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Under global warming and climate change (CC), the vulnerable piece of land is India's Eastern-Himalayan-Region (EHR), where millions' livelihood activities are at risk. Quantifying the degree of CC-induced vulnerability over the highly climate-sensitive mountain zone is challenging due to data inadequacy. This paper attempted to assess the CC perception of kiwifruit growers under EHR and the impact of CC on its cultivation. Perceived and scientific data were used for accurate decision-support information. The climatic variables of two locations were analyzed for trend using Mann–Kendall's test. Results suggested that the rainfall trend was found non-significant for both locations, but there was a negative trend during winter for Pasighat and during all seasons for Itanagar. Maximum temperature exhibited an increasing trend for annual, and minimum temperature showed an increasing trend across seasons for the Pasighat region. For the Itanagar region, the maximum temperature was found to have a significantly increasing trend in all seasons, while the minimum temperature showed an increasing trend during winter and annual seasons. Morning relative humidity showed an increasing trend for annual data for Pasighat, while annual evening relative humidity was significantly increased for Itanagar. The study shows that the indigenous farming communities were following shifting cultivation and diversifying their traditional agriculture to kiwifruit cultivation as an adaptation strategy. The community had a clear perception of CC trends and an inadequate perception of the impact on agriculture, therefore, engaging indigenous communities and other stakeholders to postulate a comprehensive adaptation and mitigation strategy for CC. [ABSTRACT FROM AUTHOR]

The present research study aims to analyze flood frequency to relate flood magnitudes with corresponding return periods. These estimates are crucial for the development of flood-preventive hydrological infrastructures and flood plain zoning, etc. Basin-wide high intensity of rainfall and high discharge from the upper riparian region during monsoon months creates flooding in the middle and lower reaches of the Ghagra River basin. Therefore, the flood estimates for three gauging sites situated on the mainstream of the Ghagra River viz., Elginbridge, Ayodhya, and Turtipar, have been comprehended using the Gumbel distribution (Extreme Value Type I) method and the Log-Pearson Type III distribution method. Flood estimates are calculated for 1.01, 1.05, 1.11, 1.25, 2, 5, 10, 20, 50, 100, 200, and 500 years return periods considering flood time series of 50 years to reduce estimation uncertainty. The findings of flood frequency analysis (FFA) revealed that the probability of occurrence of the flood is more than 80% at all three sites because Ghagra River can carry around 7800 to 9000 m3/s of water discharge without posing a high risk of levee break. The upper and lower limits of discharge carrying capacity depend on the river's desiltation process. Hence, the flood occurs almost every year in the basin; its only variation is its severity. The rainfall-runoff relationship is estimated by integrating a simple linear model and for rainfall trend analysis Mann-Kendall is applied. Linear regression analysis-based rainfall-runoff relationship outcomes revealed a significant relationship with a positive correlation coefficient i.e., 0.2722 for Elginbridge, 0.39624 for Ayodhya, and 0.4844 for Turtipar gauging site in the monsoon season but other factors like a high amount of water discharge from dams in upper riparian regions, etc. are also responsible for flooding in the middle and lower reaches. The Mann-Kendall trend analysis shows a decrease in annual average rainfall and rainfall in the monsoon season. Discharge variability indicates the direct relationship between flood fury and changes in climatic patterns in recent decades. This paper identifies that future research is needed to better inform the policy planners who strive to design sustainable infrastructure. [ABSTRACT FROM AUTHOR]

Climate model, a complex numerical representation of the global climate system, has been developed to simulate current climate and used to project future climatic conditions. Simulated climatic variables from climate models often exhibit significant deviations from observations. In climate projections, different approaches were introduced to deal with systematic deviations and random model errors. This paper demonstrates the intercomparison of four bias correction approaches (linear scaling, delta change correction, distribution mapping, and variance scaling) underlying the assumptions of stationary output from climate models. Mean monthly temperatures derived from five global climate models were corrected by four bias correction approaches for five states of southern India. The suitability of correction approaches depends upon the climate models and regional framework. The applied approaches improve the mean values and other statistical properties. The results show that all four bias techniques significantly improved the simulated data, but distribution mapping and variance scaling were more effective in removing systematic model biases. [ABSTRACT FROM AUTHOR]

