Search Results (177)

Peatlands play a critical role in global and regional climate regulation by functioning as long-term carbon sinks, regulating hydrology, and modulating land–atmosphere energy exchange. Intact peat ecosystems store large amounts of organic carbon and stabilize local climate through high water retention and evapotranspiration, whereas peatland degradation disrupts these functions and can transform peatlands into significant sources of greenhouse gas emissions and climate extremes such as drought and fire. Indonesia contains approximately 13.6–40.5 Gt of carbon, around 40% of which is stored on the island of Sumatra. However, tropical peatlands in this region are highly vulnerable to climate anomalies and land-use change. This study investigates the impacts of major climate anomalies—specifically El Niño and positive Indian Ocean Dipole (pIOD) events in 1997/1998, 2015/2016, and 2019—on peatland cover change across South Sumatra, Jambi, Riau, and the Riau Islands. Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager/Thermal Infrared Sensor imagery were analyzed using a Random Forest machine learning classification approach. Climate anomaly periods were identified using El Niño-Southern Oscillation (ENSO) and IOD indices from the National Oceanic and Atmospheric Administration. To enhance classification accuracy and detect vegetation and hydrological stress, spectral indices including the Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI) were integrated. The results show classification accuracies of 89–92%, with kappa values of 0.85–0.90. The 2015/2016 El Niño caused the most severe peatland degradation (>51%), followed by the 1997/1998 El Niño (23–38%), while impacts from the 2019 pIOD were comparatively limited. These findings emphasize the importance of peatlands in climate regulation and highlight the need for climate-informed monitoring and management strategies to mitigate peatland degradation and associated climate risks. Full article

Vector-borne diseases are strongly influenced by climate, yet the magnitude and temporal variability of climate–disease relationships remain poorly quantified. Outbreaks occur abruptly, and responses are typically delayed, underscoring the need for predictive tools that can support proactive interventions. This study applies Temporal Fusion Transformers (TFTs) to long-term, high-resolution climate datasets and to weekly malaria and dengue case records from South Africa and Vietnam to assess predictive performance and identify key environmental drivers. The models incorporated diverse climatic predictors and large-scale climate indices and were trained using multi-horizon forecasting with novel loss functions and physics-based constraints. The best malaria model achieved an R² of 0.95 and an MAE of 4.98, while leading dengue models reached R² values up to 0.90. Variable-importance analyses derived from model-learned weights showed that extreme temperature and rainfall metrics were consistently the strongest predictors, with ENSO (El Niño Southern Oscillation) and IOD (Indian Ocean Dipole) improving longer-range malaria forecasts. Furthermore, climate–disease risk dynamics were explored, revealing specific temperature and rainfall thresholds associated with elevated transmission and highlighting non-stationary relationships across decades. These findings demonstrate accurate, interpretable forecasting offered by TFTs and represent a valuable tool for early warning and understanding of complex climate–disease interactions. Full article

Large-scale climatic oscillations (COs) modulate extreme climate events (ECEs) globally and can trigger the Indian summer monsoons and associated ECEs. In this study, we introduced a Time-dependent Intrinsic Correlation (TDIC) analysis to quantify teleconnections between five major COs—the El Niño–Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO)—and multiple extreme climate indices (ECIs) over the southern Indian Peninsula. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was employed to decompose COs and ECIs into intrinsic mode functions across varying timescales, enabling a dynamic TDIC assessment. The results revealed statistically significant correlations between COs and ECIs, with the strongest influences in low-frequency modes (>10 years). Distinct COs predominantly modulate specific ECIs (e.g., ENSO with monsoon rainfall extremes; AMO and PDO with temperature extremes). These findings advance the understanding of Indian climate system dynamics and support the development of improved ECE forecasting models. Full article

