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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.

This study investigates the impacts of summer monsoon activity on aerosols over the Indian region. We analyze the variability of aerosols during active and break monsoon phases, as well as strong and weak monsoon years, using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Our findings show a clear distinction in aerosol distribution between active and break phases. During active phases, the Aerosol Optical Depth (AOD) and aerosol extinction are lower across the Indian region, while break phases are associated with higher AOD and extinction. Furthermore, we observed a significant increase in AOD over Central India during strong monsoon years, compared to weak monsoon years. Utilizing the vertical feature mask (VFM) data from CALIPSO, we identified polluted dust and dusty marine aerosols as the dominant types during both active/break phases and strong/weak monsoon years. Notably, the contributions of these pollutants are significantly higher during break phases compared to during active phases. Our analysis also reveals a shift in the origin of these aerosol masses. During active phases, the majority originate from the Arabian Sea; in contrast, break phases are associated with a higher contribution from the African region. [ABSTRACT FROM AUTHOR]

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.

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.

© 2015 Elsevier Inc. Using GPS radio occultation refractivity data collected over the period of 2002-2013, we present a new method for identification of the intertropical convergence zone (ITCZ). The ITCZ is identified by estimating the maximum in the monthly meridional refractivity and specific humidity field by applying a Gaussian fit at each longitude. The interannual variability and climatology of the ITCZ is presented from 12. years of refractivity data. This new method captures all the general features of ITCZ extent and its variability. We also examine the effects of the ITCZ vertically during different seasons. The ITCZ is observed mostly at eastern Pacific in May month, and it is zonally distributed in the September and October months of each year. The zonal variability is large between lower and higher levels, particularly over the Indian monsoon and western Pacific. The latitudinal difference in the vertical extent between 850. hPa and higher levels is larger during the northern hemisphere (NH) summer than NH winter.

The characteristics of the quasi-2-day wave (QTDW) in the upper stratosphere and lower mesospheric (USLM) altitudes over the northern hemisphere (NH) and southern hemisphere (SH) have been studied by using Global Positioning Radio Occultation (GPSRO) Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) temperature data from November 2006 to December 2010. We studied the seasonal, latitudinal, and interannual variability of the westward-propagating 2-day wave coincident with zonal wave number 3 in both hemispheres in the altitude range of 20-60 km. The Lomb-Scargle periodogram (LSP) analysis indicates the dominance of the QTDW in the USLM in both the hemispheres. The observed amplitude of the wave is maximum during the winter season in middle and higher latitudes, with monthly mean amplitudes being as high as ∼8 K. These amplitudes are found frequently during the late fall and peak to a maximum in the NH winter season. In the SH, QTDW amplitudes are found in the early winter season and appear till the early fall months. The QTDW varies from 49 ± 3 to 48 ± 1 h in the NH and SH, respectively, with westward-propagating wave number 3. The amplitudes of the wave are large during winter in both the hemispheres, and, comparatively, the NH amplitudes are larger than those of the SH in higher latitudes.

In this study, global (50°S-50°N) distribution of water vapor is investigated using COSMIC GPS RO measurements. Detailed comparisons have been made between COSMIC and high resolution GPS radiosonde measurements across 13 tropical stations and model outputs (ERA-Interim, NCEP, and JRA-25 reanalyses data sets). In comparison with independent techniques like radiosonde (Väisälä), it is found that COSMIC GPS RO wet profiles are accurate up to 7-8. km (assuming radiosonde as standard technique). In general, comparisons with corresponding seasonal means of model outputs are qualitatively in good agreement, although they differ quantitatively especially over convective regions of South America, Africa, and Indonesia. In tropical latitudes, the COSMIC specific humidity values are higher than the model outputs. Among various model outputs, ERA-Interim data set show near realistic features to that observed by COSMIC GPS RO measurements. Large asymmetry in the specific humidity distribution is observed between northern and southern hemispheres. © 2011 Elsevier Ltd.

This article offers a perspective on photoacoustic tomography (PAT) under realistic scenarios. While PAT has gained much attention in preclinical and clinical research, most early works used image reconstruction techniques based on ideal assumptions, and thus these techniques may not be fully effective in real environments. In this work, we consider such non-ideal conditions as a limited view, limited bandwidth, lossy medium, or heterogeneous medium. More importantly, we use k-Wave simulation to numerically evaluate the effects of these limiting factors on various image reconstruction algorithms. Then, to enable more reliable PAT image reconstruction, we introduce recent techniques for mitigating each of the limiting conditions. We seek to emphasize the importance of working within these realistic limitations, and we encourage researchers to develop compensating solutions that advance PAT's translation to real clinical environments. [ABSTRACT FROM AUTHOR]