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This study aims to monitor the implications of climate change on savanna ecosystem drought using time series data from the Landsat 8 sensor, spanning from 2013 to 2022. We employed a remote sensing computational approach with the semi-automatic classification plugin (SCP) in the open-source QGIS software. Specifically, we utilized channels from the operational land imager (OLI), including Band 4 Red (0.636-0.673 µm) and Band 5 Near-Infrared (0.851-0.879 µm), as well as Thermal Infrared Sensor (TIRS) channels Band 10 TIRS-1 (10.60-11.19 µm) and Band 11 TIRS-2 (11.50-12.51 µm). These channels were used to calculate the vegetation health index (VHI) using the raster calculator, followed by data reclassification with specific thresholds to compare drought-affected areas. Our findings reveal a significant impact of climate change on savanna ecosystem drought over the decade, with the most extreme conditions observed in 2015 and 2019, where drought coverage reached 42.74% and 26.58%, respectively. Other years exhibited relatively low drought dynamics, affecting less than 3% of the area. This period aligns with the el niño-southern oscillation (ENSO) phenomenon, particularly the transition from El Niño to La Niña, known to cause global weather variations, and significantly influenced by the positive phase of the Indian Ocean dipole (IOD). The novelty of this research lies in two main aspects: firstly, the use of Landsat satellite sensors for this specific region has not been extensively studied before; secondly, the discovered impacts of drought in relation to global climate change phenomena are particularly noteworthy. A limitation of this study is the relatively short investigation period of just one decade, which does not fully capture the long-term impacts of climate change. Future research is recommended to utilize imagery with higher temporal resolution over extended periods to better represent extreme climate events and derive drought patterns over durations exceeding one decade. [ABSTRACT FROM AUTHOR]

The Indonesian Throughflow (ITF) is significantly modulated by Indo-Pacific climate forcing, especially the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). However, when ENSO and IOD occur concurrently, they tend to play different roles in the ITF volume transport. By employing an improved Constructed Circulation Analogue (CCA) method, the relative contributions of these climate events to the ITF inflow and outflow transport in the upper and lower layers were quantified. The results indicate that during co-occurring El Niño and positive IOD events, ENSO is the dominant influence, with ratio values of 5.5:1 (3.5:1) in the upper layer and 1.7:1 (1.6:1) in the lower layer of the inflow (outflow). Conversely, during co-occurring La Niña and negative IOD events, the IOD predominates, with ratio values of 1:6 (1:6.5) in the upper layer and 1:4 (1:3) in the lower layer of the inflow (outflow). The mechanisms underlying these variations in the upper and lower layers can be explained by the differences in sea level anomaly (SLA) and wave propagation, respectively. This study provides a new insight into distinct roles of climate forcing on the ITF volume transport during the simultaneous occurrence of multiple climate modes. [ABSTRACT FROM AUTHOR]

Earlier proxy‐observational studies, and a sole modeling study, suggest that the Indian Ocean Dipole (IOD), an important global climate driver, exhibited multi‐scale temporal variability during the Last Millennium (LM; CE 0851–1849, with relatively high number of strong positive IOD events during the Little Ice Age (LIA; CE 1550–1749), and strong negative IOD events during the Medieval Warm Period (MWP; CE 1000–1199). Using nine model simulations from the PMIP3, we study the IOD variability during the LM after due validation of the simulated current day (CE 1850–2005) IOD variability. Majority of the models simulate relatively higher number of positive IOD events during the MWP, and negative IOD events in the LIA, commensurate with simulated background conditions. However, higher number of strong positive IOD events are simulated relative to the negative IODs during the LIA, in agreement with proxy‐observations, apparently owing to increased coupled feedback during positive IODs. Plain Language Summary: The Indian Ocean Dipole (IOD) is a natural climate phenomenon in the tropical Indian Ocean with significant global impacts. Positive IOD (pIOD) events are apparently occurring more frequently in recent decades, which may also be due to under‐sampling associated with limited observations span. Analyzing outputs for last millennium (CE 850–1850) from climate models, validated for historical period, helps in generating relatively longer‐period the paleo‐IOD records. Our analysis of simulations of the last thousand years from multiple models indicates relatively more positive (negative) IOD events in medieval warm period—CE 1000–1200 (Little Ice Age—CE 1550–1749). While during the ICA, background conditions similar to a negative IOD were simulated, models also simulate an increase in relatively‐stronger positive IOD events in its latter part, in agreement with a proxy‐climate record. The simulated centennial changes in positive and negative IOD frequencies are associated with changes in coupled ocean‐atmospheric feedback mechanisms. Key Points: Change in the Indian Ocean mean state from the medieval warm period (MWP) to the Little Ice Age (LIA)Despite negative IOD‐like background conditions in the LIA, models and paleo‐data show more stronger positive IODs thenThere are significant changes in feedback mechanisms of IODs from the MWP to LIA [ABSTRACT FROM AUTHOR]

In this study, we employ the Conformal Cubic Atmospheric Model (CCAM), a variable‐resolution global atmospheric model, driven by two distinct sea surface temperature (SST) data sets: the 0.25° Optimum Interpolation Sea Surface Temperature (CCAM_OISST) version 2.1 and the 2° Extended Reconstruction SSTs Version 5 (CCAM_ERSST5). Model performance is assessed using a benchmarking framework, revealing good agreement between both simulations and the climatological rainfall spatial pattern, seasonality, and annual trends obtained from the Australian Gridded Climate Data (AGCD). Notably, wet biases are identified in both simulations, with CCAM_OISST displaying a more pronounced bias. Furthermore, we have examined CCAM's ability to capture El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) correlations with rainfall during Austral spring (SON) utilizing a novel hit rate metric. Results indicate that only CCAM_OISST successfully replicates observed SON ENSO‐ and IOD‐rainfall correlations, achieving hit rates of 86.6% and 87.5%, respectively, compared to 52.7% and 41.8% for CCAM_ERSST5. Large SST differences are found surrounding the Australian coastline between OISST and ERSST5 (termed the "Coastal Effect"). Differences can be induced by the spatial interpolation error due to the discrepancy between model and driving SST. An additional CCAM experiment, employing OISST with SST masked by ERSST5 in 5° proximity to the Australian continent, underscores the "Coastal Effect" has a significant impact on IOD‐Australian rainfall simulations. In contrast, its influence on ENSO‐Australian rainfall is limited. Therefore, simulations of IOD‐Australian rainfall teleconnection are sensitive to local SST representation along coastlines, probably dependent on the spatial resolution of driving SST. Plain Language Summary: In this research, the Conformal Cubic Atmospheric Model (CCAM), a global atmospheric model, is used to study the impact of different driving sea surface temperature (SST) data sets on Australian rainfall simulations. Two SST data sets, one with high resolution (OISST) and another at lower resolution (ERSST5), are employed to drive CCAM (CCAM_OISST and CCAM_ERSST5). Model performance is evaluated using a benchmarking approach, indicating that both SST‐driven experiments are in good agreement with observed rainfall patterns in Australia. However, both simulations exhibit wet biases, with CCAM_OISST having a more noticeable bias. The study assesses CCAM's ability to capture the correlation between El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) with rainfall during Austral spring. Results reveal that CCAM_OISST performs better, replicating observed correlations more accurately than CCAM_ERSST5. The research identifies strong SST differences found between OISST and ERSST5 around the Australian coastline. An additional experiment underscores that this "Coastal Effect" plays an important role in simulating IOD‐Australian rainfall correlations, while its impact on ENSO‐Australian rainfall is limited. In conclusion, robust simulations of IOD‐Australian rainfall teleconnection require an accurate representation of local SST, which is related to the spatial resolution of SST products driving the model. Key Points: Novel hit rate metrics are proposed to evaluate El Niño‐Southern Oscillation and Indian Ocean Dipole‐rainfall teleconnectionsCCAM driven by different SST performs well in mean rainfall but ENSO and IOD related rainfall varies substantially over AustraliaResolution of the driving sea surface temperature is important to simulate IOD‐rainfall variability over Australia [ABSTRACT FROM AUTHOR]

Abstract Earlier proxy‐observational studies, and a sole modeling study, suggest that the Indian Ocean Dipole (IOD), an important global climate driver, exhibited multi‐scale temporal variability during the Last Millennium (LM; CE 0851–1849, with relatively high number of strong positive IOD events during the Little Ice Age (LIA; CE 1550–1749), and strong negative IOD events during the Medieval Warm Period (MWP; CE 1000–1199). Using nine model simulations from the PMIP3, we study the IOD variability during the LM after due validation of the simulated current day (CE 1850–2005) IOD variability. Majority of the models simulate relatively higher number of positive IOD events during the MWP, and negative IOD events in the LIA, commensurate with simulated background conditions. However, higher number of strong positive IOD events are simulated relative to the negative IODs during the LIA, in agreement with proxy‐observations, apparently owing to increased coupled feedback during positive IODs.