The South China Sea (SCS) sea surface temperature (SST) plays a crucial modulating effect on the climate of East Asia. While the interannual variability of South China Sea SST has been extensively examined, the decadal-scale linkages and underlying physical mechanisms between South China Sea SST and the three major ocean basins (the Atlantic, Pacific, and Indian Oceans) remain inadequately comprehended. To fill the gap, the study investigates the decadal variability of winter SST in the SCS during 1940–2023, utilizing long-term observational datasets and methods such as empirical orthogonal function decomposition, regression analysis, and teleconnections analysis. The first dominant mode of this decadal variability is characterized by basin-warming across the SCS, which is mainly driven by the Atlantic Multidecadal Oscillation (AMO, r = 0.62, p < 0.05). Specifically, the AMO imposes its remote influence on the SCS through three distinct pathways: the tropical Pacific pathway, the North Pacific pathway, and the tropical Indian Ocean pathway. These pathways collectively trigger an anomalous cyclone in the western North Pacific and SCS, and further induce basin-wide SST warming via a positive feedback that includes SST, sea level pressure, cloud cover, and longwave radiation. The second leading mode of SCS winter SST decadal variability displays a north–south dipole pattern, which is positively correlated with the Interdecadal Pacific Oscillation (IPO, r1 = 0.85, p1 < 0.05). Notably, this South China Sea SST dipole–IPO relationship weakened significantly after 1985 (r2 = 0.23, p2 < 0.05), related to the strengthening of the anomalous anticyclone over the SCS and the weakening of the anomalous cyclone over the tropical Indian Ocean. Furthermore, both the AMO and IPO influence the SST in the northern SCS by regulating wind field anomalies in the bifurcation region of the North Equatorial Current. This wind-driven modulation subsequently affects the intensity of Kuroshio intrusion into the SCS. These findings provide a novel mechanistic pathway for interpreting decadal-scale climate variability over East Asia, with implications for improving long-term climate prediction in the region. Full article

A statistical study is conducted to understand how the Mascarene High (MH) of the southwest Indian Ocean affects the springtime climate of southeastern Africa, in response to global teleconnections. A temporal index of sea-level air pressure is formed and correlated with large-scale fields of sea temperature, winds, and rainfall in the period 1980–2024. The results suggests that the MH tends to intensify and shift westward during Pacific El Niño conditions via a standing wave train in the subtropical jet stream over the South Atlantic. As this happens, anticyclonic airflow draws moisture from the Mozambique Channel and drives it onto the Kalahari plateau via low-level jets over the Limpopo and Zambezi River valleys. The Sep–Nov rainfall increases ~1 mm/day across southern Africa, accompanied by cooler temperatures and lower potential evaporation. So the spring season starts with a smaller water deficit that could favor early-planted, short-cycle crops. Outstanding questions remain on the stability of Pacific teleconnections and coupling with the Indian Ocean Dipole. Full article

Longitudinal shifts in the zonal dipole associated with the El Niño–Southern Oscillation (ENSO) in the tropical Pacific have implications for the summer climate of Southern Africa. These features are studied via Empirical Orthogonal Function analysis applied to monthly standardized sea temperatures from 1 to 100 m in depth and spanning 1980–2024. The dipole exhibits two modes: central and east Pacific. The central mode has 4–7 yr oscillations, while the east mode has a periodicity of 3 yr and 8–14 yr, with a trend toward La Niña. Correlations are mapped with environmental fields around Southern Africa. During east-mode La Niña, there are low-level westerlies over the Kalahari Plateau that coincide with a warm-west Indian Ocean and neutral summer (Dec–Mar) weather conditions over Southern Africa. The weak climatic response across the Atlantic–Indian basins during east Pacific La Niña is linked to an isolated Walker cell that feeds tropical moisture into a trough over the dateline (180° W). It is the central mode that has greater influence over Southern Africa, by triggering global Walker cells that link with the Indian Ocean Dipole. Full article

The objective of this study is to determine how easterly jets and associated convections interact over tropical North Africa during the Jul–Sep season, using reanalysis and satellite datasets for 1990–2024. Four indices are formed to describe mid- and upper-level zonal winds, and moist convection over the Sahel and India. Time-space regression identifies the large-scale features modulating the easterly jets. Cumulative departures are analyzed and ranked to form composites in east wind/convective phases and weak wind/subsident phases. The upper-level tropical easterly jet accelerates over the Arabian Sea during and after Pacific La Nina and the cool-west Indian Ocean dipole, and shows four year cycling aligned with thermocline oscillations. The mid-level Africa easterly jet strengthens during Atlantic Nino conditions that enhance the Sahel’s convection in the Jul–Sep season. Both jets accelerate when convection spreads west of India, whereas brief spells of decoupling suppress North African crop yields. The case of 15–20 August 2018 is analyzed, when a surge of Indian monsoon convection and tropical easterly jet penetrated the Sahel, leading to widespread uplift and rainfall. Full article

