Climate Dynamics

Published by Springer Nature
Online ISSN: 1432-0894
Print ISSN: 0930-7575
Learn more about this page
Recent publications
Compared with well documented and frequent occurrence of multi-year La Niña, double-year El Niño is less frequent and has not been well investigated. Both of them are a discrepancy from the cyclic behavior of the El Niño-Southern Oscillation and deserve investigation. Here, we demonstrate the diversity of single- and double-year El Niño events in their strengths, flavors, as well as associations with the recharge/discharge processes. The possible different climate impacts are also discussed. During 1950-2021, 75% of El Niño events persist for one year, and 25% of them last for two years. Both central and eastern Pacific type El Niños occur in the single-year and double-year El Niños with various strengths. On average, there is no relationship between the initial time and duration of an El Niño event. Compared with the single-year El Niños, the averaged warm water volume (WWV) is larger in the peak and declines slower for the double-year El Niños, suggesting that a persistently recharged heat condition of the equatorial Pacific is a precondition for the emergence of a second-year El Niño. The faster decline of WWV in the single-year El Niños is associated with the in-phase decrease of its intraseasonal-interseasonal and interannual components, while the slower decline of WWV in the double-year El Niños is determined by the interannual component. In addition, the single-year and double-year El Niño may have different impacts on regional climate.
 
This paper evaluates the predictability and skill of the models from the North American Multi-Model Ensemble project (NMME) in South America on seasonal timescales using analysis of variance (ANOVA). The results show that the temperature variance is dominated by the multi-model ensemble signal in the austral autumn and summer and by the inter-model biases in the austral spring and winter. The temperature predictability is higher at low latitudes, although moderate values are found in extratropical latitudes in the austral spring and summer. The predictability of precipitation is lower than that of temperature because noise dominates the variance. The highest levels of precipitation predictability are reached in tropical latitudes with large inter-seasonal variations. Southeastern South America and Patagonia present the highest predictability at midlatitudes. The NMME skill of temperature is better than that of precipitation, and it is better at low latitudes for both variables. At extratropical latitudes, the skill is moderate for temperature and low for precipitation, although precipitation reaches a local maximum in southeastern South America.
 
  • Hagar BartanaHagar Bartana
  • Chaim I. GarfinkelChaim I. Garfinkel
  • Ofer ShamirOfer Shamir
  • Jian RaoJian Rao
The simulation of the Madden–Julian Oscillation (MJO) and convectively coupled equatorial waves (CCEWs) is considered in 13 state-of-the-art models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). We use frequency–wavenumber power spectra of the models and observations for Outgoing Longwave Radiation (OLR) and zonal winds at 250 hPa (U250), and consider the historical simulations and end of twenty-first century projections for the SSP245 and SSP585 scenarios. The models simulate a spectrum quantitatively resembling that observed, though systematic biases exist. MJO and Kelvin waves (KW) are mostly underestimated, while equatorial Rossby waves (ER) are overestimated. Most models project a future increase in power spectra for the MJO, while nearly all project a robust increase for KW and weaker power values for most other wavenumber–frequency combinations, including higher wavenumber ER. In addition to strengthening, KW also shift toward higher phase speeds (or equivalent depths). Models with a more realistic MJO in their control climate tend to simulate a stronger future intensification.
 
This study focuses on the strengthening of the maritime influence on the Balkan Peninsula in summer. The study uses mainly statistical methods such as trend analysis, multiple linear regression models, etc. The research period is 1979–2020. The results show that in the beginning of the twenty-first century in southeastern Europe there is a tendency of faster increase in the average August air temperatures compared to the increase in average July air temperatures. Thus, the temperature in August is already higher than that in July. The causes for these changes are changes in atmospheric circulation in summer. Over the last two decades, the transport of air masses from east and southeast has been strengthening, which for the Balkan Peninsula means a transport from water basins toward land. The intra-annual course of air temperature above a water basin, which has a maximum in August, is now becoming typical over land. This feature is not yet present in the entire studied region, but the trends from the measurements in meteorological stations show that very soon the temperatures in August could be higher than that in July over the entire territory of the Balkan Peninsula. On a more global scale, it is still unclear which mechanisms of atmospheric circulation influence the processes in southeastern Europe. Changes in ocean temperatures and atmospheric circulation in the North Atlantic are likely to have an impact. However, other factors (e.g. the increase in global temperatures, the expansion of Hadley cell) may also have an impact.
 
The impacts of the Pacific Meridional mode (PMM) on interannual variability of tropical cyclone (TC) genesis over the western North Pacific (WNP) have previously been investigated only based on seasonal/monthly mean environmental fields. Here we focus on tropical waves to further explore multiscale mechanisms for the modulation of PMM on TC genesis over the WNP. The results suggest that PMM, tropical waves and TCs form a multiscale interaction system. The TC geneses attributed to Madden–Julian oscillation (MJO), mixed Rossby–gravity (MRG) waves and tropical depression (TD)-type disturbances are significantly positively correlated with the PMM index during the peak TC season (June to November) of 1998–2019. A detailed comparative analysis is then conducted for two selected typical PMM years (2004 in the positive phase and 2011 in the negative phase). Under the influence of the barotropic instability mechanism, the barotropic energy conversion from the basic flow to the eddy kinetic energy is much greater during the positive PMM year, making MJO, MRG waves and TD-type disturbances more active and thus providing more energy for TC genesis. The positive PMM phase modulates local environment by enhancing low-level relative vorticity and mid-level relative humidity and weakening vertical wind shear associated with MJO, MRG waves and TD-type disturbances, which are more favorable for TC genesis. Examination of the genesis potential index shows that TD-type disturbances play the most important role in the TC genesis process during both PMM years.
 
This study reveals a marked enhancement in the relationship between the variations in location of the winter East Asian Polar Front Jet (EAPJ) and the surface air temperature (SAT) in Eurasia since the mid-1990s. Before the mid-1990s, an evident wave train related to the meridional location of the EAPJ exhibited an anticyclonic anomaly over northern Europe and a cyclonic anomaly in northwestern Asia. With an equatorward shift of the EAPJ after the mid-1990s, the wave train experiences a notable adjustment that is conducive to East Asian cooling, displaying an anticyclonic anomaly around the Kara-Laptev Seas and a cyclonic anomaly near northeastern Asia. Arctic warming anomalies and sea ice loss contributed significantly to these decadal changes. Simulation experiments forced by observed Arctic sea-ice variability further confirm this result. Since the mid-1990s, Arctic sea ice loss (or Arctic warming anomaly) has contributed to a reduction in westerly winds in high latitudes by modulating the meridional temperature gradient. The deaccelerated winds intensify the Arctic cold air propagating to the south, enhancing the atmospheric baroclinicity and the westerly flow in the upper level at the south side of the EAPJ, favoring the southward shift of the EAPJ. With the equatorward shift of the EAPJ, the corresponding SAT anomalies in East Asia are more salient.
 
