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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. [ABSTRACT FROM AUTHOR]

There is an urgent need to understand and predict how extreme precipitation events (EPEs) will change at high latitudes, both for local climate change adaptation plans and risk mitigation and as a potential proxy "anticipating" the impact of climate change elsewhere in the world. This paper illustrates that a combination of non‐stationary modelling approaches can be adopted to evaluate trends in EPEs under uncertainty. A large database of daily rainfall events from 281 sparsely distributed weather stations in Finland between 1961 and 2016 was analysed. Among the tested methods, Poisson distributions provided a powerful method to evaluate the impacts of multiple physical covariates, including temperature and atmospheric circulation patterns (ACPs), on the resulting trends. The analysis demonstrates that non‐stationarity is statistically valid for the majority of observations, independently of their location in the country and the season of the year. However, subsampling can severely hinder the statistical validity of the trends, which can be easily confused with random noise and therefore complicate the decision‐making processes regarding long‐term planning. Scaling effects have a strong impact on the estimates of non‐stationary parameters, as homogenizing the data in space and time reduces the statistical validity of the trends. Trends in EPE statistics (mean, 90 and 99% percentiles) and best‐fitted Generalized Pareto parameters in the tails of the distributions appear to be stronger when approaching the Polar region (Lapland) than away from it, consistent with the Arctic amplification of climate change. ACPs are key covariates in physically explaining these trends. In particular, the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) can explain statistically significant increases in extreme precipitation in Lapland, Bothnian and South regions of Finland, particularly during summer and fall seasons. Non‐stationarity is statistically valid in the majority of observations but masked by subsampling and spatio‐temporal heterogeneity. Trends on extremes and non‐stationary generalized Pareto parameters stronger when approaching the Polar region (Lapland). Artic Oscillation (AO) and North Atlantic Oscillation (NAO) can explain statistically significant trends. [ABSTRACT FROM AUTHOR]

In the paper we focus on the notes of botanist and meteorologist Gottfried Reyger on the weather conditions in Gdańsk, Poland. In our estimation, this chronicle, covering the period from December 1721 to June 1786 (the longest weather chronicle recorded by a single person), is a reliable source of information with the potential to contribute to the understanding of climate variability in 18th‐century Gdańsk, the significant old Hanseatic city in northern Poland. The temperature and precipitation series for the period 1721–1786 were indexed against contemporary conditions using the calculated percentages of cold, normal and warm decades. The climate in the 18th century in Gdańsk was colder than nowadays; the springs were much cooler, as were the winters, while the summers were warmer. A few relatively cold periods and several warm periods were identified. The first half of the analysed period was very humid, whereas the second was quite dry. The reconstructed indexed data series were compared to annual and seasonal mean values of air temperature and precipitation derived from regular instrumental observations made in Gdańsk since 1739. The linear regression method was applied to calibrate the reconstructed index series against anomalies from the 1961–1990 average. The correlation coefficient, standard error of estimate and the root‐mean‐square error statistics were used to diagnose the quality of calibration and verification. The highest correlation between the temperature indices and the observational series was found for winter. The reconstructed series for precipitation has a smaller variability than in reality. The reconstructed values for the years prior to 1739 indicate cold years for 1725–1732 and a wet period in the 1730s. The chronicle of botanist and meteorologist Gottfried Reyger, covering the period 1721–1786, characterizes the thermal and precipitational conditions in Gdańsk, Poland. The series were indexed against contemporary conditions, compared with instrumental data and reconstructed for early non‐instrumental period. The 18th‐century Gdańsk was colder than nowadays, particularly on case of springs, while the summers were warmer. The first decades of the period were very humid, whereas the latter ones quite dry. In the figure, annual air temperature (left panel) and precipitation (right panel) reconstruction for Gdańsk for the period 1722–1785 presented in the context of observational series, 1739–1785 for air temperature and 1739–1772 for precipitation. Solid line shows observational data; dotted line shows reconstructed series. [ABSTRACT FROM AUTHOR]

Recent studies have focused on identifying the spatial coverage of heavy rainfall associated with tropical cyclones (TCs) and their remnants (TC‐events) throughout the southwestern United States from eastern North Pacific storms. Yet little is known about the larger spatial contribution of these storms among extreme floods over the western United States. This paper examines the spatial and fractional contribution of 103 TC‐events among annual maximum streamflow at 1,429 long‐term U.S. Geological Survey (USGS) streamgages with at least 30 years of daily discharge data over the 1958–2010 water years. The highest fractional contributions to annual daily maxima by these storms (~5–14%) are found in southern California, Arizona, southernmost Nevada and Utah, southern and western New Mexico, central Colorado, and Texas. While nearly 32% of the streamgages have at least one annual maximum that was generated by a TC‐event, TC‐events play a limited role in contributing to the upper tail of the flood peak distribution across the western United States. [ABSTRACT FROM AUTHOR]

In this paper we analyse the relationship between the mean and extreme precipitation for five stations in Hungary and the circulation types at the 500 hPa level, for a 52‐year period, 1958–2010. We used daily rainfall data for each station and a calendar of the daily circulation types at the 500 hPa geopotential height for Hungary based on an automatic classification scheme. A trend analysis showed that, in general, the mean and extreme precipitation rarely exhibit significant trends, similarly to previous studies. The only exception was found for the number of annual and summer rainy days in Budapest with significant negative trends (p = .05), as well as the number of days with rainfall amounts greater than the 95% probability level for Debrecen with a significant positive trend. It was found that the circulation types that are mainly responsible for the largest precipitation amounts overall show (in some cases significant) negative trends, as well as the precipitation amounts that are associated with them (Cwsw, Cse, Cwnw). In most cases, the circulation types that are prevailing during the extreme precipitation events are associated with western or almost‐western atmospheric circulations (Cwsw, Ase) and Mediterranean‐ or Atlantic‐origin depressions. [ABSTRACT FROM AUTHOR]

There are two aims of this paper: First, the relationship between daily and hourly precipitation extremes and air temperature is investigated for the validity of Clausius–Clapeyron (C–C) scaling; second, the impact of the atmospheric circulation and transport of humidity on the extreme precipitation events occurrence in Poland is analysed based on data obtained from 26 stations across Poland in the period 1951–2015. It was shown that daily‐scale extreme rainfall is less sensitive to changes in local atmospheric temperature but the hourly intensities reveal a similar behaviour at all stations showing a robust signal over the entire country. Regarding the impact of the large‐scale atmospheric circulation, three types were distinguished in cool part of the year: one connected with the positive phase of the North Atlantic Oscillation (NAO), second with a low‐pressure zone in the north and high‐pressure in the south of Europe and the northern Atlantic and third with a low over central Europe. Each time high precipitation in Poland was connected with the advection of humid air from the western sectors (SW, W or NW). In the warm part of the year three types were distinguished too, Poland was always in the scope of low‐pressure systems with the advection of warm air from the southern sectors or when the warm air from the south meets the colder air from the north. Similar localizations of low centres have been found in the case of local‐scale atmospheric circulation types during events with extreme precipitation. Both in cool and warm part of the year such events are connected with the increase of water vapour in the air. In cool season the wet and warm air masses inflow to Poland the most often from Atlantic, in the warm season—from Mediterranean and/or Black Seas. [ABSTRACT FROM AUTHOR]

The precipitation over arid regions may be low, but its environmental impacts can be very dramatic. The decadal variability in precipitation can also effectively disturb climatic environmental regimes. To advance the understanding of precipitation variability over arid regions, this paper focuses on decadal variability in summer precipitation over arid northwest China and its associated atmospheric circulations, using observation‐based data and atmospheric reanalysis during the period 1961–2016. The results show that climatologically, precipitation over this region has a strong seasonality and that 60.2% falls in summer. The summer precipitation increased 15.5 mm, accounting for 52.4% of the total annual increase in this part of China from 1961 to 2016. Decadal changes in summer precipitation occurred in approximately 1991 with a north–south difference structure modulated by large‐scale circulation anomalies over the Indian Ocean and central Asia as well as a shift in water vapour transport. In a positive phase, anticyclonic circulation anomalies occupy the Indian Ocean with cyclonic anomalies over central Asia, favouring stronger northwards moisture transport towards northwest China, and vice versa. Moreover, the significantly enhanced northwards water vapour transport from low‐latitude seas is also critical to the decadal changes approximately in 1991 summer precipitation in arid northwest China. These findings contribute to the understanding of decadal precipitation variability over arid regions, especially the increasing influence of low‐latitude circulations and moisture transport processes. [ABSTRACT FROM AUTHOR]

