Historical and Projected Surface Temperature over India during the 20th and 21st century

Deciphering multi-temporal scale dynamics in the concentration, sources and processes of near surface ozone over different climatic regions of India

This study aims to investigate the factors influencing seasonal and long-term (2003-2021) changes in the near surface ozone (850 hpa) concentrations over different climatic sub-regions of India. Detailed comparison of daily (2019-2021) near surface ozone values of ERA-5 and CAAQMS (Continuous Ambient Air Quality Monitoring Stations) ground-based measurements revealed that ERA-5 is temporally in phase with CAAQMS measurements falling indifferent climatic sub-regions of India. ERA-5 near surface ozone shows statistically significant long-term (2003-2021) positive trends [2-4 percent per decade (ppd)] over most of the climatic sub-regions, over Indo-Gangetic Planes (IGPs), Southern and Central India trends are particularly strong. Trends were also estimated for each season separately, which were largely positive (2-6 ppd) over Central and Southern India in the Autumn and Winter seasons. Extensive climatological analysis reveals that the reversal of winds in the Indian monsoonal system plays a vital role in such trend patterns across the Indian subcontinent. South-westerly winds from June through September presumably bring ozone deficit air of marine origin, thus causing a dilution effect while the North-easterly winds during late Autumn and early Winters plausibly bring ozone-rich air from the stratospheric-tropospheric efflux dominated Himalayan region. It allows near surface ozone enhancement over Central and Southern India. Seasonal Principal component analysis (PCA) revealed that precursor gases (CH4 and NO2) and climatic variables especially specific humidity (SH) are the primary drivers of near surface ozone variability in the Winter season, while in Spring, climatic variables like boundary layer height (BLH), temperature (T) and SH have a significant role. Principal component regression (PCR) reveals a long-term increase in near surface ozone levels mostly dominated by precursor concentration over IGPs and Southern sub-regions. Whereas, BLH, T and SH significantly explain near surface ozone trends over North-eastern and Coastal India.

Temperature projections and heatwave attribution scenarios over India: A systematic review

The average global temperature is rising due to anthropogenic emissions. Hence, a systematic approach was used to examine the projected impacts of rising global temperatures on heatwaves in India and provide insights into mitigation and adaptation strategies. With over 24,000 deaths attributed to heatwaves from 1992 to 2015, there is an urgent need to understand India's vulnerabilities and prepare adaptive strategies under various emission scenarios.This situation is predicted to worsen as heatwaves become more frequent, intense, and long-lasting. Severe heatwaves can exacerbate chronic health conditions, vector-borne diseases, air pollution, droughts and other socio-economic pressures causing higher mortality and morbidity. Heatwaves with severe consequences have increased and are expected to become more frequent in Indian climatic and geographical conditions. As per the future projection studies, the temperature could rise ±1.2° C to ±3.5° C and will start reducing by the end of 2050. The study also provides data from the research that employs climatic models and statistical approaches for a more precise characterization of heat extremes and improved projections. Also, the study appraises the past, present and future heatwave trend projections. Most of these studies compute future projections using the Coupled Model Intercomparison Project (CMIP5) models and Representative Concentration Pathway (RCP). Limited systematic reports have been found using CMIP6, whereas the best-suited and widely used method was the RCP8.5. The study findings will aid in identifying the zones most susceptible to heatwave risk and provide actionable projections for policymakers to examine the existing evidence for developing proper planning and policy formulation, considering the future climate and temperature projections.

Analysis of heatwave characteristics under climate change over three highly populated cities of South India: a CMIP6-based assessment

Climate change is arguably the most alarming global concern of the twenty-first century, particularly due to the increased frequency of meteorological extremes, e.g., heatwaves, droughts, and floods. Heatwaves are considered a potential health risk and urge further study, robust preparedness, and policy framing. This study presents an analysis of heatwave characteristics for historical (1980-2014), near-future (2021-2055), and far-future (2056-2090) scenarios over three highly populated cities of South India, i.e., Bangalore, Chennai, and Hyderabad. Two different approaches, i.e., the India Meteorological Department (IMD) criterion and the percentile-based criterion, are considered for defining the threshold of a heatwave day. Nine general circulation models (GCMs) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) experiment are selected, evaluated after bias correction, and the best performer was utilized to obtain the temperature projections corresponding to two shared socioeconomic pathways (SSP 2-4.5 and 5-8.5) for the future periods. The results reveal a high frequency of heatwave days over the cities in recent years from both approaches, which may further exacerbate in the future, thereby putting a large population at risk. The number of heatwave days is much higher for SSP5-8.5 than that for SSP2-4.5, depicting the direct effects of anthropogenic activities on the frequency of heatwaves. The detailed analysis of heatwave projections will help develop equitable heat resilient mitigation and adaptation strategies for the future, thereby alleviating their pernicious impacts.

