Extreme Daily Rainfall Research Articles

Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco

Abstract Here, we investigate the precipitation regionalization and the spatial variability of rainfall extremes, using a 47-year long station-based dataset from western central Morocco, a region with marked topographic and climatic variations. The principal component analysis revealed three homogeneous rainfall regimes, consistent with topographic features: the coastal area receives heavy rainfall during autumns and winters, whereas the inner lowlands, in the middle of the study area, are characterized by an overall rainfall deficit regardless of their high water demand for irrigation, and the highest rainfall amounts take place in the mid-mountain area, including the summer seasons. Furthermore, the frequency analysis of daily rainfall extremes revealed high ten-year precipitation amounts in the coastal region (about 88 mm) and exceptional daily precipitation for longer return periods (182 mm for a 100-year period). Using artificial neural networks, the spatialization of these extreme precipitation events shows that they increase from the plain to the Atlas mountains and especially from the plain to the Atlantic Ocean. The spatial distribution of extreme precipitation highlights the areas where stormwater management needs to be improved, such as efficient stormwater drainage, and where floods are more likely to take place in the future.

Analysis of Temperature and Precipitation Trends Observed at Some Selected Districts of Punjab, Pakistan

Present study examines the trends of extreme daily temperature and rainfall indices in some selectedmeteorological stations/districts of the Punjab. Due to paucity of data only six weather stations were selected from thewhole Punjab, having data of 33 years for temperature and precipitation on daily basis. A set of 14 indices(recommended by climate ET) were used to calculate the trends over a period of 32 years (1985–2017) by usingRClimDex (1.0) software package. These results showed that the number of tropical nights (TR20) and warm nights(TN90p) has been increasing in selected weather stations/districts and number for cool nights (TN10p) has been falling.Other temperature related indices trends such as, summer days, warms days, warm spell duration indicator (WSDI) andcool spell duration (CSDI) shows a mix pattern. The precipitation indices like SDII, RX1day, R10mm and PRCPTOTshowed an increasing trend in some selected stations. Most of the trends were not significant at level of 0.05 % whilemaximum day temperature increase has been observed at five out of six selected stations. Similarly, an average increasein precipitation in the vicinity of 3 mm per decade has been noted. The annual total rainfall and number of heavyrainfall days has also increased by 18 mm and 8.4 mm respectively during each decade. The analysis identified andhighlighted a slight change which was not temporally and spatially rational. However, there is need to more andadequate yearly data of different weather stations across the Punjab to identify the ongoing apparent and impeccablechanges in climate of the Punjab province.

Analysis of Temperature and Precipitation Trends Observed at Some Selected Districts of Punjab, Pakistan

Present study examines the trends of extreme daily temperature and rainfall indices in some selectedmeteorological stations/districts of the Punjab. Due to paucity of data only six weather stations were selected from thewhole Punjab, having data of 33 years for temperature and precipitation on daily basis. A set of 14 indices(recommended by climate ET) were used to calculate the trends over a period of 32 years (1985–2017) by usingRClimDex (1.0) software package. These results showed that the number of tropical nights (TR20) and warm nights(TN90p) has been increasing in selected weather stations/districts and number for cool nights (TN10p) has been falling.Other temperature related indices trends such as, summer days, warms days, warm spell duration indicator (WSDI) andcool spell duration (CSDI) shows a mix pattern. The precipitation indices like SDII, RX1day, R10mm and PRCPTOTshowed an increasing trend in some selected stations. Most of the trends were not significant at level of 0.05 % whilemaximum day temperature increase has been observed at five out of six selected stations. Similarly, an average increasein precipitation in the vicinity of 3 mm per decade has been noted. The annual total rainfall and number of heavyrainfall days has also increased by 18 mm and 8.4 mm respectively during each decade. The analysis identified andhighlighted a slight change which was not temporally and spatially rational. However, there is need to more andadequate yearly data of different weather stations across the Punjab to identify the ongoing apparent and impeccablechanges in climate of the Punjab province.

