataset from 1958 to 2021, we use a newly developed dynamic metric, the local finite-amplitude wave activity (LWA), to explore the precursory signals, outburst conditions, and key dynamic features of extreme cold waves over eastern China from the perspective of synoptic climatology. The statistical results show that approximately 40% of extreme cold waves have the following features. First, the formation of significant positive LWA anomalies over the Balkhash–Baikal region is an evident precursory signal, which is accompanied by significant cold surface air temperature anomalies that accumulate over mid- and high-latitude Eurasia. Second, the appearance of extreme positive LWA anomalies over the region east of Lake Baikal (ELB) is necessary for subsequent outbursts of extreme cold waves. These extreme positive LWA anomalies indicate the meridionally enhanced planetary trough over East Asia and advection of the accumulated cold air masses southeastward to eastern China. Third, the evident positive change in the LWA anomalies over the ELB is mainly attributable to the convergence of the zonal LWA flux due to the zonal wind in the eddy-free state and Stokes drift flux over the eastern area of the ELB and the convergence of the meridional eddy heat flux over the western area. This study demonstrates that the LWA could be used as a simple and feasible metric for monitoring and forecasting extreme cold waves. Significance Statement: Enhanced waviness in circulation usually occurs before and during the outburst of extreme cold waves over eastern China. With a state-of-the-art diagnostic tool, the local finite-amplitude wave activity (LWA), the present study reveals both precursory signals and outburst conditions of these extreme cold events from the perspective of synoptic climatology. This study not only deepens our understanding of the dynamic process for extreme cold events over eastern China but also offers a method for monitoring and forecasting those extreme events. Our work also provides a method for studying other extreme climate events that are closely related to large-amplitude circulation waviness over the middle and high latitudes. [ABSTRACT FROM AUTHOR]

The vertical structure of Arctic warming is of great importance and attracts increasing attention. This study defines two types of Arctic warming events (deep versus shallow) according to their temperature profiles averaged over the Barents–Kara Seas (BKS), and thereupon compares their characteristics and examines their difference in generation through thermodynamic diagnoses. A deep Arctic warming event—characterized by significant bottom-heavy warming extending from the surface into the middle-to-upper troposphere—emanates from the east of Greenland and then moves downstream toward the BKS primarily through zonal temperature advection. The peak day of deep warming event lags that of the precipitation and resultant diabatic heating over southeast Greenland by about four days, suggesting that the middle-to-high tropospheric BKS warming is likely triggered by the enhanced upstream convection at the North Atlantic high latitudes. In contrast, a shallow warming event—manifested by warming confined within the lower troposphere—is preceded by the meridional advection of warm air from inland Eurasia. These anomalous southerlies over Eurasian lands during shallow warming events are related to the eastward extension of the deepened Icelandic low. During deep warming events, the in situ reinforcement of the Icelandic low favors abundant moisture transport interplaying with the southeast Greenland terrain, leading to intense precipitation and latent heat release there. Both deep and shallow warming events are accompanied by Eurasian cooling, but the corresponding cooling of the deep warming event is profoundly stronger. Further, intraseasonal deep Arctic warming events could explain nearly half of the winter-mean change in the warm Arctic–cold Eurasia anomaly. Significance Statement: Divergent conclusions on whether Arctic warming is influencing the midlatitudes impede a clear understanding of the warm Arctic–cold Eurasia (WACE) phenomenon. Recent findings that on the interannual or longer time scales, Eurasian cooling tends to occur in the presence of deep rather than shallow Arctic warming have attracted increasing concern regarding the vertical structure of Arctic warming. On this basis, here we classify intraseasonal Arctic warming events into deep and shallow groups and contrast them from various aspects. Emerging near eastern Greenland and associated with upstream convection activities, intraseasonal deep Arctic warming events are accompanied by significant Eurasian cooling, largely determining the seasonal-mean WACE condition. However, caused by meridional temperature advection from Eurasian lands, shallow warming events less correlate with Eurasian cooling. [ABSTRACT FROM AUTHOR]

We investigate the large-scale weather patterns during extreme precipitation (PEx) events over the conterminous United States (CONUS) by applying a version of the quasigeostrophic (QG) omega equation. This work aims to develop a climatology of the weather patterns most related to PEx events during current climate. Extreme events are examined for each of seven regions defined by consistent annual cycles of precipitation and spanning the CONUS. For the CONUS we train several self-organizing maps (SOM) on a pressure–time series of vertical velocity from each of the advective forcing terms in the QG omega equation for each extreme event. The unsupervised learning of the SOM allows us to identify the most descriptive set of nine patterns in vertical velocity associated with precipitation extremes. This method finds multiple frontal- and cyclone-driven patterns while grouping primarily convective events into one pattern. Frontal events include a synoptic pattern consistent with West Coast atmospheric river events as well as pattern groups linked to developing and to mature ("occluded") frontal cyclones. The primary patterns found during PEx events vary seasonally and geographically. Frontal cyclone patterns are most common during PEx events during summer in the part of the Great Plains and during winter for the Northeast, Southeast, Pacific Northwest, and Southwest. Convection is the most common pattern during summer in all regions. Except in the Southeast, the annual cycles of monthly number of PEx events and average precipitation match well, partially validating our choice of regions to aggregate PEx events. [ABSTRACT FROM AUTHOR]

This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986-2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes [including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p)], is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role. [ABSTRACT FROM AUTHOR]

This paper undertakes a hydrometeorological analysis of flood events in the central United States. Vertically integrated horizontal water vapor transport over 1979-2011 is calculated in the ECMWF Interim Re-Analysis (ERA-Interim) and used in an algorithm to identify episodes of high moisture transport, or atmospheric rivers (ARs), over the central United States. The AR events are almost evenly divided among the seasons (143 during the winter, 144 during the spring, and 124 during the fall), with a minimum (40) during the summer. The annual maxima (AM) floods from 1105 basins over the period 1980-2011 are used as a measure of the hydrologic impact of the AR events. Of these basins, 470 (or 42.5%) had more than 50% of their AM floods linked to ARs. Furthermore, 660 of the 1105 basins (59.7%) had 5 or more of their top 10 AM floods related to ARs, indicating that ARs control the upper tail of the flood peak distribution over large portions of the study area. The seasonal composite average of mean sea level pressure anomalies associated with the ARs shows a trough located over the central United States and a ridge over the U.S. East Coast, leading to southerly winds and the advection of moisture over the study region. Based on the findings of this study, ARs are a major flood agent over the central United States. [ABSTRACT FROM AUTHOR]