Coming to the Caribbean-acclimation of Rhesus macaques (Macaca mulatta) at Cayo Santiago

OBJECTIVES

To investigate whether the Cayo Santiago, Puerto Rico (Latitude: 18.1564°N; temperature range 19°C to 32°C) rhesus macaque population has acclimated to their tropical island conditions since arriving from Lucknow, India (Latitude: 26.8470°N; temperature range 8°C to 41°C) in 1938.

MATERIALS AND METHODS

Using the derived skeletal collection, measurements were taken of long bone lengths, diaphyseal circumference, and body weight using 635 (237 males and 398 females) skeletally mature individuals. Measurements sampled colony members born over a 51-year time span at Cayo Santiago, from 1951 to 2002.

RESULTS

Results demonstrated that body weights and diaphyseal circumferences significantly declined in both males and females. Long bone lengths relative to body weight and diaphyseal circumference also increased in females. Whereas body weight, long bone length and diaphyseal circumference declined at near parallel rates in males.

DISCUSSION

The population has acclimated to homogenous, tropical, conditions of the Caribbean island since their arrival over 80 years ago. Trends in both sexes aligned with Bergmann's rule, though females displayed a greater decline in body weight, as well as greater affinity with Allen's rule, than did males. Buffering effects related to male competition may be responsible for this discrepancy. Overall, the Cayo Santiago populations, as shown over a significant period (1951-2002) of their history, have acclimated to their island conditions by decreasing in size and altering body proportions.

Future transition in climate extremes over Western Ghats of India based on CMIP6 models

The effect of climate change on the tropical river catchments in the Western Ghats of India is studied using the Coupled Model Intercomparison Project-6 data (CMIP-6). Multi-model ensembles of rainfall and temperature are constructed using the Random Forest ensemble technique for bias-corrected GCMs in the near future (2014-2050) and far future (2051-2100) horizons. For the two catchments each in the southern, central, and northern Ghats, the trend in minimum and maximum temperatures, precipitation, and other indices are calculated. By 2100, dry sub-humid and humid catchments will see a higher increase in mean annual temperature than per-humid central catchments. In future decades, the warm days and nights increase by 45-50% and 40-70%, respectively, with twofold warming in the winter season. Under a climate change scenario, annual rainfall increases in Vamanapuram, Ulhas, and Purna, while Chaliyar, Netravati, and Aghanashini catchments experience a decrease in rainfall in the far future with an increase in pre-monsoon rainfall. The southern catchments are anticipated to have contrasting variations in the rainfall extremes; northern catchments face a substantial increase in very wet to extremely wet days and medium to heavy rainfall. In all catchments (excluding Vamanapuram), cumulative wet days increase with a decrease in cumulative dry days. After the mid-twenty-first century, humid to per-humid catchments encompass an increase in cool nights, whereas it disappears in dry sub-humid catchments of the Ghat. Interestingly, warming tendencies begin to slow down after 2050. This investigation can assist in comprehending the regional climate extremes in the Western Ghats to formulate better climate risk planning and adaptation strategies.

Hot weather hazard analysis over India

Heat waves are often termed as the silent killer and have become even more important as recent studies suggest that the heat wave have become second most devastating extreme weather events in terms of human deaths and losses. It is also been largely realised by scientific community that it is not just the high temperatures which are responsible for the gruesome effect of heat waves but several other meteorological parameters play a vital role in aggravating the impact and causing much more damages. In view of the above the attention of scientific community, weather forecasters as well as disaster managers has shifted to also take into account the different meteorological parameters like maximum and minimum temperatures, relative humidity, wind speed, duration/spell of heat waves and its intensity which are aggravating the impact of heat stress. In this background, this study is undertaken as an attempt to quantify the effect of different meteorological parameters on heat wave on different regions of India for different summer months (March, April, May and June). In this study the impact of individual meteorological parameter as well their cumulative effect is studied based on data of 30 years (1981-2010) for 300 stations. The effect of different meteorological parameters is identified for different months for different regions of the country. Also the cumulative scores are calculated for different regions considering different meteorological parameters, as a first initiative to perform heat hazard analysis and zonation over the entire country. This could serve as initial step for planning mitigation and adaptation strategies throughout the country. These scores as thresholds for different regions may be also useful for operational forecaster's for early impact based warning services as well as for the disaster managers, for taking effective and timely actions.