Tropical inland capture fisheries are susceptible to a series of vulnerabilities such as habitat destruction, biodiversity loss, pollution, overfishing, invasive species and anthropogenic climate change. A comprehensive review of the impact of climatic uncertainties on Indian inland fisheries has not been adequately attempted yet. Recent approaches emphasizing ecosystem-based management in a regional context, specific to inland fisheries for combating climatic changes, have not been reported to date. The paper presents a critical bibliometric review of the climatic vulnerabilities faced by Indian inland fishery resources and various adaptive and mitigation strategies put forward by the country for the sustainability of the resources. In this communication, a systematic review of the impact of climate change and other stressors on various inland ecosystems of the subcontinent and the ecosystem-based management strategies adopted in India is presented and discussed. [ABSTRACT FROM AUTHOR]

Climate change is a major concern the world over more so for a predominantly agrarian country like India. In this paper we analyze the time horizon dynamics of crop and climate variables at the regional level in India. We also analyze the co-movements of crop yields with temperature and rainfall to observe the coherence across heterogenous time horizons. We employ Bai-Perron structural break and Continuous wavelet transform methods on yearly data of seven crop yields and climate variables. Observed variables are analyzed from 1956 to 2010 for the un-divided state of Andhra Pradesh, India. Breakpoint analysis shows an increase of around 1.0° temperature with two observed break points. Rainfall depicts no systematic change with fluctuations being largely random. The framework of wavelets-based time–frequency analysis employed in this study captures climate and crop dynamics at heterogeneous time horizons, allowing one to study the impact of climate and crop yields at both short and longer time-horizons. Wavelet based coherence analysis exhibited significant co-movement between climatic and crop variables. Given shifts in climate patterns and subsequent shifts in co-movements across time horizons at the regional level, policy makers and crop scientists should design time specific and locally viable adaption and mitigation policies to tackle the impact of climate change on crops and livelihoods. [ABSTRACT FROM AUTHOR]

Global warming is the average temperature of the earth's surface which has increased over the past century by about 0.6 °C. This rising temperature may vary precipitation patterns, more frequent droughts, rise in sea level and intense storms and can be termed as climate change. To understand uneven precipitation pattern for monsoon dominated region like India, there is a need to study cloud processes at high resolution with the help of cloud microphysical properties. Ocean is the major and primary source of cloud whereas local water bodies and re-evaporated water over land could be secondary source. Paper focuses over ocean (Arabian Sea) as well as over land (central India) to know the effect of global warming on cloud microphysical properties such as cloud effective radius and cloud liquid water content. Warming signal in terms of rise in sea surface temperature (0.1 °C/decade) as well as rise in surface air temperature (0.05 °C/decade) are observed over Arabian Sea and central India respectively. Satellite data show an increasing (0.5 µm/decade) trend in cloud effective radius over Arabian Sea, whereas it decreases (− 0.1 µm/decade) over central India. Increasing trend in temperature and cloud properties is may be due to warming signal. Aerosol concentration over ocean and land further helped to understand cloud processes with cloud microphysical properties. Paper will focus on the effect of warming signal in cloud properties over Arabian Sea and central India. This type of high resolution study may help to understand cloud processes which in turn may help to understand precipitation patterns. [ABSTRACT FROM AUTHOR]

Global warming is a biggest issue around the world. In this research paper, the temporal and spatial trend analysis of seasonal and annual rainfall on Bhogavo River watersheds in Sabarmati lower basin of Gujarat state of India has been analysed using the data of 11 rain gauge stations installed in Bhogavo watershed. Linear regression, Mann–Kendall Test, Sen's slope test and innovative trend analysis methods are used to carry out monthly and annual rainfall trend analysis. In addition to the rainfall analysis, a number of rainy days change in magnitude as a percentage of mean rainfall have also been analysed using linear regression and Sen's slope method, respectively. The IDW method is used to develop a spatial distribution of annual and seasonal rainfall trend over the study area. From the results, it is concluded that annual rainfall shown increasing (positive) trend at nine stations out of 11 stations. The highest value of change in magnitude of trend as a percentage of mean monthly rainfall has been obtained in the month of July, attributing increasing trend at Sayla station and lowest value magnitude of trend as a percentage of mean rainfall in the monthly rainfall has been obtained in the month of August, attributing decreasing trend at Bavla station. [ABSTRACT FROM AUTHOR]

