On the weakening relationship between the indian monsoon and ENSO

Amplified drying in South Asian summer monsoon precipitation due to anthropogenic sulfate aerosols

A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006-2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%-43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia.

Analysis of the relationship between dust aerosol and precipitation in spring over East Asia using EOF and SVD methods

This study utilized the Empirical Orthogonal Function (EOF) and Singular Value Decomposition (SVD) methods to investigate the spatial and temporal patterns and trends of dust aerosol and precipitation, and to identify the coupled modes between them. The research employed MODIS and CALIPSO retrieved dust aerosol optical depth (DAOD) data to represent dust aerosol information and CMORPH data to provide precipitation information. The results indicated that specific dust source regions were associated with the primary modes of spring dust in East Asia, while atmospheric circulation and land-sea monsoon were closely related to the primary modes of spring precipitation. Additionally, the study revealed that the impact of dust aerosol on precipitation varied based on the source region within the coupled modes. The first coupled mode, with dust sources in the Mongolian Gobi and Taklamakan Desert, demonstrated a pattern of increased dust aerosol and reduced precipitation in most regions. The second coupled mode, with dust sources focused on the Mongolian Gobi, exhibited a consistent pattern of increased dust aerosol and a significant increase in precipitation in northern China. This study highlights the significance of considering dust source regions when examining the relationship between dust aerosol and precipitation, providing new insights into the potential impact of dust aerosol on precipitation in East Asia during the spring.

Moisture control of tropical cyclones in high-resolution simulations of paleoclimate and future climate

The intensity of tropical cyclones (TCs) is expected to increase in response to greenhouse warming. However, how future climate change will affect TC frequencies and tracks is still under debate. Here, to further elucidate the underlying sensitivities and mechanisms, we study TCs response to different past and future climate forcings. Using a high-resolution TC-resolving global Earth system model with 1/4° atmosphere and 1/10° ocean resolution, we conducted a series of paleo-time-slice and future greenhouse warming simulations targeting the last interglacial (Marine Isotope Stage (MIS) 5e, 125 ka), glacial sub-stage MIS5d (115 ka), present-day (PD), and CO2 doubling (2×CO2) conditions. Our analysis reveals that precessional forcing created an interhemispheric difference in simulated TC densities, whereas future CO2 forcing impacts both hemispheres in the same direction. In both cases, we find that TC genesis frequency, density, and intensity are primarily controlled by changes in tropospheric thermal and moisture structure, exhibiting a clear reduction in TC genesis density in warmer hemispheres.

East Asian summer rainfall stimulated by subseasonal Indian monsoonal heating

The responses of the East Asian summer monsoon (EASM) to the Indian summer monsoon (ISM) have been the subject of extensive investigation. Nevertheless, it remains uncertain whether the ISM can serve as a predictor for the EASM. Here, on the basis of both observations and a large-ensemble climate model experiment, we show that the subseasonal variability of abnormal diabatic heating over India enhances precipitation over central East China, the Korean Peninsula, and southern Japan in June. ISM heating triggers Rossby wave propagation along the subtropical jet, promoting southerly winds over East Asia. The southerly winds helps steer anomalous mid-tropospheric warm advection and lower-tropospheric moisture advection toward East Asia, providing conditions preferential for rainband formation. Cluster analysis shows that, depending on jet structures, ISM heating can serve as a trigger as well as a reinforcer of the rainband.

Regional and temporal variability of Indian summer monsoon rainfall in relation to El Niño southern oscillation

The Indian summer monsoon rainfall (ISMR) exhibits significant variability, affecting the food and water security of the densely populated Indian subcontinent. The two dominant spatial modes of ISMR variability are associated with the El Niño Southern Oscillation (ENSO) and the strength of the semi-permanent monsoon trough along with related variability in monsoon depressions, respectively. Although the robust teleconnection between ENSO and ISMR has been well established for several decades, the major drivers leading to the time-varying relationship between ENSO and ISMR patterns across different regions of the country are not well understood. Our analysis shows a consistent increase from a moderate to substantially strong teleconnection strength between ENSO and ISMR from 1901 to 1940. This strengthened relationship remained stable and strong between 1941 and 1980. However, in the recent period from 1981 to 2018 the teleconnection decreased consistently again to a moderate strength. We find that the ENSO-ISMR relationship exhibits distinct regional variability with time-varying relationship over the north, central, and south India. Specifically, the teleconnection displays an increasing relationship for north India, a decreasing relationship for central India and a consistent relationship for south India. Warm SST anomalies over the eastern Pacific Ocean correspond to an overall decrease in the ISMR, while warm SST anomalies over the Indian Ocean corresponds to a decrease in rainfall over the north and increase over the south of India. The central Indian region experienced the most substantial variation in the ENSO-ISMR relationship. This variation corresponds to the variability of the monsoon trough and depressions, strongly influenced by the Pacific Decadal Oscillation and North Atlantic Oscillation, which regulate the relative dominance of the two spatial modes of ISMR. By applying the PCA-Biplot technique, our study highlights the significant impacts of various climate drivers on the two dominant spatial modes of ISMR which account for the evolving nature of the ENSO-ISMR relationship.

Extreme precipitation patterns in the Asia-Pacific region and its correlation with El Niño-Southern Oscillation (ENSO)

In the Asia-Pacific region (APR), extreme precipitation is one of the most critical climate stressors, affecting 60% of the population and adding pressure to governance, economic, environmental, and public health challenges. In this study, we analyzed extreme precipitation spatiotemporal trends in APR using 11 different indices and revealed the dominant factors governing precipitation amount by attributing its variability to precipitation frequency and intensity. We further investigated how these extreme precipitation indices are influenced by El Niño-Southern Oscillation (ENSO) at a seasonal scale. The analysis covered 465 ERA5 (the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts) study locations over eight countries and regions during 1990-2019. Results revealed a general decrease indicated by the extreme precipitation indices (e.g., the annual total amount of wet-day precipitation, average intensity of wet-day precipitation), particularly in central-eastern China, Bangladesh, eastern India, Peninsular Malaysia and Indonesia. We observed that the seasonal variability of the amount of wet-day precipitation in most locations in China and India are dominated by precipitation intensity in June-August (JJA), and by precipitation frequency in December-February (DJF). Locations in Malaysia and Indonesia are mostly dominated by precipitation intensity in March-May (MAM) and DJF. During ENSO positive phase, significant negative anomalies in seasonal precipitation indices (amount of wet-day precipitation, number of wet days and intensity of wet-day precipitation) were observed in Indonesia, while opposite results were observed for ENSO negative phase. These findings revealing patterns and drivers for extreme precipitation in APR may inform climate change adaptation and disaster risk reduction strategies in the study region.

