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From the beginning of the 21st century, the heat waves in Europe have become more frequent, severe and longer lasting, especially in the southern region. The longer duration of heat waves may be partly attributed to wave‐amplification, high‐amplitude waves in the mid‐latitudes, favouring the longer‐lasting blocking systems. The primary objective of the paper was to examine the long‐term changes of hot days and heat wave events and to identify the atmospheric circulation condition that prevails its occurrence. The other object was to investigate the correlations between hot days' occurrence in Poland and sea‐ice cover and sea surface temperature changes in the Arctic and its surroundings. Over the past few decades, Central and Southern Poland have experienced a considerable rise in maximum temperatures, which has led to an increase in the number of hot days. This increase is particularly prominent during the summer months (June, July and August) but also in May and September, which extends the hot season. Although heat waves have become more frequent and persistent since 2006, their mean intensity has remained unchanged. During all heat waves in Poland, the high‐pressure centre was located over the country or its close neighbourhood, mainly in the eastern sector but also in the south, southwest or over Scandinavia. The blocking systems were mainly related to the extended ridge of the Azores High, but also to strong blocking over the North Pole and Greenland reaching Scandinavia or anomalous high pressure in the East Arctic. The longest‐lasting heat waves were usually preceded by air masses advection from the Atlantic, but the highest potential temperature along the trajectories was observed for the southern direction of inflow. The growing number of hot days is statistically significantly related to the decreasing sea‐ice cover and increasing sea surface temperature in Arctic and Subarctic regions. [ABSTRACT FROM AUTHOR]

The observation facts of trend and variability are estimated for a century‐long timescale, as well as some possible attributions affecting temperature extremes over Beijing‐Tianjin‐Hebei region. In this paper, the new constructed daily maximum and minimum temperature series during the last 100 years in situ stations of Beijing, Tianjin and Baoding city are used, and two 30‐year baseline climatology of 1961–1990 and 1980–2010 are both used in calculating extreme temperature events. The results indicate that there are long‐lasting, frequent and serious extreme warming over Beijing‐Tianjin‐Hebei region, especially for extreme low temperature, with larger declining trends (at 5% significance) from 1981 to 2010 baseline than those from 1961 to 1990 baseline. And from a statistical perspective, El Niño decay years and surface sea temperature (SST) anomalies at some typical ocean regions of the Arabian Sea and the Bengal Bay on the northern Indian Ocean, the Western Pacific and the Mid Atlantic, Southern Indian Ocean and around 45°–85°E, 68°–82°N on the southwest Arctic Ocean can be used as the warning signals denoting extreme warming over Beijing‐Tianjin‐Hebei region. Additionally, urbanization has a significant (at 5% significance) effect on extreme warming over Beijing‐Tianjin‐Hebei region since 1979, with 24.3% warming contribution for annual minimum temperature. [ABSTRACT FROM AUTHOR]

The South China Sea summer monsoon (SCSSM) onset and withdrawal have critical impacts on the climate of East Asia. However, using different reanalysis data may lead to the uncertainty of the SCSSM. This study uses reanalysis datasets including JRA‐55, ERA5, NCEP‐NCAR NCEP‐1 and NCEP‐DOE NCEP‐2 to calculate onset and withdrawal dates and index of SCSSM from 1991 to 2020, analyses the uncertainty and figures out the possible reasons. Results reveal that the four reanalysis datasets have obvious uncertainty in calculating the withdrawal date of SCSSM, with the deviation being up to 3.4 pentads. Further analysis shows that large differences in thermal conditions and lead to the uncertainties. From the perspective of precipitation, Greater uncertainty exists in the relationship between monsoon retreat and September–October precipitation, NCEP1 and NCEP2 datasets show weak correlation in southern China and Indonesia. Moreover, the uncertainty can be also found in the correlations of SCSSM with global sea surface temperature (SST) anomalies. JRA‐55 and ERA5 show a strong correlation of with SST in several areas, and exhibit a distinct Pacific decadal oscillation (PDO) mode with monsoon onset, while NCEP‐1 and NCEP‐2 have a weaker correlation with SST anomalies than JRA‐55 or ERA5. Comparing multiple factors comprehensively, this paper concludes that JRA‐55 may be more representative in the monsoon study, followed by ERA data. In short, depending on the specific research questions, researchers can choose appropriate data sources to study the SCSSM based on the different aspects and the uncertainty also deserve our special attention when selecting the reanalysis datasets. [ABSTRACT FROM AUTHOR]

The amount of winter precipitation over southeast China (SCWP) is significantly affected by the El Niño–Southern Oscillation (ENSO), with generally an enhanced SCWP response to El Niño events. In this paper, we find that this relationship shows remarkable nonstationarities on the multidecadal timescale. Running ENSO–SCWP correlation maintains statistically significant before the mid‐1960s and after the mid‐1990s but not during the interim period, which exhibits an approximate synchronized temporal evolution with the Atlantic Multidecadal Oscillation (AMO). A statistical method for interpreting nonstationary relationships is then applied to quantitatively verify and measure this possible AMO modulation. It is demonstrated that the nonstationary ENSO–SCWP correlation can be expressed to a large extent by the influence of the AMO–ENSO nonlinear effect (AMO*Niño3.4) on the SCWP. This influence intensifies the ENSO–SCWP relationship during the positive AMO phase but weakens it during the negative AMO phase. Therefore, the nonstationarity in the ENSO–SCWP relationship comes predominantly from an AMO modulation via this key nonlinear effect. We further suggest that a positive AMO favours a westward shift of ENSO sea surface temperature (SST) anomaly pattern in the tropical Pacific. Correspondingly, the anomalous western North Pacific (WNP) anticyclone also migrates westward, which gives rise to pronounced moisture transports and vertical motions over the adjacent southeast China, thereby resulting in a significant ENSO–SCWP relationship. In contrast, during the negative AMO phase, the eastward‐shifted ENSO SST and WNP anticyclonic anomalies produce significant atmospheric anomalies primarily to the east of the Chinese mainland, thus having less effect on the SCWP. [ABSTRACT FROM AUTHOR]

Mitigating the impacts of droughts and floods over East Africa (EA) may largely be possible through accurate predictions of the long rains (March–May). Though the close interannual variability between the long rains, Indian and Pacific Oceans has been widely studied, Tanzania's long rain variability remains unclear. This paper examines the Tanzanian long rains dominant modes through an empirical orthogonal function (EOF) analysis, and their relationship with winter sea surface temperature (SST) for the period 1951–2018. Correlation and composite analyses were applied to explore the associated mechanisms. The first EOF (EOF1) mode is characterized by negative anomalies over Tanzania. The second EOF (EOF2) mode depicts positive (negative) anomalies over northern (southern) Tanzania. The third EOF (EOF3) mode reveals positive (negative) anomalies over eastern (western) Tanzania. EOF1 is closely related to the SST anomalies (SSTAs) in the southeastern Indian Ocean (SEIO). When the SSTAs are positive, they subsequently linked to upper (lower) level convergence (southeasterly winds) over Tanzania. Associated with this convergence entails a sinking motion, leading to a negative rainfall anomaly. The southeasterly winds indicate an early onset of the southeast monsoon, leading to normal rainfall been recorded. EOF2 is linked to the SSTAs in the central Pacific (CP). Positive SSTAs are related to reversed Walker circulation (WC) over northern Tanzania, while the upper‐level convergence was observed around southern Tanzania. This meridional dipole vertical motion pattern enhances (suppresses) rainfall anomalies. EOF3 is associated with mega El Niño–Southern Oscillation (ENSO)‐like SSTAs. The SSTAs are related to eastward shift of WC over the Indian Ocean, and zonal cell over the western Indian Ocean with rising limb is located east of Tanzania. The ascending motion enhances rainfall over eastern Tanzania. Predictions based on the SEIO, CP, and mega ENSO index may significantly support long rains prediction efforts and provide early warning. [ABSTRACT FROM AUTHOR]

This study investigates some of the uncertainties sources associated with the pseudo global warming (PGW) approach which was employed to project future patterns of tropical cyclones (TCs) over the Arabian Sea (AS). First, the climate variables controlling the patterns of tropical cyclones were extracted from reanalysis datasets of ERA5, ERAI, CFSR, and NCEP/NCAR. Then, each dataset was evaluated against long‐term measurements to identify the best‐performing reanalysis dataset. ERA5 showed the best performance for most of the variables. Outputs of 20 CMIP5 global climate models (GCMs) were then evaluated against the ERA5 data resulting in an ensemble of the best performing GCMs. A PGW framework was then used to project the changes in patterns of three significant historical cyclones: Gonu, Phet, and Ashobaa. In doing so, the signals of future climate variables were extracted from the GCMs ensemble to modify the initial and boundary conditions of the WRF model which was previously tuned for reproducing the historical TCs. Different tests were conducted to address the sources of uncertainty in the PGW approach, including the selection of the climate variables contributing to the computation of the signals, the selection of GCMs, and the spatial variation of signals. A considerable sensitivity of the projected track and intensity of TCs to the choice of GCMs was observed, acknowledging the importance of GCMs evaluation before calculating the signals. Moreover, it was found that among all variables, signals of sea surface temperature and air temperature have major effects on the cyclone's track and intensity. Apart from that, when the signals were applied to the domain of the WRF model uniformly, compared to applying spatially varying signals, different tracks and intensities for future TCs were also observed. Overall, the findings of this paper challenge the reliability of the projected changes in TCs patterns obtained from PGW. [ABSTRACT FROM AUTHOR]

