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In recent years, various early warning signals of critical transition have been presented, such as autocorrelation at lag 1 [AR(1)], variance, the propagator based on detrended fluctuation analysis (DFA-propagator), and so on. Many studies have shown that the climate system has the characteristics of long-term memory (LTM). Will the LTM characteristics of the climate system change as it approaches possible critical transition points? In view of this, the present paper first studies whether the LTM of several folding (folded bifurcation) models changes consistently as they approach their critical points slowly by the rescaled range (R/S) analysis. The results of numerical experiments show that when the control parameters of the folding model are close to its critical threshold, the Hurst exponent H exhibits an almost monotonic increase (significance level α = 0.05). We compare the performance of R/S with the existing indicators, including AR(1), variance, and DFA-propagator, and find that R/S is a perfectly valid alternative. When there is no extra false noise, AR(1) and variance have good early warning effects. After the addition of extra Gaussian white noise of different intensities, the values of AR(1) and variance change significantly. As a result, the DFA-propagator based on AR(1) calibration also changed significantly. Compared with the other three indicators, the early warning effect of H has stronger ability to resist the interference of external false signals. To further verify the validity of increasing H, paleoclimate reconstruction of Cariaco Basin sediment core grayscale record with long trends filtered out is studied by R/S analysis. The other three early warning signals are calculated in the same way. The data contain a well-known abrupt climate change: the transition between the Younger Dryas (YD) and the Holocene. We find that approximately 300 years before this abrupt climate change occurred, before 11.7 kyr BP, the LTM exponents for Cariaco Basin deglacial grayscale data present an obvious increasing trend at a significant level of α = 0.05. Meanwhile, the variation trend of H and DFA-propagator is basically similar. This shows that increasing H by R/S analysis is an effective early warning signal, which indicates that a dynamic system is approaching its possible critical transition points; H is a completely valid alternative signal for AR(1) and DFA-propagator. The main conclusion of this paper is based on numerical experiments. The precise relationship between H and the stability of the underlying state approaching the transition needs to be further studied. [ABSTRACT FROM AUTHOR]

The article discusses the importance of peer reviewers in scholarly publishing and expresses gratitude towards those who volunteer their time to review manuscripts. The American Meteorological Society (AMS) analyzed data on peer reviews and found no trend in reviewer acceptance rates or the time taken to complete reviews over the past decade. The article also emphasizes the responsibility of authors to participate in the peer-review process by reviewing papers themselves. The authors of the article acknowledge the time and effort involved in reviewing and encourage those who have not yet embraced their responsibilities as reviewers to volunteer. [Extracted from the article]

Climate changepoint (homogenization) methods abound today, with a myriad of techniques existing in both the climate and statistics literature. Unfortunately, the appropriate changepoint technique to use remains unclear to many. Further complicating issues, changepoint conclusions are not robust to perturbations in assumptions; for example, allowing for a trend or correlation in the series can drastically change changepoint conclusions. This paper is a review of the topic, with an emphasis on illuminating the models and techniques that allow the scientist to make reliable conclusions. Pitfalls to avoid are demonstrated via actual applications. The discourse begins by narrating the salient statistical features of most climate time series. Thereafter, single- and multiple-changepoint problems are considered. Several pitfalls are discussed en route and good practices are recommended. While most of our applications involve temperatures, a sea ice series is also considered. Significance Statement: This paper reviews the methods used to identify and analyze the changepoints in climate data, with a focus on helping scientists make reliable conclusions. The paper discusses common mistakes and pitfalls to avoid in changepoint analysis and provides recommendations for best practices. The paper also provides examples of how these methods have been applied to temperature and sea ice data. The main goal of the paper is to provide guidance on how to effectively identify the changepoints in climate time series and homogenize the series. [ABSTRACT FROM AUTHOR]

High-resolution observations have demonstrated the presence of strong time-mean near-surface wind convergence (NSWC) anchored across oceanic frontal zones, such as the western boundary currents. Initial analyses appeared to show a close association between this time-mean NSWC and time-mean properties of the underlying sea surface temperature (SST), such as the gradients and second derivatives (e.g., Laplacian of SST), acting through pressure-adjustment and vertical-mixing mechanisms. However, a series of recent papers have revealed the instantaneous NSWC to be dominated by atmospheric fronts and have suggested the importance of air–sea processes occurring instead on shorter, synoptic time scales. In this paper, using the ERA5 reanalysis dataset in the Gulf Stream region, we aim to reconcile these viewpoints by investigating the spatial and temporal dependence of NSWC and its relationship to SST. It is revealed that while atmospheric frontal processes govern the day-to-day variability of NSWC, the relatively weak but persistent pressure-adjustment and vertical-mixing mechanisms provide lower-frequency modulations in conditions both with and without atmospheric fronts. In addition to their temporal characteristics, each mechanism is shown through spectral analysis to dominate on specific spatial scales. In light of recent work that has tied remote atmospheric responses to NSWC anomalies in western boundary current regions, these results emphasize the importance of oceanic frontal zones for atmospheric variability on all spatiotemporal scales. [ABSTRACT FROM AUTHOR]

The South Pacific Oscillation (SPO), characterized by a north–south dipole-like pattern of sea level pressure anomalies, is one of the key factors in understanding tropical–extratropical interactions in the South Pacific. We show that in boreal summer (June–August), the center of the northern lobe sea level pressure anomalies in the SPO is shifted to the east gradually after the 1960–70s. This study focuses on the relationship between the boreal summer SPO and following winter El Niño–Southern Oscillation (ENSO) diversity before and after the eastward shift of the SPO's subtropical lobe. The eastward shift of the SPO's subtropical lobe altered both the seasonal footprint mechanism and the trade wind charging mechanism associated with the SPO and thus profoundly influenced the ENSO diversity. It is revealed that when the northern lobe of the SPO shifts to the west of its average location, it tends to strengthen the eastern Pacific (EP) El Niño mainly via the seasonal footprint mechanism. But after the SPO's northern lobe shifts to the east of its average location, it tends to promote the development of central Pacific (CP) El Niño mainly via the trade wind charging mechanism. The changes in the spatial structure of convection over the tropical Pacific and Indian Oceans may be one of the possible causes for the eastward shift in the SPO's northern lobe. The findings in the present study have implications for a better understanding of ENSO diversity. Significance Statement: Previous studies have demonstrated that the South Pacific Oscillation (SPO), as an important El Niño–Southern Oscillation (ENSO) precursor in the South Pacific, has the potential to provide an enhancement of the prediction of specific ENSO flavor. However, the historical variation in the SPO's spatial structure and related changes in the relationship with the diversity of ENSO are still unclear. In this paper, we show that the subtropical lobe of the boreal summer (June–August) SPO is shifted to the east gradually after the 1960–70s. The changes in the spatial structure have also altered both the seasonal footprint mechanism and the trade wind charging mechanism which play important roles in the developmental processes of different types of ENSO. Our work highlights the importance of the interdecadal changes in the spatial structure of the SPO in understanding the relationship between the SPO and ENSO diversity. [ABSTRACT FROM AUTHOR]

The coupled nature of the ocean–atmosphere system frequently makes understanding the direction of causality difficult in ocean–atmosphere interactions. This study presents a method to decompose turbulent surface heat fluxes into a component which is directly forced by atmospheric circulation and a residual which is assumed to be primarily "ocean-forced." This method is applied to the North Atlantic in a 500-yr preindustrial control run using the Met Office's HadGEM3-GC3.1-MM model. The method shows that atmospheric circulation dominates interannual to decadal heat flux variability in the Labrador Sea, in contrast to the Gulf Stream where the ocean primarily drives the variability. An empirical orthogonal function analysis identifies several residual heat flux modes associated with variations in ocean circulation. The first of these modes is characterized by the ocean warming the atmosphere along the Gulf Stream and North Atlantic Current and the second by a dipole of cooling in the western subtropical North Atlantic and warming in the subpolar North Atlantic. Lead–lag regression analysis suggests that atmospheric circulation anomalies in prior years partly drive the ocean heat flux modes; however, there is no significant atmospheric circulation response in years following the peaks of the modes. Overall, the heat flux dynamical decomposition method provides a useful way to separate the effects of the ocean and atmosphere on heat flux and could be applied to other ocean basins and to either models or reanalysis datasets. Significance Statement: Variability of the ocean affects atmospheric circulation and provides a source of long-term predictability for surface weather. However, the atmosphere also affects the ocean. This makes the separation of cause and effect in such atmosphere–ocean interactions difficult. This paper introduces a method to separate "turbulent heat fluxes," the primary means by which the atmosphere and ocean influence one another, into a component driven by atmospheric variability and a component which is primarily related to ocean variability. The method is tested by applying it to a climate model simulation and is able to identify regions in which the exchange of heat between the ocean and atmosphere is dominated by atmospheric variability and regions which are dominated by the ocean. [ABSTRACT FROM AUTHOR]