Multi‐scale features of the co‐variability between global sea surface temperature anomalies and daily extreme rainfall in Argentina

AbstractThe goal of this study is to provide a better understanding of the trends and dominant oscillations characterizing the co‐variability between global sea surface temperature (SST) anomalies and daily extreme rainfall in Argentina. A singular value decomposition was performed between daily extreme rainfall monthly index in Argentina and global SST without removing the trends. The three leading modes explain 70.5% of the co‐variability, while the two leading modes explain more than 66% of the variability. The two leading modes exhibit significant variability on inter‐annual timescales related to tropical Pacific and Indian oceans, and specifically with El Niño–Southern Oscillation and the Indian Ocean Dipole. On decadal timescales, the leading mode activity is related to the Pacific Decadal Oscillation, whereas the second leading mode is associated with the Atlantic Multi‐decadal Oscillation (AMO). The third leading mode show co‐variability between the SST of the tropical Atlantic and the Indian ocean and extreme rainfall in the eastern‐centre of Argentina; this mode distinguishes phases of AMO. In addition, the two leading modes show positive trends, being largely non‐linear for leading one. The fact that extreme rainfall changes in Argentina observed in the last decades, are significantly influenced by the combination of the multi‐decadal variability and long‐term trends associated with the tropical oceans, is valuable knowledge to assess them in the future.

Streamflow Intensification Driven by the Atlantic Multidecadal Oscillation (AMO) in the Atrato River Basin, Northwestern Colombia

The impact of the Atlantic Multidecadal Oscillation (AMO) on the variations in the streamflow in the Atrato River Basin (ARB) during the 1965–2016 period was analyzed here by considering the cold (1965–1994) and warm (1995–2015) phases of this oscillation. The mean streamflow increased after 1994 (AMO phase change). This increase is related to the strengthening of the zonal gradients of the sea surface temperature (SST) and sea level pressure (SLP) between the tropical central Pacific and the tropical Atlantic after 1994 (warm AMO phase). These gradients contributed to strengthen the Walker cell related upward movement over northern and northwestern South America, in particular during November-December (ND). Consistently, the frequency (R20 mm) and intensity (SDII) of extreme daily rainfall events increased during the 1995–2015 period. Our results show a connection between the AMO and the increase in the streamflow in the ARB during the last five decades. These results contribute to the studies of resilience and climate adaptation in the region.

Risk evaluation of slope-disaster occurrence by estimating and ranking extreme daily rainfall potential

Risk evaluation of slope-disaster occurrence by estimating and ranking extreme daily rainfall potential

Evaluation and Projection of Extreme Precipitation over Northern China in CMIP5 Models

This study evaluates 32 climate models from CMIP5 compared with a daily gridded observation dataset of extreme precipitation indices including total extreme precipitation (R95p), maximum consecutive five days of precipitation (RX5day) and wet days larger than 10 mm of precipitation (R10mm) over Northern China during the historical period (1986–2005). Results show the majority models have good performance on spatial distribution but overestimate the amplitude of precipitation over Northern China. Most models can also capture interannual variation of R95p and RX5d, but with poor simulations on R10mm. Considering both spatial and temporal factors, the best multi-model ensemble (Group 1) has been selected and improved by 42%, 34%, and 37% for R95p, RX5d, and R10mm, respectively. Projection of extreme precipitation indicates that the fastest-rising region is in Northwest China due to the enhanced rainfall intensity. However, the uncertainty analysis shows the increase of extreme rainfall over Northwest China has a low confidence level. The projection of increasing extreme rainfall over Northeast China from Group 1 due to the longer extreme rainfall days is more credible. The weak subtropical high and southwest winds from Arabian Sea lead to the low wet biases from Group 1 and the cyclonic anomalies over Northeast China, which result in more extreme precipitation.

Extreme rainfall trends of 21 typical urban areas in China during 1998-2015 based on remotely sensed data sets.

With the increase of population, many cities are growing in size at a phenomenal rate. Urbanization changes the urban underlying surface, influences the micro-climate, and sometimes affects the local precipitation process. In this study, we investigated the trends of extreme rainfall in China's 21 typical urban areas. Based on a series of daily rainfall and "Urban/built-up" dataset from TMPA 3B42 and MCD12Q1 products in China, trends in extreme precipitation, with the threshold defined as 95th (pre95p) and 99th (pre99p) percentiles of annual rain days during 1998-2015, have been assessed in China, and especially in 21 typical urban areas from 1998 to 2015. The tendency curves in extreme rainfall of different years are presented. In this period, more than 66% regions of China covered by TMPA 3B42 have increasing trends in extreme rainfall with pre95p threshold. The 21 typical urban areas showed different trends-in over half of these areas, upward tendencies in extreme rainfall were observed, particularly in Dalian, Beijing, and Chongqing. Seventeen urban areas showed increasing tendencies in pre95p extreme rainfall days, including Shanghai, Nanjing, Hangzhou, and Suzhou in the Yangtze River Delta region. The results also illustrate that southeastern coastal urban areas of China may have experienced decreasing occurrences in extreme rainfall.