Globally, agriculture is recognized as a highly vulnerable sector to climate change and risks from climatic aberrations pose an imminent danger to the food security and sustainability of livelihoods. To bring robustness in climate adaptation planning, evaluation of resilience across homogenous regions is essential for developing and scaling suitable location-need-context specific interventions and policies that build the resilience of the agricultural system. In this paper, we present an analysis and discussion of multi-scalar and multi-indicator assessment, by profiling resilience across agro-climatic zones of India, based on the development of a Climate-Resilient Agriculture Index embracing environmental, technological, socio-economic, and institutional and infrastructural dimension. A total of 26 indicators, spread across these four dimensions, were employed to purport inter- and intra-agro-climatic zone differentials in the level of resilience. Among the zones, it was found that West Coast Plains & Ghats and Tans-Gangetic Plains had the highest degree of resilience to manage climate risks. Most of the districts lying within Eastern Himalayan Region, Middle Gangetic Plains, Eastern Plateau & Hills, and Western Dry Region had a lower degree of resilience. The study places greater emphasis on deciphering region-specific drivers and barriers to resilience at a further disaggregated scale for improving rural well-beings. It is construed that devising action plans emphasizing awareness, preservation of natural resources, diversification, building physical infrastructure, strengthening of grass-root institutions, and mainstreaming climate adaptation in the developmental policy is crucial for climate-resilient pathways. [ABSTRACT FROM AUTHOR]

The current nationally determined contributions, pledged by the countries under the Paris Agreement, are far from limiting climate change to below 2 ∘C temperature increase by the end of the century. The necessary ratcheting up of climate policy is projected to come with a wide array of additional benefits, in particular a reduction of today's 4.5 million annual premature deaths due to poor air quality. This paper therefore addresses the question how climate policy and air pollution–related health impacts interplay until 2050 by developing a comprehensive global modeling framework along the cause and effect chain of air pollution–induced social costs. We find that ratcheting up climate policy to a 2 ∘ compliant pathway results in welfare benefits through reduced air pollution that are larger than mitigation costs, even with avoided climate change damages neglected. The regional analysis demonstrates that the 2 ∘C pathway is therefore, from a social cost perspective, a "no-regret option" in the global aggregate, but in particular for China and India due to high air quality benefits, and also for developed regions due to net negative mitigation costs. Energy and resource exporting regions, on the other hand, face higher mitigation cost than benefits. Our analysis further shows that the result of higher health benefits than mitigation costs is robust across various air pollution control scenarios. However, although climate mitigation results in substantial air pollution emission reductions overall, we find significant remaining emissions in the transport and industry sectors even in a 2 ∘C world. We therefore call for further research in how to optimally exploit climate policy and air pollution control, deriving climate change mitigation pathways that maximize co-benefits. [ABSTRACT FROM AUTHOR]

It is important to estimate a high-resolution spatiotemporal distribution of temperature rise under climate change for effective adaptation and mitigation planning. This paper studies the threshold crossing time (TCT) for eight Indian warming targets (IWTs) between 1.5 and 5 °C based on regional climate models (RCMs) participating in The Coordinated Regional Downscaling Experiment (CORDEX)—South Asia project. To evaluate the performance of CORDEX experiments in simulating the near-surface mean temperature, the model performance index (MPI) is used which represents that the CanESM experiment performs best for simulating Tmean over India. All India average Tmean projected by the multi-model ensemble (MME) represents that 1.5 °C TCT is about 2033 ± 3 and 2028 ± 3 in RCP4.5 and RCP8.5 scenarios, respectively. During the twenty-first century, Indian subcontinent can experience five IWTs (1.5–3.5 °C) under RCP4.5 and all eight under scenario RCP8.5. The fastest warming region in India is the western Himalayan region (North India) and north-west region (Indian Thar Desert). [ABSTRACT FROM AUTHOR]

