Probabilities of excess and deficient southwest monsoon rainfall over different meteorological sub-divisions of India

Temporal distribution of southwest monsoon (June - September) rainfall is very useful for the country's agriculture and food grain production. It contributes more than 75 of India's annual rainfall. In view of this, an attempt has been made here to understand the performance of the monthly rainfall for June, July, August and September when the seasonal rainfall is reported as excess, deficient or normal. To know the dependence of seasonal rainfall on monthly rainfall, the probabilities of occurrence of excess, deficient and normal monsoon when June, July, August and also June + July and August + September rainfall is reported to be excess or deficient, are worked out using the long homogenous series of 124 years (18711994) data of monthly and seasonal rainfall of 29 meteorological sub-divisions of the plain regions of India. In excess monsoon years, the average percentage contribution of each monsoon month to the long term mean (1871-1994) seasonal rainfall (June - September) is more than that of the normal while in the deficient years it is less than normal. This is noticed in all 29 meteorological sub-divisions. From the probability analysis, it is seen that there is a rare possibility of occurrence of seasonal rainfall to be excess/deficient when the monthly rainfall of any month is deficient/excess

On the recent changes in surface temperature trends over India

Marked differences from global trends in terms of diurnal asymmetry of temperature trends were reported earlier for India, indicating that the warming over India was solely contributed by maximum temperatures. We report substantial recent changes in the nature of trends, using updated data sets up to 2003, with special focus on the last three decades. While all-India mean annual temperature has shown significant warming trend of 0.05°C/10yr during the period 1901-2003, the recent period 1971-2003 has seen a relatively accelerated warming of 0.22°C/10yr, which is largely due to unprecedented warming during the last decade. Further, in a major shift, the recent period is marked by rising temperatures during the monsoon season, resulting in a weakened seasonal asymmetry of temperature trends reported earlier. The recent accelerated warming over India is manifest equally in daytime and nighttime temperatures

Intra-seasonal, inter-annual and decadal scale variability in summer monsoon rainfall over India

Using daily rainfall data for the 30-year period of 1960-1989 and following an objective criterion, the pre-active, active and post-active phases of the summer monsoon (June-September) rainfall are clearly delineated for all-India and homogeneous regions of India. It is seen that on average, the monsoon is active for 103 days over northeast (NE-India) India, for 75-78 days over central-northeast (CNE-India) India and so on for all the regions. Average daily normal rainfall (ADNRF) is at a maximum of 14.7 mm over NE-India and at a minimum of 4.6 mm over NW-India. To investigate possible periodic oscillations in daily rainfall, the daily normal rainfall (DNRF) of all the regions is subjected to power spectrum analysis. This analysis reveals that DNRF exhibits periodicities of 5, 8-12 and 20 days over NE-India, about 5 and 40 days over WC-India, 8-12 and 40 days over NW-India and 8-10 and 40 days over PEN-India. Inter-annual and decadal scale variability of the summer monsoon rainfall over homogeneous regions is studied using the summer monsoon rainfall for the period of 1871-1990. It is discovered that summer monsoon rainfall of WC-India and NW-India is dominated by a quasi-biennial oscillation (QBO), whereas summer monsoon rainfall of NE-India and PEN-India is dominated by ENSO-type periodicities. Epochs of increasing and decreasing rainfall are also observed in the summer monsoon rainfall over homogeneous regions of India

Recent trends in pre-monsoon daily temperature extremes over India

Extreme climate and weather events are increasingly being recognized as key aspects of climate change. Pre-monsoon season (March-May) is the hottest part of the year over almost the entire South Asian region, in which hot weather extremes including heat waves are recurring natural hazards having serious societal impacts, particularly on human health. In the present paper, recent trends in extreme temperature events for the pre-monsoon season have been studied using daily data on maximum and minimum temperatures over a well-distributed network of 121 stations for the period 1970-2005. For this purpose, time series of extreme temperature events have been constructed for India as a whole and seven homogeneous regions, viz., Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP). In general, the frequency of occurrence of hot days and hot nights showed widespread increasing trend, while that of cold days and cold nights has shown widespread decreasing trend. The frequency of the occurrence of hot days is found to have significantly increased over EC, WC and IP, while that of cold days showed significant decreasing trend over WH and WC. The three regions EC, WC and NW showed significant increasing trend in the frequency of hot nights. For India as whole, the frequency of hot days and nights showed increasing trend while cold days and nights showed decreasing trends. Day-to-day fluctuations of pre-monsoon daily maximum and minimum temperatures have also been studied for the above regions. The results show that there is no significant change in day-to-day magnitude of fluctuations of pre-monsoon maximum and minimum temperatures. However, the results generally indicate that the daily maximum and minimum temperatures are becoming less variable within the season

