Abstract:We have used 1 ∘ × 1 ∘ resolution maximum temperature (T MAX ) data sets developed by India Meteorological Department (IMD) to examine the summer time warming over India during the period 2001-2014 in comparison with the period 1971-2000. The two study periods have been arrived at based on the drastic change of Moisture Index (I M ) trends over India between the two epochs. The T MAX variations over India are discussed with the corresponding changes in Potential Evapotranspiration (PET) data of the Climate Res… Show more
“…Gautam et al (2010) report that pre-monsoon aerosols over north India are primarily of absorbing nature leading to significant warming over northern India, especially over the western Himalayas. Purnadurga et al (2018) show that observed premonsoon maximum temperatures in northern India are significantly correlated with BC surface mass concentrations obtained from the MERRA reanalysis data.…”
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confidence: 58%
“…Purnadurga et al . (2018) show that observed pre‐monsoon maximum temperatures in northern India are significantly correlated with BC surface mass concentrations obtained from the MERRA reanalysis data.…”
Heat waves in India during the pre-monsoon months have significant impacts on human health, productivity and mortality. While greenhouse gas-induced global warming is believed to accentuate high temperature extremes, anthropogenic aerosols predominantly constituted by radiation-scattering sulfate are believed to cause an overall cooling in most world regions. However, the Indian region is marked by an abundance of absorbing aerosols, such as black carbon (BC) and dust. The goal of this work was to understand the association between aerosols, particularly those that are absorbing in nature, and hightemperature extremes in north-central India during the pre-monsoon season. We use 30-year simulations from a chemistry-coupled atmosphere-only general circulation model (GCM), ECHAM6-HAM2, forced with evolving aerosol emissions in an interactive aerosol module, along with observed evolving SSTs. A composite of high-temperature extremes in the model simulations, compared to climatology, shows large-scale conditions conducive to heat waves. Importantly, it reveals concurrent positive anomalies of BC and dust aerosol optical depths. Changes in near-surface properties include a reduction in single scattering albedo (implying greater absorption) and enhancement in shortwave heating rate, compared to climatological conditions. Alterations in surface energy balance include reduced latent heat flux, but increased sensible heat flux, consistent with enhanced temperatures. Thus, chemistry-coupled GCM simulations capture an association of absorbing aerosols with hightemperature extremes in north India, arising from radiative heating in the surface layer. K E Y W O R D S absorbing aerosols, chemistry-coupled AGCM, ECHAM6-HAM2, extreme temperature, Indian heat wave, radiative forcing 1 | INTRODUCTION Extreme temperature and heat wave events in India during the pre-monsoon season (March-June) are critical in terms of their impact on human health, environment, agriculture and economy. Recent trends in extreme temperature are reported to be positive over India
“…Gautam et al (2010) report that pre-monsoon aerosols over north India are primarily of absorbing nature leading to significant warming over northern India, especially over the western Himalayas. Purnadurga et al (2018) show that observed premonsoon maximum temperatures in northern India are significantly correlated with BC surface mass concentrations obtained from the MERRA reanalysis data.…”
mentioning
confidence: 58%
“…Purnadurga et al . (2018) show that observed pre‐monsoon maximum temperatures in northern India are significantly correlated with BC surface mass concentrations obtained from the MERRA reanalysis data.…”
Heat waves in India during the pre-monsoon months have significant impacts on human health, productivity and mortality. While greenhouse gas-induced global warming is believed to accentuate high temperature extremes, anthropogenic aerosols predominantly constituted by radiation-scattering sulfate are believed to cause an overall cooling in most world regions. However, the Indian region is marked by an abundance of absorbing aerosols, such as black carbon (BC) and dust. The goal of this work was to understand the association between aerosols, particularly those that are absorbing in nature, and hightemperature extremes in north-central India during the pre-monsoon season. We use 30-year simulations from a chemistry-coupled atmosphere-only general circulation model (GCM), ECHAM6-HAM2, forced with evolving aerosol emissions in an interactive aerosol module, along with observed evolving SSTs. A composite of high-temperature extremes in the model simulations, compared to climatology, shows large-scale conditions conducive to heat waves. Importantly, it reveals concurrent positive anomalies of BC and dust aerosol optical depths. Changes in near-surface properties include a reduction in single scattering albedo (implying greater absorption) and enhancement in shortwave heating rate, compared to climatological conditions. Alterations in surface energy balance include reduced latent heat flux, but increased sensible heat flux, consistent with enhanced temperatures. Thus, chemistry-coupled GCM simulations capture an association of absorbing aerosols with hightemperature extremes in north India, arising from radiative heating in the surface layer. K E Y W O R D S absorbing aerosols, chemistry-coupled AGCM, ECHAM6-HAM2, extreme temperature, Indian heat wave, radiative forcing 1 | INTRODUCTION Extreme temperature and heat wave events in India during the pre-monsoon season (March-June) are critical in terms of their impact on human health, environment, agriculture and economy. Recent trends in extreme temperature are reported to be positive over India
