Variability Of Monsoon Rainfall Research Articles

Assessing seasonal variation and trends in rainfall patterns of Madhya Pradesh, Central India

Abstract Climate change is a worldwide problem caused by various anthropogenic activities, leading to changes in hydroclimatic variables like temperature, rainfall, riverine flow, and extreme hydrometeorological events. In India, significant changes are noted in its natural resources and agriculture sectors. In this study, we analysed the long-term spatio-temporal change in rainfall patterns of Madhya Pradesh, Central India, using Indian Meteorological Department high-resolution gridded data from 439 grid points. The coefficient of variance analysis showed low variability in annual and monsoon rainfall but significant variability in pre-monsoon, post-monsoon, and winter seasons, indicating considerable seasonal variation. Pre-monsoon rainfall exhibited an increasing trend (0.018 mm annually), while annual, monsoon, post-monsoon, and winter rainfall showed decreasing trends. Change point analysis identified shifts in rainfall patterns in 1998 (monsoon, annual), 1955 (pre-monsoon), 1987 (post-monsoon), and 1986 (winter). Spatio-temporal distribution maps depicted irregular rainfall, with some areas experiencing drastic declines in precipitation after 1998. The maximum average annual rainfall reduced from 1,769 to 1,401 mm after 1998 affecting water availability. The study's findings highlight a significant shift in Madhya Pradesh's seasonal rainfall distribution after 1998, urging researchers and policymakers to address water-intensive cropping practices and foster climate resilience for a sustainable future in the region.

Evaluation of MERRA-2 Black Carbon Characteristics and Potential Sources over China

Black carbon (BC), an important component of atmospheric aerosol, plays a significant role in regional climate, hydrological cycle, variation of monsoon rainfall, and human health. The 40-year detailed atmospheric BC over China from 1981 to 2020 is systematically investigated through the MERRA-2 reanalysis dataset. MERRA-2 BC generally showed a good correlation (R = 0.68) compared with 673 monthly samples from ground-based observation at 35 stations around China. The overall annual average of MERRA-2 BC concentration over China is 1.15 μg/m3, with a fast growth rate during 1981–2007 and a relatively slow decrease after that. The winter season has the highest mean concentration of BC, followed by autumn and spring, whereas summer shows relatively weaker values. The order of annual average BC concentrations during 1981–2020 is Beijing-Tianjin-Hebei region (BTH, 4.02 μg/m3) > Sichuan Basin (SB, 3.94 μg/m3) > Yangtze River Delta (YRD, 2.68 μg/m3) > Pearl River Delta (PRD, 1.47 μg/m3). The monthly mean BC concentrations over the BTH, YRD, PRD and SB are estimated to be smallest 3.18 μg/m3 in May, 1.94 μg/m3 in August, 0.82 μg/m3 in July, 3.04 μg/m3 in June, respectively, whilst largest consistently in December with 5.09 μg/m3, 3.83 μg/m3, 2.12 μg/m3, and 5.41 μg/m3, respectively. Our study indicates the primary potential source areas for BC are concentrated in the research city and its surroundings. Beijing and Chengdu are more BC-polluted areas than Shanghai and Guangzhou. Long-distance, regional transfer from south BTH contributes importantly to BC pollution in Beijing under the influence of prevailing southerly winds. The geographical location of Chengdu causes the transport and accumulation of BC inside the SB.

Weakening of decadal variation of Northern Hemisphere land monsoon rainfall under global warming