ABSTRACT: Extreme precipitation events are widely thought to intensify in a warmer atmosphere through the Clausius‐Clapeyron equation. The temperature‐extreme precipitation scaling was proposed to analyse the temperature dependency of short‐duration extreme precipitation and since then, the concept has been widely used in climatology. Bao et al. (2017) suggest that the apparent scaling reflects not only how surface air properties affect extreme precipitation, but also reflects how synoptic conditions and localized cooling due to the storm itself affect the scaling – implying two‐way causality. We address here critical issues of this paper and provide evidence that dew point temperature drives extreme precipitation, with the direction of causality reversed only for the storm's peak intensity. This physical inference may serve as a basis to better quantify scaling rates and to help establish the relationship between extreme precipitation and environmental conditions in the current climate, and thereby provide insights into future changes to precipitation extremes due to climate change. [ABSTRACT FROM AUTHOR]

ABSTRACT: The estimated future changes of precipitation and precipitation‐related climate indices for the Carpathian Region are analysed in this paper. Eleven regional climate model (RCM) simulations from the ENSEMBLES project taking into account the intermediate A1B emission scenario are used, hence, the analysis also includes uncertainty assessments. Validation results showed that in the target area RCM simulations overestimate precipitation throughout the year, except in summer, when underestimation occurs. In order to eliminate these systematic errors before the detailed analysis, percentile‐based bias correction is applied to the raw RCM outputs, for which the high‐quality CARPATCLIM database (1961–2010) serves as a reference. Using the bias‐corrected RCM simulations, precipitation totals and several precipitation‐related indices (describing both wet and dry climatic conditions) are calculated for the 1961–2100 time period on seasonal scale for the entire Carpathian Region, and also for five subregions (Slovakia, Ukraine, Hungary, Romania, and Serbia) within this area. The results from RCM simulations are inconsistent for some indices in some seasons, thus introducing uncertainties to the climatic projections. However, according to our results, drier summers are very likely to occur in the future, mainly in the southern parts of the selected domain. More frequent and more intense extreme precipitation events are estimated for winter and autumn, especially in the northern regions. Our conclusions suggest that the spatial distribution of precipitation is not likely to change remarkably in the future, however, the annual distribution of precipitation is projected to be restructured. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper documents the changes in climate extremes over Indonesia during the past three decades (1983-2012) based on a subset of extreme indices recommended by the Expert Team on Climate Change Detection and Indices ( ETCCDI). The extreme indices were calculated based on the quality controlled daily observational data (minimum and maximum temperature and precipitation) from 88 weather stations. Overall, we found significant and spatially coherent trends of warming in the temperature indices over Indonesia, consistent with other studies conducted at different countries within the Southeast Asia. The frequency of cool days ( TX10p) and cools nights ( TN10p) had decreased whereas warm days ( TX90p) and warm nights ( TN90p) were observed more frequently. Averaged over the country, the annual mean of daily maximum ( TXmean) and minimum temperature ( TNmean) had increased significantly by 0.18 and 0.30 °C decade−1, respectively. Other temperature indices also showed significant warming trends. In contrast, trends in the precipitation extremes indices were generally not significant and less spatially coherent. However, a tendency towards wetter conditions was observed, in agreement with the results at the global scale. The daily precipitation intensity ( SDII) had increased significantly over the country by 0.21 mm day−1 decade−1 during the period studied. At the regional scale, we observed a significant wetting trend in the annual highest daily amount ( RX1day) and the rainfall amount contributed by the extremely very wet days (R99p) in the northern part of the country. The wetting trends of a number of extreme precipitation indices were depicted prominently in December-January-February ( DJF) and/or March-April-May ( MAM) seasons, both at country and regional levels. However, for the southern region of Indonesia, a drying tendency was observed for June-July-August ( JJA), September-October-November ( SON) and MAM. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper revisits the strength and stationarity of linear statistical relationships between indices of monsoon rainfall derived from rain gauge data for three regions in tropical West Africa [West Sahel (WS), Central Sahel (CS), and Guinea Coast (GC)] and various indices describing remote variations in the ocean-atmosphere climate systems from 1921 to 2009. The results reveal that both the Atlantic Multi-decadal Oscillation ( AMO) and the Atlantic Meridional Mode ( AMM) show a positive linear correlation to Sahel rainfall. The percent variance explained ( PVE) ranges from 10 to 25%. The correlation stems from periods longer than 8 years for AMO, but AMM does show a correlation on interannual time scales for WS that was absent in the 1970s and 1980s. The PVE by El Niño Southern Oscillation ( ENSO) indices is, though statistically significant, on the order of 10% and found mainly on the interannual time scale. A strong and stable correlation with PVEs larger than 50% is found between the sea surface temperatures (SSTs) in the Atlantic 3 region ( ATL3, 0°-20°W, 3°S-3°N) and the GC rainfall. On the other hand, the correlation between ATL3 and WS rainfall changed from significantly negative to significantly positive after the 1970s. The Eastern Mediterranean SSTs are found to be significantly related to CS rainfall, especially in recent years with PVEs between 36 and 47%. Multi-linear regression analyses reveal that the relative importance of the Indian Ocean is 42% in the optimal regression model. For the CS, this value is 37% for the Eastern Mediterranean SSTs and 70% in case of the GC using the ATL3 index. However, except for the GC, non-stationarities in the correlation between the climate state indexes and West African monsoon ( WAM) rainfall suggest the need of the application of different regression models depending on the active 'teleconnection regime'. [ABSTRACT FROM AUTHOR]

The homogenization of climate observational series is a needed process before undertaking confidently any study of their internal variability, since changes in the observation methods or in the surroundings of the observatories, for instance, can introduce biases in the data of the same order of magnitude than the underlying climate variations and trends. Many methods have been proposed in the past to remove the unwanted perturbations from the climatic series, and some of them have been implemented in software packages freely available on the Internet. The Spanish project MULTITEST was intended to test their performance in an automatic way with synthetic monthly series of air temperature and atmospheric precipitation, to update inter‐comparison results from former projects, especially those of the COST Action ES0601. Several networks representing different climates and station densities were used to test a variety of homogenization packages on hundreds of random samples. Results were evaluated mainly in the form of root mean squared errors and errors in the trend of the series, showing that ACMANT, followed by Climatol, minimized these errors. However, other packages performed also relatively well, even outperforming them when there were simultaneous biases of the same sign in most or all the test series. [ABSTRACT FROM AUTHOR]

This paper analyses the daily precipitation data recorded for the last 75-80 years in SE Spain. Prior to statistical analysis, homogeneity tests were performed to determine the usefulness of the data (recorded in six pluviometric stations). If the data were homogeneous, the Mann–Kendall test was performed to detect monotonic trends for variables such as total precipitation, number of days with precipitation greater than 1, 20 or 40 mm, number of consecutive dry days and number of consecutive wet days. Moreover, the linear tendency was calculated and accepted (or rejected) by performing a Student's t-test of the calculated residual values. The results showed, on average, a clear change in precipitation patterns for the last 20 years. Annual rainfall had decreased, with values ranging from 0 to 15%, dry periods had increased in length, and the number of rainy days had decreased (especially when high daily precipitation was considered). This latter notion did not exactly concur with the conclusions of the Intergovernmental Panel on Climate Change (IPCC) 2014 Synthesis Report related to the study area. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper analyses the influence of different types of El Niño-Southern Oscillation ( ENSO) events on South American precipitation under a climate change scenario. We use two sub-selections of Coupled Model Intercomparison Project Phase 5 (CMIP5) models that have a good representation of teleconnections to the region, albeit with reduced magnitude anomalies. Comparing historical simulations and the RCP 8.5 scenario experiments, after removing the trend in the mean due climate change, the sub-ensemble means show similar global sea surface temperature anomalies and South American precipitation anomaly patterns in the future. No robust changes in the pattern or magnitude of precipitation anomalies are found, despite significant ENSO-related shifts in the Pacific basin, as highlighted in other studies. However, if the models are analysed individually, some show relatively strong changes in ENSO-related precipitation anomalies for both canonical and Modoki events. We show that, in individual models, tropical teleconnection changes associated with ENSO are primarily driven by changes in the magnitude of ENSO-related circulation but with no agreement on the sign. Increases in background moisture, which have been hypothesized to drive an intensification of ENSO-related precipitation anomalies, are of secondary importance. [ABSTRACT FROM AUTHOR]

ABSTRACT The temporal concentration of precipitation may be characterized using several methods. For climate-scale precipitation, concentration measures are usually performed by means of dimensionless indices such as the Gini index ( GI) or the Theil index. For the purposes of the present paper, a set of 66 409 daily time series from around the world were analysed to estimate the climatic concentration of precipitation. To this end, some of the most widely used indices were tested, i.e. the Theil index, the Gini index, the concentration index, the classic n index and an ordered version of the n index. Results show a strong connection between several indices, mainly between the GI and the ordered n index. The high correlation of these indices ( R = 0.98) reflects a theoretical connection between the shape and integration of the Lorenz curve. With regard to spatial distribution, the three main indices present the same relative areas of high and low concentration. The high temporal concentration of precipitation is generally linked to the rapid pace of physical processes such as convection in areas with a high degree of insolation and warm seas. The low temporal concentration of rainfall can be interpreted as a consequence of regular patterns (maritime flows or highly recurrent storms). A relationship between the number of rainy days and concentration indices was noted; however, their correlation depends on the region analysed. [ABSTRACT FROM AUTHOR]

