Search Results (32)

Under global warming, persistent extreme heat events (PHEs) in China have increased significantly in both frequency and intensity, posing severe threats to agriculture and socioeconomic development. Combining observational analysis (1961–2019) and numerical simulations, this study investigates the distinct impacts of Northwest Pacific (NWP) and North Atlantic (NA) sea surface temperature (SST) anomalies on PHEs over China. Key findings include the following: (1) PHEs exhibit heterogeneous spatial distribution, with the Yangtze-Huai River Valley as the hotspot showing the highest frequency and intensity. A regime shift occurred post-2000, marked by a threefold increase in extreme indices (+3σ to +4σ). (2) Observational analyses reveal significant but independent correlations between PHEs and SST anomalies in the tropical NWP and mid-high latitude NA. (3) Numerical experiments demonstrate that NWP warming triggers a meridional dipole response (warming in southern China vs. cooling in the north) via the Pacific–Japan teleconnection pattern, characterized by an eastward-retreated and southward-shifted sub-tropical high (WPSH) coupled with an intensified South Asian High (SAH). In contrast, NA warming induces uniform warming across eastern China through a Eurasian Rossby wave train that modulates the WPSH northward. (4) Thermodynamically, NWP forcing dominates via asymmetric vertical motion and advection processes, while NA forcing primarily enhances large-scale subsidence and shortwave radiation. This study elucidates region-specific oceanic drivers of extreme heat, advancing mechanistic understanding for improved heatwave predictability. Full article

Statistical cluster analysis applied to monthly 1–100 m ocean temperatures reveals El Niño–Southern Oscillation (ENSO) dipole patterns with a leading mode having opposing centers of action across the dateline and tropical east Pacific. We focus on the La Niña cold phase and study its impact on the Caribbean climate over the period of 1980–2024. East dipole time scores are used to identify composite years, and anomaly patterns are calculated for Jan-Jun and Jul-Dec. Convective responses over the Caribbean exhibit seasonal contrasts: dry winter–spring and wet summer–autumn. Trade winds and currents across the southern Caribbean weaken and lead to anomalous warming of upper ocean temperatures. Sustained coastal upwelling off Peru and Ecuador during east La Niña is teleconnected with easterly wind shear and tropical cyclogenesis over the Caribbean during summer, leading to costly impacts. This ocean–atmosphere coupling is quite different from the more common central Pacific ENSO dipole. Full article

This study investigates teleconnections between rainfall in the Ogooué River Basin (ORB) and sea surface temperature (SST) in the tropical ocean basins. The Maximum Covariance Analysis (MCA) is used to determine coupled patterns of SST in the tropical oceans and rainfall in the ORB, depicting regions and modes of SST dynamics that influence rainfall in the ORB. The application of MCA to rainfall and SST fields results in three coupled patterns with squared covariance fractions of 84.5%, 76.5%, and 77.5% for the Atlantic, Pacific, and Indian tropical basins, respectively. Computation of the correlations of the Savitzky–Golay-filtered resulting expansion coefficients reached 0.65, 0.5 and 0.72, respectively. The SST variation modes identified in this study can be related to the Atlantic Meridional Mode for the tropical Atlantic and the El Niño Southern Oscillation for the tropical Pacific. Over the Indian Ocean, it is a homogeneous mode over the entire basin, instead of the popular dipole mode. Then, the time-dependent correlation method is used to remove any ambiguity on the relationships established from the MCA. Full article