Over the past century, Northern Hemisphere (NH) land monsoon rainfall (NHLMR) experienced significant decadal to multidecadal variations, mainly driven by an east–west sea surface temperature (SST) contrast over the Pacific (EWPC) and an interhemispheric North Atlantic–South Indian Ocean SST dipole (NAID). However, how the NHLMR’s decadal variation would vary and whether the oceanic forcing could continue to drive it in a warming world remain unexplored. Here, by analyzing 24 Coupled Model Intercomparison Project Phase 6 (CMIP6) models’ historical simulations and future projections, we show that the leading mode of decadal NHLMR will retain its nearly-uniform spatial pattern and representation of the NHLMR’s intensity. In the future, the significant periodicities of decadal NHLMR are shortened as emissions levels increase. The intensity of decadal NHLMR variation will experience a comprehensive decline under various emission scenarios, which may link to the weakened intensity of NAID and EWPC. Although the relationship between EWPC and decadal NHLMR is slightly weakened in the future, EWPC will remain a primary driver while NAID is no longer. The significant historical correlation between NAID and NHLMR is mainly attributed to the influence of increased anthropogenic aerosols emission. However, the NAID-NHLMR linkage would no longer exist owing to the decline of anthropogenic aerosol emission in the future.

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.

Spatiotemporal Rainfall Variability and Trends over the Mahi Basin, India

Climate change can have an influence on rainfall that significantly affects the magnitude frequency of floods and droughts. Therefore, the analysis of the spatiotemporal distribution, variability, and trends of rainfall over the Mahi Basin in India is an important objective of the present work. Accordingly, a serial autocorrelation, coefficient of variation, Mann–Kendall (MK) and Sen’s slope test, innovative trend analysis (ITA), and Pettitt’s test were used in the rainfall analysis. The outcomes were derived from the monthly precipitation data (1901–2012) of 14 meteorology stations in the Mahi Basin. The serial autocorrelation results showed that there is no autocorrelation in the data series. The rainfall statistics denoted that the Mahi Basin receives 94.8% of its rainfall (821 mm) in the monsoon period (June–September). The normalized accumulated departure from the mean reveals that the annual and monsoon rainfall of the Mahi Basin were below average from 1901 to 1930 and above average from 1930 to 1990, followed by a period of fluctuating conditions. Annual and monsoon rainfall variations increase in the lower catchment of the basin. The annual and monsoon rainfall trend analysis specified a significant declining tendency for four stations and an increasing tendency for 3 stations, respectively. A significant declining trend in winter rainfall was observed for 9 stations under review. Likewise, out of 14 stations, 9 stations denote a significant decrease in pre-monsoon rainfall. Nevertheless, there is no significant increasing or decreasing tendency in annual, monsoon, and post-monsoon rainfall in the Mahi Basin. The Mann–Kendall test and innovative trend analysis indicate identical tendencies of annual and seasonal rainfall on the basin scale. The annual and monsoon rainfall of the basin showed a positive shift in rainfall after 1926. The rainfall analysis confirms that despite spatiotemporal variations in rainfall, there are no significant positive or negative trends of annual and monsoon rainfall on the basin scale. It suggests that the Mahi Basin received average rainfall (867 mm) annually and in the monsoon season (821 mm) from 1901 to 2012, except for a few years of high and low rainfall. Therefore, this study is important for flood and drought management, agriculture, and water management in the Mahi Basin.

Variations in Indian Summer Monsoon Rainfall patterns in Changing Climate

The Indian summer monsoon is a large scale synoptic and dominant circulation feature which is largely restricted to the summer months from June to September. The proper understanding of rainfall pattern and its trends may help water resources development, agriculture sector and to take decisions for developmental activities. The present study is an attempt to evaluate the spatial variability in Indian summer monsoon rainfall (ISMR) over the Indian subcontinent during the climatological period (1901-2010). The long-term annual, decadal and tricadal monsoon rainfall differences are considered for the period 1901-2010 during the monsoon (June-September) and peak monsoon month (July-August). The results show concern for the major areas of upper Himalaya, Western and peninsular India where positive rainfall difference/increase rainfall with 0.2 to 1 mm/day variation have been reported during the monsoon and peak monsoon months. Also, decrease in rainfall have been reported over Western Ghats, Indo-Gangetic Plain (IGP) and some central Indian regions in the range of -0.6 to -1.5 mm/day. Further, a broad overview of the study shows an enhancement of ISMR over Western India whereas a substantial decline over Northeast Indian regions which suggests the western shift of ISMR in changing climate.