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]

Interannual fluctuations in average summertime temperatures across the western United States are captured by a leading empirical orthogonal function that explains over 50% of the total observed variance. In this paper, we explain the origins of this pattern of interannual temperature variability by examining soil moisture–temperature coupling that acts across seasons in observations and climate models. We find that a characteristic pattern of coupled temperature–soil moisture climate variability accounts for 34% of the total observed variance in summertime temperature across the region. This pattern is reproduced in state-of-the-art global climate models, where experiments that eliminate soil moisture variability reduce summertime average temperature variance by a factor of 3 on average. We use an idealized model of the coupled atmospheric boundary layer and underlying land surface to demonstrate that feedbacks between soil moisture, boundary layer relative humidity, and precipitation can explain the observed relations between springtime soil moisture and summertime temperature. Our results suggest that antecedent soil moisture conditions and subsequent land–atmosphere interactions play an important role in interannual summertime temperature variability in the western United States; soil moisture variations cause distal temperature anomalies and impart predictability at time scales longer than one season. Our results indicate that 40% of the observed warming trend across the western United States since 1981 has been driven by wintertime precipitation trends in the U.S. southwest. Significance Statement: Year-to-year fluctuations in summertime temperatures have a large impact on drought, wildfire, and extreme heat across the Western United States. We find strong evidence that soil moisture deficits in the preceding spring may be the primary driver of higher-than-average summer temperatures in this region. Our results suggest that memory in the water cycle may lead to greater predictability in the climate system from season to season and that trends in southwest precipitation have exerted a considerable influence on observed warming over the past 40 years. [ABSTRACT FROM AUTHOR]

Does a warming world, where extremely hot summers are becoming more common, mean that cold summers will never again occur? It is crucial to know whether extremely cold summers are still possible, as such knowledge will significantly impact decisions regarding the further adaptation of crops to cold summers. Japan, which has suffered from many extremely cold summers, has managed past agricultural disruptions with emergency rice imports. In this paper, we show that a climate regime shift associated with the positive phase shift of the summer Arctic Oscillation occurred in 2010 in northeast Eurasia, making the occurrence of extremely cold summers highly unlikely as long as this new regime persists. In fact, Japan has not experienced a cold summer since 2010, while extremely hot summers have been frequent. Since 2010, a double-jet structure with subtropical and polar jets has strengthened, and the polar jet has meandered farther north of Japan, resulting in an upper-tropospheric anticyclone. This anticyclone, which extends downward and tilts southward, reaches southern Japan and prevents cold advection of oceanic air over the cold Oyashio. The Okhotsk high, known as the leading cause of cold summers, has occurred frequently in recent years; however, cold summers have not occurred due to the tilting anticyclone. The recent warming of the Oyashio weakens cold advection. The Pacific–Japan pattern, known as a remote tropical influence, has been weakened. A better understanding of the regime shift will help us understand the tilting anticyclone and the associated extreme summers in northeast Eurasia. Significance Statement: Extremely cold summers are among the most destructive natural disasters, both socioeconomically and agriculturally. Historically, food shortages due to cold summers have triggered wars. This paper proposes that a hemispheric-scale climate regime shift occurred in or around 2010. This regime shift has included warmings in the North Pacific and East Eurasian land surface temperatures. The regime shift is accompanied by the positive shift of the Arctic Oscillation (AO), a jet meander, and an upper-tropospheric anticyclone, making eastern Eurasia extremely hot. Our results imply that extremely cold summers are unlikely to occur in eastern Eurasia so long as this regime persists. Moving forward, it is important that the link between this regime shift and global warming be explored. [ABSTRACT FROM AUTHOR]

The global perspective presented here is built on earlier papers discussing the dynamics of the upper branch of the Hadley cell in the two solsticial seasons. The role of the tropics is made explicit in a conceptual model that is presented and evaluated. The fluctuation of deep tropical convection in longitude and time is seen as crucial. The filamentary outflows from such convective events move westward and across the equator deep into the winter hemisphere. The horizontal tilt of the cross-equatorial flow implies a significant upper-tropospheric flux of westerly momentum from the winter tropics to the summer hemisphere. These properties are related to the cross-equatorial propagation of wave activity triggered by deep tropical convection in the summer hemisphere. The filaments carry with them near-equatorial values of absolute vorticity and potential vorticity. After turning anticyclonically, some filaments move eastward and poleward to the equatorial edge of the winter subtropical jet. There is strong evidence they can interact with the eddies on this jet and enhance their poleward westerly momentum flux. In the global perspective, tropical and extratropical systems and the interaction between them are all important for the dynamics of the upper branch of the Hadley cell. significance statement: The Hadley cell is the large-scale overturning in the atmosphere with air in the upper troposphere moving from the equatorial region to near 30° in the winter hemisphere. In the standard view it is midlatitude weather systems that are responsible for removing angular momentum from this upper branch of the Hadley cell. Here it is proposed that tropical systems and their interaction with the midlatitude systems are also important. Insight into the role of the tropics in the dynamics of the Hadley cell can be obtained by considering it as the sum of many events of active deep convection occurring in different longitudes and at different times. [ABSTRACT FROM AUTHOR]

As the only remaining ice sheet in the Northern Hemisphere, the Greenland ice sheet (GrIS) plays a crucial role in influencing atmospheric circulations, particularly with its rapid melting under global warming. In this paper, the influences of GrIS topography and surface thermal conditions are investigated by a series of aquaplanet experiments. The results show that the GrIS topography induces stationary waves and favors more blocking events through the generation of negative potential vorticity (PV) anomalies, while it tends to suppress local storm activities through the induced stationary waves. The surface cooling center of the GrIS is found to strengthen the jet streams by enhancing the meridional temperature gradient and thermal wind, while it causes the PV and static stability to increase during near-Greenland blocking days, thereby disfavoring blocking onset. Altogether, the topography and surface thermal effects of GrIS appear to compete with each other so that the net effect would determine the final response. Nevertheless, nonlinearity is found in both GrIS-topography alone and GrIS-surface temperature alone experiments, where nonlinear responses of atmospheric circulation are detected when the GrIS topography height or surface temperature exceeds their critical values, respectively. Hence, through this study, the response of the blocking in the vicinity of Greenland to the combined effects of topography and surface thermal conditions may shed light on comprehending the underlying mechanism of blocking alteration in a changing climate. Significance Statement: Although there have been numerous observation-based studies showing that the blocking around Greenland has increased over the past few decades, which is a predominant driver in accelerating the Greenland ice sheet (GrIS) melting, the reasons for this change are still unclear. In addition, the impact of GrIS on blocking still needs investigation. Through idealized aquaplanet simulations, this study examines the effect of GrIS's topography and surface thermal conditions upon blocking onset. It suggests the nonlinearity of the blocking response in the vicinity of Greenland to the combined effects in the variation of the height and surface temperature of GrIS. This study will enhance our understanding of possible changes in blocking due to global warming. [ABSTRACT FROM AUTHOR]

