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Western disturbances (WDs) are synoptic-scale weather systems embedded within the subtropical westerly jet. Manifesting as upper-level troughs often associated with a lower-tropospheric low over Western India, they share some dynamical features with extratropical cyclones. WDs are most common during the boreal winter (December to March), during which they bring the majority of precipitation – both rain and snow – to the Western Himalaya, as well as to surrounding areas of north India, Pakistan and the Tibetan Plateau. WDs are also associated with weather hazards such as heavy snowfall, hailstorms, fog, cloudbursts, avalanches, frost, and coldwaves. In this paper, we review the recent understanding and development on WDs. Recent studies have collectively made use of novel data, novel analysis techniques, and the increasing availability of high-resolution weather and climate models. This review is separated into six main sections – structure and thermodynamics, precipitation and impacts, teleconnections, modelling experiments, forecasting at a range of scales, and paleoclimate and climate change – each motivated with a brief discussion of the accomplishments and limitations of previous research. A number of step changes in understanding are synthesised. Use of new modelling frameworks and tracking algorithms has significantly improved knowledge of WD structure and variability, and a more frequentist approach can now be taken. Improved observation systems have helped quantification of water security over the Western Himalaya. Convection-permitting models have improved our understanding of how WDs interact with the Himalayas to trigger natural hazards. Improvements in paleoclimate and future climate modelling experiments have helped to explain how WDs and their impacts over the Himalaya respond to large-scale natural and anthropogenic forcings. We end by summarising unresolved questions and outlining key future WD research topics. [ABSTRACT FROM AUTHOR]

Conceptual models demonstrate that climate can control the structural evolution of mountain belts and that Pliocene–Quaternary global climate change modulated Himalayan wedge behaviour. A key test of this hypothesis is the timing of foreland accretion. If foreland accretion pre‐dates climate change, then climate is not the primary driver of mountain building. New apatite (U–Th)/He data from NW Himalaya foreland thrust sheets suggest that accretion had occurred by the latest 4 Ma, prior to the Pliocene–Quaternary global climate change. Climate cannot, therefore, be invoked as the principal driver of Himalayan tectonics in the late Cenozoic. Statement of significance: This paper presents 66 new, single grain apatite (U–Th)/He (AHe) dates from the foreland basin that constrain NW Himalayan evolution through the late Cenozoic. We show that accretion of the NW sub‐Himalayan foreland was underway by 4 Ma at the latest, several million years earlier than previous estimates, and was followed by distributed, wedge‐internal deformation by 2 Ma. These and other published data present a consistent pattern and timing of deformation observed over nearly 600 km of the NW sub‐Himalaya. Our new constraints on orogen evolution provide key insights into the relative importance of climate and tectonics in driving orogenic systems. [ABSTRACT FROM AUTHOR]

A regional climate modelling system, the Providing REgional Climates for Impacts Studies developed by the Hadley Centre for Climate Prediction and Research, has been used to study future climate change scenarios over Indus basin for the impact assessment. In this paper we have examined the three Quantifying Uncertainty in Model Predictions simulations selected from 17-member perturbed physics ensemble generated using Hadley Centre Coupled Module. The climate projections based on IPCC SRES A1B scenario are analysed over three time slices, near future (2011-2040), middle of the twenty first century (2041-2070), and distant future (2071-2098). The baseline simulation (1961-1990) was evaluated with observed data for seasonal and spatial patterns and biases. The model was able to resolve features on finer spatial scales and depict seasonal variations reasonably well, although there were quantitative biases. The model simulations suggest a non-uniform change in precipitation overall, with an increase in precipitation over the upper Indus basin and decrease over the lower Indus basin, and little change in the border area between the upper and lower Indus basins. A decrease in winter precipitation is projected, particularly over the southern part of the basin. Projections indicate greater warming in the upper than the lower Indus, and greater warming in winter than in the other seasons. The simulations suggest an overall increase in the number of rainy days over the basin, but a decrease in the number of rainy days accompanied by an increase in rainfall intensity in the border area between the upper and lower basins, where the rainfall amount is highest. [ABSTRACT FROM AUTHOR]