The selection of general circulation models (GCMs) with high capability to represent the past and likely future climate for a specific geographical location is a crucial step to assess impacts of climate change on different sectors. This study included pool of 105 and 78 GCMs for representative concentration pathways (RCPs) 4.5 and 8.5, respectively, from Coupled Model Intercomparison Project—Phase 5, applied an advanced envelope‐based selection approach to select representative GCMs for the Koshi river basin in China and Nepal at short‐term (2016–2045), mid‐century (2036–2065) and end‐of‐century (2071–2100) periods, and developed range of possible future precipitation and temperature scenarios with high resolution downscaled data (10 × 10 km2), which is the novelty contribution of the study. Considering RCP4.5, average annual precipitation is expected to increase by 0–16%, 4–23% and 4–24% in the short‐term, mid‐century and end‐of‐century periods, respectively. Using RCP8.5, equivalent predictions are 6–20%, 6–36% and 13–49% in the short‐term, mid‐century and end‐of‐century periods, respectively. Average annual temperature is expected to increase, but with higher increases during winter than in the monsoon period. Considering RCP4.5, average annual temperature is expected to increase by 1–1.4°C, 1.3–1.9°C and 1.6–2.8°C in the short‐term, mid‐century and end‐of‐century periods, respectively. Similarly, using RCP8.5, equivalent predictions are 1–1.6°C, 1.8–2.9°C and 3.1–5.6°C in the short‐term, mid‐century and end‐of‐century periods, respectively. The ensemble mean of absolute change in average precipitation and temperature projects that High Himalaya and Tibet regions are more sensitive to climate change considering precipitation and temperature, respectively. The results also suggest that GCMs selection for a catchment varies with climate scenarios and specific future time periods. [ABSTRACT FROM AUTHOR]

Convection‐permitting models (CPMs) provide a better representation of sub‐daily precipitation statistics and convective processes on both climate and weather forecasting timescales. This study aims to establish what horizontal resolution and physical process settings are suitable for the first ensemble of convection‐permitting climate projections for the United Kingdom. For this purpose, 12‐year‐long simulations were run using three different convection‐permitting resolutions (grid spacing of 4 km, 2.2 km and 1.5 km) each with several configurations. The focus is on the ability to represent sub‐daily precipitation due to its potential for high impacts on society through flooding. The analysis shows that the use of a finer grid spacing within the convection‐permitting regime improves the representation of sub‐daily precipitation but the added value decreases as the grid becomes increasingly finer, while the computational costs substantially increase. Changes in the representation of physical processes can have as much impact as the grid spacing and can lead to similar differences in the diurnal cycle as between convection‐parametrized models and CPMs. Although the 4km model shows some key deficiencies that make it unreliable for climate projection, the 2.2km model performs as well as the 1.5km model for most of the metrics examined with considerable benefits in terms of computer cost. The optimal configuration and resolution identified here is being used for an ensemble of simulations run within the UK Climate Projections 2018 (UKCP18) project, which allows, for the first time, an estimate of uncertainty in future changes at convection‐permitting scale and providing more reliable climate change projections at local and hourly scales. [ABSTRACT FROM AUTHOR]

Results from the multiple‐realization, single‐model ensemble called "d4PDF" were used to generate hydroclimate indices for present and future climates over the Indochina region. The model performed reasonably well in capturing the reference precipitation characteristics of the present climate (1951–2010), in particular the seasonal pattern (e.g., JJA and SON) and intensity‐based indices such as SDII, R95p, Rx1D, and Rx3D. Under the +4 K future simulation conditions for 2051–2110, comprising six prescribed sea‐surface temperature scenarios, substantial and statistically significant increases in precipitation frequency (R10 and R20) and intensity (SDII, Rx1D, and Rx3D) were projected over the Indochinese Peninsula with a high degree of consistency. However, there were greater uncertainties in the changes significance of mean precipitation either during early dry‐season (DJF) or late monsoon (SON) indices demonstrated by results of the parametric U test in some river catchments, such as the Chao Phraya, Red River, central Mekong, lower Irrawaddy, and Salween Basins, where the projection consistencies in a positive change direction were less than 50%. Comparison of basin‐wide empirical probability distributions of precipitation indices pointed to a robust increase in the frequency of the occurrence of heavy precipitation in intensity indices (e.g., Rx1D, Rx3D, and SDII). The relationship between d4PDF precipitation and total runoff generation outputs from the land surface component was investigated. The results show a high degree of temporal correspondence across the region under the present climate in several seasonal and intensity indices, except during the dry period (DJF and MAM). Finally, we found that εP(P, R) of the annual and seasonal climatological indices of the future climate were always positive and larger than unity, with a median εP(P, R) of 1.28–2.04. The results strongly reaffirm the role of rainfall as the main driver of runoff changes due to its faster response relative to change in precipitation at the Indochina Region. [ABSTRACT FROM AUTHOR]

Precipitation is one of the most important atmospheric variables to assess, particularly in the context of climate change. This study evaluates future changes in precipitation over the Iberian Peninsula (IP) under the RCP8.5 scenario. Changes are assessed for two future climate periods namely (2046–2065) and (2081–2100), relative to a recent reference climate (1986–2005). Here we introduce the concept of precipitation episodes (PEs) and estimate their statistical properties for the present climate and, their changes for future climate scenarios. PEs are defined by considering a full range of durations as well as intensities. This constitutes a novel approach to estimate changes with relevance, for example, for water resources applications. The climate simulations are performed with the Weather Research and Forecast (WRF) model. These are compared with an ensemble of other similar simulations from the Coordinated Downscaling Experiment initiative. This was done to evaluate the performance of the WRF model and also to estimate uncertainty of the derived future projections. Since models may present systematic errors, results from all simulations were previously bias corrected relative to observations using the same quantile mapping method. Under climate change, a great part of the region is expected to experience reduced annual precipitation of approximately 20–40% and reaching 80% in summer by the end of the XXI century. For the PEs, a large reduction in the average number of days and duration of all types of PEs is expected across all seasons and regions. The average intensity of episodes is projected to increase in winter and spring and decrease in summer. These results imply that climate change will likely influence precipitation and precipitation extremes in the 21st century, mostly in southern areas. These, together with projected warming may amplify desertification already taking place in the southern regions of the IP and cause stresses to water resources. [ABSTRACT FROM AUTHOR]

This study examines the 1950–2017 temporal changes in climate extremes in Israel, which is located in the East Mediterranean (EM), a region which suffers from a scarcity of long and reliable datasets. It is well known that most long‐term records are affected by artificial shifts most commonly caused by station relocation, instrumental modification and local environmental changes. Therefore, for the first time, a thorough homogenization (detection and correction) routine was developed and implemented in the long‐term records. Consequently, a new daily adjusted dataset has been generated, including 34 temperature stations and 60 precipitation stations. Based on this comprehensive dataset, 38 extreme indices recommended by the Expert Team on Climate Change Detection and the Expert Team on Sector‐specific Climate Indices have been calculated. These indices will help various sectors to plan properly mitigation actions and adaptation for climate change, in addition to facilitating future studies for the EM. The results showed highly significant changes in temperature extremes associated with warming, especially for those indices derived from the daily minimum temperature (TN, 1950–2017), whereas the maximum temperature (TX) exhibited a similar increasing magnitude of the TN (~0.55°C/decade) in the last 30 years. The warming trends, which are non‐monotonic, seem to have been particularly strong since the early 1990s. The coastal area is characterized by higher heat stress during the nighttime, while mountains exhibit a strong tendency towards increasing temperatures during the noon hours. A reduction in the total precipitation amount and in the number of wet days with a tendency towards more intense wet days was found. Although all the regional trends of the precipitation indices were not statistically significant (p ≤.05), they showed a fine spatial coherence. [ABSTRACT FROM AUTHOR]