Present study attempts to project extreme precipitation indices over 34 different meteorological subdivisions and six homogeneous regions such as Northwest, Central Northeast, Northeast, West Central, Peninsular India and Hilly Region during summer monsoon season in the twenty-first century. For this purpose, the Regional Climate Model version4 (RegCM4) had been run at 50 km horizontal resolution forced with the global model GFDL-ESM2 M, during reference period 1976–2005 for the model validation, and the mid- (2031–2060) and far-future (2070–2099) for projections under RCP8.5 scenario over the South Asia CORDEX domain. In this paper, model simulated precipitation has been validated against IMD, APHRODITE and NCEP/NCAR data sets. The results indicate that RegCM4 captures the important features of seasonal precipitation and various extreme indices over the study area. The RegCM4 has projected an increase in the mean seasonal precipitation by 0.56 mm/day whereas in case of GFDL model the rate is 0.39 mm/day during the far-future relative to the reference period. The heavy precipitation indices are projected to increase more frequently (0.264/decade) than the mean precipitation rate (0.01/decade) over India. The correlations between the extreme precipitation indices and the seasonal mean precipitation are found to be strong. In addition, the consecutive dry days are projected to occur more frequently (3–5 days) over West Central (Telangana, Vidarbha and Marathwada) and west Rajasthan while consecutive wet days are projected to decrease over larger parts of India during far-future. Similarly, 1 day maximum precipitation and the simple daily intensity index are projected to increase consistently from mid- to far- futures over some sub-divisions of West coast, Hilly and Northeast regions. From a spatial probability perspective, model projection indicates more frequent severe drought and flood conditions over India. [ABSTRACT FROM AUTHOR]

Adaptation to environmental change, including biodiversity change, is both a new imperative in the face of global climate change and the oldest problem in human history. Humans have evolved a wide range of adaptation strategies in response to localised environmental changes, which have contributed strongly to both biological and cultural diversity. The evolving set of locally driven, 'bottom-up' responses to environmental change is collectively termed 'autonomous adaptation,' while its obverse, 'planned adaptation,' refers to 'top-down' (from without, e.g. State-driven) responses. After reviewing the dominant vulnerability, risk, and pathway approaches to adaptation, this paper applies an alternative framework for understanding human adaptation processes and responding more robustly to future adaptation needs. This adaptation processes-to-pathways framework is then deployed to consider human responses to biodiversity change caused by an aggressive 'invasive' plant, Lantana camara L., in several agri-forest communities of southern India. The results show that a variety of adaptation processes are developing to make Lantana less disruptive and more useable—from avoidance through mobility strategies to utilizing the plant for economic diversification. However, there is currently no clear synergy or policy support to connect them to a successful long-term adaptation pathway. These results are evaluated in relation to broader trends in adaptation analysis and governance to suggest ways of improving our understanding and support for human adaptation to biodiversity change at the household, community, and regional livelisystem levels, especially in societies highly dependent on local biodiversity for their livelihoods. [ABSTRACT FROM AUTHOR]

While much of the literature on future food consumption in India in the decades ahead focuses on cereals, this paper presents estimates of potato demand to the year 2030 according to three different scenarios. Estimated increases in total food demand for potato range from 20 to 30 million metric tonnes and from 5.5 to 15 kg capita−1 year−1, with modest, if any, increases in foreign trade. These estimates highlight the potato's growing importance in Indian diets as food consumption patterns continue to evolve while maintaining their traditional roots. They also call for a series of public and private initiatives to facilitate the realization of the potato's potential future contribution to food consumption and nutrition in India. These include renewed support for research and development as relates to improved technologies for the potato sector both on and off the farm. It also involves opportunities for industry to combine market-driven innovations to achieve commercial success with benefits for growers, consumers and the environment as well. [ABSTRACT FROM AUTHOR]