In this paper we summarize improvements in climate model simulation of eastern boundary upwelling systems (EBUS) when changing the forcing dataset from the Coordinated Ocean-Ice Reference Experiments (CORE; ∼2° winds) to the higher-resolution Japanese 55-year Atmospheric Reanalysis for driving ocean–sea ice models (JRA55-do, ∼0.5°) and also due to refining ocean grid spacing from 1° to 0.1°. The focus is on sea surface temperature (SST), a key variable for climate studies, and which is typically too warm in climate model representation of EBUS. The change in forcing leads to a better-defined atmospheric low-level coastal jet, leading to more equatorward ocean flow and coastal upwelling, both in turn acting to reduce SST over the upwelling regions off the west coast of North America, Peru, and Chile. The refinement of ocean resolution then leads to narrower and stronger alongshore ocean flow and coastal upwelling, and the emergence of strong across-shore temperature gradients not seen with the coarse ocean model. Off northwest Africa the SST bias mainly improves with ocean resolution but not with forcing, while in the Benguela, JRA55-do with high-resolution ocean leads to lower SST but a substantial bias relative to observations remains. Reasons for the Benguela bias are discussed in the context of companion regional ocean model simulations. Finally, we address to what extent improvements in mean state lead to changes to the monthly to interannual variability. It is found that large-scale SST variability in EBUS on monthly and longer time scales is largely governed by teleconnections from climate modes and less sensitive to model resolution and forcing than the mean state. [ABSTRACT FROM AUTHOR]

Coastal flooding induced by sea surface high extreme (HEX) events is an increasing risk to human society and infrastructure as both urban growth in coastal areas and anthropogenic sea level rise continue, especially for island nations like Indonesia. This paper investigates the role of atmospheric intraseasonal oscillations (ISOs), which are dominated by the Madden–Julian oscillation (MJO), in forcing HEXs on the coasts of Indonesia bordering the Indian Ocean. We use satellite altimetry data from 1993 to 2021 and tide gauge observations to detect HEXs, and modeling experiments using both the Regional Ocean Modeling System and a Bayesian dynamic linear model to understand the forcing and processes. We find that HEXs exhibit strong seasonality, with most events occurring during boreal winter (December–February) and spring (March–May) that are dominated by seasonal-to-decadal and intraseasonal variability respectively. In 32% of the 56 HEX events detected, the amplitude of ISO-induced sea level anomalies (SLAs) exceeds that of seasonal-to-decadal SLAs. Surface wind stress associated with atmospheric ISOs is the major forcing for intraseasonal SLAs, and both the remote westerly wind stress from the Indian Ocean equator and northwesterly longshore wind stress at the Indonesian coasts play important roles in driving the HEXs. The MJO is the dominant cause of ISO-dominated HEXs and its impact shows strong seasonal differences. Spring MJOs are associated with stronger convective anomalies over the eastern Indian Ocean equator that drive stronger zonal winds across the equatorial basin that lead to more HEX events compared to winter MJOs when the convection is shifted southward. [ABSTRACT FROM AUTHOR]

This paper describes a framework for identifying dominant atmospheric drivers of ocean variability. The method combines statistics of atmosphere–ocean fluxes with physics from an ocean general circulation model to derive atmospheric patterns optimized to excite variability in a specified ocean quantity of interest. We first derive the method as a weighted principal components analysis and illustrate its capabilities in a toy problem. Next, we apply our analysis to the problem of interannual upper ocean heat content (HC) variability in the North Atlantic Subpolar Gyre (SPG) using the adjoint of the MITgcm and atmosphere–ocean fluxes from the ECCOv4-r4 state estimate. An unweighted principal components analysis reveals that North Atlantic heat and momentum fluxes in ECCOv4-r4 have a range of spatiotemporal patterns. By contrast, dynamics-weighted principal components analysis collapses the space of these patterns onto a small subset—principally associated with the North Atlantic Oscillation—that dominates interannual SPG HC variance. By perturbing the ECCOv4-r4 state estimate, we illustrate the pathways along which variability propagates from the atmosphere to the ocean in a nonlinear ocean model. This technique is applicable across a range of problems across Earth system components, including in the absence of a model adjoint. Significance Statement: While the oceans have absorbed 90% of the excess heat associated with human-forced climate change, the change in the ocean's heat content is not steady, with peaks and troughs superimposed upon a general increase. These fluctuations come from chaotic changes in the atmosphere and ocean and can be hard to disentangle. We use this case of ocean heat content variability to introduce a new method for determining the patterns of weather and climate in the atmosphere that are most effective at generating fluctuations in the ocean. To do this, we combine the statistics of recent atmospheric activity with output from a state-of-the-art numerical ocean model that reveals physical processes driving changes in ocean quantities including ocean heat content. This approach suggests that the atmospheric patterns that stimulate the most energetic changes in ocean heat content in the northern North Atlantic are not necessarily the most energetic patterns present in the atmosphere. We test our findings by preventing these patterns from affecting the ocean in our numerical model and measure a strong reduction in ocean heat content fluctuations. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including the "Meteorological Monographs," peer-review process for the same, and online availability of its papers.

Dimension reduction techniques are an essential part of the climate analyst's toolkit. Due to the enormous scale of climate data, dimension reduction methods are used to identify major patterns of variability within climate dynamics, to create compelling and informative visualizations, and to quantify major named modes such as El Niño–Southern Oscillation. Principal components analysis (PCA), also known as the method of empirical orthogonal functions (EOFs), is the most commonly used form of dimension reduction, characterized by a remarkable confluence of attractive mathematical, statistical, and computational properties. Despite its ubiquity, PCA suffers from several difficulties relevant to climate science: high computational burden with large datasets, decreased statistical accuracy in high dimensions, and difficulties comparing across multiple datasets. In this paper, we introduce several variants of PCA that are likely to be of use in climate sciences and address these problems. Specifically, we introduce non-negative, sparse, and tensor PCA and demonstrate how each approach provides superior pattern recognition in climate data. We also discuss approaches to comparing PCA-family results within and across datasets in a domain-relevant manner. We demonstrate these approaches through an analysis of several runs of the E3SM climate model from 1991 to 1995, focusing on the simulated response to the Mt. Pinatubo eruption; our findings are consistent with a recently identified stratospheric warming fingerprint associated with this type of stratospheric aerosol injection. [ABSTRACT FROM AUTHOR]

This paper presents a methodology that is designed for rapid exploratory analysis of the outputs from ensembles of climate models, especially when these outputs consist of maps. The approach formalizes and extends the technique of "intermodel empirical orthogonal function" analysis, combining multivariate analysis of variance techniques with singular value decompositions (SVDs) of structured components of the ensemble data matrix. The SVDs yield spatial patterns associated with these components, which we call ensemble principal patterns (EPPs). A unique hierarchical partitioning of variation is obtained for balanced ensembles in which all combinations of factors, such as GCM and RCM pairs in a regional ensemble, appear with equal frequency: suggestions are also proposed to handle unbalanced ensembles without imputing missing values or discarding runs. Applications include the selection of ensemble members to propagate uncertainty into subsequent analyses, and the diagnosis of modes of variation associated with specific model variants or parameter perturbations. The approach is illustrated using outputs from the EuroCORDEX regional ensemble over the United Kingdom. [ABSTRACT FROM AUTHOR]

During July and August of 2022, the Yangtze River Basin (YRB) experienced its most extreme high temperature (EHT) event since 1979, resulting in large numbers of human casualties and severe economic losses. This paper reveals the spatial and temporal features of the EHT over the YRB (YRB-EHT) in 2022 and disentangles its extreme nature from a historical perspective. Results showed the following: 1) The record-breaking YRB-EHT was directly caused by the adiabatic heating associated with an anomalous barotropic high pressure (or heat dome) and descending motion in the region. The intensified and westward-shifted western North Pacific subtropical high and eastward-extended South Asian high played critical roles in the formation of the heat dome and descending motion anomaly. 2) Convection anomalies over the tropical Atlantic and Pacific induced by the reintensified La Niña–like Pacific sea surface temperature anomaly pattern, along with the strong positive North Atlantic Oscillation (NAO), were the key contributing factors to the formation of the barotropic high pressure anomaly and YRB-EHT. 3) A physics-based empirical simulation model constructed using the factors of the NAO and tropical convection successfully reproduced the historical year-to-year variation of YRB temperatures, as well as the extreme in 2022, implying that the unprecedented 2022 YRB-EHT had universal dynamic origins. This study highlights the importance of the combined impacts of tropical and extratropical forcings in the record-breaking YRB-EHT in 2022, and thus may provide useful clues for seasonal predictions of summer mean or extreme temperatures in the YRB. Significance Statement: Extreme high temperatures hit the Yangtze River Basin (YRB) in summer 2022, causing large numbers of human casualties and severe economic losses. Here, from a historical perspective, we disentangle the dynamic origins of these high temperatures over the YRB. Based on evidence from both observations and model simulations, the present study highlights the importance of the combined impacts of tropical and extratropical routes of influence on these extremely high temperatures in the YRB, and thus may provide useful clues for seasonal predictions of YRB summer mean or extreme temperatures. [ABSTRACT FROM AUTHOR]

