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Heat wave is a hazardous weather-related extreme event that affects living beings. The 2015 summer heat wave affected many regions in India and caused the death of 2248 people across the country. An attempt has been made to quantify the intensity and duration of heat wave that resulted in high mortality across the country. Half hourly Physiologically Equivalent Temperature (PET), based on a complete heat budget of human body, was estimated using automatic weather station (AWS) data of four locations in Andhra Pradesh state, where the maximum number of deaths was reported. The heat wave characterization using PET revealed that extreme heat load conditions (PET >41) existed in all the four locations throughout May during 2012-2015, with varying intensity. The intensity and duration of heat waves characterized by "area under the curve" method showed good results for Srikakulam and Undi locations. Variations in PET during each half an hour were estimated. Such studies will help in fixing thresholds for defining heat waves, designing early warning systems, etc.

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Future climate change projections for India indicate distinct rise in temperature and increased variability in rainfall. This study aims to assess the impact of climate change on sorghum productivity in India in future climatic periods (2025, 2050 and 2075) using DSSAT-sorghum and suggest adaptation strategies to negate the negative impact of climate change on sorghum productivity in the future climates. Three CMIP-5 climate models (GFDL-ESM2M, MIROC5 and NorESM1-M) generated weather data for three future periods were used at various locations for kharif (Akola, Dharwad, Surat and Udaipur) and rabi (Bijapur, Dharwad, Rahuri and Solapur) seasons to simulate sorghum yields. Projected changes in day-night temperatures and rainfall during kharif and rabi growing seasons at these locations are diverse both in direction and magnitude. Increasing trend in rainfall is observed during both crop seasons towards the end of 21st century. Sorghum crop is likely to experience warmer temperature in the second half of the century and rise in minimum temperature is more explicit than maximum temperature at all the locations. Location specific management options can be adopted to mitigate the negative impacts of the change in climate in future projected scenarios, as they are found beneficial.

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Wheat is highly sensitive to climate change especially temperature changes experienced in the later phase of crop season. Hence, it is of immense importance to know how and to what extent climate change will affect wheat yields and to assess the adaptive strategies for mitigating possible negative consequences on wheat production. Wheat yield responses to three future climatic periods (2025, 2050 and 2075) were studied by driving DSSAT-Wheat (v4.5) model with daily weather from three CMIP-5 climate models’ (GFDL-ESM2M, MIROC5, and NorESM1-M) as the basic input at four sites (Ludhiana, Raipur, Akola and New Delhi) representing three major wheat growing zones of the country. Projected changes in growing season (November-March) day and night temperatures at four sites differed substantially both in direction and magnitude. Day temperatures are projected to rise conspicuously at Ludhiana, representing northwest parts of the country, and moderately over central parts of India (Akola and Raipur). Positive rainfall anomalies at Ludhiana (+76%) and negative anomalies at Raipur (-15%) are projected in future climates. With these anticipated changes, wheat is likely to experience warmer days (+1.1 °C) at Ludhiana and nights at Raipur (+2.8 °C) and more seasonal moisture availability at Ludhiana in future climates. Negative impacts of climatic change in these sites are found to be minimized by adapting one or a combination of management practices, which are site specific.

Crop weather calendars (CWC) serve as tools for taking crop management decisions. However, CWCs are not dynamic, as they were prepared by assuming normal sowing dates and fixed occurrence as well as duration of phenological stages of rainfed crops. Sowing dates fluctuate due to variability in monsoon onset and phenology varies according to crop duration and stresses encountered. Realizing the disadvantages of CWC for issuing accurate agromet advisories, a protocol of dynamic crop weather calendar (DCWC) was developed by All India Coordinated Research Project on Agrometeorology (AICRPAM). The DCWC intends to automatize agromet advisories using prevailing and forecasted weather. Different modules of DCWC, namely, Sowing & irrigation schedules, crop contingency plans, phenophase-wise crop advisory, and advisory for harvest were prepared using long-term data of ten crops at nine centers of AICRPAM in eight states in India. Modules for predicting sowing dates and phenology were validated for principal crops and varieties at selected locations. The predicted sowing dates of 10 crops pooled over nine centers showed close relationships with observed values (r 2 of .93). Predicted phenology showed better agreement with observed in all crops except cotton (Gossypium L.; at Parbhani) and pigeon pea [Cajanus cajan (L.) Millsp.] (at Bangalore). Predicted crop phenology using forecasted and realized weather by DCWC are close to each other, but number of irrigations differed, and it failed for accurate prediction in groundnut at Anantapur in drought year (2014). The DCWCs require further validation for making it operational to issue agromet advisories in all 732 districts of India.

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