Recent Advances in Understanding Multi-scale Climate Variability of the Asian Monsoon

Studies of the multi-scale climate variability of the Asian monsoon are essential to an advanced understanding of the physical processes of the global climate system. In this paper, the progress achieved in this field is systematically reviewed, with a focus on the past several years. The achievements are summarized into the following topics: (1) the onset of the South China Sea summer monsoon; (2) the East Asian summer monsoon; (3) the East Asian winter monsoon; and (4) the Indian summer monsoon. Specifically, new results are highlighted, including the advanced or delayed local monsoon onset tending to be synchronized over the Arabian Sea, Bay of Bengal, Indochina Peninsula, and South China Sea; the basic features of the record-breaking mei-yu in 2020, which have been extensively investigated with an emphasis on the role of multi-scale processes; the recovery of the East Asian winter monsoon intensity after the early 2000s in the presence of continuing greenhouse gas emissions, which is believed to have been dominated by internal climate variability (mostly the Arctic Oscillation); and the accelerated warming over South Asia, which exceeded the tropical Indian Ocean warming, is considered to be the main driver of the Indian summer monsoon rainfall recovery since 1999. A brief summary is provided in the final section along with some further discussion on future research directions regarding our understanding of the Asian monsoon variability.

A predictable prospect of the South Asian summer monsoon

Prediction of the South Asian summer monsoon (SASM) has remained a challenge for both scientific research and operational climate prediction for decades. By identifying two dominant modes of the SASM, here we show that the unsatisfactory prediction may be due to the fact that the existing SASM indices are mostly related to the less predictable second mode. The first mode, in fact, is highly predictable. It is physically linked to the variation of the Indian monsoon trough coupled with large rainfall anomalies over core monsoon zone and the northern Bay of Bengal. An index is constructed as a physical proxy of this first mode, which can be well predicted one season in advance, with an overall skill of 0.698 for 1979-2020. This result suggests a predictable prospect of the SASM, and we recommend the new index for real-time monitoring and prediction of the SASM.

Strong influence of north Pacific Ocean variability on Indian summer heatwaves

Increased occurrence of heatwaves across different parts of the world is one of the characteristic signatures of anthropogenic warming. With a 1.3 billion population, India is one of the hot spots that experience deadly heatwaves during May-June - yet the large-scale physical mechanism and teleconnection patterns driving such events remain poorly understood. Here using observations and controlled climate model experiments, we demonstrate a significant footprint of the far-reaching Pacific Meridional Mode (PMM) on the heatwave intensity (and duration) across North Central India (NCI) - the high risk region prone to heatwaves. A strong positive phase of PMM leads to a significant increase in heatwave intensity and duration over NCI (0.8-2 °C and 3-6 days; p < 0.05) and vice-versa. The current generation (CMIP6) climate models that adequately capture the PMM and their responses to NCI heatwaves, project significantly higher intensities of future heatwaves (0.5-1 °C; p < 0.05) compared to all model ensembles. These differences in the intensities of heatwaves could significantly increase the mortality (by ≈150%) and therefore can have substantial implications on designing the mitigation and adaptation strategies.

Compression complexity with ordinal patterns for robust causal inference in irregularly sampled time series

Distinguishing cause from effect is a scientific challenge resisting solutions from mathematics, statistics, information theory and computer science. Compression-Complexity Causality (CCC) is a recently proposed interventional measure of causality, inspired by Wiener–Granger’s idea. It estimates causality based on change in dynamical compression-complexity (or compressibility) of the effect variable, given the cause variable. CCC works with minimal assumptions on given data and is robust to irregular-sampling, missing-data and finite-length effects. However, it only works for one-dimensional time series. We propose an ordinal pattern symbolization scheme to encode multidimensional patterns into one-dimensional symbolic sequences, and thus introduce the Permutation CCC (PCCC). We demonstrate that PCCC retains all advantages of the original CCC and can be applied to data from multidimensional systems with potentially unobserved variables which can be reconstructed using the embedding theorem. PCCC is tested on numerical simulations and applied to paleoclimate data characterized by irregular and uncertain sampling and limited numbers of samples.

Widespread decline in winds promoted the growth of vegetation

Vegetation dynamics are sensitive to climate change. Wind is an important climate factor that can affect carbon fluxes by altering carbon uptake and emission rates; however, the impact of wind has not been fully considered in previous studies; therefore, exploring the characteristics of vegetation responses to wind speed is crucial to sustainable natural resource utilization and ecological restoration. In this study, the global leaf area index (LAI) from 1984 to 2013 was used to investigate the vegetation spatial heterogeneities, change processes, and relative contributions of climate change. The differences in vegetation responses to climate factors, such as precipitation (PRE), temperature (TEM), and wind speed (WD), were compared by considering the effects of wind. The results revealed that (1) the global vegetation (86.24%) exhibited a greening trend, among which evergreen broad-leaved forests (0.0052 a^-1) changed the most. (2) The wind speed explained 31.54% of the vegetation variations, which is higher than the contribution of other factors. (3) Reduction of wind speed had a positive impact on vegetation changes. The contribution of climate to vegetation growth increased by 8.14% when considering the effects wind speed, particularly in India and South America. Wind speed effects were essential for enhancing the vegetation dynamics assessment and improving the prediction accuracy of the model.