The ability of the seven CMIP5 models to simulate extreme precipitation events over Iran was evaluated using the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN‐CDR) data set. The criterion used to select the CMIP5 models was the availability of historical daily precipitation data (PERSIANN‐CDR) for the retrospective period 1983–2005, as well as future projections for the three representative concentration pathways emission scenarios (RCP2.6, RCP4.5, and RCP8.5) and spatial resolution higher than 2 × 2°. This is the first study to focus on extreme precipitation climate model simulations over Iran that includes high topography and different climates. The results show that CCSM4 has the highest correlation coefficients (CC = 0.85) and lowest root‐mean‐square error (RMSE = 73.6 mm) compared to PERSIANN‐CDR for the mean annual precipitation. However, HadGEM2‐ES shows the best (highest CCs between 0.67–0.79 and almost the lowest root‐mean‐square errors [RMSEs] compared to PERSIANN‐CDR) performance for intensity indices; MIROC5 ranked seventh (least CCs and almost the highest RMSEs) among the selected models. The results show that BCC‐CSM1‐1‐M captures maximum consecutive dry days (CDD) better than the other models. The probability matching method (PMM) is used to bias‐correct daily precipitation events from CMIP5 models with respect to the PERSIANN‐CDR estimations. All the model performances designed to capture the mean annual precipitation, as well as extreme intensity indices, improved after correction. The ensemble, constructed from the bias‐corrected model simulations using multiple linear regression (MLR), has the best performance for simulating the mean annual precipitation and extreme indices (CCs between 0.82 for consecutive wet days [CWD] and 0.93 for the mean annual precipitation) compared to the PERSIANN‐CDR estimations. Among the seven selected models, CCSM4 has the highest ranking (CCs between 0.70 for CWD to 0.91 for mean annual precipitation) after bias correction. [ABSTRACT FROM AUTHOR]

Climate change and urbanization collectively influence precipitation changes. However, their separate potential contributions to precipitation changes are not well understood due to their complex interactions. Hence, a "trajectory"‐based method was used to separate their potential contributions across national, regional and local scales in China. Precipitation changes in non‐urban regions can be regarded as representing the influence of climate change and can serve as a reference for isolating precipitation changes due to urbanization in urban areas. Our results revealed that climate change was the dominant factor for precipitation trends, while urbanization exhibited a relatively weak influence, especially for extreme precipitation at the national scale. At the regional scale, the impacts of urbanization on precipitation became more significant. About 20.2 and −30.6% of positive and negative trends in total precipitation originated from urbanization. At the local scale, the potential contribution of urbanization was strongly correlated with local environmental characteristics. Although there were differences in the potential contributions of climate change and urbanization at national, regional and local scales, climate change was the dominant factor for precipitation trends and urbanization acted as a regulator to drying or wetting due to precipitation under climate change. In general, urbanization causes a greater impact on total precipitation than on precipitation extremes. Due to this, attribution approach is static and broad‐based and does not render the level of confidence that is needed for scale‐aware attribution, future studies are needed to understand the physical mechanisms of impacts of local environment changes on precipitation trends at different geographical locations over China. [ABSTRACT FROM AUTHOR]

Projections of climate change impacts over Europe are derived using a new quantile–quantile adjustment method. E‐OBS high‐resolution gridded data sets of daily observed precipitation and 2‐m surface minimum and maximum temperatures have been used as the current climate baseline. For projections, the same meteorological variables have been obtained from a set of regional climate models (RCMs) integrated in the EURO‐CORDEX project, and by considering the RCP4.5 and RCP8.5 future emissions scenarios. To enhance the reliability of RCM data at local scale, new developments of a previous quantile–quantile adjustment have been applied to the simulated regional scenarios. This method focuses not only on the bulk spectrum of the cumulative distribution functions but also on its tails. Results show an overall improvement in reproducing the present climate baseline when using calibrated series instead of raw RCM outputs. Next, we have used these locally adjusted series to quantify the climate change signal through a number of annual and seasonal indicators. A significant increase of the minimum and maximum temperatures in all seasons is projected over Europe, being more marked in the Mediterranean for summer and autumn. Prospects on future seasonal and annual changes in precipitation are more diverse, showing an overall decrease in southern Europe and the Mediterranean, while precipitation is expected to increase towards the north of the continent. With these sources of information at hand, including and accounting for the identification of the most vulnerable geographical areas, policy makers and stakeholders can respond more effectively to the future challenges imposed by climate change. [ABSTRACT FROM AUTHOR]

This study examines potential benefits of performance‐based multi‐model ensembles (MMEs) in projecting the impacts of climate change on extreme precipitation indices over East Asia (EA) using the data from 19 GCMs in the coupled model intercomparison project 5 (CMIP5). The Taylor skill score is adopted as the measure of the model skills in simulating the spatial and interannual variability of the selected extreme precipitation indices over four EA regions. The overall rank based on the total skill score (TSC) is used to construct two skill‐based MMEs, MME of high‐skill, MMH (MME of low‐skill, MML) that include the top (bottom) seven models, in addition to the simple ensemble of all 19 GCMs (ENS). Inter‐GCM consistency is measured using the signal‐to‐noise ratio (SNR). In the present‐day period, MMH yields higher skill scores than MML and ENS for almost all extreme precipitation indices as well as regions. Regional variations in biases, inter‐model consistency, and TSC are large. The inter‐model consistency is highest for Northern China and Manchuria and is lowest for Southern China. The most notable differences in the key properties of climate change signals from the three MMEs among the three ensembles are that the climate change signals from MMH and ENS exceed the 90% significance level in much larger areas than those from MML. However, the differences in the climate change signals between MMH and MML are generally below the 90% significance level. The SNR of the projected climate change signals shows that MMH yields more consistent climate change signals than ENS/MML. Both the SNR differences and the area in which statistical significance exceed the 90% level suggest that constructing climate change signals from a group of higher‐skill models may yield more reliable projections than constructing MMEs from the entire models or a group of lower‐skilled models. The domains used in the study (SOUTH: 110°–140°E, 20°–30°N, MIDDLE: 110°–140°E, 30°–40°N), NORTH: 110°–140°E, 40°–50°N, EA: 110°–140°E, 20°–50°N) [ABSTRACT FROM AUTHOR]

Spatial and temporal patterns of trends in annual and seasonal precipitation over Germany during 1951–2013 were analysed using the ensemble empirical mode decomposition (EEMD) method. Three widely used and recognized high‐resolution observation‐based gridded precipitation products, the Climatic Research Unit (CRU) time‐series data, Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis data and the EU‐FP6 project ENSEMBLES derived data set (EOBS), were used and compared. Comparison among different products showed that the CRU used a considerably lower number of gauge stations (maximum 36) in the construction of gridded product over Germany and should be used with great caution for other applications, and overall CRU presented less precipitation and smaller inter‐annual variability; GPCC and EOBS agreed well in the spatial and temporal distribution of seasonal and annual precipitation, as well as the identified trends. The spatiotemporal analysis of trends showed that trends in precipitation during 1951–2013 were, in most cases, highly nonlinear and varying over time. In particular, the spring, summer and autumn precipitation showed large variations in trends. Therefore, the assumption of linear trends on which previous studies were based is invalid. Annual precipitation showed increasing trends in over 66% of Germany (particularly northern and eastern Germany), and the magnitude of increasing trends were generally enhanced over time, e.g. GPCC showed that the average magnitude of increasing trends rose from 6.3% for the 1951–1980 period to 12% for the 1951–2013 period. There were considerable spatial and temporal variabilities in trends in seasonal precipitation totals over Germany. This study is among one of the first studies applying the EEMD method to a comprehensive analysis of time‐varying trends in precipitation over Germany, which is expected to improve our understanding of the complex and nonlinear regional climate system. Spatial and temporal patterns of the EEMD‐derived trend of the four seasonal precipitation totals (DJF, MAM, JJA, SON; the trend is presented as the percentage of the climatology mean during the whole period 1951–2013 for easy interpretation and comparison) from EOBS for five different periods, with ending years of 1980, 1990, 2000, 2010 and 2013. [ABSTRACT FROM AUTHOR]

The arid and semi‐arid areas in Central Asia have scarce water resources and fragile ecosystems that are especially sensitive and vulnerable to climate change. Reliable information regarding future projections of change in climate is crucial for long‐term planning of water resources management and structural adjustment of agriculture in this region. However, the low‐density meteorological observation network brings great challenges for investigating the effects of climate variations. In this study, variations of precipitation and temperature in Central Asia were examined by a combination of gridded climate dataset of the Climate Research Unit and the latest general circulation models (GCMs) under a representative concentration pathway 4.5. Three downscaling methods, Delta, Advanced Delta, and Bayesian model averaging (BMA) methods, translate the coarse GCMs to local climatic variations for the period 2021–2060 relative to 1965–2004. Major results suggested that the Advanced Delta and BMA methods outperformed the Delta method in precipitation downscaling. Projected precipitation exhibited a general increasing trend at a rate of 4.63 mm/decade for entire Central Asia with strong spatiotemporal heterogeneity. While a declining trend was observed in the southwestern and central parts of Central Asia in summer. The projected temperature was revealed an obvious ascending at 0.37°C/decade, while the warming rate accelerated in higher latitude and mountainous areas. [Correction added on 03 December 2018, after first online publication: The preceding statement has been corrected in this version.] The surface land coverage had significant effects on the variations of precipitation and temperature, respectively. The driven factors of local climate were suggested by analysing the relationships between climate variations and large‐scale atmospheric circulation fields anomalies. The findings of this study aims to provide useful information to improve our understanding for future climate change and benefit local decision makers. The performance of three downscaling methods in terms of precipitation and temperature from general circulation model (GCM) outputs were compared in this study. The relationships between climatic variations and different land cover types were detected based on Land‐Use and Land‐Cover Change (LUCC) and NDVI datasets. The possible drivers of local climatic variations were also suggested by analysing the relationships between local climatic variations and large‐scale atmospheric circulation fields. [ABSTRACT FROM AUTHOR]