Climate change impact on the habitat distribution of umbrella species presents a critical threat to the entire regional ecosystem. This is further perilous if the species is economically important. Sal (Shorea robusta C.F. Gaertn.), a climax forest forming Central Himalayan tree species, is one of the most valuable timber species and provides several ecological services. Sal forests are under threat due to over-exploitation, habitat destruction, and climate change. Sal's poor natural regeneration and its unimodal density-diameter distribution in the region illustrate the peril to its habitat. We, modelled the current as well as future distribution of suitable sal habitats under different climate scenarios using 179 sal occurrence points and 8 bioclimatic environmental variables (non-collinear). The CMIP5-based RCP4.5 and CMIP6-based SSP245 climate models under 2041–2060 and 2061–2080 periods were used to predict the impact of climate change on sal's future potential distribution area. The niche model results predict the mean annual temperature and precipitation seasonality as the most influential sal habitat governing variables in the region. The current high suitability region for sal was 4.36% of the total geographic area, which shows a drastic decline to 1.31% and 0.07% under SSP245 for 2041–60 and 2061–80, respectively. The RCP-based models predicted more severe impact than SSP; however, both RCP and SSP models showed complete loss of high suitability regions and overall shift of species northwards in the Uttarakhand state. We could identify the current and future suitable habitats for conserving sal population through assisted regeneration and management of other regional issues. [ABSTRACT FROM AUTHOR]

The central and western Tibetan Plateau (CWTP) is characterized by harsh environment and strong interactions among the spheres of earth as well as significant changes in climate and water cycles over the past four decades. The lack of precipitation observations is a bottleneck for the study of land surface processes in this region. Over the past six years, we have designed and established two observation transects across the south-north and the west-east in this region to obtain hourly rainfall data during the warm season (May–September). The south-north transect extends from Yadong Valley on the southern slope of the Himalayas to Shuanghu County in the hinterland of the plateau, with a total of 31 stations; the west-east transect extends from Shiquanhe in the west to Naqu in the central TP, with a total of 22 stations. The observation dataset has been applied to clarify the spatiotemporal characteristics of precipitation in the CWTP, to evaluate the quality of typical gridded precipitation products, to support the development of regional climate models, and to reveal the processes of summertime lake-air interactions. The observation dataset has been released in the National Tibetan Plateau Data Center. [ABSTRACT FROM AUTHOR]

The Himalayan region is likely particularly exposed to climate change indicated by the high regional rate of change. The number of high-resolution, well-calibrated, and long-term paleoclimate reconstructions are however regrettably few, to set this change in a longer-term context. The dendroclimatic reconstructions over Himalaya that do exist have only reconstructed summer season temperatures, and rarely or never attempted to reconstruct mean annual temperatures. The paucity of long meteorological records is a matter of concern when developing chronologies of climate sensitive tree-ring data in Bhutan, but the chronologies would theoretically be of high potential for extending short meteorological records back in time using trees in high-elevation ecotones. The objectives of this study were to explore dendroclimatic signals in tree-ring width chronologies of Abies densa growing in these extreme ecotones and to reconstruct, if possible, annual temperatures over Northern Bhutan. A point-by-point regression analysis revealed that the regional composite chronology was significantly and positively correlated with temperatures of all months of the current year, i.e., January to December. The chronology was highly correlated with annual temperatures (calibration period R = 0.67 and validation period R = 0.50; p < 0.001) allowing a reconstruction of temperature over Northern Bhutan (NB-TEMR). The NB-TEMR reveals some common variations with summer temperature reconstructions of the Northern Hemisphere as well as the Himalayan region, particularly w.r.t to the recent warming trend. The reconstruction covers the period of 1765 to 2017. This reconstruction reveals a warming trend since 1850 with higher rates of warming 1935 to 2017, but with a pause around 1940–1970. The warming is consistent with reduced volcanic activity and increase of greenhouse gases. We anticipate that our new reconstruction of annual mean temperature could be an important contribution for future climate change studies and assessments of climate models. [ABSTRACT FROM AUTHOR]