Impact of monsoon teleconnections on regional rainfall and vegetation dynamics in Haryana, India

Our study has investigated the impact of El Niño-Southern Oscillation (ENSO) on spatio-temporal dynamics of Indian summer monsoon rainfall (ISMR) as well as vegetation for a period of 1980 to 2019 at regional scale in Haryana, India. The gridded rainfall datasets of India Meteorological Department (IMD) were examined on monthly and seasonal scale using various statistical methods like mean climatology, coefficient of variation, slope of linear, Sen's slope, Mann-Kendall Z statistic, and hierarchical cluster analysis. The influence of ENSO on spatial distribution of ISMR was observed, where we found increasing and decreasing rainfall patterns during La Niña and El Niño years, respectively. We attempted to establish a link between ISMR and various teleconnections using time series of the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Laboratory, and statistically significant and positive correlation was observed with the Southern Oscillation Index (SOI), whereas significantly negative correlations were observed with SST of Niño 3, Niño 3.4, and Niño 4 regions. The gridded datasets of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis V5 (ERA5) were used to evaluate the influence of ENSO on atmospheric dynamics using lower and upper tropospheric wind circulation (850 hPa and200 hpa), vertically integrated moisture transport (VIMT), and surface moisture flux (SMF). We have used satellite-based normalised difference vegetation index (NDVI) datasets of the Global Inventory Monitoring and Modeling System (GIMMS) to investigate the impact of ENSO on vegetation dynamics of Haryana and found that NDVI values were higher and lower in case of La Niña and El Niño years, respectively.

Rising surface pressure over Tibetan Plateau strengthens indian summer monsoon rainfall over northwestern India

The dipole pattern (wetting over northwestern India and drying over the Indo-Gangetic plains and northeast India) in the rainfall trends is reported in many earlier studies. The exact cause of the rainfall trends' asymmetry remains unclear. We show that increasing trends over the northwestern parts are closely associated with the rise in surface pressure over the Tibetan Plateau. The surface pressure over Tibetan Plateau shows increasing trends (0.23 hPa decade^-1, p < 0.01) during 1979-2020. Easterlies across northwest India and southerlies over east India show rises of - 0.26 ms^-1 decade^-1 and 0.15 ms^-1 decade^-1, respectively, in line with Tibetan surface pressure trends. Water vapour transfer across northwest India has increased as a result of these changes in circulation. Increased lower-level easterlies carried more water vapour from the Bay of Bengal over northwest India. At the same time, stronger mid-level southerlies drove extratropical dry air out of India, strengthening the rainfall generating mechanism. Rising easterlies in northwest India also enhance vorticity along the monsoon trough, which promotes rainfall generation. Concurrently, because of the high surface pressure over Tibet, the circulation intensity of the mid-tropospheric cyclone over East India was weakened, resulting in less rain in the Indo-Gangetic region. The present study proposes that an increase in the surface pressure over Tibetan Plateau is an important factor contributing to the dipole pattern in the ISMR trends, particularly upward trends in rainfall over northwest India.

Warming-induced tipping points of Arctic and alpine shrub recruitment

Shrub recruitment, a key component of vegetation dynamics beyond forests, is a highly sensitive indicator of climate and environmental change. Warming-induced tipping points in Arctic and alpine treeless ecosystems are, however, little understood. Here, we compare two long-term recruitment datasets of 2,770 shrubs from coastal East Greenland and from the Tibetan Plateau against atmospheric circulation patterns between 1871 and 2010 Common Era. Increasing rates of shrub recruitment since 1871 reached critical tipping points in the 1930s and 1960s on the Tibetan Plateau and in East Greenland, respectively. A recent decline in shrub recruitment in both datasets was likely related to warmer and drier climates, with a stronger May to July El Niño Southern Oscillation over the Tibetan Plateau and a stronger June to July Atlantic Multidecadal Oscillation over Greenland. Exceeding the thermal optimum of shrub recruitment, the recent warming trend may cause soil moisture deficit. Our findings suggest that changes in atmospheric circulation explain regional climate dynamics and associated response patterns in Arctic and alpine shrub communities, knowledge that should be considered to protect vulnerable high-elevation and high-latitude ecosystems from the cascading effects of anthropogenic warming.

Asymmetric response of the Indian summer monsoon to positive and negative phases of major tropical climate patterns

The existing theories for the tropical teleconnections to Indian summer monsoon (ISM) are diverse in approaches. As a result, it is impossible to quantify the relative impacts of different tropical climate patterns on ISM, complying with a single physical mechanism. Here, we show that tropical teleconnections to ISM can be explained through net moisture convergence driven by surface pressure (Ps) gradients surrounding the Indian region. The positive and negative phases of major tropical climate patterns modulate these pressure gradients asymmetrically in the zonal and/or meridional directions leading to asymmetric changes in moisture convergence and ISM rainfall (ISMR). Stronger El Nino droughts than La Nina floods are due to greater decreased eastward moisture flux over the Arabian Sea during El Nino than the corresponding increase during La Nina driven by proportionate meridional Ps gradients. While the equatorial Atlantic Ocean's sea surface temperature in boreal summer and El Nino Southern Oscillation in the preceding winter changes ISMR significantly, moisture convergence anomalies driven by the Indian Ocean Dipole were insignificant. Moreover, while ISMR extremes during ENSO are due to asymmetric changes in zonal and meridional gradients in Ps, non-ENSO ISMR extremes arise due to the zonal gradient in zonally symmetric Ps anomalies.

Moisture variation inferred from tree rings in north central China and its links with the remote oceans

In this study we presented a composite standard chronology, spanning 1635-2018 to reconstruct May-July moisture variation in north central China. Our reconstruction revealed four severe dry epochs and five pronounced wet epochs. Additionally, spatial correlation analysis of our reconstruction with the actual self-calibrating Palmer drought severity index showed that our reconstruction was representative of large-scale May-July moisture changes. Both the severe dry and pronounced wet epochs showed one-to-one correspondence with other reconstructions nearby during their common periods, which demonstrated the reliability of our reconstruction backwards in time. Spectral analysis showed that significant spectral peaks were found at 2.1-3.8 years, which fell within the overall bandwidth of the El Niño-Southern Oscillations (ENSO). The spatial correlation patterns between our reconstruction and sea surface temperature (SST) in the equatorial eastern Pacific further confirmed the link between regional moisture and ENSO, with warm-phase ENSO resulting in low moisture and vice-versa. However, this link was time-dependent during the past four centuries, and was modulated by different phases of SST in the tropical Indian Ocean. Additionally, significant peaks at 24.9-46.5 years and spatial correlation patterns indicated that the Pacific Decadal Oscillation and the North Atlantic Oscillation may be the possible forcing factors of regional moisture at lower frequencies.