Improving the simulation of the West African Monsoon (WAM) system is paramount to increasing confidence in the projections of the region's monsoon rainfall change. This work aims to thoroughly analyze the representation of the WAM system in two state-of-the-art, high-resolution (~ 25 km) regional climate models (RCMs) in order to highlight the causes of models' biases through a process-oriented evaluation approach. Model results generally feature a north (Sahel)-south (Guinea Coast) dipole-like rainfall bias, although, sometimes, positive or negative rainfall biases are evident almost over the whole of West Africa. Our analysis shows that biases in the sea-and land-surface temperature on the one hand, and biases in the sea-level and land-surface pressure, on the other hand, lead to biases in the simulated temperature and pressure contrasts between the west African landmass and the eastern Atlantic ocean. As a consequence, biases appear in the modeled monsoon flow strength, which, in turn, lead to errors in the amount of advected moisture in the interior of the continent via southwesterlies and the West African westerly jet (WAWJ) on the one hand, and the extent of deepening of the monsoon flux inland on the other hand. In addition, the African easterly jet (AEJ) is underestimated, inducing an underestimation of the African easterly waves (AEWs) activity and a weakening of the cyclonic convective circulation resulting from the AEWs' troughs, leading to a decrease in the southwesterly flow feeding mesoscale convective systems (MCSs) embedded within the AEJ. The modeled equatorward or northward shifting of the AEJ is likewise found to contribute to the models' wet or dry biases over the Sahel. Finally, there is no consistency between models and reanalyses on the one hand, and between RCM experiments on the other hand, in the way, the simulated atmospheric instability/stability modulates the convection, especially over the Sahel.
 
Changes in summer precipitation over the Tibetan Plateau (TP) significantly influence the surface runoff, river discharge and water availability for the downstream Asian countries, which is sensitive to external forcing. But its response to volcanic eruptions remains unknown. Here we investigate the summer precipitation changes after tropical volcanic eruptions over the TP region by using multiple lines of evidence including reconstructions over the last hundreds of years, observations during recent decades and model simulations covering the last millennium. Both the instrumental data and reconstructions reveal a significant reduction in summer precipitation over the southern TP region during the first summer following tropical volcanic eruptions, which are further confirmed by the coupled model simulations driven by volcanic forcing. The model results indicate that both the dynamic processes related to atmospheric circulation changes and the thermodynamic processes related to specific humidity changes contribute to the decreased precipitation in the southwestern TP, while the thermodynamic process dominates the reduction of precipitation in the southeastern TP. The thermodynamic process results from decreased atmospheric precipitable water caused by decreased surface temperature after tropical volcanic eruptions. The dynamic processes are caused by increased gross moist stability, spatial distribution of surface cooling and a southward shift of westerlies related to weakening and shrinking of Hadley circulation following tropical eruptions. Our results imply that major tropical eruptions have significant impact on the summer precipitation over the southern TP regions, which will further decrease the source of supply for the TP glaciers and runoff output.
 
The topography of Madagascar and the strength of the Mozambique Channel Trough (MCT) modulate summer rainfall over southern Africa. A strong MCT hinders the penetration of moisture bearing easterlies from the South Indian Ocean into the mainland, thus reducing rainfall there and vice versa for weak MCT summers. Given the link between the MCT and rainfall, it is important to analyse how climate models represent the trough. Here, output from 20 models within the CMIP6 ensemble of Coupled General Circulation Models (CGCMs) are analyzed to investigate how state-of-the-art CGCMs represent the MCT and its link to southern African rainfall. Overall, the ensemble mean insignificantly underestimates the observed MCT. There is a large spread among the models, with the strength of the MCT significantly correlated with the Froude number based on the mountain height over Madagascar. In models, the vorticity tendency in the MCT area is dominated by the stretching and friction terms, whereas the vertical advection, tilting and residual terms dominate in the ERA5 reanalysis. The link between MCT and rainfall in the southern African subcontinent is missing in the models. Large rainfall biases are depicted over mainland even in models with a very strong MCT. It is found that the impacts of the MCT in the models could be masked by a complex mix of processes such as the strength of the Angola low, moisture fluxes from the Indian and South Atlantic Oceans as well as overestimated convection in the Mozambique Channel area.
 
The possible influence of changes in the Arctic stratospheric polar vortex on the extratropical troposphere especially in the mid-to-high latitudes of the Northern Hemisphere is still not well understood. Using the ERA5 reanalysis and based on the k-mean clustering algorithm, the northern winter stratospheric polar vortex is categorized into several regimes, which mainly reflect the difference in the intensity and central position of the vortex. As a consequence, the stratospheric polar vortex can be clustered into six groups, including the homogeneously-intensified (HI), homogeneously-weakened (HW), North America-intensified (NAI), North America-weakened (NAW), Eurasia-intensified (EUI), and Eurasia-weakened (EUW) shapes. Statistics of each polar vortex clustering confirms that the yearly frequency of the HI state shows a decreasing trend in past decades, while the HW increases as inferred from the long-term trend. Further, the evolutions of the tropospheric circulation and climate anomalies are explored following each clustering. It is revealed that both the strength and central position of the stratospheric polar vortex significantly modulate the behavior of tropospheric circulation and near surface climate. The relationship between the stratospheric polar vortex regimes and the tropospheric teleconnections are examined. The conventional stratosphere–troposphere coupling via the downward propagation of the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO) signal is confirmed. Other tropospheric teleconnections are also associated with the stratospheric regimes. The Pacific-North American pattern (PNA) is well correlated with the shift of the stratospheric polar vortex, and the Eurasian pattern (EU) is sensitive to the HI and NAW patterns. The patterns of rainfall and temperature anomalies following the six stratospheric regimes are different.
 
////The paper can be publicly full-text accessed by using the following SharedIt link:https://rdcu.be/cVPw3//// Previously the interannual variability of tropical cyclone genesis (TCG) in the Australian region has mainly been attributed to the climate variability in the Pacific and Indian Oceans. In this study, we found that the influence from climate variability in the Atlantic is of equal importance. Application of a state-of-the-art causality analysis reveals that the Atlantic meridional mode (AMM), Atlantic multidecadal oscillation (AMO) and north tropical Atlantic (NTA) sea surface temperature (SST) anomalies are all causal to the Australian region TCG frequency. The associated physical mechanisms are investigated as well. Based on this causal analysis and inference, a statistical model is constructed to forecast TCG, using the Poisson regression and the step-by-step predictor selection method. The Atlantic causal factors, after being taken in as new predictors, help increase the forecast skill for the seasonal Australian region TCG by as much as 10% in terms of correlation increase and 40% in terms of root-mean-square error reduction.
 
