Trends In Extreme Precipitation Indices Research Articles

Elevation dependent change in ERA5 precipitation and its extremes

Mountain regions are recognised as hot-spots of climate change. Although the existence of an Elevation-Dependent Warming has been extensively confirmed in several mountain areas of the globe, fewer studies have analysed the elevational stratification of temporal trends of other climate variables, and particularly for precipitation. This study analyses changes in mean precipitation and its extremes in ERA5 global reanalysis data in key mountain areas of the globe, along with their elevational dependence, from 1951 to 2020. These include the Tibetan Plateau, the US Rocky Mountains, the Greater Alpine Region, and the Andes, as representative of different latitudes and climatic influences. Our analysis reveals common patterns of elevational dependent change in precipitation and its extremes in most of the mountainous areas, which emerge beyond their geographical differences. A positive elevational gradient of trends of extreme precipitation indices is found in the Tibetan Plateau, the Greater Alpine Region, and the subtropical Andes, highlighting a wetting effect (positive trends) at very high elevations. In contrast, the Rocky Mountains exhibit a negative elevational gradient, with a drying effect (negative trends) increasing with the elevation. Notably, a simple linear regression proved to be effective to describe the stratification of change in the Greater Alpine Region and the Rocky Mountains, whereas more complex vertical patterns need to be considered for the Andes and the Tibetan Plateau. Mean precipitation, heavy (≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge$$\\end{document}10 mm) precipitation and the length of consecutive wet days show a consistent elevation-dependent stratification within each of the study areas, suggesting possible common driving mechanisms.

Extreme precipitation detection ability of four high-resolution precipitation product datasets in hilly area: a case study in Nepal

Given Nepal's vulnerability to extreme precipitation (EP), it is imperative to conduct a comprehensive analysis to comprehend the historical trends of such events. However, acquiring precise precipitation data for EP remains challenging in mountainous countries like Nepal owing to the scarcity of densely gauged networks. This limitation impedes the dissemination of knowledge pertaining to EP variability events in Nepal. The current research on this topic is deficient for two main reasons: 1) there is a lack of studies leveraging recently released high-resolution precipitation products to identify their EP detection capabilities, which further hinders the usability of those products in data-scarce regions like Nepal, and 2) most studies have focused on the characterisation of EP events in Nepal rather than their spatial and temporal variability. To address these issues, this study evaluated the EP detection capabilities of four high-resolution precipitation product datasets (PPDs) across Nepal from 1985 to 2020. These datasets include the ERA5 Land reanalysis data, satellite-based precipitation data (PERSIANN_CCS_CDR and CHIRPS_V2.0) and a merged dataset (TPHiPr). We used various statistical and categorical indices to assess their ability to capture the spatial and temporal variability of EP events. The annual EP events were characterised by 11 indices divided into frequency and intensity categories. The TPHiPr merged dataset offered a robust depiction of monthly precipitation estimates, achieving the highest critical success index, accuracy, probability of detection and a low false alarm ratio for daily precipitation detection of 0.1 mm in Nepal. Conversely, the PERSIANN_CCS_CDR dataset exhibited poor performance. Most PPDs showed increasing trends in EP indices. However, the TPHiPr dataset showcased those trends with fewer errors and stronger correlations for many frequency (R10mm, R20mm and R25mm) and intensity (RX1day, RX5day, PRCPTOT and R99p) indices. The results indicate that TPHiPr outperformed other PPDs in accurately representing the spatial distribution of EP trends in Nepal from 1985 to 2020, particularly noting an exacerbation of EP events mostly in the eastern region of Nepal throughout the study period. While TPHiPr demonstrated superior performance in detecting various EP indices across Nepal, individual products like the ERA5 Land reanalysis dataset showed enhanced performance in the western region of Nepal. Conversely, PERSIANN_CCS_CDR and CHIRPS_V2.0 performed well in the eastern region compared to other PPDs.