Glacial changes in sea level modulated millennial-scale variability of Southeast Asian autumn monsoon rainfall

Most paleoclimate studies of Mainland Southeast Asia hydroclimate focus on the summer monsoon, with few studies investigating rainfall in other seasons. Here, we present a multiproxy stalagmite record (45,000 to 4,000years) from central Vietnam, a region that receives most of its annual rainfall in autumn (September-November). We find evidence of a prolonged dry period spanning the last glacial maximum that is punctuated by an abrupt shift to wetter conditions during the deglaciation at ~14 ka. Paired with climate model simulations, we show that sea-level change drives autumn monsoon rainfall variability on glacial-orbital timescales. Consistent with the dry signal in the stalagmite record, climate model simulations reveal that lower glacial sea level exposes land in the Gulf of Tonkin and along the South China Shelf, reducing convection and moisture delivery to central Vietnam. When sea level rises and these landmasses flood at ~14 ka, moisture delivery to central Vietnam increases, causing an abrupt shift from dry to wet conditions. On millennial timescales, we find signatures of well-known Heinrich Stadials (HS) (dry conditions) and Dansgaard-Oeschger Events (wet conditions). Model simulations show that during the dry HS, changes in sea surface temperature related to meltwater forcing cause the formation of an anomalous anticyclone in the Western Pacific, which advects dry air across central Vietnam, decreasing autumn rainfall. Notably, sea level modulates the magnitude of millennial-scale dry and wet phases by muting dry events and enhancing wet events during periods of low sea level, highlighting the importance of this mechanism to autumn monsoon variability.

Variability and predictability of the Northeast India summer monsoon rainfall

AbstractThe mesoscale orography over one of the wettest regions of the world makes the Northeast India (NEI) vulnerable to hydrological disasters while sustaining a biodiversity “hotspot.” The monsoon rainy season over the NEI is known to be longer than June–September (JJAS), but an objective definition has been lacking. Understanding the drivers and predictability of rainfall variability over the region is key for sustainable development planning and adaptation to increasing disasters in the backdrop of a warming climate but remained poor due to lack of a working definition of “summer monsoon season” over NEI. Here, using the relationship between rainfall over the region and winds at 850 hPa over North Bay of Bengal (BoB), we provide an objective definition of the monsoon season over NEI and argue that the “summer monsoon rainy season” over the NEI (NEIR) is from May to September (MJJAS). In contrast to a significant negative relationship between JJAS Central India (CI) rainfall and a JJAS El Niño–Southern Oscillation (ENSO) index, the MJJAS rainfall over the NEI has no relationship with MJJAS or JJAS ENSO. Instead, we unravel that (a) the tropical Northwest‐Pacific (TNWP) sea surface temperature (SST), (b) the South Equatorial Indian Ocean Dipole (SEIOD) and (c) the Atlantic Zonal mode (AZM) are potential drivers of the NEIR variability. Using a causal inference algorithm, namely the Peter and Clark Momentary Conditional Independence (PCMCI) method, we show that SEIOD directly influences NEIR while TNWP SST has a two‐way connection with the NEIR. While “internal variability” may be higher over the NEI, significant modulation of the variances of the subseasonal fluctuations by predictable drivers like the Atlantic Niño and North Atlantic water temperature provides optimism for seasonal prediction of the NEIR.

Latitudinal variations of summer monsoon rainfall in different intensity classes over the Western Ghats

Latitudinal variations of summer monsoon rainfall in different intensity classes over the Western Ghats

Assessment of intraseasonal variability indices on identifying Indian summer monsoon rainfall variability

Assessment of intraseasonal variability indices on identifying Indian summer monsoon rainfall variability