Recent assessments of climate sensitivity per doubling of atmospheric CO 2 concentration have combined likelihoods derived from multiple lines of evidence. These assessments were very influential in the Intergovernmental Panel on Climate Change Sixth Assessment Report (AR6) assessment of equilibrium climate sensitivity, the likely range lower limit of which was raised to 2.5 °C (from 1.5 °C previously). This study evaluates the methodology of and results from a particularly influential assessment of climate sensitivity that combined multiple lines of evidence, Sherwood et al. (Rev Geophys 58(4):e2019RG000678, 2020). That assessment used a subjective Bayesian statistical method, with an investigator-selected prior distribution. This study estimates climate sensitivity using an Objective Bayesian method with computed, mathematical priors, since subjective Bayesian methods may produce uncertainty ranges that poorly match confidence intervals. Identical model equations and, initially, identical input values to those in Sherwood et al. are used. This study corrects Sherwood et al.'s likelihood estimation, producing estimates from three methods that agree closely with each other, but differ from those that they derived. Finally, the selection of input values is revisited, where appropriate adopting values based on more recent evidence or that otherwise appear better justified. The resulting estimates of long-term climate sensitivity are much lower and better constrained (median 2.16 °C, 17–83% range 1.75–2.7 °C, 5–95% range 1.55–3.2 °C) than in Sherwood et al. and in AR6 (central value 3 °C, very likely range 2.0–5.0 °C). This sensitivity to the assumptions employed implies that climate sensitivity remains difficult to ascertain, and that values between 1.5 °C and 2 °C are quite plausible.
 
The Coupled Model Intercomparison Project (phase 6) (CMIP6) global circulation models (GCMs) predict equilibrium climate sensitivity (ECS) values ranging between 1.8 and 5.7 $${^\circ }$$ ∘ C. To narrow this range, we group 38 GCMs into low, medium and high ECS subgroups and test their accuracy and precision in hindcasting the mean global surface warming observed from 1980–1990 to 2011–2021 in the ERA5-T2m, HadCRUT5, GISTEMP v4, and NOAAGlobTemp v5 global surface temperature records. We also compare the GCM hindcasts to the satellite-based UAH-MSU v6 lower troposphere global temperature record. We use 143 GCM ensemble averaged simulations under four slightly different forcing conditions, 688 GCM member simulations, and Monte Carlo modeling of the internal variability of the GCMs under three different model accuracy requirements. We found that the medium and high-ECS GCMs run too hot up to over 95% and 97% of cases, respectively. The low ECS GCM group agrees best with the warming values obtained from the surface temperature records, ranging between 0.52 and 0.58 $${^\circ }$$ ∘ C. However, when comparing the observed and GCM hindcasted warming on land and ocean regions, the surface-based temperature records appear to exhibit a significant warming bias. Furthermore, if the satellite-based UAH-MSU-lt record is accurate, actual surface warming from 1980 to 2021 may have been around 0.40 $${^\circ }$$ ∘ C (or less), that is up to about 30% less than what is reported by the surface-based temperature records. The latter situation implies that even the low-ECS models would have produced excessive warming from 1980 to 2021. These results suggest that the actual ECS may be relatively low, i.e. lower than 3 $${^\circ }$$ ∘ C or even less than 2 $${^\circ }$$ ∘ C if the 1980–2021 global surface temperature records contain spurious warming, as some alternative studies have already suggested. Therefore, the projected global climate warming over the next few decades could be moderate and probably not particularly alarming.
 
Time series of AMM [a red bars], AMO [b blue bars] and north tropical Atlantic (90 °W–15 °E, 0°–25° N) SST anomaly [c NTA; green bars] in austral spring (ASO) and the Australian region TC genesis frequency [tropical cyclone genesis frequency (TCGF); white bars] during the typhoon season (NDJFMA). Both time series are unfiltered and are standardized
Wavelet analysis for NTA SST in ASO during the period of 1972–2016
Composite differences of the NDJFMA (November–April) TC genesis frequency (TCGF) over the Australian basin between positive and negative phases of AMM within 5° × 5° grid box based on the International Best Track Archive for Climate Stewardship version 3
Lagged regressed fields of a OLR, b 850 hPa relative vorticity, and c 500 hPa vertical velocity during NDJFMA with respect to the interannual ASO AMO index. Regression coefficients exceeding 95% confidence level are stippled
Seasonal forecasts for TCG frequency in the Australian region. a Variations in observed annual TCG accounts (red line) and leave-one out cross-validation hindcasts (black line) using the ENSO + AMM + AMO predictor model for the period of 1972–2016. b Seasonal hindcasts for the 2007–2016 period. Red: observations, black: ENSO + AMM + AMO predictor model
Previously the interannual variability of tropical cyclone genesis (TCG) in the Australian region has mainly been attributed to the climate variability in the Pacific and Indian Oceans. In this study, we found that the influence from climate variability in the Atlantic is of equal importance. Application of a state-of-the-art causality analysis reveals that the Atlantic meridional mode (AMM), Atlantic multidecadal oscillation (AMO) and north tropical Atlantic (NTA) sea surface temperature (SST) anomalies are all causal to the Australian region TCG frequency. The associated physical mechanisms are investigated as well. Based on this causal analysis and inference, a statistical model is constructed to forecast TCG, using the Poisson regression and the step-by-step predictor selection method. The Atlantic causal factors, after being taken in as new predictors, help increase the forecast skill for the seasonal Australian region TCG by as much as 10% in terms of correlation increase and 40% in terms of root-mean-square error reduction.
 
Most of Australia was in severe drought from 2018 to early 2020. Here we link this drought to the Pacific and Indian Ocean sea surface temperature (SST) modes associated with Central Pacific (CP) El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Over the last 20 years, the occurrence frequency of CP El Niño has increased. This study extends the previous understanding of eastern Pacific (EP) El Niño-Australian rainfall teleconnections, exhibiting that CP El Niño can bring much broader and stronger rainfall deficiencies than EP El Niño during austral spring (September–November) over the northern Australia (NAU), central inland Australia and eastern Australia (EAU). The correlations between SST fields and rainfall in three Cluster regions divided by clustering analysis also confirm this, with rainfall variability in most of Australia except southern Australia (SAU) most significantly driven by CP ENSO. Also, we demonstrate that the CP El Niño affects rainfall in extratropical EAU via the Pacific-South American (PSA) pattern. While the influence of EP El Niño is only confined in tropical NAU because its PSA pattern sits far too east to convey its variability. With the development of ENSO diversity since 2000, the footprint of El Niño on Australian rainfall has become more complex.
 
The impacts of tropical interbasin interaction (TBI) on the characteristics and predictability of sea surface temperature (SST) in the tropics are assessed with a linear inverse modelling (LIM) framework that uses SST and sea surface height anomalies in the tropical Pacific (PO), Atlantic (AO), and Indian Ocean (IO). The TBI pathways are shown to be successfully isolated in stochastically-forced simulations that modify off-diagonal elements of the linear operators. The removal of TBI leads to a substantial increase in the amplitude of El Niño-Southern Oscillation (ENSO) and related variability. Partial decoupling experiments that eliminate specific coupling components reveal that PO-IO interaction is the dominant contributor, whereas PO-AO and AO-IO interactions play a minor role. A series of retrospective forecast experiments with different operators shows that decoupling leads to a substantial decrease in ENSO prediction skill especially at longer lead times. The relative contributions of individual pathways to forecast skill are generally consistent with the results from the stochastically-forced experiments. Qualitatively similar results are obtained from an additional set of forecast experiments that partially apply initial conditions over specific basins, but several important differences were also found due to differences in the representations of each TBI pathway. Finally, the cause of contrasting SST anomalies over the AO after the extreme 1982/83 and 1997/98 El Niño events is explored using LIM forecast experiments to demonstrate the strength and flexibility of our LIM-based approach.
 