Meridionally Extending Anomalous Wave Train over Asia During Breaks in the Indian Summer Monsoon

Anomalous interactions between the Indian summer monsoon (ISM) circulation and subtropical westerlies are known to trigger breaks in the ISM on subseasonal time-scales, characterised by a pattern of suppressed rainfall over central-north India, and enhanced rainfall over the foothills of the central–eastern Himalayas (CEH). An intriguing feature during ISM breaks is the formation of a mid-tropospheric cyclonic circulation anomaly extending over the subtropical and mid-latitude areas of the Asian continent. This study investigates the mechanism of the aforesaid Asian continental mid-tropospheric cyclonic circulation (ACMCC) anomaly using observations and simplified model experiments. The results of our study indicate that the ACMCC during ISM breaks is part of a larger meridional wave train comprising of alternating anticyclonic and cyclonic anomalies that extend poleward from the monsoon region to the Arctic. A lead–lag analysis of mid-tropospheric circulation anomalies suggests that the meridional wave-train generation is linked to latent heating (LH) anomalies over the CEH foothills, Indo-China, and the Indian landmass during ISM breaks. By conducting sensitivity experiments using a simplified global atmospheric general circulation model forced with satellite-derived three-dimensional LH, it is demonstrated that the combined effects of the enhanced LH over the CEH foothills and Indo-China and decreased LH over the Indian landmass during ISM breaks are pivotal for generating the poleward extending meridional wave train and the ACMCC anomaly. At the same time, the spatial extent of the mid-latitude cyclonic anomaly over Far-East Asia is also influenced by the anomalous LH over central–eastern China. While the present findings provide interesting insights into the role of LH anomalies during ISM breaks on the poleward extending meridional wave train, the ACMCC anomaly is found to have important ramifications on the daily rainfall extremes over the Indo-China region. It is revealed from the present analysis that the frequency of extreme rainfall occurrences over Indo-China shows a twofold increase during ISM break periods as compared to active ISM conditions.

Extreme Daily Rainfall in Central-Southern Chile and Its Relationship with Low-Level Horizontal Water Vapor Fluxes

AbstractExtreme rainfall events are thought to be one of the major threats of climate change given an increase of water vapor available in the atmosphere. However, before projecting future changes in extreme rainfall events, it is mandatory to know current patterns. In this study we explore extreme daily rainfall events along central-southern Chile with emphasis in their spatial distribution and concurrent synoptic-scale circulation. Surface rain gauges and reanalysis products from the Climate Forecast System Reanalysis are employed to unravel the dependency between extreme rainfall and horizontal water vapor fluxes. Results indicate that extreme rainfall events can occur everywhere, from the subtropical to extratropical latitudes, but their frequency increases where terrain has higher altitude, especially over the Andes Mountains. The majority of these events concentrate in austral winter, last a single day, and encompass a north–south band of about 200 km in length. Composited synoptic analyses identified extreme rainfall cases dominated by northwesterly (NW) and westerly (W) moisture fluxes. Some features of the NW group include a 300-hPa trough projecting from the extratropics to subtropics, a surface-level depression, and cyclonic winds at 850 hPa along the coast associated with integrated water vapor (IWV) > 30 mm. Conversely, features in the W group include both a very weak 300-hPa trough and surface depression, as well as coastal westerly winds associated with IWV > 30 mm. About half of extreme daily rainfall is associated with an atmospheric river. Extreme rainfall observed in W (NW) cases has a strong orographic (synoptic) forcing. In addition, W cases are, on average, warmer than NW cases, leading to an amplified hydrological response.

The contribution of tropical cyclones to the atmospheric branch of Middle America\u2019s hydrological cycle using observed and reanalysis tracks

Middle America is affected by tropical cyclones (TCs) from the Eastern Pacific and the North Atlantic Oceans. We characterize the regional climatology (1998–2016) of the TC contributions to the atmospheric branch of the hydrological cycle, from May to December. TC contributions to rainfall are quantified using Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product 3B42 and TC tracks derived from three sources: the International Best Track Archive for Climate Stewardship (IBTrACS), and an objective feature tracking method applied to the Japanese 55-year and ERA-Interim reanalyses. From July to October, TCs contribute 10–30% of rainfall over the west and east coast of Mexico and central Mexico, with the largest monthly contribution during September over the Baja California Peninsula (up to 90%). TCs are associated with 40–60% of daily extreme rainfall (above the 95th percentile) over the coasts of Mexico. IBTrACS and reanalyses agree on TC contributions over the Atlantic Ocean but disagree over the Eastern Pacific Ocean and continent; differences over the continent are mainly attributed to discrepancies in TC tracks in proximity to the coast and TC lifetime. Reanalysis estimates of TC moisture transports show that TCs are an important moisture source for the regional water budget. TC vertically integrated moisture flux (VIMF) convergence can turn regions of weak VIMF divergence by the mean circulation into regions of weak VIMF convergence. We discuss deficiencies in the observed and reanalysis TC tracks, which limit our ability to quantify robustly the contribution of TCs to the regional hydrological cycle.