Intraseasonal and diurnal variations are two basic periodic oscillations in global/regional climate and weather. To investigate their joint impacts over East Asia, this paper categorizes the boreal summer intraseasonal oscillations (ISOs) in 1998–2019 into two groups with different diurnal cycles. It is shown that the active ISOs with large diurnal cycles feature a northwestward-moving anomalous anticyclone with strong southerlies at the western flank. These ISOs have in-phase patterns of geopotential height anomaly between low and midlatitudes over East Asia, associated with the simultaneous expansions of the western Pacific subtropical high (WPSH) and South Asian high (SAH). They couple with the anomalous ABL heating by daytime solar radiation over East Asia, which acts to enhance monsoon southerlies at midnight. The nocturnally strengthened southerlies facilitate dynamic lifting, moisture transport, and convective instability for producing midnight to morning rainfall at their northern terminus, thereby yielding a remarkable northward propagation of the monsoon rain belt. In contrast, the other ISOs with small diurnal cycles are related to a westward-moving anomalous anticyclone, while the WPSH and SAH have relatively small expansions and the westerly trough is active at middle latitudes. They lead to the dipole patterns of geopotential height anomaly and weak ABL heating over East Asia. The daily-mean southerlies and moisture conditions as well as their nocturnal enhancements are relatively weak, and thus, the northward shift of the monsoon rain belt is less pronounced. These results highlight that the large-scale conditions of ISOs can be distinguished by their different couplings with regional-scale diurnal forcings, which help the understanding and prediction of multiscale rainfall activities. [ABSTRACT FROM AUTHOR]

The climate system responds to changes in the amount of atmospheric greenhouse gases or aerosols through rapid processes, triggered within hours and days, and through slower processes, where the full response may only be seen after centuries. In this paper, we aim to elucidate the mechanisms operating on time scales of hours to years to better understand the response of key climate quantities such as energy fluxes, temperature, and precipitation after a sudden increase in either carbon dioxide (CO2), black carbon (BC), or sulfate (SO4) aerosols. The results are based on idealized simulations from six global climate models. We find that the effect of changing ocean temperatures kicks in after a couple of months. Rapid precipitation reductions start occurring instantly and are established after just a few days. For BC, they constitute most of the equilibrium response. For CO2 and SO4, the magnitude of the precipitation response gradually increases as surface warming/cooling evolves, and for CO2, the sign of the response changes from negative to positive after 2 years. Rapid cloud adjustments are typically established within the first 24 h, and while the magnitude of cloud feedbacks for CO2 and SO4 increases over time, the geographical pattern of the equilibrium cloud change is present already after the first year. While there are model differences, our work underscores the overall similarity of the major time-varying processes and responses simulated by current global models and hence the robustness of key features of simulated responses to historical and future anthropogenic forcing. Significance Statement: How does the climate system respond to a change in the amount of atmospheric greenhouse gases or aerosols? Some processes are rapid, responding within hours and days. Others are slow, and the full response to a forcing of the climate may only be seen after centuries. In this paper, we use six global climate models to investigate the time scales of climate responses to carbon dioxide, black carbon, and sulfate, focusing on key climate quantities, such as temperature, precipitation, and clouds. While there are ample model differences, our work underscores the overall similarity of the major time-varying processes and responses simulated by current global models and hence the robustness of key features of simulated responses to historical and future anthropogenic forcing. [ABSTRACT FROM AUTHOR]

This paper examines the trends in hot summer days for the Pacific Northwest in observations and a regional climate model ensemble. Hot days are identified by the temperature threshold for several percentile values computed over 10-yr intervals (85th, 90th, and 95th percentiles and absolute maximum) to differentiate heat events of different intensities and are compared to the median temperature (50th percentile). For the stations analyzed, the observed rate of warming during hot days is not statistically different from the warming rate of median days since the 1950s. However, for projections to 2100, hot days show a statistically significant increase in the warming rate of the hottest days compared to the warming rate for median days. Depending on location, the 95th-percentile daily maximum temperature shows a warming rate of up to 0.2°C decade−1 above the median warming rate. The divergence in the trends of median and extreme temperature shows substantial regional variation depending on local terrain and coastlines. The warming trend during hot days is related to the unique circulation patterns during heat events, which respond to different feedbacks and amplifying effects in the land–atmosphere system from those that prevail during typical days. The regional climate model simulations are taken from an ensemble of the Weather Research and Forecasting (WRF) Model simulations forced by 12 global climate model simulations from phase 5 of the Climate Model Intercomparison Project (CMIP5) using the RCP8.5 emissions scenario and 12-km grid spacing. Significance Statement: The heatwave of June 2021 had substantial societal and ecological impacts, illustrating vulnerability to record-shattering events. This paper addresses whether climate change can cause heat events in the Pacific Northwest to warm at a more rapid rate than typical days. Based on observations, in the recent past, the hottest days warmed at about the same rate as typical days in the recent past. However, results from a high-resolution climate model show a higher rate of warming during the warmest days relative to median days under the most aggressive future emissions scenario. This effect could cause heatwaves to become more intense relative to typical days by 2100, making adaptation to extreme events more difficult. [ABSTRACT FROM AUTHOR]

This paper describes the new Regional Arctic Ocean/sea ice Reanalysis (RARE) with a domain that spans a subpolar/polar cap poleward of 45°N. Sequential data assimilation constrains temperature and salinity using World Ocean Database profiles as well as in situ and satellite SST, and PIOMAS sea ice thickness estimates. The 41-yr (1980–2020) RARE1.15.2 reanalysis with resolution varying between 2 and 5 km horizontally and 1–10 m vertically in the upper 100 m is examined. To explore the impact of resolution RARE1.15.2 is compared to a coarser-resolution SODA3.15.2, which uses the same modeling and data assimilation system. Improving resolution in the reanalysis system improves agreement with observations. It produces stronger more compact currents, enhances eddy kinetic energy, and strengthens along-isopycnal heat and salt transports, but reduces vertical exchanges and thus strengthens upper ocean haline stratification. RARE1.15.2 and SODA3.15.2 are also compared to the Hadley Center EN4.2.2 statistical objective analysis. In regions of reasonable data coverage such as the Nordic seas the three products produce similar time-mean distributions of temperature and salinity. But in regions of poor coverage and in regions where the coverage changes in time EN4.2.2 suffers more from those inhomogeneities. Finally, the impact on the Arctic of interannual temperature fluctuations in the subpolar gyres on the Arctic Ocean is compared. The influence of the subpolar North Pacific is limited to a region surrounding Bering Strait. The influence of the subpolar North Atlantic, in contrast, spreads throughout the Nordic seas and Barents Sea in all three products within two years. Significance Statement: The Arctic Ocean/sea ice system plays crucial roles in climate variability and change by controlling the northern end of the oceanic overturning circulation, the equator to pole air pressure gradient, and Earth's energy balance. Yet the historical ocean observation set is sparse and inhomogeneous, while ocean dynamics has challengingly fine horizontal and vertical scales. This paper introduces a new Regional Arctic Ocean/sea ice Reanalysis (RARE) whose goal is to use the combined constraints of mesoscale ocean dynamics, historical observations, surface meteorology, and continental runoff in a data assimilation framework to reconstruct historical variability. RARE is used to produce a 41-yr ocean/sea ice reanalysis 1980–2020 whose results are described here. [ABSTRACT FROM AUTHOR]