Wind speed is an important parameter reflecting the climate and environmental conditions on the Earth's surface. It is also a pivotal factor influencing wind energy, a renewable and clean energy source. The mechanisms exerting influence on the surface wind speed over China, which have been mentioned in previous studies, include the temperature difference between the high and low latitudes of China, surface drag force, and climatic factors such as the Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), and El Niño-Southern Oscillation (ENSO). The Indian Ocean Dipole (IOD), which has attracted increasing attention during the past two decades, is an important climatic factor that exerts a significant influence on the climate and environment in the areas surrounding the Indian Ocean and globally. However, to date, it has not been reported whether the IOD is a climatic factor that significantly affects surface wind speed in China. Coastal South China is one of the most economically developed areas in China, and wind energy is becoming an important energy source in this area. An investigation of the relationship between the IOD and wind speed variations in coastal South China and their connecting mechanisms would contribute substantially to the understanding of the controlling mechanisms of climatic and environmental variations in coastal South China as well as to the planning of sustainable development in this area. Based on observations of surface wind speed in coastal South China, reanalysis data from the National Center of Environment Prediction (NCEP) and the National Center of Atmospheric Research (NCAR), research on the IOD over the last two decades, the effects of IOD activities on surface wind speed in coastal South China, and the controlling mechanisms were investigated using statistical analyses and atmospheric circulation variations. The results indicate that, regardless of the temporal or spatial scale, variations in the surface wind speed in coastal South China show significant positive correlations with the dipole mode index (DMI), which is a proxy for IOD activity. An increase in the DMI index (indicating a strengthening of IOD activity) corresponds to a decrease in the surface wind speed in coastal South China, and vice versa. This suggests that, in addition to the factors suggested in previous studies, which include the temperature difference between high and low latitudes, AO, PDO, and ENSO, IOD activity is also one of the most important factors affecting surface wind speed variation in coastal South China. The influence of IOD activity was weaker than that of the temperature difference between high and low latitudes. However, it played a more important role in the surface wind speed variation in this region than the AO, PDO, and ENSO. Strengthening of the IOD activity would enhance two anti-cyclones in the northwest Pacific and Bengal Bay, east of the Indian subcontinent, and, in turn, contribute to the reduction of surface wind speed variation in coastal South China. More serious global warming and increasing greenhouse gas emissions will further strengthen IOD activity in the future. Consequently, a greater decline in surface wind speed is expected in coastal South China, necessitating attention to sustainable wind energy use in this region.

Wind speed is an important parameter reflecting the climate and environmental conditions on the Earth's surface. It is also a pivotal factor influencing wind energy, a renewable and clean energy source. The mechanisms exerting influence on the surface wind speed over China, which have been mentioned in previous studies, include the temperature difference between the high and low latitudes of China, surface drag force, and climatic factors such as the Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), and El Niño-Southern Oscillation (ENSO). The Indian Ocean Dipole (IOD), which has attracted increasing attention during the past two decades, is an important climatic factor that exerts a significant influence on the climate and environment in the areas surrounding the Indian Ocean and globally. However, to date, it has not been reported whether the IOD is a climatic factor that significantly affects surface wind speed in China. Coastal South China is one of the most economically developed areas in China, and wind energy is becoming an important energy source in this area. An investigation of the relationship between the IOD and wind speed variations in coastal South China and their connecting mechanisms would contribute substantially to the understanding of the controlling mechanisms of climatic and environmental variations in coastal South China as well as to the planning of sustainable development in this area. Based on observations of surface wind speed in coastal South China, reanalysis data from the National Center of Environment Prediction (NCEP) and the National Center of Atmospheric Research (NCAR), research on the IOD over the last two decades, the effects of IOD activities on surface wind speed in coastal South China, and the controlling mechanisms were investigated using statistical analyses and atmospheric circulation variations. The results indicate that, regardless of the temporal or spatial scale, variations in the surface wind speed in coastal South China show significant positive correlations with the dipole mode index (DMI), which is a proxy for IOD activity. An increase in the DMI index (indicating a strengthening of IOD activity) corresponds to a decrease in the surface wind speed in coastal South China, and vice versa. This suggests that, in addition to the factors suggested in previous studies, which include the temperature difference between high and low latitudes, AO, PDO, and ENSO, IOD activity is also one of the most important factors affecting surface wind speed variation in coastal South China. The influence of IOD activity was weaker than that of the temperature difference between high and low latitudes. However, it played a more important role in the surface wind speed variation in this region than the AO, PDO, and ENSO. Strengthening of the IOD activity would enhance two anti-cyclones in the northwest Pacific and Bengal Bay, east of the Indian subcontinent, and, in turn, contribute to the reduction of surface wind speed variation in coastal South China. More serious global warming and increasing greenhouse gas emissions will further strengthen IOD activity in the future. Consequently, a greater decline in surface wind speed is expected in coastal South China, necessitating attention to sustainable wind energy use in this region. [ABSTRACT FROM AUTHOR]

Negative Indian Ocean Dipole (nIOD) can exert great impacts on global climate and can also strongly influence the climate in China. Early nIOD is a major type of nIOD, which can induce more pronounced climate anomalies in summer than La Niña-related nIOD. However, the characteristics and triggering mechanisms of early nIOD are unclear. Our results based on reanalysis datasets indicate that the early nIOD and La Niña-related nIOD are the two major types of nIOD, and the former accounts for over one third of all the nIOD events in the past six decades. These two types of nIODs are similar in their intensities, but are different in their spatial patterns and seasonal cycles. The early nIOD, which develops in spring and peaks in summer, is one season earlier than the La Niña-related nIOD. The spatial pattern of the wind anomaly associated with early nIOD exhibits a winter monsoon-like pattern, with strong westerly anomalies in the equatorial Indian Ocean and eastly anomalies in the northern Indian Ocean. Opposite to the triggering mechanism of early positve IOD, the early nIOD is induced by delayed Indian summer monsoon onset. The results of this study are helpful for improving the prediction skill of IOD and its climate impacts. [ABSTRACT FROM AUTHOR]

The Indonesian Throughflow (ITF) is significantly modulated by Indo-Pacific climate forcing, especially the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). However, when ENSO and IOD occur concurrently, they tend to play different roles in the ITF volume transport. By employing an improved Constructed Circulation Analogue (CCA) method, the relative contributions of these climate events to the ITF inflow and outflow transport in the upper and lower layers were quantified. The results indicate that during co-occurring El Niño and positive IOD events, ENSO is the dominant influence, with ratio values of 5.5:1 (3.5:1) in the upper layer and 1.7:1 (1.6:1) in the lower layer of the inflow (outflow). Conversely, during co-occurring La Niña and negative IOD events, the IOD predominates, with ratio values of 1:6 (1:6.5) in the upper layer and 1:4 (1:3) in the lower layer of the inflow (outflow). The mechanisms underlying these variations in the upper and lower layers can be explained by the differences in sea level anomaly (SLA) and wave propagation, respectively. This study provides a new insight into distinct roles of climate forcing on the ITF volume transport during the simultaneous occurrence of multiple climate modes.

Teleconnection events can influence normal regional weather patterns and affect weather forecast accuracy. To improve the forecast ability, the relationship between main teleconnections such as El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Madden–Julian Oscillation (MJO), and climate variables (rainfall, maximum and minimum surface temperature, vertical mixing ratio, and vertical maximum temperature) was established using lag correlation coefficient and t-test methods. The results reveal moderately significant correlations between El Niño, positive IOD and rainfall, and vertical mixing ratio, which can be associated with lower-than-usual rainfall. The coincidence between El Niño and positive IOD events can worsen drought. Even though the MJO and regional weather correlations were significant, the magnitude of correlation coefficients was negligible. In addition, the spatiotemporal distribution of ENSO shows that the strong El Niño has more influence on rainfall anomalies in the post-1980s. Since there are insufficient studies on the association between teleconnections and climate variables, especially vertical mixing ratio, our findings can benefit prediction development for teleconnection-induced regional climate anomalies for extreme events and water management preparations in northern and northeastern Thailand. HIGHLIGHTS ENSO events have significant correlations in northern compared with northeastern Thailand.; El Niño, positive IOD, and climate variables have significant negative correlations in the dry season in northern Thailand.; La Niña, negative IOD, and climate variables have a less significant negative correlation in northern and northeastern Thailand.; MJO has significant correlations with rainfall and temperature.;

