Extreme Daily Rainfall Research Articles

Spatial distribution of the trends in precipitation and precipitation extremes in the sub-Himalayan region of Pakistan

The northern sub-Himalayan region is the primary source of water for a large part of Pakistan. Changes in precipitation and precipitation extremes in the area may have severe impacts on water security and hydrology of Pakistan. The objective of the study is to evaluate the spatial characteristics of the trends in annual and seasonal precipitation and precipitation extremes in Gilgit Baltistan, the northern administrative territory of Pakistan surrounded by Hindu Kush, Karakoram, and the Himalayan regions. The daily gridded rainfall data (1951–2007) of Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) at 0.25° spatial resolution was used for evaluating the trends. The novelty of the present study is the application of the modified Mann-Kendall (MMK) trend for the evaluation of the significance of precipitation trends in order to differentiate the secular trends from climate natural variability. Besides, cumulative distribution function (CDF) plots of daily rainfall for the early (1951–1980) and later (1981–2007) periods were used to show the changes in extremes. The results revealed no significant change in annual precipitation but increase in summer rainfall in the range of 0.25 to 1.25 mm/year in the upper part and decrease in winter precipitation from 0 to − 0.25 mm/year in the west part of the region. Annual number of rainy days was also found to decrease in winter up to − 1.33 days/decade where the region receives a major portion of total precipitation. The decrease in winter rainfall and rainy days caused an increase in continuous dry days (around 0.27 days/year) and decrease in continuous wet days (up to − 0.26 days/year). Trend analysis and CDF plot revealed that though the numbers of rainy days are decreasing, the numbers of extreme rainfall days are increasing, which indicates rainfall become more erratic and intense in the region. The increases in both continuous dry days and extreme rainfall days indicate more droughts and floods may have adverse impacts on the hydrology of Pakistan.

Patterns in Indices of Daily and Seasonal Rainfall Extremes: Southwest Florida Gulf Coastal Zone

Extreme events have the most adverse impacts on society and infrastructure, and present the greatest challenges with respect to impacts. Information on the status and trends of these events is, thus, important for system design, management, and policy decision-making. In this study, variations in daily and seasonal rainfall extremes were explored with a focus on the southwest Florida Gulf coastal zone for the period 1950–2016. Rainfall occurring on very wet days accounted for about 50% of the seasonal rainfall in the area (regardless of the season), while about 25% of the seasonal rainfall came from extremely wet days except in the period between October and December for which this latter value was about 40%. No significant changes were seen in the maximum one-day rainfall at any of the stations regardless of the time scale. However, there was a significant increase in the number of wet days in the rainy season at Myakka River (p = 0.0062) and Naples (p = 0.0027) and during October–December at Myakka River (p = 0.0204). These two stations also experienced significant increases in the number of wet days in a year. Significant increases in the contribution to rainy season rainfall from very wet days (rainfall > 25.4 mm, 1 in) were seen at Arcadia (p = 0.0055). Regional results point to an increasingly wetter climate with increasing contributions from extreme events in some areas, both of which have implications for design and management decision making.

Modeling of Daily Rainfall Extremes, Using a Semi-Parametric Pareto Tail Approach

Various approaches have been widely proposed for simulation of the occurrence and the amount of daily rainfall. In this study, a piecewise distribution approach has been developed to improve extreme event amount simulation. The gamma-generalized Pareto (GGP) approach employs a combination of the generalized Pareto (GP) and the gamma density estimation method to model the daily rainfall distribution. Furthermore, three stochastic rainfall time series generations have been developed and compared to simulate the daily rainfall occurrence based on the first-order Markov chain (MC1), the second-order Markov chain (MC2) and the third-order Markov chain (MC3) approaches. 30 years daily datasets from 5 synoptic stations have been used in the semi-arid extra cold in Iran. The performance of different approaches has been compared using Akaike information climate criterion (AIC) and root mean square error (RMSE). Results show that MC1 performs relatively better than MC2 and MC3 for daily rainfall occurrence modeling. Results also show that the GGP probability density performs better to reproduce extreme daily rainfall compared with gamma, GP and exponential distributions.