Long term temperature trends at major, medium, small cities and hill stations in India during the period 1901-2013

Industrialization and urbanization are the most dominant causal factors for long-term changes in surface air temperatures. To examine this fact, the long term changes in the surface-air temperatures have been evaluated by the linear trend for the different periods, i.e. 1901-2013, 1901-1970 and recent period 1971-2013 as rapid industrialization was observed during the recent four decades. In the present study, seasonal and annual mean, maximum and minimum temperature data of 36 stations for the period 1901-2013 have been used. These stations are classified into 4 groups, namely major, medium, small cities and hill stations. During the period 1901-1970, less than 50% stations from each group showed a significant increasing trend in annual mean temperature, whereas in the recent period 1971-2013, more than 80% stations from all the groups except small city group showed a significant increasing trend. The minimum temperature increased faster than that of the maximum temperature over major and medium cities, while maximum temperature increased faster than the minimum temperature over the small cities and hill stations. The annual mean temperature of all the coastal stations showed a significant increasing trend and positive correlation with Precipitable Water Vapour (PWV). The effect of PWV is more pronounced on minimum temperature than that of the maximum

Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing

Remote sensing-derived wheat crop yield-climate models were developed to highlight the impact of temperature variation during thermo-sensitive periods (anthesis and grain-filling; TSP) of wheat crop development. Specific questions addressed are: can the impact of temperature variation occurring during the TSP on wheat crop yield be detected using remote sensing data and what is the impact? Do crop critical temperature thresholds during TSP exist in real world cropping landscapes? These questions are tested in one of the world's major wheat breadbaskets of Punjab and Haryana, north-west India. Warming average minimum temperatures during the TSP had a greater negative impact on wheat crop yield than warming maximum temperatures. Warming minimum and maximum temperatures during the TSP explain a greater amount of variation in wheat crop yield than average growing season temperature. In complex real world cereal croplands there was a variable yield response to critical temperature threshold exceedance, specifically a more pronounced negative impact on wheat yield with increased warming events above 35 °C. The negative impact of warming increases with a later start-of-season suggesting earlier sowing can reduce wheat crop exposure harmful temperatures. However, even earlier sown wheat experienced temperature-induced yield losses, which, when viewed in the context of projected warming up to 2100 indicates adaptive responses should focus on increasing wheat tolerance to heat. This study shows it is possible to capture the impacts of temperature variation during the TSP on wheat crop yield in real world cropping landscapes using remote sensing data; this has important implications for monitoring the impact of climate change, variation and heat extremes on wheat croplands

Projection of Indian summer monsoon climate in 2041–2060 by multiregional and global climate models

Using the results from three global climate models (GCMs) and seven regional climate models (RCMs), summer monsoon climate changes during 2041–2060 over Indian Peninsula are projected based on the Intergovernmental Panel on Climate Change A1B emission scenario. For the control climate of 1981–2000, most nested RCMs can improve the temporal-spatial distributions of temperature and precipitation over Indian Peninsula compared to the driving GCM of European Centre/Hamburg Fifth Generation (ECHAM5). Most nested RCMs produce advanced monsoon onset for control climate, which is similar to the result of driving GCM of ECHAM5. For future climate widespread summer warming is projected over Indian Peninsula by all climate models, with the Multi-RCMs ensemble mean (MME) temperature increasing of 1°C to 2.5°C and the maximum warming center located in northern Indian Peninsula. The disagreement in precipitation changes projected by RCMs indicates that the surface climate change on regional scale is not only dominated by the large-scale forcing which is provided by driving GCM but also sensitive to RCM\u27 internal physics. Overall, wetter condition is shown in MME with significant increase of monsoon rainfall over southern India, with intermodel spread ranging from −8.9% to 14.8%. Driven by same GCM, most RCMs project advanced monsoon onset while delayed onset is found in two Regional Climate Model (RegCM3) projections, indicating uncertainty can be expected in the Indian Summer Monsoon onset. All climate models except Conformal-Cubic Atmospheric Model with equal resolution (referred as CCAMP) and two RegCM3 models project stronger summer monsoon during 2041–2060