Heat Stress During Gametogenesis Irreversibly Damages Female Reproductive Organ in Rice

Heat stress during gametogenesis leads to spikelet sterility. To ascertain the role of female reproductive organ (pistil), two rice genotypes N22 and IR64 with contrasting heat stress responses were exposed to control (30 °C) and heat stress (38 °C and 40 °C) during megasporogenesis. Anatomical observations of ovule revealed greater disappearance of megaspore mother cell and nuclei at early stages, and during later stages mature embryo sac without female germ unit, improper positioning of nuclei, and shrunken embryo sac was observed in the sensitive IR64. Under heat stress, a decrease in sugar and starch, increase in H₂O₂ and malondialdehyde with lower antioxidant enzyme activities were recorded in pistils of both N22 and IR64. Lower accumulation of TCA cycle metabolites and amino acids were noticed in IR64 pistils under heat stress at gametogenesis, whereas N22 exhibited favorable metabolite profiles. At heading, however, N22 pistils had higher carbohydrate accumulation and better ROS homeostasis, suggesting higher recovery after heat stress exposure. In summary, the results indicate that heat stress during megasporogenesis leads to irreversible anatomical and physiological changes in pistil and alters metabolic signatures leading to increased spikelet sterility in rice. Mechanisms identified for enhanced heat tolerance in pistil can help in developing rice varieties that are better adapted to future hotter climate.

Evaluation of the Effect of Average Annual Temperatures in Slovakia between 1971 and 2020 on Stresses in Rigid Pavements

The scientific community in Central Europe often discusses the extent to which temperature changes over the last two decades have contributed to changing the stresses induced in structures. In the field of road and environmental engineering, this question is especially pertinent for pavements. The pavement structure must first be defined methodologically by identifying and defining the types of parameters that change with time. Additionally, it is important to identify the areas of Central Europe that are most affected by climate change. The most important parameters must be described statistically for these areas. Slovakia is one of the countries that may be able to contribute to the solution of this issue due to its location in the middle of Europe. This paper provides a statistical analysis for the period from 1971 to 2020 in Slovakia. A concrete pavement, which is the most commonly used type of pavement, must be used as an example to numerical assess the situation. The conclusions and discussion in this scientific field are directed towards the evaluation of the measurement results in the context of the designed pavement composition and the calculations using the different methods specified in the standards.

Anthropogenic influence on the changing risk of heat waves over India

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.

Observed Climatology and Trend in Relative Humidity, CAPE, and CIN over India

Water vapor is the most dominant greenhouse gas in the atmosphere and plays a critical role in Earth’s energy budget and hydrological cycle. This study aims to characterize the long-term seasonal variation of relative humidity (RH), convective available potential energy (CAPE), and convective inhibition (CIN) from surface and radiosonde observations from 1980–2020. The results show that during the monsoon season, very high RH values are depicted while low values are depicted during the pre-monsoon season. West Coast stations represent large RH values compared to other stations throughout the year. Irrespective of the season, the coastal regions show higher RH values during monsoon season. Regardless of season, the coastal regions have higher RH values during the monsoon season. During the pre-monsoon season, the coastal region has high RH values, whereas other regions have high RH values during the monsoon season. The rate of increase in RH in North-West India is 5.4%, followed by the West Coast, Central, and Southern parts of India. An increase in water vapor leads to raised temperature, which alters the instability conditions. In terms of seasonal variation, our findings show that CAPE follows a similar RH pattern. CAPE increases sharply in Central India and the West Coast region, while it declines in South India. Opposite features are observed in CIN with respect to CAPE variability over India. The results of the study provide additional evidence with respect to the role of RH as an influencing factor for an increase in CAPE over India.

