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The high Himalayas in northern India are an essential source of climate generation and maintenance over the entire northern belt of the Indian subcontinent. It also affects extreme weather phenomena such as western disturbances in the region during winter. The work presented here describes the trends in 117-year precipitation changes and their impact on the western Himalayas and suggests some possible explanations in the context of changing rainfall patterns. Under the investigation, the forecasting efficiency and the prediction pattern of artificial neural network (ANN) and seasonal autoregressive integrated moving average (SARIMA) models for rainfall series in the western Himalayan states of India have been assessed. The results revealed significant changes in the monthly, seasonal, and annual rainfall series data for the three states of the Western Himalayan regions from the years 1900 to 2017. The study also concludes that the nonlinear autoregressive neural network (NARNN) models can be used to forecast the western Himalayan region data series well. According to the result interpretation, the highest rainfall may be estimated in August, 1632.63 mm (2023), whereas the lowest rainfall can be obtained in October (0.43 mm) during 2023. The model predicted a gradual decrease in annual rainfall trends in Uttarakhand and Himachal Pradesh from 2018 to 2023 despite heavy rainfall prediction in the monsoon season, whereas Jammu and Kashmir increase in annual rainfall has been predicted from 2018 to 2023. Possible explanations for the change in precipitation over the western Himalayas have also been proposed and explained. [ABSTRACT FROM AUTHOR]

In the Northeast Himalayas (NEH) region, four major conventional land-use types are forest, Jhum lands, fallow Jhum lands and plantations, but little is known about their sustainability and responses to changes. We collected soil samples at two uniform depths (0-15 and 15-30 cm) from the Zunheboto district of Nagaland (India). The dataset was statistically analyzed by conducting an ANOVA-one way, principal component analysis (PCA) and calculating an additive soil quality index (SQIa). Our results confirmed that sand content, bulk density (BD), porosity, soil organic carbon (SOC), cation exchange capacity (CEC), exchangeable calcium and potassium showed significant statistical differences among soil depths depending on the land use management. PCA results showed that soil texture, BD, porosity, SOC and exchangeable cations could be considered the major indicators to define soil quality. After estimating the SQIa, Jhum soils showed the highest values at the surface, while at 15-30 cm soil depth, fallow Jhum soils phase showed the highest ones. The conversion from natural forest to plantation does not hamper the SQ, but their conversion into Jhum may even increase it, for a shorter duration. However, after 1-2 year of cultivation and conversion from Jhum into fallow Jhum land, soil quality could be reduced. [ABSTRACT FROM AUTHOR]

The study aimed to evaluate the impact of shifting cultivation on soil quality, in Wokha district of Nagaland, using weighted soil quality index (SQIw). Four forest sites and three sites under shifting cultivation were selected and physical (texture and bulk density) and chemical (pH, electrical conductivity, cation exchange capacity, organic carbon, available N, P, K, exchangeable cations) parameters were analyzed. The SQIw was calculated on a minimum data set selected by principal component analysis, followed by varimax rotation algorithm and through subsequent normalization of the parameters using the linear scoring function. Significant (P < 0.05) variations in SQIw were found across the depth of the soil and land use according to severity of factors associated with land use. Three different classes of soil quality were also identified: high quality (SQIw > 0.70) for two forest soils (FS1 and FS2) and land under shifting cultivation (JH1), low quality (SQIw < 0.50), only to FS3, and intermediate quality (0.50 < SQI < 0.70) in all other soils. The approach used in this study proved to be sensitive to evaluate the soil quality, however further research is required to better understand the sustainability of shifting cultivation by including more physical, biological and chemical indicators. [ABSTRACT FROM AUTHOR]

A Droplet Measurement Technology (DMT) Cloud Condensation Nuclei Counter (CCNC) was deployed to measure cloud condensation nuclei (CCN) for the first time in the pristine Himalayan region at Himalayan Clouds Observatory (HCO), Swami Ram Tirtha (SRT) Campus (30°34′ N, 78°41′ E, 1706 m AMSL), Hemvati Nandan Bahuguna (HNB) Garhwal University, Badshahithaul, Tehri Garhwal, Uttarakhand, India. The CCN concentration (N CCN) was observed at four supersaturation levels (SS: 0.2, 0.5, 0.8, and 1.0%). In this study, we reported CCN concentration at 0.5% SS in different weather conditions from Aug 01, 2018 to Jun 30, 2019. During this observation period, the monthly averaged value of CCN concentration ranged between 1098.3 ± 448.9 cm−3 (mean ± SD) and 3842.9 ± 2512.9 cm−3. It covers a significantly wide range of daily averaged concentrations from the minimum concentration of 43.84 cm−3 (during heavy wet scavenging due to snowfall) to maximum concentration of 17000 cm−3 (during the events of a forest fire) at the observation site. The highest CCN concentration is observed at the time of sunrise (~07:00 a.m.) and after the sunset (~07:00 p.m.) for the diurnal variation of monsoon, post-monsoon, and winter season. Pre-monsoon season shows peak values at 10:00 a.m. and at 07:00 p.m. with higher concentrations at night hours. The possible reasons for maximum concentration in morning and evening time could be upliftment and settlement of CCN because of the convection process, anthropogenic emission, vehicular emission, and biomass burning in the residential area and valley region adjacent to HCO, Badshahithaul. The highest CCN concentration (3842.9 ± 2513 cm−3) values of the whole observation period were observed in May 2019. It was significantly affected by the heavy fire activities over the Uttarakhand and nearby IGP regions. Diurnal variation of CCN concentration during the HFAD shows higher values in the night time differing from the diurnal pattern of CCN for other months of the observation period. The long-range transport of air mass could also contribute to the high CCN concentration values, as found through the five-day air mass backward trajectory analysis. The lowest value of CCN concentration corresponds to the heavy rains and snowfall days, possibly caused by extensive wet scavenging. Cluster analysis of the air mass trajectories used for the allocation and classification of the possible sources of pollutants reaching the observation site. The highest fraction of CCN concentration (more than 2000 cm−3) corresponds to the air mass from the arid and semi-arid regions of Asian countries. Large air mass fraction (~40–60%) with moderate CCN concentration was received from northwestern IGP region and foothills of central Himalaya. • Time series of CCN at four different levels of supersaturation (Superssaturation: 0.2, 0.5, 0.8, and 1.0%), and its role in the macroscopic cloud formation mechanism over the high-altitude region. • Study of seasonal, diurnal, and temporal variation of CCN over the Himalayan regions and comparisons with different altitude sites, geographic and climatic conditions of India. • Observations provided the average CCN concentration 1411.3 ± 1110.1 cm−3, 1645.7 ± 690.62 cm−3, 1712.3 ± 862.8 cm−3, and 2514.7 ± 2166.4 cm−3 for Monsoon, Post- Monsoon, Winter and Pre-monsoon Seasons respectively. • Analysis of local meteorological conditions impact on the formation of high-altitude cloud, and complexity of local weather phenomenon. • Use of transport models to analyze and characterize the possible sources of the pollutant for rural areas with relatively low urbanization and industrialization activities and role transported pollutants from the urban (highly polluted and populated) regions on the modification of local meteorology of the Garhwal Himalayan regions. [ABSTRACT FROM AUTHOR]