This paper deals with the analysis of the relationship between CO2 emissions and temperatures. For this purpose, global CO2 emissions and four measures of global temperatures (land, land and ocean, northern and southern temperatures) are used. We used techniques based on fractional integration and cointegration. The results indicate first that the orders of integration differ in the two variables. Thus, while emissions are I(1) or I(d) with d higher than 1, temperatures display orders of integration strictly smaller than 1 and thus invalidating the hypothesis of cointegration between the two variables. Due to this, another approach is conducted where we suppose that the emissions are weakly exogenous in relation to the temperatures. The results using this approach show a significantly positive relationship between the two variables with a long memory pattern. [ABSTRACT FROM AUTHOR]

Based on the ERA5 reanalysis dataset, this paper examines the vertical variation of tropical cyclone (TC) size in the western North Pacific during 1998–2018. The TC size is defined as the distance from the TC centre to the radius at which the azimuthally averaged relative vorticity decreases to 1 × 10−5 s−1 (Rvor). It is found that TCs with similar sizes at the surface can be significantly different in size at higher levels. The Rvor at 10 m height (Rvor10) and that at 200 hPa (Rvor200) are related to TC intensity categories, and Rvor10 and that at 700 hPa (Rvor700) correlate linearly with the relative sea surface temperature (RSST) averaged within a 500‐km radius. Further, a positive correlation is found between the 500‐km radius averaged rain rate and Rvor200, while Rvor10, Rvor700 and Rvor200 all decrease with an increasing vertical wind shear (VWS). The spatial distributions of Rvor10, Rvor700, Rvor200 and Vmax, RSST, and rain rate are all similar to one another, and the spatial correlation coefficient between any pair of variations is larger than 0.91, which is statistically significant at the 0.01 level. The monthly variations of Rvor10, Rvor700 and Rvor200 are generally larger in the months with strong TC activity (May–October) than in the other months, although a peak of Rvor10 during March has been identified for the more recent few TCs. No significant interannual trend is found during 1998–2018 for any of the three variables (Rvor10, Rvor700 and Rvor200). Statistically significant correlations between the ENSO (El Niño–Southern Oscillation) index and Rvor10 and Rvor200 are 0.54 and 0.47, respectively, while no statistically significant correlation is found between the ENSO index and Rvor700. The mechanisms that affect the TC size at different heights are complicated and will be explored in later studies. [ABSTRACT FROM AUTHOR]

This paper examines the oceanic mean states associated with the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO) and their relations to the El Niño (EN). The mean states refer to the simultaneous occurrences of warm (W) and cold (C) phases of these oscillations: WAMO/CPDO, CAMO/WPDO and CAMO/CPDO. In general, the sea surface temperature (SST) anomaly patterns of the mean states show a combination of the PDO and AMO related anomaly patterns in the Pacific Ocean, and the strongest AMO‐related anomaly signals in the Atlantic Ocean with almost antisymmetric SST anomaly patterns in the northern and southern extratropical sectors of this Ocean. One of the most important results of this paper concerns the contrasting features between the CAMO/WPDO and the WAMO/CPDO mean states, which are noticeable for the SST, zonal circulation cell and precipitation during the austral autumn. Besides the opposite inter‐basin equatorial Atlantic/eastern equatorial Pacific cells, the CAMO/WPDO and WAMO/CPDO mean states also feature, respectively, a weakened and strengthened Walker cell in the tropical Pacific during the austral autumn. The results here indicate that the inter‐basin east–west cell between the equatorial Atlantic and eastern Pacific contributes to strengthen (weaken) the Walker cell during the austral autumn of the WAMO/CPDO (CAMO/WPDO) mean state. We also found that the mean states alter the EN features. The EN‐related largest positive SST anomalies occur in the central tropical Pacific during the WAMO/CPDO, and in the eastern tropical Pacific during the CAMO/WPDO. The Atlantic and Pacific oceanic mean states play an important role in modulating the EN features and their effects on the South American rainfall. The results presented in this paper might be relevant for climate monitoring and modelling studies. [ABSTRACT FROM AUTHOR]

There is a large discrepancy between studies on how the Indian Ocean Dipole (IOD) is defined. Indeed, the definition of historical events varies substantially, resulting in conflicting classifications, hampering hydroclimatic impact assessment of this phenomenon. Therefore, this paper aims to compare the various methods that have previously been adopted to define IOD events and demonstrate an alternative method that specifically captures different "flavours" of IOD. It is shown that the choice of sea surface temperature (SST) data set and climatological baseline has significant impact on the resulting classification of IOD events. Furthermore, not all events display the traditional dipole signature pattern of warming/cooling occurring at opposite poles. Rather, some events could be considered "pseudo dipoles," whereby the SST anomalies in the two poles are not of opposite sign. Importantly, the different types of IOD (i.e., "pseudo and true") are associated with varying impacts on rainfall for surrounding regions. To overcome these issues, this study treats Indian Ocean SST anomalies as a continuum of a finite maximum number of statistically distinguishable patterns using a neural network‐based cluster analysis. Ten individual SST patterns were identified with distinct rainfall teleconnections. In particular, four strong IOD patterns (two positive and two negative) were identified, alongside three pseudo dipoles representing anomalously warm conditions across the entire Indian Ocean Basin, with a SST gradient towards the east (i.e., a pseudo negative dipole) or west (i.e., a pseudo positive dipole). The occurrence of each of the 10 self‐organizing mapping (SOM) patterns is shown to be variable over the past 130 years, with some types more common during certain phases of the El Niño/Southern Oscillation or during the first (or second) half of the 20th century. The implications of these findings are particularly significant for attribution studies, development of proxy climate reconstructions, climate model evaluation and future climate change assessment. The Indian Ocean Dipole (IOD) is known to impact hydroclimate across many Indian Ocean rim counties. However, there is a growing body of research that confirms the IOD is a complex phenomenon with multiple variants, which cannot be captured by a simple index such as the dipole mode index (DMI). This paper uses a novel technique (SOM) to identify 10 individual flavours of the IOD with distinct rainfall teleconnections. Figure shows 10 different Indian Ocean SST "types" derived using SOM. Note that numbers in brackets show the number of occurrences of each type. [ABSTRACT FROM AUTHOR]

In recent years, numerous studies have investigated the relationship of extreme precipitation intensities with temperature derived from a binning method using present‐day weather data. The aim of this approach is that these dependencies, or so‐called apparent scaling rates, provide insights on how precipitation extremes could evolve in the future climate. In a recent paper, Bao et al. showed that there is a large discrepancy between the present‐day apparent scaling rates—showing a negative dependency of daily rainfall extremes on temperature for Darwin—and the climate change response showing a substantial increase in daily rainfall extremes. Their results provide compelling evidence that it may not be straightforward to predict the climate change response from the temperature scaling. We agree with this statement, but disagree with the physical explanation put forward in that study and think that moisture limitations are the most likely cause. Therefore, we advocate the use of dew point temperatures in scaling studies as a much more direct proxy of the absolute humidity of the air in which precipitation extremes develop, which we think is physically more consistent with the underlying mechanism causing the increase in precipitation extremes with global warming. [ABSTRACT FROM AUTHOR]

It is well‐documented that United States (US) wintertime temperature variability is related to teleconnection patterns that are commonly extracted using Empirical Orthogonal Function (EOF) analysis. However, recent work suggests that EOF patterns are not necessarily physical or strongly related to temperature variability at a specified location. In this paper, US wintertime temperature variability is understood using an alternative continuum approach to teleconnection patterns, contrasting with many previous studies that adopt an EOF‐based approach. Using the continuum approach, two patterns resembling the East Pacific‐North Pacific pattern are identified that are more strongly related to US wintertime temperature than common EOF‐based patterns. Using a simple correlation method and a teleconnection impact index, 13 teleconnection indices were ranked based on how much US wintertime temperature variability they can explain. The ranking methodologies revealed that three continuum‐based dipole patterns are the leading modes of US wintertime temperature variability and that common EOF‐based patterns like the Arctic Oscillation are relatively weak temperature influencers. It is also shown that the dipole patterns are related to a tropical sea surface temperature pattern termed the pan‐Niño (PN) pattern whose associated index was created using the continuum approach. The PN pattern was found to have moderate to strong relationships with the dipole patterns and US wintertime temperature, suggesting that tropical processes have contributed to recent wintertime temperature variability. These results have important implications for research focusing on seasonal forecasting, recent cooling trends across the eastern US, and the impact of Arctic warming on US winter weather. [ABSTRACT FROM AUTHOR]

