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The overarching goal of this paper is to shed light on the human influence on the changing patterns of heat waves in India using the Heat Wave Magnitude Index daily (HWMId). The HWMId obtained from the observational data sets shows a large increase in the heat waves during the past decades. Investigating the effects of natural (e.g., solar variations and volcanic forcings) and anthropogenic (e.g., greenhouse gas emissions, anthropogenic, land use, and land cover) forcings revealed that the anthropogenic factors have cause a two-fold increase in the occurrence probability of severe heat waves in central and mid-southern India during twentieth century. The spatial distribution of maximum HWMId values under natural and all forcings (including anthropogenic) indicates that in most places human activities have increases the frequency, duration and intensity of extreme heat waves. Under the Representative Concentration Pathway (RCP) 4.5, the risk of heat waves is projected to increase tenfold during the twenty-first century. More than ~ 70% of the land areas in India is projected to be influenced by heat waves with magnitudes greater than 9. Furthermore, we find a significant relationship between heat waves and deficits in precipitation. Results show that concurrent heat waves and droughts are projected to increase in most places in India during the twenty-first century.

The Middle East can experience extended wintertime spells of exceptionally hot weather, which can result in prolonged droughts and have major impacts on the already scarce water resources of the region. Recent observational studies point at increasing trends in mean and extreme temperatures in the Middle East, while climate projections seem to indicate that, in a warming weather scenario, the frequency, intensity and duration of warm spells will increase. The nonstationary warm spell frequency analysis approach proposed herein allows considering both climate variability through global climatic oscillations and climate change signals. In this study, statistical distributions with parameters conditional on covariates representing time, to account for temporal trend, and climate indices are used to predict the frequency, duration and intensity of wintertime warm spells in the Middle East. Such models could find a large applicability in various fields of climate research, and in particular in the seasonal prediction of warm spell severity. Based on previous studies linking atmospheric circulation patterns in the Atlantic to extreme temperatures in the Middle East, we use as covariates two classic modes of ‘fast’ and ‘slow’ climatic variability in the Atlantic Ocean (i.e., the Northern Atlantic Oscillation and the Atlantic Multidecadal Oscillation respectively). Results indicate that the use of covariates improves the goodness-of-fit of models for all warm spell characteristics.

Changing patterns in aerosol concentrations over the Asian region is well documented with a concurrent increase over India and a marked reduction over China. However, aerosol vertical distribution in the changing climate is not fully understood. By combining long-term satellite observations from MODIS and CALIOP, here we show rapid changes in the aerosol vertical distribution over the South and East Asia covering India and China. A statistically significant decreasing (increasing) trend in the boundary layer (free troposphere) aerosol concentrations is noticed over India. ERA-Interim reanalysis model suggests that this increase in free tropospheric aerosol concentrations are due to the lifting of boundary layer pollutants through an increase in convection (and vertical velocity) in a changing climate. In contrast, a consistent decreasing trend is observed over China irrespective of the altitude. Interestingly, a decreasing trend in Aerosol Optical Depth is observed over the northwest India and we relate this to an observed increase in precipitation leading to increase in the vegetation. It is also found that long-term oscillations like QBO, ENSO and solar cycle significantly affect the aerosol concentrations. Thus, it is prudent to conclude that background meteorology and dynamics play an important role in changing patterns of aerosol vertical distribution.

Rubia cordifolia L., is an industrially viable medicinal crop and is widely exploited for the therapeutic potential of its bioactive metabolite, purpurin. The present investigation aimed to explore the chemotypic and molecular variability in seven wild populations of R. cordifolia from South Eastern Ghats region of India. Thirty-eight individuals were assessed for molecular fingerprinting (ISSR markers) and densitometric quantification of purpurin and alizarin. The populations of Yelagiri Hills and Shervaroy Hills contained the highest levels of alizarin (0.115 and 0.093%, respectively) while Pachamalai and Kolli Hills revealed the highest purpurin content (0.284 and 0.280%, respectively). Genetic diversity was generally higher in the same populations that produced higher metabolite content, with the exception of Pachamalai, suggesting a highly prioritized conservation concern. The study revealed a Nei's total gene diversity at species level of 0.266 and of 0.187 at population level, with an average population genetic differentiation of 0.28. No clear genetic or chemical structure was retrieved between the studied populations, with individuals from different locations clustering together, and no significant correlation was obtained between metabolites and genetic diversity or between these and the populations' geographic distances.

Accurate estimation of the planetary boundary layer (PBL) top is essential for air quality prediction, weather forecast, and assessment of regional and global climate models. In this article, the long-term climatology of seasonal, global distribution of PBL is presented by using global positioning system radio occultation (GPSRO) based payloads such as Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), Communication/Navigation Outage Forecast System (C/NOFS), TerraSAR-X, and The Gravity Recovery and Climate Experiment (GRACE) from the year 2006–2015. We used Wavelet Covariance Transform (WCT) technique for precise PBL top identification. The derived PBL top from GPSRO data is rigorously evaluated with GPS radiosonde data over Gadanki. Significant seasonal variation is noticed in both radiosonde and GPSRO observations. Further, we compared the PBL obtained GPS RO with global radiosonde network and observed very good correlation. The number of occultations reaching down to 500 m and retrieval rate of PBL top from WCT method is very high in mid-latitudes compared to tropical latitudes. The global distribution of PBL top shows significant seasonal variation with higher during summer followed by spring, fall, and minimum in winter. In the vicinity of Inter Tropical Convergence Zone (ITCZ), the PBL top is high over eastern Pacific compared to other regions. The ERA-Interim reanalysis data underestimate the PBL top compared to GPS RO observations due to different measurement techniques. The seasonal variation of global averaged PBL top over land and ocean shows contrasting features at different latitude bands.