Spatial and temporal variability of daily precipitation concentration in the Sardinia region (Italy)

AbstractRecent studies evidenced that extreme daily rainfall often increases in spite of a decrease of the total rainfall. For this reason, the analysis of daily precipitation concentration is an important issue in climate research and can be useful to evaluate risks linked to extreme rainfall events. In this paper, an analysis of the spatial and temporal variability of the daily precipitation concentration in the Sardinia region, the second largest island in the Mediterranean Sea, has been performed for the period 1922–2011 by applying the Concentration Index. First, the CI has been evaluated at annual and seasonal scale. Then, the coefficient of variation, and the 5th and 95th percentiles of the annual CI values were calculated and mapped as a set of descriptors of variability and extreme characterization of precipitation concentration across the study area. Finally, in order to evaluate the temporal evolution of the CI, a trend analysis has been also performed using the Mann–Kendall test. Results show CI values ranging from a minimum of 0.477 to a maximum of 0.723. Spatially, the region can be divided in two parts with opposite behaviours: the western side characterized by a more uniform temporal distribution of rainfall intensity and the eastern side with the most critical intensity and aggressiveness of rainfall. From a seasonal point of view, this spatial gradient was evidenced in winter, spring and autumn while summer showed a more homogeneous spatial distribution of CI. The spatial distribution of the coefficient of variation did not show any spatial gradient between the two sides of the region, both at annual and seasonal scale. As regards the trend analysis, a marked positive trend of the CI has been detected, thus indicating a tendency towards more intense and aggressive rainfall. Copyright © 2019 John Wiley & Sons, Ltd.

Long-term trends in precipitation indices at eastern districts of Bangladesh

This study analyzed the trends of extreme daily rainfall indices over three meteorological stations located in the eastern region of Bangladesh from 1960 to 2000. The climate change-related indices included frequency-based indices: number of heavy rainfall days and consecutive dry and wet days, and intensity-based indices: annual wet-day rainfall total, daily and consecutive five-day maximum rainfall, very and extremely wet days and simple daily intensity index. The magnitude of trends in extreme rainfall indices time series was determined using the nonparametric Sen’s slope estimator method, and the statistical significance of the trends was analyzed using the Mann–Kendall test. The rainfall trends exhibited regional patterns. Overall, results suggested an increase in annual rainfall over the study area; however, a tendency toward reduction of rainfall in the wet season was observed. Analysis of extreme rainfall indices demonstrated non-significant increase in frequency of heavy rainfall days, decrease in consecutive dry days and increase in consecutive wet days coupled with regional decline in daily and consecutive five-day maximum rainfall in the monsoon.

Historical extreme rainfall events in southeastern Australia

The cities of Melbourne, Sydney and Adelaide are home to almost half of the Australian population, and are often exposed to extreme rainfall events and high year-to-year rainfall variability. However the majority of studies into rainfall in these cities, and southeastern Australia in general, are limited to the 20th century due to data availability. In this study we use rainfall data from a range of sources to examine four rainfall indices for Melbourne, Sydney and Adelaide for 1839–2017. We derive the total rainfall, number of raindays, wettest day of the month and the simple daily intensity index for each city over the past 178 years, and find relatively consistent relationships between all indices despite potential data quality issues associated with the historical data. We identify several extreme daily rainfall events in the pre-1900 period in Sydney and Melbourne that warrant further examination as they appear to be more extreme than anything in the modern record. We find a moderate and relatively stable relationship between El Niño–Southern Oscillation (ENSO) and annual variations of total rainfall and the number of raindays at all three cities over the research period, but no relationship between ENSO and the annual wettest day, in agreement with other studies using shorter time series.