Given the essential impact of mixed-layer temperature (MLT) seasonality in Kuroshio–Oyashio Confluence Region (KOCR) on the variations of climate and marine economic species, the present study investigates causes of seasonal MLT anomaly (MLTA) in KOCR under bimodal states of Kuroshio Extension (KE). The results reveal that KE bimodality plays a modulation role in the seasonal variability of MLTA in KOCR. There is an opposite seasonal variation trend of MLTA under different KE states, and the MLTA amplitude in cold season (winter and spring) is larger than that in warm season (summer and autumn). Such behavior is directly induced by different distribution of climatological MLT and wind field in cold and warm seasons, as well as the opposite anomalous velocity of wind and ocean currents nearby KOCR associated with different KE states through changing sensible and latent heat flux, Ekman and geostrophic advection. The results suggest the dependency of short-term (seasonal) variability of KOCR-MLTA on the long-term (decadal) variations of KE background state.
 
Oceanic cross-density (diapycnal) mixing helps sustain the ocean density stratification and its Meridional Overturning Circulation (MOC) and is key to global tracer distributions. The Southern Ocean (SO) is a key region where different overturning cells connect, allowing nutrient and carbon rich Indian and Pacific deep waters, and oxygen rich Atlantic deep waters to resurface. The SO is also rife with intense diapycnal mixing due to the interaction of energetic eddies and currents with rough topography. SO diapycnal mixing is believed to be of secondary importance for the MOC. Here we show that changes to SO mixing can cause significant alterations to biogeochemical tracer distributions over short and long time scales in an idealized model of the AMOC (Atlantic MOC). While such alterations are dominated by the direct impact of changes in diapycnal mixing on tracer fluxes on annual to decadal time scales, on centennial time scales they are dominated by the mixing-induced variations in the advective transport of the tracers by the AMOC. This work suggests that an accurate representation of spatio-temporally variable local and non-local mixing processes in the SO is essential for climate models’ ability to (i) simulate the global biogeochemical cycles and air sea carbon fluxes on decadal time scales, (ii) represent the indirect impact of mixing-induced changes to AMOC on biogeochemical cycles on longer time scales.
 
Few studies have investigated the retreat of the East Asian summer monsoon (EASM) in comparison to its seasonal advances. This study examined the climatological characteristics of the EASM retreat based on the Japanese 55-year Reanalysis data and multiple observation data. First, the retreat date of EASM is defined based on the reversal of 850 hPa meridional winds over coastal East Asia. Then, the climatological characteristics of the EASM retreat are investigated based on the retreat date of the EASM. At lower troposphere, the differences of the 850-hPa winds between after and before the EASM retreat display an anticyclone (cyclone) over the East Asian continent (the subtropical western Pacific), resulting in the strengthening of northerly winds over the coastal region of East Asia. Such northerly winds lead to decrease of moisture transport over East Asia and bring colder air from higher latitudes to the coastal East Asia, both favoring the retreat of the EASM. At middle troposphere, the WPSH moves eastward, and a mid-latitude trough appears over northeast Asia. In addition, the difference fields show descending (ascending) motion and cold (warm) advection in the rear (front) of the mid-latitude trough. At upper troposphere, a divergent center exhibits a southeastward movement, which shifts from the Philippine Islands to the western North Pacific. As such, a convergence center appears over the coastal East Asia in the difference map. The retreat of the EASM is also associated with the decreased rainfall, the demise of the wet season, and the broadscale cooling over East Asia.
 
The maximum signal-to-noise ratio empirical orthogonal function (MSN-EOF) is used to evaluate the midsummer 2 m temperature over Eastern China using subseasonal forecast data in the ECMWF model. The predictable sources of the most predictable components in the ECMWF model are analyzed, and the improvement of reconstructed predictions with leading predictable components is also investigated. ECMWF has the highest forecast ability among all S2S models but decays significantly after 10 d. The leading predictable mode mainly presents a dipole mode over Eastern China. Both the El Niño-Southern Oscillation and tropical Indian Ocean sea surface temperature anomalies are the main predictable sources of MSN-EOF1. A positive MSN-EOF1 is accompanied by El Niño decay, which can cause the strong and westward West Pacific Subtropical High, accompanied by anomalous southwesterlies over the north of Eastern China. The second predictable mode is the warmer characteristic of the Yangtze-Yellow River Basin, and the sea ice anomalies over the Barents Sea in the previous winter are the main predictable sources. This is accompanied by the wave train propagating from northwestern Russia to northeast Asia. The third predictable mode is mainly the temperature trend item extracted from the ECMWF model. The reconstructed predictions with the leading four MSN-EOF components show higher ability than the model raw predictions, therefore, this method can use the predictable components to filter the model noise and reduce the model error.
 
The occurrence of extreme precipitation events during Indian Summer Monsoon Rainfall (ISMR) has increased significantly in recent decades. Natural spatio-temporal variability of extreme precipitation events in India has been linked to various climatic variables like El Niño Southern Oscillation (ENSO), Equatorial Indian Ocean Oscillation (EQUINOO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO). In this study, extreme precipitation indices are used to characterize the ISMR extremes and possible individual and coupled association with climatic variables identified using wavelet analysis. Region-based analysis revealed that ENSO, EQUINOO, PDO, and AMO influence extreme precipitation events on spatio-temporal scales. Variability of the duration of extreme precipitation events strongly depends on the ENSO at interannual scale compared to the other climate variables whereas, total precipitation greater than 95th percentile and maximum consecutive 5-day precipitation values were significantly coherent on inter-decadal scale with ENSO, EQUINOO, and PDO. It is also found that the climate variables together cause variability in ISMR extremes, particularly AMO-ENSO-EQUINOO and AMO-ENSO-PDO combinations explain the variability better than any other combination. An increase in the number of climate variables did not improve the coherence, since these climatic variables are correlated with each other. Further, the decomposition of wavelets at different scales shows that more than half of the grid points considered were significant at interdecadal and multidecadal scales even though they are designated with different time scales. This indicates that the non-stationary behavior of the ISMR extremes is directly linked to the climatic variables at higher scales.
 
Diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.
 