Tropical cyclones (TCs) over the Arabian Sea pose significant threats to coastal populations and result in substantial economic losses, yet their variability in response to major climate modes remains insufficiently understood. This study examines the relationship between the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Indo-Pacific Warm Pool (IPWP) with TC activity over the Arabian Sea from 1982 to 2021. Utilizing the India Meteorological Department (IMD)’s best-track data, reanalysis datasets, and composite analysis, we find that ENSO and IOD phases affect TC activity differently across seasons. The pre-monsoon season shows a limited association between TC activity and both ENSO and IOD, with minimal variation in frequency, intensity, and energy metrics. However, during the post-monsoon season, El Niño enhances TC intensity, resulting in a higher frequency of intense storms, leading to increased accumulated cyclone energy (ACE) and power dissipation index (PDI) in a statistically significant way. In contrast, La Niña favors the development of weaker TC systems and an increased frequency of depressions. While negative IOD (nIOD) phases tend to suppress TC formation, positive IOD (pIOD) phases are associated with increased TC activity, characterized by longer durations and higher ACE and PDI (statistically significant). Genesis sites shift with ENSO: El Niño favors genesis in the eastern Arabian Sea, causing westward or northeastward tracks, while La Niña shifts genesis toward the central-western basin, promoting northwestward movement. Composite analysis indicates that higher sea surface temperatures (SSTs), reduced vertical wind shear (VWS), increased mid-tropospheric humidity, and lower sea level pressure (SLP) during El Niño and pIOD phases create favorable conditions for TC intensification. In contrast, La Niña and nIOD phases are marked by drier mid-level atmospheres and less favorable SST patterns. The Indo-Pacific Warm Pool (IPWP), particularly its westernmost edge in the southeastern Arabian Sea, provides a favorable thermodynamic environment for genesis and exhibits a moderate positive correlation with TC activity. Nevertheless, its influence on interannual variability over the basin is less significant than that of dominant large-scale climate patterns like ENSO and IOD. These findings highlight the critical role of SST-related teleconnections (ENSO, IOD, and IPWP) in regulating Arabian Sea TC activity, offering valuable insights for seasonal forecasting and risk mitigation in vulnerable areas. Full article

El Niño fundamentally elevates the southern South China Sea (SSCS) winter sea surface temperature (SST), and this relationship exhibits significant interdecadal modulation by the Pacific Decadal Oscillation (PDO). Correlation analyses reveal a negative linkage between El Niño-SSCS SST relationship and PDO index (r = −0.5, p < 0.05). Mechanistically, negative PDO phase reconfigures the multi-anticyclone system: a weaker and northeastward-shifted Philippine Sea anticyclone (PSAC, 25° poleward), dissipating northern Indian Ocean anticyclone (NIOAC) and persistent southeastern Indian Ocean anticyclone (SEIOAC) through a reduction in Aleutian low and El Niño intensity. In the negative-minus-positive PDO phase composite, this drives anomalous southerlies/southwesterlies over the SSCS, establishing a zonal SST dipole (west-cooling/east-warming; −0.1 °C/+0.2 °C east/west of 108° E). Ekman dynamics (positive/negative wind stress curl west/east of 108° E), horizontal heat advection and latent heat flux (driven by southwesterly wind) dominate the SST dipole formation. From December to February, Aleutian low suppression and El Niño decay progressively modify the multi-anticyclone system configuration and replace southerly anomalies with northerlies, reducing regional warm SST in the N-P composite. The multi-anticyclone system thus mediates SSCS SST interannual variability, with critical implications for marine predictability under climate oscillations. Full article

Since the 1980s, earlier European springs have led to the earlier arrival of migrant passerines. We predict that arrival is related to a suite of climate indices operating during the annual cycle (breeding, autumn migration, wintering, spring migration) in Europe and Africa over the year preceding arrival. The climate variables include the Indian Ocean Dipole (IOD), Southern Oscillation Index (SOI), and North Atlantic Oscillation (NAO). Furthermore, because migrants arrive sequentially from different wintering areas across Africa, we predict that relationships with climate variables operating in different parts of Africa will change within the season. We tested this using daily ringing data at Bukowo, a spring stopover site on the Baltic coast. We calculated an Annual Anomaly (AA) of spring passage (26 March–15 May, 1982–2024) for four long-distance migrants (Blackcap, Lesser Whitethroat, Willow Warbler, Chiffchaff). We decomposed the anomaly in two ways: into three independent main periods and nine overlapping periods. We used multiple regression to explore the relationships of the arrival of these species at Bukowo. We found sequential effects of climate indices. Bukowo is thus at a crossroads of populations arriving from different wintering regions. The drivers of phenological shifts in passage of wide-ranging species are related to climate indices encountered during breeding, wintering, and migration. Full article