Prediction of El Niño–Southern Oscillation (ENSO) is hindered by a spring predictability barrier (SPB). In this paper, we investigate the effects of the Indian Ocean (IO) on the SPB. Using a seasonally varying extended IO–ENSO recharge oscillator model, we find that the SPB is much weakened when IO is coupled with ENSO. To gauge the relative role of the Indian Ocean dipole (IOD) and the Indian Ocean Basin (IOB) modes in weakening ENSO SPB, we develop an empirical dynamical model, the linear inverse model (LIM). By coupling/decoupling the IOB or IOD mode with ENSO, we show that the IOB significantly weakens eastern Pacific and central Pacific ENSO SPBs, while the IOD plays a weaker role. The evolution of the optimum initial structures also illustrates the importance of the IOB in ENSO SPB. Moreover, the IOB strongly influences the forecast skill of La Niña SPB rather than El Niño SPB. This point is also identified through six coupled models from the North American multimodel ensemble. It may be related to the role of the IO in the asymmetry in the duration of El Niño and La Niña. The IOB-induced easterly wind anomalies are conducive to the development of La Niña and thus the prediction of La Niña events, whereas these anomalous easterlies are less important during the development of El Niño and the related forecast of El Niño events. [ABSTRACT FROM AUTHOR]

In this paper, we present a late summer (August-September) temperature reconstruction over the period 1792-2020 based on a tree-ring maximum latewood density (MXD) chronology for the southern Tibetan Plateau (TP). The reconstruction explained 66.2% of the variance in the instrumental temperature records during the calibration period 1960-2020 and captured the warming trend since the 1960s, which would support the current warming on the TP. In addition, a warming hiatus existed during 2001-12 and the last 20 years (2000-20) were the warmest period in the past two centuries. The reconstruction matched other MXD- and mean latewood density (LWD)-based late summer temperature reconstructions from neighboring regions, and fluctuated in synchrony with the Climatic Research Unit (CRU) Northern Hemisphere land surface temperature during 1850-2020. Multitaper method analysis and wavelet analysis revealed significant periodicities of 2-3, 20-30, and 40-60 years in the reconstructed series. Our reconstructed series was very consistent and highly correlated with the Atlantic multidecadal oscillation (AMO). During the warm phase of the AMO, higher pressure and divergent horizontal winds over the TP contribute to warmer summers in the region. In addition, we found that the southern TP experienced the lowest temperature and downward solar radiation in the second year following large volcanic eruptions. The decrease in downward solar radiation may be directly responsible for the occurrence of the lowest temperatures. The results indicate that the AMO and large volcanic eruptions were impacting factors on temperature in our study area. [ABSTRACT FROM AUTHOR]

This paper estimates a two-component energy balance model as a linear state-space system (EBM-SS model) using historical data. It is a joint model for the temperature in the mixed layer, the temperature in the deep ocean layer, and radiative forcing. The EBM-SS model allows for the modeling of nonstationarity in forcing and the incorporation of multiple data sources for the unobserved processes. We estimate the EBM-SS model using historical datasets at the global level for the period 1955–2020 by maximum likelihood. We show in the empirical estimation and in simulations that using multiple data sources for the unobserved processes reduces parameter estimation uncertainty. When fitting the EBM-SS model to six observational global mean surface temperature (GMST) anomaly series, the GMST projections under representative concentration pathway scenarios are comparable to those from Coupled Model Intercomparison Project models. The results show that a simple statistical climate model estimated on the historical period can produce GMST projections compatible with output from large-scale Earth system models. Significance Statement: We develop a statistical model to understand Earth's energy balance and how it impacts temperature across the planet's surface and deep oceans. Unlike previous approaches, ours is fully statistical. This means that we use maximum likelihood to calculate the estimates and evaluate the level of uncertainty in the model's parameters. By applying the model to historical data from 1955 to 2020, we are able to make predictions about the average global surface temperature that are consistent with those from the Coupled Model Intercomparison Project. Our findings support current predictions about global temperatures using a straightforward statistical climate model, grounded in historical data. [ABSTRACT FROM AUTHOR]

Snow cover (SC) is an important contributor to atmospheric predictability on subseasonal to seasonal time scales. This paper evaluates the submonthly scale cause-and-effect relationship between SC and surface air temperature (SAT) in Eurasia, which has been typically overlooked in previous statistical analyses of subseasonal to seasonal atmospheric predictability. We focus on the November east–west dipolar SC pattern, a dominant large-scale SC phenomenon. We use an information flow analysis, based on information theory, to infer causal relations not revealed by conventional correlation analysis. This analysis indicates a one-way causality from SAT to SC around the west pole (Europe) in boreal autumn (November), implying that SC has little influence on the time evolution of SAT. In contrast, causality from SC to SAT is significant around the east pole (the Mongolian Plateau). An atmospheric model experiment suggests that the SAT response to SC can persist for a month via snow–albedo feedback, although the response of the upper atmosphere in the model is small. Furthermore, the subseasonal hindcasts show that the contribution of SC may affect the predictability of SAT for up to four weeks around the east pole. We suggest that the geographical and climatological atmospheric conditions are favorable for generating a positive albedo feedback as a “hotspot” of SC–SAT coupling around the east pole in autumn. The agreement of our causality analysis with other analytical and modeling approaches underscores the cause-and-effect relationship between SC and SAT and its contribution to the subseasonal predictability over autumnal Eurasia. [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]

It is well known that El Niño–Southern Oscillation (ENSO) can influence the East Asian winter climate by modifying the atmospheric circulation over the western North Pacific (WNP). While the impact on precipitation in southeastern China has been extensively studied, the ENSO signal in surface air temperature (SAT) remains overlooked. In this paper, we identify robust ENSO footprints in the winter daily minimum SAT in southeastern China, with El Niño winters generally accompanied by warmer-than-normal minimum SAT anomalies. In contrast, the responses of maximum SAT are weak and negligible, suggesting a diurnal cycle–dependent ENSO influence. Further analysis indicates that this diurnal cycle dependence stems primarily from the disparate surface radiative heating between day and night induced by ENSO-related local total cloud cover (TCC) change. The warmer minimum SAT occurring in the early morning of El Niño winters is mainly caused by the enhanced surface downward longwave radiative heating as a result of the TCC increase. However, in the afternoon of El Niño winters, although the anomalous horizontal advection of warm air plays a role, there is surface radiative cooling as the weakening of solar radiation due to TCC reflection overwhelms the increase in downward longwave radiation, which leads to a weakened sensible heat flux and thus has a cooling effect on the SAT. Ultimately, these two processes effectively cancel each other out and together produce insignificant maximum SAT responses. Our conclusions carry important implications for the seasonal to interannual winter climate prediction in southeastern China. Significance Statement The purpose of this study is to better understand how ENSO influences winter surface air temperature in southeastern China. Despite insignificant responses of winter daily maximum temperature to ENSO, we find here a robust ENSO influence on the daily minimum temperature, with warm anomalies tending to occur during El Niño events. Further evidence suggests that this diurnal cycle–dependent ENSO influence is mainly caused by ENSO-induced change in local cloudiness, which has a different radiative heating effect between day and night. Our findings are of great importance for improving regional climate prediction, which will benefit social and economic activities. [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]

In this paper we introduce an objective definition for the onset and the retreat of the northern Australian rainy season that overlaps significantly with the Australian monsoon season. We define onset and retreat dates of the northern Australian rainy season as being the first and the last day of the year when the daily rain rate exceeds and falls below the climatological annual mean rain rate, respectively. However, our definition of onset/demise is not as restrictive as the traditional monsoon season that seeks the arrival of the westerlies and the equatorward retreat of the trough at its onset and demise, respectively. As defined in this paper, the length of the rainy season is longer than the monsoon season and includes the pre- and post-monsoon rainfall. It is noted that an early or later onset date of the northern Australian rainy season is associated with a longer or shorter, wetter or drier, and colder or warmer season, respectively. Similar relationship is also observed with demise date variations, which are, however, weaker than the onset date variations. Furthermore, we find that the relationship of the northern Australian seasonal rainfall variations with ENSO variability becomes stronger when we account for variations in the length of the rainy season compared to the fixed (December-- February) monsoon season length. We also find a significant linear trend over the time period of the analysis from 1901 to 2015 toward an increasing length of the northern Australian rainy season that influences the corresponding rising trend of seasonal rainfall anomalies. [ABSTRACT FROM AUTHOR]

This paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century. Significance Statement: This paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation. [ABSTRACT FROM AUTHOR]

ISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1° grid, all other gridded products at 1.0°-equivalent equal area, separate satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data, expanded documentation, the processing code, and an operations guide are available online. Notable changes are 1) a lowered ice–liquid temperature threshold, 2) a treatment of the radiative effects of aerosols and surface temperature inversions, 3) refined specification of the assumed cloud microphysics, and 4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high cloud and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud-top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events. Significance Statement: This paper reports on the evolution of the research goals and satellite cloud data products produced by ISCCP, a long-term international project, which is now fully operational. The growing length of record with 10-km and 3-h sampling makes possible studies of cloud variations from diurnal-to-weather scale (cloud process scale) to climate variation scale. In particular the length of record includes many examples of ENSO and is beginning to encompass the slower modes of ocean variation, allowing studies of the role of cloud feedbacks in coupling the atmosphere and ocean circulations. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) is characterized by abundant warm and cold structures that influence the overlying atmospheric boundary layer dynamics through two different mechanisms. First, turbulence and large eddies in the lower troposphere are affected by atmospheric stability, which can be modified by local SST, resulting in enhanced vertical mixing and larger surface winds over warmer waters. Second, the thermodynamic adjustment of air density to the underlying SST structures and the subsequent changes in atmospheric pressure drive secondary circulations. This paper aims to disentangle the effects of these processes and explore the environmental conditions that favor them. Two main environmental variables are considered: the large-scale air–sea temperature difference (proxy for stability) and wind speed. Using 5 years of daily reanalyses data, we investigate the 10-m wind response to SST structures. Based on linear regression between wind divergence and SST derivatives, we show that both mechanisms operate over a large spectrum of conditions. Ten-meter wind divergence is strongly impacted by the local SST via its effect on vertical mixing for midwind regimes in slightly unstable to near-neutral conditions, whereas the secondary circulation is important in two distinct regimes: low wind speed with a slightly unstable air column and high background wind speed with a very unstable air column. The first regime is explained by the prolonged Lagrangian time that the air parcel stays over an SST structure while the second one is related to strong heat fluxes at the air–sea interface, which greatly modify the marine atmospheric boundary layer properties. Location and frequency of the environmentally favorable conditions are discussed, as well as the response in low-cloud cover and rainfall. Significance Statement: The main objective of this study is to explore the wind response to thermal structures at the sea surface under different environmental conditions using the latest atmospheric reanalysis. Recent literature suggests that fine-scale air–sea interactions affect a large spectrum of atmospheric dynamics, from seasonal to weather-type regimes. It is thus important to characterize the atmospheric response to ocean surface variability. Our findings describe the environmental conditions for which the two main physical processes through which the atmosphere responds to sea surface temperature structures are active the most and can guide the development of high-resolution observing missions and campaigns in specific geographical locations and seasons to retrieve data that can be used to improve parameterization in models. [ABSTRACT FROM AUTHOR]

Prediction of summer precipitation in north China (NCP) has long been a challenge partly because its low correlation with previous sea surface temperature (SST) anomalies (SSTA) limits the application of SST in NCP prediction. This study aims to extract optimal predictors of NCP from the SST field using an objective method—empirically optimal screening (EOS). It finds that the optimal precursory signal of NCP lies in the change of SSTA from winter to spring rather than the SSTA itself. This study identifies two optimal precursory signs predicting a positive (negative) NCP anomaly: the anomalous SST cooling (warming) from winter to spring in the coastal area of Somalia and Peru. Interestingly, these two presummer conditions have considerable independence, but they lead to a similar summer development of La Niña (El Niño). In summer, the tropical precipitation anomaly pattern associated with La Niña (El Niño) development excites a meridional wave train over the western Pacific and the circumglobal teleconnection in the Northern Hemisphere. Both of the anomalous wave trains show abnormal high (low) pressure over northeast Asia, which induces the south (north) wind anomalies over north China and produces abundant (deficient) precipitation there. These results highlight the importance of the SST evolution from winter to spring, break through the limitation of SST application in NCP prediction, and thus bring a prospect of improving NCP forecast skills. Significance Statement: Sea surface temperature (SST) anomalies are most used as predictors in climate prediction. However, the forecast of summer precipitation in north China is limited by its low correlation with prior SST anomalies. In this paper, we find that the optimal precursory signal of north China precipitation (NCP) is not the SST anomaly itself, but the changes of SST anomalies from winter to spring in the coastal area of Somalia and Peru. These two precursory signals are almost independent yet indicate similar summer situations leading to NCP anomaly. These results highlight the importance of the dynamic evolution of sea surface temperature in improving the forecast skill of NCP. [ABSTRACT FROM AUTHOR]

Reconstructing the history of polar temperature from ice core water isotope (δ18O) calibration has remained a challenge in paleoclimate research, because of our incomplete understanding of various temperature--δ18O relationships. This paper resolves this classical problem in a new framework called the unified slope equations (USE), which illustrates the general relations among spatial and temporal δ18O--surface temperature slopes. The USE is applied to the Antarctica temperature change during the last deglaciation in model simulations and observations. It is shown that the comparable Antarcticamean spatial slope with deglacial temporal slope in δ18O--surface temperature reconstruction is caused, accidentally, by the compensation responses between the δ18O--inversion layer temperature relation and the inversion layer temperature itself. Furthermore, in light of the USE, we propose that the present seasonal slope of δ18O--inversion layer temperature is an optimal paleothermometer that is more accurate and robust than the spatial slope. This optimal slope suggests the possibility of reconstructing past Antarctic temperature changes using present and future instrumental observations. [ABSTRACT FROM AUTHOR]

Using 25 quasi-biennial oscillation (QBO)-resolving models from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5/6), this study systematically explores the Southern Hemisphere (SH) extratropical response to the QBO. The observed maximum stratospheric polar vortex–weakening response to the 20-hPa easterly QBO appears in the austral spring, which is reproduced qualitatively by seven models. The Eliassen–Palm (EP) flux convergence associated with enhanced upward propagation of waves from the SH midlatitude troposphere is also reasonably simulated following easterly QBO in these seven models. The Brewer–Dobson (BD) circulation response, especially its deep branch, has a large bias among models. The anomalous upwelling of the deep branch of the BD circulation and the cold anomalies are confined to midlatitudes above 20 hPa in reanalyses, while this deep branch is simulated to expand to the Antarctic stratosphere with unrealistically cold anomalies for some models. Models with a decent stratospheric pathway tend to simulate the observed negative Southern Annular Mode (SAM)-like response in the troposphere. Further, the largest enhanced convection center is observed over the tropical Indo-Pacific Ocean and simulated by 12 models, most of which also simulate a more reasonable height anomaly pattern in the troposphere. The near-surface response to the QBO also resembles the SAM pattern with warm anomalies over eastern Antarctic, which are simulated by only five models. Seven models simulate the observed wet signals in the midlatitude southern Indo-Pacific Ocean, where an anomalous low develops. Overall, models with a better reproduction of the SH stratospheric polar vortex response exhibit a more reasonable near-surface response, though for all models the response is too weak. Significance Statement: The equatorial stratospheric quasi-biennial oscillation (QBO) has been widely reported to influence the Northern Hemisphere. This paper focuses on the possible impact of the QBO on the Southern Hemisphere (SH) using 25 models. The maximum QBO signal in the Antarctic stratosphere forms in austral spring when the climatological vortex intensity has weakened relative to austral winter. The timing and magnitude of the QBO signal is simulated with different degrees of success by the 25 models, and those with a reasonable polar vortex response tend to better simulate the near-surface response. The QBO has another pathway for the extratropical circulation change via modifying tropical convection, and models also simulate a large spread in the tropical convection change associated with the QBO. [ABSTRACT FROM AUTHOR]