Regional and Local Impacts of the ENSO and IOD Events of 2015 and 2016 on the Indian Summer Monsoon—A Bhutan Case Study

The Indian Summer Monsoon (ISM) plays a vital role in the livelihoods and economy of those living on the Indian subcontinent, including the small, mountainous country of Bhutan. The ISM fluctuates over varying temporal scales and its variability is related to many internal and external factors including the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). In 2015, a Super El Niño occurred in the tropical Pacific alongside a positive IOD in the Indian Ocean and was followed in 2016 by a simultaneous La Niña and negative IOD. These events had worldwide repercussions. However, it is unclear how the ISM was affected during this time, both at a regional scale over the whole ISM area and at a local scale over Bhutan. First, an evaluation of data products comparing ERA5 reanalysis, TRMM and GPM satellite, and GPCC precipitation products against weather station measurements from Bhutan, indicated that ERA5 reanalysis was suitable to investigate ISM change in these two years. The reanalysis datasets showed that there was disruption to the ISM during this period, with a late onset of the monsoon in 2015, a shifted monsoon flow in July 2015 and in August 2016, and a late withdrawal in 2016. However, this resulted in neither a monsoon surplus nor a deficit across both years but instead large spatial-temporal variability. It is possible to attribute some of the regional scale changes to the ENSO and IOD events, but the expected impact of a simultaneous ENSO and IOD events are not recognizable. It is likely that 2015/16 monsoon disruption was driven by a combination of factors alongside ENSO and the IOD, including varying boundary conditions, the Pacific Decadal Oscillation, the Atlantic Multi-decadal Oscillation, and more. At a local scale, the intricate topography and orographic processes ongoing within Bhutan further amplified or dampened the already altered ISM.

Restored relationship between ENSO and Indian summer monsoon rainfall around 1999/2000

El Niño–Southern Oscillation (ENSO) was identified as the dominant predictor for the Indian summer monsoon rainfall (ISMR) in the early 1900s. An apparent weakening of the ENSO–ISMR relationship has been observed since the 1970s. Here, we found a clear restoration of the ENSO–ISMR relationship since 1999/2000. This restoring relationship is closely linked to the interdecadal transition of ENSO evolution and the associated sea surface temperature anomalies (SSTAs) over the tropical Atlantic. During 1979–1997, summer ENSO events mainly continued from the previous winter, which can drive apparent Atlantic Niña SSTAs to offset ENSO's impact on ISMR and weaken the ENSO–ISMR relationship. In contrast, when ENSO events newly emerge from late spring, as they have done more recently during 2000–2018, the associated tropical Atlantic SSTAs are weak and shift to the tropical North Atlantic, which can offset the contribution of Atlantic Niña and reinforce the ENSO–ISMR relationship. We identified that the diversity of ENSO's evolution, continuing from the previous winter or emerging from late spring, is the dominant factor perturbing the ENSO–ISMR relationship in recent epochs, with tropical Atlantic SSTAs as the crucial bridge. This finding should be considered in our efforts to improve ISMR prediction.

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The relationship between ENSO and ISMR has been restoring since 1999/2000

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The transition of ENSO's evolution, continuing or emerging, is the dominant factor

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The response of tropical Atlantic SSTAs to ENSO's evolution are the crucial bridge

Assessment of Merged Satellite Precipitation Datasets in Monitoring Meteorological Drought over Pakistan

The current study evaluates the potential of merged satellite precipitation datasets (MSPDs) against rain gauges (RGs) and satellite precipitation datasets (SPDs) in monitoring meteorological drought over Pakistan during 2000–2015. MSPDs evaluated in the current study include Regional Weighted Average Least Square (RWALS), Weighted Average Least Square (WALS), Dynamic Clustered Bayesian model Averaging (DCBA), and Dynamic Bayesian Model Averaging (DBMA) algorithms, while the set of SPDs is Global Precipitation Measurement (GPM)-based Integrated Multi-Satellite Retrievals for GPM (IMERG-V06), Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA 3B42 V7), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and ERA-Interim (re-analyses dataset). Several standardized precipitation indices (SPIs), including SPI-1, SPI-3, and SPI-12, are used to evaluate the performances of RGs, SPDs, and MSPDs across Pakistan as well as on a regional scale. The Mann–Kendall (MK) test is used to assess the trend of meteorological drought across different climate regions of Pakistan using these SPI indices. Results revealed higher performance of MSPDs than SPDs when compared against RGs for SPI estimates. The seasonal evaluation of SPIs from RGs, MSPDs, and SPDs in a representative drought year (2008) revealed mildly to moderate wetness in monsoon season while mild to moderate drought in winter season across Pakistan. However, the drought severity ranges from mild to severe drought in different years across different climate regions. MAPD (mean absolute percentage difference) shows high accuracy (MAPD <10%) for RWALS-MSPD, good accuracy (10% < MAPD <20%) for WALS-MSPD and DCBA-MSPD, while good to reasonable accuracy (20% < MAPD < 50%) for DCBA in different climate regions. Furthermore, MSPDs show a consistent drought trend as compared with RGs, while SPDs show poor performance. Overall, this study demonstrated significantly improved performance of MSPDs in monitoring the meteorological drought.

Spatial Variability of Rainfall Trends in Sri Lanka from 1989 to 2019 as an Indication of Climate Change

Analysis of long-term rainfall trends provides a wealth of information on effective crop planning and water resource management, and a better understanding of climate variability over time. This study reveals the spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. The exclusivity of the study is the use of rainfall data that provide spatial variability instead of the traditional location-based approach. Henceforth, daily rainfall data available at Climate Hazards Group InfraRed Precipitation corrected with stations (CHIRPS) data were used for this study. The geographic information system (GIS) is used to perform spatial data analysis on both vector and raster data. Sen’s slope estimator and the Mann–Kendall (M–K) test are used to investigate the trends in annual and seasonal rainfall throughout all districts and climatic zones of Sri Lanka. The most important thing reflected in this study is that there has been a significant increase in annual rainfall from 1989 to 2019 in all climatic zones (wet, dry, intermediate, and Semi-arid) of Sri Lanka. The maximum increase is recorded in the wet zone and the minimum increase is in the semi-arid zone. There could be an increased risk of floods in the southern and western provinces in the future, whereas areas in the eastern and southeastern districts may face severe droughts during the northeastern monsoon. It is advisable to introduce effective drought and flood management and preparedness measures to reduce the respective hazard risk levels.