Population exposure to compound extreme events in India under different emission and population scenarios

It is well understood that India is largely exposed to different climate extremes including floods, droughts, heat waves, among others. However, the exposure of co-occurrence of these events is still unknown. The present analysis, first study of its kind, provides the projected changeability of five different compound extremes under three different emission scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5). These changes are combined with population projection under SSP2, SSP3, and SSP5 scenarios to examine the total exposure in terms of number of persons exposed during 2021-2060 (T1) and 2061-2100 (T2). Here, the outputs from thirteen GCMs are used under CMIP6 experiment. The findings from the study show that all the compound extremes are expected to increase in future under all the emission scenarios being greater in case of SSP5-8.5. The population exposure is highest (2.51- to 4.96-fold as compared to historical) under SSP3-7.0 scenario (2021-2100 i.e., T1 and T2) in case of coincident heat waves and droughts compound extreme. The total exposure in Central Northeast India is projected to be the highest while Hilly Regions are likely to have the lowest exposure in future. The increase in the exposure is mainly contributed from climate change, population growth and their interaction depending on different kinds of compound extremes. The findings would help in devising sustainable policy strategies to climate mitigation and adaptation.

Role of economic growth and innovative technologies in the outlook of energy and environmental efficiency: a way forward for developing Asian economies

Energy consumption is widely regarded as the primary driver of economic development and environmental degradation. The current study examines how energy use is related to technological innovation, human resources, energy pricing, economic development, and trade openness. For this context, the data set of OECD economies' indicators as mentioned above has been compiled for the period 1991-2019. Three estimators were used in this study from the family of autoregressive distributed lag (ARDL): the mean group (MG), the dynamic fixed effect (DFE), and the pooled mean group (PMG). According to empirical research, technical advances, human resources, and energy pricing all have a negative impact on OECD countries' long-run energy consumption. In the short term, however, these variables have a negligible or inverse effect on energy consumption. On the other hand, economic growth and trade openness in OECD economies all contribute positively to energy demand in the short and long run. Based on the empirical findings, this study recommends a policy structure for emerging economies.

Association between climate and infectious diseases among children in Varanasi city, India: A prospective cohort study

The effects of climate on infectious diseases could influence the health impacts, particularly in children in countries with the unfair socioeconomic conditions. In a prospective cohort of 461 children under 16-years-of-age in Varanasi city, India, the association of maximum-temperature (Tmax), relative humidity (RH), absolute humidity (AH), rainfall (RF), wind-speed (WS), and solar radiation (SLR) with prevalent infectious diseases (Diarrhea, Common cold and flu, Pneumonia, Skin-disease and Malaria, and Dengue) was examined using binomial-regression, adjusting for confounders and effect modifiers (socioeconomic-status; SES and child anthropometry), from January 2017 to January 2020. Attributable-fraction (AFx) was calculated due to each climate variable for each infectious disease. The result showed that each unit (1 °C) rise in Tmax was associated with an increase in diarrhea and skin-disease cases by 3.97% (95% CI: 2.92, 5.02) and 3.94% (95% CI: 1.67, 6.22), respectively, whereas, a unit decline in Tmax was associated with an increase in cold and flu cases by 3.87% (95% CI: 2.97, 4.76). Rise in humidity (RH) was associated with increase in cases of cold and flu by 0.73% (95% CI: 0.38, 1.08) and malaria (AH) by 7.19% (95% CI: 1.51, 12.87) while each unit (1 g/m³) decrease in humidity (AH) observed increase in pneumonia cases by 3.02% (95% CI: 0.75, 5.3). WS was positively associated with diarrhea (14.16%; 95% CI: 6.52, 21.80) and negatively with dengue (17.40%; 12.32, 22.48) cases for each unit change (kmph). RF showed marginal association while SLR showed no association at all. The combined AFx due to climatic factors ranged from 9 to 18%. SES and anthropometric parameters modified the climate-morbidity association in children with a high proportion of children found suffering from stunting, wasting, and underweight conditions. Findings from this study draw the attention of government and policymakers to prioritize effective measures for child health as the present association may increase disease burden in the future under climate-change scenarios in already malnourished paediatric population through multiple pathways.