The aim of this study is to explore the long‐term trends in the distribution of global monsoon precipitation over recent decades using the Global Precipitation Climatology Project (GPCP) data set. In addition, the potential4 mechanisms are examined by applying the atmospheric moisture budget decomposition method to the outputs from the ERA‐Interim medium‐range weather forecasting reanalysis produced by the European Centre for Medium‐Range Weather Forecasts (ECMWF). Changes in global monsoon precipitation are primarily thermodynamically caused by changes in specific humidity and dynamically caused by changes in circulation, as well as by changes in moisture transport that are driven by transient eddies and local evaporation. The results show that the increasing trends in global summer monsoon precipitation from 1979 to 2016 were dominated by contributions from the southern Asian, South African, and North American monsoon regions and were driven by the response of atmospheric circulation to the enhanced east–west thermal contrast in the tropical Pacific. We find that changes in the sea surface temperature (SST) patterns promote increased low‐level vertical velocities in monsoon regions, leading to moisture convergence through divergent circulation anomalies when combined with the climatological humidity field. Hence, the processes result in increasing trends in monsoon precipitation. In addition, evaporation makes increasing contributions to monsoon precipitation throughout the world, except in the South American monsoon region. Moreover, subtropical regions in the East Pacific (the Atlantic) may be major sources of water vapour that have supported increases in precipitation over the southern Asian and North American monsoon regions (the South African monsoon region) in recent decades. Linear trends in (a) precipitation, (b) the moisture convergence term, (c) evaporation, and (d) residual term (precipitation minus the divergence of vertically integrated moisture transport term and evaporation) in local summer (May–September in the Northern Hemisphere and November–March in the Southern Hemisphere) from 1979 to 2016 (unit: mm day−1 year−1). The black curves depict the monsoon domains. Stippled regions indicate statistical significance at the 95% level or higher, as determined using the Mann–Kendall trend test. [ABSTRACT FROM AUTHOR]

This article proposes to use the Köppen classification to evidence climate change in Brazil. To do so, the average monthly temperature and precipitation data were computed for a set of 208 stations, representative of the climatic diversity of Brazil for the period from 1964 to 2015. The originality of our approach is not only to look at the shift between the averages of two references periods but also to observe how each year can be classified using Köppen's classification; thus, we defined "annual climate types" (ACT) and established the frequency of ACTs for each station and each period of 26 years: 1964–1989 and 1990–2015. The statistical and cartographic treatment of this information makes it possible to define the limits of the climates of Brazil and look at its evolution showing the diversity of regional situations in Brazil. The results show that 35 stations (17%) changed from the average Köppen's type, with significant regression of wet tropical types (Af and Am) and temperate types (C). On the other hand, the tropical (Aw), arid and semi‐arid (B) types progress between the two periods showing significant modifications of the climatic limits in Brazil: extension of aridity in the northeast of Brazil and increasing extinction of tropical types upon temperate climates in the south of the country and upon rainy types in the south of the Amazon. These results are consistent with other studies and illustrate the potential for climate change and variability monitoring using a simple classification method. The Köppen's classification is very often used in climatology. However, almost all the works use it on average data over periods of 20 or 30 years, thus erasing the inter‐annual variability of climate. The originality of our study is to use this classification on an annual scale to calculate frequencies of "types of annual climate" for two periods and to compare them. The study focuses on Brazil, which presents two additional interests: such a frequency approach has never been realized there to study climate change; the diversity of climates and changes observed in this country makes it possible to test the robustness of the method on different climates (from equatorial to semi‐arid and temperate types). In the figure, frequency of TCA per station for the period 1990–2015. [ABSTRACT FROM AUTHOR]

In the present study, four different bias correction methods are assessed in improving the precipitation output from a set of two regional climate simulations for 1971–2005 period. The simulations come from Coordinated Regional Climate Downscaling Experiment over South Asia (CORDEX‐SA). The bias correction methods applied here are linear scaling (Scaling), empirical quantile mapping (EQM), power transformation (PTR) and local intensity scaling (LOCI). All the bias correction techniques show skill in improving the model results, but there are clear differences in the degrees of success depending upon the characteristic of precipitation studies—like seasonal mean, seasonal extremes or inter‐annual variability. Most of the methods show equivalently high ability in correcting the seasonal mean precipitation values; however, there also exist residual biases which vary spatially over India. The largest reduction in bias was observed for the frequency of dry days and precipitation on very wet days, which are significantly altered after adjustment by EQM and PTR. It is found that distribution‐based EQM method is more skilful followed by PTR and LOCI in most of the cases including correction of frequency‐based indices (e.g., dry days number and inter‐annual variability). (a) Climatology of JJAS mean precipitation (mm/day) (1971–2005) from (A) IMD, (B) uncorrected values from RCA4, (C–F) same as (B) but bias corrected by different methods, respectively, scaling, EQM, PTR and LOCI. (b) Same as (a) but their biases against IMD. [ABSTRACT FROM AUTHOR]

Frequency analysis of precipitation extremes is significant for the selection of design rainfalls, which are essential inputs for the design of water infrastructure projects, especially when the climate has changed. Therefore, the objective of this study was to propose a framework for more reasonably analysing the frequency of extreme rainfalls. The proposed framework consists of a maximum likelihood estimate (MLE) method for analysing the parameter trends, a hydrological variation diagnosis system to determine abrupt change times, generalized extreme value (GEV) and generalized Pareto distribution (GPD) models for frequency analysis of precipitation extremes, and an ensemble‐methods approach for choosing the most appropriate distributions. The methodology was successfully implemented using a 52‐year time series (1963–2014) of rainfall data recorded by eight rain gauges in Chengbi River basin (south China). The results show that the rainfall series mutated in 1993 and that the entire data set could be divided into two slices (1963–1992 and 1993–2014). Climate change was found to have some impacts on the precipitation extremes: the extreme rainfall value and the parameters of GEV and GPD were variable in the context of climate change. Furthermore, the GPD distribution model outperformed the GEV distribution model. The location of Chengbi River basin and the distribution of the rainfall stations, and the representative rainfall stations are shown as red stars. [ABSTRACT FROM AUTHOR]

Drought is viewed as a naturally recurring phenomenon in many Australian agricultural systems. Identifying regional changes in frequency and severity of drought induced by climate change is required to develop regionally specific adaptation strategies. In this study, we provided a first look at the impacts of climate change on 21st century drought characteristics over the New South Wales wheat belt of southeastern Australia. These impacts were assessed from an ensemble of 28 statistical downscaled global climate models under representative concentration pathway (RCP8.5). A modified relative standardized precipitation and evapotranspiration index (rSPEI) at the seasonal scale (3 months) was used to analyse temporal and spatial changes in drought. Results indicated that there was a tendency towards more frequent and severe winter–spring droughts over the study area. Moreover, winter–spring drought prone areas were expected to expand from west to east. Until the end of the 21st century, more than half the wheat belt would be vulnerable to winter–spring drought. The combined effects of reduced precipitation and increased temperature during future winter and spring seasons were the main reasons causing these changes of drought. In addition, summer and autumn droughts would have both slight temporal and spatial changes across the study region. This study also revealed that traditionally dry areas would likely experience an increased frequency of drought compared to wetter areas when subjected to a same increase in temperature or decrease in precipitation. Furthermore, the western part of the wheat belt might be unsuitable for winter crops in the future, or at least exposed to an increased risk of variable yield and would require a gradual transformation which might include summer crops or pastures. Investments in cropping land should be focused on the east part of the wheat belt to achieve more consistent financial returns. Drought prone areas were identified in the study region using the modified drought index, rSPEI. Spring and winter drought prone areas were likely to expand remarkably. By the end of the 21st century, over half of the study area was at a high risk of suffering spring and winter drought. Summer and autumn drought prone areas were primarily in the southwest and northwest and might only experience slight changes. [ABSTRACT FROM AUTHOR]

