Changes In Precipitation Extremes Research Articles

Historical Changes and Future Projections of Extreme Temperature and Precipitation along the Sichuan-Tibet Railway

Based on multiresource high-resolution in situ and satellite merged observations along with model simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), this paper first investigated historical changes in extreme temperature and precipitation during the period of 1979–2018 in areas along the Sichuan–Tibet Railway, and then projected the future changes in the frequency and intensity of extreme temperature and precipitation under the representative concentration pathways (RCPs) of the RCP 4.5 and 8.5 scenarios. This study is expected to enhance our understanding of the spatiotemporal variability in the extreme temperature and precipitation along the Sichuan–Tibet Railway, and to provide scientific basis to advance the Sichuan–Tibet Railway construction and operation. The results show that temperatures in the Sichuan–Tibet region have shown a noticeable warming trend in the past 40 years, and the increase of minimum temperature is significantly higher than that of maximum temperature in the northwest of the region. The significant increase of precipitation is mainly distributed in the northwest of the Tibetan Plateau, and there is no significant change in precipitation in other areas along the Sichuan–Tibet Railway, except in Lhasa and its surrounding areas. However, precipitation along the Sichuan–Tibet Railway has shown a remarkable decrease in the past 20 yr. The warm days and nights have clearly increased by 6 and 5 day decade−1 for 1979–2019, while cold days and nights have markedly decreased by about 6.6 and 3.6 day decade−1, respectively. In the past 20 yr, the areas with increased precipitation from very wet days and extremely wet days are mainly distributed to the north of the Sichuan–Tibet Railway, while in the areas along the railway itself the very wet days and extremely wet days are decreasing. Under the RCP 4.5 and 8.5, the temperature in the Sichuan–Tibet region will increase significantly, and the frequency of extreme high (low) temperature events in the late 21st century (2070–2099) will greatly increase (decrease) by about 50%–80% (10%) compared with occurrences in the late 20th century (1970–1999). Meanwhile, the frequency of very wet days and extremely wet days in the Sichuan–Tibet region will increase by ~2%–19% and 2%–5%, respectively, and the areas along the Sichuan–Tibet Railway will be affected by more extreme high temperature and extreme precipitation events.

Forecast and uncertainty analysis of extreme precipitation in China from ensemble of multiple climate models

Global climate change is expected to have a major impact on the hydrological cycle. Understanding potential changes in future extreme precipitation is important to the planning of industrial and agricultural water use, flood control, and ecological environment protection. In this paper, we study the statistical distribution of extreme precipitation based on historical observation and various global climate models (GCMs), and predict the expected change and the associated uncertainty. The empirical frequency, generalized extreme value (GEV) distribution, and L-moment estimator algorithms are used to establish the statistical distribution relationships and the multi-model ensemble predictions are established by the Bayesian model averaging (BMA) method. This ensemble forecast takes advantage of multi-model synthesis, which is an effective measure to reduce the uncertainty of model selection in extreme precipitation forecasting. We have analyzed the relationships among extreme precipitation, return period, and precipitation durations for 6 representative cities in China. More significantly, the approach allows for establishing the uncertainty of extreme precipitation predictions. The empirical frequency from the historical data is all within the 90% confidence interval of the BMA ensemble. For the future predictions, the extreme precipitation intensities of various durations tend to become larger compared to the historic results. The extreme precipitation under the RCP8.5 scenario is greater than that under the RCP2.6 scenario. The developed approach not only effectively gives the extreme precipitation predictions, but also can be used to any other extreme hydrological events in future climate.

Assessing the Impacts of Extreme Precipitation Change on Vegetation Activity

Extreme climate events frequently have more severe effects on terrestrial vegetation activity than long-term changes in climate averages. However, changes in extreme climate events as well as their potential risk on vegetation activity are still poorly understood. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper aims to understand the vegetation response to changes in extreme precipitation events from 1982 to 2012 using the maximum normalized difference vegetation index (NDVI) as an indicator. By applying extreme value theory (EVT), the potential risks of extreme precipitation events on vegetation activity were analyzed by conducting return period analysis. Results indicated that vegetation activity could be affected by extreme precipitation events, especially the combined effects of the frequency and intensity of precipitation extremes. For instance, vegetation activity could be enhanced in the regions with weakened intensity but increased occurrence of extreme precipitation events. In addition, we found potential risk of extreme precipitation events on vegetation activity from the results of precipitation extreme trend and return period analysis. These phenomena can be associated with the local occurrence of extreme precipitation events, different land cover types, and soil moisture cumulative effect on vegetation growth. This study stresses the importance of considering both current changes in and the potential risk of extreme precipitation events to understand their effects on vegetation activity.