The regularity of rainfall seasonality is very important for vegetation growth, the livelihood of the population, agricultural production, and ecosystem sustainability. Changes in precipitation and its extremes have been widely reported; however, the spatial and temporal variations in rainfall seasonality and their underlying mechanisms are less understood. Here, we analyzed the changes in rainfall seasonality and possible teleconnection mechanisms in the eastern China monsoon region during 1981–2022, with a special focus on the El Niño-Southern Oscillation (ENSO), El Niño Modoki (ENSO_M), and Indian Ocean Dipole (IOD). Our results show that due to the changes in rainfall concentration, rainfall magnitude, or both, rainfall seasonality has developed in the northern China (NC, 0.15 × 10⁻³ yr⁻¹) and central China (CC, 0.07 × 10⁻³ yr⁻¹) monsoon regions, and weakened in the northeastern China (NEC, −0.08 × 10⁻³ yr⁻¹) and southern China (SC, −0.15 × 10⁻³ yr⁻¹) monsoon regions during the recent decades. The large-scale circulation and SST anomalies induced by cold or warm phases of the IOD, ENSO_M, and (or) ENSO can explain the enhanced seasonality in the NC and CC monsoon regions and weakened seasonality in the NEC and SC monsoon regions. The wavelet coherence analysis further shows that the dominated climatic factors for rainfall seasonality changes are different in the CC, NC, SC, and NEC monsoon regions, and that rainfall seasonality is also affected by the coupling of the IOD, ENSO_M, and ENSO. Our results highlight that the IOD, ENSO_M, and ENSO are important climatic causes for rainfall seasonality changes in the eastern China monsoon region. Full article

In this work, the preindustrial control (piControl) and Historical experiments results from climatic Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) are analyzed for their ability to predict the El Niño–Southern Oscillation (ENSO). Using the principal component method, it is shown that the Global Atmospheric Oscillation (GAO), of which the ENSO is an element, is the main mode of interannual variability of planetary anomalies of surface air temperature (SAT) and atmospheric sea level pressure (SLP) in the ensemble of 50 CMIP6 models. It turns out that the CMIP6 ensemble of models reproduces the planetary structure of the GAO and its west–east dynamics with a period of approximately 3.7 years. The models showed that the GAO combines ENSO teleconnections with the tropics of the Indian and Atlantic Oceans, and with temperate and high latitudes. To predict strong El Niño and La Niña events, we used a predictor index (PGAO) obtained earlier from observation data and reanalyses. The predictive ability of the PGAO is based on the west–east propagation of planetary structures of SAT and SLP anomalies characteristic of the GAO. Those CMIP6 models have been found that reproduce well the west–east spread of the GAO, with El Niño and La Niña being phases of this process. Thanks to this, these events can be predicted with approximately a year’s lead time, thereby overcoming the so-called spring predictability barrier (SPB) of the ENSO. Thus, the influence of global anomalies of SAT and SLP on the ENSO is shown, taking into account that it may increase the reliability of the early forecast of El Niño and La Niña events. Full article

The interaction between soil moisture (SM) and vegetation dynamics has been proven in previous studies. In situ measurements have provided reliable data to investigate and validate the time effect in different zones, which is important in the hydrology and agriculture fields. There were 845 SM in situ monitoring measurements utilized with the correlation between SM and vegetation across various soil depths and climate zones in China. The impact of climate and teleconnection factors on SM and the leaf area index (LAI) are also discussed. The results indicate that SM increases from northwest to southeast in China. The time lag responses of SM to temperature, precipitation, relative humidity, and sunshine duration are 0–3 days, 3–7 days, 1–3 days, and 3–15 days, respectively. The LAI is most strongly correlated with the climate of the current month. When the LAI leads SM, a negative correlation is observed, whereas a positive correlation is observed when SM leads the LAI. This proves that vegetation growth restricts the increase in SM, and soil drying further restricts the growth of vegetation. There was a response time of 2–4 months between the LAI and SM. The effect of vegetation and deeper SM was significant in the arid zone, while they were coupled with shallow SM in the humid zone. Additionally, the El Niño–Southern Oscillation (ENSO) showed a significant positive correlation with SM in 2015–2016 with signals of 9–14 months. The results provide support for balancing the contradiction between future vegetation restoration and water resource scarcity. Full article