Space–Time Characterization of Extreme Precipitation Indices for the Semiarid Region of Brazil

Various indices of climate variability and extremes are extensively employed to characterize potential effects of climate change. Particularly, the semiarid region of Brazil is influenced by adverse effects of these changes, especially in terms of precipitation. In this context, the main objective of the present study was to characterize the regional trends of extreme precipitation indices in the semiarid region of Brazil (SAB), using daily precipitation data from the IMERG V06 product, spanning the period from 1 January 2001 to 31 December 2020. Twelve extreme precipitation indices were considered, which were estimated annually, and their spatial and temporal trends were subsequently analyzed using the nonparametric Mann–Kendall test and Sen’s slope. The analysis revealed that the peripheral areas of the SAB, especially in the northwest and extreme south regions, exhibited higher intensity and frequency of extreme precipitation events compared to the central portion of the area. However, a negative trend in event intensity was noted in the north, while positive trends were identified in the south. The frequency of extreme events showed a predominance of negative trends across most of the region, with an increase in consecutive dry days particularly throughout the western SAB. The average total precipitation index was above 1000 mm in the north of the SAB, whereas in the central region, the precipitation averages were predominantly below 600 mm, with rainfall intensity values ranging between 6 and 10 mm/day. Over the span of 20 years, the region underwent an average of 40 consecutive dry days in certain localities. A negative trend was observed in most of the indices, indicating a reduction in precipitation intensity in future decades, with variations in some indices. The dry years observed towards the end of the analyzed period likely contributed to the observed negative trends in the majority of extreme precipitation indices. Such trends directly impact the intensity and frequency of extreme weather events in the SAB. The study is important for highlighting and considering the impacts of changes in precipitation extremes in the semiarid region of Brazil. Based on the obtained results, we advocate the implementation of public policies to address future challenges, such as incorporating adaptations in water resource management, sustainable agricultural practices, and planning for urban and rural areas.

Performance of the PERSIANN Family of Products over the Mekong River Basin and Their Application for the Analysis of Trends in Extreme Precipitation Indices

Near-real-time satellite precipitation estimation is indispensable in areas where ground-based measurements are not available. In this study, an evaluation of two near-real-time products from the Center for Hydrometeorology and Remote Sensing at the University of California, Irvine—PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification System) and PDIR-Now (PERSIANN-Dynamic Infrared Rain Rate near-real-time)—were compared to each other and evaluated against IMERG Final (Integrated Multi-satellite Retrievals for Global Precipitation Measurement—Final Run) from 2015 to 2020 over the Mekong River Basin and Delta (MRB) using a spatial resolution of 0.1∘ by 0.1∘ and at a daily scale. PERSIANN-CDR (PERSIANN-Climate Data Record) was also included in the evaluation but was not compared against the real-time products. In this evaluation, PDIR-Now exhibited a superior performance to that of PERSIANN-CCS, and the performance of PERSIANN-CDR was deemed satisfactory. The second part of the study entailed performing a Mann–Kendall trend test of extreme precipitation indices using 38 years of PERSIANN-CDR data over the MRB. This annual trend analysis showed that extreme precipitation over the 95th and 99th percentiles has decreased over the Upper Mekong River Basin, and the consecutive number of wet days has increased over the Lower Mekong River Basin.

Assessing spatiotemporal trends of total and extreme precipitation in a subtropical highland region: A climateperspective.

This study used a dataset of 30 years (1990-2020) of daily observations from 24 meteorological stations in the northern highlands of Pakistan to assess trends in extreme precipitation indices. The RClimDex model was used to analyze the indices, and the Modified Mann-Kendal test and the Theil-Sen slope estimator were applied to determine trends and slopes, respectively. The results showed a significant decrease in total annual precipitation amount (PRCPTOT) with varying rates of negative trend from -4.44 mm/year to -19.63 mm/year. The total winter and monsoon precipitation amounts were also decreased during the past three decades. The intensity-based precipitation indices (RX1Day, RX5Day, R95p, R99p, and SDII) showed a significant decrease in extreme intensity events over time, while the count of consecutive dry days (CDD) and consecutive wet days (CWD) indicated a significant decrease in duration at multiple stations. The annual counts of days with precipitation more than or equal to 10 mm (R10), 20 mm (R20), and 25 mm (R25) exhibited a significant decrease in frequency of extreme precipitation events, with the decrease more pronounced in the northern parts of the study domain. The findings of this study indicate a significant decline in the intensity, frequency, and extent of precipitation extremes across the northern highlands of Pakistan over the past 30 years.