Future changes in extreme precipitation in central Serbia

Abstract This paper presents the results of a study focused on the projected changes in extreme precipitation during the 21st century in Central Serbia. The changes are investigated on the basis of historical and modelled data sets of daily precipitation. The historical observation data were recorded at 18 synoptic weather stations in Central Serbia and modelled data were extracted from the regional climate model EBU-POM (Eta Belgrade University-Princeton Ocean Model) under the A1B scenario. The average number of days in a year with precipition ≥ 20, 30, 40 and 50 mm (R20, R30, R40 and R50), the share of daily precipitation above the 20, 30, 40 and 50 mm (P20, P30, P40, P50) in the total annual precipitation and the monthly distribution of these heavy daily precipitation are used as indices of changes in extreme precipitation. These indices, for the three periods 2011–2040, 2041–2070 and 2071–2100, are determined and compared with those obtained for the historical reference period 1961–1990. The results have shown that the main changes in extreme precipitation in Central Serbia will be in their spatial distribution, and the uncertainty of the occurrence of extreme events will decrease. In the future the increase will be more pronounced than the decrease of these indices. We strongly emphasize the benefit of this paper for both the prevention of natural disasters in the study area and for the improvement of the regional climate model.

How Strongly Are Mean and Extreme Precipitation Coupled?

AbstractChanges in mean and extreme precipitation are among the most important consequences of climate change. Here, we examine the relationship between the mean and three different measures of extreme precipitation over Australia, from a regional climate model (RCM) ensemble. We show that model uncertainty in mean and extreme precipitation are tightly coupled for both the present‐day climate and future changes. On the continental scale, strong correlations (0.79–0.99) are observed across models between the changes in mean and extreme precipitation. We also find that except in eastern coastal regions, precipitation statistics projected by RCM are highly predictable (up to 60%–70% of variance explained) from the mean precipitation of the global climate model (GCM) providing the boundary conditions. In coastal locations where RCMs are more accurate than GCMs for the present climate, they are less predictable, hence provide information—but this impact disappears for climate change, suggesting that improved present‐day accuracy may not carry over to climate change.

Application of Normalized Difference Vegetation Index (NDVI) for the Detection of Extreme Precipitation Change

Remote sensing has frequently been employed to monitor extreme climatic events, especially droughts, by identifying the anomalies of vegetation activity from the regional to global scale. However, limited research has addressed the performance of remote sensing on detecting extreme precipitation events. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper examines the application of the satellite-derived normalized difference vegetation index (NDVI) for detecting the change of extreme precipitation events from 1982 to 2012. The performances of three NDVI-based indices, including minimum, mean, and maximum NDVIs, were examined to capture the sensibility of vegetation activity to changes in extreme precipitation events. The results show not only common enhanced trends, but also obvious spatial discrepancies between the intensity and frequency of extreme precipitation events in the MLR-YR. As to its application on terrestrial vegetation, changes in extreme precipitation intensity coincided with that of the vegetation activity, which was represented as the maximum and the minimum NDVIs, especially the maximum NDVI. In addition, similar patterns were found between the standard deviation of the maximum NDVI and the trend of extreme precipitation intensity. Furthermore, the correlation coefficients were relatively greater between the maximum NDVI and extreme precipitation intensity than that of the minimum NDVI. Our results support the hypothesis that maximum NDVI is more suited to capture the response of vegetation activity to extreme precipitation events in the MLR-YR region, in comparison to the other two NDVI indices.

Sensitivity of Tropical Extreme Precipitation to Surface Warming in Aquaplanet Experiments Using a Global Nonhydrostatic Model

AbstractIncreases of atmospheric water vapor holding capacity with temperature (7% K−1–8% K−1, CC‐rate) can lead to increasing extreme precipitation (EP). Observations show that tropical EP has increased during the last five decades with a rate higher than in the extratropics. Global climate models (GCM's) diverge in the magnitude of increase in the tropics, and cloud‐resolving models (CRM's) indicate correlations between changes in tropical EP and organization of deep convection. We conducted global‐scale aquaplanet experiments at a wide range of resolutions with explicit and parameterized convection to bridge the gap between GCM's and CRM's. We found increases of tropical EP beyond the CC rate, with similar magnitudes when using explicit convection and parametrized convection at the resolution it is tuned for. Those super‐CC rates are produced due to strengthening updrafts where extreme precipitation occurs, and they do not exhibit relations with changes in convective organization.

