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English as spoken as a second language in India has developed distinct sound patterns in terms of both segmental and prosodic characteristics. We investigate the differences between two groups varying in native language (Gujarati, Tamil) to evaluate to what extent Indian English (IE) accents are based on a single target phonological-phonetic system (i.e., General Indian English), and/or vary due to transfer from the native language. Consonants, vowels and intonation patterns from five Gujarati English (GE) and five Tamil English (TE) speakers of IE were transcribed and, in a subset of cases, acoustically analyzed. The results showed transfer effects in GE back vowels, TE rhotics and the proportion of rising versus falling pitch accents in GE intonation. The effect of the General Indian English model was evident in the front vowels of both GE and TE and in the presence of initial voiced stops in TE. Thus, the data reveal both phonetic and phonological influences of IE speakers' native language on their accent in IE, even in proficient speakers; these influences appear to supersede IE norms and can be found in both the segmental and suprasegmental properties of their speech.

Land-surface models (LSMs) typically simulate a single crop per year in a field or location. However, actual cropping systems are characterized by a succession of distinct crop cycles that are sometimes interspersed with long periods of bare soil. Sequential cropping (also known as multiple or double cropping) is particularly common in tropical regions, where the crop seasons are largely dictated by the main wet season. In this paper, we implement sequential cropping in a branch of the Joint UK Land Environment Simulator (JULES) and demonstrate its use at sites in France and India. We simulate all the crops grown within a year in a field or location in a seamless way to understand how sequential cropping influences the surface fluxes of a land-surface model. We evaluate JULES with sequential cropping in Avignon, France, providing over 15 years of continuous flux observations (a point simulation). We apply JULES with sequential cropping to simulate the rice–wheat rotation in a regional 25 km resolution gridded simulation for the northern Indian states of Uttar Pradesh and Bihar and four single-grid-box simulations across these states, where each simulation is a 25 km grid box. The inclusion of a secondary crop in JULES using the sequential cropping method presented does not change the crop growth or development of the primary crop. During the secondary crop growing period, the carbon and energy fluxes for Avignon and India are modified; they are largely unchanged for the primary crop growing period. For India, the inclusion of a secondary crop using this sequential cropping method affects the available soil moisture in the top 1.0 m throughout the year, with larger fluctuations in sequential crops compared with single-crop simulations even outside the secondary crop growing period. JULES simulates sequential cropping in Avignon, the four India locations and the regional run, representing both crops within one growing season in each of the crop rotations presented. This development is a step forward in the ability of JULES to simulate crops in tropical regions where this cropping system is already prevalent. It also provides the opportunity to assess the potential for other regions to implement sequential cropping as an adaptation to climate change. [ABSTRACT FROM AUTHOR]

Sequential cropping (also known as multiple or double cropping) is a common feature, particularly for tropical regions, where the crop seasons are largely dictated by the main wet season such as the Asian summer monsoon (ASM). The ASM provides the water resources for crops grown for the whole year, thereby influencing crop production outside the ASM period. Land surface models (LSMs) typically simulate a single crop per year, however, in order to understand how sequential cropping influences demand for resources, we need to simulate all of the crops grown within a year in a seamless way. In this paper we implement sequential cropping in a branch of the Joint UK Land Environment Simulator (JULES) and demonstrate its use at Avignon, a site that uses the sequential cropping system and provides over 15-years of continuous flux observations which we use to evaluate JULES with sequential cropping. In order to implement the method in future regional simulations where there may be large variations in growing conditions, we apply the same method to four locations in the North Indian states of Uttar Pradesh and Bihar to simulate the rice--wheat rotation and compare model yields to observations at these locations. JULES is able to simulate sequential cropping at Avignon and the four India locations, representing both crops within one growing season in each of the crop rotations presented. At Avignon the maxima of LAI, above ground biomass and canopy height occur at approximately the correct time for both crops. The magnitudes of biomass, especially for winter wheat, are underestimated and the leaf area index is overestimated. The JULES fluxes are a good fit to observations (r-values greater than 0.7), either using grasses to represent crops or the crop model, implying that both approaches represent the surface coverage correctly. For the India simulations, JULES successfully reproduces observed yields for the eastern locations, however yields are under estimated for the western locations. This development is a step forward in the ability of JULES to simulate crops in tropical regions, where this cropping system is already prevalent, while also providing the opportunity to assess the potential for other regions to implement it as an adaptation to climate change. [ABSTRACT FROM AUTHOR]