Extreme Temperatures and Firm-Level Stock Returns

By linking stock returns with weather conditions from 2007 to 2019 in China, we study how firm-level stock returns react to extreme temperatures. Based on a multivariate ordinary least squares regression model with fixed effects, empirical results show that firm-level stock returns decrease with exposure to extreme temperatures. We further explore the heterogeneity in the temperature-return relation to enrich our understanding of the economic mechanism behind it. The impact of extreme temperatures on abnormal stock returns is more pronounced in smaller, younger, more volatile, less profitable firms and firms with more intangible assets. The results indicate that the investor mood likely plays a role in the extreme temperature effect. The impact of extreme temperatures holds after addressing a series of concerns. Overall, our paper provides additional firm-level evidence on the environment-induced mood effect in the stock market.

Changing patterns in aerosol vertical distribution over South and East Asia

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.

Dengue situation in India: Suitability and transmission potential model for present and projected climate change scenarios

Dengue fever is mosquito borne viral disease caused by dengue virus and transmitted by Aedes mosquitoes. In recent years the dengue has spread rapidly to several regions and it becomes a major public health menace globally. Dengue transmission is strongly influenced by environmental factors such as temperature and rainfall. In the present study, a climate driven dengue model was developed and predicted areas vulnerable for dengue transmission under the present and future climate change scenarios in India. The study also projected the dengue distribution risk map using representative concentration pathways (RCP4.5 and RCP8.5) in India in 2018-2030 (forthcoming period), 2031-2050 (intermediate period) and 2051-2080 (long period). The dengue cases assessed in India from 1998 to 2018 and found that the dengue transmission is gradually increasing year over year. The temperature data from 1980 to 2017 shows that, the mean temperatures are raising in the Southern region of India. During 2000-2017 periods the dengue transmission is steadily increasing across the India in compare with 1980-1999 periods. The dengue distribution risk is predicted and it is revealed that the coastal states have yearlong transmission possibility, but the high transmission potential is observed throughout the monsoon period. Due to the climate change, the expansion two more months of dengue transmission risk occurs in many regions of India. Both RCP4.5 and RCP8.5 scenarios revealed that dengue outbreaks might occur at larger volume in Southern, Eastern, and Central regions of India. Furthermore a sensitivity analysis was performed to explore the impact of climate change on dengue transmission. These results helps to suggest appropriate control measures should be implemented to limit the spread in future warmer climates. Besides these, a proper plan is required to mitigate greenhouse gas emissions to reduce the epidemic potential of dengue in India.

Consistency in Vulnerability Assessments of Wheat to Climate Change—A District-Level Analysis in India

In India, a reduction in wheat crop yield would lead to a widespread impact on food security. In particular, the most vulnerable people are severely exposed to food insecurity. This study estimates the climate change vulnerability of wheat crops with respect to heterogeneities in time, space, and weighting methods. The study uses the Intergovernmental Panel on Climate Change (IPCC) framework of vulnerability while using composite indices of 27 indicators to explain exposure, sensitivity, and adaptive capacity. We used climate projections under current (1975–2005) conditions and two future (2021–2050) Representation Concentration Pathways (RCPs), 4.5 and 8.5, to estimate exposure to climatic risks. Consistency across three weighting methods (Analytical Hierarchy Process (AHP), Principal Component Analysis (PCA), and Equal Weights (EWs)) was evaluated. Results of the vulnerability profile suggest high vulnerability of the wheat crop in northern and central India. In particular, the districts Unnao, Sirsa, Hardoi, and Bathinda show high vulnerability and high consistency across current and future climate scenarios. In total, 84% of the districts show more than 75% consistency in the current climate, and 83% and 68% of the districts show more than 75% consistency for RCP 4.5 and RCP 8.5 climate scenario for the three weighting methods, respectively. By using different weighting methods, it was possible to quantify “method uncertainty” in vulnerability assessment and enhance robustness in identifying most vulnerable regions. Finally, we emphasize the importance of communicating uncertainties, both in data and methods in vulnerability research, to effectively guide adaptation planning. The results of this study would serve as the basis for designing climate impacts adjusted adaptation measures for policy interventions.