This paper investigates the asymmetric response of the boreal winter Hadley cell (HC) to the meridional structures of the tropical sea surface temperature (SST) over the period 1979–2016. The variations in the zonal‐mean SST and HC are decomposed into equatorially symmetric (i.e. SES for SST, HES for HC) and equatorially anti‐symmetric (i.e. SEA for SST, HEA for HC) components. The response of the HEA to a given amplitude variation in SEA is stronger (by around three times) than that of the HES to the same amplitude variation in SES; this response ratio for the boreal winter is smaller than that for the annual mean. The variations in boreal winter HEA and HES are both related to the canonical El Niño, but in different regions; that is, the HEA is connected to the tropical Northwest Pacific SST, whereas the HES is linked to the SST over the tropical Eastern Pacific. During the period 1979–2016, warming of the tropical Northwest Pacific SST weakened the HEA and contributed to the decreased response ratio of the boreal winter HC to tropical SST. This point is further supported by examining the situation over the period 1958–2001, during which an interdecadal variation of tropical Northwest Pacific SST modulated the linkage between the boreal winter HC and SST. This observation shows that the warming of Northwest Pacific SST contributes to the decreased sensitivity of the boreal winter HC to SST, raising the possibility that global warming may affect the relationship between the HC and SST. Key Findings: The ratio of the Hadley circulation to different SST meridional structures is reduced during boreal winter. The result raises the possibility that the contribution of global warming in impacting the relationship between the Hadley circulation and SST. [ABSTRACT FROM AUTHOR]

In this paper, the physical processes underlying recent winter cold anomalies over East Asia (EA) are examined via statistical analysis. It is found that the EA cold anomaly depends on the warming in the North Atlantic, sea ice loss in the Barents–Kara Sea (BKS), and atmospheric teleconnection patterns. Specifically, the sea ice loss in the BKS can anchor teleconnection patterns originating from different North Atlantic sea surface temperature (SST) patterns. Different patterns of North Atlantic warming can affect the position of the cold anomaly region through altering the atmospheric circulations. In addition, whether the relevant teleconnection pattern leads to enhanced cold anomaly over EA crucially depends on the sea ice loss in the BKS, because it can anchor the blocking anticyclone embedded in the teleconnection pattern over the Ural region and make it more persistent and quasi‐stationary. Furthermore, it is found that the role of SST modes in the EA cold anomaly depends on their time scales. Although the strong basin‐scale warming (north–south SST tripolar mode) in the North Atlantic mid‐ to high‐latitudes plays a major role in decadal (interannual) cold anomaly over EA, it appears that the Atlantic east–west SST dipole structure dominates winter temperature variations over EA in recent decades on both the interannual and decadal time scales. [ABSTRACT FROM AUTHOR]

Two skilful 2‐month‐leading hybrid downscaling prediction schemes in October for winter surface air temperature (SAT) over China are proposed in this paper. The schemes are based on the year‐to‐year increment approach and the coupled climate patterns between the winter SAT over China and its predictors. Observed North Pacific sea surface temperature (SST) from the preceding July to September, Arctic sea ice concentration (SIC) in the preceding August and winter sea level pressure (SLP) over pan Eurasia from version 2 of the Climate Forecast System (CFSv2) are selected as the predictors based on the fundamental physics. Individual‐predictor schemes (IP‐schemes), that is, SLP‐scheme, SST‐scheme, SIC‐scheme, indicate that these predictors exhibit prediction skills in different regions. Multi‐predictor scheme I (MP‐schemeI) is developed by combining three predictors. However, MP‐schemeI shows limited skill in predicting SAT over Northeast China (NECTA), due to the limited skill of CFSv2 over the extratropics. Thus, MP‐schemeII is established, in which a hybrid downscaling model for NECTA is constructed. These two MP‐schemes have comparable prediction skill over China, but MP‐schemeII outperforms MP‐schemeI over NEC. The temporal (spatial) anomaly correlation coefficient (ACC) increases from 0.23 (0.15) in MP‐schemeI to 0.36 (0.21) in MP‐schemeII, and the ratio of the same sign of anomalous years (Anomalous‐RSS) improves from 39.1% to 56.5% over NEC. For the winter SAT over China, the MP‐schemes greatly enhance the prediction compared with CFSv2 outputs and the IP‐schemes. The temporal (spatial) ACC increases from 0.29 (0.05) in CFSv2 to 0.52 (0.29) in the MP‐schemes, and the station‐average root‐mean‐square error decreases by about 48.0% compared with CFSv2. Moreover, the RSS (Anomalous‐RSS) of the winter SAT over China is 55.9% (47.4%) in CFSv2 and 64.7% (63.2%) in the MP‐schemes. This indicates that the MP‐schemes perform better in predicting anomalous winters. [ABSTRACT FROM AUTHOR]

From the perspectives of remote sensing and climatic factors like surface meteorological parameters, large‐scale atmospheric circulations, and external forcing factors (EFFs), the authors synthesize and review spatiotemporal variations of PM2.5 over North China and how climate anomalies affect autumn and winter haze variability in North China according to recent studies. This review focuses on both interannual and interdecadal timescales. It is shown that circulations play an important role in influencing haze variability. Atmospheric circulations, which would be modulated by EFFs like sea surface temperature, sea ice, and snowpack, can affect the climate variability in haze over North China via modulation of surface‐layer parameters that are closely connected with the haze phenomenon. Therefore, EFFs are deemed significant factors impacting the climate variability of haze over North China, serving as paramount precursory signals for haze prediction. Furthermore, this paper suggests potential future research directions for haze variability studies in North China on the basis of summarizing and concluding the associated processes/mechanisms on how climatic factors affect haze variability, which could provide reference for treating and forecasting in situ hazy conditions. [ABSTRACT FROM AUTHOR]

Understanding the reliability of global climate models (GCMs) to reproduce the historical surface wind fields is integral part of building robust projections of surface wind‐climate, and other wind‐dependent geophysical climatic variables. Understanding the skill of atmosphere‐only models (AGCM), coupled atmosphere–ocean models (AOGCM) and fully coupled earth system models (ESM) is likewise paramount to assess any systematic model improvements. In this paper, we systematically assess whether surface wind fields obtained from 28 CMIP5 GCMs can represent large‐scale spatial patterns and temporal variability of historical surface winds. We show that inter‐model uncertainty is typically 2–4 times larger than the uncertainty associated with GCM internal variability, although the latter can be significant within specific regions. We also find that CMIP5 models are typically capable of reliably reproducing large‐scale spatial patterns of historical near‐surface winds, but considerable uncertainty lies within the CMIP5 ensemble with strong latitudinal dependence. CMIP5 models show limitations in their ability to reliably represent inter‐annual and inter‐seasonal variability particularly within tropical‐cyclone‐affected regions. In further analysis, we quantify and intercompare historical wind bias from different types of models with different dynamical cores, based on multiple CMIP5 diagnostic experiments. We find that bias in surface wind fields are largely intrinsic to the atmospheric components of the models, and that the inclusion of carbon‐cycle dynamics has insignificant effect on simulated surface winds (at decadal time‐scales). Inconsistencies between AGCM and AOGCM simulations are largely driven by errors in sea surface temperatures (SST); though such differences are not statistically significant relative to the inter‐model uncertainty within the CMIP5 ensemble. These results show that the dominant source of bias in simulated wind fields lies in the underlying physics of the atmospheric component of the models. [ABSTRACT FROM AUTHOR]

The present paper investigates the impact of El Niño‐Southern Oscillation (ENSO) on the Bay of Bengal tropical cyclone (TC) activity and associated alterations in environmental conditions during post‐monsoon (October–December) season for a period of 44 years (1972–2015). The analysis reveals that the post‐monsoon season TCs frequency, accumulated cyclone energy (ACE) and power dissipation index (PDI) values are negatively correlated with the Niño 3.4 sea surface temperature (SST) anomalies (significant at the 95% confidence level). La Niña years are characterized by more frequent and intense cyclonic events compared with El Niño years. The mean ACE and PDI values are approximately two times higher in La Niña than El Niño years. The mean number of TC days per year is also higher in La Niña (7.64 days) than El Niño (3.68 days) years (significant at 95% confidence level). In addition, a significant shift in genesis locations, tracks and landfalling locations of TCs has been observed under different ENSO phases. The mean genesis location of TCs have shifted eastward with tendency of more recurving tracks in La Niña than El Niño years. The presence of strong convective activity, reduced vertical wind shear, high SST (≥28°C), enhanced mid‐tropospheric relative humidity and low‐level cyclonic circulation aids the TCs formation and strengthening during La Niña and vice‐versa in El Niño conditions. [ABSTRACT FROM AUTHOR]

Climate change is the result of complex interactions between a wide array of climatic variables. Over a long period of time, climatic patterns can shift, possibly multiple times. Abrupt shifts that occur over a relatively short period of time are known as change points. During these intervals, different climatic variables may undergo dramatic shifts posing serious consequences for many biological and physical systems. In this paper, we discuss a Bayesian algorithm for detecting the location of change points in time series data. In particular, we utilize our method to analyse five different global surface temperature anomaly data sets, as well as temperature records associated with land, ocean, and different zonal bands in an attempt to identify common features of these data sets. Change points in the five global records were detected between 1902–1917, 1936–1945, and 1963–1976, but do these change points also manifest themselves across other parts of the globe? Our analysis indicates that the timing of change points is consistent from one record to the next, but not all change points appear in all records. In particular, there were more change points in the ocean than on land, and also more change points in southern latitudes than in northern latitudes. [ABSTRACT FROM AUTHOR]