The synergistic effects of the Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) have been investigated in this study over various subregions of India during 1981–2015. The IOD, is aperiodic and erratic, still this phenomenon is intrinsic in nature dependent on coupled ocean and atmospheric characteristics of the Indian ocean. About 60% of the IOD events showed its coexistence with ENSO during the 35-year recent climatology, still 40% of IOD events are independently occurring. For this analysis, the strongest three positive IOD (1994, 1997, 2006) and three negative IOD (1996, 1998, 2010) events have been identified that co-occurred with El-Nino and La-Nina events respectively. This study reveals that pIOD events are stronger and but the nIOD events are frequent and effecting Indian Summer Monsoon Rainfall (ISMR). The Sea Surface Temperature (SST) anomalies helps in explaining how strong pIOD favors moisture transport towards the western ghats, central India, northwest India, and anticyclonic conditions in the Bay of Bengal area whereas nIOD produces less rainfall in central India and the western ghats, but greater rainfall in the northeastern region. The reduced ENSO-IOD coupling in the 2000s may have strengthened the connection between ENSO and the Indian Summer Monsoon (ISMR), which had experienced a weakening in preceding decades, as reported by Kumar et al. (Science 284:2156–2159, 1999) and Ashok et al. (Geophys Res Lett 28:4499–4502, 2001). This study also investigates whether a regional climate model (RegCM4.7) accurately incorporate the realistic ENSO-IOD coupling mechanisms, and simulate its impact on regionalized precipitation during summer monsoon. The high-resolution RegCM4.7 simulations are close to the observation of rainfall during 2006, 1996 and 2010 extreme IOD events simulation that indicate RCM's higher sensitivity towards the abrupt change in boundary condition such as SST. Overall, the monsoon core regions i.e., central India, western ghats and northeast India, both IOD and southern oscillations are the synergistic predictor for the ISMR. [ABSTRACT FROM AUTHOR]

The Indonesian Throughflow (ITF), which connects the tropical Pacific and Indian oceans, plays important roles in the inter-ocean water exchange and regional or even global climate variability. The Makassar Strait is the main inflow passage of the ITF, carrying about 77% of the total ITF volume transport. In this study, we analyze the simulated ITF in the Makassar Strait in the Simple Ocean Data Assimilation version 3 (SODA3) datasets. A total of nine ensemble members of the SODA3 datasets, of which are driven by different surface forcings and bulk formulas, and with or without data assimilation, are used in this study. The annual mean water transports (i.e., volume, heat and freshwater) are related to the combination of surface forcing and bulk formula, as well as whether data assimilation is employed. The phases of the seasonal and interannual variability in water transports cross the Makassar Strait, are basically consistent with each other among the SODA3 ensemble members. The interannual variability in Makassar Strait volume and heat transports are significantly correlated with El Niño-Southern Oscillation (ENSO) at time lags of -6 to 7 months. There is no statistically significant correlation between the freshwater transport and the ENSO. The Makassar Strait water transports are not significantly correlated with the Indian Ocean Dipole (IOD), which may attribute to model deficiency in simulating the propagation of semiannual Kelvin waves from the Indian Ocean to the Makassar Strait. [ABSTRACT FROM AUTHOR]

Climate variability has distinct spatial patterns with the strongest signal of sea surface temperature (SST) variance residing in the tropical Pacific. This interannual climate phenomenon, the El Niño-Southern Oscillation (ENSO), impacts weather patterns across the globe via atmospheric teleconnections. Pronounced SST variability, albeit of smaller amplitude, also exists in the other tropical basins as well as in the extratropical regions. To improve our physical understanding of internal climate variability across the global oceans, we here make the case for a conceptual model hierarchy that captures the essence of observed SST variability from subseasonal to decadal timescales. The building blocks consist of the classic stochastic climate model formulated by Klaus Hasselmann, a deterministic low-order model for ENSO variability, and the effect of the seasonal cycle on both of these models. This model hierarchy allows us to trace the impacts of seasonal processes on the statistics of observed and simulated climate variability. One of the important outcomes of ENSO's interaction with the seasonal cycle is the generation of a frequency cascade leading to deterministic climate variability on a wide range of timescales, including the near-annual ENSO Combination Mode. Using the aforementioned building blocks, we arrive at a succinct conceptual model that delineates ENSO's ubiquitous climate impacts and allows us to revisit ENSO's observed statistical relationships with other coherent spatio-temporal patterns of climate variability—so called empirical modes of variability. We demonstrate the importance of correctly accounting for different seasonal phasing in the linear growth/damping rates of different climate phenomena, as well as the seasonal phasing of ENSO teleconnections and of atmospheric noise forcings. We discuss how previously some of ENSO's relationships with other modes of variability have been misinterpreted due to non-intuitive seasonal cycle effects on both power spectra and lead/lag correlations. Furthermore, it is evident that ENSO's impacts on climate variability outside the tropical Pacific are oftentimes larger than previously recognized and that accurately accounting for them has important implications. For instance, it has been shown that improved seasonal prediction skill can be achieved in the Indian Ocean by fully accounting for ENSO's seasonally modulated and temporally integrated remote impacts. These results move us to refocus our attention to the tropical Pacific for understanding global patterns of climate variability and their predictability. [ABSTRACT FROM AUTHOR]

There is a vast upwelling area induced by the southeast monsoon in the waters off South Java, making the region an important fishing ground. Climate events can affect the variation of upwelling, but oceanographers have different understandings on the extent to which climate events control upwelling in this area, which leads to a lack of basis for studies on the evaluation and mechanisms of the variability of fishery resources in the region. The correlation between environmental parameters, including surface temperature (SST), chlorophyll-a (Chl-a) concentration, and climate event indices in South Java from 2003 to 2020 was analyzed. Results show that the Indian Ocean Dipole (IOD) has a greater influence on the interannual variability of upwelling intensity than ENSO. During the IOD, variations in equatorial latitudinal winds excite different types of Kelvin waves that anomalously deepen or shallow the thermocline, which is the main cause of anomalous variations in upwelling, independent of variations in the local wind field. A correlation between the interannual variability in upwelling and the annual catches was revealed, showing that climatic events indirectly affect fishery resources through upwelling effects. During positive IOD/El Niño periods, strong upwelling delivers more nutrients to the surface layer, which favors fish growth and reproduction, resulting in higher annual catches. A negative IOD/La Niña, on the other hand, leads to weaker upwelling and fewer nutrients into the surface waters. Fish tend to move in deeper waters, making traditional fishing methods less efficient and consequently lower annual catches. [ABSTRACT FROM AUTHOR]

IntroductionThe Indonesian Throughflow (ITF) connects the Pacific Ocean and the Indian Ocean. It plays an important role in the global ocean circulation system. The interannual variability of ITF transport is largely modulated by climate modes, such as Central-Pacific (CP) and Eastern-Pacific (EP) El Niño and Indian Ocean Dipole (IOD). However, the relative importance of these climate modes importing on the ITF is not well clarified.MethodsDominant roles of the climate modes on ITF in specific periods are quantified by combining a machine learning algorithm of the random forest (RF) model with a variety of reanalysis datasets.ResultsThe results reveal that during the period from 1993 to 2019, the average ITF transport derived from high-resolution reanalysis datasets is -14.97 Sv with an intensification trend of -0.06 Sv year-1, which mainly occurred in the upper layer. Four periods, which are 1993–2000, 2002–2008, 2009–2012 and 2013–2019, are identified as Niño 3.4, Dipole Mode Index (DMI), no significant dominant index, and DMI dominated, respectively.DiscussionThe corresponding sea surface height differences between the Northwest Tropical Pacific Ocean (NWP) and Southeast Indian Ocean (SEI) in these three periods when exist dominant index are -0.50 cm, 0.99 cm and -3.22 cm, respectively, which are responsible for the dominance of the climate modes. The study provides a new insight to quantify the response of ITF transport to climate drivers.

The South China Sea (SCS) summer monsoon (SCSSM) and Western North Pacific tropical cyclones (TCs) are both tropical systems that interact with each other on multiple scales. This study examines the differences in TCs activity characteristics between anomalous strong and weak SCSSM years, and explores the possible mechanisms behind these differences through the coupling relationship between tropical atmospheric circulation and oceanic surface conditions. Results show that the destructiveness of TCs over the Western North Pacific is stronger during weak SCSSM years than in strong years, whereas the opposite occurs for TCs over the SCS. The interaction between the tropical Indo-Pacific ocean and atmosphere plays a key role in the relationship between SCSSM intensity and TCs activity. In strong (weak) SCSSM years, the sea surface temperature anomaly (SSTA) in the tropical Pacific Ocean tends to correspond to a La Niña-like (El Niño-like) distribution, whereas the tropical Indian Ocean shows an Indian Ocean dipole-negative (positive) phase distribution. Moreover, Walker circulations in both the Indian and Pacific Oceans are coupled during these years, which creates a seesaw-like relationship in the conditions for TCs formation between the SCS and the Western Pacific Ocean. During weak SCSSM years, the formation and activity of TCs over the SCS are suppressed due to the weakened water vapor transport caused by abnormal easterly winds from the eastern Indian Ocean to the southern SCS. Meanwhile, the higher SSTA in the Western Pacific Ocean enhances the TCs activity. In strong SCSSM years, the enhanced monsoon drives a stronger monsoon trough, improving the convective environment over the SCS, whereas in contrast, the Western Pacific Ocean is covered by colder water, resulting in poorer conditions for TCs genesis. [ABSTRACT FROM AUTHOR]