In the present scenario, the synthesis and characterization of zinc oxide (ZnO) and cerium oxide (CeO2) nanoparticles (NPs) through biological routes using green reducing agents are quite interesting to explore various biomedical and pharmaceutical applications, particularly for the treatment of cancer. This study was focused on the phytosynthesis of ZnO and CeO2 NPs using the leaf extract of Rubia cordifolia L. The active principles present in the plant extract were liable for rapid reduction of Zn and Ce ions to metallic nanocrystals. ZnO and CeO2 NPs were characterized by UV-visible spectroscopy, X-ray diffraction analysis (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDAX), and photoluminescence (PL) techniques. ZnO and CeO2 NPs were partially agglomerated with a net-like structure. Biomedical activities of ZnO and CeO2 NPs were tested against MG-63 human osteosarcoma cells using MTT and reactive oxygen species (ROS) quantification assays. In treated cells, loss of cell membrane integrity, oxidative stress, and apoptosis was observed and it is well correlated with cellular damage immediately after induction. Overall, this study shed light on the anti-cancer potential of ZnO and CeO2 NPs on MG-63 human osteosarcoma cells through differential ROS production pathways, describing the potential role of greener synthesis.

This paper provides a first overview of the performance of global climate models participating in the Coupled Model Inter-Comparison Project phase 5 (CMIP5) in simulating the upper troposphere and lower stratosphere (UTLS) temperatures. Temperature from CMIP5 models is evaluated with high resolution global positioning system radio occultation (GPSRO) constellation observing system for meteorology, ionosphere, and climate (COSMIC) data during the period of July 2006–December 2013. Future projections of 17 CMIP5 models based on the representative concentration pathway (RCP) 8.5 scenarios are utilized to assess model performance and to identify the biases in the temperature in the UTLS region at eight different pressure levels. The evaluations were carried out vertically, regionally, and globally to understand the temperature uncertainties in CMIP5 models. It is found that the CMIP5 models successfully reproduce the general features of temperature structure in terms of vertical, annual, and inter-annual variation. The ensemble mean of CMIP5 models compares well with the COSMIC GPSRO data with a mean difference of ±1 K. In the tropical region, temperature biases vary from one model to another. The spatial difference between COSMIC and ensemble mean reveals that at 100 hPa, the models show a bias of about ±2 K. With increase in altitude the bias decreases and turns into a cold bias over the tropical and Antarctic regions. The future projections of the CMIP5 models were presented during 2006–2099 under the RCP 8.5 scenarios. Projections show a warming trend at 300, 200, and 100 hPa levels over a wide region of 60°N–45°S. The warming decreases rapidly and becomes cooling with increase in altitudes by the end of twenty-first century. Significant cooling is observed at 30, 20, and 10 hPa levels. At 300/10 hPa, the temperature trend increases/decreases by ~0.82/0.88 K/decade at the end of twenty-first century under RCP 8.5 scenarios.

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial–temporal analyses of rainfall have been studied by using 107 (1901–2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.

Surface Temperature (ST) over India has increased by ~0.055 K/decade during 1860–2005 and follows the global warming trend. Here, the natural and external forcings (e.g., natural and anthropogenic) responsible for ST variability are studied from Coupled Model Inter-comparison phase 5 (CMIP5) models during the 20th century and projections during the 21st century along with seasonal variability. Greenhouse Gases (GHG) and Land Use (LU) are the major factors that gave rise to warming during the 20th century. Anthropogenic Aerosols (AA) have slowed down the warming rate. The CMIP5 projection over India shows a sharp increase in ST under Representative Concentration Pathways (RCP) 8.5 where it reaches a maximum of 5 K by the end of the 21st century. Under RCP2.6 emission scenarios, ST increases up to the year 2050 and decreases afterwards. The seasonal variability of ST during the 21st century shows significant increase during summer. Analysis of rare heat and cold events for 2080–2099 relative to a base period of 1986–2006 under RCP8.5 scenarios reveals that both are likely to increase substantially. However, by controlling the regional AA and LU change in India, a reduction in further warming over India region might be achieved.

The present study deals with using long-term database for upper tropospheric water vapour (UTWV) variability studies over three tropical stations (Gadanki, Singapore and Truk), where different climatic conditions prevail. Over Gadanki (13.5°N, 79.2°E) strong seasonal variation in UTWV is revealed but not over Singapore (1.37°N, 103.98°E) and Truk (7.46°N, 151.85°E) except at 100 hPa. It is examined whether high resolution radiosonde measurements represent well the UTWV by comparing with different satellite based (Atmospheric Infrared Sounder (AIRS), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Limb Sounder (MLS)) water vapour measurements. Very good comparison in the nature of variations of UTWV is observed between radiosonde data and satellite data, except over Singapore particularly with AIRS and MLS data, on long-term basis. An attempt is also made to examine the source for UTWV. A close relationship is found between UTWV and deep convection over Gadanki indicating that the source for UTWV is convection particularly during the summer monsoon season.