The paper tests if the two La Niña (LN) types can be distinguished from each other using their climate impacts on northeastern Brazil (NEB). To this end, all LN events during the 1901–2010 period followed by a wet or dry rainy season (from February to April) in NEB are classified into two categories: WET‐LN and DRY‐LN. The global and regional anomalous atmospheric circulation patterns and the rainfall anomaly patterns in South America associated with the two cases are analysed. The WET‐LN and DRY‐LN events present, respectively, the eastern Pacific LN and central Pacific LN sea surface temperature (SST) anomaly features in the tropical Pacific. On the other hand, the WET‐LN features an interhemispheric SST dipole pattern in the tropical Atlantic, and the DRY‐LN, colder‐than‐normal surface waters in the tropical South Atlantic (TSA) and equatorial Atlantic during MAM(+1). The two analysed cases show regional differential circulation patterns in all seasons. The anomalous wetness over northern and northwestern South America occurs for the WET‐LN type during JJA(0)–DJF(+1) and for the DRY‐LN type, during DJF(+1)–MAM(+1). The anomalous dryness over SESA is more evident for the WET‐LN during JJA(0) and MAM(+1), and for the DRY‐LN, during SON(0). Anomalous dryness occurs in central and eastern South America noted during JJA(0) and DJF(+1) for both cases analysed. The precipitation anomalies in northern South America during DJF(+1) are stronger and more extensive for the DRY‐LN than for the WET‐LN events due to the action of both the anomalous (double) Walker and Hadley cells for the DRY‐LN, in contrast with the exclusive action of an anomalous Walker cell for the WET‐LN case. Also, a double Walker cell drives the dry–wet dipole between northern South America and NEB during MAM(+1) for the DRY‐LN. Our results might be useful mainly for climate monitoring purposes. The two La Niña (LN) types were distinguished from each other using their climate impacts on northeastern Brazil (NEB) and classified in two categories WET‐LN (LN events followed by a wet rainy season in NEB) and DRY‐LN (LN events followed by a dry rainy season in NEB) that present, respectively, the eastern Pacific LN and central Pacific LN sea surface temperature (SST) anomaly features in the tropical Pacific. The illustration shows the LN‐related SST and precipitation anomaly patterns evolutions associated with the two LN types. [ABSTRACT FROM AUTHOR]

Model‐based sensitivity experiments are a widely used method for studying climate change attributions. In traditional climate sensitivity studies, "climate drift" occurs because of the accumulation of model errors during long‐term integrations, both in "actual" and "hypothetical" states. A more accurate piecewise‐integration method is used to reduce the model errors, dividing the continuous simulation into a series of sequential short‐term simulations. The model fields are updated at the end of each subinterval with analysis data for the "actual" state run, and with the sum of the analysis data and the difference between "hypothetical" and "actual" states for the "hypothetical" state run. This paper conducts sensitivity experiments with the continuous‐integration method and the piecewise‐integration method to evaluate the impacts of the central and eastern Pacific Ocean sea surface temperature anomalies (SSTAs) on the severe drought that occurred in southwestern China (SWC) in the winter of 2009/2010. The results show the following. (a) Model errors produced by the piecewise‐integration method for the actual state simulation are significantly less than those produced by the continuous‐integration method. (b) The intensity of the drought is significantly overestimated in continuous‐integration experiments. However, the drought can be accurately simulated in its spatial distribution and intensity via the piecewise‐integration method. Thus, climate sensitivity to changes in external forcing can be studied with greater credibility. (c) The warm central Pacific Ocean SSTAs may be the main cause of the drought over SWC. Adequate precipitation occurred over SWC when the centre of the SSTAs shifted to the east. (d) Warm SSTAs over the central Pacific Ocean influenced precipitation over SWC by weakening the water vapour transport branch from South China Sea to SWC. With a deficit of water vapour, the pronounced subsidence and warm temperatures were the main dynamic and thermodynamic factors that caused and maintained the drought. Model‐based sensitivity experiment is a method of studying climate change attributions. In traditional climate sensitivity studies, "climate drift" occurs both in "actual" and "hypothetical" states. Therefore, the scientific value of climate sensitivity experiments is questioned. In this study, piecewise‐integration method (shown in the figure) is used to significantly reduce model errors caused by inaccuracies of analysis fields, to improve the accuracies of climate sensitivity simulations and to evaluate the impacts of the Pacific Ocean SSTAs on a drought. [ABSTRACT FROM AUTHOR]

This paper compares extreme value statistics of daily maximum 10 m wind speed in winter simulated by the regional climate model COSMO‐CLM at a horizontal resolution of 15 km (C15) with the reanalyses ERA‐Interim and Arctic System reanalysis (ASR version 1 and 2) and with a satellite data set (CCMPv2). Our C15 simulation (1979/1980–2015/2016, November–April) is thereby the longest high‐resolution simulation available for the Arctic. The results show that the extreme wind speeds tend to increase over the ocean with increasing the horizontal model resolution. A horizontal resolution of ≤15 km is required to sufficiently capture all extreme wind characteristics, in particular for the tip jets and barrier winds over the Irminger Sea and in the Denmark Strait, and for the low‐level jets in the Nares Strait. Of almost equal importance are physical parameterizations of surface fluxes and of turbulence. Capturing extreme wind characteristics has a direct effect on climate relevant air–ice–ocean interactions, such as triggering open‐ocean deep convection, polynya dynamics, or on the sea ice and freshwater balance of the Arctic. State‐of‐the‐art global climate models and reanalyses (e.g., ERA‐Interim) underestimate the extreme near‐surface wind speeds in the Arctic and around Greenland. Regional climate models, for example, ASR/WRF or COSMO‐CLM, resolve the mesoscale wind systems that frequently produce extreme winds, which we estimated i.a. as 10‐year return levels (see the figure). Capturing extreme wind characteristics has a direct effect on climate relevant air–ice–ocean interactions, such as triggering open‐ocean deep convection, polynya dynamics, or on the sea ice and freshwater balance of the Arctic. [ABSTRACT FROM AUTHOR]

ABSTRACT Sea surface temperature ( SST) is an important oceanic variable that impacts regional and global climate. This paper examines the relation of summer (June to August) surface air temperature ( SAT) variability over Saudi Arabia (1948-2013) with SST over the Atlantic, Pacific and Indian Oceans. The SAT over Saudi Arabia shows an abrupt increase around the 1980s (i.e. 1986). Partial correlations between SAT and different SST indices indicate that the Indo-Pacific warm pool ( IPWP) has a more significant effect on SAT than does the tropical North Atlantic ( TNA), tropical South Atlantic ( TSA) or Western Hemisphere warm pool ( WHWP). Hence, the change in IPWP SST can be considered as one of the factors linked to increase SAT over Saudi Arabia. The only significant relationship between El Niño and SAT is found in the Niño 4 region. Moreover, interactions between the tropical Atlantic meridional gradient mode and SAT are undetectable in the summer season, indicating that the TNA and TSA may have effectively independent roles on SAT over Saudi Arabia. The tropical Atlantic, through TNA and TSA, may influence the IPWP SST which modifies the strength of the Indian monsoon low, and in turn, has a strong influence on Saudi Arabia SAT variability. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper examines the distributions of anomalies of sea surface temperature ( SST) and of the moisture sources in the South Atlantic Ocean during extreme dry events in southeastern Brazil in the austral autumn, winter and spring for the period 1982-2009. The extreme dry events were identified based on a combination in which consecutive dry days and variable percentiles were considered in five homogeneous regions in terms of precipitation in southeastern Brazil, as defined through cluster analysis. Composites of anomalies of SST and moisture sources for the dry events selected for the different homogeneous regions show specific characteristics for each region, but some similarities were apparent for the southern and northern parts of southeast Brazil. During spring in all regions, and during autumn and winter in the southern regions, a tripole pattern of SST anomalies was found (negative, positive and negative), together with an anomalous anticyclonic circulation in the Atlantic Ocean transporting moisture to southern Brazil associated with positive SST anomalies. A decrease in the climatological moisture sources in the south of Brazil then ensues, and dry conditions prevail in the regions of interest. In winter and autumn in the northern regions, the same tripole pattern of SST anomalies was also found, but shifted northwards. An anomalous cyclone is associated with the negative SST anomalies, and the climatological moisture sources to the northeast of Brazil reduce their contribution to the region of interest, where negative precipitation anomalies are registered. It seems that the events selected show the results of reductions both in terms of the availability of moisture and in atmospheric instability. [ABSTRACT FROM AUTHOR]