Present and future diurnal hourly precipitation in 0.11° EURO-CORDEX models and at convection-permitting resolution

The diurnal cycle of precipitation (DCP) is a core mode of precipitation variability in regions and seasons where the dominant precipitation type is convective. The occurrence of extreme precipitation is often closely linked to the DCP. Future changes in extreme precipitation may furthermore, in certain regions, exhibit a strong diurnal signal. Here we investigate the present and future diurnal cycle of hourly precipitation in the state-of-the-art 0.11°C EURO-CORDEX (EC-11) ensemble and in a convection-permitting model (CPM), with a focus on extremes. For the present climate, long-standing timing and frequency biases in the DCP found in lower-resolution models persist in the EC-11 ensemble. In the CPM, however, these biases are largely absent, particularly the diurnal distribution of extremes, which the EC-11 ensemble misrepresents. For future changes to hourly precipitation, we find clear diurnal signals in the CPM and in EC-11 models, with high regional and intra-ensemble variability. The diurnal signal typically peaks in the morning. Interestingly, the EC-11 ensemble mean shows reasonable agreement with the CPM on the diurnal signal’s timing, showing that this feature is representable by models with parametrized convection. Comparison with the CPM suggests that EC-11 models greatly underestimate the amplitude of this diurnal signal. Our study highlights the advantages of CPMs for investigating future precipitation change at the diurnal scale, while also showing the EC-11 ensemble capable of detecting a diurnal signal in future precipitation change.

SSP 시나리오에 따른 동아시아 극한기후 미래전망

This study investigates the extreme temperature and precipitation indices as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We calculate 14 indices representing extreme climate over East Asia. Here, we utilized the ensemble results of NIMS-KMA (National Institute of Meteorological Sciences and Korea Meteorological Administration) climate models (UKESM1 and K-ACE) for analysis of long-term variation in present-day (1995 ~ 2014) and future (2015 ~ 2100) periods. The spatial distributions of simulated daily maximum and minimum temperatures and daily mean precipitation are comparable to those of ERA5 reanalysis data. Simulated extreme indices are well reproduced in the present-day period, although the NIMS-KMA climate models tend to underestimate annual minimum temperature extremes and overestimate extremes in precipitation intensity. In the future scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), intensity and frequency of warm temperature extremes increased for the late 21st century, but magnitude and number of cold temperature extremes significantly decreased. Changes in extreme precipitation associated with a warming climate are becoming more intense and frequent in Southern China. But the changes in precipitation duration indices tend to have high uncertainty under SSP scenarios.

Capacity of the PERSIANN-CDR Product in Detecting Extreme Precipitation over Huai River Basin, China

Assessing satellite-based precipitation product capacity for detecting precipitation and linear trends is fundamental for accurately knowing precipitation characteristics and changes, especially for regions with scarce and even no observations. In this study, we used daily gauge observations across the Huai River Basin (HRB) during 1983–2012 and four validation metrics to evaluate the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) capacity for detecting extreme precipitation and linear trends. The PERSIANN-CDR well captured climatologic characteristics of the precipitation amount- (PRCPTOT, R85p, R95p, and R99p), duration- (CDD and CWD), and frequency-based indices (R10mm, R20mm, and Rnnmm), followed by moderate performance for the intensity-based indices (Rx1day, R5xday, and SDII). Based on different validation metrics, the PERSIANN-CDR capacity to detect extreme precipitation varied spatially, and meanwhile the validation metric-based performance differed among these indices. Furthermore, evaluation of the PERSIANN-CDR linear trends indicated that this product had a much limited and even no capacity to represent extreme precipitation changes across the HRB. Briefly, this study provides a significant reference for PERSIANN-CDR developers to use to improve product accuracy from the perspective of extreme precipitation, and for potential users in the HRB.

