The present study has been conducted to investigate the relative changes of carbonaceous aerosols (CA) over a high altitude Himalayan atmosphere with and without (very low) anthropogenic emissions. Measurements of atmospheric organic (OC) and elemental carbon (EC) were conducted during the lockdown period (April 2020) due to global COVID 19 outbreak and compared with the normal period (April 2019). The interesting, unexpected and surprising observation is that OC, EC and the total CA (TCA) during the lockdown (OC: 12.1 ± 5.5 μg m −3 ; EC: 2.2 ± 1.1 μg m −3 ; TCA: 21.5 ± 10 μg m −3 ) were higher than the normal period (OC: 7.04 ± 2.2 μg m −3 ; EC: 1.9 ± 0.7 μg m −3 ; TCA: 13.2 ± 4.1 μg m −3 ). The higher values for OC/EC ratio too was observed during the lockdown (5.7 ± 0.9) compared to the normal period (4.2 ± 1.1). Much higher surface O 3 during the lockdown (due to very low NO) could better promote the formation of secondary OC (SOC) through the photochemical oxidation of biogenic volatile organic compounds (BVOCs) emitted from Himalayan coniferous forest cover. SOC during the lockdown (7.6 ± 3.5 μg m −3 ) was double of that in normal period (3.8 ± 1.4 μg m −3 ). Regression analysis between SOC and O 3 showed that with the same amount of increase in O 3 , the SOC formation increased to a larger extent when anthropogenic emissions were very low and biogenic emissions dominate (lockdown) compared to when anthropogenic emissions were high (normal). Concentration weighted trajectory (CWT) analysis showed that the anthropogenic activities over Nepal and forest fire over north-east India were the major long-distant sources of the CA over Darjeeling during the normal period. On the other hand, during lockdown, the major source regions of CA over Darjeeling were regional/local. The findings of the study indicate the immense importance of Himalayan biosphere as a major source of organic carbon.

Assessing warming over the Western Himalayan Region (WHR) of India is challenging due to its limited station data availability and poor data quality. The missing values in the station data were replaced using the Multiple Imputation Chained Equation technique. Finally, 16 stations having continuous records during 1969-2009 were considered as the 'reference stations' for assessing the warming/cooling trends in addition to evaluate the Coupled Model Intercomparison, phase 5 (CMIP5), Global Circulation Model (GCM). Station data indicates winter (DJF) warming is higher and rapid (1.41 ∘ C) than the other seasons and less warming was observed in the post-monsoon (0.31 ∘ C) season. Overall mean annual warming over WHR is ∼0.84 ∘ C during 1969-2009. The performance of 34 CMIP5 models was evaluated based on three different criteria namely (1) mean seasonal cycle, (2) temporal trends and (3) spatial correlation between simulated and observed signals for common available period of 1969-2003 over the study area. Models are provided a final rank on the basis of the cumulative rank obtained in each of three approaches. CMCC-CM, GISS-E2-H and MIROC 5 are three top-ranked models while MIROC-ESM, MIROC-ESM-CHEM and bcc-csm1-1 are three bottom-ranked models over the WHR. The study also extended to judge whether the selected top-ranked models perform well through two alternative data sources namely European Reanalysis (ERA)-interim and Climate Research Unit (CRU), which have not used in the process of model evaluation. The spatial patterns of top-ranked GCM are similar to the spatial pattern obtained through ERA-interim and CRU while zoomed in to WHR but bottom-ranked models fail to reproduce such spatial patterns indicating the top-ranked GCMs would offer more reliability for projecting future climate over WHR.

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Temperature change scenarios over the Chilika Lagoon of India for 200 years were quantified by the observational data sets of the Climate Research Units (CRU) of UK as well as 39 numbers of GCMs simulations from the Couple Model Inter-comparison Project Phase 5 (CMIP5) through Mann Kendall trends analysis. Long-term trend during 1901-2005 over Chilka Lake indicates the highest warming in the pre-monsoon season (1.79°C) and lowest warming (1.09°C) was shown in both the winter and post-monsoon seasons while opposite warming trends i.e., the lowest warming was observed in pre-monsoon season and highest warming was shown in the winter season for recent four decades data. The performance of the CMIP5 GCMs was evaluated over a target point of Chilika Lake. Twelve numbers of models were considered as a group of "better performing GCMs" on the basis of their ability to simulate the long-term trends as well as the mean seasonal correlation with observation. Quantile mapping technique is used for adjusting the bias for the selected GCMs. Improvement in the multi-model ensemble (MME) of bias corrected better performing models compared to MME of 39 GCMs was judged with the help of Taylor plot as well as using four different conventional statistical indices viz. correlation (r), index of agreement (d index), Nash-Sutcliffe efficiency (NSE) and root mean square error (RMSE). All the ensemble members commonly available in the four Representative Concentrations Pathways (RCPs) from the better performing selected models show a temperature change of 0.27-3.61°C, 0.38-3.98°C, 0.28-3.72°C, 0.33-3.41°C and 0.22-2.50°C in annual, winter, pre-monsoon, monsoon and post-monsoon seasons respectively at the end of 21st century over Chilika Lagoon.