This paper examines climate change adaptation and gender issues through an application of a feminist intersectional approach. This approach permits the identification of diverse adaptation responses arising from the existence of multiple and fragmented dimensions of identity (including gender) that intersect with power relations to shape situation-specific interactions between farmers and ecosystems. Based on results from contrasting research cases in Bihar and Uttarakhand, India, this paper demonstrates, inter alia, that there are geographically determined gendered preferences and adoption strategies regarding adaptation options and that these are influenced by the socio-ecological context and institutional dynamics. Intersecting identities, such as caste, wealth, age and gender, influence decisions and reveal power dynamics and negotiation within the household and the community, as well as barriers to adaptation among groups. Overall, the findings suggest that a feminist intersectional approach does appear to be useful and worth further exploration in the context of climate change adaptation. In particular, future research could benefit from more emphasis on a nuanced analysis of the intra-gender differences that shape adaptive capacity to climate change. [ABSTRACT FROM AUTHOR]

This paper attempts to assess the vulnerability to climate change of human communities in selected mouzas of Sagar Island, South 24 Parganas District of India. A primary household survey has been conducted to collect data on socio-demographic profile, livelihood strategy, health, food, water, social network, natural disaster and climate variation indicators, were selected for Livelihood Vulnerability Index (LVI) and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) analyses to measure and compare the vulnerability of mouzas (administrative unit) currently suffering from frequent flooding, coastal erosion and embankment breaching on an annual basis. Secondary data collected from the Indian Meteorological Department, the Water Resources Information System of India and the Global Sea Level Observing System have been used to identify dynamics of climate change by employing statistical and Geographic Information System (GIS) techniques. A GPS survey has been conducted to identify locations of embankment breaching, and satellite images obtained from the National Aeronautics and Space Administration and U.S. Geological Survey (NASA USGS) Government website have been applied to shoreline and land use change detection, using a supervised maximum likelihood classification. The results indicate that the study area has experienced increasing temperature, changing precipitation patterns, rise in sea level, higher storm surges, shoreline change, constant land loss, embankment breaching and changing land use, which have had impact on vulnerability, particularly of poorer people. The LVI (0.48 to 0.68) and LVI-IPCC (0.04 to 0.14) scores suggest that the populations of Dhablat, Bankimnagar, Sumatinagar, Muri Ganga and Sibpur mouzas are highly vulnerable (LVI scores of 0.60 to 0.68 and LVI-IPCC scores of 0.11 to 0.14) to climate change both because the communities are more exposed to it, and because poor access to food, health facilities and water makes them extremely sensitive to it and lowers their adaptive capacity. The findings of this study could be crucial to framing further development and adaptation strategies relating to climate change, and to safeguarding the estuarine ecosystem and the vulnerable population. [ABSTRACT FROM AUTHOR]

Impacts of global warming and local scale urbanization on precipitation are evident from observations; hence both must be considered in future projections of urban precipitation. Dynamic regional models at a fine spatial resolution can capture the signature of urbanization on precipitation, however simulations for multiple decades are computationally expensive. In contrast, statistical regional models are computationally inexpensive but incapable of assessing the impacts of urbanization due to the stationary relationship between predictors and predictand. This paper aims to develop a unique modelling framework with a demonstration for Mumbai, India, where future urbanization is projected using a Markov Chain Cellular Automata approach, long term projections with climate change impacts are performed using statistical downscaling and urban impacts are simulated with a dynamic regional model for limited number of years covering different precipitation characteristics. The evaluation of the statistical downscaling methodology over historical time period reveals large underestimation of the extreme rainfall, which is improved effectively by applying another regression model, for extreme days. The limited runs of dynamic downscaling models with different stages of urbanization for Mumbai, India, reveal spatially non uniform changes in precipitation, occurring primarily at the higher quantiles. The statistical and dynamical outputs are further integrated using quantile transformation for precipitation projection in Mumbai during 2050s. The projections show dominant impacts of urbanization compared to those from large scale changing patterns. The uniqueness of this computationally efficient framework lies in an integration of global and local factors for precipitation projections through a conjugal statistical–dynamical approach. [ABSTRACT FROM AUTHOR]