Statistical physics approaches to the complex Earth system

Global warming, extreme climate events, earthquakes and their accompanying socioeconomic disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, multiple interactions and complex structures of the Earth system, the understanding and, in particular, the prediction of such disruptive events represent formidable challenges to both scientific and policy communities. During the past years, the emergence and evolution of Earth system science has attracted much attention and produced new concepts and frameworks. Especially, novel statistical physics and complex networks-based techniques have been developed and implemented to substantially advance our knowledge of the Earth system, including climate extreme events, earthquakes and geological relief features, leading to substantially improved predictive performances. We present here a comprehensive review on the recent scientific progress in the development and application of how combined statistical physics and complex systems science approaches such as critical phenomena, network theory, percolation, tipping points analysis, and entropy can be applied to complex Earth systems. Notably, these integrating tools and approaches provide new insights and perspectives for understanding the dynamics of the Earth systems. The overall aim of this review is to offer readers the knowledge on how statistical physics concepts and theories can be useful in the field of Earth system science.

Fingerprint of volcanic forcing on the ENSO-Indian monsoon coupling

Coupling of the El Niño-Southern Oscillation (ENSO) and Indian monsoon (IM) is central to seasonal summer monsoon rainfall predictions over the Indian subcontinent, although a nonstationary relationship between the two nonlinear phenomena can limit seasonal predictability. Radiative effects of volcanic aerosols injected into the stratosphere during large volcanic eruptions (LVEs) tend to alter ENSO evolution; however, their impact on ENSO-IM coupling remains unclear. Here, we investigate how LVEs influence the nonlinear behavior of the ENSO and IM dynamical systems using historical data, 25 paleoclimate reconstructions, last-millennium climate simulations, large-ensemble targeted climate sensitivity experiments, and advanced analysis techniques. Our findings show that LVEs promote a significantly enhanced phase-synchronization of the ENSO and IM oscillations, due to an increase in the angular frequency of ENSO. The results also shed innovative insights into the physical mechanism underlying the LVE-induced enhancement of ENSO-IM coupling and strengthen the prospects for improved seasonal monsoon predictions.

A tree-ring δ18O based reconstruction of East Asia summer monsoon over the past two centuries

The East Asian summer monsoon (EASM) exhibits considerable decadal variations since the late 20th century. Efforts to examine long-term behaviors and dynamics of the EASM are impeded largely due to the shortness of instrumental meteorological records. So far, reconstructions of the EASM with annual resolution from its core regions remain limited. We conduct the first 200-year robust EASM reconstruction based on tree-ring cellulose δ¹⁸O records derived from Pinus massoniana trees growing in the middle Yangtze River basin, one of the core EASM areas. The δ¹⁸O chronology accounts for 46.2% of the actual variation in an index of the EASM from 1948 to 2014. The reconstructed EASM indicates that the monsoon intensity was below average before the 1950s, peaked in the 1950s-1970s, and then began to decline. The reconstructed EASM is negatively correlated with the El Niño-Southern Oscillation (ENSO), but this teleconnection is dynamic through time, i.e. enhanced (reduced) ENSO variability coheres with strong (weak) EASM-ENSO connections. In addition, despite high ENSO variability since the 1980s, the EASM-ENSO relationship weakened possibly due to anthropogenic impact, particularly aerosol emissions.

Hydrological cycle changes under global warming and their effects on multiscale climate variability

Despite a globally uniform increase in the concentrations of emitted greenhouse gases, radiatively forced surface warming can have significant spatial variations. These define warming patterns that depend on preexisting climate states and through atmospheric and oceanic dynamics can drive changes of the hydrological cycle with global-scale feedbacks. Our study reviews research progress on the hydrological cycle changes and their effects on multiscale climate variability. Overall, interannual variability is expected to become stronger in the Pacific and Indian Oceans and weaker in the Atlantic. Global monsoon rainfall is projected to increase and the wet season to lengthen despite a slowdown of atmospheric circulation. Strong variations among monsoon regions are likely to emerge, depending on surface conditions such as orography and land-sea contrast. Interdecadal climate variability is expected to modulate the globally averaged surface temperature change with pronounced anomalies in the polar and equatorial regions, leading to prolonged periods of enhanced or reduced warming. It is emphasized that advanced global observations, regional simulations, and process-level investigations are essential for improvements in understanding, predicting, and projecting the modes of climate variability, monsoon sensitivity, and energetic fluctuations in a warming climate.

Surface chlorophyll anomalies associated with Indian Ocean Dipole and El Niño Southern Oscillation in North Indian Ocean: a case study of 2006-2007 event

North Indian Ocean witnesses varied dynamical response due to independent climate modes such as Indian Ocean Dipole (IOD)/El Niño Southern Oscillations (ENSO) and their co-occurrences. These modes have a significant impact on ocean productivity, which in turn shows feedback for the strengthening of these patterns. Keeping this in view, the present work attempts to analyze the biological activity during the combined influence of positive IOD with El Niño during 2006-2007 event. To divulge the biological variability along with the dynamical response, the study includes intra-annual variability surface chlorophyll anomaly with D20 anomaly using satellite observations. Here, the individual role of IOD and ENSO on both surface chlorophyll and D20 is segregated through partial regression analysis for a period of 25 years (1993-2017). By the regression method, it can be seen varied chlorophyll response for the 2006-2007 event with the IOD forcing leads to the major spatial and temporal variability with positive anomalies in Eastern Equatorial Indian Ocean (EEIO) (generally oligotrophic), Northwestern Bay of Bengal (NWBoB), and Northwestern Arabian Sea (NAS2) where production begins in fall intermonsoon and peaks up during November. On the other hand, negative anomalies are observed around the southern tip of India (SBoB) and the Northern Arabian Sea (NAS1). While ENSO depicts the high surface chlorophyll variability in the Western Indian Ocean (WIO1, WIO2) with negative anomalies of surface chlorophyll. This study observed an asymmetric response of chlorophyll variability over the North Indian Ocean during the 1997-1998 and 2006-2007 events with a major influence of IOD mode compared with the El Niño. Therefore, understanding the chlorophyll anomalies during different climate modes will help us to better understand the interannual variability and improve the predictability of chlorophyll productivity regions.

