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The impact of climatic change on the summer monsoon season is studied to understand the rainfall pattern towards the end of the century utilizing the Coupled Model Intercomparison Project, Phase 6 (CMIP6) released by the World Climate Research Programme (WCRP). The analysis of model simulations from CMIP6 was carried out using 64 years of the historical period (1951–2014) and future projections till the end of the century (2015–2100). The models are compared with observed daily rainfall data from the APHRODITE (Asian Precipitation‐Highly‐Resolved Observational Data Integration Towards Evaluation). The analysis revealed that most of the models show an overestimation in the annual cycle of rainfall in the historical period; however, a few of them underestimate the values. The majority of them capture the onset signal of the summer monsoon in early June, along with a good seasonality in the daily rainfall climatology. The simulations that are coherent with the observational data sets are selected on the basis of the Taylor diagram for future projections in four scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5). The projections of the aforementioned scenarios are taken from the model outputs of EC‐Earth3‐Veg‐LR, INM‐CM4‐8, INM‐CM5‐0, MIROC‐ES2L and MPI‐ESM1‐2‐HR. The selected models exhibit far greater agreement among the 30 models when it comes to the features of rainfall during the summer monsoon. We have given more emphasis on summer monsoon rainfall in the historical and future projection periods since the trends are becoming more chaotic, as reported in observational studies. Over the Indian subcontinent, all of the chosen scenarios show an increased frequency of intense rainfall events with varying decadal and multidecadal features. Central India and west coastal belts are showing positive trends in extreme rainfall events towards the end of the century. At the turn of the century, the southern peninsular region experienced a decline in monsoon precipitation, whereas central India experienced an increase. The severity of rainfall variations during the monsoon season and trends in extremes are increasing as we move from the low‐emission scenario to the high‐emission scenario. [ABSTRACT FROM AUTHOR]

A regional earth system model (ROM) was used to examine the projected change in the precipitation extremes (PEs) and associated dynamical and thermodynamical processes over India during the Indian summer monsoon (ISM). In this regard, PEs are computed for India, its six homogeneous regions and subregions the Western Ghats (WG) and central India (CI). The changes are computed for mid‐future (2040–2069: MDF) and far‐future (2070–2099: FRF) with respect to the historical period (1969–2000). ROM showed better resemblance with observation in simulating PEs over other regional climate models (RCMs) that participated in the CORDEX‐CORE simulation. The intense rainfall (95th percentile: R95) is expected to be enhanced over most of the region during MDF that further intensifies in FRF except CNE (central northeast) and NEI (northeast India), where the increase in R95 was restricted only up to MDF. Interestingly, very intense rainfall (99.9th percentile: R99) showed robust increases in both MDF and FRF for all regions. Additionally, long wet (dry) events were shortened (lengthen). Moreover, the short wet and dry spell frequency has increased, while the duration of the wet (dry) spell has decreased (increased) in both time slices over India with noticeable regional variation. This is attributed to the strong cyclonic circulation, reduced vertical wind shear and enhanced moisture transport during the ISM in both time slices. It is very important to highlight the substantial changes in the precipitation extremes to have better planning and strategies that will be helpful to minimize the incurred losses. [ABSTRACT FROM AUTHOR]

The Indian summer monsoon rainfall (ISMR, June–September) is an important factor in agricultural planning and the Indian economy. The ISMR over East India (EI: Chhattisgarh-Bihar-Jharkhand-Odisha) is particularly significant, and it can have an impact on the country's average ISMR. The current study examined projected changes in ISMR over EI with two emission scenarios, RCP4.5 and RCP8.5, for near (2017–2040) and far-future (2041–2070) projections using a set of ten CORDEX-SA Regional Climate Model (RCMs). To begin, the performance of raw and bias-corrected ISMR over EI outputs from ten CORDEX-SA RCMs was compared to a high-resolution (0.25° × 0.25°) gridded rainfall analysis dataset from the India Meteorological Department (IMD) over the hindcast period (1971–2005). Following that, bias-corrected results were used to calculate ISMR projections over EI for the near and distant futures. Most RCMs, according to the findings, can imitate the spatial pattern of ISMR across EI but are restricted in their ability to capture actual magnitudes. Notably, RCM prediction skill increased greatly after employing various bias-correction approaches, the quantile mapping (QQM) bias-correction technique outperformed other current conventional bias correction methods, and the QQM technique was employed for ISMR future projections using RCP4.5 and RCP8.5 emission scenarios. The analysis of ISMR projections over EI reveals that there will be more deficit rainfall years in the short term while more excess rainfall years in the far future. [ABSTRACT FROM AUTHOR]

The contradictory approaches to water sharing at regional and global scale has detrimental impacts on human (domestic and agricultural) and ecological demands. Economic activities have also been affected, including where livelihoods and survival depends upon agriculture. This study considers past and future flow trends and water availability in the Jhelum basin, focusing on the Neelum River. The Neelum River is largest tributary of Jhelum basin and is also an important transboundary river shared between Pakistan and India. To detect historical trends of flow data, Man Kendall and Sen's slope trend analysis were carried out, whereas the future projections in the flow regime were estimated using First Order Morkove stationary method. The analysis shows significant flow depreciation in the period between 1991 and 2013. The two stations were considered in this study Nusheri (Upstream) and Muzaffarabad (Downstream). At Nusheri station monthly and annual decreasing trends dominated (significant decline in the months of June, July and August) including the annual average declining rate of 3.386 cumecs per year. At Muzaffarabad station (downstream to Nusheri) the similar decreasing trends were dominated as were at the upstream, the overall annual average decline rate was 3.186 Cumecs per year The overall flow depreciation was estimated about14% by volume at both stations in the period of 1991 to 2013. The Pakistan has built Neelum-Jhelum hydropower and India has built Kishan Ganga hydropower project on the same river, therefore fair allocation of flow without curtailing water must be made to ensure water availability throughout the year in this river. This will also help to reduce long withstanding turbulence of Pak-India relations. [ABSTRACT FROM AUTHOR]