Statistical Analysis of Rainfall Pattern and Trend of Chhattisgarh State, India

To analyze, the present rainfall status and trend, the long term weather data (1980-2020) viz., gridded annual rainfall data was analysed which was obtained from the department of Agrometeorology, Indira Gandhi Krishi Vishwavidyalaya Raipur, Using linear trend, the long-term change in rainfall has been evaluated. It is obsered that the state receives the maximum amount of rainfall from the southwest monsoon, around 87 percent from June to September, the state receives 15 percent in June and the state receives 29,26 and 16 percent rainfall in the Month of July, August and September, respectively. Long term weather data of state rainfall, it is seen that rainfall in June and September is less consistent since the coefficient of variation is around 33 and 30 percent, respectively; we would conclude that rainfall in June has more variability than in monsoon months, SW monsoon and annual rainfall. Average Monsoon and Annual rainfall variability are less than monsoon months. District-wise minimum rainfall variability of June, July, August, and September is around 37 percent (Kanker) and 22 percent (Jashpur). Kabirdham district has a 25 percent variability in August and September. District Kanker and Raigarh varied around 14 percent for monsoon and annual rainfall. As the linear regression in southwest monsoon and annual rainfall in the state of Chhattisgarh is increasing in order, but from 1980 to 2020 it shows more fluctuation in trend line, then if a system is developed for agrometeorology station at cluster level or block level and for forecasting, it will be able to account for these changes.From this, farmers will receive timely information about the monsoon and rainfall, allowing them to conduct agricultural activities at the appropriate time.

Eccentricity-paced geomagnetic field and monsoon rainfall variations over the last 870 kyr

Whether there are links between geomagnetic field and Earth's orbital parameters remains unclear. Synchronous reconstructions of parallel long-term quantitative geomagnetic field and climate change records are rare. Here, we present 10Be-derived changes of both geomagnetic field and Asian monsoon (AM) rainfall over the last 870kyr from the Xifeng loess-paleosol sequence on the central Chinese Loess Plateau. The10BeGM flux (a proxy for geomagnetic field-induced 10Be production rate) reveals 13consecutive geomagnetic excursions in the Brunhes chron, which are synchronized with the global records, providing key time markers for Chinese loess-paleosol sequences. The10Be-derived rainfall exhibits distinct ~100 kyr glacial-interglacial cycles, and superimposed precessional (~23 kyr) cycles that match with those in Chinese speleothem δ18O record. We find that changes in the geomagnetic field and AM rainfall share a common ~100 kyr cyclicity, implying a likely eccentricity modulation of both the geomagnetic field and climate.

Quantifying the role of antecedent Southwestern Indian Ocean capacitance on the summer monsoon rainfall variability over homogeneous regions of India

The role of ocean variability is at a focal point in improving the weather and climate forecasts at different spatial and temporal scales. We study the effect of antecedent southwestern Indian Ocean mean sea level anomaly (MSLA) and sea surface temperature anomalies (SSTA) as a proxy to upper ocean heat capacitance on all India summer monsoon rainfall (AISMR) during 1993–2019. SSTA and MSLA over the southwestern Indian Ocean (SWIO) have been influenced by El Niño-Southern Oscillation (ENSO), the impact of ENSO-induced SWIO variability was low on rainfall variability over several homogeneous regions. Rainfall over northeast (NE) and North India (EI) has been modulated by ENSO-induced SSTA and MSLA over SWIO, thus effecting the total AISMR magnitude. The ENSO-induced changes in heat capacitance (SSTA and MSLA) over SWIO during antecedent months has less impact on west coast of India, central India and North India (NI) rainfall variability. The long-term trend in pre-monsoonal SSTA and MSLA over SWIO shows decreasing rainfall trend over NI, NE, and EI in the recent time. Furthermore, the cooler (warmer) anomaly over the western Indian Ocean affects rainfall variability adversely (favourably) due to the reversal of the wind pattern during the pre-monsoon period. While SSTA and MSLA are increasing in the SWIO, large-scale variability of these parameters during preceding winter and pre-monsoon months combined with surface winds could impact the inter-annual AISMR variability over homogeneous regions of India. Similarly, from an oceanic perspective, the antecedent heat capacitance over SWIO on an inter-annual time scale has been the key to the extreme monsoon rainfall variability.