Investigations into the role of anthropogenic emissions in the occurrence of extreme weather often use a method that compares simulations of atmospheric climate models run under a factual scenario of historical boundary conditions observed during the period of the event against simulations run under a counterfactual scenario of what those boundary conditions might naturally have been over that same period in the absence of anthropogenic emissions. A particular requirement for this experiment design is an accurate estimation of ocean surface boundary conditions for use by the counterfactual natural simulations. Here we use output from the CMIP5 multi‐climate‐model archive to develop a robust estimate of sea surface temperatures and sea ice conditions for use in counterfactual natural simulations, intended as a benchmark estimate to facilitate comparison across climate models and across studies. This development includes tests to ensure that the final estimate is stable from year‐to‐year and stable against other perturbations to the methodology, as well as consideration of the strengths and weaknesses in comparison to other available attributable warming estimates. While this estimate is tailored specifically for the International CLIVAR C20C+ Detection and Attribution Project, it can be used by related projects as well. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper examines the impact of the wintertime Arctic Oscillation ( AO) on the following November circulation. The application of a set of statistical methods shows that a response of November sea level pressure ( SLP) to the preceding wintertime AO operates on a hemispheric scale. At high and middle latitudes, this response is a well-pronounced seesaw in SLP between the Eastern and Western Hemispheres. Winters of the positive AO polarity tend to be followed by positive SLP anomalies spanning the whole Northern Eurasia and negative SLP anomalies extending from the Bering Sea through the Western North Atlantic. Opposite SLP anomalies prevail after winters of the negative AO polarity. The response of November SLP to the preceding wintertime AO closely resembles the first empirical orthogonal function of November SLP. That is, the polarity of the wintertime AO precedes the polarity of the leading mode of variability of November SLP over the Northern Hemisphere. The wintertime AO exerts a 9-month lag impact on November circulation due to the re-emergence of a sea surface temperature anomaly over the western North Atlantic. [ABSTRACT FROM AUTHOR]

ABSTRACT The objective of this paper is to understand the response of upper tropospheric ( UT) clouds and water vapour ( H2O) to sea surface temperature ( SST) changes over the Indian Ocean. UT ice water content ( IWC) and H2O observed by Aura Microwave Limb Sounder (MLS) show dominant dipole mode variability over the Indian Ocean. This is characterized by the oscillating differences between the western and eastern Indian Ocean ( WIO and EIO) with greater amplitude in September, October and November ( SON) as compared with other seasons. We denote δX = X_WIO − X_EIO, with X being H2O and IWC at three UT levels ( 215, 147 and 100 hPa) or SST, following the documented definition for Indian Ocean Dipole ( IOD). We find a strong positive correlation between δIWC at the three UT levels and δSST, and a relatively weak positive correlation between δIWC and Niño 3.4 SST, suggesting that the UT clouds over the Indian Ocean are largely controlled by the local thermally driven circulation, while teleconnection to El Niño and Southern Oscillation (ENSO) plays a secondary role. The change per degree of δSST for δIWC in SON is 5.5 mg m−3 C−1 at 215 hPa, 1.6 mg m−3 C−1 at 147 hPa and 0.13 mg m−3 C−1 at 100 hPa (i.e. 96% C−1, 87% C−1 and 46% C−1 increase at 215, 147 and 100 hPa, respectively). We find 36% C−1 increase in δH2O at 215 hPa with increasing δSST, associated with a sharp contrast in convective strength (indicated by δIWC) over the Indian Ocean region. On the other hand, δH2O at 100 hPa decreases with increasing δSST because cold temperature is observed above convective clouds and 100 hPa H2O is largely controlled by temperature. The Niño 3.4 SST has a relatively weak positive (negative) correlation with δH2O at 215 hPa ( 100 hPa). [ABSTRACT FROM AUTHOR]

A wet‐to‐dry shift in summer over the Sichuan Basin (SCB) during the late 20th century was noticed by previous studies. However, this study found that summer precipitation over SCB significantly increases during the past two decades, with an abrupt change point around 2011/2012. An anomalous cyclone over Lake Baikal, accompanied by an anticyclone over southern China, is responsible for the increase in SCB precipitation by inducing anomalous upper‐level divergence, mid‐level ascending motion and moisture convergence. Such atmospheric circulation anomalies are closely associated with the sea surface temperature (SST) warming over the Barents–Kara Sea (BKS). Observational analyses and model experiments indicate that the SST warming over the BKS warms local atmosphere and weakens meridional air temperature gradients over northern Asia and induces local anomalous easterlies, which further induce the anomalous cyclone over Lake Baikal that favours SCB precipitation. Additionally, the inhomogeneous warming over Europe increases local meridional air temperature gradients, enhances atmospheric baroclinicity and intensifies local transient eddy activities over central Europe. The intensified transient eddy activities generate negative geopotential height tendency anomalies over northern Europe, which can further excite a Rossby wave train that directly influences SCB precipitation, and can warm the atmosphere above the Kara Sea that indirectly influences SCB precipitation. This study can deepen our understanding of the interdecadal variability of summer precipitation over the SCB. [ABSTRACT FROM AUTHOR]

Several studies have demonstrated the influence of sea surface temperature (SST) in the Indian Ocean on the interannual variability of the Tanzanian long rains (TLR). A new investigation into the south‐central tropical Indian Ocean (SCTIO) SST–TLR relationship has been undertaken, focusing on the modulating role played by the Interdecadal Pacific Oscillation (IPO). The relationship experienced interdecadal change during the early 1990s and was strong (weak) during the 1950–1990 (1991–2010) period. Further diagnosis revealed that the interdecadal change is closely associated with changes in atmospheric circulation anomalies induced by the SCTIO SST anomalies (SSTAs). Prior to the early 1990s, warm SCTIO SST induced anomalous upper‐level cyclone and easterlies over Tanzania, which led to evidence of abnormal subsidence over this region. These were accompanied by an early onset of the Southeast Asia monsoon (SAM) to promote dryness in Tanzania. Easterlies, cyclones and SAMs ceased to exist after the early 1990s. The SCTIO SSTA alone does not induce distinct atmospheric circulation anomalies linked to the TLR variation. It was found that IPO is a crucial factor modulating the nonstationary SCTIO SST–TLR relationship. Prior to the early 1990s, IPO‐related SSTA induced anomalous descending motion through the atmospheric bridge, resulting in northeasterly (easterly) over the north Indian (eastern Indian) Ocean. These anomalies also affect the mixed‐layer depth (latent heat flux), which in turn alters the SST, warming the whole Indian Ocean basin. In this case, the SCTIO SSTA exerts significant influence on the TLR, independent of the IPO. After the early 1990s, sea surface height anomalies from the Pacific propagate through the oceanic pathway to the SCTIO, which in turn modifies SSTs. During the 1991–2010 period, a weaker SCTIO SST–TLR association correlated with a stronger SCTIO SST–IPO relationship. We suggest that the IPO may act as a crucial modulator for the SCTIO SST–TLR relationship. [ABSTRACT FROM AUTHOR]

Heat waves (HWs) are atmospheric events of synoptic and global scale that negatively impact productive sectors and the population. This study aims to investigate HWs in the São Paulo (SP) State, Brazil, and describe their intensity, duration, spatial coverage and atmospheric characteristics. HWs were identified using observed data from 65 weather stations for the period 2000–2020. The NCEP‐DOE Reanalysis was used to determine synoptic and global scale circulation characteristics. The results showed that SP experiences different effects of thermal stress on maximum temperatures (Tmax), with the north and northwest sectors reaching the highest average values (38°C). The average temperature of HWs in the state was 34.9°C, with an average duration of 5.3 days and 92% of events taking place between 2010 and 2020. A greater number of events occurred in 2015, 2016 and 2019, mainly in the austral summer and spring. The following atmospheric characteristics were found to be associated with HWs in SP: an anomalous semistationary anticyclonic circulation at 500 hPa over the hinterland regions of Brazil, a thermal low at 1000 hPa over Paraguay, a Rossby wave train originating in the South Pacific Ocean and spreading to centre‐south Brazil, a positive sea surface temperature anomaly in the South Atlantic Ocean near the coast of Brazil and another over the South Pacific, and a negative pattern circling Antarctica. Apparently, there is a certain degree of coupling between sea surface temperature anomalies and the Rossby train, the former being the trigger of the event. [ABSTRACT FROM AUTHOR]