In this study we present a methodological framework to obtain statistically downscaled high resolution climate projections over the Attica region in Greece. The framework relies on the construction of a local daily gridded dataset for temperature variables (maximum, minimum and mean daily temperatures) and daily precipitation sums. To this aim, a mosaic of data that includes observations derived from ground stations and a high resolution simulation, performed by the Weather Research and Forecasting (WRF) model, for 1 year (1995) are blended using various gridding techniques to produce a 1 km 1 km high resolution daily gridded dataset for the period 1981–2000. The comparison of the gridded dataset against the observations reveals that the produced dataset maintains the observed long term statistical properties over the period 1981–2000 for both temperature and precipitation variables. Consequently, the produced dataset is used to statistically downscale Regional Climate Model simulations from the EURO-CORDEX initiative for the present (1981–2000) and the future climate (2081–2100) under the Representative Concentration Pathway (RCP) 8.5 climate scenario using two different bias adjustment techniques. The results indicate that the selection of the bias adjustment method is important and can affect the simulated climate change signals in a different way. Thus bias adjustment should be performed with caution and examined thoroughly before any such downscaled climate change projection dataset reach decision and policy makers in order to plan climate change related adaptation strategies.
 
Climate models are vital to the assessment of the impacts of climate change in the Central African regions. Establishing how well models reproduce key processes is important to the confidence we attach to these tools. This study examines model representation of the September to November characteristics, such as location and intensity, of the African Easterly Jet (AEJ) north and south in a sample of 16 commonly evaluated CMIP5 and CMIP6 models and in two reanalyses (ERA5 and MERRA2). The analysis evolves to assess key drivers of the AEJ from energetic interactions, the characteristics of mid-level highs and thermal lows and the nature of surface thermal heating. Over West Africa, several models miss the southeast-northwest orientation of the AEJ-N core, leading to a gap of around 6 ⁰ in the location of the jet while most CMIP5 models also fail to locate AEJ-S over southern Central Africa. In general, the spread of simulated AEJ locations around reanalyses is larger for the CMIP5 sample compared to CMIP6 equivalent models, indicating improvement from CMIP5 to CMIP6 in this 16 model subset. However, this improvement in some CMIP6 models (e.g. GISS-E2-1-G and MIROC6) is not related to a maximum surface meridional gradient in temperature. Most CMIP5 and CMIP6 models underestimate the surface temperature gradient over AEJ-N region. As a first order diagnostic of the jet's acceleration, most coupled models better simulate the atmospheric energetic interactions over AEJ-N region that leads to its strong contribution to AEJ-N maintenance compared to AEJ-S. This study strengthens our understanding of the mid-level circulation over Central Africa by detecting gaps in the mechanisms maintaining the AEJ in coupled models and highlights processes that should be improved in future ensembles.
 
Climate models are important tools for investigating how the climate might change in the future, however recent observations have suggested that these models are unable to capture the overturning in subpolar North Atlantic correctly, casting doubt on their projections of the Atlantic Meridional Overturning Circulation (AMOC). Here we compare the overturning and surface water mass transformation in a set of CMIP6 models with observational estimates. There is generally a good agreement, particularly in the recent conclusion from observations that the mean overturning in the east (particularly in the Iceland and Irminger seas) is stronger than that in the Labrador Sea. The overturning in the Labrador Sea is mostly found to be small, but has a strong relationship with salinity: fresh models have weak overturning and saline models have stronger mean overturning and stronger relationships of the Labrador Sea overturning variability with the AMOC further south.We also find that the overturning reconstructed from surface flux driven water mass transformation is a good indicator of the actual overturning, though mixing can modify variability and shift signals to different density classes.
 
This study identified three distinct circulation patterns that induce enhanced intraseasonal precipitation events (IPEs) over South China (SC) in boreal winter based on observational data of 1979–2016. The three categories account for 45%, 33% and 14% of total IPEs, respectively. In Category I, a cyclonic anomaly with quasi-barotropic vertical structure propagates southward from the northern Asia while no signal of the Madden–Julian Oscillation (MJO) is observed. Category II (III) is featured by a fast (slow)-propagating MJO that shows suppressed (enhanced) convection over the equatorial western Pacific (Maritime Continent) during the peak-wet phase of SC. The common process responsible for the onset of IPEs is boundary-layer moistening dominated by mean moisture advection due to intraseasonal southerly wind. For Category I, the anomalous southerly arises from the southwesterly to the southeast of the mid-latitude cyclone. For Category II, it is attributed to the southwesterly to the west of the anticyclone over the northwestern Pacific, as a response to the suppressed MJO convection over the western Pacific. For Category III, it is due to the southwesterly to the east of the cyclone over India in response to the enhanced MJO convection over the eastern Indian Ocean. The moisture origins for the three categories are also distinguishable.
 
Using the ensemble empirical mode decomposition method, this study systematically investigates the multiple timescales of the southern annular mode (SAM) and identifies their relative contributions to the persistence of the SAM. Analyses show that the persistence of SAM mainly depends on the contribution of longer-timescale variabilities, especially the cross-seasonal variability of SAM. When subtracting the cross-seasonal variability from the SAM, the long-term positive covariance between the eddy forcing and zonal flow disappears. Composite analysis shows that the meridional shift of zonal wind, eddy momentum forcing and baroclinicity anomalies can be maintained for more than 40 days only under the circumstance of strong cross-seasonal variability, indicating the dominant role played by the cross-seasonal variability for the low-frequency persistence of the SAM. Analysis further shows that the cross-seasonal variability of the SAM, in addition to the internal dynamics, is associated with the extratropical air–sea interaction. About half of the strong cross-seasonal SAM events are accompanied by evident extratropical dipolar SST anomalies, which mostly occur in austral summer. The cross-seasonal dependence of the low-frequency change in SAM suggests that the contribution of longer-timescale variabilities, especially the cross-seasonal variability, cannot be neglected in subseasonal prediction of the SAM.
 
Most studies on wind variability have deepened into the stilling vs. reversal phenomena at global to regional scales, while the long-term changes in local-scale winds such as sea-breezes (SB) represent a gap of knowledge in climate research. The state-of-the-art of the wind variability studies suggests a hypothetical reinforcement of SB at coastal stations. We first developed a robust automated method for the identification of SB days. Then, by using homogenized wind observations from 16 stations across Eastern Spain, we identified 9,349 episodes for analyzing the multidecadal variability and trends in SB speeds, gusts and occurrence for 1961–2019. The major finding is the opposite trends and decoupled variability of SB speeds and gusts: the SB speeds declined significantly in all seasons (except for winter), and the SB gusts strengthened at the annual scale and in autumn–winter, being most significant in autumn. Our results also show that the SB occurrence has increased across most of Eastern Spain, although presenting contrasting seasonal trends: positive in winter and negative in summer. We found that more frequent anticyclonic conditions, NAOI + and MOI + are positively linked to the increased winter occurrence; however, the causes behind the opposite trends in SB speeds and gusts remain unclear. The SB changes are complex to explain, involving both large-scale circulation and physical-local factors that challenge the understanding of the opposite trends. Further investigation is needed to assess whether these trends are a widespread phenomenon, while climate models could simulate the drivers behind these decoupled SB changes in a warmer climate.
 