Chemical weathering evidence for East Asian Summer Monsoon rainfall variability in the upper reaches of the Yellow River since the Early Pleistocene

The East Asian Summer Monsoon (EASM) is critically important for determining the spatial variability of precipitation in the continental interior of East Asia. Hence, knowledge of past EASM variability may help predict the response of monsoon rainfall to ongoing global climate change, with important implications for the living environment of the large human population of East Asia. In this study, we obtained several geochemical records from the Hetao Basin in the upper reaches of the Yellow River (UYR), which we use to reconstruct variations in chemical weathering intensity since 1.68 Ma. Our results suggest that chemical weathering was significantly intensified during the interval of ∼0.47–0.18 Ma, evidenced by lower Rb/Sr and αAlSr values, and higher LEF Mg/Al values, within the lacustrine sediments during this period. This enhanced chemical weathering was closely linked to increased monsoon rainfall associated with a strong EASM. The long-term trends of EASM rainfall in the UYR were caused by variations in the atmospheric circulation over the Pacific Ocean, such as the ENSO cycle and the PDO phase transition, which may act as testable factors in the prediction of future EASM rainfall.

Different role of spring season Atlantic SST anomalies in indian summer monsoon rainfall (ISMR) variability before and after early 2000

The present study shows that the weak (out-of-phase) correlation between the boreal spring Atlantic Meridional Mode (AMM) index and Indian summer monsoon rainfall (ISMR) during the 1990–2001 periods turned into a significant positive relationship after that. During the first period, boreal spring (MAM) season Atlantic SST variability is dominated by stronger cooling in the southeastern region. After 2002, the spring season SST pattern has north Atlantic warming extending to the equatorial region and continuing to summer (JJAS). The primary mode of the Atlantic SST co-occurred with a pre-existing El Nino during period 1 and the formation of La Nina by summer during period 2. During period 1, ENSO-induced anomalies dominated with weak divergence over India and the Atlantic region, while during period 2, the warm SST anomalies of north Atlantic-induced off-equatorial convection and associated circulation extended to the Indian Ocean and Indian land region resulting in increased monsoon rainfall during JJAS. The study further showed that during period 2, the increased correlation of ENSO and ISMR is also contributed by the Atlantic SST anomalies with additional off-equatorial wind anomalies and circulation from the north Atlantic extending to the Indian Ocean and monsoon region. Thus, MAM season Atlantic SST anomalies play a significant role in ENSO phase reversal and ISMR during the recent period. Many of the seasonal prediction models that participated in the NMME project capture the phase reversal of AMM-ISMR correlation when initialized during February. But models have more robust equatorial SST patterns during the summer season, and the north Atlantic SST anomalies are vital in the absence of ENSO. The study indicates that the spring season AMM index can provide a predictive signal for ISMR in seasonal prediction models. Still, they need to improve the simulation of the Atlantic basic state and its teleconnection with the tropical east Pacific.

The Influences of Atlantic Sea Surface Temperature Anomalies on the ENSO-Independent Interannual Variability of East Asian Summer Monsoon Rainfall

Abstract As the most dominant tropical climate mode on the interannual time scale, El Niño–Southern Oscillation (ENSO) is suggested to significantly influence the interannual variation of East Asian summer monsoon rainfall (IEASMR). However, the leading mode of IEASMR remains almost untouched when the impacts of preceding ENSO events are linearly removed, suggesting the existence of alternative impact factors and predictability sources of IEASMR. After removing the impact of ENSO, the sea surface temperature anomalies (SSTAs) over both the tropical Atlantic and extratropical North Atlantic are found to be related to IEASMR through atmospheric teleconnections. Positive SSTA over the tropical Atlantic could induce tropical diabatic heating, which triggers an equivalent barotropic Rossby wave train emanating from the Atlantic, going across the Eurasian continent, and ending with a cyclonic anomaly over northeast Asia. The tropical diabatic heating could also induce western North Pacific anomalous anticyclone via tropical routes. The dipole SSTA pattern with cooling in the west and warming in the east over the extratropical North Atlantic induces local circulation anomalies through heat flux exchange, which could further perturb a Rossby wave train with a cyclonic anomaly over northeast Asia, thus modulating IEASMR. Numerical experiments with prescribed atmospheric heating associated with Atlantic SSTAs could realistically reproduce these teleconnections toward IEASMR. By adding the predictability sources of Atlantic SSTAs, the seasonal hindcast skills of IEASMR could be significantly improved over both the tropical western North Pacific and subtropical land regions such as central China and Japan. Significance Statement The purpose of this article is to identify the alternative impact factors of the interannual variation of East Asian summer monsoon rainfall (IEASMR), after removing the impact of ENSO, considering the limited contribution of ENSO to the variances of IEASMR. Here, we find that the Atlantic sea surface temperature anomalies (SSTAs) play a considerable role in driving IEASMR. The impact of ENSO on IEASMR is mainly confined to the tropical western North Pacific, while the Atlantic SSTAs influence rainfall over subtropical East Asia and the tropical western North Pacific through both tropical and extratropical routes. The results unravel the important roles of Atlantic SSTAs in driving ENSO-independent IEASMR, which will have a large implication for the seasonal prediction of East Asian summer climate.

