Possible shift in the ENSO-Indian monsoon rainfall relationship under future global warming

Heat waves characteristics intensification across Indian smart cities

Indian cities have frequently observed intense and severe heat waves for the last few years. It will be primarily due to a significant increase in the variation in heat wave characteristics like duration, frequency, and intensity across the urban regions of India. This study will determine the impact of future climate scenarios like SSP 245 and 585 over the heat wave characteristics. It will present the comparison between heat waves characteristics in the historical time (1981 to 2020) with future projections, i.e., D1 (2021-2046), D2 (2047-2072), and D3 (2073-2098) for different climate scenarios across Indian smart cities. It is observed that the Coastal, Interior Peninsular, and North-Central regions will observe intense and frequent heat waves in the future under SSP 245 and 585 scenarios. A nearly two-fold increase in heat wave' mean duration will be observed in the smart cities of the Interior Peninsular, Coastal, and North Central zones. Thiruvananthapuram city on the west coast has the maximum hazard associated with heat waves among all the smart cities of India under both SSPs. This study assists smart city policymakers in improving the planning and implementation of heat wave adaptation and mitigation plans based on the proposed framework for heat action plans and heat wave characteristics for improving urban health well-being under hot weather extremes in different homogeneous temperature zones.

Improved drought monitoring in teleconnection to the climatic escalations: A hydrological modeling based approach

Catchment-scale efficient agricultural drought monitoring and irrigation planning mostly depend on the accuracy of evapotranspiration (ET) estimates under different crop-growth phases. As indirect ET estimation under limited data availability scenario and complex paddy-field dynamics could not be sufficiently addressed by the conventional curve number (CN) based SWAT model, SWAT incorporates an add-in pothole module (SWAT-P) that conceptualizes the paddy-field hydrology with the empirical coefficient or equations resulting in poor ET estimates. To address these limitations, this study integrates an improved pothole methodology in SWAT (SWAT-EP) accounting the vadose-zone soil water dynamics under alternate ponding and drying conditions, ET variation under moisture abundant and stress conditions, and role of irrigation return flow generated in the paddy fields. The proposed approach was validated in the Kangsabati River integrated reservoir-catchment-command (12,014.70 km²) of the eastern India, and the results reveal that SWAT-EP outperformed the existing SWAT-P in reproducing the catchment-scale streamflow and ET flux with respect to the FAO-56 Penman-Monteith (PM) based ET estimates in all the four cropping seasons. The SWAT-EP derived Standardized Evapotranspiration Drought Index (SEDI) based drought severity and duration well-corroborate with the benchmark MOD16A2 derived drought estimates; whereas, the SWAT-P tends to overestimate the drought severity in the command area. The predictive uncertainty in drought monitoring was the lowest by SWAT-EP with relatively lower uncertainty was observed in the crop-growing locations of Kharagpur and Mohanpur. Moreover, the teleconnection between drought and climatic escalations corresponds to a better reproducibility of El Niño and La Niña phases by the SWAT-EP, while the SWAT-P performed un-satisfactorily across different spatiotemporal domains. This study endorses to adopt the proposed SWAT-EP model for river basin-scale drought monitoring and irrigation planning with prior validation in the diversified climatic and topographic conditions.

Tracing impact of El Niño Southern Oscillation on coastal hydrology using coral 87Sr/86Sr record from Lakshadweep, South-Eastern Arabian Sea

El Niño Southern Oscillation (ENSO) is one of the dominant climate modes influencing global precipitation and temperature. ENSO has a large impact on the monsoonal precipitations over the Indian subcontinent and thereby influences hydrological conditions. Due to dearth of long-term instrumental records of the hydrological parameters on sufficient spatial resolution, it is difficult to assess the impact of ENSO on regional hydrology. Though several geochemical proxies have been used to reconstruct past ENSO events through tracing the changes in past hydrological and climatic parameters, however, such reconstructions are often complicated by the influence of multiple processes and/or factors and their nonlinear relation with the proxy records. In this study, Sr isotope composition (⁸⁷Sr/⁸⁶Sr) was measured in Porites coral from the Lakshadweep, south-eastern Arabian Sea to reconstruct past ENSO events and to trace its regional hydrological impacts. The high precision measurements of ⁸⁷Sr/⁸⁶Sr in Lakshadweep coral show resolvable variations ranging from 0.709080 to 0.709210. The ⁸⁷Sr/⁸⁶Sr record shows an inverse relation with Niño 3.4 record; lower values matched with El Niño years and higher values with La Niña years. Our investigation reveals that ENSO driven precipitation changes impacted submarine groundwater discharge (SGD) to the Minicoy Atoll and resulted in ⁸⁷Sr/⁸⁶Sr variations of the Minicoy Atoll water. Therefore, deviation from the average seawater ⁸⁷Sr/⁸⁶Sr value can be quantified in terms of SGD contribution to the Minicoy Atoll. Our estimates based on binary mixing between seawater and SGD ⁸⁷Sr/⁸⁶Sr suggest a significant supply of SGD, maximum up to ~20 % of the total volume of the Minicoy Atoll during La Niña years due to higher rainfall compared to El Niño years. This finding highlights potential application of coral ⁸⁷Sr/⁸⁶Sr record as an alternate proxy to reconstruct past ENSO events and to trace its quantitative impact on regional hydrology, chemical and nutrient fluxes to coastal oceans via SGD.