Five extreme precipitation indicators were calculated on an annual basis for 1890 through 2013 and analysed to determine spatial patterns and temporal trends in the frequency and magnitude of observed extreme precipitation events in Kansas located in the central United States. Indicators were selected from the list of the World Meteorological Organization–Commission for Climatology (WMO–CCL) and the Research Programme on Climate Variability and Predictability (CLIVAR). The indicators included the number of days with precipitation greater than or equal to 10 mm/day (R10), maximum number of consecutive dry days (CDD; days with precipitation lower that 1 mm), maximum 5‐day precipitation total (R5D), and simple daily intensity index (SDII) which is the annual precipitation total divided by number of days with precipitation greater than or equal to 1 mm, and the fraction of annual total precipitation due to events exceeding the 95th percentile (R95T) based on the period 1961–1990. Positive trends in the results were found for a majority of stations for R10, R5D, SDII, and R95T. Consecutive dry days was the only index that had a negative trend at a majority of stations. Spatial pattern analysis indicates greater changes in frequencies and magnitudes for eastern Kansas. Results from this study highlight observed climate shifts in precipitation patterns with a tendency towards greater and more frequent extreme precipitation in eastern Kansas and a tendency towards drier conditions in western Kansas. These hydroclimatic adjustments can produce costly impacts in areas that include flood management, hydraulic structures, water availability throughout the year, agricultural production, ecosystems, and human health. Results from five extreme precipitation indicators highlight observed climate shifts in precipitation patterns with a tendency towards greater and more frequent extreme precipitation in eastern Kansas and a tendency towards drier conditions in western Kansas. The increasing trends for the wet condition indicators, particularly in the eastern Kansas, emphasize the necessity to update water management techniques and maintain water control structures adequately in a variable and changing climate. Western Kansas is faced with prolonged strings of dry weather and a lack of enough water in the growing season has resulted in water withdrawals from underground resources. [ABSTRACT FROM AUTHOR]

Multi‐member ensembles of climate models are used to study the role of internal climate variability and its potential impact on climate change impact studies. The reliability of such ensembles with respect to representing the internal climate variability is generally implicitly accepted. Using the latest version of the Climate Research Unit (CRU) data set as a baseline, this study verifies the reliability of multi‐member ensembles in estimating the internal precipitation and temperature variability at the multi‐decadal scale. To achieve this, multi‐decadal variability calculated using climate model multi‐member ensembles is first compared to that calculated using CRU data. The inter‐member variability of a single climate model is then compared to the multi‐decadal variability of CRU precipitation and temperature. Three climate models, with the number of members ranging between 5 and 40, are used to investigate whether the reliability is dependent upon the number of members of a climate model. The results show that multi‐member ensembles are capable of capturing the observed spatial pattern of multi‐decadal variability for both precipitation and temperature at the global scale. However, multi‐member ensembles perform better over regions with smaller variability. For the variables and timescale investigated, all three multi‐member ensembles show similar performances, suggesting that a five‐member ensemble may be sufficient to estimate the internal multi‐decadal climate variability for the chosen variables. Overall, this study indicates that the multi‐member ensemble of a climate model can be used to estimate the internal climate variability of annual and seasonal precipitation and temperature at the multi‐decadal and regional scales, if long historical records are not available. Climate model multi‐member ensembles are capable of capturing the observed spatial pattern of MDV for both precipitation and temperature. Climate model multi‐member ensembles perform better over regions with smaller variability. Performance of multi‐member ensembles did not depend on the number of members within each ensemble for annual and seasonal precipitation at the multi‐decadal scale. In the figure, multi‐decadal variability of mean annual precipitation estimated using CRU data and different climate model ensembles. Different colors represent the standard deviation of precipitation in millimeters. [ABSTRACT FROM AUTHOR]

In this study, we assess whether dynamical downscaling using a regional climate model (RCM) would provide added value against the driving global climate model (GCM) and whether a statistically bias‐corrected GCM could be used as an alternative to a bias‐corrected RCM for assessing the hydrological response to climate change. The target region is the Chungju Basin in Korea, which is characterized by complex geographical features. The analysis focuses on runoff simulations driven by raw outputs and bias‐corrected outputs from the HadGEM2‐AO and RegCM4, which are used to generate national standard climate change scenarios throughout the Korean Peninsula. Statistical methods, such as linear scaling and quantile mapping, improve the performance in precipitation simulations and effectively correct the systematic biases seen with the climatological means of the HadGEM2‐AO and RegCM4. Although there is no relevant difference between the bias‐corrected HadGEM2‐AO and RegCM4 in terms of long‐term averaged climatology, the bias‐corrected RegCM4 performs better in capturing the dominant mode of runoff variability and hydrological extremes (e.g., floods measured by 1‐day maximum runoff and droughts measured by the standardized runoff index). Because the magnitude of the bias correction factor tends to influence the preservation of future change signals derived from raw and bias‐corrected outputs, the HadGEM2‐AO, which requires a large bias correction factor to compensate for poor performance, produces future changes in high flows with low coherence between the raw and bias‐corrected projections. A distributed hydrological model (VIC) at the basin level is performed with different meteorological input to assess whether RCM provides added value against driving GCM and whether statistical bias correction is sufficient to improve GCM projections. GCM produces future changes in yearly maximum 1‐day runoff with low coherence between the raw and bias‐corrected projections due to a large magnitude of the bias correction factor, whereas RCM with a relatively smaller bias tends to preserve future change signals in high flows. [ABSTRACT FROM AUTHOR]

Understanding the changes in aridity is crucial because of the substantial impacts it can have on human society. However, realistic aridity changes and their underlying climatic mechanisms demonstrate large uncertainties in China. Here we adopted the aridity index (AI) to assess the aridity changes in China, and we quantified the relative contributions of various climatic drivers (the precipitation, net radiation, wind speed, relative humidity, and air temperature) to AI changes based on the station data during 1961–2016. Our results showed that the arid/semi‐arid northwest China and Tibet Plateau experienced wetting trends, while western sub‐humid north and northeast China and western humid south China exhibited drying trends during 1961–2016. The dominant climatic drivers involved in the changing AI trends changed from arid to humid regions. In arid northwest China, increasing precipitation and decreasing wind speeds contributed the most to the wetting trends (0.024 and 0.017 in 56 years, respectively). In the semi‐arid Tibet Plateau, increasing precipitation dominated the wetting trends (0.045 in 56 years). However, in sub‐humid/humid north and northeast China and south China, decreasing wind speed and net radiation dominated the annual AI changes (0.061 and 0.092 in 56 years, respectively). In addition, AI of northwest China and the Tibet Plateau exhibited a significant abrupt change in 1987 and exhibited wetter states afterwards, which could be caused by the abrupt increase in precipitation in 1987. This study could improve current understanding of the aridity changes in China and help adapt its potential impacts. This study investigated the aridity changes and their underlying climatic mechanisms in China using station data during 1961–2016. Results showed that the "arid regions getting drier; humid regions getting wetter" is not applicable to China. The dominant climatic driver for aridity changes varies from arid to humid regions. Precipitation dominates the wetting trends in arid/semi‐arid northwest China and the Tibet Plateau, whereas wind speed and net radiation dominate aridity changes in sub‐humid/humid north and northeast China and south China. [ABSTRACT FROM AUTHOR]

Two versions of the "reliability ensemble averaging" (REA and REA Xu) method and an unweighted mean were used to generate multi‐model ensembles of 14 general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) for a baseline (1971–2000) period and future scenarios (RCP4.5 and RCP8.5) for the 21st century. To test the consistency of the REA ensembles at different scales, one ensemble was area‐averaged at regional scale and two were obtained at 50‐km gridpoints. Climatic metrics of temperature and precipitation during the baseline period served to evaluate the performance of the GCMs and the ensembles in the North American monsoon (NAM) and the mid‐summer drought (MSD) regions. The metrics of the three REA ensembles are very similar among them in each region and show a better performance than the unweighted multi‐model ensemble (U‐MME). The majority of the GCMs overestimate winter precipitation in the NAM and fail to retract the end of the monsoon in autumn; REA ensembles reduce this overestimation. All ensembles capture well the MSD's double peak of rainfall, but underestimate summer precipitation. According to all ensembles, temperature increases of 1.5–2 °C in the two regions may be reached between 2035 and 2055 relative to the baseline, and by 2070–2099 temperature (precipitation) in Mexico may increase (decrease) between 2° C (5%) and 5.8 °C (10%) in the RCP4.5 and RCP8.5 scenarios, respectively. Annual changes of precipitation show a north (positive) and south of 35°N (negative) pattern. The largest impacts are expected during summer with a possible decrease of ~13% (up to −1.5 mm/day), especially in southern Mexico, Central America, and the Caribbean, while autumn precipitation may slightly increase. Future projections from the REA Xu (by gridpoint) ensemble show spatial patterns similar to the U‐MME, but with more regional detail, which could be an added value for regional climate impact studies. Two versions of the "reliability ensemble averaging" (REA and REA Xu) method and the unweighted multi‐model ensemble (U‐MME) were used to generate CMIP5 ensembles for a baseline period (1971–2000) and 21st century scenarios (RCP4.5 and RCP8.5) for Mexico, the North American monsoon, and the mid‐summer drought region. REA ensembles show better performance than U‐MME. Future temperature and precipitation changes from REA Xu show more regional detail than the U‐MME, which could be an added value for regional climate impact studies. Maps of seasonal (DJF and JJA) precipitation change in 2070–2099 with respect to 1971–2000 in RCP8.5 scenarios according to the U‐MME and the REA Xu ensemble. [ABSTRACT FROM AUTHOR]