The role of the Gulf of California (GoC) in the North American monsoon (NAM) is investigated using a global climate model with 50-km horizontal atmospheric resolution and prescribed SSTs. Specifically, two 135-yr simulations are compared to quantify the influence of the GoC on the NAM: in the first simulation a realistic representation of the GoC is incorporated, while in the second simulation the GoC is replaced with land surface. The results suggest that the GoC has a significant impact on circulation, with cooler surface air temperatures and lower surface friction allowing for south-southeasterly surface flow along the entire length of the GoC, in turn increasing low-level moisture fluxes into the NAM region. Cooler air over the GoC also leads to lower heights at 700–500 hPa, with a corresponding cyclonic moisture flux anomaly, further increasing moisture fluxes into the NAM region. Correspondingly, precipitation is substantially higher over the NAM region and even east of the Continental Divide in areas such as New Mexico and the U.S. Great Plains. July/August precipitation with a realistic GoC is generally 25%–50% greater in northwestern Mexico than the land-filled case, with precipitation 50% greater in much of the southwestern United States. Due to enhanced surface evaporation, areas with increased precipitation also tend to have lower surface temperatures, higher sea level pressure, and lower mid- to upper-tropospheric heights, thus altering the large-scale circulation. These results highlight the importance of the GoC in the NAM and demonstrate the necessity of resolving the GoC in climate simulations. Significance Statement: This paper seeks to improve our understanding of the North American monsoon, an important moisture source in the relatively arid region of northwest Mexico and the Southwest United States. Specifically, we investigate the role of the Gulf of California: a long, narrow sea surrounded by elevated topography within the North American monsoon region, oriented roughly southeast–northwest. The results suggest the Gulf of California is an important component of the North American monsoon system. We find that the Gulf of California acts to enhance moisture transports into the North American monsoon, leading to substantially higher precipitation over a large region. Therefore, the Gulf of California should be carefully considered in climate simulations and future projections, especially given it is often not well resolved. [ABSTRACT FROM AUTHOR]

The spatial distribution of summer rainfall anomalies over eastern China often shows a tripole pattern with rainfall anomalies over the Yangtze River basin varies in opposite phase with North China and South China. It is not clear whether this tripole pattern is an intrinsic atmospheric mode or it is remotely forced. Using two sets of model outputs from 20 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5), this paper investigates the driving mechanisms of this leading rainfall mode and its major influencing factors. One set (piControl) is fully coupled atmosphere–ocean simulations under constant preindustrial forcing and the other (sstClim) is atmosphere-alone models forced by prescribed climatological sea surface temperatures (SSTs). By comparing results from these two different sets of simulations, it is found that the tripole pattern is the leading mode of summer precipitation variability over eastern China with or without oceanic forcing. It can be regarded as an intrinsic atmospheric mode although air–sea interaction can modify its temporal variability. The cyclonic–anticyclonic atmospheric circulation anomaly over the northern North Pacific is identified as a key factor in both experiments. As atmospheric internal variability, it is related to a circumglobal zonal wave train propagating along the westerly jet stream. When air–sea interactions involved, modulation from SST anomalies is exerted through the meridional Pacific–Japan/East Asia–Pacific wave train propagating along the East Asian coast. Our results suggest that the North Pacific could be another key region providing potential predictability to the East Asian monsoon in addition to the Indo-Pacific. [ABSTRACT FROM AUTHOR]

This study uses Global Historical Climate Network (GHCN) data in each season to identify the days with the most extreme precipitation ("EP days") in the mid-Atlantic and northeast United States between 1979 and 2019. These days are sorted according to the fraction of extreme precipitation attributed to tropical cyclone (TC), atmospheric river (AR), and extreme integrated vapor transport (IVT) influences. In winter and spring, there have been increases in seasonal precipitation from the most extreme days, associated with a combination of frequency and intensity changes. These increasing trends come primarily from atmospheric rivers. In summer and fall, there have also been large increases in precipitation on extreme days, in this case due entirely to increased event frequency. These changes come from a combination of AR, TC, and extreme IVT influences. Synoptic characteristics of AR-related EP days in winter and spring have changed significantly. In winter, there has been an amplification of the Atlantic ridge and a deepening of the upstream trough over the upper Great Plains, as well as enhanced AR detection and IVT on these days. The composite low has shifted north and intensified. In spring, the trough has weakened and 1000–500-hPa thickness has increased broadly to the south. These changes are related to changes in the large-scale flow. In winter and spring, the North Atlantic subtropical high (NASH) has strengthened and shifted west, leading to increased southwesterly IVT over the mid-Atlantic and Northeast United States. In summer, southerly IVT along the east coast has increased, and 1000–500-hPa climatological thickness has increased broadly in all seasons. Significance Statement: This paper studies the days with the most extreme precipitation over the mid-Atlantic and Northeast United States in each season and finds that there have been large changes in the frequency, intensity, and characteristics of some of these days. Extreme days associated with atmospheric rivers (ARs) and tropical cyclones (TCs) have become more frequent. Precipitation on AR-related days has also become more intense in some areas. On winter extreme days associated with ARs, the pattern has become more amplified and moisture fluxes have become stronger; these changes are likely associated with strengthened high pressure over the Atlantic. Throughout all seasons, there is evidence of warming on extreme days. This is important because it adds to our understanding of how total and AR-related extreme precipitation is changing in a warming climate. [ABSTRACT FROM AUTHOR]

Changes in the amplitude of decadal climate variability over the twentieth century have been noted, with most evidence derived from tropical Pacific sea surface temperature records. However, the length, spatial coverage, and stability of most instrumental records are insufficient to robustly identify such nonstationarity, or resolve its global spatial structure. Here, it is found that the long-term, stable, observing platform provided by tide gauges reveals a dramatic increase in the amplitude and spatial coherence of decadal (11–14-yr period) coastal sea level (ζ) variability between 1960 and 2000. During this epoch, western North American ζ was approximately out of phase with ζ in Sydney, Australia, and led northeastern U.S. ζ by approximately 1–2 years. The amplitude and timing of changes in decadal ζ variability in these regions are consistent with changes in atmospheric variability. Specifically, central equatorial Pacific wind stress and Labrador Sea heat flux are highly coherent and exhibit contemporaneous, order-of-magnitude increases in decadal power. These statistical relationships have a mechanistic underpinning: Along the western North American coastline, equatorial winds are known to drive rapidly propagating ζ signals along equatorial and coastal waveguides, while a 1–2-yr lag between Labrador Sea heat fluxes and northeastern United States ζ is consistent with a remotely forced, buoyancy-driven, mechanism. Tide gauges thus provide strong independent support for an increase in interbasin coherence on decadal time scales over the second half of the twentieth century, with implications for both the interpretation and prediction of climate and sea level variability. Significance Statement: Decadal climate variability influences the frequency and severity of many natural hazards (e.g., drought), with considerable human and ecological impacts. Understanding observed changes and predicting future impacts relies upon an understanding of the physical processes and any changes in their variability and relationship over time. However, identifying such changes requires very long observational records. This paper leverages a large set of tide gauge records to show that decadal time scale coastal sea level variability increased dramatically in the second half of the twentieth century, in widely separated geographic locations. The increase was driven by a shift in the amplitude, spatial pattern, and interbasin coherence of atmospheric pressure, wind, and sea surface temperature variability. [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]

The northeastern Tibetan Plateau is located in a climatic junction, which is considered an ideal region to explore the interactions between the summer monsoons and the westerly circulation patterns. However, to date, the needed long-term precipitation-based isotopic dataset is too limited to predict the interactions and patterns. This paper presents an evaluation of hydrometeorological processes and climate dynamics in the northeastern Tibetan Plateau based on a 7-yr precipitation isotope dataset covering the summer monsoon periods from 2012 to 2018. Results illustrated remarkable seasonal isotopic variability, characterized by lower δ18O and δ2H values in June with an average of −10‰ and −66.7‰, respectively. Higher δ18O and δ2H values in July averaged −6.7‰ and −39.5‰, respectively. This clear isotopic variability is largely related to seasonal changes of moisture sources and hydrometeorological processes. These precipitation isotopic values were primarily determined by the amount of precipitation, relative humidity, and convective activity, but showed no correlation with air temperature. Backward trajectory model results showed that Xinjiang, northern China, the Arctic, central Asia, and the South China Sea (SCS) were the primary sources of precipitation for the study site with varying seasonal contributions. The maritime moisture source of the SCS primarily resulted in the lowest precipitation δ18O values during the prevailing summer monsoon, which is mainly as a result of the strong convective activity and rainout processes along the air trajectory. The higher average deuterium excess (d-excess) value of precipitation in September indicated continental sources from central Asia (e.g., 75.4%) as land vapor recycling increases d-excess concentration in the atmosphere. These findings provide further insights into the main factors of precipitation isotopic variability related to atmospheric processes along the trajectory and the relevant factors in the monsoon regions. Significance Statement: Recently, scientists and policy makers have become aware that Tibetan hydroclimate variability provides evidence of changes in regional and global circulation patterns that may result in the intensification of climate-driven extremes. However, these studies largely depend on crucial paleoclimate records of past precipitation isotopes in monsoon regions, which contain great uncertainties because of the complex relationship between climatic variability and precipitation isotopes. This study first presented a 7-yr isotopic dataset to understand the hydrological processes and climate dynamics controlling the isotopic variability in the northeastern Tibetan Plateau. The findings reveal important factors on the isotopic variability associated with atmospheric processes and their key climatic variables, which can enhance our interpretation of the paleoclimate records in monsoon regions. [ABSTRACT FROM AUTHOR]

