Search Results (250)

The Wyrtki Jet (WJ), a pivotal surface circulation system in the equatorial Indian Ocean, exerts significant regulatory control over regional climate dynamics through its intense eastward transport characteristics, which modulate water mass exchange, thermohaline balance, and cross-basin energy transfer. To address the scarcity of in situ observational data, this study developed a satellite remote sensing-driven multi-parameter coupled model and reconstructed the WJ’s seasonal variations using the XGBoost machine learning algorithm. The results revealed that wind stress components, sea surface temperature, and wind stress curl serve as the primary drivers of its seasonal dynamics. The XGBoost model demonstrated superior performance in reconstructing WJ’s seasonal variations, achieving coefficients of determination (R²) exceeding 0.97 across all seasons and maintaining root mean square errors (RMSE) below 0.2 m/s across all seasons. The reconstructed currents exhibited strong consistency with the Ocean Surface Current Analysis Real-time (OSCAR) dataset, showing errors below 0.05 m/s in spring and autumn and under 0.1 m/s in summer and winter. The proposed multi-feature integrated modeling framework delivers a high spatiotemporal resolution analytical tool for tropical Indian Ocean circulation dynamics research, while simultaneously establishing critical data infrastructure to decode monsoon current coupling mechanisms, advancing early warning systems for extreme climatic events, and optimizing regional marine resource governance. Full article

Atmospheric pressure gradients determine the dynamics of the southwest monsoon (SWM) and northeast monsoon (NEM), resulting in rainfall in the Indian subcontinent. Consequently, the surface salinity, mixed layer, and thermocline are impacted by the seasonal freshwater outflow and direct rainfall. Moreover, seasonally reversing monsoon gyre and associated currents govern the northern Indian Ocean surface oceanography. This study provides an overview of the impact of these dynamic changes on sea surface temperature, salinity, and productivity by integrating more than 3000 planktonic foraminiferal censuses and bulk sediment geochemical data from sediment core tops, plankton tows, and nets between 25° N and 10° S and 40° E and 110° E of the past six decades. These data were used to construct spatial maps of the five most dominant planktonic foraminifers and illuminate their underlying environmental factors. Moreover, the cured foraminiferal censuses and the modern oceanographic data were used to test the newly developed artificial neural network (ANN) algorithm to calculate the relationship with modern water column temperatures (WCTs). Furthermore, the tested relationship between the ANN derived models was applied to two foraminiferal censuses from the northern Bay of Bengal core MGS29-GC02 (13°31′59″ N; 91°48′21″ E) and the southern Bay of Bengal Ocean Drilling Program (ODP) Site 758 (5°23.05′ N; 90°21.67′ E) to reconstruct the WCTs of the past 890 ka. The reconstructed WCTs at the 10 m water depth of core GC02 suggest dramatic changes in the sea surface during the deglacial periods (i.e., Bolling–Allerǿd and Younger Dryas) compared to the Holocene. The WCTs at Site 758 indicate a shift in the mixed-layer summer temperature during the past 890 ka at the ODP Site, in which the post-Mid-Brunhes period (at 425 ka) was overall warmer than during the prior time. However, the regional alkenone-derived sea-surface temperatures (SSTs) do not show such a shift in the mixed layer. Therefore, this study hypothesizes that the divergence in regional SSTs is most likely due to differences in seasonality and depth habitats in the paleo-proxies. Full article

The evaluation of cloud distribution, properties, and their interaction with the radiation (longwave and shortwave) is of utmost importance for the proper assessment of future climate. Therefore, this study focuses on the Coupled Model Inter-Comparison Project Phase-6 (CMIP6) historical and future projections using the Shared Socio-Economic Pathways (SSPs) low- (ssp1–2.6), moderate- (ssp2–4.5), and high-emission (ssp5–8.5) scenarios along the South Asian region. For this purpose, a multi-model ensemble mean approach is employed to analyze the future projections in the low-, mid-, and high-emission scenarios. The cloud water content and cloud ice content in the CMIP6 models show an increase in upper and lower troposphere simultaneously in future projections as compared to ERA5 and historical projections. The longwave and shortwave cloud radiative effects at the top of the atmosphere are examined, as they offer a global perspective on radiation changes that influence atmospheric circulation and climate variability. The longwave cloud radiative effect (44.14 W/m²) and the shortwave cloud radiative effect (−73.43 W/m²) likely indicate an increase in cloud albedo. Similarly, there is an expansion of Hadley circulation (intensified subsidence) towards poleward, indicating the shifting of subtropical high-pressure zones, which can influence regional monsoon dynamics and cloud distributions. The impact of future projections on the tropospheric temperature (200–600 hPa) is studied, which seems to become more concentrated along the Tibetan Plateau in the moderate- and high-emission scenarios. This increase in the tropospheric temperature at 200–600 hPa reduces atmospheric stability, allowing stronger convection. Hence, the strengthening of convective activities may be favorable in future climate conditions. Thus, the correct representation of the model physics, cloud-radiative feedback, and the large-scale circulation that drives the Indian Summer Monsoon (ISM) is of critical importance in Coupled General Circulation Models (GCMs). Full article