Since the 1980s, rapid Arctic sea ice loss has been observed, and its potential influences on the midlatitude weather and climate have been extensively examined, but strongly debated. This study instead investigates influences of Arctic sea ice loss on the Eastern Hemisphere westerly wind on the poleward side of the polar front jet (PFJ), which has significantly weakened in winter but strengthened in summer since 1980s. Observational analyses indicate that the Eastern Hemisphere PFJ anomalies in winter and summer are strongly correlated with Northern Hemisphere (NH) atmospheric circulation, surface air temperature and precipitation changes, and that the winter PFJ variability is significantly correlated to Barents-Kara sea ice anomalies from autumn and winter at interannual time scales. About 58% of the observed winter PFJ weakened trend during 1979–2014 is congruent with the autumn sea ice index over the Barents-Kara Seas. Atmospheric model ensemble simulations from four models show that Arctic sea ice loss contributes to Arctic warming in winter and reduces the northern Eurasia-pole temperature contrast, leading to an significant weakening winter PFJ. Ensemble mean effects of four models and each model due to Arctic sea ice loss explain about 10–20% of the observed winter PFJ weakening trend, because the model simulations underestimate observed impacts of sea ice reduction on Arctic troposphere warming. In summer, the strengthening PFJ is mostly controlled by increasing greenhouse gases and sea surface temperature changes outside the Arctic, but is little affected by Arctic sea ice loss. Our observational and numerical results consistently suggest that a dynamical pathway linking observed Arctic sea ice loss to northern Eurasian winter is through its weakening effect on the westerly wind on the poleward side of the PFJ.
 
The backward nonlinear local Lyapunov exponent (BNLLE) was developed based on the NLLE method to quantitatively investigate the local predictability of extreme events. By studying the dynamical characteristics of error growth preceding extreme events, the local predictability limits of these events can be determined. In this study, the BNLLE method is used to quantify the local predictability limits of two extreme high-temperature events (EHTEs) that occurred in Europe during the summer of 2019. The results show that the error dynamics are dependent on the geographical location. During the early forecast period, positive error-growth rates are mainly located in southern regions, whereas negative error-growth rates are mainly located in northern regions. However, the variations in the error growth rates exhibit regional differences with the forecast time. As such, the relative growth of initial errors (RGIEs) also depends on the geographical location. From the RGIEs, the local predictability limits of the two EHTEs are determined to be 11 and 9 days, respectively. By measuring the forecast skill, the local predictability limits (11 and 9 days) are verified to be reasonable and realistic. Therefore, the BNLLE method can quantify the local predictability of EHTEs, and is an effective technique for studying the predictability of future extreme weather and climate events.
 
The variability of Indian Ocean shallow meridional overturning circulation (SMOC) is studied using the century long ocean reanalysis simple ocean data assimilation (SODA) data. Though SMOC exhibits stronger southward transport during boreal summer, it displays stronger variability during boreal winter. The spectrum analysis of winter SMOC index reveals presence of highest amplitude between 5 to 7 years at 95% confidence level, suggesting the dominance of intra-decadal SMOC variability. The robustness of intra-decadal SMOC variability is also confirmed in different ocean reanalysis data sets. Composite analysis of filtered upper Ocean Heat Content, sea level, thermocline depth and Sea Surface Temperature anomalies for strong (weak) SMOC years show negative (positive) anomaly over north and East of Madagascar. Correlation analysis, of filtered SMOC index and sea level pressure (zonal winds) over the India Ocean, found significant negative (positive) correlation coefficient north of 40 °S (around 10 °S) and significant positive (negative) correlation coefficient over the 45 °S to 70 °S (20 °S to 50 °S and north of 5 °S). This meridional pattern of correlation coefficient for sea level pressure, manifesting the out of phase relationship between sub-tropics and high latitude mean sea level pressure, resembles with Southern Annular Mode (SAM). We conclude that the intra-decadal variability of mean sea level pressure leads to zonal wind variation around 10 °S modulating SMOC, which in turn affects the upper ocean thermal properties in the east and north of Madagascar. This study for the first time brought out coherent intra-decadal evolution of SAM and SMOC during boreal winter.
 
Mesoscale convective systems (MCSs) downstream of the Tibetan Plateau (TP) exhibit unique precipitation features. These MCSs can have damaging impacts and there is a critical need for improving the representation of MCSs in numerical models. However, most global climate models are typically run at resolutions that are too coarse to reasonably resolve MCSs, and it is still unclear how well higher-resolution global models can reproduce the precipitation characteristics of MCSs. In this study, the sensitivity of MCSs simulated by a global high resolution (~ 10 km), atmosphere-only climate model to different treatments of convection (with and without parametrized convection, and a hybrid representation of convection) have been investigated. The results show that explicit convection (i.e., non-parameterized) can better reproduce the observed pattern of MCS precipitation over the East Asian Summer Monsoon region. In general, explicit convection better simulates the diurnal variability of MCSs over the eastern China, and is able to represent the distinctive diurnal variations of MCS precipitation over complex terrain particularly well, such as the eastern TP and the complex terrain of central-northern China. It is shown that explicit convection is better at simulating the timing of initiation and subsequent propagating features of the MCS, resulting in better diurnal variations and further a better spatial pattern of summer mean MCS precipitation. All three experiments simulate MCS rainfall areas which are notably smaller than those in observations, but with much stronger rainfall intensities, implying that these biases in simulated MCS morphological characteristics are not sensitive to the different treatment of convection.
 
The effects of volcanic eruptions on hurricane statistics are examined using two long simulations from the Community Earth System Model (CESM) Last Millennium Ensemble (LME). The first is an unforced control simulation, wherein all boundary conditions were held constant at their 850 CE values (LMEcontrol). The second is a “fully forced” simulation with time evolving radiative changes from volcanic, solar, and land use changes from 850 CE through present (LMEforced). Large tropical volcanic eruptions produce the greatest change in radiative forcing during this time period, which comprise the focus of this study. The Weather Research and Forecasting (WRF) model is used to dynamically downscale 150 control years of LMEcontrol and an additional 84 years of LMEforced for all mid-latitude volcanic eruptions between 1100 and 1850 CE. This time period was selected based on computational considerations. For each eruption, 2 years are dynamically downscaled. 23 of these volcanic eruptions are in the Northern Hemisphere and 19 are in the Southern Hemisphere. The effectiveness of the downscaling methodology is examined by applying the same downscaling approach to historical ERA-I reanalysis data and comparing the downscaled storm tracks and intensities to the International Best Track Archive for Climate Stewardship (IBTrACS) database. Hurricane statistics are then computed from both the downscaled control and downscaled forced LME simulations. Results suggest moderate effects on hurricanes from the average of all northern hemisphere eruptions, with the largest effects being from the volcanoes with the most aerosol forcing. More specifically, reductions in hurricane frequency, intensity, and lifetime following northern hemisphere eruptions are apparent. Strong evidence is also shown for correlation between eruption strength and changes in these diagnostics. The aggregate effect from both northern and southern hemisphere eruptions is minor. While reductions in frequency, intensity, and lifetime from northern hemisphere eruptions occur, the opposite effect is observed from southern hemisphere eruptions.
 