In a recent paper, a climatology of tropical moisture exports (TMEs) to the Northern Hemisphere (NH) was constructed on the basis of 7-day forward trajectories, started daily from the tropical lower troposphere, which were required to reach a water vapor flux of at least 100 g kg−1 m s−1 somewhere north of 35°N. It was shown that TMEs contribute significantly to regional precipitation. Here, the authors complement and extend this work by (i) using 6-hourly European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data from 1979 to 2010 instead of the earlier 40-yr ECMWF Re-Analysis (ERA-40), (ii) extending the climatology to the Southern Hemisphere (SH), and (iii) relating TME events to atmospheric rivers (ARs) previously discussed in the literature. The main conclusions are as follows: First, the TME climatology is not sensitive to the reanalysis dataset. Second, SH TME shows four activity centers: the central and eastern Pacific Ocean (170°-90°W, near the South Pacific convergence zone), eastern South America and the adjacent Atlantic Ocean (60°W-0°, near the South Atlantic convergence zone), the western Indian Ocean (30°-80°E), and western Australia (110°-140°E). Third, TME activity in the SH peaks in austral summer because of higher moisture contents and possibly because of increased Rossby wave activity from the NH. Fourth, El Niño warm events are associated with reduced activity over the South Pacific and increased activity over the South Atlantic and around Australia, while correlations with the southern annular mode are generally weak. Finally, around 90% of all ARs affecting the U.S. West Coast during December-May are connected to TME events, revealing their importance for heavy rain and flooding. [ABSTRACT FROM AUTHOR]

Climate model simulations of daily precipitation statistics from the third phase of the Coupled Model Intercomparison Project (CMIP3) were evaluated against precipitation observations from North America over the period 1979-99. The evaluation revealed that the models underestimate the intensity of heavy and extreme precipitation along the Pacific coast, southeastern United States, and southern Mexico, and these biases are robust among the models. The models also overestimate the intensity of light precipitation events over much of North America, resulting in fairly realistic mean precipitation in many places. In contrast, heavy precipitation is simulated realistically over northern and eastern Canada, as is the seasonal cycle of heavy precipitation over a majority of North America. An evaluation of the simulated atmospheric dynamics and thermodynamics associated with extreme precipitation events was also conducted using the North American Regional Reanalysis (NARR). The models were found to capture the large-scale physical mechanisms that generate extreme precipitation realistically, although they tend to overestimate the strength of the associated atmospheric circulation features. This suggests that climate model deficiencies such as insufficient spatial resolution, inadequate representation of convective precipitation, and overly smoothed topography may be more important for biases in simulated heavy precipitation than errors in the large-scale circulation during extreme events. [ABSTRACT FROM AUTHOR]

In this paper the statistics of daily maximum and minimum surface air temperature at weather stations in the southeast United States are examined as a function of the El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) phase. A limited number of studies address how the ENSO and/or AO affect U.S. daily-as opposed to monthly or seasonal-temperature averages. The details of the effect of the ENSO or AO on the higher-order statistics for wintertime daily minimum and maximum temperatures have not been clearly documented. Quality-controlled daily observations collected from 1960 to 2009 from 272 National Weather Service Cooperative Observing Network stations throughout Florida, Georgia, Alabama, and South and North Carolina are used to calculate the first four statistical moments of minimum and maximum daily temperature distributions. It is found that, over the U.S. Southeast, winter minimum temperatures have higher variability than maximum temperatures and La Niña winters have greater variability of both minimum and maximum temperatures. With the exception of the Florida peninsula, minimum temperatures are positively skewed, while maximum temperatures are negatively skewed. Stations in peninsular Florida exhibit negative skewness for both maximum and minimum temperatures. During the relatively warmer winters associated with either a La Niña or AO+, negative skewnesses are exacerbated and positive skewnesses are reduced. To a lesser extent, the converse is true of the El Niño and AO−. The ENSO and AO are also shown to have a statistically significant effect on the change in kurtosis of daily maximum and minimum temperatures throughout the domain. [ABSTRACT FROM AUTHOR]

Formal detection and attribution analyses of changes in daily extremes give evidence of a significant human influence on the increasing severity of extremely warm nights and decreasing severity of extremely cold days and nights. This paper presents an optimal fingerprinting analysis that also detects the contributions of external forcings to recent changes in extremely warm days using nonstationary extreme value theory. The authors'' analysis is the first that attempts to partition the observed change in warm daytime extremes between its anthropogenic and natural components and hence attribute part of the change to possible causes. Changes in the extreme temperatures are represented by the temporal changes in a parameter of an extreme value distribution. Regional distributions of the trend in the parameter are computed with and without human influence using constraints from the global optimal fingerprinting analysis. Anthropogenic forcings alter the regional distributions, indicating that extremely warm days have become hotter. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) has a profound influence on the occurrence of extreme precipitation events at local and regional scales in the present-day climate, and thus it is important to understand how that influence may change under future global warming. We consider this question using the large-ensemble simulations of CESM2, which simulates ENSO well historically. CESM2 projects that the influence of ENSO on extreme precipitation will strengthen further under the SSP3–7.0 scenario in most regions whose extreme precipitation regimes are strongly affected by ENSO in the boreal cold season. Extreme precipitation in the boreal cold season that exceeds historical thresholds is projected to become more common throughout the ENSO cycle. The difference in the intensity of extreme precipitation events that occur under El Niño and La Niña conditions will increase, resulting in "more extreme and more variable hydroclimate extremes." We also consider the processes that affect the future intensity of extreme precipitation and how it varies with the ENSO cycle by partitioning changes into thermodynamic and dynamic components. The thermodynamic component, which reflects increases in atmospheric moisture content, results in a relatively uniform intensification of ENSO-driven extreme precipitation variation. In contrast, the dynamic component, which reflects changes in vertical motion, produces a strong regional difference in the response to forcing. In some regions, this component amplifies the thermodynamic-induced changes, while in others, it offsets them or even results in reduction in extreme precipitation variation. [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) off Western Australia (110°–116°E, 22°–32°S; herein, WA MHWs) can cause devastating ecological impacts, as was evidenced by the 2011 extreme event. Previous studies suggest that La Niña is the major large-scale driver of WA MHWs, while the Indian Ocean dipole (IOD) may also play a role. Here, we investigate historical WA MHWs and their connections to these large-scale climate modes in an ocean model (ACCESS-OM2) simulation driven by a prescribed atmosphere from JRA-55-do over 1959–2018. Rather than analyzing sea surface temperature, the WA MHWs and climate mode indices were characterized and investigated in vertically averaged temperature (VAT) to ∼300-m depth to afford the longer ocean dynamic time scales, including remote oceanic connections. We develop a cyclostationary linear inverse model (CS-LIM; from 35°S to 10°N, across the Indo-Pacific Ocean), to investigate the relative contributions of La Niña VAT and positive IOD VAT to the predictability of WA VAT MHWs. Using a large ensemble of CS-LIM simulations, we found that ∼50% of WA MHWs were preceded about 5 months by La Niña, and 30% of the MHWs by positive IOD about 20 months prior. While precursor La Niña or positive IOD, on their own, were found to correspond with increased WA MHW likelihood in the months following (∼2.7 times or ∼1.5 times more likely than by chance, respectively), in combination these climate mode phases were found to produce the largest enhancement in MHW likelihood (∼3.2 times more likely than by chance). Additionally, we found that stronger and longer La Niña and/or positive IOD tend to lead stronger and longer WA MHWs. Significance Statement: This study examines seasonal-to-interannual time-scale predictability of marine heatwaves off Western Australia. We developed and applied a linear inverse model, informed by numerical model results, to generate a large number of 60-yr temperature simulations across the broader Indian–Pacific Ocean region to quantify this marine heatwave predictability. We found that La Niña typically increases the likelihood of marine heatwaves off Western Australia about 5 months (3–7 months) later, while positive Indian Ocean dipole events increase their likelihood about 20 months (18–22 months) later. Marine heatwaves can severely impact local marine ecosystems and the economy. Our findings are expected to be valuable for marine heatwave prediction system development on time scales that can be beneficial to marine ecosystem conservation and fishery management. [ABSTRACT FROM AUTHOR]