With climate warming, the global precipitation patterns have undergone significant changes, which will profoundly impact flood–drought disaster regimes and socioeconomic development in key regions of human activity worldwide. The convergence zone of the Indian Ocean monsoon and Pacific monsoon in China covers most of the middle and lower reaches of the Yangtze River (MLRYR), which is located in the transitional area of the second and third steps of China’s terrain. Changes in precipitation patterns in this region will significantly impact flood and drought control in the MLRYR, as well as the socioeconomic development of the MLRYR Economic Belt. In this study, Huaihua area in China was selected as the study area to study the characteristics of regional precipitation change, and to analyze the evolution in the trends in annual precipitation, extreme precipitation events, and their spatiotemporal distribution, so as to provide a reference for the study of precipitation change patterns in the intersection zone. This study utilizes precipitation data from meteorological stations and the China Meteorological Forcing Dataset (CMFD) reanalysis data for the period 1979–2023 in Huaihua region. The spatiotemporal variation in precipitation in the study area was analyzed by using linear regression, the Mann–Kendall trend test, the moving average method, the Mann–Kendall–Sneyers test, wavelet analysis, and R/S analysis. The results demonstrate the following: (1) The annual precipitation in the study area is on the rise as a whole, the climate tendency rate is 9 mm/10 a, and the precipitation fluctuates greatly, showing an alternating change of “dry–wet–dry–wet”. (2) Wavelet analysis reveals that there are 28-year, 9-year, and 4-year main cycles in annual precipitation, and the precipitation patterns at different timescales are different. (3) The results of R/S analysis show that the future precipitation trend will continue to increase, with a strong long-term memory. (4) Extreme precipitation events generally show an upward trend, indicating that their intensity and frequency have increased. (5) Spatial distribution analysis shows that the precipitation in the study area is mainly concentrated in the northeast and south of Jingzhou and Tongdao, and the precipitation level in the west is lower. The comprehensive analysis shows that the annual precipitation in the study area is on the rise and has a certain periodic precipitation law. The spatial distribution is greatly affected by other factors and the distribution is uneven. Extreme precipitation events show an increasing trend, which may lead to increased flood risk in the region and downstream areas. In the future, it is necessary to strengthen countermeasures to reduce the impact of changes in precipitation patterns on local and downstream economic and social activities. Full article

This study presents a global assessment of the climatological seasonal variability of river discharge into the oceans, based on an expanded dataset comprising 958 gauging stations across 136 countries. Monthly discharges were compiled for 145 major rivers and tributaries, with a focus on improving the accuracy and spatial coverage of global freshwater flux estimates. Compared to previous datasets, this updated compilation includes a broader set of rivers, explicitly integrates tributary inflows, and quantifies both the absolute and relative seasonal amplitudes of discharge variability. The results reveal substantial differences among ocean basins. The Atlantic Ocean, although receiving the highest total runoff, shows relatively weak seasonal variability, with a coefficient of variation of CV = 12.6% due to asynchronous peak discharge from its major rivers (Amazon, Congo, Orinoco). In contrast, the Indian Ocean exhibits the most pronounced seasonal cycle (CV = 88.3%), driven by monsoonal rivers. The Pacific Ocean shows intermediate variability (CV = 62.1%), influenced by a combination of monsoon rains and snowmelt. At the river scale, Orinoco and Changjiang display high seasonal amplitudes, exceeding 89% of their mean flows, whereas more stable regimes are found in equatorial and temperate rivers like the Amazon and Saint Lawrence. In addition, the critical role of tributaries in altering discharge magnitude and seasonal variability is well established. This study provides high-resolution monthly discharge climatologies at global and basin scales, enhancing freshwater forcing in OGCMs. By improving the representation of land–ocean exchanges, it enables more accurate simulations of salinity, circulation, biogeochemical cycles, and climate-sensitive processes in coastal and open-ocean regions. Full article