Symmetric and asymmetric response of Indian Summer Monsoon rainfall to different ENSO decay phases in observations and CMIP6 models

The present study assesses the ability of the World Climate Research Programme's Coupled Model Intercomparison Project-6 (CMIP6) models in simulating the Indian Summer Monsoon (ISM) rainfall variability and its symmetric or asymmetric relationship with the El Niño–Southern Oscillation (ENSO) decay phase. The El Niño decays are classified into three categories based on their transition characteristics (rapid/slow) with respect to the subsequent boreal summer season, namely El Niño early-decay, El Niño mid-decay, and El Niño no-decay. Similarly, La Niña decays are also classified into the La Niña early-decay, La Niña mid-decay, and La Niña no-decay. In the case of El Niño and La Niña early-decay events, the observed summer rainfall anomalies over India are similar in spatial distribution and amplitude but opposite in sign, suggesting the symmetric rainfall response. This symmetric response is mainly due to the influence of the westward extension of western north Pacific (WNP) anomalous anticyclone/cyclone accompanied by tropical Indian Ocean (TIO) warming/cooling. In contrast to this, summers of El Niño and La Niña mid-decay events exhibited asymmetric rainfall anomaly pattern over India. This asymmetry in rainfall pattern between these two summers is attributed to differences mainly in the moisture divergence and low-level circulation over the Indo-Western Pacific region. Similar to El Niño and La Niña mid-decay cases, the summers of observed El Niño and La Niña no-decay events displayed ISM rainfall asymmetry. Differences in spatial distribution and magnitude of Sea surface temperature anomalies and related atmospheric circulation between these events mainly responsible for ISM rainfall asymmetry. Analysis of CMIP6 revealed that only ∼ 14% of selected CMIP6 models have simulated the rainfall anomalies somewhat correctly compared to observations during summers of different decay phases of ENSO. Further, symmetric/asymmetric response of summer rainfall anomalies over India between decay phases of El Niño and La Niña are not well captured by CMIP6 models. It is also noted that the CMIP6 models have displayed a tendency to simulate positive (negative) Indian Ocean Dipole conditions during the summers of El Niño no-decay (La Niña no-decay) events unlike in the observations.

Secular Changes of the Decadal Relationship Between the Northern Hemisphere Land Monsoon Rainfall and Sea Surface Temperature Over the Past Millennium in Climate Model Simulations

AbstractUnderstanding the decadal variability of Northern Hemisphere land monsoon rainfall (NHLMR) is crucial to social‐economic development. However, due to the temporal limitation of instrumental data, the decadal relationship between NHLMR and sea surface temperature (SST) remains uncertain. The extended El Niño–Southern Oscillation (XEN) SST index and the North Atlantic–south Indian Ocean dipole (NAID) SST index can be the predictors to help us understand the decadal relationship between NHLMR and SST. In this study, using the Community Earth System Model‐Last Millennium Ensemble (CESM‐LME) simulations, we find a significant and stable decadal correlation between the NHLMR and XEN in the all‐forcing (AF) (with natural and anthropogenic forcings, AF), control (internal variability only), and other external forcings run over the past millennium, which means that this simulated NHLMR‐XEN relationship is caused by internal variability. The AF experiments show that the decadal relationship between NHLMR and NAID is practically non‐existent until an abrupt and significant increase in volcanic eruptions at about 1700, which is also indicated by the Paleoclimate Modeling Intercomparison Project Phase 3 (Paleoclimate Modeling Intercomparison Project Phase 3) simulations. Using the volcanic forcing sensitivity experiments, we find that the successive strong volcanic eruptions in the Northern Hemisphere (NH) significantly strengthen the synchronous changes of NHLMR and NAID after 1700, with a periodicity of 20–40‐year for NHLMR and NAID. Specifically, successive NH eruptions weaken the north‐south hemispheric thermal contrast, contributing to the weakened NAID index. The cross‐equator flow is thus weakened, decreasing the NHLMR, which cause a resonant behavior of NHLMR and NAID.