The Southern Indonesian (SI) region is known for its high-intensity coastal upwelling caused by monsoonal wind. Interannual phenomena such as El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) also influence upwelling activity in this region. This study analyzed the relationship between upwelling intensity (UI sst) and those variables and their impact on oceanographic features such as Sea Surface Temperature (SST) and chlorophyll-a concentration. We used satellite imagery data, including SST from the National Oceanic and Atmospheric Administration (NOAA) and chlorophyll-a from MODIS, to analyze the aforementioned issue. To identify the impact of wind patterns on coastal upwelling, we analyzed using zonal wind stress from ERA-5 Data. Quantification of UI sst is defined as the SST gradient between the coastal and open ocean waters. Linear and partial correlation analysis between UI sst with the Ocean Niño Index (ONI) and Dipole Mode Index (DMI) were conducted to see the influence of ENSO and IOD phenomena. Anomaly analysis was also conducted on SST, chlorophyll-a concentration, zonal windstress and UI sst to see how large the values were during the years of the ENSO and IOD events. Upwelling in the SI region typically occurs during southeast monsoon (SEM) periods, starting earlier in the East side (Nusa Tenggara Islands) and moving towards the West side (South Coast of Java). The correlation analysis (both linear and partial) indicates that the IOD has a stronger influence on UI sst in the SI region compared to ENSO, especially during June to October (SEM periods). This finding is confirmed by anomaly analysis, which reveals significant changes in SST, chlorophyll-a concentration, zonal windstress, and UI sst during ENSO and IOD events. The magnitude of the anomalies is generally stronger during IOD events than those observed under ENSO conditions. • Remote sensing satellite data can identify the variability of upwelling phenomena in the Southern Indonesian (SI) seas. • The strength of upwelling intensity in SI is strongly influenced by Interannual phenomena such as the ENSO and IOD. • Sea Surface Temperature and Chlorophyll-a anomalies confirm the influence of changes in upwelling intensity by ENSO and IOD. • IOD has a stronger influence than ENSO on Upwelling intensity in the SI Region. [ABSTRACT FROM AUTHOR]

Long-term change in the timing of coastal upwelling due to climate variations alters the heat budget and biogeochemical balance in the regional ocean and is an important issue in local fisheries. In this study, we investigated decadal changes in the onset of coastal upwelling along the southern coast of Java over the past two decades (2003–2020) based on the timing of chlorophyll-a (Chl-a) bloom. We estimated the bloom from satellite Chl-a concentration data. On average, the onset of coastal upwelling observed (the first Chl-a bloom of the year) was around mid-June. In the most recent decade (2011–2020), earlier-onset upwelling (before early June) was observed frequently, and the linear trend for the onset date during 2003–2020 was about 2 weeks earlier/decade. To explore the causes of the change in the timing of the upwelling, we focused on the season (April–June) during which these earlier upwelling onsets occurred, and investigated decadal changes in atmosphere and ocean conditions associated with climate change. While sea surface temperature (SST) trends reflected a basin-wide warming pattern in the Indian Ocean, warming was not significant in the southeastern Indian Ocean. During the onset period of coastal upwelling, significant SST warming trends were also observed west of Sumatra. In association with the SST warming pattern, enhanced convective activity and convergent zonal winds around Sumatra were observed. Atmospheric forcing revealed trends favoring Ekman downwelling in the equatorial eastern Indian Ocean and upwelling in the southeastern Indian Ocean, which was consistent with the trends in thermocline depth. This study provides the first results regarding the recent decadal shift in the onset timing of coastal upwelling. Ongoing monitoring is needed to better understand the long-term change of the upwelling system in the eastern tropical Indian Ocean.

Using reanalysis data from the ECMWF and Hadley Centre of the UK Meteorological Office, the present study analyzes the relationship between Indian Ocean Dipole (IOD) in the previous autumn (September–November) and South China Sea Summer (June–August) Monsoon (SCSSM) from 1951 to 2021. It is found that the relationship between the two indices was significantly enhanced from the late 1970s to the beginning of the 21st century, with a significant resonance cycle of 2–4a. The previous autumn IOD forced the Gill pattern in the upper troposphere by changing the Sea Surface Temperature Anomaly (SSTA) of the following summer in the Tropical Indian Ocean (TIO), resulting in the anticyclonic circulation anomaly in the Philippine Sea. It eventually alters the southwest monsoon near the South China Sea and the Philippine Sea. However, for a decade or more, as the Pacific Decadal Oscillation (PDO) phase turns from warm to cold and the relationship between El Niño–Southern Oscillation (ENSO) and IOD weakens, the impact of the previous autumn IOD on Indian Ocean SSTA in the summer of the following year weakens, resulting in a decrease in the correlation between the previous autumn IOD and SCSSM. The impact of the previous autumn’s Indian Ocean SSTA on the following year’s SCSSM is more considered in terms of the eastern Bay of Bengal and the Somali Sea basin. In addition, during the warm phase of PDO, the IOD of the previous autumn can cause abnormal summer precipitation in South China by strengthening or weakening the Western Pacific Subtropical High (WPSH) of the following summer, but there is no significant effect in the cold phase of PDO.

The Indian Ocean Dipole (IOD) is one of the dominant interannual variabilities in the Indian Ocean (IO), and an extreme IOD, in particular, has dramatic effects on the weather, agriculture, and ecosystem around it. Therefore, the formation of an extreme IOD has been a worldwide research focus. Among 13 positive IOD (PIOD) events, two type-east and two type-comparable PIODs developed into extreme events during the 1960–2020 period. This investigation focuses on the cause of the formation of the type-east extreme PIOD, as previous studies have discussed the origin of the type-comparable extreme PIOD. Composite analysis showed that, as an entity, the strong East Asian and Australian monsoon (EAAM) may result in an evident easterly wind anomaly around the Indonesian region of the Marine Continent during May to August of the years when type-east PIODs occurred. The easterly wind anomaly associated with the EAAM was stronger in the extreme IOD group, whereas it was relatively weak in the regular group. The difference in the easterly wind anomaly between the extreme and regular groups could result in a vertical motion anomaly by enhancing the anomalous westward current. The stronger vertical motion created an upwelling in the deep-layer cold water, resulting in a more distinct difference in the vertical temperature gradient. All these conditions promoted the transformation of the type-east PIODs that occurred in 1961 and 1994 into extreme events and are indicative of the importance of vertical advection terms in the formation of type-east extreme PIODs. This study reveals the cause of the formation of type-east extreme PIODs, which will be helpful in understanding IOD diversity.

The Tropical Cyclonic Disturbances (TCDs) over the Bay of Bengal (BoB) have always disrupted life, economy and environment across the coastal regions. The present study evaluates the ability of COoordinated Regional Climate Downscaling Experiment (CORDEX) constituting regional climate model (here REMO2009) in simulating the behaviour of some precursors of TCDs, frequency of TCDs and their intensity over the BoB. Furthermore, the impacts of El Niño Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD) are addressed to determine the sensitivity of the model in capturing large-scale ocean-atmosphere coupled phenomena. The model outputs (resolution 0.44° × 0.44°) are evaluated against the recorded observations of India Meteorological Department and ERA-Interim reanalysis (resolution 0.25° × 0.25°) over the time period 1979–2005. Evaluation of TCD frequencies and intensities on a year-to-year basis shows the model performing reasonably well against observations but intensity is largely reduced. Also, we find an overestimated number of TCDs in the model as pre-monsoon (post-monsoon) shows + 195% (+ 80%) more TCDs. The large-scale environmental fields associated with TCDs show spatiotemporal biases of varying magnitudes in the model however are consistent in capturing TCDs and their behaviours. The mean climatology shows clear differences in environmental fields during days with TCDs and without TCDs. The genesis geolocations in observations are coherent with their environmental fields and are firmly reproduced in the model albeit with spatial differences. The intensity in the model is found to be mostly low showing weak TCDs besides overestimating (underestimating) TCDs of moderate (high) intensities. The REMO2009 model is found satisfactorily simulating the TCDs (year-to-year basis) and associated large-scale environmental fields against the observations and reanalysis. The impacts of large climatic teleconnections (ENSO and IOD) are also captured in the model with warm ENSO phase suppressing the TCDs activities while cold phase triggering the TCDs. On the similar watch, a negative dipole over the Indian Ocean triggers the TCDs while a positive dipole suppresses the TCDs formation in the model. The present study using the regional climate model (RCM) REMO2009 is moreover a needed baseline for the future projections and evaluation of other RCMs under the CORDEX domains. [ABSTRACT FROM AUTHOR]

Existed studies have suggested a precursory relation between Indian Ocean Dipole (IOD) and El Niño and the Southern Oscillations (ENSO) with 1-year time lag. The underlying mechanisms were attributed to atmospheric bridge and/or oceanic channel processes. In this study, the oceanic channel dynamics in 23 climate models of the Coupled Model Intercomparison Project phase 5 (CMIP5) are assessed by correlation analyses in comparison with observations. The results show that the lag correlations between the IOD and ENSO anomalies associated with oceanic channel are significant, suggesting important role of oceanic channel dynamics in the cross-basin teleconnection in the analyzed CMIP5 models, consistent with observational analyses. In comparison, the correlations associated with atmospheric bridge are highly dispersive among the models and generally inconsistent with the observational analyses, suggesting model deficiencies. In a single climate model, the lag correlations associated with oceanic channel dynamics are consistent among different ensemble experiments, whereas those associated with atmospheric bridge processes are dispersive.