SSP 시나리오에 따른 동아시아 극한기후 미래전망

SSP 시나리오에 따른 동아시아 극한기후 미래전망

Assessment of potential risks induced by increasing extreme precipitation under climate change

A warmer climate has caused more extreme climate events like the heatwave or extreme precipitation, which has led to a large number of lives and economic losses. In this study, we adopt historical daily precipitation from rainfall estimates on a gridded network (REGEN) and future daily projections from 10 general circulation models (GCMs) to analyze the potential risks of extreme precipitation due to changes in the magnitude and frequency. We calculate the 10-year and 100-year return levels by fitting the partial duration series (PDS) data with the generalized Pareto (GP) distribution. The potential risks are quantified in two terms: by the ratio of the magnitude to the threshold and by the exceedance frequency comparing to the theoretical value. The results show that in the future, about 46% of the world may suffer from mid or high risk of change in extreme precipitation. Most regions show higher risk due to the increased frequency of extreme precipitation events under the RCP8.5 scenario. The high risk of humid regions mainly appears under the RCP8.5 scenario and is mainly driven by frequency change, while that of arid regions appears under both the scenarios and is driven by both the frequency and magnitude change. The tropical rainforest climate areas of South America (SA (N)), the tropical savanna or tropical wet monsoon and tropical dry areas of South Asia (SA), and the subarctic climate areas of Northern Asia (NOA) may suffer more risks from the view of both magnitude and frequency changes of extreme precipitation.

Spatiotemporal nexus between vegetation change and extreme climatic indices and their possible causes of change

Climate extremes have a significant impact on vegetation. However, little is known about vegetation response to climatic extremes in Bangladesh. The association of Normalized Difference Vegetation Index (NDVI) with nine extreme precipitation and temperature indices was evaluated to identify the nexus between vegetation and climatic extremes and their associations in Bangladesh for the period 1986–2017. Moreover, detrended fluctuation analysis (DFA) and Morlet wavelet analysis (MWA) were employed to evaluate the possible future trends and decipher the existing periodic cycles, respectively in the time series of NDVI and climate extremes. Besides, atmospheric variables of ECMWF ERA5 were used to examine the casual circulation mechanism responsible for climatic extremes of Bangladesh. The results revealed that the monthly NDVI is positively associated with extreme rainfall with spatiotemporal heterogeneity. Warm temperature indices showed a significant negative association with NDVI on the seasonal scale, while precipitation and cold temperature extremes showed a positive association with yearly NDVI. The DEA revealed a continuous increase in temperature extreme in the future, while no change in precipitation extremes. NDVI also revealed a significant association with extreme temperature indices with a time lag of one month and with precipitation extreme without time lag. Spatial analysis indicated insensitivity of marshy vegetation type to climate extremes in winter. The study revealed that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and low solar radiation with higher humidity contributed to climatic extremes in Bangladesh. The nexus between NDVI and climatic extremes established in this study indicated that increasing warm temperature extremes due to global warming might have severe implications on Bangladesh's ecology and the environment in the future.

Precipitation response to climate change and urban development over the continental United States

Appropriately characterizing future changes in regional-scale precipitation requires assessment of the interactive effect owing to greenhouse gas-induced climate change and the physical growth of the built environment. Here we use a suite of medium resolution (20 km grid spacing) decadal scale simulations conducted with the Weather Research and Forecasting model coupled to an urban canopy parameterization to examine the interplay between end-of-century long-lived greenhouse gas (LLGHG) forcing and urban expansion on continental US (CONUS) precipitation. Our results show that projected changes in extreme precipitation are at least one order of magnitude greater than projected changes in mean precipitation; this finding is geographically consistent over the seven CONUS National Climate Assessment (NCA) regions and between the pair of dynamically downscaled global climate model (GCM) forcings. We show that dynamical downscaling of the Geophysical Fluid Dynamics Laboratory GCM leads to projected end-of-century changes in extreme precipitation that are consistently greater compared to dynamical downscaling of the Community Earth System Model GCM for all regions except the Southeast NCA region. Our results demonstrate that the physical growth of the built environment can either enhance or suppress extreme precipitation across CONUS metropolitan regions. Incorporation of LLGHGs indicates compensating effects between urban environments and greenhouse gases, shifting the probability spectrum toward broad enhancement of extreme precipitation across future CONUS metropolitan areas. Our results emphasize the need for development of management policies that address flooding challenges exacerbated by the twin forcing agents of urban- and greenhouse gas-induced climate change.