This study examines the multiscale modulation of mean and extreme rainfall in Northeast (NE) Australia under different background modes of variability, which is a new aspect given the high-resolution and long-term observational datasets. Daily rainfall probability is significantly modified by the Madden–Julian oscillation (MJO), and its influence varies with the seasons and is associated with atmospheric circulation anomalies. Rainfall generally decreases during El Niño and increases during La Niña years; however, there is a notable spatial nuance to El Niño–Southern Oscillation (ENSO)-associated extreme rainfall, with some locations showing the opposite precipitation response to the typical ENSO–rainfall relationship. Despite more precipitation overall in La Niña years, the mean and extreme precipitation responses to the MJO appear to be stronger and more often statistically significant during El Niño compared to La Niña periods. The impact of ENSO on the MJO–rainfall relationship is stronger than the variation of the MJO itself with ENSO, and likely reflects a change in the MJO modulation of rain-bearing atmospheric processes. During El Niño periods, diurnal rainfall amplitude is generally stronger in the central and southern subtropical parts of the study area than during La Niña periods, while the opposite tendency occurs in the northern tropical part. The diurnal cycle of both mean and extreme precipitation is amplified during suppressed convection phases compared to enhanced convection phases of the MJO. In general, the peak time of diurnal cycle does not change with MJO regimes, but there are some notable differences in rainfall propagation between enhanced and suppressed MJO phases. Significance Statement: This study presents a new perspective on the relationship between precipitation in Northeast (NE) Australia and two important climate modes, the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO). Rainfall in NE Australia is strongly influenced by the MJO, ENSO, and their interaction, suggesting that climate models need to capture both individual climate modes and their interactions for reliable rainfall projections. These findings have societal climate risk implications, as NE Australia is an area prone to catastrophic flooding due to extreme rainfall. [ABSTRACT FROM AUTHOR]

The extreme precipitation (EP) in the early and late rainy seasons in Southern China is investigated from the perspective of moist static energy (MSE). At the synoptic time scale, the EP is accompanied by the charge–discharge paradigm of the vertically integrated MSE (hMSEi); the positive hMSEi anomaly reaches the peak one day before EP and decreases quickly during the event. The charge–discharge paradigm of hMSEi is dominated by the horizontal and vertical advection, respectively. However, synoptic systems responsible for the hMSEi charge in the early and late rainy seasons are different due to the different horizontal distributions of climatological MSE in the lower troposphere caused by the northward migration of solar radiation and the monsoon system. At the interannual time scale, more EP in the early (late) rainy season is associated with the higher seasonal-mean hMSEi that can be caused by the anomalous anticyclone (cyclone) in the western North Pacific induced by the SST anomalies in the tropical Indian Ocean and central North Pacific (the tropical Pacific). The multimodel ensemble mean of CMIP6 models reproduces well the observed hMSEi–EP relationship in both the historical and Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) runs. Moreover, the mean state of hMSEi increases in the SSP5–8.5 compared to historical runs along with more frequent occurrence of EP events. Hence, hMSEi can serve as a useful metric for studying EP in Southern China at various time scales. [ABSTRACT FROM AUTHOR]

Much of Siberia experienced exceptional warmth during the spring of 2020, which followed an unusually warm winter over the same region. Here, we investigate the drivers of the spring warmth from the perspective of atmospheric dynamics and remote influences, focusing on monthly-time-scale features of the event. We find that the warm anomalies were associated with separate quasi-stationary Rossby wave trains emanating from the North Atlantic in April and May. The wave trains are shown to be extreme manifestations of the dominant modes of spring subseasonal meridional wind variability over the Northern Hemisphere. Using a large ensemble of simulations from NASA’s GEOS atmospheric model, in which the model is constrained to remain close to observations over selected regions, we further elucidate the remote drivers of the unusual spring temperatures in Siberia. In both April and May, the wave trains were likely forced from an upstream region including eastern North America and the western North Atlantic. Analysis with a stationary wave model shows that transient vorticity flux forcing over and downwind of the North Atlantic, which is strongly related to storm activity caused by internal variability, is key to generating the wave trains, suggesting limited subseasonal predictability of the Rossby waves and hence the exceptional Siberian warmth. Our observational and model analyses also suggest that anomalous tropical atmospheric heating contributed to the unusual warmth in Siberia through a teleconnection involving upper-troposphere dynamics and the mean meridional circulation. This tropical–extratropical teleconnection offers a possible physical mechanism by which anthropogenic climate change influenced the extreme Siberian warmth. [ABSTRACT FROM AUTHOR]

In this study, the synoptic atmospheric patterns responsible for regional extreme high-temperature events (REHEs) over northern Asia (NA) are investigated. First, a hybrid regionalization approach is applied to the daily maximum temperature (Tmax), and three subregions of NA can be identified: western NA, central NA, and southeastern NA. To better understand the mechanism for the NA REHE formation, the REHE-related synoptic circulation patterns over each subregion are further categorized into two types. These six synoptic circulation patterns influence the NA REHE occurrence through different radiation and advection processes. Generally, the radiation process dominates the NA REHE occurrence, while the horizontal temperature advection plays a more important role in the synoptic dipole patterns than in the monopole high patterns. The heatwaves associated with the six synoptic patterns can last more than 3.8 days, with a maximum of 2 weeks. From the forecasting perspective, six wave trains are explored as the precursors of these six synoptic circulation patterns, separately. The wave trains originate from the North Atlantic Ocean and Europe with at least a 3-day lead and then propagate eastward to NA, exerting influences on the pronounced six synoptic circulation patterns and consequently affecting the NA REHEs. In terms of long-term change, the REHEs over the three subregions show significant increasing trends over 1960–2018 and significant interdecadal increases around the mid-1990s, in which the contribution of each synoptic pattern–related REHE is different. [ABSTRACT FROM AUTHOR]