Sri Lanka typically experiences anomalously wet conditions during the summer following El Niño events, but this response varies due to El Niño complexity. This study investigates the impact of post-El Niño conditions on Sri Lanka’s Monsoon rainfall, contrasting summers after fast- and slow-decaying El Niño events. Results indicate that fast-decaying El Niño events lead to wet and cool summers while slow-decaying events result in dry and warm summers. These contrasting responses are linked to sea surface temperature (SST) changes in the central to eastern Pacific. During the fast-decaying El Niño, the transition to La Niña generates strong easterlies in the central and eastern Pacific, enhancing moisture convergence, upward motion, and cloud cover, resulting in wetter conditions over Sri Lanka. During the fast-decaying El Niño, enhanced precipitation over the Maritime Continent acts as a diabatic heating source, inducing Gill-type easterly wind anomalies over the tropical Pacific. These winds promote coupled feedbacks that accelerate the transition to La Niña, strengthening moisture convergence and upward motion over Sri Lanka. Conversely, slow-decaying El Niño events are associated with cooling in the western North Pacific and warming in the Indian Ocean, which promotes the development of the western North Pacific anticyclone, suppressing upward motion and reducing cloud cover, leading to conditions over Sri Lanka. Changes in the Walker circulation further contribute to these distinct rainfall patterns, highlighting its influence on regional climate dynamics. These findings enhance our understanding of the seasonal predictability of rainfall in Sri Lanka during post-El Niño Summers. Full article

In this study, we evaluate aerosol, cloud, and radiation interactions in GFS.V17.p8 (Global Forecast System System Version 17 prototype 8). Two experiments were conducted for the summer of 2020. In the control experiment (EXP CTL), aerosols interact with radiation only, incorporating direct and semi-direct aerosol effects. The sensitivity experiment (EXP ACI) couples aerosols with both radiation and Thompson microphysics, accounting for aerosol indirect effects and fully interactive aerosol–cloud dynamics. Introducing aerosol and cloud interactions results in net cooling at the top of the atmosphere (TOA). Further analysis shows that the EXP ACI produces more liquid water at lower levels and less ice water at higher levels compared to the EXP CTL. The aerosol optical depth (AOD) shows a good linear relationship with cloud droplet number concentration, similar to other climate models, though with larger standard deviations. Including aerosol and cloud interactions generally enhances simulations of the Indian Summer Monsoon, stratocumulus, and diurnal cycles. Additionally, the study evaluates the impacts of aerosols on deep convection and cloud life cycles. Full article

Precipitation cyclicity plays a crucial role in regional water supply and climate predictions. In this study, we used observational data from 34 representative meteorological stations in the Xinjiang region, a major part of inland arid China, to characterize the interannual cyclicity of regional precipitation from 1951 to 2021 and analyze its contributing factors. The results indicated that the mean annual precipitation in Xinjiang (MAP_XJ) was dominated by a remarkably increasing trend over the past 70 years, which was superimposed by two bands of interannual cycles of approximately 3 years with explanatory variance of 56.57% (Band I) and 6–7 years with explanatory variance of 23.38% (Band II). This is generally consistent with previous studies on the cyclicity of precipitation in Xinjiang for both seasonal and annual precipitation. We analyzed the North Tropical Atlantic sea-surface temperature (NTA_SST), El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Indian Summer Monsoon (ISM) as potential forcing factors that show similar interannual cycles and may contribute to the identified precipitation variability. Two approaches, multivariate linear regression and the Random Forest model, were employed to ascertain the relative significance of each factor influencing Bands I and II, respectively. The multivariate linear regression analysis revealed that the AO index contributed the most to Band I, with a significance score of −0.656, whereas the ENSO index with a one-year lead (ENSO_−1yr) played a dominant role in Band II (significance score = 0.457). The Random Forest model also suggested that the AO index exhibited the highest significance score (0.859) for Band I, whereas the AO index with a one-year lead (AO_−1yr) had the highest significance score (0.876) for Band II. Overall, our findings highlight the necessity of employing different methods that consider both the linear and non-linear response of climate variability to driving factors crucial for future climate prediction. Full article

