Recent spatial aggregation tendency of rainfall extremes over India.
ABSTRACT: Significant increase in the frequency of occurrences of rainfall extremes has been reported over several parts of the world. These extreme events were defined at individual grids without considering their spatial extent. Here, using ground-based observations over India during boreal summer, we show that the average size of spatially collocated rainfall extremes has been significantly increasing since 1980. However, the frequency of occurrences of such collocated extreme events remains unchanged. Around 90% of the total number of large-sized events (area ≥ 70 × 103 km2) of our study period (1951 to 2015) have occurred after 1980. Some of the major floods in recent decades over India are attributed to these large events. These events have distinctive precursory planetary-scale conditions, unlike their smaller counterparts. As the underlying physical mechanisms of extremes rainfall events are size-dependent, their changing spatial extent needs to be considered to understand the observed trends correctly and obtain realistic future projections.
Project description:India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.
Project description:The changing characteristics of precipitation extremes under global warming have recently received tremendous attention, yet the mechanisms are still insufficiently understood. The present study attempts to understand these processes over India by separating the ‘dynamic’ and ‘thermodynamic’ components of precipitation extremes using a suite of observed and reanalysis datasets. The former is mainly due to changes in atmospheric motion, while the latter is driven mainly by the changes associated with atmospheric moisture content. Limited studies have attributed dynamic and thermodynamic contributions to precipitation extremes, and their primary focus has been on the horizontal atmospheric motion component of the water budget. Our study, on the other hand, implements the decomposition of vertical atmospheric motion, based on the framework proposed by Oueslati et al. (Sci Rep 9: 2859, 2019), which has often been overlooked, especially for India. With the focus on two major and recent extreme events in the Kerala and Uttarakhand regions of India, we show that the vertical atmospheric motion has a more significant contribution to the events than the horizontal atmospheric motion. Further, decomposition of the vertical atmospheric motion shows that the dynamic component overwhelms the thermodynamic component’s contribution to these extreme events, which is found to be negligible. Using a threshold method to define extreme rainfall, we further extended our work to all India, and the results were consistent with those of the two considered events. Finally, we evaluate the contributions from the recently made available CMIP6 climate models, and the results are interestingly in alignment with the observations. The outcomes of this study will play a critical role in the proper prediction of rainfall extremes, whose value to climate adaptation can hardly be overemphasised. <h4>Electronic supplementary material</h4> The online version of this article (10.1007/s00382-020-05410-3) contains supplementary material, which is available to authorized users.
Project description:Rainfall extremes are projected to increase under the warming climate. The Clausius-Clapeyron (C-C) relationship provides a physical basis to understand the sensitivity of rainfall extremes in response to warming, however, relationships between rainfall extremes and air temperature over tropical regions remain uncertain. Here, using station based observations and remotely sensed rainfall, we show that at a majority of urban locations, rainfall extremes show a negative scaling relationship against surface air temperature (SAT) in India. The negative relationship between rainfall extremes and SAT in India can be attributed to cooling (SAT) due to the monsoon season rain events in India, suggesting that SAT alone is not a good predictor of rainfall extremes in India. In contrast, a strong (higher than C-C rate) positive relationship between rainfall extremes and dew point (DPT) and tropospheric temperature (T850) is shown for most of the stations, which was previously unexplored. Subsequently, DPT and T850 were used as covariates for non-stationary daily design storms. Higher magnitude design storms were obtained under the assumption of a non-stationary climate. The contrasting relationship between rainfall extremes with SAT and DPT has implications for understanding the changes in rainfall extremes in India under the projected climate.
Project description:In this study, we provide a comprehensive analysis of trends in the extremes during the Indian summer monsoon (ISM) months (June to September) at different temporal and spatial scales. Our goal is to identify and quantify spatiotemporal patterns and trends that have emerged during the recent decades and may be associated with changing climatic conditions. Our analysis primarily relies on quantile regression that avoids making any subjective choices on spatial, temporal, or intensity pattern of extreme rainfall events. Our analysis divides the Indian monsoon region into climatic compartments that show different and partly opposing trends. These include strong trends towards intensified droughts in Northwest India, parts of Peninsular India, and Myanmar; in contrast, parts of Pakistan, Northwest Himalaya, and Central India show increased extreme daily rain intensity leading to higher flood vulnerability. Our analysis helps explain previously contradicting results of trends in average ISM rainfall.
Project description:Iran is experiencing unprecedented climate-related problems such as drying of lakes and rivers, dust storms, record-breaking temperatures, droughts, and floods. Here, we use the ensemble of five high-resolution climate models to project maximum and minimum temperatures and rainfall distribution, calculate occurrences of extreme temperatures (temperatures above and below the historical 95th and 5th percentiles, respectively), analyze compound of precipitation and temperature extremes, and determine flooding frequencies across the country. We found that compared to the period of 1980-2004, in the period of 2025-2049, Iran is likely to experience more extended periods of extreme maximum temperatures in the southern part of the country, more extended periods of dry (for ?120 days: precipitation <2?mm, Tmax ?30?°C) as well as wet (for ?3 days: total precipitation ?110?mm) conditions, and higher frequency of floods. Overall, the combination of these results projects a climate of extended dry periods interrupted by intermittent heavy rainfalls, which is a recipe for increasing the chances of floods. Without thoughtful adaptability measures, some parts of the country may face limited habitability in the future.