Reconciling the Discrepancy of Post-Volcanic Cooling Estimated from Tree-Ring Reconstructions and Model Simulations over the Tibetan Plateau

Volcanic eruptions are a major factor influencing global climate variability, usually with a cooling effect. The magnitudes of post-volcanic cooling from historical eruptions estimated by tree-ring reconstructions differ considerably with the current climate model simulations. It remains controversial on what is behind such a discrepancy. This study investigates the role of internal climate variability (i.e., El Niño/Southern Oscillation (ENSO) warm phase) with a regional focus on the Tibetan Plateau (TP), using tree-ring density records and long historical climate simulations from the fifth Coupled Model Intercomparsion Project (CMIP5). We found that El Niño plays an important role behind the inconsistencies between model simulations and reconstructions. Without associated El Niño events, model simulations agree well with tree-ring records. Divergence appears when large tropical eruptions are followed by an El Niño event. Model simulations, on average, tend to overestimate post-volcanic cooling during those periods as the occurrence of El Niño is random as part of internal climate variability.

A Modal Rendition of ENSO Diversity

The El Nino and Southern Oscillation (ENSO) ‘diversity’ has been considered as a major factor limiting its predictability, a critical need for disaster mitigation associated with the trademark climatic swings of the ENSO. Improving climate models for ENSO forecasts relies on deeper understanding of the ENSO diversity but currently at a nascent stage. Here, we show that the ENSO diversity thought previously as ‘complex,’ arises largely as varied contributions from three leading modes of the ENSO to a given event. The ENSO ‘slow manifold’ can be fully described by three leading predictable modes, a quasi-quadrennial mode (QQD), a quasi-biennial (QB) mode and a decadal modulation of the quasi-biennial (DQB). The modal description of ENSO provides a framework for understanding the predictability of and global teleconnections with the ENSO. We further demonstrate it to be a useful framework for understanding biases of climate models in simulating and predicting the ENSO. Therefore, skillful prediction of all shades of ENSO depends critically on the coupled models’ ability to simulate the three modes with fidelity, providing basis for optimism for future of ENSO forecasts.

Elevated aerosol layer over South Asia worsens the Indian droughts

Droughts have become more severe and recurrent over the Indian sub-continent during the second half of the twentieth century, leading to more severe hydro-climatic and socio-economic impacts over one of the most densely populated parts of the world. So far, droughts have mostly been connected to circulation changes concomitant with the abnormal warming over the Pacific Ocean, prevalently known as "El Niño". Here, exploiting observational data sets and a series of dedicated sensitivity experiments, we show that the severity of droughts during El Niño is amplified (17%) by changes in aerosols. The model experiments simulate the transport of boundary layer aerosols from South Asian countries to higher altitudes (12-18 km) where they form the Asian Tropopause Aerosol Layer (ATAL) (~ 60-120°E, 20-40°N). During El Niño, the anomalous overturning circulation from the East Asian region further enriches the thickness of aerosol layers in the ATAL over the northern part of South Asia. The anomalous aerosol loading in the ATAL reduces insolation over the monsoon region, thereby exacerbating the severity of drought by further weakening the monsoon circulation. Future increases in industrial emissions from both East and South Asia will lead to a wider and thicker elevated aerosol layer in the upper troposphere, potentially amplifying the severity of droughts.

SST Indexes in the Tropical South Atlantic for Forecasting Rainy Seasons in Northeast Brazil

May-to-July and February-to-April represent peak rainy seasons in two sub-regions of Northeast Brazil (NEB): Eastern NEB and Northern NEB respectively. In this paper, we identify key oceanic indexes in the tropical South Atlantic for driving these two rainy seasons. In Eastern NEB, the May-to-July rainfall anomalies present a positive relationship with the previous boreal winter sea surface temperature anomalies (SSTA) in the southeast tropical Atlantic (20°–10° S; 10° W–5° E). This positive relationship, which spread westward along the southern branch of the South Equatorial Current, is associated with northwesterly surface wind anomalies. A warmer sea surface temperature in the southwestern Atlantic warm pool increases the moisture flux convergence, as well as its ascending motion and, hence, the rainfall along the adjacent coastal region. For the Northern NEB, another positive relationship is observed between the February-to-April rainfall anomalies and the SSTA of the previous boreal summer in the Atlantic Niño region (3° S–3° N; 20° W–0°). The negative remote relationship noticeable between the Northern NEB rainfall and the concomitant Pacific Niño/Niña follows cold/warm events occurring during the previous boreal summer in the eastern equatorial Atlantic. The southeastern tropical Atlantic and Atlantic Niño SSTA indexes may, then, be useful to predict seasonal rainfall over the Eastern and Northern NEB, respectively, for about a 6 month leading period. The ability of both southeastern tropical Atlantic and Atlantic Niño SSTA indexes to forecast the Eastern and Northern NEB rainfall, with about a 6 month lead time, is improved when these indexes are respectively combined with the Niño3 (5° S–5° N; 150°–90° W) and the northeast subtropical Atlantic (20° N–35° N, 45° W–20° W), mainly from the 1970’s climate shift.

Increased drought events in southwest China revealed by tree ring oxygen isotopes and potential role of Indian Ocean Dipole

The highlands in southwestern China experience pronounced fluctuations in the hydroclimate with profound impacts on agriculture and economics. To investigate the drought history of this region beyond instrumental records, a tree ring cellulose oxygen isotope (δ¹⁸O_c) chronology was developed for the period 1733-2013 using samples collected from six Larix trees in the low-latitude highlands (LLH) of southwestern China. The analysis revealed that δ¹⁸O_c is significantly correlated with the rainy season (May-October) precipitation and relative humidity, as well as drought severity. The δ¹⁸O_c chronology accounts for 46% of the observed variance in the rainy season precipitation and it was subsequently used to reconstruct precipitation. The reconstructed precipitation reveals an apparent drying trend since 1840, accompanied by increasingly frequent drought events since 1970. Interdecadal variability is also present, characterized with two distinct wet periods in 1740-1760 and 1800-1900 and two drier periods in 1760-1800 and 1900-2013. On the interannual timescale, the LLH precipitation was modulated collectively by the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD). There appears to be an enhanced precipitation-IOD relationship since 1970 in response to the increase in positive-IOD events, implying an increasing likelihood of drought for the southwest China LLH.