The recharge oscillator mechanism suggests that a strong El Niño event can trigger a following La Niña event that sometimes lasts for two or even three years through warm water volume preconditioning within the tropical Pacific. However, a prominent and persistent “double-dip” La Niña event appeared in the boreal winters of 2020/2021 and 2021/2022 without any significant El Niño preconditioning. Here we explore the possibility that tropical basin interactions may have initiated and helped to prolong La Niña conditions over the 2-year period 2020–2022. This period was preceded by a strong positive Indian Ocean Dipole (IOD) during the boreal fall of 2019 that gave way to basin-scale warming in the Indian Ocean in early 2020 and a notable tropical Atlantic warming in the boreal winter of 2019/2020. Later, a strong Atlantic Niño developed in the boreal summer of 2021. Using composite analyses to characterize earlier double-dip La Niñas, we argue the unusual sequence of events in 2019–2021 in the Indian and Atlantic Oceans may have energized and sustained the 2020–2022 La Niña event without any significant warm water volume preconditioning within the tropical Pacific.

In this study, we train a convolutional neural network (CNN) model using a selection of Coupled Model Intercomparison Project (CMIP) phase 5 and 6 models to investigate the predictability of the sea surface temperature (SST) variability off the Sumatra-Java coast in the tropical southeast Indian Ocean, the eastern pole of the Indian Ocean Dipole (IOD). Results show that the CNN model can beat the persistence of the interannual SST variability, such that the eastern IOD (EIOD) SST variability can be forecast up to 6 months in advance. Visualizing the CNN model using a gradient weighted class activation map shows that the strong positive IOD events (cold EIOD SST anomalies) can stem from different processes: internal Indian Ocean dynamics were associated with the 1994 positive IOD, teleconnection from the equatorial Pacific was important in 1997, and cooling off the Australian coast in the southeast Indian Ocean contributed to the 2019 positive IOD. The CNN model overcomes the winter prediction barrier of the IOD, to a large extent due to the frequent transition from a warm state of the Indian Ocean to a negative IOD condition (warm EIOD SST anomalies) over the boreal winter to the following spring period. The forecasting skills of the CNN model are on par with predictions from a coupled seasonal forecasting model (ACCESS-S2), even outperforming this dynamic model in seasons leading to the IOD peaks. The ability of the CNN model to identify key dynamic drivers of the EIOD SST variability suggests that the CMIP models can capture the internal Indian Ocean variability and its teleconnection with the Pacific climate variability.

Marine ecosystems are experiencing rapid shifts under climate change scenarios and baleen whales are vulnerable to environmental change, although not all impacts are yet clear. We identify how the migration behaviour of the Chagos whale, likely a pygmy blue whale (Balaenoptera musculus brevicauda), has changed in association with shifts in environmental factors. We used up to 18 years of continuous underwater acoustic recordings to analyse the relationships between whale acoustic presence and sea surface temperature (SST), chlorophyll-a concentration, El-Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). We compared these relationships between two independent sites Diego Garcia southeast (DGS) and Diego Garcia northwest (DGN) where Chagos whales are detected and are suspected to move interannually across the Chagos-Laccadive ridge. We showed that the number of whale songs detected increased on average by 7.7% and 12.6% annually at DGS and DGN respectively. At the DGS site, Chagos whales shifted their arrival time earlier by 4.2 ± 2.0 days/year ± SE and were detected for a longer period by 7.3 ± 1.2 days/year ± SE across 18 years. A larger number of songs were detected during periods of higher chlorophyll-a concentration, and with positive IOD phases. At the DGN site, we did not see an earlier shift in arrival and songs were not detected for a longer period across the 13 years. Whale presence at DGN had a weaker but opposite relationship with chlorophyll-a and IOD. The oceanic conditions in the Indian Ocean are predicted to change under future climate scenarios and this will likely influence Chagos whale migratory behaviour. Understanding how environmental factors influence whale movement patterns can help predict how whales may respond to future environmental change. We demonstrate the value of long-term acoustic monitoring of marine fauna to determine how they may be affected by changing environmental conditions.

The South China Sea (SCS) summer monsoon (SCSSM) and Western North Pacific tropical cyclones (TCs) are both tropical systems that interact with each other on multiple scales. This study examines the differences in TCs activity characteristics between anomalous strong and weak SCSSM years, and explores the possible mechanisms behind these differences through the coupling relationship between tropical atmospheric circulation and oceanic surface conditions. Results show that the destructiveness of TCs over the Western North Pacific is stronger during weak SCSSM years than in strong years, whereas the opposite occurs for TCs over the SCS. The interaction between the tropical Indo-Pacific ocean and atmosphere plays a key role in the relationship between SCSSM intensity and TCs activity. In strong (weak) SCSSM years, the sea surface temperature anomaly (SSTA) in the tropical Pacific Ocean tends to correspond to a La Niña-like (El Niño-like) distribution, whereas the tropical Indian Ocean shows an Indian Ocean dipole-negative (positive) phase distribution. Moreover, Walker circulations in both the Indian and Pacific Oceans are coupled during these years, which creates a seesaw-like relationship in the conditions for TCs formation between the SCS and the Western Pacific Ocean. During weak SCSSM years, the formation and activity of TCs over the SCS are suppressed due to the weakened water vapor transport caused by abnormal easterly winds from the eastern Indian Ocean to the southern SCS. Meanwhile, the higher SSTA in the Western Pacific Ocean enhances the TCs activity. In strong SCSSM years, the enhanced monsoon drives a stronger monsoon trough, improving the convective environment over the SCS, whereas in contrast, the Western Pacific Ocean is covered by colder water, resulting in poorer conditions for TCs genesis.

The highly dynamic nature of the marine environment can have a substantial influence on the foraging behaviour and spatial distribution of marine predators, particularly in pelagic marine systems. However, knowledge of the susceptibility of benthic marine predators to environmental variability is limited. This study investigated the influence of local-scale environmental conditions and large-scale climate indices on the spatial distribution and habitat use in the benthic foraging Australian fur seal (Arctocephalus pusillus doriferus; AUFS). Female AUFS provisioning pups were instrumented with GPS or ARGOS platform terminal transmitter tags during the austral winters of 2001–2019 at Kanowna Island, south-eastern Australia. Individuals were most susceptible to changes in the Southern Oscillation Index that measures the strength of the El Niño Southern Oscillation, with larger foraging ranges, greater distances travelled and more dispersed movement associated with 1-yr lagged La Niña-like conditions. Additionally, the total distance travelled was negatively correlated with the current year sea surface temperature and 1-yr lagged Indian Ocean Dipole, and positively correlated with 1-yr lagged chlorophyll-a concentration. These results suggest that environmental variation may influence the spatial distribution and availability of prey, even within benthic marine systems.

Abstract Modes of climate variability are known to influence rainy season onset, but there is less understanding of how they impact flood timing. We use streamflow reanalysis and gauged observation data sets to examine the influence of the Indian Ocean Dipole and El Niño–Southern Oscillation across sub‐Saharan Africa. We find significant changes in flood timing between positive and negative phases of both Indian Ocean Dipole and El Niño–Southern Oscillation; in some cases the difference in the timing of annual flood events is more than three months. Sensitivity to one or other mode of variability differs regionally. Changes in flood timing are larger than variability in rainy season onset reported in the literature, highlighting the need to understand how the hydrological system alters climate variability signals seen in rainy season onset, length, and rainfall totals. Our insights into flood timing could support communities who rely on flood‐based farming systems to adapt to climate variability.