A multi-temporal analysis of streamflow using multiple CMIP5 GCMs in the Upper Ayerawaddy Basin, Myanmar

In this study, bias-corrected daily rainfall data of eight global climate models (GCMs) was used as input for a hydrologic model (Hydrological Engineering Center - Hydrological Modeling System (HEC-HMS)) to simulate daily streamflow in the Upper Ayerawaddy River basin (UARB), Myanmar. Monthly, seasonal, annual, and decadal mean flows, calculated for the baseline (1975–2014), were compared with projections for future periods (2040s: 2021–2060 and 2080s: 2061–2100) under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The spread of low flows (10th and 25th percentile of daily flows) and high flows (75th, 90th, and 100th percentiles) were analyzed for each period. The ensemble of GCMs indicates an increase in mean monthly (except in October and November), seasonal (except post-monsoon), annual, and decadal rainfalls and corresponding flows in the UARB. Future low flows are expected to have high variability while high flows are expected to have higher means than that of baseline. The density distribution analysis of baseline and future flows reveals that future periods are likely to experience an increase in the magnitude of mean flows but a decrease in variability. Rainfall extremes indicated by 1-day maximum rainfall, 5-day consecutive maximum rainfall, and the number of extreme rainfall days reveals frequent wetter extremes in the UARB under future climate conditions. Extreme floods, as estimated by the frequency analysis of daily flows, are also expected to become more frequent during the future periods. These changes in flows can be attributed solely to climate change since the analyses did not account impacts of possible land use change and water resources development in the UARB. This study is a good starting point to assess future flows, and further research is recommended to address the limitations of this study for improved understanding and assessments that will prove useful for planning purposes in the study area.

Sensitivity Analysis of Extreme Daily Rainfall Depth in Summer Season on Surface Air Temperature and Dew-Point Temperature

Looking at future data obtained from global climate models, it is expected that future extreme rainfall will increase in many parts of the world. The Clausius-Clapeyron equation provides a physical basis for understanding the sensitivity of rainfall in response to warming, but the relationship between rainfall and temperature is still uncertain. The purpose of this study is to analyze the sensitivity of extreme daily rainfall depth during the summer season (June–September) to climate change in Korea. The relationship between the observed extreme daily rainfall depth and the surface air temperature (SAT) and dew-point temperature (DPT), which were observed in the 60 sites of the Korea Meteorological Administration, were analyzed. The same analysis was also performed using future data provided in various climate models. In addition, the future trends of extreme rainfall, SAT, and DPT were analyzed using future data obtained from climate models, and the effects of increasing SAT and DPT on future extreme rainfall changes were investigated. Finally, it has been confirmed that using changes in SAT and DPT to look at changes in future extreme rainfall can give more consistent future projection results than using future rainfall data directly.

Projected intensification of sub-daily and daily rainfall extremes in convection-permitting climate model simulations over North America: implications for future intensity–duration–frequency curves

Abstract. Convection-permitting climate models have been recommended for use in projecting future changes in local-scale, short-duration rainfall extremes that are of the greatest relevance to engineering and infrastructure design, e.g., as commonly summarized in intensity–duration–frequency (IDF) curves. Based on thermodynamic arguments, it is expected that rainfall extremes will become more intense in the future. Recent evidence also suggests that shorter-duration extremes may intensify more than longer durations and that changes may depend on event rarity. Based on these general trends, will IDF curves shift upward and steepen under global warming? Will long-return-period extremes experience greater intensification than more common events? Projected changes in IDF curve characteristics are assessed based on sub-daily and daily outputs from historical and late 21st century pseudo-global-warming convection-permitting climate model simulations over North America. To make more efficient use of the short model integrations, a parsimonious generalized extreme value simple scaling (GEVSS) model is used to estimate historical and future IDF curves (1 to 24 h durations). Simulated historical sub-daily rainfall extremes are first evaluated against in situ observations and compared with two high-resolution observationally constrained gridded products. The climate model performs well, matching or exceeding performance of the gridded datasets. Next, inferences about future changes in GEVSS parameters are made using a Bayesian false discovery rate approach. Large portions of the domain experience significant increases in GEVSS location (>99 % of grid points), scale (>88 %), and scaling exponent (>39 %) parameters, whereas almost no significant decreases are projected to occur (<1 %, <5 %, and <5 % respectively). The result is that IDF curves tend to shift upward (increases in location and scale), and, with the exception of the eastern US, steepen (increases in scaling exponent), which leads to the largest increases in return levels for short-duration extremes. The projected increase in the GEVSS scaling exponent calls into question stationarity assumptions that form the basis for existing IDF curve projections that rely exclusively on simulations at the daily timescale. When changes in return levels are scaled according to local temperature change, median scaling rates, e.g., for the 10-year return level, are consistent with the Clausius–Clapeyron (CC) relation at 1 to 6 h durations, with sub-CC scaling at longer durations and modest super-CC scaling at sub-hourly durations. Further, spatially coherent but small increases in dispersion – the ratio of scale and location parameters – of the GEVSS distribution are found over more than half of the domain, providing some evidence for return period dependence of future changes in extreme rainfall.