The summer (June through September) monsoon 2020 has been very erratic with episodes of heavy and devastating rains, landslides and catastrophic winds over South Asia (India, Pakistan, Nepal, Bangladesh), East Asia (China, Korea, and Japan), and Southeast Asia (Singapore, Thailand, Vietnam, Laos, Cambodia, Philippines, Indonesia). The withdrawal of the summer monsoon over India was delayed by 2 weeks. The monsoon season over East Asia has been the longest. China recorded a Dam burst in the twentieth century. Furthermore, the Korean Peninsula has experienced back-to-back severe tropical cyclones. Could the lockdown activities initiate to control the COVID-19 spread a possible cause for these major episodes? The strict enforcement of the lockdown regulations has led to a considerable reduction of air pollutants—dust and aerosols throughout the world. A recent study based on satellites and merged products has documented a statistically significant mean reduction of about 20, 8, and 50% in nitrogen dioxide, Aerosol Optical Depth (AOD) and PM2.5 concentrations, respectively over the megacities across the globe. Our analysis reveals a considerable reduction of about 20% in AOD over South as well as over East Asia, more-over East Asia than over South Asia. The reduced aerosols have impacted the strength of the incoming solar radiation as evidenced by enhanced warming, more-over the land than the oceans. The differential warming over the land and the ocean has resulted in the amplification of the meridional ocean-land thermal contrast and strengthening of the monsoon flow. These intense features have supported the surplus transport of moisture from the oceans towards the main lands. Some similarity between the anomalous rainfall pattern and the anomalous AOD pattern is discernable. In particular, the enhancement of rainfall, the reduction in AOD and the surface temperature warming match very well over two regions one over West-Central India and the other over the Yangzte River Valley. Results further reveal that the heavy rains over the Yangzte River Valley could be associated with the preceding reduced aerosols, while the heavy rains over West-Central India could be associated with reduced aerosols and also due to the surface temperature warming.
 
This paper investigates the causes for the interdecadal change in the relationships between early and late summer precipitation over South China (SC). It is found that the correlations of the precipitation over SC between June and August shift from weak positive in 1979–1995 to significantly negative in 1996–2019. Further analysis demonstrates that the distinct evolution of sea surface temperature (SST) pattern between the two periods accounts for the interdecadal variations of their relationships. Although the warming of the tropical western Indian Ocean (WIO) in June favors increasing precipitation over the SC via enhancing the Northwest Pacific Subtropical High (NWPSH) during the whole period, the associated SST anomalies in August are rather different between the two periods. Specifically, the WIO warming in June corresponds to slightly positive anomalies over the tropical central-eastern Pacific in August during the 1979–1995, which has weak impact on the NWPSH and results in a weak precipitation correlation between June and August. However, the WIO warming in June corresponds to La Niña’s rapid development in August during the 1996–2019, which favors the enhancement of the NWPSH via increasing the regional Hadley circulation. Due to the climatologically northward movement of NWPSH from June to August, the enhanced NWPSH in August acts to decrease the precipitation over SC, causing a significantly negative correlation between precipitation in June and August. Overall, the distinct evolution of tropical SST pattern is the key factor inducing the change of the relationships between June and August precipitation in the two periods.
 
This study examines the impacts of sea surface temperature (SST) confguration on the monthly prediction of summer mon�soon over the western North Pacifc (WNP) by conducting several sets of hindcast experiments using the Beijing Climate Center Climate System Model and its atmospheric component model. The results show that the atmosphere-only model exhibits limited skill in predicting the WNP monsoon rainfall and circulation, and this skill can hardly be improved by sim�ply increasing the frequency of prescribed SST observation. Compared to the atmosphere-only model, the coupled model shows much better performance in predicting the WNP monsoon rainfall and circulation, which can be further improved by adopting the observed SST with relatively higher frequency in the model initialization. This indicates that the high fre�quency of observed SST used is much more important in the coupled model than in the uncoupled model. In addition, the uncoupled model forced by the SST predicted by coupled model tends to produce better prediction of WNP monsoon rainfall and circulation than that forced by the observed SST. Both the coupled model and the atmosphere-only model forced by the coupled model predicted SST can well reproduce the surface latent heat fux and shortwave radiation fux over the WNP, leading to a reasonable SST-monsoon relationship and thus skillful predictions of WNP monsoon. Therefore, although the Tier-1 approach based on coupled model is increasingly popular, the Tier-2 approach based on atmosphere-only model is still feasible for the monthly prediction of WNP summer monsoon despite the lack of air-sea interaction. To obtain more skillful Tier-2 prediction, we recommend seeking for SST forcing that is unrealistic but consistent with the atmospheric model rather than SST forcing with very high accuracy.
 
The topographic dynamical effect from Eurasia (EA_Topo) and North America (NA_Topo) on the winter isentropic meridional mass circulation (IMMC) is investigated using the WACCM. The independent effect of EA_Topo and that of NA_Topo, with the former much stronger, are both to strengthen the IMMC that is composed of the lower equatorward cold air branch (CB) and the upper poleward warm air branch in the extratropical tropopshere (WB_TR) and stratosphere (WB_ST). Further investigation of the individual contributions from changes in stationary vs. transient and zonal-mean flow vs. waves reveals that, due to the topography-forced mass redistribution, changes in the low-level meridional pressure gradient force a zonal-mean counter-clockwise/clockwise meridional cell in the southern/northern side of topography. This weakens/strengthens the IMMC south/north of 30° N from the troposphere to lower stratosphere, acting as a dominant contributor to the IMMC changes south of 50° N. Meanwhile, the EA/NA_Topo-forced amplification of stationary waves constructively interacts with those determined by land-sea contrast, making the dominant/minor contributions to the strengthening of CB and WB_TR north of 50° N. The related increase in the upward wave propagation further dominates the WB_ST strengthening in the subpolar region. Meanwhile, transient eddy activities are depressed by EA/NA_Topo along with the weakened background westerly, which partly-offset/dominate-over the contribution from stationary flow in midlatitudes and subpolar region. The coexistence of the other topography (NA/EA_Topo) yields destructive mutual interferrence, which can weaken/offset the independent-EA/NA_Topo-forced meridional mass transport mainly via changing the zonal-mean as well as the downstream wave pattern of mass and meridional wind.
 
The impacts of global warming on Meiyu–Baiu extreme rainfall and the associated mid-latitude synoptic-scale weather systems over the Eastern China (EC) and the Baiu rainband (Bu) regions in East Asia have been examined, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model (MRI-AGCM3.2S). This model was demonstrated to give realistic Asian extreme rainfall, when compared with data from the Tropical Rainfall Measuring Mission (TRMM). Here we used a novel wave-selection algorithm based on the 300 hPa wind, in order to identify upper-level propagating wave signals in conjunction with the occurrence of extreme precipitation in either EC or Bu. The same algorithm was applied for both the present (1979–2003) and future (2075–2099) climate simulations from the AGCM, so as to infer the impacts of global warming on the behavior of these systems. Results show robust decrease of intensity of systems influencing both Bu and EC in the future warmer climate. Their corresponding low-to-mid level circulation, as revealed by vertical velocity, temperature advection and sea-level pressure composites, was also found to be weakened. This is likely related to changes in the background circulation in future over the East Asian mid-latitude zone, such as the widespread increment of the seasonal mean static stability at 500 hPa. However, the wave-associated precipitation over these regions was enhanced in the future climate simulations. This can be attributed to more strong intensity rainfall, which increases as the background temperature in these regions warms, largely following the Clausius–Clapeyron relation. Therefore, changes of wave-related extreme precipitation in EC and Bu are mainly controlled by the thermodynamic effect; the latter appears to be much stronger than the potential impacts due to the slight weakening of these weather systems.
 