Greenland experienced multiple extreme weather/climate events in recent decades that led to significant melting of the ice sheet. However, how the intensity of extreme climate events over Greenland varied under recent warming has not been fully examined. Here, we collect 176 in situ observations over Greenland and demonstrate that the observed extreme temperature/precipitation events over Greenland are well captured by the RACMO2.3p2 model, in terms of climatological distribution, interannual variability, and long-term trend. Thus, we then investigate the spatiotemporal features of extreme events over Greenland during 1958–2019, using the daily model outputs at 5.5-km resolution. The simulated annual maximum temperature exhibits a significant increasing trend (∼0.13°C decade−1) during 1958–2019, whereas there is a weakening trend (−0.24°C decade−1) in annual minimum temperature over Greenland, especially after the 1990s (−1.24°C decade−1). For the interannual variability, changes in temperature extremes between warm and cold temperature years share large similarities with the distributions of long-term trends. The extreme precipitation events measured by annual maximum daily precipitation amount show a profound increasing trend (0.52 mm day−1 decade−1) over northeastern Greenland during 1958–2019, with large interannual variability in the ice-free coastal region and southern Greenland. Additionally, the changes in extreme warm and cold events are generally linked with the variation of Greenland blocking in summer and Arctic polar vortex in winter, respectively, in terms of favorable circulation background, and the extreme precipitation events are often associated with the position of the polar jet stream. [ABSTRACT FROM AUTHOR]

Long-term variations in the translation speed of tropical cyclones (TCs) in the South China Sea (SCS) are examined based on five TC datasets from different institutions. TC translation speed during the TC peak season in the SCS shows an evident rhythm of interdecadal change throughout 1977-2020. This interdecadal change in TC translation speed in the SCS can be well reproduced by a newly developed trajectory model. The model results indicate that the interdecadal change in TC translation speed is primarily due to an interdecadal change in the steering flow in the SCS. Such an interdecadal change in the steering flow is closely related to an east-west shift of the subtropical high in the western North Pacific (WNP) ocean basin, which may be driven by the zonal sea surface temperature (SST) gradient between the north Indian (NI) andWNP ocean basins. A new index of the zonal SST gradient is proposed, which is shown to be effective for indicating the interdecadal change in east-west shift of subtropical high, and thus, the TC translation speed in the SCS. [ABSTRACT FROM AUTHOR]

Current models for spatial extremes are concerned with the joint upper (or lower) tail of the distribution at two or more locations. Such models cannot account for teleconnection patterns of 2-m surface air temperature (T2m) in North America, where very low temperatures in the contiguous United States may coincide with very high temperatures in Alaska in the wintertime. This dependence between warm and cold extremes motivates the need for a model with opposite-tail dependence in spatial extremes. This work develops a statistical modeling framework that has flexible behavior in all four pairings of high and low extremes at pairs of locations. In particular, we use a mixture of rotations of common Archimedean copulas to capture various combinations of four-corner tail dependence. We study teleconnected T2m extremes using ERA5 of daily average 2-m temperature during the boreal winter. The estimated mixture model quantifies the strength of opposite-tail dependence between warm temperatures in Alaska and cold temperatures in the midlatitudes of North America, as well as the reverse pattern. These dependence patterns are shown to correspond to blocked and zonal patterns of midtropospheric flow. This analysis extends the classical notion of correlation-based teleconnections to considering dependence in higher quantiles. [ABSTRACT FROM AUTHOR]

Extreme near-surface wind speeds in cities can have major societal impacts but are not well represented in climate models. Despite this, large-scale dynamics in the free troposphere, which models resolve better, could provide reliable constraints on local extreme winds. This study identifies synoptic circulations associated with midlatitude extreme wind events and assesses how resolution affects their representation in analysis products and a climate model framework. Composites of reanalysis (ERA5) sea level pressure and upper-tropospheric winds during observed extreme wind events reveal distinct circulation structures for each quadrant of the surface-wind rose. Enhanced resolution of the analysis product (ERA5 versus the higher-resolution ECMWF Operational Analysis) reduced wind speed biases but has little impact on capturing occurrences of wind extremes seen in station observations. Composite circulations for surface wind extremes in a climate model (CESM) skillfully reproduce circulations found in reanalysis. Regional refinement of CESM over a region centered on southern Ontario, Canada, using variable resolution (VR-CESM) improves representation of surface ageostrophic circulations and the strength of vertical coupling between upper-level and near-surface winds. We thus can distinguish situations for which regional refinement (dynamical downscaling) is necessary for realistic representation of the large-scale atmospheric circulations associated with extreme winds, from situations where the coarse resolution of standard GCMs is sufficient. [ABSTRACT FROM AUTHOR]

In North China (NC), heat stress, which can be quantitatively characterized by wet-bulb globe temperature (WBGT), is closely related to specific humidity. This study focuses on the total days for NC average daily maximum WBGT exceeding 26°C (WGBT26) per summer (June–August) from 1979 to 2017. Rather than local precipitation or evaporation in NC, the NC WBGT26 is significantly related to the nonlocal evaporation around the Yangtze River valley (YR). The abnormal positive evaporated water vapor in YR, associated with anomalously high water vapor flux from south to north at 925 hPa, is continuously transported to NC in the above-normal WBGT26 years. Such an abnormal "evaporation and transportation" process can significantly increase the water vapor in NC and therefore enhance WBGT26. The evaporation in YR peaks in mid- to late July and is closely associated with the occurrence days for daily maximum WBGT exceeding 26°C and maximum daily mean specific humidity at 925 hPa in summer. The main driver for the strongest YR evaporation anomaly from 15 July to 15 August is the simultaneous surface air temperature rather than the simultaneous or earlier soil moisture, precipitation, and vapor pressure deficit (VPD) anomaly. This condition is due to the continuously abundant soil moisture in the YR from April to September. The results of this study provide new ideas for studying heat stress in NC, indicating that nonlocal land–atmosphere interactions are crucial. [ABSTRACT FROM AUTHOR]

A Lagrangian model—the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT)—is used to quantify changes in moisture sources and paths for precipitation over North China's Henan Province associated with tropical cyclone (TC) over the western North Pacific (WNP) during July–August of 1979–2021. During TC-active periods, an anomalous cyclone over the WNP enhances southeasterly and reduces southwesterly moisture transport to Henan. Accordingly, compared to TC-inactive periods, moisture contributions from the Pacific Ocean (PO), eastern China (EC), and the local area (Local) are significantly enhanced by 48.32% (16.73% versus 11.28%), 20.42% (9.44% versus 7.84%), and 2.89% (4.91% versus 4.77%), respectively, while moisture contributions from the Indian Ocean (IO), Southwestern China (SWC), Eurasia (EA), and the South China Sea (SCS) are significantly reduced by −31.90% (8.61% versus 12.64%), −16.27% (4.60% versus 5.50%), −8.81% (19.10% versus 20.95%), and −6.92% (12.18% versus 13.09%). Furthermore, the moisture transport for a catastrophic extreme rainfall event during 17–22 July ("21⋅7" event) influenced by Typhoon Infa is investigated. Compared to the mean state during TC-active periods, the moisture contribution from the PO was substantially increased by 126.32% (37.87% versus 16.73%), while that from IO significantly decreased by −98.26% (0.15% versus 8.61%) during the "21⋅7" event. Analyses with a bootstrap resampling method show that moisture contributions from the PO fall outside the +6σ range, for both the TC-active and TC-inactive probability distributions. Thus, the "21⋅7" event is rare and extreme in terms of the moisture contribution from the PO, with the occurrence probability being less than 1 in 1 million times. Significance Statement: Henan, one of the most populated provinces in China, experienced a catastrophic extreme precipitation event in July 2021 (the "21⋅7" event), coinciding with the activity of a tropical cyclone (TC) over the western North Pacific, which helps establish the moisture channel. Using a Lagrangian model, we provide a better understanding of how moisture transport changes associated with TC for the mean state of 1979–2021, and reveal how extreme is the moisture transport for the "21⋅7" event with the bootstrap technique. It is found that during active TC periods, the moisture contribution from the Pacific Ocean (the Indian Ocean) is significantly enhanced (reduced). For every 1 000 000 six-day events, less than one instance like the "21⋅7" event should be expected. [ABSTRACT FROM AUTHOR]