A new high‐resolution global analysis product is constructed from a fully coupled surface wave‐tide‐circulation Ocean Model developed by the First Institute of Oceanography Coupled Ocean Model (FIO‐COM). The performance of the FIO‐COM analysis data set is assessed based on comparisons with two other widely used high‐resolution global analysis products (Copernicus marine and environment monitoring service and HYbrid isopycnal‐sigma‐pressure coordinate ocean model), and observations in tropical oceans. Through comparison with observations, the FIO‐COM analysis is shown to be able to accurately capture the large‐scale mixed layer depth (MLD) structures in the tropical oceans during all seasons. Seasonal variations of MLDs can exceed ±80% in the southern and northern tropical oceans (10°‐25°S and 10°‐25°N) in both boreal winter and summer, as inferred from observations and FIO‐COM analysis data. Quantitative assessments of the 20°C isothermal depth, temperature at 5°m depth, and temperature and salinity profiles, among the analyses and in situ observations are also conducted. The capability of the FIO‐COM analysis to reflect the observed sea surface temperature variability during the 2015 El Niño episode is further investigated through comparisons with observations from 19 TAO buoys located in the Niño 3.4 region. All indicate the high quality of the new data set. Plain Language Summary: We present a new high‐resolution global analysis data set, which is for the first time constructed from a surface wave‐tide‐circulation fully coupled model system. To evaluate the accuracy of the analysis data set, we present intercomparisons with two other high‐resolution global analysis datasets, as well as observations from tropical ocean areas. We show that the new analysis data set simulates the large‐scale ocean mixed layer depth structures accurately during all seasons over a two‐year period. Specifically, we make comparisons with in situ observations of the 20°C isothermal depth, temperature at 5°m depth, and the temperature and salinity profiles. The new data set exhibits high quality in all of these variables. Key Points: This is a first attempt to generate analysis data based on a surface wave‐tide‐circulation fully coupled model system, First Institute of Oceanography Coupled Ocean ModelThe quality of this data set is comprehensively verified through comparison with two other analysis datasets and observationsThe new data set can well capture the seasonal variation of sea surface temperature, mixed layer depth, El Niño, Indian Ocean dipole, and Atlantic meridional mode [ABSTRACT FROM AUTHOR]

Indian Ocean Dipole (IOD) is a large-scale physical ocean phenomenon in the Indian Ocean that plays an important role in predicting the El Nino Southern Oscillation in the tropical Pacific. Predicting the occurrence of IOD is of great significance to the study of climate change and other marine phenomena. Generally, the IOD index is calculated to judge whether the IOD occurs. In this paper, a convolutional LSTM (convLSTM) neural network is used to build the deep learning model to predict the sea surface temperature in the next seven months and calculate the IOD index. Through the analysis of marine atmospheric data with complex temporal and spatial relationships, the wind field signal knowledge of the physical ocean is introduced to predict IOD phenomenon by combining the prior knowledge of the physical ocean and deep learning. The experimental results show that the average correlation of IOD index time series to the true IOD index time series is 82.87% from 2015 to 2018, seven months ahead for IOD prediction. IOD manifests as sea surface temperature (SST) anomaly changes, and this thesis verifies that the wind field signal information has a positive impact on the prediction of IOD changes. Moreover, the convLSTM can predict this anomaly better. The IOD index line graph can generally fit the real IOD index variation trend, which has a profound impact on the study of the IOD phenomenon.

Wildfires are sensitive to climate change, but their response to changes in temperature and precipitation on long timescales is still disputed. In this study, we present a ~9.4 ka black carbon mass sedimentation rate (BCMSR) record from Lake Ximenglongtan (XMLT), southwestern China, to elucidate the Holocene fire regime and its linkages to climatic conditions. The results indicate that the regional fire activity was low during the early Holocene (before 7.6 cal ka BP), increased notably at 7.6 cal ka BP, and continued to increase gradually during the mid- to late Holocene until 2.2 ka. The episodes of higher fire occurrence reflected by higher BCMSR over the last 2.2 ka might be more likely related to the intensified human activities. The cool and humid climate during the early Holocene limited the spread of fire, while warming and drying at ~7.6 cal ka BP triggered higher fire occurrence. Instead of temperature, changes in precipitation dominated fire regime variation during the mid- to late Holocene. On millennial timescales, we suggest that Holocene fire variability has been predominantly controlled by the combined effects of Northern Hemisphere (NH) summer and winter insolation that influenced monsoonal precipitation and fire season temperature, respectively. Indian Ocean Dipole (IOD) events may also have affected fire incidence through influencing monsoon intensity. [ABSTRACT FROM AUTHOR]

Indian Ocean decadal sea-level variability is an active research area, with many unresolved questions due to inadequate observational coverage. In this study, we analyse 26 Coupled Model Intercomparison Project (CMIP) pre-industrial simulations and isolate two consistent modes of Indian Ocean variability, which collectively explain about 50% of the total decadal sea-level variance. With opposite sea-level signals in the southwestern and eastern Indian Ocean, the first mode is related to decadal modulation of the Indian Ocean Dipole (DIOD) and equatorial wind-driven dynamics. Though IOD is more independent of the El Niño–Southern Oscillation (ENSO) at decadal (r ~ 0.4) than interannual (r ~ 0.6) timescales, the DIOD–ENSO co-variability yields sea-level signals along the west coast of Australia, transmitted from the western Pacific via the Indonesian Throughflow. The second mode encompasses variability in the south Indian Ocean (SIODV), exhibiting a broad monopolar sea-level pattern east of Madagascar. In about half of the models, the SIODV is largely independent from DIOD (and decadal ENSO) and driven by south Indian Ocean wind-stress curl associated with meridional shifts in the Mascarene High (MH). In the other models, the SIODV lags the DIOD about 3 years. In those models, in addition to MH forcing, the DIOD-related alongshore wind stress off the northwest Australian coast triggers Rossby waves that also contribute to the SIODV, further west. The DIOD and MH forcing are mutually independent (r ~ 0.2). The results are broadly consistent with sea-level variations derived from the short altimeter data, despite an underestimation of the Oceanic bridge signals in CMIP models. [ABSTRACT FROM AUTHOR]

Novel and long-term satellite data (2003–2017) are analyzed to investigate the variability of ocean surface chlorophyll-a (Chl-a) concentration off the Western Lesser Sunda Islands (WLSI) under the influence of the Indonesian Australian monsoon, the El Niño-Southern Oscillation, and the Indian Ocean Dipole (IOD). In this article, we first analyzed the seasonal variability of Chl-a, and then describe the relationship among the sea surface Chl-a, sea surface temperature (SST), and sea surface wind stress in the region. Our results demonstrate that prevailing southeasterly wind stress plays a pivotal role in generating the Chl-a maxima off the WLSI. Particularly on seasonal time scale, the strengthening of southeasterly wind stress (up to ∼0.01 N·m−2) during the southeast monsoon season produces enhanced Chl-a concentrations (0.59 mg·m−3) associated with sea surface cooling (∼28.8 °C) in the area of study. In contrast, the Chl-a maxima completely vanished during the northwest monsoon season. On interannual time scale, the largest positive Chl-a and wind stress anomalies and the coolest SST anomaly are observed in 2006 when El Niño and positive IOD events occur at the same time. Meanwhile, the greatest negative Chl-a anomaly is prevailed during the 2016 negative IOD event. This article demonstrates that wind variability is the essential factor in determining the magnitude of the Chl-a maxima off the WLSI. [ABSTRACT FROM AUTHOR]

Modes of climate variability are known to influence rainy season onset, but there is less understanding of how they impact flood timing. We use streamflow reanalysis and gauged observation data sets to examine the influence of the Indian Ocean Dipole and El Niño–Southern Oscillation across sub‐Saharan Africa. We find significant changes in flood timing between positive and negative phases of both Indian Ocean Dipole and El Niño–Southern Oscillation; in some cases the difference in the timing of annual flood events is more than three months. Sensitivity to one or other mode of variability differs regionally. Changes in flood timing are larger than variability in rainy season onset reported in the literature, highlighting the need to understand how the hydrological system alters climate variability signals seen in rainy season onset, length, and rainfall totals. Our insights into flood timing could support communities who rely on flood‐based farming systems to adapt to climate variability. Plain Language Summary: Patterns of climate variability such as the El Niño–Southern Oscillation or the Indian Ocean Dipole affect the timing of the start of the rainy season, but little is known about how this translates into changes in the timing of the annual flood in rivers. We use computer model reconstructions and observed records of river flows in Africa to understand how these patterns of climate variability are changing the timing of river floods. In eastern and southern Africa, in particular, the differences in flood timing can be more than three months. This information could help farmers in African floodplains to adapt their water management, planting, and cropping practices to these patterns of climate variability. Key Points: Modes of climate variability in the Pacific and Indian Oceans drive significant changes in flood timing across sub‐Saharan AfricaThe hydrological system enhances and alters climate variability signals seen in rainy season onset, duration, and total rainfallUnderstanding of how climate variability changes the timing of floods can support flood‐based farming systems [ABSTRACT FROM AUTHOR]

This work addresses the relationship between major dynamical forcings and variability in NO _2 column measurements. The dominating impact in Northern Southeast Asia is due to El Niño-Southern Oscillation (ENSO); in Indonesia, Northern Australia and South America is due to Indian Ocean Dipole (IOD); and in Southern China Land and Sea, Populated Northern China, Siberia, Northern and Arctic Eurasia, Central and Southern Africa, and Western US and Canada is due to North Atlantic Oscillation (NAO). That NO _2 pollution in Indonesia is modulated by IOD contradicts previous work claiming that the emissions in Indonesia are a function of El Niño impacting upon Aerosol Optical Depth and Fire Radiative Power. Simultaneous impacts of concurrent and lagged forcings are derived using multi-linear regression, demonstrating ENSO impacts future NO _2 variability, enhancing NO _2 emissions 7–88 weeks in the future, while IOD and NAO in some cases increase the emissions from or the duration of the future burning season as measured by NO _2 . This impact will also extend to co-emitted aerosols and heat, which may impact the climate. In all cases, lagged forcings exhibit more impact than concurrent forcings, hinting at non-linearity coupling with soil moisture, water table, and other dynamical effects. The regression model formed demonstrates that dynamical forcings are responsible for over 45% of the NO _2 emissions variability in most non-urban areas and over 30% in urban China and sub-arctic regions. These results demonstrate the significance of climate forcing on short-lived air pollutants.