As a combination of temperature and humidity, wet-bulb temperature (WBT) is useful for assessing heat stress and its societal and economic impacts. However, spatial and temporal behaviors of summer WBT in China remain poorly understood. In this study, we investigate the dominant spatiotemporal modes of summer (June–July–August) WBT in the mainland of China during 1960–2017 by using empirical orthogonal function (EOF) analysis and reveal their corresponding underlying mechanisms. The leading mode (EOF1) of summer WBT in China shows a nationwide increasing WBT with a stronger magnitude in northern and western than southeastern China. The second mode (EOF2) displays a zonal pattern with anomalously increased WBT in the west and decreased WBT in the east. The third mode (EOF3) shows a meridional feature with the largest WBT trends appearing in the Yangtze River valley. Further examinations suggest that EOF1 exhibits remarkable interdecadal/long-term variations and is likely connected with global warming and the Atlantic Multidecadal Oscillation (AMO), which induce an anomalous anticyclone centering over northern China and covering nearly the whole country. This anticyclone not only plays a key role in the nationwide WBT increases, but also dominates the spatial pattern of EOF1 by modulating relative humidity. EOF2 and EOF3 reflect interannual variations and show significant correlations with the El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), respectively. A zonal wavelike pattern with troughs over Balkhash and northeastern China, and Mongolia high substantially modulates the water vapor transport in China, thus playing a key role in EOF2. In the case of EOF3, an anomalous anticyclone in the middle-upper troposphere and a shallow intensified cyclone in the lower troposphere collectively format the spatial pattern of EOF3 by inducing significant increases in temperature in central-eastern China and transporting a large amount of water vapor to northeastern China, respectively. These findings are critical to improve our understanding of summer WBT in China and to mitigate the negative effects of heat stress.
 
Increasing frequency and intensity of heatwaves (HWs) in a warming climate exert catastrophic impacts on human society and natural environment. However, spatiotemporal variations of HW and their driving factors still remain obscure, especially for HW changes over Eurasia, the region with the largest population of the world. Here we provide a systematic investigation of the HW changes over Eurasia and quantify the contributions of different natural and anthropogenic factors to these changes. Increasing frequency, duration and intensity of HW are observed in most parts of Eurasia, and the occurrence of the first HW event tends to be earlier as well, especially in Europe, East Asia, Central Asia, Southwest Asia, and the Mediterranean region. These intensified HW activities are particularly stronger and more widespread after 1990 s. The spatial pattern of the increasing HW trend is closely tied to the interdecadal changes of sea surface temperature in the North Pacific. More intense hot airmass convection, atmospheric circulation obstruction over the Mediterranean region and the enhanced Mongolian high hinders the southward movement of cold air and cold and wet airmass exchange. Further analyses suggest that the intensifying Eurasian HW tendency is a combined result of both climate change and human activities. Overall, the fractional contributions of climate warming, urbanization, standardized precipitation evaporation index, and Atlantic Multi-decadal Oscillation to the frequency of Eurasian HWs are 30%, 25%, 21% and 24%, respectively. It is also suggested that the relative influential rate of different driving factors for HW varies over time and differs in different areas.
 
Extreme climate events can cause large risks to ecosystems and human society in a short period. Investigating the changing trends of such events is essential for regional climate risk management. However, there is limited information on the regional assessment of the history and future trends of extreme climate events in Xinjiang, China. This study investigated the historical changes and projected trends of extreme climate events in Xinjiang based on observational data and Coupled Model Intercomparison Project phase 6 (CMIP6) model simulations. The results showed that the bias correction effectively reduced the bias of the CMIP6 model to the extreme climate indices simulation. During the period 1961–2014, the extreme indices representing warmth showed robust growth, while the extreme indices representing cold showed a robust decline. The intensity and frequency indices of extreme precipitation continued to increase, while consecutive dry days (CDDs) shortened and consecutive wet days (CWDs) lengthened. The changing trend of the extreme temperature indices had strong spatial consistency, while the changing trend of the extreme precipitation indices had obvious spatial heterogeneity. Based on the CMIP6 model simulations, the extreme climate indices in the twenty-first century were projected to continue the changing trend of the historical period (1961–2014). Compared with north Xinjiang (NXJ) and south Xinjiang (SXJ), the cold spell duration index (CSDI), cold nights (TN10p), cold days (TX10p), and extreme precipitation events in the Tianshan Mountains (TSM) were projected to experience stronger changes in the twenty-first century. The response of extreme temperature and extreme precipitation indices to global warming was approximately linear. Compared with SSP585, most extreme climate indices under the SSP245 scenario changed slightly in response to global warming. The superposition of the increase (decrease) in extreme warm (cold) events and the increase in extreme precipitation events will exacerbate the threat of extreme climate events to the agricultural and ecological security of the Xinjiang oasis, especially in the TSM. Given the limited water vapor sources and precipitation and the high rate of evapotranspiration, it is projected that the current situation of water shortages in Xinjiang will not be fundamentally changed.
 
Nonhydrostatic Icosahedral Atmospheric Model (NICAM) coupled with a slab ocean model was applied to a paleoclimate research for the first time. The model was run at a horizontal resolution of 56 km with and without a convective parameterization, given the orbital parameters of the last interglacial (127,000 years before present). The simulated climatological mean-states are qualitatively similar to those in previous studies reinforcing their robustness, however, the resolution of this model enables to represent the narrow precipitation band along the southern edge of the Tibetan Plateau. A particular focus was given to convectively coupled disturbances in our analysis. The simulated results show a greater signal of the Madden–Julian Oscillation and weakening of the moist Kelvin waves. Although the model's representation of the boreal summer intraseasonal oscillation in the present-day simulations is not satisfactory, a significant enhancement of its signal is found in the counterpart of the last interglacial. The density of the tropical cyclones decreases over the western north Pacific, north Atlantic and increases over the south Indian Ocean and south Atlantic. The model's performance is generally better when the convective parameterization is used, but the tropical cyclones are better represented without the convective parameterization. Additional simulations using the low-resolution topography reveals that the better representation of the Tibetan Plateau enhances the boreal summer Asian monsoon and its impact is similar and comparable to that of the orbital parameters over the south Asia and the Indian Ocean.
 
Top-cited authors
Bin Wang
  • University of Hawaiʻi at Mānoa
Tim Li
  • University of Hawai'i System
Samuel Somot
  • Centre National de Recherches Météorologiques
Andreas Franz Prein
  • National Center for Atmospheric Research
Magdalena Alonso Balmaseda
  • European Center For Medium Range Weather Forecasts