The global incidence of very intense cyclones has increased in recent decades with climate projections signaling that this trend will intensify. To what degree can vulnerability to extreme weather events be mitigated by access to a rural livelihoods program, particularly with regard to the impacts on women? This paper addresses this question through a natural experiment arising from two independent but overlapping sources of variation: exposure to a devastating cyclone that occurred in the Bay of Bengal region of India and the staggered rollout of a rural livelihoods intervention. Comparisons from household surveys across communities more or less exposed to the storm before and after the introduction of the program reveal that the storm led to significant reductions in overall household expenditure, and that these reductions were indeed the largest for women, adding to the emerging evidence for the frequently-posed hypothesis that women bear the brunt of the effects of disasters on overall household consumption. Participation in the livelihoods program mitigated some of the reductions in household nonfood expenditure and women's consumption, but not on food expenditure. These results from a densely populated region whose topography makes it particularly vulnerable to storms can inform future policy approaches and aid in modeling the impact of these policies on the effects of climate change. [ABSTRACT FROM AUTHOR]

Given the general notion that dynamical downscaling leads to added accuracy in both historical simulations as well as climate change projections, this paper investigates its validity over India using historical data (1975-2005) from the CORDEX models and their driving global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5), and comparing them against observed temperature and rainfall. We find that downscaling invariably leads to an improvement in the spatial pattern of surface air temperature, but compared to the driving GCMs, the errors in magnitude after downscaling are even worse in some cases. In regard to JJAS rainfall simulations, the CMIP5 driving GCMs are found to be superior to their dynamically downscaled counterparts both in terms of spatial patterns as well as magnitude of errors. Both CMIP5 driving GCMs as well as the CORDEX models underestimate rainfall during JJAS; however, negative bias in CORDEX models is worse. Unlike the driving CMIP5 GCMs, their dynamically downscaled counterparts simulate an early onset followed by a slow and late withdrawal of the Indian summer monsoon rainfall. The frequency of occurrence of rainfall intensities is simulated well by both sets of models in the lower intensity regime (0-20 mm/day); however, for higher intensities, the driving CMIP5 GCMs underestimate whereas the CORDEX models overestimate. [ABSTRACT FROM AUTHOR]

The initial collision between Indian and Asian continents marked the starting point for transformation of land-sea thermal contrast, uplift of the Tibet-Himalaya orogen, and climate change in Asia. In this paper, we review the published literatures from the past 30 years in order to draw consensus on the processes of initial collision and suturing that took place between the Indian and Asian plates. Following a comparison of the different methods that have been used to constrain the initial timing of collision, we propose that the tectono-sedimentary response in the peripheral foreland basin provides the most sensitive index of this event, and that paleomagnetism presents independent evidence as an alternative, reliable, and quantitative research method. In contrast to previous studies that have suggested collision between India and Asia started in Pakistan between ca. 55 Ma and 50 Ma and progressively closed eastwards, more recent researches have indicated that this major event first occurred in the center of the Yarlung Tsangpo suture zone (YTSZ) between ca. 65 Ma and 63 Ma and then spreading both eastwards and westwards. While continental collision is a complicated process, including the processes of deformation, sedimentation, metamorphism, and magmatism, different researchers have tended to define the nature of this event based on their own understanding, an intuitive bias that has meant that its initial timing has remained controversial for decades. Here, we recommend the use of reconstructions of each geological event within the orogenic evolution sequence as this will allow interpretation of collision timing on the basis of multidisciplinary methods. [ABSTRACT FROM AUTHOR]