This paper presents a statistical analysis of structural changes in the Central England temperature series, one of the longest surface temperature records available. A changepoint analysis is performed to detect abrupt changes, which can be regarded as a preliminary step before further analysis is conducted to identify the causes of the changes (e.g., artificial, human-induced, or natural variability). Regression models with structural breaks, including mean and trend shifts, are fitted to the series and compared via two commonly used multiple changepoint penalized likelihood criteria that balance model fit quality (as measured by likelihood) against parsimony considerations. Our changepoint model fits, with independent and short-memory errors, are also compared with a different class of models termed long-memory models that have been previously used by other authors to describe persistence features in temperature series. In the end, the optimal model is judged to be one containing a changepoint in the late 1980s, with a transition to an intensified warming regime. This timing and warming conclusion is consistent across changepoint models compared in this analysis. The variability of the series is not found to be significantly changing, and shift features are judged to be more plausible than either short- or long-memory autocorrelations. The final proposed model is one including trend shifts (both intercept and slope parameters) with independent errors. The analysis serves as a walk-through tutorial of different changepoint techniques, illustrating what can be statistically inferred. [ABSTRACT FROM AUTHOR]

This paper evaluates the ability of 35 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to simulate Arctic sea ice by comparing simulated results with observation from the aspects of spatial patterns and temporal variation. The simulation ability of each model is also quantified by the Taylor score and e score from these two aspects. Results show that biases between observed and simulated Arctic sea ice concentration (SIC) are mainly located in the East Greenland, Barents, and Bering Seas and the Sea of Okhotsk. The largest difference between the observed and simulated SIC spatial patterns occurs in September. Since the beginning of the twenty-first century, the ability of most models to simulate summer SIC spatial patterns has decreased. We also find that models with the Sea Ice Simulator (SIS) sea ice component in CMIP6 show a consistent larger positive simulation biases of SIC in the East Greenland and Barents Seas. In addition, for most models, the higher the model resolution is, the better the match between the simulated and observed spatial patterns of winter Arctic SIC is. Furthermore, this paper makes a detailed assessment for temporal variation of Arctic sea ice extent (SIE) with regard to climatological average, seasonal SIE, multiyear linear trend, and detrended standard deviation of SIE. The sensitivity of September Arctic SIE to a given change of Arctic surface air temperature over 1979–2014 in each model has also been investigated. Most models simulate a smaller loss of September Arctic SIE per degree of warming than is observed (1.37 × 106 km2 K−1). [ABSTRACT FROM AUTHOR]

This paper complements an earlier paper on the June-August Hadley cell by giving a detailed analysis of the December-February Hadley cell as seen in a 30-yr climatology of ERA-Interim data. The focus is on the dynamics of the upper branch of the Hadley cell. There are significant differences between the Hadley cells in the two solsticial seasons. These are particularly associated with the ITCZs staying north of the equator and with mean westerlies in the equatorial regions of the east Pacific and Atlantic in December-February. The latter enables westward-moving mixed Rossby--gravity waves to be slow moving in those regions and therefore respond strongly to upstream off-equatorial active convection. However, the main result is that in both seasons it is the regions and times of active convection that predominantly lead to upper-tropospheric outflows and structures that average to give the mean flow toward the winter pole, and the steady and transient fluxes of momentum and vorticity that balance the Coriolis terms. The response to active convection in preferred regions is shown by means of regressions on the data from the climatology and by synoptic examples from one season. Eddies with tropical origin are seen to be important in their own right and also in their interaction with higher-latitude systems. There is support for the relevance of a new conceptual model of the Hadley cell based on the sporadic nature of active tropical convection in time and space. [ABSTRACT FROM AUTHOR]

The early twentieth-century warming (ETCW), defined as occurring within the period 1921–50, saw a clear increase in actinometric observations in the Arctic. Nevertheless, information on radiation balance and its components at that time is still very limited in availability, and therefore large discrepancies exist among estimates of total solar irradiance forcing. To eliminate these uncertainties, all available solar radiation data for the Arctic need to be collected and processed. Better knowledge about incoming solar radiation (direct, diffuse, and global) should allow for more reliable estimation of the magnitude of total solar irradiance forcing, which can help, in turn, to more precisely and correctly explain the reasons for the ETCW in the Arctic. The paper summarizes our research into the availability of solar radiation data for the Arctic. An important part of this work is its detailed inventory of data series (including metadata) for the period before the mid-twentieth century. Based on the most reliable data series, general solar conditions in the Arctic during the ETCW are described. The character of solar radiation changes between the ETCW and present times, in particular after 2000, is also analyzed. Average annual global solar radiation in the Russian Arctic during the ETCW was slightly greater than in the period 1964–90 (by about 1–2 W·m−2) and was markedly greater than in the period 2001–19 (by about 16 W·m−2). Our results also reveal that in the period 1920–2019 three phases of solar radiation changes can be distinguished: a brightening phase (1921–50), a stabilization phase (1951–93), and a dimming phase (after 2000). [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]

Precipitable water vapor (PWV) with high precision and high temporal resolution can be obtained based on the global navigation and satellite positioning system (GNSS) technique, which is important for GNSS in disaster prevention and mitigation. However, related studies on drought monitoring using PWV have rarely been performed before, which becomes the focus of this paper. This paper proposes a novel drought monitoring method using GNSS-derived PWV and precipitation, and a multi-time-scale standardized precipitation conversion index (SPCI) is established. This index is different from the traditional index in terms of expression, standardization, and time scale. The proposed SPCI is then compared with the standardized precipitation index/standardized precipitation evapotranspiration index/self-calibrating Palmer drought severity index (SPI/SPEI/scPDSI) and applied to local and global drought monitoring. Validated results show that multi-time-scale SPCI has good consistency with the corresponding SPI/SPEI/scPDSI. The correlation between SPCI and SPEI is the strongest (more than 0.96) on a 12-month scale, which indicates the application potential of SPCI in drought monitoring. In addition, applications for regional (Queensland, Australia) and global drought/wet monitoring further verify the capability of the proposed SPCI. The average percentage deviations of drought/wet monitoring between SPCI and SPEI are 2.77% and 3.75%, respectively on a global scale. The above results show that the SPCI developed in this study is efficiently applied to global flood/wet studies. [ABSTRACT FROM AUTHOR]

The western North Pacific anomalous anticyclone (WNPAC) significantly affects East Asian climate. Previous studies have elucidated interannual variability of the WNPAC associated with El Niño, but decadal variability of the WNPAC remains unknown. The present paper investigates the dominant modes of decadal variability of the WNPAC by using observational data. The first decadal mode, characterized by an anomalous anticyclone centered over the western North Pacific, is associated with the Pacific decadal oscillation (PDO). The relationship between the first mode and the PDO shifted from in phase to out of phase around 1966. From 1900 to 1966 when the PDO and the first mode are in phase, the anticyclone is maintained by the effects of both the strengthened Aleutian low through meridional atmospheric forcing and Indian Ocean warming through enhanced zonal Walker circulation. From 1967 to 2012, the anticyclone is induced by cold SST anomalies over the central equatorial Pacific when the PDO and the first mode are out of phase. The second decadal mode is characterized by an anomalous anticyclone extending from southeastern China to the Philippine Sea and is associated with the Maritime Continent (MC). This anticyclone resides in the sinking branch of the local Hadley circulation, triggered by enhanced convection associated with the MC warming from 1900 to 2012. The finding of the decadal WNPAC in this paper may provide a new way to explain East Asian climate on a decadal time scale. [ABSTRACT FROM AUTHOR]