Project description:Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ?1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ?380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high-resolution climate models and improved understanding of the drivers of extreme rainfall.
Project description:The trends of extreme precipitation events during the Indian summer monsoon measured by two different indicators have been analyzed for the period of 1901–2020, covering the entire India in 9 regions segregated by a clustering analysis based on rainfall characteristics using the Indian Meteorological Department high-resolution gridded data. In seven regions with sufficiently high confidence in the precipitation data, 12 out of the 14 calculated trends are found to be statistically significantly increasing. The important climatological parameters correlated to such increasing trends have also been identified by performing for the first time a multivariate analysis using a nonlinear machine learning regression with 17 input variables. It is found that man-made long-term shifting of land-use and land-cover patterns, and most significantly the urbanization, play a crucial role in the prediction of the long-term trends of extreme precipitation events, particularly of the intensity of extremes. While in certain regions, thermodynamical, circulation, and convective instability parameters are also found to be key predicting factors, mostly of the frequency of the precipitation extremes. The findings of these correlations to the monsoonal precipitation extremes provides a foundation for further causal relation analyses using advanced models.
Project description:Global climate models predict more frequent periods of drought stress alternated by heavier, but fewer rainfall events in the future. Biodiversity studies have shown that such changed drought stress may be mitigated by plant species richness. Here, we investigate if grassland communities, differing in species richness, respond differently to climatic extremes within the growing season. In a 3-year outdoor mesocosm experiment, four grassland species in both monoculture and mixture were subjected to a rainfall distribution regime with two levels: periods of severe drought in the summer intermitted by extreme rainfall events versus regular rainfall over time. Both treatments received the same amount of water over the season. Extreme rainfall combined with drought periods resulted in a 15% decrease in aboveground biomass in the second and third year, compared to the regular rainfall regime. Root biomass was also reduced in the extreme rainfall treatment, particularly in the top soil layer (-?40%). All species developed higher water use efficiencies (less negative leaf ?13C) in extreme rainfall than in regular rainfall. These responses to the rainfall/drought treatment were independent of species richness, although the mixtures were on an average more productive in terms of biomass than the monocultures. Our experimental results suggest that mixtures are similarly able to buffer these within-season rainfall extremes than monocultures, which contrasts with findings in the studies on natural droughts. Our work demonstrates the importance of investigating the interactions between rainfall distribution and drought periods for understanding effects of climate change on plant community performance.
Project description:The impacts of concurrent droughts and heatwaves could be more serious compared to their individual occurrence. Meteorological drought condition is generally characterized by low rainfall, but impact of such an event is amplified with simultaneous occurrence of heatwaves. Positive feedback between these two extremes can worsen the rainfall deficit situation to serious soil moisture depletion due to enhanced evapotranspiration. In this study, the concurrence of meteorological droughts and heatwaves is investigated in India using Indian Meteorological Department (IMD) high resolution gridded data over a period of 60 years. Significant changes are observed in concurrent meteorological droughts and heatwaves defined at different percentile based thresholds and durations during the period 1981-2010 relative to the base period 1951-1980. There is substantial increase in the frequency of concurrent meteorological droughts and heatwaves across whole India. Statistically significant trends in the spatial extent of droughts are observed in Central Northeast India and West Central India; however, the spatial extent affected by concurrent droughts and heatwaves is increasing across whole India. Significant shifts are identified in the distribution of spatial extent of concurrent drought and heatwaves in India compared to the base period.
Project description:The attribution of changing intensity of rainfall extremes to global warming is a key challenge of climate research. From a thermodynamic perspective, via the Clausius-Clapeyron relationship, rainfall events are expected to become stronger due to the increased water-holding capacity of a warmer atmosphere. Here, we employ global, 1-hourly temperature and 3-hourly rainfall data to investigate the scaling between temperature and extreme rainfall. Although the Clausius-Clapeyron scaling of +7% rainfall intensity increase per degree warming roughly holds on a global average, we find very heterogeneous spatial patterns. Over tropical oceans, we reveal areas with consistently strong negative scaling (below -40%<sup>∘</sup>C<sup>-1</sup>). We show that the negative scaling is due to a robust linear correlation between pre-rainfall cooling of near-surface air temperature and extreme rainfall intensity. We explain this correlation by atmospheric and oceanic dynamics associated with cyclonic activity. Our results emphasize that thermodynamic arguments alone are not enough to attribute changing rainfall extremes to global warming. Circulation dynamics must also be thoroughly considered.