The results of a piControl experiment investigating general circulation models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) were examined. The global interannual variability in the monthly surface temperature (ST) and sea level pressure (SLP) anomalies was considered. The amplitudes of the fluctuations in the anomalies of these meteorological fields between opposite phases of the El Niño–Southern Oscillation (ENSO) were calculated. It was shown that most CMIP6 models reproduced fluctuations in the ST and SLP anomalies between El Niño and La Niña not only in the equatorial Pacific, but also throughout the tropics, as well as in the middle and high latitudes. Some of the CMIP6 models reproduced the global structures of the ST and SLP anomaly oscillations quite accurately between opposite phases of ENSO, as previously determined from observational data and reanalyses. It was found that the models AS-RCEC TaiESM1, CAMS CAMS-CSM1-0, CAS FGOALS-f3-L, CMCC CMCC-ESM2, KIOST KIOST-ESM, NASA GISS-E2-1-G, NCAR CESM2-WACCM-FV2, and NCC NorCPM1 reproduced strong ENSO teleconnections in regions beyond the tropical Pacific. Full article

The westerly circulation and the monsoon circulation are the two major atmospheric circulation systems affecting the middle latitudes of the Northern Hemisphere (NH), which have significant impacts on climate and environmental changes in the middle latitudes. However, until now, people’s understanding of the long-term paleoenvironmental changes in the westerly- and monsoon-controlled areas in China’s middle latitudes is not uniform, and the phase relationship between the two at different time scales is also controversial, especially the exception to the “dry gets drier, wet gets wetter” paradigm in global warming between the two. Based on the existing literature data published, integrated paleoenvironmental records, and comprehensive simulation results in recent years, this study systematically reviews the climate and environmental changes in the two major circulation regions in the mid-latitudes of China since the Middle Pleistocene, with a focus on exploring the phase relationship between the two systems at different time scales and its influencing mechanism. Through the reanalysis and comparative analysis of the existing data, we conclude that the interaction and relationship between the two circulation systems are relatively strong and close during the warm periods, but relatively weak during the cold periods. From the perspective of orbital, suborbital, and millennium time scales, the phase relationship between the westerly and Asian summer monsoon (ASM) circulations shows roughly in-phase, out-of-phase, and anti-phase transitions, respectively. There are significant differences between the impacts of the westerly and ASM circulations on the middle-latitude regions of northwest China, the Qinghai–Tibet Plateau, and eastern China. However, under the combined influence of varied environmental factors such as BHLSR (boreal high-latitude solar radiation), SST (sea surface temperature), AMOC (north Atlantic meridional overturning circulation), NHI (Northern Hemisphere ice volume), NAO (North Atlantic Oscillation), ITCZ (intertropical convergence zone), WPSH (western Pacific subtropical high), TIOA (tropical Indian Ocean anomaly), ENSO (El Niño/Southern Oscillation), CGT/SRP (global teleconnection/Silk Road pattern), etc., there is a complex and close coupling relationship between the two, and it is necessary to comprehensively consider their “multi-factor’s joint-action” mechanism and impact, while, in general, the dynamic mechanisms driving the changes of the westerly and ASM circulations are not the same at different time scales, such as orbital, suborbital, centennial to millennium, and decadal to interannual, which also leads to the formation of different types of phase relationships between the two at different time scales. Future studies need to focus on the impact of this “multi-factor linkage mechanism” and “multi-phase relationship” in distinguishing the interaction between the westerly and ASM circulation systems in terms of orbital, suborbital, millennium, and sub-millennium time scales. Full article