Since 1960s, India experiences a series of extreme drought and flood events during the summer months. The Humid Subtropical Climatic Zone ( HSTC), which comprises the Indo-Gangetic Plain region of India, is highly vulnerable to the climatic extremities. This region is the home for approximately 40% of total population and yields approximately 50% of total agricultural production of India. We investigate the historical variation in dry/wet conditions and project the future changes in extreme events under two different scenarios of the Coupled Model Inter-comparison Project 5 models. First, the model parameters, that is, precipitation ( P) and temperature ( T) are bias corrected with respect to observation data and finally six models are selected, which are in right phase with the observation for composite analysis. Next, we calculate the potential evapotranspiration (PET) and the Standardized Potential Evapotranspiration Index to characterize the extreme events. Both P and PET are projected to increase in the HSTC zone; however, both the wet and dry conditions demonstrate a persistent increase in future. In relative terms, P increases faster than PET along the Gangetic Plain region (wet condition) and decreases in the southern and eastern part of the region (dry condition). The mitigating effect (RCP4.5 scenario) of precipitation increase will be overridden by strengthened PET and extreme dry condition project markedly under RCP8.5 scenario. The features are consistent with the increase/ decrease in multimodel mean SPEI, consistent with the spatial pattern of P−PET. The area affected due to wet and dry events will be relatively higher under the RCP4.5 and RCP8.5 scenario, respectively. [ABSTRACT FROM AUTHOR]

Abstract: Changes in the surface air temperature and rainfall, extreme events and their future projections at four Indian cities and corresponding meteorological subdivisions and homogeneous zones have been analyzed in this study based on observed gridded datasets from the India Meteorological Department (IMD) and climate projections from nine IPCC models. The cities include Howrah, Vishakhapatnam, Madurai and Kochi. Their corresponding meteorological subdivisions are Gangetic West Bengal, Coastal Andhra Pradesh, Tamil Nadu & Pondicherry and Kerala. When one considers the larger spatial scale, these cities and meteorological subdivisions are situated in the temperature homogeneous zones of North East, East Coast and West Coast. Similarly, North East and Peninsular India are the rainfall homogeneous zones where these four cities are situated. In this study, indication of change in any climate parameter is assumed to be strong if the same is found in a city and also in its meteorological subdivision and homogeneous zone. When the indications are of the same nature in a city and either in its meteorological subdivision or homogeneous zone, it is termed as weak. Comparison shows that the values of annual mean temperature and summer monsoon precipitation simulated by MIROC 3.2 (medres) and NCAR_CCSM3 models are close to the corresponding observed values at each of the four cities. Analysis shows similar trends in the annual mean observed temperature and monsoon precipitation in the selected four cities and their corresponding meteorological subdivisions and homogeneous zones. Based on IMD gridded datasets, the rise in annual mean temperature at 1% significant level during 1969–2005 in Kochi and its subdivision and homogeneous zone is a strong indication of warming. At Madurai such warming is weak. Whereas, at Howrah and Vishakhapatnam, there are no strong indications of warming based on the available IMD gridded data. So far as the future is concerned, the results show that in the coming 30years, the projections of mean temperature rise at Vishakhapatnam, Madurai and Kochi at 1% significance are strong, whereas at Howrah it is weak. Extreme temperature events such as warm days & nights and cold days & nights have also been examined. There is strong projection of the decrease in the moderately cold events (T05p) at 1% significance at Madurai. At the same place, the projection of moderately warm events (T95p) is weak. At Kochi the projections of increase in low (T90p) and moderate (T95p) warm events at 1% significance are weak. There are no strong projections of increase/decrease of warm/cold events in Howrah and Vishakhapatnam. [Copyright &y& Elsevier]

Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius-Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that such effects are small compared to other sources of uncertainty, although models with large Arabian Sea cold SST biases may suppress the range of potential outcomes for changes to future early monsoon rainfall. [ABSTRACT FROM AUTHOR]

The simulations from the regional climate model, PRECIS (Providing REgional Climates for Impacts Studies), were analysed for the occurrence of tropical cyclones in the Bay of Bengal in a baseline scenario (1961-1990) and a future climate scenario (2071- 2100), A2. The analysis showed an increase in the frequency of cyclones in the Bay of Bengal during the late monsoon (August and September) season in the A2 scenario compared to the baseline scenario. However, composite ground-tracks of cyclones do not show any appreciable spatial difference between the two simulations. Extreme sea-level projections along the east coast of India were made using a storm surge model developed for the Bay of Bengal, driven by winds and surface atmospheric pressure obtained from PRECIS. For A2 simulations, a uniform sea-level rise of 4 mm/yr from 1990 was included from the present levels. This corresponds approximately to the average sea-level projections for 2100. The simulated extreme sea-level events were identified and an extreme value analysis was performed using Gumbel fit to determine the return levels. The 100-year return levels of extreme sea-level events are found to be higher by about 15-20% for the A2 scenario than those in the baseline scenario for locations north of Visakhapatnam. However, for the regions experiencing large tidal ranges (Sagar and Kolkata), increase in 100-year return levels for the future scenario are found to be less than 5%. [ABSTRACT FROM AUTHOR]