Extreme events contribute significantly to rainfall variability in semi‐arid regions like South Africa. Here, following the definition of a novel typology of rainfall extremes, disentangling large‐ and small‐scale events in Part I, we use quality‐controlled observational databases in South Africa, the ERA5 reanalysis and satellite estimates TRMM‐3B42 to examine the relationship between these two types of rainfall extremes and different modes of climate variability at various timescales. At low frequencies, rainfall extremes are assessed at interannual (IV: 2–8 years) and quasi‐decadal (QDV: 8–13 years) timescales, which are primarily associated with the El Niño–Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO), respectively. At subseasonal timescales, the typology of rainfall extremes is analysed depending on the synoptic configurations, as inferred by seven convective regimes including tropical temperate troughs (TTTs: 3–7 days), and the intraseasonal variability associated with the Madden–Julien Oscillation (MJO: 30–60 days). At the IV timescale, the occurrence of large‐scale extremes is substantially higher during its wet phases thereby suggesting a 400% rise in the occurrence of large‐scale extremes as compared to its dry phases. At the QDV timescale, variability mostly relates to the modulation of small‐scale extremes during its wet phases. Teleconnections with global sea surface temperature (SST) confirm that La Niña conditions favour overall wet conditions and extremes in South Africa. The numbers of large‐scale extremes are consistently related to warmer SSTs in the North Atlantic, while their link with warmer Indian and tropical South Atlantic oceans is found to be statistically independent of the state of ENSO. At the subseasonal timescales, large‐scale extremes largely occur during three out of the seven convective regimes identified in the southern African region whereas small‐scale extremes are nearly equiprobable during all convective regimes. The occurrence of large‐scale extremes during continent‐rooted TTT is further enhanced during the locally wet phases of the MJO and is symmetrically weakened during its dry phases. [ABSTRACT FROM AUTHOR]

Mesoscale eddies are the important phenomenon of world oceans that play a prominent role in influencing the near‐surface atmosphere and transport of heat. Ocean and atmosphere responses due to the presence of oceanic mesoscale eddies are not well studied in the Northern Indian Ocean (NIO) region. The present study analysed the ocean and atmospheric response due to the presence of mesoscale eddies using a composite analysis. Generally, it is assumed that the anti‐cyclonic eddies are associated with the positive anomalies of sea surface temperature (SST), and cyclonic eddies are accompanied by negative anomalies. However, for the two marginal seas in the NIO, that is, the Bay of Bengal (BoB) and Arabian Sea (AS), the composite picture of SST anomalies associated with mesoscale eddies showed an abnormal response of SST. This unusual behaviour of cold SST near anti‐cyclonic eddies and warm SST near cyclonic eddies in BoB and AS is analysed with the mean composites of precipitation, outgoing longwave radiation (OLR), and turbulent fluxes. The mean composites over all anti‐cyclonic eddies reveal the presence of enhanced precipitation and convection (low OLR), whereas over cyclonic eddies, suppressed convection and negative precipitation anomalies are evident. The composites of latent heat flux (LHF), precipitation and OLR near surface cold anti‐cyclonic eddies indicate the loss of heat from the ocean to the atmosphere, intense precipitation along with cloudy conditions are responsible for the cooling of the ocean. Along with this, stronger winds are also evident during cloudy conditions could play a role in anomalous cooling of SST observed near anti‐cyclonic through intense surface mixing. Similarly, vice versa is observed near the surface warm cyclonic eddies. The overlying atmosphere and abnormal response of SST near oceanic eddies are essential for understanding the significant role of oceanic mesoscale eddies in influencing the large‐scale circulation of the atmosphere and climate. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate is a primary driver for extreme rainfall and flood events. In this paper, the temporally changing flood risk associated with the annual maximum 30-day rainfall (30-day AMR) and the annual maximum daily inflow ( AMDI) related to the Xidayang Reservoir catchment is analysed from a climatic context. This is the largest catchment in Daqing River Basin in North China and is highly prone to floods related to the East Asian summer monsoon. Two climate factors, the average May-June-July sea surface temperature anomalies in areas of the northern Indian Ocean and western Pacific Ocean, are identified. They show a high negative correlation with the AMDI and 30-day AMR. Bayesian nonstationary models are then developed for the AMDI and 30-day AMR using the climate predictors identified as covariates. We compared three types of models of AMDI and 30-day AMR: (1) time-invariant, (2) linear temporal trend and (3) climate informed, and found that the climate-informed models exhibit the best performance according to Deviance Information Criterion (DIC) and 90th percentile Bayesian coverage rate for both AMDI and 30-day AMR. A significant decreasing trend is identified in the AMDI and the 30-day AMR, which is found to be associated with the climate predictors. Leave one out cross validation (LOOCV) is used to demonstrate that these models have decent skill in predicting year-to-year variability in flood risk. This can help to provide flood/rainfall dynamic management measures for reservoirs in Daqing River Basin using information from before the beginning of monsoon season, thus facilitating adaptation to a changing climate. [ABSTRACT FROM AUTHOR]

The Madden–Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability, which serves as a primary source of subseasonal‐to‐seasonal (S2S) predictability. Noticeably, MJO is not always a regularly recurring cycle but is characterized by discrete episodes. In this study, considering the quasi‐consecutive actives and eastward propagating features, a standard metric is proposed to identify MJO events based on the real‐time multivariate MJO (RMM) index. The re‐identification of historical MJO events reveals that there were 5.4 MJO events each year since 1981, and the average duration of each event is about 31.5 days. More MJO events tend to occur in the boreal winter and spring, with stronger intensity, longer duration and faster propagating speed than those in the boreal summer. Furthermore, MJO events are more likely to initiate in Phases 2 and 5, with a longer lifetime than those initiating in other phases. The amplitude and propagation characteristics of MJO events are strongly modulated by the dominant modes of sea surface temperature interannual variability with a strong regional dependence. Based on hindcast datasets of six S2S models, the prediction skill for the MJO is evaluated in the perspective of individual events. The longest leading time of the skilful prediction for individual MJO events ranges from 11 to 17 days, far below the traditional recognition. This result could be attributed to the apparent prediction barrier of MJO initiation, that is, a rapid decrease in prediction skill when predictions are carried out before the initiation of MJO events. In addition, the prediction skills of MJO events depends on interannual variabilities, with relatively higher skills under the conditions of the El Niño and Indian Ocean basin warming. These findings may shed light on the complexity and challenges of profoundly understanding and skilfully predicting MJO events. [ABSTRACT FROM AUTHOR]

Seasonal rainfall forecasts provide information several months ahead to support decision making. These forecasts may use dynamic, statistical, or hybrid approaches, but their comparative value is not well understood over Central America. This study conducts a regional evaluation of seasonal rainfall forecasts focusing on two of the leading dynamic climate ensembles: the Copernicus Climate Change Service seasonal forecasting system (C3S) and the North American Multimodel Ensemble (NMME). We compare the multimodel ensemble mean and individual model predictions of seasonal rainfall over key wet season periods in Central America to better understand their relative forecast skill at the seasonal scale. Three types of rainfall forecasts are compared: direct dynamic rainfall predictions from the C3S and NMME ensembles, a statistical approach using the lagged observed sea surface temperature (SST), and an indirect hybrid approach, driving a statistical model with dynamic ensemble SST predictions. Results show that C3S and NMME exhibit similar regional variability with strong performance in the northern Pacific part of Central America and weaker skill primarily in eastern Nicaragua. In the northern Pacific part of the region, the models have high skill across the wet season. Indirect forecasts can outperform the direct rainfall forecasts in specific cases where the direct forecasts have lower predictive power (e.g., eastern Nicaragua during the early wet season). The indirect skill generally reflects the strength of SST associations with rainfall. The indirect forecasts based on Tropical North Atlantic SSTs are best in the early wet season and the indirect forecasts based on Niño3.4 SSTs are best in the late wet season when each SST zone has a stronger association with rainfall. Statistical predictions are competitive with the indirect and direct forecasts in multiple cases, especially in the late wet season, demonstrating how a variety of forecasting approaches can enhance seasonal forecasting. [ABSTRACT FROM AUTHOR]

Summer precipitation in the Meiyu region of China arises from the synergy of multiple factors such as the East Asian summer monsoon (EASM), Western Pacific subtropical high (WPSH), the sea surface temperature (SST), etc. Based on an analysis of the key influencing factors of summer precipitation in the Meiyu region of China from 1961 to 2019, we selected five key factors: the EASM index (EXSMI), Western Pacific subtropical high area index and ridge line index (WPSH‐AI and WPSH‐RLI), Westerly Index (WI), and NAO index. These five indexes were then used to construct a multi‐factor synergy index (MFSI) by the weighted least‐square method. The results show that the MFSI was able to describe the characteristics of EASMI, WPSH, NAO, and the westerly circulation. It showed a good correlation with the temporal and spatial distribution of summer precipitation in the Meiyu region. In the strong (weak) MFSI years, the NAO index was low (high), the North Atlantic region presented a "+ − +" ("− + −") three‐pole structure from south to north, the WI was low (high), the Siberian high pressure was weak (strong), the middle and high latitude Eurasia Mainland upper trough and ridge meridional decreased (increased). On the contrary, the precipitation increased (reduced). This index has a good indication of summer precipitation in the Meiyu region, which has important scientific significance and practical value for the prediction and prediction of precipitation in the Meiyu region of China. [ABSTRACT FROM AUTHOR]