Rice yield formation under high day and night temperatures-A prerequisite to ensure future food security

Increasing temperatures resulting from climate change dramatically impact rice crop production in Asia. Depending on the specific stage of rice development, heat stress reduces tiller/panicle number, decreases grain number per plant and lower grain weight, thus negatively impacting yield formation. Hence improving rice crop tolerance to heat stress in terms of sustaining yield stability under high day temperature (HDT), high night temperature (HNT), or combined high day and night temperature (HDNT) will bolster future food security. In this review article, we highlight the phenological alterations caused by heat and the underlying molecular-physiological and genetic mechanisms operating under different types of heat conditions (HDT, HNT, and HDNT) to understand heat tolerance. Based on our synthesis of HDT, HNT, and HDNT effects on rice yield components, we outline future breeding strategies to contribute to sustained food security under climate change.

A DEA Approach for Assessing the Energy, Environmental and Economic Performance of Top 20 Industrial Countries

Due to growing concerns of global warming, reducing carbon emissions has become one of the major tasks for developing countries to meet the national demand for energy policies. The objective of this study is to measure the energy consumption, carbon emission and economic-environmental efficiency in terms of the environmental performance of the top 20 industrial countries by employing a data envelopment analysis (DEA) model from 2013 to 2017. This study used the trilemma of energy efficiency, CO2 emission efficiency, and environmental efficiency, and also the contribution included the quantitative analysis of 20 industrial countries The results show that the energy efficiency of Australia, China, Japan, Saudi Arabia, and Poland are the best performing countries, whereas Mexico, Indonesia, Russia, and Brazil are identified as least efficient among all 20 countries. Furthermore, Russia’s energy intensity has a maximum score while Poland has a minimum score. Additionally, in the case of CO2 emission efficiency, Brazil, France, and Saudi Arabia are considered as efficient while nine country’s scores were less than 0.5. The results show that most countries exhibit higher performance in economic efficiency than environmental efficiency. The study provides valuable information for energy policy-makers.

Vulnerability of Indian wheat against rising temperature and aerosols

Potential impacts of change in climate on Indian agriculture may be significantly adverse, if not disastrous. There are projections of potential loss in wheat yield due to the rise in daily minimum (Tmin) and maximum (Tmax) temperature, but only few researchers have considered the extent of such loss on a spatial scale. We therefore, systematically studied the effect of change in Tmax, Tmean (daily average temperature) and Tmin, solar radiation (Srad) and precipitation (RAIN) during wheat growing seasons (from 1986 to 2015) on wheat crop yield over five wheat growing zones across India, taking into account the effect modification by aerosol loading (in terms of aerosol optical depth, 2001-2015). We note that for the entire India, 1 °C rise in Tmean resulted a 7% decrease in wheat yield which varied disproportionately across the crop growing zones by a range of -9% (peninsular zone, PZ) to 4% (northern hills zone, NHZ). The effect of Tmean on wheat yield was identical to the marginal effect of Tmax and Tmin, while 1% increase in Srad enhance wheat yield by 4% for all India with small geographical variations (2-5%), except for the northern hill region (-4%). Rise in 1 °C Tmean exclusively during grain filling duration was noted positive for all the wheat growing regions (0-2%) except over central plain zone (-3%). When estimates of weather variables on wheat yield was combined with the estimated impact of aerosols on weather, the most significant impact was noted over the NHZ (-23%), which otherwise varied from -7% to -4%. Overall, the study brings out the conclusive evidence of negative impact of rising temperature on wheat yield across India, which we found spatially inconsistent and highly uncertain when integrated with the compounding effect of aerosols loading.

Changes in the distribution of hydro-climatic extremes in a non-stationary framework

Hydro-climatic extremes are influenced by climate change and climate variability associated to large-scale oscillations. Non-stationary frequency models integrate trends and climate variability by introducing covariates in the distribution parameters. These models often assume that the distribution function and shape of the distribution do not change. However, these assumptions are rarely verified in practice. We propose here an approach based on L-moment ratio diagrams to analyze changes in the distribution function and shape parameter of hydro-climate extremes. We found that important changes occur in the distribution of annual maximum streamflow and extreme temperatures. Eventual relations between the shapes of the distributions of extremes and climate indices are also identified. We provide an example of a non-stationary frequency model applied to flood flows. Results show that a model with a shape parameter dependent on climate indices in combination with a scale parameter dependent on time improves significantly the goodness-of-fit.

Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis

This study investigates the spatial and temporal variability of the soil moisture in India using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) gridded datasets from June 2002 to April 2017. Significant relationships between soil moisture and different land surface–atmosphere fields (Precipitation, surface air temperature, total cloud cover, and total water storage) were studied, using maximum covariance analysis (MCA) to extract dominant interactions that maximize the covariance between two fields. The first leading mode of MCA explained 56%, 87%, 81%, and 79% of the squared covariance function (SCF) between soil moisture with precipitation (PR), surface air temperature (TEM), total cloud count (TCC), and total water storage (TWS), respectively, with correlation coefficients of 0.65, −0.72, 0.71, and 0.62. Furthermore, the covariance analysis of total water storage showed contrasting patterns with soil moisture, especially over northwest, northeast, and west coast regions. In addition, the spatial distribution of seasonal and annual trends of soil moisture in India was estimated using a robust regression technique for the very first time. For most regions in India, significant positive trends were noticed in all seasons. Meanwhile, a small negative trend was observed over southern India. The monthly mean value of AMSR soil moisture trend revealed a significant positive trend, at about 0.0158 cm3/cm3 per decade during the period ranging from 2002 to 2017.

A sixfold rise in concurrent day and night-time heatwaves in India under 2 °C warming

Heatwaves with severe impacts have increased and projected to become more frequent under warming climate in India. Concurrent day and nighttime heatwaves can exacerbate human discomfort causing high morbidity and mortality; however, their changes in the observed and projected climate remain unrecognized. Here using observations and model simulations from climate of 20^th century plus (C20C+) detection and attribution (D&A) and coupled model intercomparison project 5 (CMIP5) projects, we show that 1 and 3-day concurrent hot day and hot night (CHDHN) events have significantly increased during the observed climate in India. Our results show that the anthropogenic emissions contribute considerably to the increase of 1 and 3-day CHDHN events in India. The frequency of 3-day CHDHN events is projected to increase 12-fold of the current level by the end of 21^st century and 4-fold by the mid 21^st century under the high emission pathway of RCP 8.5. The increase in 3-day CHDHN events can be limited to only 2-fold by the end of 21^st century under low emission scenario of RCP 2.6. One and 3-day CHDHN events are projected to increase by 4, 6, and 8 folds of the current level in India under the 1.5, 2, and 3 °C warming worlds, respectively. Restricting global mean temperature below 1.5° from the pre-industrial level can substantially reduce the risk of 1 and 3-day CHDHN events and associated implications in India.

Nonstationary Temperature-Duration-Frequency curves

Persistent extreme heat events are of growing concern in a climate change context. An increase in the intensity, frequency and duration of heat waves is observed in several regions. Temperature extremes are also influenced by global-scale modes of climate variability. Temperature-Duration-Frequency (TDF) curves, which relate the intensity of heat events of different durations to their frequencies, can be useful tools for the analysis of heat extremes. To account for climate external forcings, we develop a nonstationary approach to the TDF curves by introducing indices that account for the temporal trend and teleconnections. Nonstationary TDF modeling can find applications in adaptive management in the fields of health care, public safety and energy production. We present a one-step method, based on the maximization of the composite likelihood of observed heat extremes, to build the nonstationary TDF curves. We show the importance of integrating the information concerning climate change and climate oscillations. In an application to the province of Quebec, Canada, the influence of Atlantic Multidecadal Oscillations (AMO) on heat events is shown to be more important than the temporal trend.

Human influence on sub-regional surface air temperature change over India

Human activities have been implicated in the observed increase in Global Mean Surface Temperature. Over regional scales where climatic changes determine societal impacts and drive adaptation related decisions, detection and attribution (D&A) of climate change can be challenging due to the greater contribution of internal variability, greater uncertainty in regionally important forcings, greater errors in climate models, and larger observational uncertainty in many regions of the world. We examine the causes of annual and seasonal surface air temperature (TAS) changes over sub-regions (based on a demarcation of homogeneous temperature zones) of India using two observational datasets together with results from a multimodel archive of forced and unforced simulations. Our D&A analysis examines sensitivity of the results to a variety of optimal fingerprint methods and temporal-averaging choices. We can robustly attribute TAS changes over India between 1956-2005 to anthropogenic forcing mostly by greenhouse gases and partially offset by other anthropogenic forcings including aerosols and land use land cover change.