In a warming climate, rising temperature are expected to influence atmospheric humidity. This study examined the spatio-temporal dynamics of temperature (TEMP) and relative humidity (RH) across Equatorial Africa from 1980 to 2020. The analysis used RH data from European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) reanalysis, TEMP and precipitation (PRE) from Climate Research Unit (CRU), and soil moisture (SM) and evapotranspiration (ET) from the Global Land Evaporation Amsterdam Model (GLEAM). In addition, four teleconnection indices were considered: El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO). This study used the Mann–Kendall test and Sen’s slope estimator to analyze trends, alongside multiple linear regression to investigate the relationships between TEMP, RH, and key climatic variables—namely evapotranspiration (ET), soil moisture (SM), and precipitation (PRE)—as well as large-scale teleconnection indices (e.g., IOD, ENSO, PDO, and NAO) on annual and seasonal scales. The key findings are as follows: (1) mean annual TEMP exceeding 30 °C and RH less than 30% were concentrated in arid regions of the Sahelian–Sudano belt in West Africa (WAF), Central Africa (CAF) and North East Africa (NEAF). Semi-arid regions in the Sahelian–Guinean belt recorded moderate TEMP (25–30 °C) and RH (30–60%), while the Guinean coastal belt and Congo Basin experienced cooler, more humid conditions (TEMP < 20 °C, RH (60–90%). (2) Trend analysis using Mann–Kendal and Sen slope estimator analysis revealed spatial heterogeneity, with increasing TEMP and deceasing RH trends varying by region and season. (3) The warming rate was higher in arid and semi-arid areas, with seasonal rates exceeding annual averages (0.18 °C decade⁻¹). Winter (0.27 °C decade⁻¹) and spring (0.20 °C decade⁻¹) exhibited the strongest warming, followed by autumn (0.18 °C decade⁻¹) and summer (0.10 °C decade⁻¹). (4) RH trends showed stronger seasonal decline compared to annual changes, with reduction ranging from 5 to 10% per decade in certain seasons, and about 2% per decade annually. (5) Pearson correlation analysis demonstrated a strong negative relationship between TEMP and RH with a correlation coefficient of r = − 0.60. (6) Significant associations were also observed between TEMP/RH and both climatic variables (ET, SM, PRE) and large scale-teleconnection indices (ENSO, IOD, PDO, NAO), indicating that surface conditions may reflect a combination of local response and remote climate influences. However, further analysis is needed to distinguish the extent to which local variability is independently driven versus being a response to large-scale forcing. Overall, this research highlights the physical mechanism linking TEMP and RH trends and their climatic drivers, offering insights into how these changes may impact different ecological and socio-economic sectors. Full article

Based on the Clouds and the Earth’s Radiant Energy System (CERES) satellite data from 2001 to 2023 and the climate indices from the National Oceanic and Atmospheric Administration (NOAA), this study analyzes the solar irradiance over mainland China and the impacts of clouds and aerosols on it and constructs monthly forecasting models to analyze the influence of climate indices on irradiance forecasts. The irradiance over mainland China shows a spatial distribution of being higher in the west and lower in the east. The influence of clouds on irradiance decreases from south to north, and the influence of aerosols is prominent in the east. The average explained variance of clouds on irradiance is 86.72%, which is much higher than that of aerosols on irradiance, 15.62%. Singular Value Decomposition (SVD) analysis shows a high correlation between the respective time series of irradiance and cloud influence, with the two fields having similar spatial patterns of opposite signs. The variation in solar irradiance can be attributed mainly to the influence of clouds. Empirical Orthogonal Function (EOF) analysis indicates that the variation in the first mode of irradiance is consistent in most parts of China, and its time coefficient is selected for monthly forecasting. Both the traditional multiple linear regression method and the Long Short-Term Memory (LSTM) network are used to construct monthly forecast models, with the preceding time coefficient of the first EOF mode and different climate indices as input. Compared with the multiple linear regression method, LSTM has a better forecasting skill. When the input length increases, the forecasting skill decreases. The inclusion of climate indices, such as the Indian Ocean Basin (IOB), El Nino–Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD), can enhance the forecasting skill. Among these three indices, IOB has the most significant improvement effect. The research provides a basis for accurate forecasting of solar irradiance over China on monthly time scale. 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

As important components of the equatorial current system in the Indian Ocean, Wyrtki jets (WJs) play a significant role in distributing heat and matter in the East and West Indian Oceans. By dividing the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events into several phases, we find that the spring branch exhibits positive (negative) anomalies during the El Niño (La Niña) decaying phase, while the fall branch exhibits negative (positive) anomalies during the El Niño (La Niña) developing phase. The spring and fall branches are characterized by negative (positive) anomalies under the influence of positive (negative) dipole events, and these anomalies are particularly pronounced during fall. This study systematically analyzes the characteristics of WJs under the interactions between the Indo-Pacific ocean and the atmosphere, based on the phase-locking characteristics of ENSO, and reveals the regulatory mechanisms underlying their different response patterns. 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