The Hindu Kush Himalaya region in Nepal is considered hydrologically vulnerable and fragile, and is likely to face adverse impacts due to climate change. Many rivers originate in this region, which are the lifeline for the millions of riparian people. The Marsyangdi river basin is the hub of hydroelectric power generation. The main objective of this study is to assess the impact of climate change in water availability by using the Soil and Water Assessment Tool (SWAT) model. Future climate projections were derived from three regional climate models (RCMs), namely ACCESS1‐CCAM (ACCESS) CNRM‐CM5‐CCAM (CNRM), and MPI‐ESM‐LR‐CSIRO‐CCAM under two representative concentration pathways, RCP 4.5 and RCP 8.5. These projections were bias‐corrected against the observed historical data, and simulation of impact was assessed using the SWAT model. This study reveals an increase in maximum temperature by 1.4°C by the 2040s (2031–50) and 2.6°C by the 2070s (2061–80) and in minimum temperature by 1.8 and 2.9°C by the 2040s and 2070s, respectively. The future projected rainfall shows a declining trend in all the models. The maximum increase in annual rainfall in the CNRM model is about 31.1% for RCP 8.5 during the 2040s and the MPI RCP 8.5 model show a minimum reduction of about 19.6% in the 2070s. In all three models the average annual rainfall is expected to increase by 10.2 and 10.7% by the 2040s and 2070s respectively. The reduction in streamflow in 2031–2050 is maximally about 19% in the CNRM RCP 8.5 and minimally about 6.3% in the MPI RCP 8.5. For the period 2061–2080, the CNRM RCP 8.5 shows a maximum decrease in streamflow of about 18.9% and the MPI RCP 8.5 shows a minimum reduction in streamflow of about 2.6%. This study will give significant insight to the planners for sustainable and integrated management of water resources and for the operation and design of hydropower projects in the basin. [ABSTRACT FROM AUTHOR]

This study investigated the impacts of climate and socio-economic changes on water resources in the Beas-Sutlej river basin, Himalaya. Multiple-model ensembles of five climate models forced with the Representative Concentration Pathway (RCP) 8.5 scenario and the Shared Socio-economic Pathway SSP 1 were used. A validated Water Evaluation And Planning (WEAP) model of the basin was used for assessing the resulting sectoral water allocations. The results showed increasing runoff during the pre-monsoon and monsoon seasons, principally as the respective consequences of increased glaciers melting and higher rainfall. The finding also indicates that ensemble mean annual irrigation water demand will decrease by between 8 and 13% in Punjab due to the conversion of agricultural land to urban centres but will increase in Rajasthan by about 14%. These outcomes will be useful for the Bhakra and Beas Management Board in developing adaptation strategies to cope with any future water shortages that may occur in the basin. [ABSTRACT FROM AUTHOR]

The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP6 are of interest. Here, we analyze 32 models of the latest CMIP6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with a high agreement between the models independent of the SSP if global warming is the dominant forcing of the monsoon dynamics as it is in the 21st century; the multi-model mean for JJAS projects an increase of 0.33 mm d -1 and 5.3 % per kelvin of global warming. This is significantly higher than in the CMIP5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP6 simulations largely confirm the findings from CMIP5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall. [ABSTRACT FROM AUTHOR]

The selection of global climate models (GCMs) for a region remained a difficult step in climate change studies. A state-of-the-art Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm is proposed in this paper for GCM selection. The ranking of GCMs obtained using SVM-RFE was compared to that obtained using entropy-based similarity assessment index known as Symmetrical Uncertainty (SU). The study was conducted in the sub-Himalayan region of Pakistan where a reliable projection of climate is highly significant for water resources management in the entire western part of South Asia. The RF-based regression model was employed to generate a multi-model ensemble (MME) mean of the top-ranked GCMs. The MME mean projection was utilized to estimate the spatiotemporal changes in annual precipitation in comparison with precipitation of 1961‐–2000 for various representative concentration pathway (RCP) scenarios. The SVM-RF selected five GCMs (MIROC5, EC-EARTH, CNRM-CM5, BCC-CSM1.1(m) and BCC-CSM1.1) as most suitable for climate change projections in the study area. Obtained results were found to collaborate well with the results of multiple conventional statistical metrics. The MME mean projections revealed precipitation alteration between −1% and 18% during 2020‐–2059, and 0 and 24% during 2060–2099 for different RCPs. Precipitation was projected to increase up to 20% in the north whereas a decrease up-to −16% in the south. • SVM-RFE algorithm is used for selection of GCMs for Upper Indus Basin (IUB). • Performance of SVM-RF was compared with symmetrical uncertainty (SU) and conventional statistics based methods. • SVM-RFE was found to select the same GCMs as selected by SU and conventional statistics. • Precipitation projections in IUB revealed high heterogeneity in future changes in precipitation. [ABSTRACT FROM AUTHOR]