Trends in Extreme Precipitation Indices in Northwest Ethiopia: Comparative Analysis Using the Mann–Kendall and Innovative Trend Analysis Methods

This study analyzed long-term extreme precipitation indices using 4 × 4 km gridded data obtained from the National Meteorological Agency of Ethiopia between 1981 and 2018. The study examined trends in extreme precipitation over three districts (Lay Gayint, Tach Gayint, and Simada) in the northwestern highlands of Ethiopia. Innovative Trend Analysis (ITA) and Mann–Kendall (MK) trend tests were used to study extreme precipitation trends. Based on the ITA result, the calculated values of nine indices (90% of the analyzed indices) showed significant increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 70% (seven indices) showed significantly increasing trends at p < 0.01. On the other hand, 60% of the extreme indices showed significant downward trends (p < 0.01) in Simada. The MK test revealed that 30% of the extreme indices had significantly increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 30% of the extreme indices showed significant increasing trends at p < 0.05, while 10% of the extreme indices exhibited significant increasing trends at p < 0.01. In Simada, 20% of the extreme indices showed significant increasing trends at p < 0.05. Overall, the results showed that the ITA method can identify a variety of significant trends that the MK test misses.

Trends in Extreme Precipitation Indices over Bhutan

With the changing climate, the frequency and intensity of extreme precipitation events are increasing. Climate change is projected to increase both mean and extreme precipitation. Socio-economic damages can be immense and require a difficult recovery, especially for developing countries such as Bhutan. Furthermore, changing precipitation patterns affect land productivity and water availability. The Experts Team on Climate Change Detection Indices (ETCCDI) is used to find the changes associated with extreme precipitation in Bhutan. The study of extreme precipitation is important for Bhutan, whose economy is dependent on agriculture and hydropower. Even for a small country, there were varying patterns of precipitation in different districts. Deothang district received less frequent and more intense rainfall, while Haa, Bumthang, Trashiyangtse, and Chukha received weak but persistent rainfall. Mann–Kendall trends revealed a drier climate for two districts, Dagana and Trashiyangtse, and a wetter climate for the Mongar district. Modeling of the extreme rainfall with extreme value theory (EVT) revealed that the generalized extreme value (GEV) distribution by their T = 50-year return value, indicating an increasing value of annual maximums for all stations. This study is the first of its kind for Bhutan, and the findings can be used for decision support and the planning of appropriate adaptation strategies for hydro-meteorological disasters, hydropower, and agriculture sectors in Bhutan.

Estimating the impact of urbanization on non-stationary models of extreme precipitation events in the Yangtze River Delta metropolitan region

Rapid urbanization has significantly increased the proportion of impervious surfaces in Yangtze River Delta urban agglomeration (YRDUA), hence quantifying its impact on extreme precipitation events is essential for waterlogging control and urban planning. The spatiotemporal evolution patterns of extreme precipitation indices (EPIs) based on a non-stationary Generalized Extreme Value (GEV) model are analyzed in urban, suburban, and rural stations. Additionally, the degree of change of the recurrence levels are calculated to evaluate the effect of the urbanization process on EPIs in these stations. The results indicated that (1) Except for CWD, other EPIs show an increasing trend and EPIs with significantly increasing trend distributed in the downwind direction of the YRD. The percentages of significantly positive trends in EPIs, accounted for more than 85%, are mainly in the urban and suburban stations. (2) The optimal non-stationary GEV model with urbanization factor is predominately distributed in the highly urbanized areas. Urbanization factor has a significant impact on short-term, high-intensity precipitation and PRCPTOT in urban areas. (3) While the proportion of urban impervious areas in the urban area increased from 0.11 in 1985 to 0.63 in 2016, the effect of urbanization on EPIs changes from negative to positive and R95p, R25, R50, PRCPTOT in urban are much higher than those in rural after 2000. Urbanization significantly affects the recurrence levels of Rx5day in the rural, urban, and suburban stations, which increased by 27%, 29%, and 29%, respectively. The degree of change in the recurrence level in the suburban and urban areas is greater than that in the rural areas.