A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments

AbstractThe impact of climate change on future soil loss is commonly assessed with soil erosion models, which are suggested to be an important source of uncertainty. Here, we present a novel soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments. The model ensemble consists of five continuous process‐based soil erosion models that run at a daily time step (i.e., DHSVM, HSPF, INCA, MMF, SHETRAN). The models were implemented in the SPHY hydrological model and simulate detachment by raindrop impact, detachment by runoff, and immediate deposition. The soil erosion model ensemble was applied in a semiarid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3°C). Data from two contrasting regional climate models were used to assess how an increase and a decrease in projected extreme precipitation affect model uncertainty. Soil loss is projected to increase (up to 95%) and decrease (up to −30%) under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent of the projected change in annual precipitation and extreme precipitation. This stresses the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate‐change impact assessments.

A global climatological perspective on the importance of Rossby wave breaking and intense moisture transport for extreme precipitation events

Abstract. Extreme precipitation events (EPEs) frequently cause flooding with dramatic socioeconomic impacts in many parts of the world. Previous studies considered two synoptic-scale processes, Rossby wave breaking and intense moisture transport, typically in isolation, and their linkage to such EPEs in several regions. This study presents for the first time a global and systematic climatological analysis of these two synoptic-scale processes, in tandem and in isolation, for the occurrence of EPEs. To this end, we use 40-year ERA-Interim reanalysis data (1979–2018) and apply object-based identification methods for (i) daily EPEs, (ii) stratospheric potential vorticity (PV) streamers as indicators of Rossby wave breaking, and (iii) structures of high vertically integrated horizontal water vapour transport (IVT). First, the importance of these two synoptic-scale processes is demonstrated by case studies of previously documented flood events that inflicted catastrophic impacts in different parts of the world. Next, a climatological quantification shows that Rossby wave breaking is associated with >90 % of EPEs over central North America and the Mediterranean, whereas intense moisture transport is linked to >95 % of EPEs over many coastal zones, consistent with findings of atmospheric river-related studies. Combined Rossby wave breaking and intense moisture transport contributes up to 70 % of EPEs in several subtropical and extratropical regions, including (semi)arid desert regions where tropical–extratropical interactions are of key importance for (heavy) rainfall. Odds ratios of EPEs linked to the two synoptic-scale processes suggest that intense moisture transport has a stronger association with the occurrence of EPEs than Rossby wave breaking. Furthermore, the relationship between the PV and IVT characteristics and the precipitation volumes shows that the depth of the wave breaking and moisture transport intensity are intimately connected with the extreme precipitation severity. Finally, composites reveal that subtropical and extratropical EPEs, linked to Rossby wave breaking, go along with the formation of upper-level troughs and cyclogenetic processes near the surface downstream, reduced static stability beneath the upper-level forcing (only over water), and dynamical lifting ahead (over water and land). This study concludes with a concept that reconciles well-established meteorological principles with the importance of Rossby wave breaking and intense moisture transport for the formation of EPEs. Another conclusion with major implications is that different combinations of Rossby wave breaking and intense moisture transport can reflect a large range of EPE-related weather systems across climate zones and can thus form the basis for a new classification of EPE regimes. The findings of this study may contribute to an improved understanding of the atmospheric processes that lead to EPEs and may find application in climatic studies on extreme precipitation changes in a warming climate.

Updating intensity–duration–frequency curves for urban infrastructure design under a changing environment

AbstractThe intensity and frequency of extreme precipitation have increased in many regions in the past century due to climate change. Many studies have revealed that short‐duration extreme precipitations are likely to become more and more severe in many areas, thus raising a question on whether our urban infrastructures have been designed adequately to cope with these changes. Currently, Intensity–duration–frequency (IDF) curves, which summarize the relationships between the intensity and frequency of extreme precipitation for different durations, are recommended as a criterion for urban infrastructure design and stormwater management. However, climate change is thought to have invalidated the stationary assumption in deriving IDF curves, that is, current IDF curves could misevaluate future extreme precipitation in many cases. Therefore, it is necessary to update the current IDF curves by considering possible changes of extreme precipitation. In this review, we first summarize observed changes in urban short‐duration extreme precipitation and explore the physical mechanisms associated with changes. Then, we introduce two major approaches for updating IDF curves, namely the covariate‐based nonstationary IDF curves and climate‐model‐based IDF curves. Advances in these two updating approaches for IDF curves are the focus of this review. These include the investigation of physically‐based covariates with nonstationary modeling of extreme precipitation; nonstationary precipitation design strategies; and the statistical downscaling and dynamic downscaling methods for projecting future short‐duration precipitation. Finally, we summarize some future research challenges and opportunities on providing reliable projections of future short‐duration extreme precipitation and better characterize the probabilistic behavior of short‐duration extreme precipitation for IDF design.This article is categorized under: Engineering Water > Engineering Water

Sensitivity of organized convective storms to model grid spacing in current and future climates.