Severe weather impacts in the central Caribbean are quantified by an objective index of daily maximum wind and rainfall (W•R) in the area 16–19°N, 63–69°W over the period 1970–2021. The index, based on ERA5 hindcast assimilation of satellite and in situ data, peaks from the July to October season as high sea temperatures and weak wind shear promote tropical cyclogenesis. Climate forcing is studied by reducing the W•R index to seasonal values and regressing the time series onto reanalysis fields 10°S–25°N, 180°W–20°E. The outcome reflects Jul–Oct warming in the tropical Atlantic, cooling in the tropical east Pacific (cold tongue), decreased/increased convection over the Pacific/Atlantic, and tropical upper easterly winds. New findings emerge in the Mar–Jun season preceding higher W•R: reduced SW-cloud bands in the northeast Pacific, a convective trough over the equatorial Atlantic, and Caribbean cold-air outbreaks. The multivariate El Niño Southern Oscillation index correlates with Jul–Oct Caribbean W•R at 2-month lead time and shows growing influence. Composite analysis of the top-10 years identifies an anomalous Pacific–Atlantic Walker Circulation favoring higher Caribbean W•R. Salinity is below normal and heat flux is downward across the Atlantic. Anomalous low-level airflow inhibits upwelling in the SW Caribbean, deepening atmospheric moisture. A leading case (TC Fiona 2022) demonstrates the environmental conditions underpinning storm intensification. The key drivers of severe weather impacts yield guidance in strategic planning, risk management and disaster preparedness. New insights are gained from a localized index of severe weather. Full article

This study explores the drivers of drought over northeast (NE) Africa as represented by monthly ERA5 potential evaporation during 1970–2022. The comparisons with surface heat flux and A-pan measurements suggest that potential evaporation quantifies moisture deficits that lead to drought. A principal component (PC) analysis of potential evaporation has the following leading modes: PC-1 in the Nile Basin and PC-2 in the Rift Valley. Time scores were filtered and regressed onto fields of SST, netOLR, and 500 hPa zonal wind to find teleconnections, and drought composites were analyzed for anomalous structure. The results identify that cold-phase Indian Ocean Dipole (IOD) couples with the overlying zonal Walker circulation. Deep easterly winds subside at −0.1 m/s over the west Indian Ocean and NE Africa, causing desiccation that spreads westward from the Rift Valley via diurnal heat fluxes. Insights are gained on IOD modulation based on the Pacific ENSO, but long-range forecasts remain elusive. Full article

In this study, a pattern detection method is applied on the RCP4.5 and RCP8.5 simulation outputs of seven GCMs—disseminated by the Coupled Model Intercomparison Project Phase 5 (CMIP5)—to determine whether atmospheric teleconnection patterns detected in the ERA-20C reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) will be observable in the future projections of the CMIP5 GCMs. The pattern detection technique—which combines the negative extrema method and receiver operating characteristic (ROC) curve analysis—is used on the geopotential height field at the 500 hPa pressure level in wintertime, in the Northern Hemisphere. It was found that teleconnections obtained from the ERA-20C reanalysis dataset for the period of 1976–2005 remain observable in the majority of the GCM outputs under the RCP4.5 and RCP8.5 scenarios for the periods of 2006–2035, 2021–2050, and 2071–2100. The results imply that atmospheric internal variability is the major factor that controls the teleconnections rather than the impact of radiative forcing. Full article

Daily groundwater level is an indicator of groundwater resources. Accurate and reliable groundwater level (GWL) prediction is crucial for groundwater resources management and land subsidence risk assessment. In this study, a representative deep learning model, long short-term memory (LSTM), is adopted to predict groundwater level with the selected predictors by partial mutual information (PMI), and bootstrap is employed to generate different samples combination for training many LSTM models, and the predicted values by many LSTM models are used for the uncertainty assessment of groundwater level prediction. Two wells of different climate zones in the USA were used as a case study. Different significant predictors of GWL for two wells were identified by PMI from candidate predictors incorporating teleconnection patterns information. The results show that GWL is significantly affected by antecedent GWL, AO, Niño 3.4, Niño 1 + 2, and precipitation in humid areas, and by antecedent GWL, AO, Niño 3.4, Niño 3, Niño 1 + 2, and PNA in arid areas. Predictor selection can assist in improving the prediction performance of the LSTM model. The relationship between GWL and significant predictors were modeled by the LSTM model, and it achieved higher accuracy in humid areas, while the performance in arid areas was poorer due to limited precipitation information. The performance of LSTM was improved by increasing correlation coefficient (R²) values by 10% and 25% for 2 wells compared to generalized regression neural network (GRNN). Three uncertainty evaluation metrics indicate that LSTM reduced the uncertainty compared to GRNN model. LSTM coupling with PMI and bootstrap can be a promising approach for accurate and reliable groundwater level prediction for different climate zones. Full article