Long‐term trends in extreme precipitation indices in Ireland

AbstractKnowledge of long‐term changes in climate extremes is vital to better understand climate variability and place present day extreme events in historical context. Analysis of trends in extreme precipitation in Ireland have largely been limited to the second half of the 20th century due to lack of data availability in digital format. Using recently digitized data, this study provides the first assessment of long‐term changes in extreme daily precipitation observed at 30 locations across Ireland. Quality control of rescued data is carried out before selected long‐term stations are tested for homogeneity using the RHtests software. Details of detected breakpoints and the application of adjustments to daily values are discussed. Eleven extreme precipitation indices are calculated on an annual basis and analysed to determine spatial and temporal trends in the frequency, intensity and magnitude of observed precipitation. The persistence of trends for varying record lengths and for two fixed periods (1910–2019 and 1940–2019) of analysis is assessed for all stations and indices. Results show increases in precipitation intensity, especially notable in the east and southeast of the island. Our findings also show that the contribution of heavy and extreme precipitation events to annual totals is increasing, while there was no persistent trends in annual totals or consecutive wet or dry days.

Spatial variations of extreme precipitation events and attribution analysis in the main water resource area of the Belt and Road Initiative

Under the background of global warming, extreme precipitations had caused important issues, and the spatiotemporal precipitation of the main water resource (MWR) area of the Belt and Road (BR) Initiative had complex conditions. Therefore, observed daily precipitation data from 351 meteorological stations were selected to analyze temporal and spatial characteristics in extreme precipitations. The Mann-Kendall trend test was utilized to detect trends of extreme precipitation indices which were derived from the Expert Team on Climate Change Detection and Indices (ETCCDI), and the periodical characteristics of 4 typical extreme precipitation indices were calculated using wavelet analysis. In order to further analyze the relationship between extreme precipitation indices and global climate anomalies, the Southern Oscillation Index (SOI) and Arctic Oscillation (AO) were selected as climate indices to investigate teleconnections between extreme precipitation indices and atmospheric oscillations. Our results revealed that (Alexander et al. in J Geophys Res Atmos 111(D5): 1042–1063, 2006) the climate in the MWR had become more humid, and the frequency and intensity of extreme precipitation had shown a positive trend; (Allan and Soden in Science 321(5895): 1481–1484, 2008) 4 typical extreme precipitation indices exhibited multiple and overlapping cycles, while 23–32-year cycles were universal; (Limsakul and Singhruck in Atmos Res 169: 301–317, 2016) the teleconnection between large-scale circulation and extreme precipitation of MWR varied not only from region to region, but was also different at different time scales and different time periods, but had a negative effect on the whole.

Quantifying precipitation extremes and their relationships with large‐scale climate oscillations in a tropical country, Singapore: 1980–2018

Extreme precipitation indices (EPIs) were defined to quantify the precipitation extremes in Singapore, a typical tropical country situated near the equator. The paper investigated the spatial and temporal variability of precipitation extremes based on seventeen EPIs using non‐parametric Mann‐Kendall test and Sen’s slope, and further explored the linear and nonlinear relationships between precipitation extremes and four large‐scale global climate oscillations using correlation and wavelet analysis, during the period of 1980–2018 in Singapore. The results indicated that the trends of precipitation extremes varied for different EPIs, regions and stations. Increasing trends dominated thirteen out of seventeen EPIs. The trends of EPIs were scattered and irregularly distributed. The cross‐correlation analysis between different EPIs demonstrated that annual total precipitation on wet days (PRCPTOT) was strongly correlated with other EPIs. The result of composite analysis indicated that El Niño Southern Oscillation (ENSO) exerted stronger impacts on southwest monsoon season (SMS) precipitation than PRCPTOT and northeast monsoon season (NMS) precipitation. The SMS precipitation composite suggested that ENSO created more influence on dry spells than wet spells. The linear and nonlinear relationships revealed that all climate oscillations were negatively correlated with precipitation. The wavelet coherence and phase differences were consistent with the results of correlation analysis, indicating possible prediction of precipitation extremes using climate oscillations as potential predictors.

Vertical variation and temporal trends of extreme precipitation indices in a complex topographical watershed in the Hengduan Mountain Region, China