In this study, persistent rainfall (PR) over South China (SC) is divided into two types. One type occurs multiple times in succession [defined as multiple PR (MPR)]; another type represents isolated PR (IPR), for which no new PR occurs for 10 days after the previous PR. The spatiotemporal structures of the 10-30-day intraseasonal oscillations (ISOs) associated with the two types of PR are compared and analyzed. The results reveal that the low-level moisture and air temperature perturbations always have a leading phase relative to the anomalous precipitation. In addition, the positive low-level moisture tendency appears in the MPR ending phase, whereas that in the IPR is close to zero. This difference results in convective development after the MPR ending phase, though not after the IPR. The moisture budget shows that the difference in moisture tendency between MPR and IPR is mainly due to meridional advection, including advections by the mean meridional flow across the perturbation moisture gradient and by the perturbation meridional flow across the mean moisture gradient. For the former, the difference is attributed to the perturbation moisture gradients, while the mean moisture gradients are responsible for the difference of the latter. Furthermore, an essential cause of the difference is the influence of higher-latitude disturbances that affect the IPR more significantly than the MPR. Two associated mechanisms are proposed. One is the perturbation stacking effect, and the other is the effect of angular momentum conservation. By contrast, the low-level temperature anomalies are not the key factor causing the difference between MPR and IPR. [ABSTRACT FROM AUTHOR]

This study investigates the mechanisms of low-latitude intraseasonal oscillations affecting regional persistent extreme precipitation events (RPEPEs) over Southwest China (SWC) during rainy seasons. Most of the RPEPEs over SWC are dominated by 7-20-day variability. The RPEPEs over SWC are preconditioned by two different types of 7-20-day Rossby waves with almost opposite phases over the western North Pacific (WNP). The two types of 7-20-day Rossby waves have direct and indirect effects on type-1 and -2 RPEPEs, respectively. For type 1, a coupled 7-20-day low-level anticyclone and suppressed convection originating from the tropical WNP propagate northwestward and cover the region from the South China Sea (SCS) to the Bay of Bengal before the RPEPEs. The anticyclone triggers ascending motion over SWC and transports more moisture to SWC, favoring the SWC RPEPEs. Before the type-2 RPEPEs, a coupled 7-20-day low-level cyclone and enhanced convection propagates from the tropical WNP to the SCS. The enhanced convection over the SCS leads to the westward extension of the western Pacific subtropical high (WPSH) and the eastward shift of the South Asian high (SAH). The variations in the WPSH and the SAH directly cause SWC RPEPEs by inducing ascending motion and transporting moisture. The mechanisms for type-2 RPEPEs tend to work under the background with a strong WPSH. Using a Lagrangian model, we found that both the 7-20-day oscillations and their background atmospheric circulations result in significant differences in moisture sources for the two types of RPEPEs. These findings benefit a better understanding of SWC extreme precipitation events. [ABSTRACT FROM AUTHOR]

This study presents a novel mechanism for the generation of extreme El Niño events by analyzing interactions between tropical cyclones (TCs) in the western North Pacific (WNP) in spring [March–May (MAM)] and summer [June–August (JJA)] and sea surface warming in the eastern tropical Pacific. It is suggested that anomalously strong TCs in the WNP in MAM and JJA are essential for the formation of extreme El Niño events. MAM TCs excite considerable westerly wind bursts (WWBs) and facilitate the generation of El Niño events in late spring. The sea surface temperature (SST) in the central-eastern tropical Pacific increases prominently during the following summer, which is due to the warm water carried by downwelling Kelvin waves induced by the anomalous westerlies in the western tropical Pacific associated with the WNP TCs, as well as the lessening cold water upwelling resulting from the deepening thermocline in the eastern tropical Pacific. The developing El Niño in turn contributes to the TC activities over the southeastern quadrant of the WNP in summer, characterized by a stronger intensity, higher frequency, and longer duration. The resulting JJA TC-induced westerlies could further enhance the eastern tropical Pacific warm SST anomalies, and thus an extreme El Niño event tends to appear in the following autumn and winter. These physical processes are verified by several sets of atmosphere–ocean coupled model experiments. Significance Statement: Tropical cyclone activity is one of the most destructive phenomena in the world. Extreme El Niño events can also cause devastating climate disasters. Understanding the relationship between these two events can help with disaster forecasting and prevention. This study finds that TC activity in the western North Pacific contributes to the appearance of extreme El Niño events. Abnormally active TC activity in spring can cause strong near-equatorial westerly wind anomalies, eastward transport of warm water from the western tropical Pacific, and a deepening ocean thermocline in the east, resulting in the earlier onset of El Niño events. Influenced by the El Niño event, the TC activity in summer is strengthened, which in turn continues to promote the surface warming of the central-eastern tropical Pacific, eventually resulting in extreme event occurrence. [ABSTRACT FROM AUTHOR]

Hydroclimatic extremes, such as heavy daily rainfall and dry spells, are expected to intensify under anthropogenic warming. Often, these changes are diagnostically related to thermodynamic increases in humidity with warming. Here, we develop a framework that uses an online calculation of the thermodynamically induced changes of the full precipitation distribution with warming in an idealized moist atmospheric general circulation model. Two water vapor variables, the standard active one and an additional passive one (i.e., no latent heat release when condensation occurs), are advected by the resolved circulation. The passive water vapor is thermodynamically perturbed by modifying the saturation specific humidity used in the calculation of its condensation tendency and surface evaporation. The difference between the precipitation of the perturbed passive water vapor relative to the control one corresponds to the thermodynamic component of precipitation change, which can be evaluated for the entire distribution. Here, we evaluate wet and dry extremes. Our simulations have tropical increases and higher-latitude decreases of dry spell's length (defined as the maximum consecutive dry days), as found in the zonal mean of comprehensive models. This simulated thermodynamically induced intensification of dry spells in the tropics arises from the decreased contrast between sea surface temperature and surface air temperature with warming. There is a simulated increase in heavy daily rainfall (e.g., the 99.9th percentile of the daily precipitation distribution) at all latitudes that differ modestly from a previous theory that assumes moist-adiabatic stratification. Consistent with this theory, increased warming aloft slightly dampens the simulated increase. [ABSTRACT FROM AUTHOR]