The Pacific‐Japan (PJ) pattern is the dominant teleconnection over East Asia, closely related to the summer precipitation on various time scales. However, studies on the connection between the interdecadal variations of the PJ pattern and sea surface temperature (SST) forcing are still limited. This study indicates that the relationship between the PJ pattern and ENSO presents a pronounced interdecadal change around 1997/1998. The PJ pattern shows a baroclinic structure over the northwest Pacific and a barotropic structure near Japan during 1979–1997, while its baroclinic structure in the tropics weakens remarkably during 1998–2021, with a southward shift of its midlatitude barotropic structure. As a result, the connection between the PJ pattern and summer precipitation over East Asia exhibits an interdecadal transition in the late 1990s. In the slow La Niña decaying summer of 1979–1997, the cold SST anomalies in the tropical Indian Ocean (TIO) excite an eastward‐propagating Kelvin wave that enhances convection over the northwest Pacific, resulting in the formation of the PJ pattern. In contrast, the cold SST anomalies in the Maritime Continent rather than the TIO yield a zonally confined Kelvin wave in the rapid La Niña decaying summer of 1998–2021. The elongated Kelvin wave penetrating the central Pacific weakens convective anomalies over the northwest Pacific, thereby weakening the baroclinic structure of the PJ pattern in the tropics. Meanwhile, the warm SST anomalies in the Kuroshio Extension (KE) induce a northward shift of the East Asian subtropical westerly jet, with the anomalous anticyclonic circulation over the KE significantly affecting summer precipitation along the Meiyu belt. Therefore, the midlatitude barotropic structure of the PJ pattern shifts southward after the late 1990s. [ABSTRACT FROM AUTHOR]

The north China July precipitation (NCJP) accounts for the largest proportion of annual total precipitation in north China and displays a significant decadal variability of a cycle about 20‐year at least from the past 40 years. There is a significant negative correlation between the July northern North Atlantic sea surface temperature (NNASST) and NCJP on decadal scale. When the detrended July NNASST anomaly is in negative phase, the NCJP anomaly is in positive phase, and vice versa. We present the coupled oceanic–atmospheric bridge (COAB) mechanism of the July NNASST influences on NCJP decadal variability via the Eurasian decadal teleconnection (EAT) pattern: the NNASST stimulates the EAT pattern which regulates circulation anomalies in north China and its surrounding regions, and finally regulates precipitation anomalies in north China by influencing the local water vapour transport. In addition, a preliminary analysis about the causes of the super‐abnormal NCJP in 2021 indicates that the super‐abnormal NCJP in 2021 is not just the decadal role of the NNASST on NCJP, may be the combined influence of the WPSH in the northeastern of north China, the abnormal high pressure in the northwest and the low‐pressure cyclone in the south in the rainy decadal background. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper analyses the influence of different types of El Niño-Southern Oscillation ( ENSO) events on South American precipitation under a climate change scenario. We use two sub-selections of Coupled Model Intercomparison Project Phase 5 (CMIP5) models that have a good representation of teleconnections to the region, albeit with reduced magnitude anomalies. Comparing historical simulations and the RCP 8.5 scenario experiments, after removing the trend in the mean due climate change, the sub-ensemble means show similar global sea surface temperature anomalies and South American precipitation anomaly patterns in the future. No robust changes in the pattern or magnitude of precipitation anomalies are found, despite significant ENSO-related shifts in the Pacific basin, as highlighted in other studies. However, if the models are analysed individually, some show relatively strong changes in ENSO-related precipitation anomalies for both canonical and Modoki events. We show that, in individual models, tropical teleconnection changes associated with ENSO are primarily driven by changes in the magnitude of ENSO-related circulation but with no agreement on the sign. Increases in background moisture, which have been hypothesized to drive an intensification of ENSO-related precipitation anomalies, are of secondary importance. [ABSTRACT FROM AUTHOR]

Convective sea‐effect snowfall, in the form of snowbands, is observed over the northern Baltic Sea annually. Quasi‐stationary snowbands may last up to several days over the sea and, depending on the wind direction, move towards the coast. This study provides climatology of spatial and temporal occurrence of snowbands in Finland for a 48‐year period (1973–2020). We used a set of detection criteria together with ERA5 reanalysis at off‐shore areas and FMIClimGrid gridded observational data for on‐shore areas to find the days favouring snowband formation. Only those snowband days (SBD) when snow reached the Finnish coastal mainland were considered. The total annual number of SBDs in Finland varied from 6 to 40 with an average of 16. SBDs were detected most frequently over the Gulf of Bothnia near the western coast of the country. The largest increase in snow depth (SDI) during an SBD (67 cm/day) also took place on the western coast, although the long‐term mean of SDI (3–5 cm/day) was highest over the southern coast. Throughout the country, November and December showed the highest frequency of SBDs. However, between the periods 1973–1996 and 1997–2020, the seasonal cycle of SBDs shifted 1 month forward from late autumn to mid‐winter as the decrease in the number of SBDs during December as well as the increase during January and February were statistically significant in Finland. In northern Baltic Sea, long‐term increases in monthly means of sea surface temperature (SST) and air temperature at the atmospheric level of 850 hPa (T850) were in line with the decadal changes in the occurrence of SBDs. The increasing trend in SST favours the formation of snowbands but in late autumn the probability for snowband formation decreased because even larger increases in T850 resulted in diminishing differences between SST and T850. [ABSTRACT FROM AUTHOR]

Air pollution of fine particulate matter (PM2.5) is severe in winter and causes vast premature deaths in north China. Many previous studies have concerned winter‐mean haze conditions and identified some useful climate factors. However, obvious differences in the number of haze days also existed between December and January (HDJ‐D) that lacked of understandings. The HDJ‐D maximum was 6.6 days, which occurred between December 2005 and January 2006, accounting for more than 45% of the monthly mean number of haze days in these 2 months. Differences of large‐scale atmospheric circulations were distributed like a Rossby wave pattern in mid‐troposphere, with centres in the west of Europe (+), the north to the Caspian Sea (−) and north China (+). Associated meteorological conditions in north China resulted in more adverse ventilation conditions and stronger chemical productions, and thus larger number of haze days in January than in December. In addition, significant relationships between HDJ‐D and three preceding climate factors during 1979–2018 were also revealed, including August–September–October sea ice over the Laptev Sea and the north of the Kara Sea (correlation coefficient = −0.53), November snow depth in eastern Europe and western Siberia (correlation coefficient = −0.44) and sea surface temperature over the Mid‐Atlantic Ridge (correlation coefficient = −0.48). Abundant analyses, basing on the observation data, large‐ensemble climate simulations and atmospheric chemical simulations, all reproduced the influences of each climate factor on large‐scale atmospheric circulations and local meteorological conditions associated with HDJ‐D changes. [ABSTRACT FROM AUTHOR]

A careful isolation of the externally forced component (EFC) and the internal climate variability (ICV) embedded in the observed records as well as the climate simulations is critical to investigate an actual response to the external radiative forcing and/or background dynamics in the ICV. Employing three different methods, we evaluate the EFCs contained in the observed sea surface temperature (SST) and sea level pressure (SLP) fields in the Indo‐Pacific region. After removing these EFCs, we obtain the respective ICVs as the remaining anomalies. The remaining SST and SLP anomalies are then evaluated on decadal time scales in a combined empirical orthogonal function (EOF) analysis of different spatial portions: the tropical Pacific, the Indian Ocean and the whole Indo‐Pacific region. After making statistical intercomparisons of the spatial patterns and associated time series of the EOF analyses, we found that the EFCs of the individual grid point values (GPVs) were appropriately estimated by regressing onto the multi‐model ensemble global mean surface temperature (GMSTMME) and were less well approximated by the conventional linear trend and the multi‐model ensemble mean of the simulated GPVs. The regressed SST anomalies of the individual historical simulations onto the GMSTMME were much larger than the observed anomalies, illustrating that the ICV‐to‐EFC variance ratio is a performance‐improvement indicator of climate models. [ABSTRACT FROM AUTHOR]

Based on the daily minimum temperature data from 199 meteorological stations in northeast China (NEC), the cold wave (CW) processes in winter from 1980 to 2020 are identified. Then, by using the reanalysis 500‐hPa geopotential height data provided by the European Centre for Medium‐Range Weather Forecasts (ECMWF), the CWs are objectively classified into two types (abbreviated as Type 1 and Type 2) according to the corresponding atmospheric circulation through the hierarchical cluster algorithm (HCA). The relationships of the CWs with the Arctic sea sic (SIC) and sea surface temperature (SST) are revealed. For Type 1, the SIC in the north of the Barents Sea–Kara Sea is relatively less in the previous autumn, and a wave train propagating from the polar regions to Northeast Asia is stimulated under the ice–atmosphere interaction. This wave train further cooperates with the positive SST anomaly in the southern Indian Ocean to excite the low‐vortex circulation under the negative phase of Arctic Oscillation (AO) in winter, which is conducive to the occurrence of Type 1. However, the relatively low SST in the western Pacific warm pool in previous autumn stimulates a northward propagating wave train along the meridian, which increases the degree of meridionality of the atmospheric circulation over East Asia and thus indirectly causes the polar‐vortex‐splitting circulation under the positive AO phase, which favours the formation of Type 2. The numerical simulations can well reproduce the observational facts, further confirming the possible impact of the SIC and SST in the previous autumn on the two types of CW over the NEC. [ABSTRACT FROM AUTHOR]