AbstractSpatial–temporal trends of extreme precipitation have great impacts on disaster risks, and relevant studies usually receive much attention. In China, spatial–temporal trends have been analysed in numerous studies based on daily rainfall data; however, the densities of rain gauges in many studies were relatively low, and the effects of complex topography on extreme precipitation were usually not considered, which have lowered the reliability and accuracy of the reported results. In this study, several widely used extreme precipitation indices were chosen, and the spatial–temporal trends of a typical watershed in the Hengduan Mountain Region in Southwest China, the Longchuanjiang watershed, were analysed using the Mann–Kendall trend analysis based on daily rainfall data. The effect of elevation on the extreme precipitation indices based on the high‐intensity rain gauges and the effect of elevation on the temporal trends of extreme precipitation indices were analysed, which have rarely been reported. The results indicated that: (a) significant positive correlations with elevation were reported for annual precipitation and most of the extreme precipitation indices, including PRCPTOT, Rx5day, R95P, R99P, RD, SDII, and CWD, while significant negative correlations were reported for CDD; the relationships between SDII and Rx1day were not significant with elevation; (b) the density of rain gauges in the regions with complex topography can have great impacts on the results; and (c) no significant correlation between the elevation and the temporal trends of extreme precipitation indices were reported. This study highlights the effects of the density of rain gauges and elevation, or topographical factors on the spatial distribution and temporal trends of extreme precipitation indices, which has rarely been reported in previous studies, implying that such effects should be fully taken into consideration in the relevant studies in the future.

Observed trends in daily extreme precipitation indices in Aguascalientes, Mexico

AbstractPrecipitation and its distribution greatly influence the evolution of ecosystems and the development of society. The objective was to analyse trends in extreme precipitation indices at 25 weather stations of Aguascalientes State. Eleven extreme precipitation indices were obtained. The time series of these indices were analysed with the non‐parametric Mann–Kendall test. The number of days above 50 mm, consecutive wet days, and extremely wet days did not have significant trends at any of the weather stations. Each of the indices maximum 1 day precipitation amount, maximum 5 day precipitation amount and number of very heavy precipitation days showed a significant positive trend at 12% of the weather stations; both the number of heavy precipitation days and the number of very wet days had significant positive trends at 8% of the weather stations; the simple daily intensity index, consecutive dry days and annual total wet‐day precipitation showed significant positive trends at 20%, 36% and 4% of weather stations, respectively. The intensity index was the only one that showed a significant negative trend, which happened at 4% of the weather stations. In a small part of Aguascalientes, the precipitation intensity, the number of rainy days and the accumulated total increased in short periods. Also, in a reduced region, daily precipitation intensity decreased; and in another very small area the number of dry days increased. For mitigating the effects of these phenomena, it is suggested that water be used more efficiently for sustained agricultural production systems and ecosystem management. The results of the present study will be of great importance in future economic planning in the Aguascalientes State.

Trend Analysis of Temperature and Precipitation Extremes during Winter Wheat Growth Period in the Major Winter Wheat Planting Area of China

In this study, the major winter wheat planting area of China is selected as the study area, with the time scale of the growth period of winter wheat (a total of 56 growth periods during October 1961 to May 2016). The significance, stability, magnitude of the trend and the average trend of the study area with eight temperature indices and seven precipitation indices of 453 meteorological stations are tested by Mann–Kendall method and Sen’s nonparametric method. The following observation can be made: (1) the cold extreme indices show strong and stable downward trend in most of the stations in the study area, while the hot extreme indices show a strong and stable upward trend, especially in the northern winter wheat planting area and the north of the southern winter wheat planting area. (2) The trends of extreme precipitation indices in most of the sites in the study area are insignificant and unstable. Only in R20mm, a significant and stable decreasing trend is shown in some stations, which is mainly located in the northern winter wheat planting area and part of the central and western regions in the study area. The results in some ways could enrich the references for understanding the climate change in the growth period of winter wheat in the region and help to formulate a better agronomic management practice of winter wheat.

Variation patterns of extreme precipitation and relation to ocean-atmospheric climate in Sichuan province China from 1961 to 2017

Based on daily precipitation records in the Sichuan province, spatiotemporal changes in extreme precipitation from 1961 to 2017 and the relation to ocean-atmospheric climate were investigated. The trends and their statistical significance were computed with the nonparametric Sen’s and Mann–Kendall tests. The characteristics of mutation and period were investigated with heuristic segmentation and continuous wavelet transform. The relations between extreme precipitation and ocean-atmospheric climate were diagnosed by cross-wavelet analysis. The results comprised three aspects. (1) The intensity, frequency, and duration of extreme precipitation increased in the Sichuan plateau, while the intensity and frequency of extreme precipitation decreased, but the duration of extreme precipitation did not change in the Sichuan basin. The contrary trends of extreme precipitation indices may have been influenced by the complex local geography, dramatically increased human activity, and source transportation of water vapor. (2) Temporally, the trends in extreme precipitation indices constituted slight changes in the Sichuan province. The Sichuan province experienced notable climate change because abrupt change points were observed for most of the extreme precipitation indices. Extreme precipitation was a fluctuation process from 1961 to 2017. (3) Because there was a decrease in precipitation during the warm phase periods of El Nino events and an increase during the cool phase periods of La Nina events in the Sichuan province, we show that the El Nino-Southern Oscillation (ENSO) has longer and stronger relations with extreme precipitation than the South Asian Summer Monsoon (SASM) or East Asian Summer Monsoon (EASM). The results of the present study will facilitate better decisions concerning preparedness for extreme precipitation events and management of water hazards in the Sichuan province.