The effect of large-scale irrigation in India on the moisture budget of the atmosphere was investigated using three regional climate models and one global climate model, all of which performed an irrigated run and a natural run without irrigation. Using a common irrigation map, year-round irrigation was represented by adding water to the soil moisture to keep it at 90% of the maximum soil moisture storage capacity, regardless of water availability. For two focus regions, the seasonal cycle of irrigation matched that of the reference dataset, but irrigation application varied between the models by up to 0.8 mm day−1. Because of the irrigation, evaporation increased in all models, but precipitation decreased because of a strong decrease in atmospheric moisture convergence. A moisture tracking scheme was used to track individual evaporated moisture parcels through the atmosphere to determine where these lead to precipitation. Up to 35% of the evaporation moisture from the Ganges basin is recycling within the river basin. However, because of a decreased moisture convergence into the river basin, the total amount of precipitation in the Ganges basin decreases. Although a significant fraction of the evaporation moisture recycles within the river basin, the changes in large-scale wind patterns due to irrigation shift the precipitation from the eastern parts of India and Nepal to the northern and western parts of India and Pakistan. In these areas where precipitation increases, the relative precipitation increase is larger than the relative decrease in the areas where precipitation decreases. It is concluded 1) that the direct effects of irrigation on precipitation are small and are not uniform across the models; 2) that a fraction of up to 35% of any marginal evaporation increase (for example, due to irrigation) will recycle within the river basin; and 3) that when irrigation is applied on a large scale, the dominant effect will be a change in large-scale atmospheric flow that decreases precipitation in eastern India and increases it in western and northern India. [ABSTRACT FROM AUTHOR]

Abstract: An ensemble of regional climate model (RCM) runs from the EU HighNoon project are used to project future air temperatures and precipitation on a 25km grid for the Ganges basin in northern India, with a view to assessing impact of climate change on water resources and determining what multi-sector adaptation measures and policies might be adopted at different spatial scales. The RCM results suggest an increase in mean annual temperature, averaged over the Ganges basin, in the range 1–4°C over the period from 2000 to 2050, using the SRES A1B forcing scenario. Projections of precipitation indicate that natural variability dominates the climate change signal and there is considerable uncertainty concerning change in regional annual mean precipitation by 2050. The RCMs do suggest an increase in annual mean precipitation in this region to 2050, but lack significant trend. Glaciers in headwater tributary basins of the Ganges appear to be continuing to decline but it is not clear whether meltwater runoff continues to increase. The predicted changes in precipitation and temperature will probably not lead to significant increase in water availability to 2050, but the timing of runoff from snowmelt will likely occur earlier in spring and summer. Water availability is subject to decadal variability, with much uncertainty in the contribution from climate change. Although global social-economic scenarios show trends to urbanization, locally these trends are less evident and in some districts rural population is increasing. Falling groundwater levels in the Ganges plain may prevent expansion of irrigated areas for food supply. Changes in socio-economic development in combination with projected changes in timing of runoff outside the monsoon period will make difficult choices for water managers. Because of the uncertainty in future water availability trends, decreasing vulnerability by augmenting resilience is the preferred way to adapt to climate change. Adaptive policies are required to increase society''s capacity to adapt to both anticipated and unanticipated conditions. Integrated solutions are needed, consistent at various spatial scales, to assure robust and sustainable future use of resources. For water resources this is at the river basin scale. At present adaptation measures in India are planned at national and state level, not taking into account the physical boundaries of water systems. To increase resilience adaptation plans should be made locally specific. However, as it is expected that the partitioning of water over the different sectors and regions will be the biggest constraint, a consistent water use plan at catchment and river basin scale may be the best solution. A policy enabling such river basin planning is essential. [Copyright &y& Elsevier]

The ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981-2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land-sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from observationally based gridded datasets, while the monsoon withdrawal is less well simulated. A Hovmöller diagram representation of the mean annual cycle of precipitation reveals that the meridional motion of the precipitation simulated by the RCMs is comparable to the one observed, but the precipitation amounts and the regional distribution differ substantially between the four RCMs. In summary, the spread at the regional scale between the RCMs indicates that important feedbacks and processes are poorly, or not, taken into account in the state-of-the-art regional climate models. [ABSTRACT FROM AUTHOR]

English as spoken as a second language in India (IE) has developed different sound patterns from other varieties of English. While most descriptions of IE have focused on the English of speakers whose first languages belong to the Indo-Aryan or Dravidian families, in this study, I examine the phonetic and phonological characteristics of the English produced by speakers of three Indian L1s from the Tibeto-Burman language family (Angami, Ao, and Mizo). In addition to describing aspects of Tibeto-Burman Indian English, a previously unreported Indian English variety, I also examine how and why this variety of English differs from General Indian English. The English of Tibeto-Burman L1 speakers seems to form a variety distinct from Indian English, most noticeably in terms of the lack of retroflexion of coronal consonants, the devoicing of word-final obstruents, the simplification of consonant clusters, the presence of post-vocalic [p], and the reduced set of vowel contrasts. Most of these can be traced to transfer from the L1 phonology, with the coda devoicing and cluster reductions reflecting simplification in terms of markedness, following developmental sequences found in second language acquisition. [ABSTRACT FROM AUTHOR]