Future changes in the annual cycle of the precipitation in central Asia (CA) were estimated based on the historical and representative concentration pathway 8.5 (RCP8.5) experiments from 25 models of the Coupled Model Intercomparison Project phase 5. Compared with the Global Precipitation Climatology Project observations, the historical (1979–1999) experiments showed that most models can capture the migration of rainfall centres, but remarkable discrepancies exist in the location and intensity of rainfall centres between simulations and observations. Considering the skill scores of precipitation and pattern correlations of circulations, which are closely related to the precipitation for each month, for the 25 models, the four best models (e.g., CanESM2, CMCC‐CMS, MIROC5 and MPI‐ESM‐LR) with relatively good performance were selected. The four models' ensemble mean indicated that the migration and location of the precipitation centres were better reproduced, except the intensity of the centres was overestimated, compared with the result that only took the precipitation into consideration. Based on the four best models' ensemble mean under RCP8.5 scenarios, precipitation was projected to increase dramatically over most of the CA region in the boreal cold seasons (November, December, January, February, March and April) and May, with the maximum in December at the end of 21st century (2079–2099), and several positive centres were located in the Pamirs Plateau, the Tianshan Mountains and the northern Himalayas. The precipitation changes were weak in the boreal warm seasons (June, July, August, September and October), with a dry centre located in the Pamirs Plateau and a wet centre in the northern Himalayas. These projected changes can be directly attributed to the overlay of anomalous moisture convergence and evaporation, and other possible mechanisms of dynamic and thermodynamic factors need to be further elucidated. Annual cycle of precipitation (unit: mm/day) averaged by (a) latitudes (35–55°N) and (b) regions of 35–55°N and 50–95°E during 1979–1999 from the GPCP observations [ABSTRACT FROM AUTHOR]

A renewed interest in historical droughts is due to the current climate change issues and also to the recent extreme drought of 2017 in Portugal. This work aims to lengthen the historical drought series and help improve projections for the future. The main droughts of the 18th century in mainland Portugal were identified using mostly direct documentary sources: individual (poems, letters, memoirs, manuscripts and printed newspapers) and institutional (ecclesiastical and administrative), as well as accounts of Pro pluvia ceremonies and processions. All the records had been assembled in the KlimHist database (http://clima.ul.pt/Klimhist-project). A summary statistical analysis of the drought evidence including its impacts was performed to assess its temporal distribution and geographical incidence. A strong precipitation variability was detected, which, similar to the present times, hardly presents trends in long series. The main years of drought during the 18th century in Portugal are highlighted, particularly the severe and long‐lasting 1737–38 and 1753–54 droughts that, together with their atmospheric causes, were studied in detail. There are more drought records for Southern Portugal (SP) than for Northern Portugal (NP). It was also observed that spring March, April and May (MAM) and winter December, January and February (DJF) drought evidence are more frequent in SP, whereas in NP there are more records concerning summer June, July and August (JJA). The results obtained agree with those of others of the Iberian Peninsula (IP). Despite Portugal being a small country, our results confirm the existence of an important climatic boundary between the NP and the SP with different precipitation variability. This article is devoted to the study of the 18th century droughts in Portugal, based on documentary data, including Pro pluvia processions. The following droughts were identified: 1734, 1750, 1757, and 1779–1783, as well as the particularly severe and long‐lasting ones in 1737/38 and 1753/54. The results agree with others in Spain. Regional differences are pointed out. As nowadays, the main cause of the severe winter droughts is the occurrence of strong and persistent anticyclonic ridges over the Eastern North Atlantic. [ABSTRACT FROM AUTHOR]

The Mackenzie River basin (MRB), which covers a geographic region from central Alberta of Canada to the coast of Arctic Ocean, has an area of approximately 1.8 × 106 km2. In this study, the regional climate of MRB, in particular the precipitation and air temperature from the late spring to the fall (May–October), was simulated using a regional climate model Weather Research and Forecasting (WRF). In the open water season of May–October, Mackenzie River provides a critical corridor for Canada's Arctic transportation network. With nine sets of physical parameterizations of WRF selected, we simulated the climate of MRB over representative dry, normal, and wet years to identify the best setting prior to performing the 27‐year simulation for 1979–2005. The major physical parameterizations considered were shortwave (Dudhia, CAM, and RRTMG) and longwave radiation scheme (RRTM, CAM, and RRTMG), microphysics scheme (WRF Double‐Moment 6‐class, WRF Single‐Moment 5‐class, Stony Brook University, and Morrison double‐moment), and cumulus parameterization (Kain–Fritsch, Betts–Miller–Janjic, Tiedtke, and New Simplified Arakawa–Schubert). The simulation for MRB by each set of parameterizations of WRF is assessed using root‐mean‐square error (RMSE), absolute error percentage, and bias maps. After a detailed fine tuning process, and from verifying the 1979–2005 long‐term simulations of WRF, WRF generally simulated realistic air temperature and precipitable water over MRB, but precipitation is over‐simulated, especially at Canadian Rockies. Air temperature simulated is sensitive to selected parameterizations of radiation and mircophysics but not precipitation simulated. Surface variables of sea surface temperature, sea ice fraction, and snow depth are essential for the accuracy of albedo and air temperature estimated. Air temperature and precipitable water are simulated to be reasonable over the domain, but the precipitation is over‐simulated around the high terrain areas. [ABSTRACT FROM AUTHOR]

To diagnose the influence of sea surface temperature (SST) biases on temperature and precipitation patterns in the western United States, we analysed atmospheric and coupled global climate model (GCM) simulated output from the Coupled and Atmospheric Model Intercomparison Project versions 3 and 5 (CMIP3, AMIP3, CMIP5, and AMIP5). We further analyse the impact of SST biases in regional climate modelling simulations. CMIP3 and CMIP5 multi‐model ensembles show systematic warm SST biases offshore of California and the Baja California Peninsula (Baja) region, with ensemble mean SST biases of the order of ~3–5 °C. Throughout the western United States, 75% of all models in CMIP3 and CMIP5 exhibit wet precipitation biases and corresponding cold biases in surface temperature. The CMIP5 ensemble shows on average a stronger and more consistent relationship between Baja SST biases and precipitation over the west compared to the CMIP3 ensemble. We attempted to isolate the atmospheric response to regional SST biases using a regional climate model (RCM) based on the Weather Research and Forecasting model with a 36 km grid size. The RCM was driven with the CMIP3‐CCSM3 as boundary conditions with and without corrections of simulated SSTs. Results from RCM simulations further confirm that SST biases impact climate regionally and propagate over the western United States and can explain up to 80% of wet precipitation biases. Our regional GCM comparison and RCM experiment assess the robustness of model estimates of climate mean states and constitute an often neglected prerequisite for characterizing how errors transfer from GCM to regional downscaling modelling frameworks and how they could potentially affect downscaling application and impact studies. This study shows how the coupled global climate models SST biases impact climate regionally and propagate over the western United States and can explain up to 80% of wet precipitation biases. We performed a regional GCM comparison and RCM experiment that assess how errors transfer from GCM to regional downscaling modelling, potentially affecting downscaling application and impact studies. Figure shows RCM wet precipitation differences over SW United States resulting from isolating the effect of using raw (biased) GCM SST minus bias‐corrected SSTs. [ABSTRACT FROM AUTHOR]

Extreme precipitation and associated flooding cause severe damage to society and the environment. Future climate projections suggest an intensification of precipitation extremes in many regions. However, there is an increasing need for climate change impact assessment at higher spatial resolution, particularly for regions with complex geography such as Southeast Asia (SEA). In this study, we analysed the NASA Earth Exchange 0.25° resolution daily precipitation projections from an ensemble of 20 climate models under two emission scenarios RCP4.5 and RCP8.5. The variability in future precipitation projections is analysed and quantified for six geographical subregions, two climatological regions (wet and dry), and the low‐elevation coastal zones in SEA. Various aspects of precipitation structure are studied using indices that characterize precipitation amount, number of heavy precipitation days, extreme precipitation amount, and maximum daily precipitation at annual and seasonal scales. The results show substantial increases in mean and extreme precipitation in many parts of SEA by the end of the 21st century under both emission scenarios, thus increasing the region's vulnerability to precipitation‐driven hazards. The projected centennial increase in total annual precipitation relative to the baseline period of 1970–1999 when averaged over all land grid cells is about 15% under RCP8.5 scenario, with larger values (∼20%) over mainland SEA and Philippines and smaller values (∼6%) in Java island. The projected changes in extreme precipitation are stronger compared to the total annual precipitation under both emission scenarios. The New Guinea and Java regions show the largest and smallest increases in annual maximum daily precipitation, with ensemble mean values of 30 and 17%, respectively, under RCP8.5 scenario. The results also reveal large inter‐model spread in projected changes, particularly during boreal winter and summer months. The study assessed changes in different precipitation characteristics such as the annual maximum daily rainfall (shown here) over nine regional masks in Southeast Asia for the time period 2070–2099 relative to the baseline period of 1970–1999. Results indicate substantial changes in total precipitation and extreme precipitation, particularly for the RCP8.5 scenario. The regional and seasonal variability in future changes and associated uncertainties are described in detail in this study. [ABSTRACT FROM AUTHOR]