Eastern China (EC) suffered an extreme drought with long-lasting duration and record-breaking intensity in late summer–autumn 2019. Our diagnosed results show that the central Pacific (CP) El Niño, in tandem with warm sea surface temperature anomalies (SSTAs) over the Kuroshio Extension (KE) region, induces the meridionally elongated cyclonic circulation anomalies stretching from the western North Pacific (WNP) to the Yellow Sea. Its western flank corresponds to overwhelming low-level northerly wind anomalies over EC, which result in deficient moisture and anomalous descent over EC and hence cause the extreme drought in 2019. To investigate the relative contributions of SSTAs over different regions, we performed sensitivity experiments, and analyzed the relationship between extreme drought like what occurred in 2019 (a 2019Drought-like event) and the SSTAs in CMIP6 historical simulations. Modeling evidences reveal that both warm SSTAs over the central equatorial Pacific and the KE region are indispensable for shaping the meridionally elongated cyclone anomaly. Specifically, the cyclone anomaly over the WNP induced by CP El Niño aligns with the cyclone anomaly over the Yellow Sea induced by the warm SSTAs over the KE region, merging into a meridionally stretched cyclone anomaly to the east of EC. Consequently, the northerly anomalies stretch across EC, leading to unfavorable atmospheric conditions and the rainfall deficit there. Projection results show that the occurrence probability of a 2019Drought-like event will increase by 20% (decrease by 40%–50%) under a high (medium-low) emission scenario compared to present-day climate, indicating the nonlinear response of extreme drought to different emission scenarios and the urgency of carbon emission reduction. Significance Statement: An extreme drought hit the Eastern China (EC) region in 2019 and caused tremendous losses. This study proposed that both the 2019 CP El Niño and the warm SST anomalies over the Kuroshio Extension (KE) region induce the meridionally elongated circulation anomalies and the resultant extreme drought. We showed that the typical circulation anomalies induced by central Pacific (CP) El Niño cannot totally explain the meridionally elongated circulation anomalies in 2019. Our modeling evidences confirmed the indispensable role of warm SST anomalies over KE region in the 2019 extreme drought's formation. The projection results show that extreme drought like that in 2019 will occur more (less) frequently under a high (medium-low) emission scenario compared to modern-day level, indicating the urgency of carbon emission reduction. [ABSTRACT FROM AUTHOR]

We assess seasonally varying impacts of the Madden–Julian oscillation (MJO) on Australian maximum and minimum temperature anomalies and extremes, and their modulation by El Niño–Southern Oscillation (ENSO), for the period June 1974–May 2022. Our composite-based approach uses observed temperatures from the Australian Gridded Climate Data, and 850-hPa wind data from the NCEP–NCAR reanalysis, to show how relationships to temperature and circulation evolve over the eight-phase life cycle of the MJO, which we derive from the real-time multivariate MJO index. The MJO has significant impacts on Australian temperatures and winds in all parts of the country at various times throughout the year, and to varying degrees. Two of the most pronounced impacts are 1) daytime warming across southeastern Australia in MJO phase 3 during spring associated with a strong anomalous anticyclone and 2) nighttime cooling over Queensland in MJO phase 7 during winter associated with anomalous advection of cool dry continental air. La Niña acts to significantly lessen both of these impacts, while El Niño enhances both the phase 3 warming over southern Australia in spring and the phase 7 overnight cooling over southern Queensland in winter. We show how the MJO can combine with El Niño and La Niña to have strong compounding influences, thus highlighting the importance of understanding interactions between multiple modes of climate variability and how they relate to Australian temperatures and extremes. [ABSTRACT FROM AUTHOR]

Heavy precipitation (HP) events can be preceded by moist heatwaves (HWs; i.e., hot and humid weather), and both can be intensified by urbanization. However, the effect of moist HWs on increasing urban HP remains unknown. Based on statistical analyses of daily weather observations and ERA5 reanalysis data, we herein investigate the effect of moist HWs on urban-intensified HP by dividing summer HP events into NoHW- and HW-preceded events in the Yangtze River delta (YRD) urban agglomeration of China. During the period 1961–2019, the YRD has experienced more frequent, longer-lasting, and stronger intense HP events in the summer season (i.e., June–August), and urbanization has contributed to these increases (by 22.66%–37.50%). In contrast, urban effects on HP are almost absent if we remove HW-preceded HP events from all HP events. Our results show that urbanization-induced increases in HP are associated with, and magnified by, moist HWs in urban areas of the YRD region. Moist HWs are conducive to an unstable atmosphere and stormy weather, and they also enhance urban heat island intensity, driving increases in HP over urban areas. Significance Statement: The contribution of urbanization to increases in heavy precipitation has been widely reported in previous studies. HP events can be preceded by moist heatwaves (hot and humid extremes); however, it is unknown whether moist HWs enhance urban effects on HP. We choose the Yangtze River delta urban agglomeration to explore this question and find that urbanization contributes to the increasing frequency, duration, maximum intensity, and cumulative intensity of HP events in the summer season. However, this urban signal is not detectable if we remove HW-preceded events from all HP events. In other words, moist HWs play a key role in magnifying urbanization-induced increases in HP. Given that urban areas are projected to continue expanding and moist HWs are projected to occur with increasing frequency and intensity in the future, the role of HWs in the urban water cycle merits further investigation. [ABSTRACT FROM AUTHOR]

Climate change is expected to increase the frequency and intensity of rainfall extremes. Understanding future changes in rainfall is necessary for adaptation planning. Eastern Africa is vulnerable to rainfall extremes because of low adaptive capacity and high future population growth. Convection-permitting climate models have been found to better represent moderate (yearly) rainfall extremes than parameterized convection models, but there is limited analysis of rare extremes that occur less frequently than once per year. These events often have the largest socioeconomic impacts. We use extreme value theory and regional frequency analysis to quantify rare rainfall extremes over East Africa in a convection-permitting climate model (CP4A). We compare the results with its parameterized counterpart (P25), the Coordinated Regional Climate Downscaling Experiment for the African region (CORDEX-Africa) ensemble, and observations to understand how the convection parameterization impacts the results. We find that CP4A better matches observations than the parameterized models. With climate change, we find the parameterized convection models have unrealistically high changes in the shape parameter of the extreme value distribution, which controls the tail behavior (i.e., the most extreme events), leading to large increases in return levels of events with a return period of >20 years. This suggests that parameterized convection models may not be suitable for looking at relative changes in rare rainfall events with climate change and that convection-permitting models should be preferred for this type of work. With the more realistic CP4A, RCP8.5 end-of-century climate change leads to 1-in-100-yr events becoming 1-in-23-yr events, which will necessitate serious adaptation efforts to avoid devastating socioeconomic impacts. Significance Statement: We use a new, high-resolution climate model to examine how rare extreme rainfall events in East Africa might change in the future with climate change and compare the results with those from standard-resolution climate models. We find that the standard-resolution models have unrealistically large increases in rainfall for events that occur less frequently than every 20 years. The high-resolution model is more realistic and is required to illustrate possible future changes in rare rainfall extremes. Extreme events will become more common with climate change, and in the more realistic model we show that a 1-in-100-yr event may become a 1-in-23-yr event by the end of the century if greenhouse gas emissions are not significantly reduced. [ABSTRACT FROM AUTHOR]