Spatial distribution of unidirectional trends in climate and weather extremes in Nile river basin

The recent finding of the influence of long-term persistence (LTP) in time series on trend significance has made the past findings of climatic trends in the Nile river basin (NRB) disputable. Four versions of the Mann-Kendall test including the latest one which considers the LTP in time series have been used in this study to distinguish the unidirectional trend from natural variability of climate in NRB. The gridded Princeton global meteorological forcing data having 1-day and 0.25° temporal and spatial resolution, respectively, for the available period 1948–2010 was used. The results showed that the number of grid points showing a significant change in climate and weather extremes reduced drastically when LTP in time series was considered. The annual rainfall was increasing only at some locations in the main Nile and Atbara sub-basins at a rate of 0.26–26.4 mm/decade while decreasing in Sobat sub-basin up to − 76.6 mm/decade. The maximum temperatures were increasing in the main Nile, Atbara, Blue Nile, Bahr Elgazal, and Bahr Eljabel at a rate of 0.09–0.48 °C/decade, while the minimum temperatures were increasing in most parts of the NRB by 0.17–0.50 °C/decade. Among the weather extremes, a significant trend over a large part of NRB was found for extreme rainfall days (− 0.53–0.75 day/decade), cold nights (− 6.05–3.26 days/decade), heat waves (0.29–2.00 days/decade), and cold waves (− 4.05–1.15 day/decade).

Contribution of Moisture from Mediterranean Sea to Extreme Precipitation Events over Danube River Basin

In the most recent decades, central Europe and the Danube River Basin area have been affected by an increase in the frequency and intensity of extreme daily rainfall, which has resulted in the more frequent occurrence of significant flood events. This study characterised the link between moisture from the Mediterranean Sea and extreme precipitation events, with varying lengths that were recorded over the Danube River basin between 1981 and 2015, and ranked the events with respect to the different time scales. The contribution of the Mediterranean Sea to the detected extreme precipitation events was then estimated using the Lagrangian FLEXPART dispersion model. Experiments were modelled in its forward mode, and particles leaving the Mediterranean Sea were tracked for a period of time determined with respect to the length of the extreme event. The top 100 extreme events in the ranking with durations of 1, 3, 5, 7, and 10 days were analysed, and it was revealed that most of these events occurred in the winter. For extreme precipitation, positive anomalies of moisture support from the Mediterranean were found to be in the order of 80% or more, but this support reached 100% in summer and spring. The results show that extreme precipitation events with longer durations are more influenced by the extreme Mediterranean anomalous moisture supply than those with shorter lengths. However, it is during shorter events when the Mediterranean Sea contributes higher amounts of moisture compared with its climatological mean values; for longer events, this contribution decreases progressively (but still doubles the climatological moisture contribution from the Mediterranean Sea). Finally, this analysis provides evidence that the optimum time period for accumulated moisture to be modelled by the Lagrangian model is that for which the extreme event is estimated. In future studies, this fine characterisation could assist in modelling moisture contributions from sources in relation to individual extreme events.

Reply to comments on “Temperature‐extreme precipitation scaling: a two‐way causality?”

In recent years, numerous studies have investigated the relationship of extreme precipitation intensities with temperature derived from a binning method using present‐day weather data. The aim of this approach is that these dependencies, or so‐called apparent scaling rates, provide insights on how precipitation extremes could evolve in the future climate. In a recent paper, Bao et al. showed that there is a large discrepancy between the present‐day apparent scaling rates—showing a negative dependency of daily rainfall extremes on temperature for Darwin—and the climate change response showing a substantial increase in daily rainfall extremes. Their results provide compelling evidence that it may not be straightforward to predict the climate change response from the temperature scaling. We agree with this statement, but disagree with the physical explanation put forward in that study and think that moisture limitations are the most likely cause. Therefore, we advocate the use of dew point temperatures in scaling studies as a much more direct proxy of the absolute humidity of the air in which precipitation extremes develop, which we think is physically more consistent with the underlying mechanism causing the increase in precipitation extremes with global warming.

Detection of continental-scale intensification of hourly rainfall extremes

Temperature scaling studies suggest that hourly rainfall magnitudes might increase beyond thermodynamic expectations with global warming1–3; that is, above the Clausius–Clapeyron (CC) rate of ~6.5% °C−1. However, there is limited evidence of such increases in long-term observations. Here, we calculate continental-average changes in the magnitude and frequency of extreme hourly and daily rainfall observations from Australia over the years 1990–2013 and 1966–1989. Observed changes are compared with the uncertainty from natural variability and expected changes from CC scaling as a result of global mean surface temperature change. We show that increases in daily rainfall extremes are consistent with CC scaling, but are within the range of natural variability. In contrast, changes in the magnitude of hourly rainfall extremes are close to or exceed double the expected CC scaling, and are above the range of natural variability, exceeding CC × 3 in the tropical region (north of 23° S). These continental-scale changes in extreme rainfall are not explained by changes in the El Nino–Southern Oscillation or changes in the seasonality of extremes. Our results indicate that CC scaling on temperature provides a severe underestimate of observed changes in hourly rainfall extremes in Australia, with implications for assessing the impacts of extreme rainfall. Theory predicts that hourly rainfall extremes may increase with anthropogenic warming. Observations from Australia suggest changes two to three times above the Clausius–Clapeyron rate, above that expected from natural variability.