This study analyzed the sensitivity of rainfall patterns in South China and the Indochina Peninsula (ICP) using statistical simulations of observational data. Quantitative changes in rainfall patterns over the ICP were examined for both wet and dry seasons to identify hotspots sensitive to ocean warming in the Indo-Pacific sector. The rainfall variability was amplified by combined and/or independent effects of the El Niño–Southern Oscillation and the Indian Ocean Dipole (IOD). During the years of El Niño and a positive phase of the IOD, rainfall is less than usual in Thailand, Cambodia, southern Laos, and Vietnam. Conversely, during the years of La Niña and a negative phase of the IOD, rainfall throughout the ICP is above normal, except in parts of central Laos, northern Vietnam, and South China. This study also simulated the change of ICP rainfall in the wet and dry seasons with intentional IOD changes and verified IOD-sensitive hotspots through quantitative analysis. The results of this study provide a clear understanding both of the sensitivity of regional precipitation to the IOD and of the potential future impact of statistical changes regarding the IOD in terms of understanding regional impacts associated with precipitation in changing climates.

Abstract: The impacts of explosive volcanism on the densely populated Indian Ocean (IO) region remain elusive. Dedicated sensitivity experiments indicate that tropical volcanic eruptions induce a stronger surface cooling over Africa than of ocean, promoting westerlies in the equatorial IO. These westerlies drive a subsurface response reminiscent to that of a negative IO Dipole (IOD) during autumn in the year of eruption. The eruption also drives an enhanced cooling over the northwestern IO as a direct response to climatological cloud cover distribution. The resulting anomalous zonal sea surface temperature gradient contributes to enhance equatorial westerly anomalies in summer. The response is sensitive to the IO preconditioning, being larger when the system is favorable to a positive IOD development. Volcanic eruptions also induce a subsurface IOD‐like response in the multimodel database from the Coupled Model Intercomparison Project Phase 5 as well as a primary productivity decrease in the eastern IO. [ABSTRACT FROM AUTHOR]

The dynamics of the teleconnection between the Indian Ocean Dipole (IOD) in the tropical Indian Ocean and El Niño-Southern Oscillation (ENSO) in the tropical Pacific Ocean at the time lag of one year are investigated using lag correlations between the oceanic anomalies in the southeastern tropical Indian Ocean in fall and those in the tropical Indo-Pacific Ocean in the following winter-fall seasons in the observations and in high-resolution global ocean model simulations. The lag correlations suggest that the IOD-forced interannual transport anomalies of the Indonesian Throughflow generate thermocline anomalies in the western equatorial Pacific Ocean, which propagate to the east to induce ocean-atmosphere coupled evolution leading to ENSO. In comparison, lag correlations between the surface zonal wind anomalies over the western equatorial Pacific in fall and the Indo-Pacific oceanic anomalies at time lags longer than a season are all insignificant, suggesting the short memory of the atmospheric bridge. A linear continuously stratified model is used to investigate the dynamics of the oceanic connection between the tropical Indian and Pacific Oceans. The experiments suggest that interannual equatorial Kelvin waves from the Indian Ocean propagate into the equatorial Pacific Ocean through the Makassar Strait and the eastern Indonesian seas with a penetration rate of about 10%-15% depending on the baroclinic modes. The IOD-ENSO teleconnection is found to get stronger in the past century or so. Diagnoses of the CMIP5 model simulations suggest that the increased teleconnection is associated with decreased Indonesian Throughflow transports in the recent century, which is found sensitive to the global warming forcing. [ABSTRACT FROM AUTHOR]

This letter investigates the relationship between wind, sea surface temperature (SST), and thermocline in the Seychelles–Chagos Thermocline Ridge (SCTR, 5°S–10°S, 50°E–80°E) using a combination of satellite data and a reanalysis version of the HYbrid Coordinate Ocean Model from 1993 to 2012. The asymmetry of this relationship during positive and negative Indian Ocean Dipole (IOD) events and the impacts on the SST—thermocline depth (represented by the 20 °C isotherm depth, D20) relationship—are examined. On interannual timescales, an asymmetric relation between SST and zonal wind stress causes a strengthening of easterlies that enhances anticyclonic wind stress curl and local Ekman downwelling, which in turn deepens the D20 and increases the heat content during positive IOD (PIOD) events. In contrast, during negative IOD (NIOD) events, the winds reverse to be westerlies and cause a three times greater impact on remotely generated upwelling Rossby waves. Subsequently, these asymmetric relations cause an asymmetric D20–SST feedback in the SCTR such that a shoaling D20 is ~2.5 times more effective at lowering SST during NIOD events than a deepening D20 is at raising the SST during PIOD events. The changes to D20 are observed to extend into the year following IOD events, persisting into the end of the year following a PIOD event (due to stronger asymmetric reinforcing effects of warm SST anomalies on zonal wind anomalies) but only to May–June of the year following NIOD events. [ABSTRACT FROM PUBLISHER]

The Maritime Continent (MC) is under influences of both the tropical Pacific and the Indian Ocean. Anomalous convective activities over the MC have significant impacts on the East Asian summer monsoon (EASM) and climate in China. In the present study, the variation in convective activity over the MC in boreal summer and its relationship to EASM anomalies are investigated based on regression analysis of NCEP-NCAR reanalysis and CMAP [Climate Prediction Center (CPC) Merged Analysis of Precipitation] data, with a focus on the impacts of ENSO and the Indian Ocean Dipole (IOD). The most significant interannual variability of convective activity is found over 10°S-10°N, 95°-145°E, which can be roughly defined as the key area of the MC (hereafter, KMC). Outgoing longwave radiation anomaly (OLRA) exhibits 3- to 7-yr periodicities over the KMC, and around 70% of the OLRA variance can be explained by the ENSO signal. However, distinct convection and precipitation anomalies still exist over this region after the ENSO and IOD signals are removed. Abnormally low precipitation always corresponds to positive OLRA over the KMC when negative diabatic heating anomalies and anomalous cooling of the atmospheric column lead to abnormal descending motion over this region. Correspondingly, abnormal divergence occurs in the lower troposphere while convergence occurs in the upper troposphere, triggering an East Asia-Pacific/Pacific-Japan (EAP/PJ)-like anomalous wave train that propagates northeastward and leads to a significant positive precipitation anomaly from the Yangtze River valley in China to the islands of Japan. This EAP/PJ-like wave pattern becomes even clearer after the removal of the ENSO signal and the combined effects of ENSO and IOD, suggesting that convective anomalies over the KMC have an important impact on EASM anomalies. The above results provide important clues for the prediction of EASM anomalies and associated summer precipitation anomalies in China. [ABSTRACT FROM AUTHOR]

Water availability and food security are tightly coupled on a global scale. The occurrence of drought puts this balance at risk due to reductions in dryland farming production and water allocations to irrigated agriculture. Improved understanding of drought initiation and cessation would therefore be beneficial for drought planning and management. The study objective was to determine factors affecting drought initiation and cessation over the past century in two climatologically similar regions that represent net agricultural exporters; south central U.S. (Texas) and southeast Australia (Murray Darling Basin, MDB). Drought indices included the Standardized Precipitation Index (SPI, 1900–2014) for meteorological drought, the Normalized Difference Vegetation Index (NDVI, 1981–2014) for agricultural drought, and the Streamflow Drought Index (SDI, 1930–2014) for hydrological drought. Results show that meteorological drought tends to develop gradually over a period of up to six months, with agricultural drought developing shortly thereafter (within one month) in both regions. Evidence of hydrological drought was observed within one month (Texas) and within four months (MDB) on average after meteorological drought was established. Further, droughts appear to cease more quickly than they initiate over Texas, whereas rates of drought initiation and cessation are similar over the MDB. Drought breaking rainfall in Texas is generally a result of a southward shift in the Polar Jet Stream or a low-pressure trough over central North America, whereas drought cessation in the MDB is typically associated with a monsoon trough or low-pressure system in the Tasman Sea/Great Australian Bight. Improved knowledge of the climate mechanisms controlling the onset and termination of drought periods should enhance drought forecasts and improve drought management practices, particularly in regions where water security is a primary objective. [ABSTRACT FROM AUTHOR]