Spatiotemporal Characteristics of Extreme Precipitation Regimes in the Eastern Inland River Basin of Inner Mongolian Plateau, China

In this work, we use the gridded precipitation dataset (with a resolution of 0.5° × 0.5°) of the eastern part of inland river basin of Inner Mongolian Plateau from 1961–2015 as the basis and adopt the methods of climatic diagnosis (e.g., the Modified Mann-Kendall method, principal component analysis, and correlation analysis) to analyze the spatial and temporal variations of six extreme precipitation indices. Furthermore, we analyzed the relationship between El Niño–Southern Oscillation (ENSO) events and the observed extreme precipitation. The results indicated that the gridded dataset can be used to describe the precipitation distribution in our study area. In recent 55 years, the inter-annual variation trends of extreme precipitation indices are generally dominated by declination except for the maximum precipitation over five days (RX5DAY) and the heavy precipitation (R95P), in particular, the decreasing regions of consecutive dry days (CDD) accounts for 91% of the entire basin, 17.28% of which is showing the significant downward trend. Contrary to CDD, the spatial distribution of the other five indices is gradually decreasing from northeast to southwest, and the precipitation intensity (SDII) ranges from 3.8–5.3 mm·d−1, with relatively small spatial differences. To some extent, CDD and R95P can used to characterize the extreme precipitation regimes. Moreover, the number of days with heavy precipitation (RR10), SDII, and R95P are more susceptible to the ENSO events. In addition, the moderate El Niño event may increase the probability of CDD, while the La Niña events may increase the risk of the heavy rainfall regime in the study area.

Quality Control, Homogeneity Analysis, and Trends of Extreme Precipitation Indices in Northern Cyprus

AbstractIn this study, the annual and seasonal changes in extreme precipitation indices were investigated in Northern Cyprus by using the non-parametric Mann–Kendal trend test and Sen’s slope estim...

Daily extreme precipitation indices and their impacts on rice yield—A case study over the tropical island in China

Frequent occurrences of extreme precipitation events have significant impacts on agricultural production. Tropical agriculture has been playing an important role in national economy in China. A precise understanding of variability in extreme precipitation indices and their impacts on crop yields are of great value for farmers and policy makers at county level, particularly in tropical China where almost all agriculture is rainfed. This research has studied observed trends in extreme precipitation indices (a total of 10) during 1988–2013 over Hainan island, tropical China. Mann–Kendall nonparametric test was adopted for trend detection and the results showed that most of precipitation indices showed increasing trend. Since rice is the most important staple food in Hainan island, the impacts of extreme precipitation indices on rice yields were also analyzed through simple correlations. In general, the rainy days and rain intensity in late rice growing season showed increasing trend over Hainan island. The rice yield presented ninth-degree polynomial technological trend at all stations and increasing trend for early rice yield. Late rice yield showed a decreasing trend in some parts of Hainan island. Spearman rank correlation coefficient indicated that the correlation was more pronounced between extreme precipitation indices and yields at Haikou site for early rice, and Haikou, Sanya, and Qionghai stations for late rice, respectively. Further results also indicated that there were statistically significant positive trends of R10 and R20 (number of days with precipitation ≥10 mm and precipitation ≥20 mm, respectively) from July to November at Haikou (located in north of Hainan island), and this positive trend may be a disadvantage for late rice yield. The cut-off value of extreme precipitation indices and its correlation with rice yield anomaly indices for Hainan island provided a foundation for vulnerability assessment as well as a contribution to set up contingency program under potential climate change conditions.

Extreme precipitation event over the Yellow Sea western coast: Is there a trend?