In this study, we show that changes in the 250 hPa vorticity cut-off low (COL) activity may possibly be driven by sea surface temperature (SST) variations in the tropical Pacific. Using ERA5 reanalysis, the existence of different large-scale circulation patterns is identified that work to enhance the COL activity with a weakened jet stream, while COLs are suppressed with strengthened westerlies. The present-day simulations of AMIP-CMIP6 models reproduce realistic features of the El Niño Southern Oscillation (ENSO)–COL teleconnection, but biases exist, especially in coupled models. The differences are a priori due to the inability of the models to accurately predict the time-mean zonal flow, which may be in part due to systematic biases in the predicted SST. The underestimation of warm SST anomalies over the eastern Pacific is a common problem in CMIP3 and CMIP5 models and remains a major uncertainty in CMIP6. We find that a reduced bias in the predicted SST by coupled models is most likely to produce more skillful simulations in the Southern Hemisphere, but the same evidence does not hold for the Northern Hemisphere. The study suggests the potential for seasonal prediction of COLs and the benefits that would result using accurate initialization and consistent model coupling. Full article

This paper describes the long-term grid-point rainfall trends in the context of climate change, recent regionalised rainfall decline and drought events for mainland Portugal, which is teleconnected, in most cases, to the trends of mathematical descriptions of the North Atlantic Oscillation (NAO) during the century from October 1919 to September 2019. Grid-point rainfall dataset (1919–2019, from 126 centroids in a regular mesh over the country) have been constructed from high-quality ground-based data and as such, it provides a reliable source for the analysis of rainfall trends at different timescales: October–December, January–March, December–March, and the hydrological year. The Mann–Kendall (MK) coupled with Sen’s slope estimator test are applied to quantify the trends. The Sequential Mann–Kendall (SQMK) analysis is implemented to obtain the fluctuation of the progressive trends along the studied 100-year period. Because of their pivotal role in linking and synchronising climate variability, teleconnections to the North Atlantic Ocean are also explored to explain the rainfall trends over the Portuguese continuum. The results provide a solid basis to explain the climate change effects on the Portuguese rainfall based on significant associations with strong negative correlations between changes in rainfall and in NAO indices. These strong opposing correlations are displayed in most of the winter seasons and in the year. After the late 1960s, a generalised rainfall decrease emerges against a background of significant upward trends of the NAO; such coupled behaviour has persisted for decades. Regionalised droughts at three identified climatic regions, based on factor analysis and Standardised Precipitation Index (SPI), are also discussed, concluding that the frequency of severe droughts may increase again, accompanied by a stronger influence of the recently more positive and unusual winter season and annual NAO indices. Full article

In this study, the characteristics of systematic errors in subseasonal prediction for East Asia are investigated using an ensemble hindcast (1991–2010) produced by the Global Seasonal Forecasting System version 5 (GloSea5). GloSea5 is a global prediction system for the subseasonal-to-seasonal time scale, based on a fully coupled atmosphere, land, ocean, and sea ice model. To examine the fidelity of the system with respect to reproducing and forecasting phenomena, this study assesses the systematic biases in the global prediction model focusing on the prediction skill for the East Asian winter monsoon (EAWM), which is a major driver of weather and climate variability in East Asia. To investigate the error characteristics of GloSea5, the hindcast period is analyzed by dividing it into two periods: 1991–2000 and 2001–2010. The main results show that the prediction skill for the EAWM with a lead time of 3 weeks is significantly decreased in the 2000s compared to the 1990s. To investigate the reason for the reduced EAWM prediction performance in the 2000s, the characteristics of the teleconnections relating to the polar and equatorial regions are examined. It is found that the simulated excessive weakening of the East Asian jet relating to the tropics and a failure in representing the Siberian high pressure relating to the Arctic are mainly responsible for the decreased EAWM prediction skill. Full article