El Niño/Southern Oscillation (ENSO) teleconnections present a hemispheric dipole pattern in both rainfall and vegetation between eastern and southern Africa. We analyze precipitation and normalized difference vegetation index (NDVI) departures during the 2015–2017 ENSO cycle; with one of the strongest warm events (El Niño) on record followed by a short and weak cold event (La Niña). Typically, southern (eastern) Africa is associated with dry (wet) conditions during El Niño, and wet (dry) conditions during La Niña. In general, the temporal and spatial evolution of vegetation responses show the expected dipole pattern during the 2015–2016 El Niño and following 2016–2017 La Niña. However, in 2015–2016 the eastern African impacts were displaced to the west and south of the canonical pattern. Composites of seasonal vegetation anomalies highlight the magnitude and position of impacts. Further investigation through empirical orthogonal teleconnections and spatial correlation analysis confirms the similar, but opposite, teleconnection impacts in eastern and southern Africa. The diametrically opposed patterns have particular implications for agricultural production and the availability of fodder and forage, especially in the pastoral communities of the two regions.

Remote processes, such as El Niño- Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), are primary drivers of the Seychelles–Chagos thermocline ridge (SCTR) interannual variability with respect to ocean temperature and salinity. Although salinity variability in this region is understudied, previous studies have separated out effects of El Niño and IOD on sea surface temperature (SST) anomalies and concluded SST changes due to IOD are primarily associated with the southward advection of warmer equatorial water. Likewise, SST changes due to El Niño are associated with the suppression of clouds over the Indian Ocean. Although ENSO is known to have a stronger impact on SST south of the SCTR (10°S–15°S), this letter finds that the ENSO has a stronger impact on sea surface salinity (SSS) in the SCTR. This letter further explores how the surface and subsurface salinity and temperature in SCTR varies throughout the year in response to ENSO and IOD separate and coevents using long-term Simple Ocean Data Assimilation (SODA) reanalysis records. Our SSS results from the SODA reanalysis are compared and found to be consistent with soil moisture active passive derived SSS observations for both a positive and negative IOD year. [ABSTRACT FROM PUBLISHER]

The different impacts of El Niño during peak phases with and without a positive Indian Ocean Dipole (P-IOD) on the Northwest Pacific circulation were studied. The authors focused on the Northwest Pacific circulation features in the mature phase of El Niño from September to February of the next year. Composite maps and simulations demonstrate that the atmospheric circulation under the impact of El Niño with and without P-IOD exhibits large differences in temporal evolution and intensity. In single El Niño (SE) years without a P-IOD, an anomalous low-level anticyclonic circulation around the Philippines (PSAC) is instigated by the single El Niño-induced Indonesian subsidence. However, during the years when El Niño and a P-IOD matured simultaneously, a much greater anomalous subsidence over the western Pacific and the Maritime Continent occurred. The PSAC tends to occur earlier, is much stronger and has a longer lifetime than that during SE. More importantly, the PSAC shows a characteristic of an eastward movement from the southern South China Sea (SCS) to the Philippine Sea. This characteristic does not appear during SE. These patterns imply that a positive IOD event tends to exert a prominent influence on the PSAC during El Niño events and there is a combined impact of El Niño and P-IOD on the development of the PSAC. [ABSTRACT FROM AUTHOR]

Lag correlations between sea surface temperature anomalies (SSTA) in the southeastern tropical Indian Ocean (STIO) in fall and Niño 3.4 SSTA in the eastern equatorial Pacific in the following fall are subjected to decadal variation, with positive correlations during some decades and negative correlations during others. Negative correlations are smaller and of shorter duration than positive correlations. Variations in lag correlations suggest that the use of the Indian Ocean Dipole (IOD) as a predictor of the El Niño-Southern Oscillation (ENSO) at a lead time of one year is not effective during some decades. In this study, lag correlations between IOD and ENSO anomalies were analyzed to investigate why the IOD-ENSO teleconnection disappears during decades with negative correlations. Anomalies induced by the IOD in the equatorial Pacific Ocean during decades with negative correlations are still present, but at a greater depth than in decades with positive correlations, resulting in a lack of response to oceanic channel dynamics in the cold tongue SSTA. Lag correlations between oceanic anomalies in the west Pacific warm pool in fall and the equatorial Pacific cold tongue with a one-year time lag are significantly positive during decades with negative correlations. These results suggest that oceanic channel dynamics are overwhelmed by ocean-atmosphere coupling over the equatorial Pacific Ocean during decades with negative correlations. Therefore, the Indonesian throughflow is not effective as a link between IOD signals and the equatorial Pacific ENSO. [ABSTRACT FROM AUTHOR]

The Indian Ocean sea surface temperature (SST) variability has been represented with the two dominant variability modes: the Indian Ocean basin-wide (IOBW) and dipole (IOD) modes. Here we investigate future changes of the two modes together with mean state and El Niño and Southern Oscillation (ENSO) relationship under the anthropogenic global warming using 20 coupled models that participated in the phase five of Coupled Model Intercomparison Project by comparing the historical run from 1950 to 2005 and the RCP 4.5 run from 2050 to 2099. The five best models are selected based on the evaluation of the 20 models' performances in simulating the two modes and Indian Ocean basic state for the latest 56 years. They are capable of capturing the IOBW and IOD modes in their spatial distribution, seasonal cycle, major periodicity, and relationship with ENSO to some extent. The five best models project the significant changes in the Indian Ocean mean state and variability including the two dominant modes in the latter part of twenty-first century under the anthropogenic warming scenario. First, the annual mean climatological SST displays an IOD-like pattern change over the Indian Ocean with enhanced warming in the northwestern Indian Ocean and relatively weaker warming off the Sumatra-Java coast. It is also noted that the monthly SST variance is increased over the eastern and southwestern Indian Ocean. Second, the IOBW variability on a quasi-biennial time scale will be enhanced due to the strengthening of the ENSO-IOBW mode relationship although the total variance of the IOBW mode will be significantly reduced particularly during late summer and fall. The enhanced air-sea coupling over the Indian-western Pacific climate in response to El Nino activity in the future projection makes favorable condition for a positive IOD while it tends to derive relatively cold temperature over the eastern Indian Ocean. This positive IOD-like ENSO response weakens the relationship between the eastern Indian Ocean and El Nino while strengthens the relationship with western Indian Ocean. Third, the IOD mode, intrinsic coupled mode of the Indian Ocean may not be changed appreciably under the anthropogenic global warming. [ABSTRACT FROM AUTHOR]

The relationship between the number of lightning flashes (NLF) and the cosmic ray flux (CRF) during the period of ENSO (El Niño/La Niña Southern Oscillations) with and without IOD (Indian Ocean Dipole) has been studied for the first time in the region of South/Southeast Asia (8°N–35°N and 60°E–120°E) to the authors' knowledge. Our analysis shows that the relationship is governed by regional meteorology and not by direct solar influence. Unlike on global scale, the data during ENSO are important for this relationship on regional scale. CRF and NLF are in statistically significant relationship only when CRF is significantly correlated with the meteorological parameters. CRF and NLF are significantly correlated during the period of ENSO with IOD (ENSO–IOD) but not during the period of ENSO without IOD (ENSO). The Aerosol Optical Depth (AOD), the positive temperature anomaly (TA) and an increase in TA may be responsible for this relationship during the ENSO–IOD period. On the shorter temporal/spatial scale, meso-scale meteorological parameters are responsible for the negative correlation between the CRF and the NLF. On the other hand, on the longer scale, an amount of Low Level Cloud Fraction (LLCF) is responsible for the positive correlation between the CRF and the NLF. Our partial correlation analysis shows that controlling for the AOD weakens the correlation between the CRF and the NLF but does not affect that between the 12month running means of the same. Thus, aerosols are responsible during the total study period and during the IOD period for enhancing the significant CRF–NLF relationship. Solar radio flux F10.7 cm (SRF10.7) seems to be the main controlling parameter for the stronger relationship. We find that there is a distinct difference in the average magnitude of different solar and meteorological parameters between that during the ENSO period and the ENSO–IOD period which may be attributed to the difference in cloud types and aerosol properties between the two periods. The results of our analysis may be confirmed with longer data sets and more number of IOD events in the future. [ABSTRACT FROM AUTHOR]