Spatio-temporal analysis of rainfall in relation to monsoon teleconnections and agriculture at Regional Scale in Haryana, India.

This study examined the long-term (1980-2019) spatio-temporal trends, variability and teleconnections of Indian summer monsoon rainfall (ISMR) of all districts of Haryana, India and their impact on agricultural productivity. The gridded datasets of India Meteorological Department (IMD) were used to statistically analyse the rainfall distribution, trend, coefficient of variation and intensity of rainfall. The gridded datasets of European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis V5 (ERA5) were examined for lower and upper tropospheric wind circulation (850hPa and 200hpa), vertically integrated moisture transport (VIMT) and surface moisture flux (SMF). The datasets of National Oceanic and Atmospheric Administration (NOAA) were correlated with ISMR and composite deviation of rainfall and rainfall intensity during El Niño and La Niña from neutral years was examined at district level. Our analysis revealed that districts lying in eastern agroclimatic zone (EAZ) of Haryana received more ISMR during each month of monsoon season as compared to the ones situated in western agroclimatic zone (WAZ). Trend-free pre-whitening Mann-Kendall (TFPW-MK) test revealed that Kurukshetra, Panipat, Ambala, Rohtak, Faridabad, Jhajjar, Sonipat, Fatehabad and Palwal have shown a decreasing trend while Mahendragarh and Panchkula have shown an increasing trend of rainfall. During the El Niño years, most of the locations in the state received deficient to large deficient category, whereas during the La Niña episodes, most of the locations received excess to large excess category of ISMR, which is indicative of the influence of El Niño-Southern Oscillation (ENSO) on the regional scale. The influence of ISMR on bajra productivity for the districts lying in WAZ and rice productivity for the districts lying in EAZ was undertaken. This study is beneficial for understanding the impacts of climate change and climate variability on ISMR dynamics in Haryana which may further guide the policy-makers and beneficiaries for optimising the use of hydrological resources.

Coherent Indian Summer Monsoon and Sahel Rainfall Variability Revealed by Ethiopian Rainfall δ18O

AbstractCoherent fluctuations in Sahel and Indian summer monsoon (ISM) rainfall influence the socio‐economic welfare of several densely populated regions. Here we identify a common mode of interannual rainfall variability over the Sahel and Indian regions and demonstrate the influence of both Pacific and Atlantic sea surface temperatures (SST) in inducing such a large‐scale response. The principal component of the leading mode of precipitation variability (PC1) over these regions correlates independently well with both ISM and Sahel rainfall indices. Here we show that this global SST‐driven dominant mode of Indo‐Sahel rainfall variability is well captured in present‐day rainfall δ18O and speleothem δ18O of the Ethiopian region. We use a ∼40‐year‐long monthly observational record of precipitation stable isotopes at Addis Ababa, Ethiopia to show that episodic isotopic depletions in rainfall at this site occur during the wet phases of PC1. These isotopic anomalies are associated with eastward intrusions of moisture initiating from the tropical Atlantic Ocean. Finally, we demonstrate decadal‐scale co‐variability between PC‐1 and a century‐long δ18O record from an actively growing Ethiopian speleothem to highlight the potential of rainfall isotopic records from this region to capture fluctuations in the coupled variability of the Indo‐African boreal monsoons.