“…Compared to east coast, west coast is not much vulnerable but both emission scenarios show an increase in extreme caution days and project an increase in danger days under RCP 8.5 by end of the century. It is reported that the anomalous westerlies over the Indian land mass which reduce the land sea thermal contrast may cause the hot conditions over the eastern coastal regions of India 68 Significant rise in maximum temperature over the west coast 69 and east coast 70 caused the diurnal temperature range of 1–2 °C over the coastal regions for the period 1951 to 2010 which may contribute to the higher loads of heat stress over these areas. Figure 4 MMM of CMIP5 historical (1986–2005, purple) and future projections for three-epochs ( 2016–2035 (blue), 2046–2065 (green) and 2080–2099 (red) ) of number of heat stress days/year over east coast region under RCP 4.5 (top) & RCP 8.5 (bottom).…”
Section: Resultsmentioning
confidence: 99%
“…This subdued moist winds in combination with the already raised temperatures over land, together create the higher values of heat stress. The increase in the heat stress is also attributed to the increased anthropogenic forcing, increasing trends of temperature and decreasing trends in humidity during summer time 70 . Also, the air which is heated due to the absorbing aerosols in central and northeastern parts of India sinks in northwestern and southern Indian regions that cause more heating in the recent decades 73 .…”
Summertime heat stress future projections from multi-model mean of 18 CMIP5 models show unprecedented increasing levels in the RCP 4.5 and RCP 8.5 emission scenarios over India. The estimated heat stress is found to have more impact on the coastal areas of India having exposure to more frequent days of extreme caution to danger category along with the increased probability of occurrence. The explicit amount of change in temperature, increase in the duration and intensity of warm days along with the modulation in large scale circulation in future are seemingly connected to the increasing levels of heat stress over India. A decline of 30 to 40% in the work performance is projected over India by the end of the century due to the elevated heat stress levels which pose great challenges to the country policy makers to design the safety mechanisms and to protect people working under continuous extreme hot weather conditions.
“…The Moderate Resolution Imaging Spectroradiometer (MODIS) global ET data sets are available with 0.5 × 0.5 grid resolution and reported as widely accepted remote sensing products (Miralles et al, 2016;Wang et al, 2017). The ET data sets developed by CRU (on monthly basis from 1901 to 2014) and ECMWF (1979 onwards) are used in many studies (Purnadurga et al, 2017;Weiland et al, 2012;Uml et al, 2017;Srivastava et al, 2013;Romanou et al, 2010). These reanalysis data sets are developed based on the forecast models and data assimilation methods and proven as the best indicators of the weather and climate patterns (Saha et al, 2006;Krogh et al, 2015).…”
In this study, we have computed the evapotranspiration (ET) from the input variables of India Meteorological Department (IMD) for different stations in Monsoon Core Region (MCR) of India and Indian Peninsular Region (IPR) and compared with the ERA Interim (ERA‐I) and CRU ET data sets. While studying the discrepancies among the data sets, rainfall (source: IMD gridded), relative humidity (source: ERA Interim gridded), air temperature (source: IMD gridded) and soil moisture (source: TRMM/LPRM/TMI‐Model) were made use to illustrate the ET variations. When compared with IMD ET, our results show the CRU ET is underestimated but maintained the close pattern over MCR and IPR during South West (SW) monsoon (June–September) and North East (NE) monsoon (October–December) period, respectively. ERA‐I ET bounded to have mixed response over MCR and are higher than the IMD ET over IPR. Daily comparison of the IMD and ERA‐I ET data sets shows a large bias during the beginning of SW monsoon (June month) compared to other months. Site wise correlations show the substantial positive correlations between IMD and CRU ET over MCR than IPR. Overall analysis shows the monsoon features were better explained by the variations in IMD ET compared to CRU and ERA‐I ET data sets. The reported disparities among the data sets play an important role in the choice of selection for different applications such as water resource assessments, crop water requirements, monitoring of droughts etc.
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