Oceanic Forcing on Interannual Variability of Sahel Heavy and Moderate Daily Rainfall

AbstractThis article analyzes SST remote forcing on the interannual variability of Sahel summer (June–September) moderate (below 75th percentile) and heavy (above 75th percentile) daily precipitation events during the period 1981–2016. Evidence is given that interannual variability of these events is markedly different. The occurrence of moderate daily rainfall events appears to be enhanced by positive SST anomalies over the tropical North Atlantic and Mediterranean, which act to increase low-level moisture advection toward the Sahel from the equatorial and north tropical Atlantic (the opposite holds for negative SSTs anomalies). In contrast, heavy and extreme daily rainfall events seem to be linked to El Niño–Southern Oscillation (ENSO) and Mediterranean variability. Under La Niña conditions and a warmer Mediterranean, vertical atmospheric instability is increased over the Sahel and low-level moisture supply from the equatorial Atlantic is enhanced over the area (the reverse is found for opposite-sign SST anomalies). Further evidence suggests that interannual variability of Sahel rainfall is mainly dominated by the extreme events. These results have implications for seasonal forecasting of Sahel moderate and heavy precipitation events based on SST predictors, as significant predictability is found from 1 to 4 months in advance.

Observed trends in indices for daily rainfall extremes specific to the agriculture sector in Lower Vellar River sub-basin, India

Globally, climate change has caused changes in frequency and intensity of climate extremes such as heat waves, droughts, floods and tropical cyclones. There is a need to understand the pattern of regional climate extremes to develop crucial adaptation strategies for the farming community. This paper focuses on developing the Expert Team on Climate Risk and Sector-specific Indices for rainfall, relevant for the agriculture and food security sector. The indices have been developed for Lower Vellar River sub-basin, a coastal basin in Tamil Nadu, India. Trend analysis has been done for the climatic and cropping seasons in the sub-basin. Overall, there has not been any trend in the annual rainfall index values. The monthly trend values for the different indices have mostly exhibited insignificant trends throughout the study period (1978–2015) except for a few indices. Overall, the southwest monsoon season has shown a significantly decreasing trend in the indices. The northeast monsoon season has shown insignificant trends with positive slopes for most indices. There were insignificant or no trends in the indices for the summer season. The findings from the study can be used as a guiding tool for developing adaptation strategies, for the farming community.

On the relationship of daily rainfall extremes and local mean temperature

Extreme rainfall is the most common cause of flooding and likelihood of such events is found to increase in recent studies. Large scale natural variability, human induced global warming and local atmospheric warming are important drivers of extreme rainfall. Understanding the association of these drivers with extreme rainfall and finding out the most significant physical driver will provide a foundation for risk assessment. This study presents a methodology to investigate the association of extreme rainfall events with physical drivers and to model their dependence structure. The methodology is demonstrated with application to Mahanadi River basin, India. Non-stationary extreme value models with multivariate ENSO index, global average temperature anomalies and local mean temperature anomalies as covariates are fitted at non-stationary rainfall grids of the basin. Statistical modelling confirms localized temperature to be the main driver influencing rainfall extremes. Clausius-Clapeyron (CC) scaling curves relating daily rainfall extremes and local mean temperature are developed at all the grids to obtain insights into warming induced changes in rainfall extremes. Significant deviations from the expected CC scaling behaviour are observed. Daily rainfall extremes show peaks at low (25 °C) to medium (30 °C) range of temperature, but exhibit a decrease at high temperatures for most of the grids. No change in this pattern of relationship is observed when the extreme rainfall is lagged by 1–9 days with temperature. This time lag is selected based on the concept of residence time of water in the atmosphere. The Copula theory is applied to capture the dependence of annual maximum daily rainfall and temperature extremes. Conditional probabilities of extreme rainfall are estimated by conditioning on local mean temperature values of strongest extreme rainfall events. Comparison of conditional probabilities suggests that stronger rainfall events are occurring at 30 °C. This study emphasizes the necessity of understanding the dependence structure of extreme rainfall and local mean temperature.