The weakening relationship between Eurasian spring snow cover and Indian summer monsoon rainfall

Substantial progress has been made in understanding how Eurasian snow cover variabilities affect the Indian summer monsoon, but the snow-monsoon relationship in a warming atmosphere remains controversial. Using long-term observational snow and rainfall data (1967-2015), we identified that the widely recognized inverse relationship of central Eurasian spring snow cover with the Indian summer monsoon rainfall has disappeared since 1990. The apparent loss of this negative correlation is mainly due to the central Eurasian spring snow cover no longer regulating the summer mid-tropospheric temperature over the Iranian Plateau and surroundings, and hence the land-ocean thermal contrast after 1990. A reduced lagged snow-hydrological effect, resulting from a warming-induced decline in spring snow cover, constitutes the possible mechanism for the breakdown of the snow-air temperature connection after 1990. Our results suggest that, in a changing climate, Eurasian spring snow cover may not be a faithful predictor of the Indian summer monsoon rainfall.

Effects of ENSO on Temperature, Precipitation, and Potential Evapotranspiration of North India’s Monsoon: An Analysis of Trend and Entropy

The influence of El Niño Southern Oscillation (ENSO) on the north Indian temperature, precipitation, and potential evapotranspiration (PET) change patterns were evaluated during the monsoon season across the last century. Trends and shifts in 146 districts were assessed using nonparametric statistical tests. To quantify their temporal variation, the concept of apportionment entropy was applied to both the annual and seasonal scales. Results suggest that the El Niño years played a greater role in causing hydro-climatological changes compared to the La Niña or neutral years. El Niño was more influential in causing shifts compared to trends. For certain districts, a phase change in ENSO reversed the trend/shift direction. The century-wide analysis suggested that the vast majority of the districts experienced significant decreasing trends/shifts in temperature and PET. However, precipitation experienced both increasing and decreasing trends/shifts based on the location of the districts. Entropy results suggested a lower apportionment of precipitation compared to the other variables, indicating an intermittent deviation of precipitation pattern from the generic trend. The findings may help understand the effects of ENSO on the hydro-climatological variables during the monsoon season. Practitioners may find the results useful as monsoon is the most important season for India causing climate extremes.

Variation in Climate Signals in Teak Tree-Ring Chronologies in Two Different Growth Areas

We developed two tree-ring chronologies of teak (Tectona grandis L.f.) from Mae Tuen (462-year, 1555–2016) and Umphang (165-year, 1852–2016) in Tak province, northwestern Thailand. The chronologies were based on 67 and 71 living teak trees, respectively. We used crossdating methods to check and verify the tree-ring width data and tree-ring chronology construction using the ARSTAN program. In this study, the two teak tree-ring chronologies from two different growth areas could not be crossdated. The relationship among these chronologies is, thus, relatively low (r = 0.33, n = 165, p < 0.01). This result shows that the growth of tree-ring structure from two sites can be affected by a variety of non-climatic patterns due to site variation, such as topography, nutrient, light, and internal factors. However, these chronologies have a significant positive correlation with rainfall, during the pre-monsoon season (April to May). As demonstrated by the spatial correlation patterns, these chronologies represent April to May rainfall, which was a limiting factor of teak growth from northwestern Thailand. While the difference in surface temperatures of the Indian Ocean Dipole (IOD) might not be affected by rainfall, its unstable relationship with the El Niño-Southern Oscillation (ENSO) was noted to have occurred.

A Review of Atmosphere–Ocean Forcings Outside the Tropical Pacific on the El Niño–Southern Oscillation Occurrence

The El Niño–Southern Oscillation (ENSO) is the strongest interannual air–sea coupled variability mode in the tropics, and substantially impacts the global weather and climate. Hence, it is important to improve our understanding of the ENSO variability. Besides the well-known air–sea interaction process over the tropical Pacific, recent studies indicated that atmospheric and oceanic forcings outside the tropical Pacific also play important roles in impacting and modulating the ENSO occurrence. This paper reviews the impacts of the atmosphere–ocean variability outside the tropical Pacific on the ENSO variability, as well as their associated physical processes. The review begins with the contribution of the atmosphere–ocean forcings over the extratropical North Pacific, Atlantic, and Indian Ocean on the ENSO occurrence. Then, an overview of the extratropical atmospheric forcings over the Northern Hemisphere (including the Arctic Oscillation and the Asian monsoon systems) and the Southern Hemisphere (including the Antarctic Oscillation and the Pacific–South American teleconnection), on the ENSO occurrence, is presented. It is shown that the westerly (easterly) wind anomaly over the tropical western Pacific is essential for the occurrence of an El Niño (a La Niña) event. The wind anomalies over the tropical western Pacific also play a key role in relaying the impacts of the atmosphere–ocean forcings outside the tropical Pacific on the ENSO variability. Finally, some relevant questions, that remain to be explored, are discussed.

Impact of snow-darkening by deposition of light-absorbing aerosols on snow cover in the Himalaya-Tibetan-Plateau and influence on the Asian Summer monsoon: A possible mechanism for the Blanford Hypothesis

The impact of snow darkening by deposition of light absorbing aerosols (LAAs) on snow cover over the Himalaya-Tibetan-Plateau (HTP) and influence on the Asian summer monsoon are investigated using the NASA Goddard Earth Observing System Model Version 5 (GEOS-5). We find that during April-May-June, deposition of LAAs on snow leads to a reduction in surface albedo, initiating a sequence of feedback processes, starting with increased net surface solar radiation, rapid snowmelt in HTP and warming of the surface and upper troposphere, followed by enhanced low-level southwesterlies and increased dust loading over the Himalayas-Indo-Gangetic Plain. The warming is amplified by increased dust aerosol heating, and subsequently amplified by latent heating from enhanced precipitation over the Himalaya foothills and northern India, via the Elevated Heat Pump (EHP) effect during June-July-August. The reduced snow cover in the HTP anchors the enhanced heating over the Tibetan Plateau and its southern slopes, in conjunction with an enhancement of the Tibetan Anticyclone, and the development of an anomalous Rossby wavetrain over East Asia, leading to weakening of the subtropical westerly jet, and northward displacement and intensification of the Mei-Yu rainbelt. Our results suggest that atmosphere-land heating induced by LAAs, particularly desert dust play a fundamental role in physical processes underpinning the snow-monsoon relationship proposed by Blanford more than a century ago.