Moisture transports play a key role in maintaining the hydrometeorological cycle and forming its climate variability over the Tibetan Plateau (TP), also known as the “Asian water tower”. This study focuses on understanding the interannual variability mode characteristics of moisture transport in the TP in boreal summer, using satellite-based analysis and reanalysis data from 1983 to 2022 with a combined empirical orthogonal function (EOF) analysis. We identified the first two primary interannual modes of TP summer water vapor fluxes, which are primarily characterized by zonal and meridional dipole patterns, respectively. The zonal pattern of the TP water vapor flux dominates the TP and East Asian summer rainfall variability, while the meridional pattern of the TP water vapor flux tends to be a result of the South Asian summer rainfall and its circulation anomalies. The tropical Indo-Pacific sea surface temperature (SST) variations, such as El Niño and Indian Ocean SST modes, have significantly delayed relationships with the interannual variability modes of the summer water vapor fluxes over the TP, indicating a significant modulation effect of the low-latitude oceanic variability on the interannual variations in TP summer moisture transport. These results deepen our understanding of the relationship between TP moisture transport and summer monsoonal rainfall variability, as well as the influence of the tropical oceans. Full article

The remarkable expansion of lake areas across the Changtang Plateau (CTP, located in the central Tibetan Plateau) since the late 1990s has drawn considerable scientific interest, presenting a striking contrast to the global decline in natural lake water storage observed during the same period. This study systematically investigates the mechanisms underlying lake area variations on the CTP by integrating glacierized area changes derived from the Google Earth Engine (GEE) platform with atmospheric circulation patterns from the ERA5 reanalysis dataset. Our analysis demonstrates that the limited glacier coverage on the CTP exerted significant influence only on glacial lakes in the southern region (r = −0.65, p < 0.05). The widespread lake expansion across the CTP predominantly stems from precipitation increases (r = 0.74, p < 0.01) associated with atmospheric circulation changes. Enhanced Indian summer monsoon (ISM) activity facilitates anomalous moisture transport from the Indian Ocean to the southwestern CTP, manifesting as increased specific humidity (Qa) in summer. Simultaneously, the weakened westerly jet stream reinforces moisture convergence across the CTP, driving enhanced annual precipitation. By coupling glacier coverage variations with atmospheric processes, this research establishes that precipitation anomalies rather than glacial meltwater primarily govern the extensive lake expansion on the CTP. These findings offer critical insights for guiding ecological security strategies and sustainable development initiatives on the CTP. Full article

Here, we discuss the results of an experiment in toe-line protection of estuarine embankments from frequent slope failure using silt traps. We test the feasibility of terracotta rings to trap silt and promote natural mangrove regeneration in barren patches in front of embankments around human settlements in the Indian Sundarban region, designated as the Sundarban Biosphere Reserve. The initial results of the first sixteen months of observations, between May 2023 and August 2024, are encouraging. Sediment accumulation in the silt traps across sites ranges between 4 and 42 cm. Periodic granulometric analyses of sediments indicate that while the middle estuarine sites accumulate more clay/silt, the lower estuarine sites accumulate more sand. During the late and post-monsoon seasons, all sites except one, on the eastern coast of the lower estuarine island, exhibit natural mangrove regeneration, the main species being Porteresia coarctata, Sueda maritima and Avicennia marina. Additionally, oysters Saccostrea cuculata and occasionally Crassostrea cuttakensis are found attached to the terracotta silt traps. The results highlight the potential of the nature-based Living Shoreline strategy to support mangrove regeneration and toe-line protection cost-effectively. The study also successfully opens up new possibilities for sustainable elevation management in the sinking and shrinking mangrove region of the Sundarbans, a significant development in the face of climate change and accelerated sea level rise. Full article

Arabian Sea (AS) and Bay of Bengal (BoB) cyclones around the Indian subcontinent cause widespread floods and other natural hazards. There is no single convincing answer to this puzzle in the era of global warming. The warming of the western and central Indian Ocean is one of the few prominent features of local warming. The availability of moisture in the atmosphere in the last decade is an important factor in the rapid intensification and strengthening of tropical cyclones (TCs) before landfall. Essentially, the AS basin has shown an upward trend in the number and intensity of very severe cyclones during the period of 2009–2019. The decadal variation (1991–2001, 2002–2011, and 2012–2021) in SST, vorticity, wind shear, and moisture is primarily responsible for the genesis and intensification of cyclones during the post-monsoon season (October–November–December) over the AS. The results showed that slight changes in wind conditions, such as increased wind shear and the northward shift of the Asian Jet Stream over the region, facilitate TC formation. Full article