The western Pacific subtropical high (WPSH) substantially affects the climate in the Pacific and East Asia. Previous studies have revealed that the springtime Indo‐Pacific warm pool (IPWP) sea surface temperature zonal gradient (SSTG) could be used as a predictor of the subsequent summertime WPSH's intensity. Here, we find that the interannual variability of the springtime IPWP SSTG has greatly decreased after the late 1990s, accompanied by the weakened relationship between the springtime IPWP SSTG and the following summertime WPSH, which may reduce the efficiency of the springtime IPWP SSTG as a key predictor for the summertime WPSH in recent decades. This observed recent weakening IPWP SSTG–WPSH relationship could be largely contributed by the decadal shift of the El Niño–Southern Oscillation (ENSO) and the WPSH around the late 1990s. The ENSO regime shift from the eastern Pacific (EP) type to the central Pacific (CP) type could alter the spatial pattern of the springtime IPWP sea surface temperature (SST) dipole and further weaken the local air–sea interaction between the underlying IPWP SST and the WPSH. From another perspective of the WPSH decadal shift, the WPSH‐related first leading mode before (after) the late 1990s, characterized by a large‐scale uniform (dipole) pattern with an oscillating period of ~4–5 year (~2–3 year), tended to promote a stronger (weaker) linkage with the springtime IPWP SSTG. In addition, the recent enhancement of the tropical Atlantic SST influences is considered to possibly promote the decadal shifts of the ENSO and the WPSH‐related leading mode. After the springtime tropical Atlantic SST was added as a predictor, the predicting skills of the empirical equation for the summertime WPSH could be substantially improved. The results herein have important implications for the further improvement of the seasonal WPSH prediction, which is of great practical significance in the prevention and mitigation of climate disasters. [ABSTRACT FROM AUTHOR]

Year‐to‐year variations of southern Thailand rainfall (STR) in boreal winter exert profound social and economic impacts, whereas current multimodel ensemble prediction systems have low skills to predict the STR. This study proposes a physical‐based seasonal prediction model for the winter STR 1 month in advance using the outputs from the dynamic models. The prediction model is constructed using linear regression, with the tropical western Pacific (TWP) sea surface temperature (SST) anomaly in preceding October as a predictor. Its prediction skill in the leave‐five‐out cross‐validation is significantly higher than that of the multimodel ensemble mean. The mechanism behind this model is also discussed. In October, the warm TWP SST anomalies can trigger anomalous low‐level convergence surrounding the South China Sea in terms of the Matsuno–Gill mechanism and persist into the following winter, causing above‐than‐normal STR. This information is essential and may provide another perspective to improve the model prediction on the winter STR. [ABSTRACT FROM AUTHOR]

The present study evaluates the skill of seasonal forecasts of temperatures over India during April to June using the Monsoon Mission Coupled Forecasting System (MMCFS) model hindcasts, which are initialized with February initial conditions. Model hindcast data of 1981–2017 period have been used for the analysis. The India Meteorological Department (IMD) gridded temperature dataset has been used for model verifications. The MMCFS model captures the annual cycle of temperatures reasonably well, but with a higher mean and smaller variability compared to observations. The model hindcasts show a significant skill for seasonal forecasts of temperatures over most of northwest and central India. Empirical Orthogonal Function (EOF) analysis suggests that the model captures temporal and spatial characteristics of different modes of maximum temperatures but with less accuracy. The model teleconnections of maximum temperatures with Indian Ocean sea surface temperatures (SSTs) and El Niño–Southern Oscillation (ENSO) are weakly represented. The model is also found capable of predicting the spatial distribution of heat wave characteristics such as heat wave frequency (HWF) and heat wave duration (HWD) reasonably well. The present study suggests that the MMCFS Model can be used to generate a useful outlook of hot weather seasonal temperatures and heat waves over India. [ABSTRACT FROM AUTHOR]

Investigation of SST–streamflow connectivity unravels the large‐scale climate influences that may have a potential role in modulating local hydrological components. Most studies exploring this relationship only focus on a single timescale; however, various atmospheric and oceanic phenomena occur at different temporal scales, which must be considered. This study examines the association of sea surface temperature (SST) and streamflow in Germany, divided into three regions, viz. Alpine, Atlantic and Continental, at timescales ranging from seasonal to interannual by integrating wavelet transform and complex network techniques. Wavelet transform is used to decompose the time series into multiple frequency signals. The network theory identifies the spatial connections for the 99 percentile correlation coefficient value based on these decomposed signals. The degree centrality metric is used to evaluate the characteristics of the spatially embedded networks. Our results re‐establish known SST regions that have a potential connection with the various streamflow regions of Germany. Spatial patterns that resemble the North Atlantic SST tripole‐like pattern is predominant for Alpine streamflow regions at finer timescale. Equatorial Atlantic Mode regions observed for Atlantic streamflow at interannual timescale and Vb weather system connected regions in the Mediterranean Sea have appeared for all the streamflow regions of Germany. Besides, continental streamflow regions exhibited combined characteristics of the Alpine and Atlantic streamflow spatial patterns. In addition to the above regions, we also identify the scale‐specific patterns in the Pacific, Indian and Southern Ocean regions at different timescales. [ABSTRACT FROM AUTHOR]

Extreme precipitation in July across Henan Province and the possible mechanisms involved were investigated. The precipitation in Henan reaches its maximum in July. During 1979–2021, the precipitation in July changed weakly, but the intensity (R99p) and frequency (R99f) of extreme precipitation showed certain increasing trends, with a significant increase in northern Henan. The proportion of extreme precipitation in total precipitation exhibited a significant upward trend. Wavelet analysis results showed that the extreme precipitation in Henan mainly has a 2–3‐year periodicity, and remarkable interannual variation. Furthermore, nearly 80% of the July extreme precipitation events within the magnitude of 50–100 mm occurred 2–3 times. The first two empirical orthogonal function modes of July R99p exhibited a quasi‐monopole pattern (EOF1) and meridional dipole pattern (EOF2), respectively. Further analysis revealed that EOF1 and EOF2 were related to the Silk Road teleconnection pattern (SRP) and the East Asia/Pacific teleconnection pattern (EAP). Circulation factors influenced the interannual variation of R99p, especially in recent years. Furthermore, the associated sea surface temperature anomalies over the Western Pacific and Indian Ocean can intensify the eastward extension of the South Asian high and westward strengthening of the western Pacific subtropical high, which further impacted the SRP and EAP pattern and enhanced the increment of extreme precipitation in Henan Province. [ABSTRACT FROM AUTHOR]

Understanding climate variability requires good quality high resolution spatially and temporally varying ocean fields due to its decisive role in regulating the region's climate, including the Indian summer monsoon. In this regard, we employed a new high‐resolution regional earth system model (RESM), namely ROM over CORDEX South Asia. We demonstrated the performance of the RESM and its added value over the global earth system model, namely MPI‐ESM, in simulating the hydrographic characteristics and associated mechanism over the tropical Indian Ocean (TIO). ROM shows better skill than MPI‐ESM in simulating the near‐surface and subsurface characteristics of the ocean. However, larger added values are noticed for subsurface (>350 m) thermal structure. MPI‐ESM's cold sea surface temperature (SST) bias is reduced in ROM which is associated with weaker winds, anomalous cyclonic wind stress curl, enhanced stratifications, and a shallower mixed layer, resulting in greater upper‐ocean heating. The reduced SST bias is also consistent with improved ocean meridional heat transport (OMHT) in ROM. For example, reduced southward export of OMHT over the Arabian Sea increases the surface warming by ~4%, reducing the RMSE by ~0.2–0.6°C and becoming closer to observation. The anomalous cyclonic wind stress curl, in turn, caused mixed layer stratifications in the western Indian Ocean. The advective heat transfer from the south‐eastern Indian Ocean to the western Indian Ocean reduced oceanic cooling by vertical processes, overcame the cooling by the net loss of surface heat fluxes, and favoured the TIO's surface warming. [ABSTRACT FROM AUTHOR]

As two pronounced anomaly patterns over the tropical Indian Ocean, the Indian Ocean basin mode (IOBM) and the Indian Ocean Dipole (IOD) feature phase‐locking with seasonal cycle. We find that IOBM and IOD exhibit significant connection without the influence of the preceding El Niño–Southern Oscillation (ENSO). The tropical IOBM cooling in preceding winter, which is accompanied by anomalous westerlies in the lower troposphere of the tropical eastern Indian Ocean, can transit to a positive IOD in subsequent seasons. In boreal spring following a IOBM cooling, the equatorial wind anomalies over the Indian Ocean turn to easterlies due to the Rossby wave response to the decreased precipitation over the Maritime Continent region. The increased zonal gradient of the sea surface temperature anomalies in the tropical Indian Ocean favours the intrinsic Bjerknes feedback to build up a positive IOD. With the reinforcing process of the weakened Walker circulation in the tropical Indian Ocean, the positive IOD events develop during boreal summer and then reach the peak in following autumn. These results demonstrate that the IOD is transited from the preceding IOBM, which is independent of the influence of the preceding ENSO in boreal winter. [ABSTRACT FROM AUTHOR]