The climate change induced by global warming has raised concerns over safety of coastal and offshore infrastructure. At several places in the world therefore studies are being made to know the effect of such change on design and operational ocean parameters. This paper is oriented in this direction and its aim is to specify future changes in the design significant wave height (Hs) over a series of locations along the Indian coastline. Thirty-nine sites were selected along the 7000-km-long Indian coast and design Hs with a return period of 100 years were calculated on the basis of past as well as future wave data of duration 27 years each. The simulation of waves was done by running a numerical wave model forced by wind derived from a modeling experiment called CORDEX. Fitting of data to Generalized Pareto Distribution gave the 100-year Hs at all 39 locations. The results indicate that the design Hs calculated on the basis of projected data was much higher than the one based on historical data. Such increase was as small as 5 % and as high as 58 % as per the location. The west coast sites showed a higher rise in the Hs value than the east ones. [ABSTRACT FROM AUTHOR]

This paper presents results of a study of long term trends in the characteristics of the within-season temporal profile of southwest monsoon rainfall over western India during the last five decades in relation to global warming induced regional climate change. In contrast to recent climate change analyses and projections, no significant long-term trends have been observed in this study. Slow decadal scale variations observed are analysed in relation to Pacific Decadal Oscillations (PDO). Daily variations in rainfall anomaly show opposite characteristics during negative and positive phases of PDO. The above-normal rainfall (>25%) is found during the starting phase of monsoon in negative PDO. Over the last decade, i.e., during 2000-2007, the seasonal rainfall amount, as well as seasonal span of southwest monsoon over western India is indicative of a gradual increase. [ABSTRACT FROM AUTHOR]

In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments. [ABSTRACT FROM AUTHOR]

India's position on climate change negotiations is likely to have far reaching implications for the success of global climate cooperation. Since the beginning of negotiations, the principle of equity and common but differentiated responsibilities (CBDR) remained the centerpiece of India's stand. The stand started to evolve at the 15th Conference of Parties to the United Nations Framework Convention on Climate Change at Copenhagen in 2009, when India accepted voluntary commitments to reduce emission intensity. Though India still swears by CBDR, status of the principle in the negotiations has become doubtful after the Durban Climate Conference in 2011 committed all parties to take emission targets. This paper traces major transition points in India's negotiating position over the years and provides a descriptive context of its climate-related concerns. It analyzes the interview responses of 15 top scientists, experts, and negotiators to build upon core areas of climate change issues in India, its future role, and position in negotiations. Interviewees, in general, were in favor of protecting the carbon space for the poor who had very low emissions. [ABSTRACT FROM AUTHOR]

Existing studies in the context of assessing vulnerability to climate variability and change delineate, rather inadequately, interconnected interactions occurring within the climate-human-environment interaction space. Besides, studies documenting stakeholders' perceptions regarding climate change induced vulnerabilities are limited in terms of providing indicators for decision-making. This paper aims at constructing a livelihood vulnerability index for climate variability and change capturing interconnected interactions based on peoples' perceptions while providing indicators for evidence based decision-making. A semi-quantitative fuzzy cognitive mapping (FCM) approach has been deployed to capture peoples' perceptions of climate induced perturbations and adaptations. This approach helps quantify stakeholders' perspectives while capturing interconnected interactions in order to estimate livelihood vulnerability to climate variability and change of poor agro-pastoralists in the Bhilwara, a district in Western India. Combining the FCM approach with a sustainable livelihood framework warrants an understanding of assets sensitive to climate variability and change along with those serving as adaptive capacities. The findings of this study confirm that financial and natural assets are most susceptible to harm while organisational and financial assets provide resilience against climate variability and change. The results suggest that livelihood vulnerability of agro-pastoralists lie in the range of being 'vulnerable' to climate variability and change while varying across three seasons summer, winter, and rainfall. [ABSTRACT FROM AUTHOR]