The scarcity of in situ observation stations and the unreliability of long-term satellite data necessitate the use of reanalysis datasets to study elevation-dependent climate change (EDCC) in the third pole (TP) region. We analyzed elevation-dependent temperature and precipitation patterns over TP using the ECMWF Atmospheric Reanalysis Fifth Generation (ERA5), a global reanalysis product with coarse resolution, along with three high-resolution regional reanalysis datasets that cover our study domain: Indian Monsoon Data Assimilation and Analysis (IMDAA), High Asia Refined Analysis—Version 2 (HAR-v2), and Tibetan Plateau Regional Reanalysis (TPRR). Comparing the performance of the four reanalysis datasets in capturing EDCC over TP is crucial, as these datasets provide spatially and temporally consistent data at an optimum resolution that greatly aids EDCC research. Our study results reveal the following: (1) A positive elevation-dependent warming trend is observed across all four datasets in winter and autumn, with varying magnitudes of warming across the datasets. (2) All four datasets exhibit positive elevation-dependent wetting trends in all seasons, except autumn. These are primarily driven by pronounced drying trends at lower elevations and relatively minimal changes in precipitation trends at higher elevations. (3) ERA5 and IMDAA exhibit similar results in capturing elevation-dependent climate change, whereas the TPRR dataset reveals more extreme and unique features in temperature trends compared to the other three datasets. HAR-v2 shows smaller variations in temperature and precipitation trends across different elevations and seasons, in contrast to the other three datasets. While all reanalysis datasets indicate EDCC in the TP, their varying degrees of seasonal and spatial differences underscore the need for a careful evaluation before using them as reference data. Comparison of reanalysis datasets with available observational records, such as in situ measurements and satellite data, over overlapping spatial and temporal domains is essential to assess their quality. This evaluation can help identify the most suitable reanalysis dataset, or combination of datasets, to serve as reliable a reference even in regions or periods without observational data. Full article

Per- and polyfluoroalkyl substances (PFAS) are increasingly detected in remote environments. This review aims to provide a comprehensive overview of the types and concentrations of PFAS found in the air, water, soil, sediments, ice, and precipitation across different remote environments globally. Most of the recent studies on PFAS remote occurrence have been conducted for the Arctic, the Antarctica, and the remote regions of China. Elevated perfluorooctane sulfonate (PFOS) in Meretta and Resolute Lakes reflects the impact of local sources like airports, while PFAS in lakes located in remote regions such as East Antarctica and the Canadian High Arctic suggest atmospheric deposition as a primary PFAS input. Long-chain PFAS (≥C7) accumulate in sediments, while short-chain PFAS remain in water, as shown in Hulun Lake. Oceanic PFAS are concentrated in surface waters, driven by atmospheric deposition, with PFOA and PFOS dominating across oceans due to current emissions and legacy contamination. Coastal areas display higher PFAS levels from local sources. Arctic sediment analysis highlights atmospheric deposition and ocean transport as significant PFAS contributors. PFAS in Antarctic coastal areas suggest local biological input, notably from penguins. The Tibetan Plateau and Arctic atmospheric data confirm long-range transport, with linear PFAS favoring gaseous states, while branched PFAS are more likely to associate with particulates. Climatic factors like the Indian monsoon and temperature fluctuations affect PFAS deposition. Short-chain PFAS are prevalent in snowpacks, serving as temporary reservoirs. Mountainous regions, such as the Tibetan Plateau, act as cold traps, accumulating PFAS from atmospheric precursors. Future studies should focus on identifying and quantifying primary sources of PFAS. Full article

Lake areas across the Tibet Plateau have been taken as the major indicator of water resources changes. However, drivers behind spatiotemporal variations of lake areas over the Tibet Plateau have remained obscure. Selin Co Lake is the largest lake in the Qinghai–Tibet Plateau. Here, we delineate the Selin Co Lake area changes during the period of 1988–2023 based on Landsat remote sensing data. We also delved into causes behind the Selin Co Lake area changes from perspectives of glacier changes and tracing water vapor sources. We identified the persistently increasing lake area of Selin Co Lake. The Selin Co Lake area reached 2462.59 km² in 2023. We delineated the basin of Selin Co Lake and found a generally decreasing tendency of the main glaciers within the Selin Co basin. Specifically, the loss in the Geladandong Glacier area is 17.39 km² in total and the loss in the Jiagang Glacier area is 76.42 km². We found that the melting glaciers and precipitation within the Selin Co basin are the prime drivers behind the increasing the Selin Co Lake area. In the Selin Co basin, approximately 89.12% of the evaporation source of precipitation is propagated external to the Selin Co basin by the westerlies and the Indian monsoon. The internal hydrological circulation rate is 10.88%, while 30.61% of the moisture transportation is sourced from the ocean, and 69.39% is from the continental land. The moisture transportation from the ocean evaporation shows a significant increasing trend, which may contribute to the continued expansion of the Selin Co Lake area. Full article