A recent article in World Englishes (Pickering and Wiltshire, 2000) suggests that one difference between Indian English (IE) and American English (AE) varieties is the phonetic realization of prominence. In IE, the syllable considered prominent by Pickering and Wiltshire falls in pitch, while the amplitude changes little. In this study, we show that the results of Pickering and Wiltshire (2000) may be due to a misinterpretation of the positioning of stress in IE. We show that by considering the louder syllable to be the stressed one, IE stress correlates differ in magnitude but not in direction from AE. However, our results confirm Pickering and Wiltshire's in that the phonetic correlates of AE and IE stressed syllables do differ; furthermore, the position of stress may differ, and hence the potential for communication problems between speakers of different varieties remains. [ABSTRACT FROM AUTHOR]

Himalayan headwaters supply large quantities of runoff derived from snowmelt and monsoon rainfall to the Ganges River. Actual snowmelt contribution to discharge in the Ganges remains conjectural under both present and future climatic conditions. As snowmelt is likely to be perturbed through climatic warming, four hydrological models, VIC, JULES, LPJmL and SWAT, appropriate for coupling with regional climate models, were used to provide a baseline estimate of snowmelt contribution to flow at seasonal and annual timescales. The models constrain estimates of snowmelt contributions to between 1% and 5% of overall basin runoff. Snowmelt is, however, significant in spring months, a period in which other sources of runoff are scarce., (Copyright © 2013 Elsevier B.V. All rights reserved.)

The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The northern Indian subcontinent has frequently been identified as a hotspot for land atmosphere interactions. It is also a region with the highest concentration of irrigated land and highest (and increasing) population density in the world. The available water in the region with which to grow food depends on the Asian monsoon, groundwater and melt from Himalayan snows. Any changes or disruptions to these sources of water could threaten the food supply. It is therefore essential to understand how the land surface, and in particular irrigated land, interacts with the atmosphere. It is anticipated that the interactions will occur on many scales. To an extent the magnitude and form of these will depend on the depth of the atmosphere which is affected. Thus at the local, or micro, scale it is the surface layer (some 10 s m deep) which is cooled and moistened by the evaporation of irrigated water, at the meso-scale the Planetary boundary layer (up to 1 or 2 km) will be modified - with possible atmospheric moistening, increased cloud and rain formation and at very large scales the whole dynamics of the south Asian Monsoon will be affected. This illustrates a strong interaction between the Asian monsoon and the regional topography. Of considerable significance is the finding in this paper that up to 60% of the evaporation from irrigated areas in the summer months is ultimately recycled to Himalayan rainfall and so feedbacks to river flows in the Ganges., (Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.)

This study presents the possible regional climate change over South Asia with a focus over India as simulated by three very high resolution regional climate models (RCMs). One of the most striking results is a robust increase in monsoon precipitation by the end of the 21st century but regional differences in strength. First the ability of RCMs to simulate the monsoon climate is analyzed. For this purpose all three RCMs are forced with ECMWF reanalysis data for the period 1989-2008 at a horizontal resolution of ~25 km. The results are compared against independent observations. In order to simulate future climate the models are driven by lateral boundary conditions from two global climate models (GCMs: ECHAM5-MPIOM and HadCM3) using the SRES A1B scenario, except for one RCM, which only used data from one GCM. The results are presented for the full transient simulation period 1970-2099 and also for several time slices. The analysis concentrates on precipitation and temperature over land. All models show a clear signal of gradually wide-spread warming throughout the 21st century. The ensemble-mean warming over India is 1.5°C at the end of 2050, whereas it is 3.9°C at the end of century with respect to 1970-1999. The pattern of projected precipitation changes shows considerable spatial variability, with an increase in precipitation over the peninsular of India and coastal areas and, either no change or decrease further inland. From the analysis of a larger ensemble of global climate models using the A1B scenario a wide spread warming (~3.2°C) and an overall increase (~8.5%) in mean monsoon precipitation by the end of the 21st century is very likely. The influence of the driving GCM on the projected precipitation change simulated with each RCM is as strong as the variability among the RCMs driven with one., (Copyright © 2013 Elsevier B.V. All rights reserved.)