In the present study, the structures and mechanisms of the heatwaves (HWs) associated with the quasi-biweekly (QBW; 10–20-day period) variability (QBW-HW) over southern China (SC; 106°–120°E, 21°–30°N) are investigated by using observation data from surface stations in China and the related gridded dataset (CN05.1), and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. We found that the strongest anticyclonic anomaly and subsidence appear over SC during the developing phase of QBW-HW, and then induced excess solar radiation at surface and significant diabatic heating lead to a positive surface air temperature change, thus favoring occurrence of QBW-HW over SC. In addition, we found a wet near-surface atmosphere in the QBW-HW events over SC, and further confirmed that near-surface moisture should play an important role in the occurrence of QBW-HW, via absorptions of longwave and shortwave radiation. This result is quite different from previous studies since they did not pay attention to the near-surface moisture. On the other hand, warmer SAT favors more water vapor evaporated from the moist soil when considering the Clausius–Clapeyron relationship. Then, the positive feedback processes promote the occurrence of QBW-HW over SC. In contrast, during the developing and warm phases of QBW-HW over SC, except for the near-surface level, the troposphere is in a dry condition, even at 850 and 700 hPa. In the QBW-HW events over SC, the factor responsible for the wet near-surface atmosphere is the enhanced surface evaporation, which is attributed to strengthened surface wind speed and background moist soil. Significance Statement: Under the background of global warming, heatwaves over Southern China are experiencing an increasing trend. In this study, we want to understand the structures and mechanisms of the heatwaves related to 10–20-day (quasi-biweekly) variability. We that found some structures of heatwaves (e.g., anticyclonic anomalies along with subsidence) are consistent with previous studies. In addition, we also show that the moist soil and increased induced near-surface moisture play a key role in the occurrence of heatwaves over Southern China, via enhanced absorptions of longwave and shortwave radiation. This study is helpful for understanding the processes and prediction of heatwaves over Southern China. Future work should examine the findings by some numerical experiments with a climate model. [ABSTRACT FROM AUTHOR]

Humid heat extremes, taking account of both temperature and humidity, have adverse impacts on society, particularly on human health. It has been suggested that quasi-stationary waves (QSWs) with anomalously high amplitudes contribute to the occurrence of near-surface precipitation extremes and temperature extremes in the midlatitudes of the Northern Hemisphere. However, little attention has been paid to the linkages between amplified QSWs and humid heat extremes. Using the ERA5 dataset, we identify amplified QSWs of zonal wavenumbers 5–7 (Wave 5–7) in summer months from 1979 to 2020. These amplified QSWs show clear circumglobal wave patterns horizontally and nearly barotropic structure vertically. Linking amplified Wave 5–7 to wet-bulb temperature (WBT) extremes, we find that amplified QSWs preferentially induce prominently prolonged WBT extremes in specific regions: north-central North America for amplified Wave 5; western United States, south-central Asia, and eastern Asia for amplified Wave 6; and western Europe and the Caspian Sea region for amplified Wave 7. Analyses of physical processes indicate that, accompanied by the amplification of Wave 5–7, the changes in horizontal temperature advection, adiabatic heating associated with descending motion, downward solar radiation, moisture transport and moisture flux convergence, and surface latent heat fluxes largely account for the increase in persistence of WBT extremes. Significance Statement: In the context of climate change, humid heat extremes exhibit different changes and impacts from high-temperature extremes, but the physical processes that may cause them remain unclear. This study aims to explore the atmospheric dynamic processes leading to the concurrence of humid heat extremes, which may exacerbate the risk from heat stress in today's interconnected world. In specific regions over the Northern Hemisphere midlatitudes, durations of humid heat extremes are found to be elevated simultaneously by amplified quasi-stationary waves. We further identify the physical connections between amplified quasi-stationary waves and humid heat extremes over targeted regions. This would help in better understanding the role of changing atmospheric circulations in the humid heat extremes. [ABSTRACT FROM AUTHOR]

California is one of the nation's top agriculture producers and is vulnerable to extreme events such as droughts and heat waves. Concurrent extreme events may further stress water and energy resources, exerting greater adverse socioeconomic, environmental, and health impacts than individual events. Here we examine the features of compound drought, heat wave, and dust events in California during spring and summer. From 2003 to 2020, 16 compound events are found in warm seasons, with a mean duration of ∼4 days. Compound events are characterized by enhanced surface temperature up to 4.5°C over northern and western California, reduced soil moisture and vegetation density, and an increase in dust optical depth (DOD) by 0.05–0.1 over central and southern California. The enhanced DOD is largely associated with severe vegetation dieback that favors dust emissions and southeasterly wind anomalies that support northward transport of dust from source regions in southern California. Surface fine dust and PM2.5 concentrations also increase by more than 0.5 and 5 μg m−3, respectively, during compound events associated with both enhanced dust emissions and a relatively stable atmosphere that traps pollutants. The development of the compound events is related to an anomalous high over the west coast in the lower to middle troposphere, which is a pattern favoring sinking motion and dry conditions in California. The anomalous high is embedded in a wave train that develops up to 7 days before the events. In comparison with heat wave extremes alone, compound events show significantly higher DOD and lower vegetation density associated with droughts. [ABSTRACT FROM AUTHOR]

Extreme heat events are a threat to human health, productivity, and food supply, so understanding their drivers is critical to adaptation and resilience. Anticyclonic circulation and certain quasi-stationary Rossby wave patterns are well known to coincide with heatwaves, and soil moisture deficits amplify extreme heat in some regions. However, the relative roles of these two factors in causing heatwaves is still unclear. Here we use constructed circulation analogs to estimate the contribution of atmospheric circulation to heatwaves in the United States in the Community Earth System Model version 1 (CESM1) preindustrial control simulations. After accounting for the component of the heatwaves explained by circulation, we explore the relationship between the residual temperature anomalies and soil moisture. We find that circulation explains over 85% of heatwave temperature anomalies in the eastern and western United States but only 75%–85% in the central United States. In this region, there is a significant negative correlation between soil moisture the week before the heatwave and the strength of the heatwave that explains additional variance. Further, for the hottest central U.S. heatwaves, positive temperature anomalies and negative soil moisture anomalies are evident over a month before heatwave onset. These results provide evidence that positive land–atmosphere feedbacks may be amplifying heatwaves in the central United States and demonstrate the geographic heterogeneity in the relative importance of the land and atmosphere for heatwave development. Analysis of future circulation and soil moisture in the CESM1 Large Ensemble indicates that, over parts of the United States, both may be trending toward greater heatwave likelihood. [ABSTRACT FROM AUTHOR]