Mesoscale convective systems (MCSs) are complexes of thunderstorms that become organized and cover hundreds of kilometres over several hours. MCSs are prolific rain producers in the tropics and mid-latitudes and are the major cause of warm-season flooding. Traditionally, climate models have difficulties in simulating MCSs partly due to the misrepresentation of complex process interactions that operate across a large range of scales. Significant improvements in simulating MCSs have been found in kilometre-scale models that explicitly simulate deep convection. However, these models operate in the grey zone of turbulent motion and have known deficiencies in simulating small-scale processes (e.g. entrainment, vertical mass transport). Here, we perform mid-latitude idealized ensemble MCS simulations under current and future climate conditions in three atmospheric regimes: hydrostatic (12 km horizontal grid spacing; Δx), non-hydrostatic (Δx = 4, 2 and 1 km) and large eddy scale (Δx = 500 m and 250 m). Our results show a dramatic improvement in simulating MCS precipitation, movement, cold pools, and cloud properties when transitioning from 12 km to 4 km Δx. Decreasing Δx beyond 4 km results in modest improvements except for up- and downdraft sizes, average vertical mass fluxes, and cloud top height and temperature, which continue to change. Most important for climate modelling is that Δx = 4 km simulations reliably capture most MCS climate change signals compared to those of the Δx = 250 m runs. Significantly different climate change signals are found in Δx = 12 km runs that overestimate extreme precipitation changes by up to 100%.This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

Impacts of land use change on thermodynamic and dynamic changes of precipitation for the Yangtze River Basin, China

AbstractMany studies found that land use change (LUC) had great impacts on regional precipitation, due to thermodynamic and dynamic responses. However, the relative contributions of these two factors to changes in precipitation due to LUC are rarely investigated. This study quantifies the relative contributions of thermodynamic and dynamic to the changes of mean and extreme precipitation due to LUC based on simulations of the Weather Research and Forecasting (WRF) model. The Yangtze River Basin (YRB) is used as a case study, as it has experienced great LUC during the past decades. Four land use scenarios (two factual cases and two hypothetical reforestation scenarios) were used to test the sensitivity of precipitation changes to LUC. Changes in mean and extreme precipitation over the YRB for all seasons are attributed to thermodynamic and dynamic changes using 500‐hPa geopotential height and precipitation data derived from the simulations of WRF. The results show that the factual process of LUC results in a decrease in summer mean daily precipitation and precipitation extremes in most areas of the YRB (except for the middle reaches of the YRB), while the hypothetical reforestation contributes to an increase in summer mean and extreme precipitation, and the impacts of reforestation on increasing precipitation are limited. The thermodynamic change contributes to an increase in seasonal mean daily precipitation, extreme precipitation totals and occurrence frequency of precipitation extremes with contributions ranging from 94 to 102%, which is the main contributor of changes in precipitation due to LUC. The dynamic change only makes a small contribution to the change of precipitation. Because the contributions of thermodynamic can be offset by dynamic changes to changes in precipitation, it could result in minimal changes in precipitation and occurrences of precipitation extremes.

Temporal changes in extreme precipitation and exposure of tourism in Eastern and South-Eastern Spain

Climate change is modifying the arrival of tourists in the Mediterranean region of Spain, and also the occurrence of extreme torrential rainfall events in the same area, affecting the tourist potentiality of the area. These events show a good relationship with the Western Mediterranean Oscillation (WeMO) on the Mediterranean coast of Spain. From 1950 to 2016, 239 episodes of extreme torrential rainfall (≥200 mm/24 h) were recorded in the Jucar and Segura hydrographic basins. 92.1% of these events took place during a negative WeMO phase. We performed calendar and Fourier analyses to study the WeMO index (WeMOi) intraannual variability. The lowest WeMOi values tally with the highest frequency of extreme torrential rainfall events during the second 10-day period of October. A change in the calendar of the minimum values of the WeMOi was identified between 1950 and 1982 and 1983–2016. Negative WeMOi values persist until November during the second subperiod. This might be associated with a new temporal distribution of extreme torrential events of precipitation. This has given rise to greater exposure of people to torrential events in autumn. Tourism in this area faces new challenges related to the increase in tourist numbers, and also to the exposure risk to rainfall events.