A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges–Brahmaputra–Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.

Temporal evolution of hydroclimatic teleconnection and a time-varying model for long-lead prediction of Indian summer monsoon rainfall

Several cases of failure in the prediction of Indian Summer Monsoon Rainfall (ISMR) are the major concern for long-lead prediction. We propose that this is due to the temporal evolution of association/linkage (inherent concept of temporal networks) with various factors and climatic indices across the globe, such as El Niño-Southern Oscillation (ENSO), Equatorial Indian Ocean Oscillation (EQUINOO), Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO) etc. Static models establish time-invariant (permanent) connections between such indices (predictors) and predictand (ISMR), whereas we hypothesize that such systems are temporally varying in nature. Considering hydroclimatic teleconnection with two major climate indices, ENSO and EQUINOO, we showed that the temporal persistence of the association is as low as three years. As an application of this concept, a statistical time-varying model is developed and the prediction performance is compared against its static counterpart (time-invariant model). The proposed approach is able to capture the ISMR anomalies and successfully predicts the severe drought years too. Specifically, 64% more accurate performance (in terms of RMSE) is achievable by the recommended time-varying approach as compared to existing time-invariant concepts.

El Niño–Southern Oscillation and its impact in the changing climate

Extensive research has improved our understanding and forecast of the occurrence, evolution and global impacts of the El Niño–Southern Oscillation (ENSO). However, ENSO changes as the global climate warms up and it exhibits different characteristics and climate impacts in the twenty-first century from the twentieth century. Climate models project that ENSO will also change in the warming future and have not reached an agreement about the flavor, as to the intensity and the frequency, of future ENSO conditions. This article presents the conventional view of ENSO properties, dynamics and teleconnections, and reviews the emerging understanding of the diversity and associated climate impacts of ENSO. It also reviews the results from investigations into the possible changes in ENSO under the future global-warming scenarios.

Indian summer monsoon variability forecasts in the North American multimodel ensemble

The representation of the seasonal mean and interannual variability of the Indian summer monsoon rainfall (ISMR) in nine global ocean-atmosphere coupled models that participated in the North American Multimodal Ensemble (NMME) phase 1 (NMME:1), and in nine global ocean-atmosphere coupled models participating in the NMME phase 2 (NMME:2) from 1982-2009, is evaluated over the Indo-Pacific domain with May initial conditions. The multi-model ensemble (MME) represents the Indian monsoon rainfall with modest skill and systematic biases. There is no significant improvement in the seasonal forecast skill or interannual variability of ISMR in NMME:2 as compared to NMME:1. The NMME skillfully predicts seasonal mean sea surface temperature (SST) and some of the teleconnections with seasonal mean rainfall. However, the SST-rainfall teleconnections are stronger in the NMME than observed. The NMME is not able to capture the extremes of seasonal mean rainfall and the simulated Indian Ocean-monsoon teleconnections are opposite to what are observed.

Latitudinal variation in summer monsoon rainfall over Western Ghat of India and its association with global sea surface temperatures

The Western Ghats (WG) of India are basically north-south oriented mountains having narrow zonal width with a steep rising western face. The summer monsoon winds during June to September passing over the Arabian Sea are obstructed by the WG and thus orographically uplift to produce moderate-to-heavy precipitation over the region. However, it is seen that characteristic features of rainfall distribution during the season vary from north to south. Also its correlation with all-India summer monsoon rainfall increases from south to north. In the present study, an attempt is also made to examine long-term as well as short-term trends and variability in summer monsoon rainfall over different subdivisions of WG using monthly rainfall data for the period 1871-2014. Konkan & Goa and Coastal Karnataka show increase in rainfall from 1871 to 2014 in all individual summer monsoon months. Short-term trend analysis based on 31-year sliding window indicates that the trends are not monotonous, but has epochal behavior. In recent epoch, magnitudes of negative trends are consistently decreasing and have changed its sign to positive during 1985-2014. It has been observed that Indian Ocean Dipole (IOD) plays a dominant positive role in rainfall over entire WG in all summer monsoon months, whereas role of Nino regions are asymmetric over WG rainfall. Indian summer monsoon is known for its negative relationship with Nino SST. Negative correlations are also seen for WG rainfall with Nino regions but only during onset and withdrawal phase. During peak monsoon months July and August subdivisions of WG mostly show positive correlation with Nino SST.

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance

Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2–3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

Realism of modelled Indian summer monsoon correlation with the tropical Indo-Pacific affects projected monsoon changes

El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) tend to exert an offsetting impact on Indian summer monsoon rainfall (ISMR), with an El Niño event tending to lower, whereas a positive IOD tending to increase ISMR. Simulation of these relationships in Phase Five of the Coupled Model Intercomparison Project has not been fully assessed, nor is their impact on the response of ISMR to greenhouse warming. Here we show that the majority of models simulate an unrealistic present-day IOD-ISMR correlation due to an overly strong control by ENSO. As such, a positive IOD is associated with an ISMR reduction in the simulated present-day climate. This unrealistic present-day correlation is relevant to future ISMR projection, inducing an underestimation in the projected ISMR increase. Thus uncertainties in ISMR projection can be in part induced by present-day simulation of ENSO, the IOD, their relationship and their rainfall correlations.

Hydroclimatic contrasts over Asian monsoon areas and linkages to tropical Pacific SSTs

Knowledge of spatial and temporal hydroclimatic differences is critical in understanding climatic mechanisms. Here we show striking hydroclimatic contrasts between northern and southern parts of the eastern margin of the Tibetan Plateau (ETP), and those between East Asian summer monsoon (EASM) and Indian summer monsoon (ISM) areas during the past ~2,000 years. During the Medieval Period, and the last 100 to 200 years, the southern ETP (S-ETP) area was generally dry (on average), while the northern ETP (N-ETP) area was wet. During the Little Ice Age (LIA), hydroclimate over S-ETP areas was wet, while that over N-ETP area was dry (on average). Such hydroclimatic contrasts can be broadly extended to ISM and EASM areas. We contend that changes in sea surface temperatures (SSTs) of the tropical Pacific Ocean could have played important roles in producing these hydroclimatic contrasts, by forcing the north-south movement of the Intertropical Convergence Zone (ITCZ) and intensification/slowdown of Walker circulation. The results of sensitivity experiments also support such a proposition.