This study analyzes the spatiotemporal distributions and climate trends of tropical cyclone (TC)-induced extreme hourly precipitation (EXHP) in the warm season (May–September) during 1975–2018 over China and the involved mechanisms. Each TC is classified as a high-, mid-, and low-EXHP TC according to the total amount of EXHP it produces over China during its lifetime. Results show that low-EXHP TCs have a greater contribution to the total TC-induced EXHP over southern and southwestern China, whereas high-EXHP TCs make greater contributions over eastern and northeastern China as they tend to move northwestward after making landfall. It is shown that, although the total frequency of EXHP-producing TCs displays a decreasing trend, the total frequency of TC-induced EXHP over China shows a significant increasing trend, which is largely contributed by the high-EXHP TCs. To explore the possible mechanisms responsible for the different characteristics in EXHP-producing TC groups, we further analyze the large-scale environmental conditions with respect to three groups by composite analysis. The cooperation of large-scale environmental fields between high and low levels provides favorable conditions for the intensification of TCs and the enhancement of the TC-induced precipitation for the high-EXHP group, such as stronger divergence at high levels, weaker vertical wind shear, more sufficient water vapor, and more conducive steering airflow over the southeastern and eastern area of mainland China. The westward and northward movement of western North Pacific subtropical high is conducive to the northward shift of TC tracks, thus contributing to the high frequency of TC-induced EXHP over the eastern area of mainland China. [ABSTRACT FROM AUTHOR]

Southeast Asia lies at the heart of heavy precipitation on Earth, and a large amount of latent heat released here provides substantial energy for the global atmospheric circulation. Utilizing gauge-based daily precipitation and the self-organizing map technique, the summertime extreme and total precipitation over Southeast Asia during 1979–2019 are classified into three and five distinct patterns, respectively. The three extreme precipitation clusters are characterized by southern dry and northern wet (C1_extreme), overall wet (C2_extreme), and northern dry and southern wet (C3_extreme) structures. The frequencies of these patterns exhibit increasing trends during the analysis, although they are not statistically significant for C1_extreme. The C1_extreme pattern is accompanied by an anomalous cyclone over the South China Sea in response to negative Indian Ocean sea surface temperature anomalies (SSTAs). The C2_extreme and C3_extreme clusters are characterized by a westward extension of the western Pacific subtropical high, regulated by cool SSTAs over the tropical central-eastern Pacific that are induced by the tropical North Atlantic warming and the tropical Pacific and Atlantic SSTAs, respectively. For total precipitation, the first and second clusters show overall dry distributions, which are mainly composed of nonextreme precipitation. The spatial patterns and atmospheric and oceanic features associated with the other three clusters of total precipitation bear large resemblances to those of C1_extreme, C2_extreme, and C3_extreme, respectively, but their trends exhibit smaller similarities. Comparing the differences between extreme and total precipitation over Southeast Asia could improve our understanding of their regional variabilities and relationships, and potentially their global impacts. Significance Statement: We explore the atmospheric and oceanic processes associated with extreme precipitation, and compare them with those for total precipitation over Southeast Asia. The three key modes of summertime extreme precipitation over Southeast Asia are characterized by southern drought and northern flood, overall flood, and northern drought and southern flood structures. Each pattern is closely linked to tropical sea surface temperature anomalies, but in different regions. Total precipitation can be classified into five distinct patterns. The first two modes are largely determined by nonextreme precipitation, while the other three bear large resemblances to the three extreme precipitation modes. These findings provide guidance on what is the key factor in driving each extreme precipitation mode over Southeast Asia, allowing better prediction. [ABSTRACT FROM AUTHOR]

The future change in dry and humid heatwaves is assessed in 10-yr pan-African convective-scale (4.5 km) and parameterized convection (25 km) climate model simulations. Compared to reanalysis, the convective-scale simulation is better able to represent humid heatwaves than the parameterized simulation. Model performance for dry heatwaves is much more similar. Both model configurations simulate large increases in the intensity, duration, and frequency of heatwaves by 2100 under RCP8.5. Present-day conditions that occur on 3–6 heatwave days per year will be normal by 2100, occurring on 150–180 days per year. The future change in dry heatwaves is similar in both climate model configurations, whereas the future change in humid heatwaves is 56% higher in intensity and 20% higher in frequency in the convective-scale model. Dry heatwaves are associated with low rainfall, reduced cloud, increased surface shortwave heating, and increased sensible heat flux. In contrast, humid heatwaves are predominately controlled by increased humidity, rainfall, cloud, longwave heating, and evaporation, with dry-bulb temperature gaining more significance in the most humid regions. Approximately one-third (32%) of humid heatwaves commence on wet days. Moist processes are known to be better represented in convective-scale models. Climate models with parameterized convection, such as those in CMIP, may underestimate the future change in humid heatwaves, which heightens the need for mitigation and adaptation strategies and indicates there may be less time available to implement them to avoid future catastrophic heat stress conditions than previously thought. Significance Statement: Temperatures are higher in dry heatwaves, but humid heatwaves can be more dangerous, as the ability to cool by sweating is limited. We found that dry heatwaves are caused by decreased cloud, allowing the sun to heat the surface, whereas humid heatwaves are caused by increased cloud, rainfall, and evaporation from the surface. We found that a state-of-the-art very high-resolution climate model predicts a larger future change in humid heatwaves compared to a more traditional global climate model. Previous estimates of the prevalence of humid heatwaves in the future may therefore be underestimated. If we do not cut emissions of greenhouse gases, present-day African heatwave conditions could be experienced on up to half of all days of the year by 2100. [ABSTRACT FROM AUTHOR]

The Maritime Continent is one of the most challenging regions for atmospheric models. Processes that modulate deep convection are poorly represented in models, which affects their ability to simulate precipitation features accurately. Thus, future projections of precipitation over the region are prone to large uncertainties. One of the key players in modeling tropical precipitation is the convective representation, and hence convection-permitting experiments have contributed to improve aspects of precipitation in models. This improvement creates opportunities to explore the physical processes that govern rainfall in the Maritime Continent, as well as their role in a warming climate. Here, we examine the response to climate change of models with explicit and parameterized convection and how that reflects in precipitation changes. We focus on the intensification of spatial contrasts as precursors of changes in mean and extreme precipitation in the tropical archipelago. Our results show that the broad picture is similar in both model setups, where islands will undergo an increase in mean and extreme precipitation in a warmer climate and the ocean will see less rain. However, the magnitude and spatial structure of such changes, as well as the projection of rainfall percentiles, are different across model experiments. We suggest that while the primary effect of climate change is thermodynamical and it is similarly reproduced by both model configurations, dynamical effects are represented quite differently in explicit and parameterized convection experiments. In this study, we link such differences to horizontal and vertical spatial contrasts and how convective representations translate them into precipitation changes. [ABSTRACT FROM AUTHOR]