Serious attempts have been made to manage the highly populated Indian coast during the last 25 years in terms of regulating the activities and managing disasters. This has lead to formulation of various policies to maintain environmental quality and sustainably manage the coastal resources. Basically, the coastal zone needs to address the demands of all the stakeholders starting from traditional local communities, administrators, to academic researchers etc. India has faced tremendous challenges in implementing regulatory measures like Coastal Regulation Zone (CRZ) issued in 1991 by demarcating countries coast in to four different zones with provisions and prohibitions for various activities. The concept of Integrated Coastal Zone Management (ICZM) has been taken with the support of spatial decision-support tools derived from satellite data including national programmes on inter-sectoral approaches towards ICZM. 2004 onwards a series of disasters have reminded the necessity of having regulatory measures through implementable approaches. Subsequently, the CRZ 2011 notification has been a new addition to the list of policies using bottom-up approach as a good governance tool. The country has strengthened its potential in coastal management, disaster management and several community based field projects to enhance participation of stakeholders. This paper is aimed to critically review the processes that are made during the last two decades including the future challenges towards sustainable management of coastal zone with special emphasis on the three coastal areas from eastern, western and southern coast of India. [ABSTRACT FROM AUTHOR]

The paper presents detailed studies on the radiation levels and the seasonal variation and vertical profiles of activity of natural radio nuclei in sand samples of Chavara beach, a high background radiation area of Kerala on the south west coast of India. The elevated levels of Th and Ra activity were observed in the region with highest activity of 18,515 Bq kg for Th. The study on vertical profiles of radionuclides showed a significant variation of activity along with the depth. The higher activity of radionuclides was observed in postmonsoon season. The effective dose rate was evaluated and statistical analysis of the results was performed. [ABSTRACT FROM AUTHOR]

The paper presents the nature of variations of tropospheric and total ozone column retrieved from the Convective Cloud Differential (CCD) technique, Ozone Monitoring Instrument (OMI), and Total Ozone Mapping Spectrometer (TOMS) data, National Aeronautics and Space Administrations (NASA), USA, respectively; surface temperature, relative humidity, total rainfall, ozone precursors (non-methane hydrocarbon, carbon monoxide, nitrogen dioxide, and sulphur dioxide) that are collected from India Meteorological Department (IMD), Alipore, Kolkata; solar insolation obtained from Solar Geophysical Data Book and El-Niño index collected from National Climatic Data Center, US Department of Commerce, National Oceanic and Atmospheric Administration, USA. The effect of these climatic parameters and ozone precursors on ozone variations is critically analyzed and explained on the basis of linear regression and correlation. It has been observed that the maximum, minimum and mean temperature, relative humidity, solar insolation, tropospheric, and total ozone column (TOC) showed slight increasing tendencies from October 2004 to December 2011, while total rainfall and El-Niño index showed little decreasing tendencies for the same period. Amongst selected climatic parameters and ozone precursors, the solar insolation and the average temperature had a significant influence on both, the tropospheric ozone and total ozone column formation. The solar insolation had contributed more in tropospheric ozone than in total ozone column; while El-Niño index had played a more significant role in total ozone column build up than in tropospheric ozone. Negative correlation was observed between almost all ozone precursors with the tropospheric and total ozone. The tropospheric ozone and total ozone column were also significantly correlated. The level of significance and contribution of different climatic parameters are determined from correlation technique and Multiple Linear Regression (MLR) method. The related chemical kinetics for ozone production processes has been critically described. [ABSTRACT FROM AUTHOR]

The summer monsoon rainfall affects most of the population of the Indian subcontinent. A slight variation of strength and spatial distribution in monsoon rains has huge societal impacts. So understanding the significance of its variability and the factors that control this variability is an imperative task. The Indian monsoon (also regarded as a global phenomenon) varies with the global climatic components like geopotential height, sea surface temperature, outgoing long-wave radiation and mean sea level pressure. The paper presents a statistical analysis of rainfall (over India) and climatic components (over the Arabian Peninsula) and the relationship between them. The period (1979–2013) shows a decrease in monsoon rainfall over the country. During this period, there was an increase in the tropospheric temperature over the Arabian Peninsula. Rainfall showed a direct relationship with the tropospheric temperature and thickness that gets stronger during the period (1979–2013). Except for the northeastern region of India, the rest showed a strong positive correlation with the middle and upper tropospheric temperature over the Arabian Peninsula while the lower tropospheric temperature showed a weak relationship. However, this correlation gets weakened during the El Nino and La Nina years. The findings will be helpful to enhance the Indian rainfall variation and the climatic factors responsible for this variation. [ABSTRACT FROM AUTHOR]