Station based Profile of Extreme Rainfall Events in the Punjab Province of Pakistan during 1981-2014

The changes in extreme daily rainfall totals in Punjab Province, Pakistan, during the period (1981- 2014) are examined in this study. The analysis was focused on the extreme annual and monthly rainfall events, by processing the exceeding of the daily rainfall over various thresholds, which are indicators for the incidence of extreme rainfall events. To analyze the changes in extreme rainfall events and trends of the time series of the annual number of extreme rainfall days (%) the thresholds of 30mm and 50mm has been estimated. Evidence from the twelve stations considered shows that there is an increase in annual number of extreme rainfall days (%) in dataset. These changes of heavy and extreme rainfall events pronounce significant environmental consequences which cause considerable impact on society.

An assessment of temporal effect on extreme rainfall estimates

Abstract. This study assesses the temporal behaviour in terms of inter-decadal variability of extreme daily rainfall of stated return period relevant for hydrologic risk analysis using a novel regional parametric approach. The assessment is carried out based on annual maximum daily rainfall series of 180 meteorological stations of Yangtze River Basin over a 50-year period (1961–2010). The outcomes of the analysis reveal that while there were effects present indicating higher quantile values when estimated from data of the 1990s, it is found not to be noteworthy to exclude the data of any decade from the extreme rainfall estimation process for hydrologic risk analysis.

Observed increase in extreme daily rainfall in the French Mediterranean

We examine long-term trends in the historical record of extreme precipitation events occurring over the French Mediterranean area. Extreme events are considered in terms of their intensity, frequency, extent and precipitated volume. Changes in intensity are analysed via an original statistical approach where the annual maximum rainfall amounts observed at each measurement station are aggregated into a univariate time-series according to their dependence. The mean intensity increase is significant and estimated at + 22% (+ 7 to + 39% at the 90% confidence level) over the 1961–2015 period. Given the observed warming over the considered area, this increase is consistent with a rate of about one to three times that implied by the Clausius–Clapeyron relationship. Changes in frequency and other spatial features are investigated through a Generalised Linear Model. Changes in frequency for events exceeding high thresholds (about 200 mm in 1 day) are found to be significant, typically near a doubling of the frequency, but with large uncertainties in this change ratio. The area affected by severe events and the water volume precipitated during those events also exhibit significant trends, with an increase by a factor of about 4 for a 200 mm threshold, again with large uncertainties. All diagnoses consistently point toward an intensification of the most extreme events over the last decades. We argue that it is difficult to explain the diagnosed trends without invoking the human influence on climate.

Extreme Daily Rainfall in Pakistan and North India: Scale Interactions, Mechanisms, and Precursors

While much of India is used to heavy precipitation and frequent low pressure systems during the summer monsoon, toward the northwest and into Pakistan, such events are uncommon. Here, as much as a third of the annual rainfall is delivered sporadically during the winter monsoon by western disturbances. Such events of sparse but heavy precipitation in this region of typically mountainous valleys in the north and desert in the south can be catastrophic, as in the case of the Pakistan floods of July 2010. In this study, extreme precipitation events (EPEs) in a box approximately covering this region (25°–38°N, 65°–78°E) are identified using the APHRODITE gauge-based precipitation product. The role of the large-scale circulation in causing EPEs is investigated: it is found that, during winter, it often coexists with an upper-tropospheric Rossby wave train that has prominent anomalous southerlies over the region of interest. These winter EPEs are also found to be strongly collocated with incident western disturbances whereas those occurring during the summer are found to have a less direct relationship. Conversely, summer EPEs are found to have a strong relationship with tropical lows. A detailed Lagrangian method is used to explore possible sources of moisture for such events and suggests that, in winter, the moisture is mostly drawn from the Arabian Sea, whereas during the summer, it comes from along the African coast and the Indian monsoon trough region.