MicroRNA-mediated bioengineering for climate-resilience in crops

Global projections on the climate change and the dynamic environmental perturbations indicate severe impacts on food security in general, and crop yield, vigor and the quality of produce in particular. Sessile plants respond to environmental challenges such as salt, drought, temperature, heavy metals at transcriptional and/or post-transcriptional levels through the stress-regulated network of pathways including transcription factors, proteins and the small non-coding endogenous RNAs. Amongs these, the miRNAs have gained unprecedented attention in recent years as key regulators for modulating gene expression in plants under stress. Hence, tailoring of miRNAs and their target pathways presents a promising strategy for developing multiple stress-tolerant crops. Plant stress tolerance has been successfully achieved through the over expression of microRNAs such as Os-miR408, Hv-miR82 for drought tolerance; OsmiR535A and artificial DST miRNA for salinity tolerance; and OsmiR535 and miR156 for combined drought and salt stress. Examples of miR408 overexpression also showed improved efficiency of irradiation utilization and carbon dioxide fixation in crop plants. Through this review, we present the current understanding about plant miRNAs, their roles in plant growth and stress-responses, the modern toolbox for identification, characterization and validation of miRNAs and their target genes including in silico tools, machine learning and artificial intelligence. Various approaches for up-regulation or knock-out of miRNAs have been discussed. The main emphasis has been given to the exploration of miRNAs for development of bioengineered climate-smart crops that can withstand changing climates and stressful environments, including combination of stresses, with very less or no yield penalties.

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.

La Niña weather impacts dietary patterns and dietary diversity among children in the Peruvian Amazon

Objective:

In 2011–2012, severe El Niño Southern Oscillation (ENSO) conditions (La Niña) led to massive flooding and temporarily displacement in the Peruvian Amazon. Our aims were to examine the impact of this ENSO exposure on child diets, in particular: (1) frequency of food consumption patterns, (2) the amount of food consumed (g/d), (3) dietary diversity (DD), (4) consumption of donated foods, among children aged 9–36 months living in the outskirts of City of Iquitos in the Amazonian Peru.

Design:

This was a longitudinal study that used quantitative 24-h recall dietary data collection from children aged 9–36 months from 2010 to 2014 as part of the MAL-ED birth cohort study.

Setting:

Iquitos, Loreto, Peru.

Participants:

Two hundred and fifty-two mother–child dyads.

Results:

The frequency of grains, rice, dairy and sugar in meals reduced by 5–7 %, while the frequency of plantain in meals increased by 24 % after adjusting for covariates. ENSO exposure reduced girl’s intake of plantains and sugar. Despite seasonal fluctuations in the availability of fruits, vegetables and fish, DD remained constant across seasons and as children aged. However, DD was significantly reduced under moderate La Niña conditions by 0·32 (P < 0·05) food groups. Adaptive social strategies such as consumption of donated foods were significantly higher among households with girls.

Conclusions:

This is the first empirical study to show differential effect of the ENSO on the dietary patterns of children, highlighting differences by gender. Public health nutrition programmes should be climate- and gender-sensitive in their efforts to safeguard the diets of vulnerable populations.

Impact of Climate Variability on Crop Yield in Kalahandi, Bolangir, and Koraput Districts of Odisha, India

Most tropical regions in the world are vulnerable to climate variability, given their dependence on rain-fed agricultural production and limited adaptive capacity owing to socio-economic conditions. The Kalahandi, Bolangir, and Koraput districts of the south-western part of Odisha province of India experience an extreme sub-humid tropical climate. Based on the observed changes in the magnitude and distribution of rainfall and temperature, this study evaluates the potential impact of climate variation on agricultural yield and production in these districts. The study is conducted by taking into account meteorological data like rainfall and temperature from 1980 to 2017 and crop productivity data from 1980–81 to 2016–17. Additionally, climate variability indices like Monsoon Index, Oceanic Nino Index, and NINO-3 and NINO 3.4 are used. To analyse the data, various statistical techniques like correlation and multiple linear regression are used. The amount of monsoon rainfall is found to have a significant impact on crop productivity, compared to temperature, in the study area, and as a result the Monsoon Index has a determining impact on crop yield among various indices.

Network-based identification and characterization of teleconnections on different scales

Sea surface temperature (SST) patterns can - as surface climate forcing - affect weather and climate at large distances. One example is El Niño-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of - at a certain timescale - similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole.

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.

Quasi-asymmetric response of the Indian summer monsoon rainfall to opposite phases of the IOD

The El Niño/Southern Oscillation has been traditionally linked to the extremes in the Indian summer monsoon rainfall (ISMR) affecting more than a billion people in the region. This trans-oceanic influence is seen to be moderated by the Indian Ocean Dipole (IOD) phenomenon in recent decades. In the presence of a positive IOD (pIOD), the otherwise subdued ISMR in an El Niño year remains close to normal even in the face of record breaking El Niños. While this general influence of pIOD on ISMR is understood, the influence of negative IOD (nIOD) on ISMR is not yet recognized. In this study, it is revealed that those opposite phases of IOD are associated with distinct regional asymmetries in rainfall anomalies. The pIOD is associated with a tripolar pattern in rainfall anomalies with above normal rainfall in central parts of India and below normal rainfall to north and south of it. Conversely, the nIOD is associated with a zonal dipole having above (below) normal rainfall on the western (eastern) half of the country. This spatial quasi-asymmetry arises from the differences in the atmospheric responses and the associated differences in moisture transports to the region during contrasting phases of the IOD.