Based on dataset at 12 meteorological stations across the Yellow Sea western coast (YSWC) during 1951–2011, spatiotemporal variations of extreme precipitation events are analyzed by the methods of linear regression, Mann–Kendall test and wavelet analysis. Results show that the majority of precipitation indices exhibit decreasing trends excepting for consecutive dry days (CDD) and simple daily intensity index (SDII), which display increasing trends in most of locations, indicating that the rainfall becomes more concentrated and the intensity of precipitation increases in the last decades. Trends in extreme precipitation indices have mixed patterns over the intersection regions between Shandong and Jiangsu, where the increases in drought-flood disasters may be dramatic. Regional extreme precipitation indices in CDD and SDII show significant positive trends even though the annual total wet day precipitation (PRCPTOT) has a significant decline trend, this suggests that the increases in intensity of precipitation cannot counteract the decreases in other wet-related indices and the YSWC tends to be drier conditions. The temporal variability in seasonal indices of max 1-day precipitation (RX1day) and max 5-day precipitation (RX5day) shows that winter is becoming the wettest season. And the abrupt shift of precipitation regime in the later 1970s is detected for several indices. Factor analysis indicates that the changes in precipitation extremes, rather moderate rainfall, are of great contributions to the variability of annual total rainfall. There are multiple and overlapping cycles for most precipitation indices during 1951–2011, suggesting variations of time and frequency, while the 12–15-year cycle is prevailing for some indices. Further analyses indicate that global warming, coupled ocean-atmosphere phenomena, and urbanization are three major forcing factors affecting the variations in precipitation extremes over the YSWC during last decades.

Recent trends of extreme precipitation indices in the Iberian Peninsula using observations and WRF model results

Spatial and temporal distributions of the trends of extreme precipitation indices were analysed between 1986 and 2005, over the Iberian Peninsula (IP). The knowledge of the patterns of extreme precipitation is important for impacts assessment, development of adaptation and mitigation strategies. As such, there is a growing need for a more detailed knowledge of precipitation climate change.This analysis was performed for Portuguese and Spanish observational datasets and results performed by the Weather Research and Forecast (WRF) model forced by the ERA-Interim reanalysis. Extreme precipitation indices recommended by the Expert Team for Climate Change Detection Monitoring and Indices were computed, by year and season. Then, annual and seasonal trends of the indices were estimated by Theil-Sen method and their significance was tested by the Mann-Kendal test. Additionally, a second simulation forced by the Max Planck Institute Earth System Model (MPI-ESM), was considered. This second modelling configuration was created in order to assess its performance when simulating extremes of precipitation.The annual trends estimated for the 1986–2005, from the observational datasets and from the ERA-driven simulation reveal: 1) negative statistically significant trends of the CWD index in the Galicia and in the centre of the IP; 2) positive statistically significant trends of the CDD index over the south of the IP and negative statistically significant trends in Galicia, north and centre of Portugal; 3) positive statistically significant trends of the R75p index in some regions of the north of the IP; 4) positive statistically significant trends in the R95pTOT index in the Central Mountains Chain, Leon Mountains and in the north of Portugal.Seasonally, negative statistically significant trends of the CWD index were found in Galicia, in winter and in the south of the IP, in summer. Positive statistically significant trends of the CWD index were identified in the Leon Mountains, in spring, and in Galicia, in autumn. For the CDD index, negative statistically significant trends were seen in Valencia, in the spring, and, in Galicia and Portugal (north and centre), in summer. Positive statistically significant trends of the CDD index were found: in the east of the IP, in the winter; in the Cantabrian Mountain, in the spring; and, in the south of the IP, in summer. Regarding to the R75p index, negative statistically significant trends were found in Galicia, in winter and positive statistically significant trends in the north of Portugal, in spring and in the Central Mountains Chain and north of Portugal, in autumn. For the R95pTOT index, negative statistically significant trends were found over the Sierra Cuenca and Sierra Cazorla, in winter and positive statistically significant trends were found over the Sierra Cebollera, in winter and in Castile-la Mancha region, in spring.The results of the annual and seasonal trends of the extreme precipitation indices performed for observational datasets and the simulation forced by ERA-Interim, are similar. The results obtained for the simulation forced by MPI-ESM are not satisfactory, and can be a source of criticism for the use of simulation forced by MPI-ESM in this type of climate change studies. Even for the relatively short period used, the WRF model, when properly forced is a useful tool due to the similar results of Portuguese and Spanish observational datasets and the simulation forced by ERA-Interim.