Historical simulations and climate change projections over India by NCAR CCSM4: CMIP5 vs. NEX-GDDP

A new bias-corrected statistically downscaled product, namely, the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), has recently been developed by NASA to help the scientific community in climate change impact studies at local to regional scale. In this work, the product is validated over India and its added value as compared to its CMIP5 counterpart for the NCAR CCSM4 model is analyzed, followed by climate change projections under the RCP8.5 global warming scenario using the two datasets for the variables daily maximum 2-m air temperature (Tmax), daily minimum 2-m air temperature (Tmin), and rainfall. It is found that, overall, the CCSM4-NEX-GDDP significantly reduces many of the biases in CCSM4-CMIP5 for the historical simulations; however, some biases such as the significant overestimation in the frequency of occurrence in the lower tail of the Tmax and Tmin still remain. In regard to rainfall, an important value addition in CCSM4-NEX-GDDP is the alleviation of the significant underestimation of rainfall extremes found in CCSM4-CMIP5. The projected Tmax from CCSM4-NEX-GDDP are in general higher than that projected by CCSM4-CMIP5, suggesting that the risks of heat waves and very hot days could be higher than that projected by the latter. CCSM4-NEX-GDDP projects the frequency of occurrence of the upper extreme values of historical Tmax to increase by a factor of 100 towards the end of century (as opposed to a factor of 10 increase projected by CCSM4-CMIP5). In regard to rainfall, both CCSM4-CMIP5 and CCSM4-NEX-GDDP project an increase in annual rainfall over India under the RCP8.5 global warming scenario progressively from the near term through the far term. However, CCSM4-NEX-GDDP consistently projects a higher magnitude of increase and over a larger area as compared to that projected by CCSM4-CMIP5. Projected daily rainfall distributions from CCSM4-CMIP5 and CCSM4-NEX-GDDP suggest the occurrence of events that have no historical precedents. Worth noting is that the extreme daily rainfall values projected by CCSM4-NEX-GDDP are two to three times larger than that projected by CCSM4-CMIP5.

Increased Spatial Variability and Intensification of Extreme Monsoon Rainfall due to Urbanization

While satellite data provides a strong robust signature of urban feedback on extreme precipitation; urbanization signal is often not so prominent with station level data. To investigate this, we select the case study of Mumbai, India and perform a high resolution (1 km) numerical study with Weather Research and Forecasting (WRF) model for eight extreme rainfall days during 2014–2015. The WRF model is coupled with two different urban schemes, the Single Layer Urban Canopy Model (WRF-SUCM), Multi-Layer Urban Canopy Model (WRF-MUCM). The differences between the WRF-MUCM and WRF-SUCM indicate the importance of the structure and characteristics of urban canopy on modifications in precipitation. The WRF-MUCM simulations resemble the observed distributed rainfall. WRF-MUCM also produces intensified rainfall as compared to the WRF-SUCM and WRF-NoUCM (without UCM). The intensification in rainfall is however prominent at few pockets of urban regions, that is seen in increased spatial variability. We find that the correlation of precipitation across stations within the city falls below statistical significance at a distance greater than 10 km. Urban signature on extreme precipitation will be reflected on station rainfall only when the stations are located inside the urban pockets having intensified precipitation, which needs to be considered in future analysis.

On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen’s slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

Dynamical Downscaling Luaran Global Climate Model (GCM) Menggunakan Model REGCM3 untuk Proyeksi Curah Hujan di Kabupaten Indramayu

Future rainfall projection can be predicted by using Global Climate Model (GCM). In spite of low resolution, we are not able specifically to describe a local or regional information. Therefore, we applied downscaling technique of GCM output using Regional Climate Model (RCM). In this case, Regional Climate Model version 3 (RegCM3) is used to accomplish this purpose. RegCM3 is regional climate model which atmospheric properties are calculated by solving equations of motion and thermodynamics. Thus, RegCM3 is also called as dynamic downscaling model. RegCM3 has reliable capability to evaluate local or regional climate in high spatial resolution up to 10 × 10 km. In this study, dynamically downscaling techniques was applied to produce high spatial resolution (20 × 20 km) from GCM EH5OM output which commonly has rough spatial resolution (1.875<sup>o</sup> × 1.875<sup>o</sup>). Simulation show that future rainfall in Indramayu is relatively decreased compared to the baseline condition. Decreased rainfall generally occurs during the dry season (July-June-August/JJA) in a range 10-20%. Study of extreme daily rainfall indicates that there is no significant increase or decrease value.