The study investigates the future climate change in the Jammu and Kashmir (J&K) Himalaya, India, by the end of the twenty-first century under 3 emission scenarios and highlights the changes in the distribution of the prevalent climate zones in the region. The multi-model climate high-resolution projections for the baseline period (1961–1990) are validated against the observed climate variables from 8 meteorological stations in the region. The temperature projections from the GFDL CM2.1 model are found in good agreement with the observations; however, no single model investigated in the present study reasonably simulates precipitation and therefore multi-model ensemble is used for precipitation projections. The average annual temperature is projected to increase by 4.5 °C, 3.98 °C, and 6.93 °C by the end of the twenty-first century under A1B, RCP4.5, and RCP8.5 scenarios, respectively. In contrast, an insignificant variation in precipitation projection is observed under all the 3 scenarios. The analysis indicates that, unlike the 13 climate zones under the updated Köppen-Geiger climate classification scheme, the J&K Himalaya broadly falls into 10 main climate zones only namely, "3 subtropical (~ 11%), 4 temperate (~ 19%), and 3 cold desert (~ 70%) zones". The projected climate change under the 3 emission scenarios indicates significant changes in the distribution of prevalent climate zones. The cold desert climate zone in the Ladakh region would shrink by ~ 22% and correspondingly the subtropical and temperate zones would expand due to the projected climate change. This information is vital for framing robust policies for adaptation and mitigation of the climate change impacts on various socio-economic and ecological sectors in the region. [ABSTRACT FROM AUTHOR]

ABSTRACT The spatial climatic characteristics of the Himalayas are complex and a challenge for regional climate models ( RCMs). There is no doubt that some form of correction before any application of RCM simulations is a must. In recent years, simple bias correction techniques have been overshadowed by more popular and complex bias correction techniques. In this study an attempt is made to compare the performance of a simple and of a comparatively complex correction technique for hydrological analysis at a monthly resolution in the Kaligandaki River Basin of Nepal. The research workflow consists of bias correction of temperature and precipitation using a simple technique (linear scaling) and a comparatively complex one (quantile mapping). The performance at monthly resolution is evaluated against observed meteorological data while a combined evaluation is made via hydrological model response analysis. The wetter and colder RCM estimates were significantly improved after bias correction. The hydrological modelling response also shows the importance of the bias correction of the RCMs. However, no significant difference was observed between the outputs of linear scaling and quantile mapping which exhibited almost identical performances. Hence, this study has a novel conclusion that a simple method, such as linear scaling, is sufficient for hydrological analysis at monthly resolution. [ABSTRACT FROM AUTHOR]

Climate change vulnerability depends on who you are, where you are and what you do. The indigenous communities who primarily depend on natural resources for subsistence livelihoods are among the first and most affected by climate change. Climate models have predicted pronounced warming in high altitude regions of the Himalayas. The transhumant communities of the Himalayas follow traditional lifestyles based on seasonal livestock rearing and subsistence agriculture. There is however, no information on how vulnerable transhumant communities are to climate change, and how vulnerability of transhumant herders differs across the mountainous areas of Nepal. Based on semi-structured interviews with transhumant herders and using the IPCC climate change vulnerability framework, this study assessed and compared the vulnerability of transhumant communities from three districts representing Eastern, Central and Western mountainous region of Nepal. The results showed that the livelihood vulnerability and the climate change vulnerability differ across sites; both of them having lowest index values in the Central region. The vulnerability dimensions viz. exposure, sensitivity and adaptive capacity are largely influenced by diversity in livelihood strategies, income sources and crops, and access to food, water and health facilities. The findings will inform the design of policies and programmes to reduce vulnerability and enhance adaptive capacity of indigenous communities in general and the transhumant communities of the Himalayas in particular. [ABSTRACT FROM AUTHOR]