Trend in the Co‐Occurrence of Extreme Daily Rainfall in West Africa Since 1950

AbstractWe propose in this paper a statistical framework to study the evolution of the co‐occurrence of extreme daily rainfall in West Africa since 1950. We consider two regions subject to contrasted rainfall regimes: Senegal and the central Sahel. We study the likelihood of the 3% largest daily rainfall (considering all days) in each region to occur simultaneously and, in a 20 year moving window approach, how this likelihood has evolved with time. Our method uses an anisotropic max‐stable process allowing us to properly represent the co‐occurrence of daily extremes and including the possibility of a preferred direction of co‐occurrence. In Senegal, a change is found in the 1980s, with preferred co‐occurrence along the E‐50‐N direction (i.e., along azimuth 50°) before the 1980s and weaker isotropic co‐occurrence afterward. In central Sahel, a change is also found in the 1980s but surprisingly with contrasting results. Anisotropy along the E‐W direction is found over the whole period, with greater extension after the 1980s. The paper discusses how the co‐occurrence of extremes can provide a qualitative indicator on change in size and propagation of the strongest storms. This calls for further research to identify the atmospheric processes responsible for such contrasted changes in storm properties.

Trends in autumn rain of West China from 1961 to 2014

Autumn rain of West China is a typical climate phenomenon, which is characterized by continuous rainy days and large rainfall amounts and exerts profound impacts on the economic society. Based on daily precipitation data from 524 observation stations for the period of 1961–2014, this article comprehensively examined secular changes in autumn rain of West China, including its amount, frequency, intensity, and associated extremes. The results generally show a significant reduction of rainfall amount and rainy days and a significant enhancement of mean rainfall intensity for the average of West China during autumn (September–October) since 1961. Meanwhile, decreasing trends are consistently observed in the maximum daily rainfall, the longest consecutive rainy days, the greatest consecutive rainfall amount, and the frequencies of the extreme daily rainfall, consecutive rainfall, and consecutive rainfall process. Further analysis indicates that the decreases of autumn rainfall and related extremes in West China are associated with the decreases in both water vapor content and atmospheric unstable stratification during the past decades. On the regional scale, some differences exist in the changes of autumn rainfall between the eastern and western parts of West China. Besides, it is found that the autumn rainy season tends to start later and terminate earlier particularly in eastern West China.

Recent Trends in Climate Extreme Indices over Sri Lanka

Trends in 20 extreme indices of temperature and precipitation are examined for Sri Lanka using high-quality datasets for 19 meteorological stations, for a period between 1980 and 2015. It is evident that annually averaged mean minimum temperatures are increasing across most of Sri Lanka. The difference between maximum and minimum temperatures, diurnal temperature range is decreasing, indicating that the minimum temperature is increasing faster than the maximum temperature. Significant decrease in the annual occurrence of cold nights and increase in the annual occurrence of warm nights are also obvious. When compared with temperature changes, less spatially coherent pattern of change and a lower level of statistical significance were observed in precipitation indices. The annual total precipitation (PRCPTOT) has indicated a significant increasing over 1980-2015. More than 80% of stations showed an increasing trend in precipitation indices. The trends in extreme precipitation events such as maximum one-day precipitation, maximum five-day precipitation, and total precipitation on extreme rainfall days (R95p and R99p) are increasing at most locations, indicating that the intensity of the rainfall is increasing. Increase of precipitation extreme trends indicates that occurrence of extreme rainfall events notably influences total annual precipitation in Sri Lanka. Therefore, the observed increases in total rainfall observed in many locations may be due in part to an increase in of extreme rainfall events. Patterns of change in precipitation extremes are more heavily influencing the climate variability by aggravating the variability, significantly influencing climate sensitive sectors such as agriculture and water resource management.

The Influence of Atmospheric Rivers over the South Atlantic on Winter Rainfall in South Africa

Abstract A climatology of atmospheric rivers (ARs) impinging on the west coast of South Africa (29°–34.5°S) during the austral winter months (April–September) was developed for the period 1979–2014 using an automated detection algorithm and two reanalysis products as input. The two products show relatively good agreement, with 10–15 persistent ARs (lasting 18 h or longer) occurring on average per winter and nearly two-thirds of these systems occurring poleward of 35°S. The relationship between persistent AR activity and winter rainfall is demonstrated using South African Weather Service rainfall data. Most stations positioned in areas of high topography contained the highest percentage of rainfall contributed by persistent ARs, whereas stations downwind, to the east of the major topographic barriers, had the lowest contributions. Extreme rainfall days in the region are also ranked by their magnitude and spatial extent. The results suggest that although persistent ARs are important contributors to heavy rainfall events, they are not necessarily a prerequisite. It is found that around 70% of the top 50 daily winter rainfall extremes in South Africa were in some way linked to ARs (both persistent and nonpersistent). Overall, the findings of this study support similar investigations on ARs in the North Atlantic and North Pacific.