The understanding of the atmospheric phase of the hydrological cycle is an important step forward in improving our abilities to predict droughts and floods, as well as the impacts of climate change on water resources. Here we focus on the study of the atmospheric moisture transport to the Upper Paraná River basin, Brazil, through the hybrid single‐particle Lagrangian integrated trajectory (HYSPLIT) dispersion model, which is used to generate air masses trajectories based on the 1970–2010 National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. In terms of moisture source regions, we found that the tropical South Atlantic is the main contributor to the Upper Paraná River basin, exporting about 175 mm/month of water vapour during the rainy season. The North Atlantic contribution is relevant in February (about 38 mm/month). Other regions over the Atlantic Ocean (North and subtropical South) are also identified as sources, and moisture evaporated from these places has a significant impact on the streamflow variability at the Itaipu streamflow gauge, located at the basin outlet. The continental sources play a more relevant role during the dry season (May–October). The Amazon region is more relevant as a moisture source during the dry season, exporting an average of 45 mm/month. A similar pattern is observed in other continental sources, such as Chaco/Pantanal/Cerrado, which together export about 99 mm/month to the Paraná River basin during the dry season. An extreme event analysis reveals that changes in moisture advection from the tropical South Atlantic are related to floods and droughts in the region. Particularly, we observe that flood events are preceded by positive anomalies of moisture advection up to 2 months in advance, while persistent, negative anomalies of moisture transport lead seasonal droughts by up to 8 months beforehand. Numeric water vapour tracers are air masses trajectories, such as those shown in the image, obtained using reanalysis data and Lagrangian models. Through a moisture balance procedure, the exchanges with the surface as evaporation and precipitation are accounted, and source or sink regions identified. The gridded or region time series produced in this manner reveals seasonal, inter‐annual and extreme patterns in the moisture transport to the Upper Paraná River basin, showing relations between droughts, floods and transport from the Atlantic. [ABSTRACT FROM AUTHOR]

This study is to investigate changes in maximum 24‐hr precipitation for 20 stations during the typhoon season (July–October) and how the El Niño–Southern Oscillation (ENSO) may modulate precipitation extremes in Taiwan. Based on the nonparametric Mann–Kendall method and Sens's test, 15 out of 20 stations (three fourth) exhibited an upward trend from 1958 to 2013. Results of the field significance test suggest that the significant increasing trend is not caused by random variability. The method of the non‐stationary generalized extreme value distribution (NGEV) is then applied to determine temporal changes in return levels. Results show that a large majority of stations are marked by an increasing trend in the three chosen return levels (2, 20, and 100 years) over the last 56 years. Therefore, more intense typhoon producing seasonal maximum 24‐hr precipitation has been observed in Taiwan. The waiting time for an extreme event to occur has shortened considerably in recent years. For stations located in western/central Taiwan, an El Niño (La Niña) event favours low (high) precipitation extremes. It is the opposite for stations in northern and eastern Taiwan. Thus, an east–west regional difference in precipitation extremes across Taiwan is noted. A NGEV model based on both time and ENSO as covariates is also applied. Inter‐annual variations influenced by ENSO are more dominant than long‐term trend in return levels for most stations in western/central Taiwan. Historical 24‐hr maximum precipitation during the typhoon season (July–October) is used and a majority of stations in Taiwan are marked by an increasing trend in the three chosen return levels (2, 20, and 100 years) over the last 56 years. An east–west regional difference in precipitation extremes across Taiwan is noted based on the antecedent state of ENSO. Inter‐annual variations influenced by ENSO are more dominant than long‐term trend in return levels for most stations in western/central Taiwan. [ABSTRACT FROM AUTHOR]

The diurnal variation of the rainfall amount, frequency and intensity, and the rainfall with different durations, as well as their seasonality, were analysed by using the hourly rainfall data at 90 stations in the UK during 1998–2015. The rainfall amount averaged in the entire UK presented two comparable peaks in the early morning and the late afternoon, which contributed by the frequency (the early morning) and the intensity (the late afternoon), separately. The rainfall peaks were closely related with the location and the duration of the rainfall. For the rainfall amount, the early morning peaks were more prevailing in the rainfall events lasting more than 6 hr and at the stations along the western coast of the British Isles; however, the rainfall events lasting 1–6 hr usually reached the hourly maximum in the late afternoon. For the seasonal variability, more nocturnal rainfall peaks of rainfall amount and intensity were found over the southern plains in winter. In spring to autumn, only the rainfall at some coastal stations or the stations on islands got the maximum during midnight to the early morning. For the rainfall frequency, the regional differences were more apparent in spring and summer, and the hourly rainfall frequency in the UK mainly peaked around 0600 GMT (Greenwich mean time) in autumn and in 1100–1300 GMT in winter. The results enriched the knowledge of the hourly rainfall features over the UK. The diurnal variations in the rainfall amount, frequency and intensity, rainfall events with different durations, and their seasonality were analysed using the hourly rainfall data collected at 90 stations in the UK from 1998 to 2015. The average rainfall amount in the entire UK presented two comparable peaks in the early morning and late afternoon, which reflected contributions from the frequency (the early morning) and intensity (the late afternoon), respectively. The rainfall peaks of rainfall amount, frequency and intensity were closely related to their location and the durations. Spatial distributions of the peaks of the diurnal cycles of the hourly precipitation amount (a), frequency (b), and intensity (c) averaged during 1998–2015, as well as topography (shaded, units: m). The vectors denote the GMT at which the maximum precipitation occurred (the phase clock). [ABSTRACT FROM AUTHOR]

The dominant modes wintertime precipitation in northwest China (NWC) and the possible causes are investigated during the period 1961–2013 in the inter‐annual timescale, as winter climate condition could greatly affect local economic development and people's lives. The analysis of this study is divided into three parts. First, the spatiotemporal variability of dominant modes wintertime precipitation is described by an empirical orthogonal function (EOF) method. The atmospheric circulation anomalies associated with wintertime precipitation variations are then discussed through regression and composite analysis. Third, the relationships between wintertime precipitation and sea surface temperature (SST) anomalies are investigated. The results indicate that the leading mode (EOF1) shows a uniform sign in the entire region, and the second mode (EOF2) exhibits a zonal‐dipole pattern; they account for 25.6 and 15.7% of the total variance, respectively. The atmospheric circulation anomalies EOF1 closely related to is the Eurasian (EU) teleconnection pattern. Years when a negative phase of EU pattern occurs tend to be rainy with anomalous southerly transporting water vapour from low‐latitudes and profound ascending motion anomalies. Atmospheric circulation anomalies associated with the second mode resemble the Arctic Oscillation (AO) pattern. AO pattern influences EOF2 precipitation variations through the anomalous circulations over Mongolia and western Europe. The sea surface temperature (SST) anomalies related to EOF1 show an El Niño‐Southern Oscillation (ENSO) like pattern, which may modulate the wintertime precipitation mode through the western North Pacific anticyclone. The EOF2 mode has a close relationship with a tripole SST anomaly mode in the North Atlantic Ocean. This SST pattern is likely to influence wintertime precipitation by modulating the North Atlantic Oscillation (NAO). The results of this study could be beneficial for wintertime precipitation prediction and the decrease of economic losses in NWC and may also provide useful references for other areas with similar climatic features such as the central Asia. (a, c) EOF1 and (b, d) EOF2 of inter‐annual wintertime precipitation variations for 1961–2013 in NWC. (a, b) Regression maps on the normalized time series (unit: mm); (c, d) normalized time series. [ABSTRACT FROM AUTHOR]

We provide a broad view of East Asian summer monsoon (EASM) precipitation and their changes in the 21st century under the representative concentration pathway RCP4.5 and RCP8.5 scenarios using a high‐resolution (at 40 km) atmospheric general circulation model (AGCM). The simulated fields are validated against the multiple observational data sets in the reference period (1979–2008). Validation of seasonal simulated global climatology and EASM precipitation, annual cycle and various circulation fields including 25 individual Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP5 MME suggests that AGCM can be used to study the future projected characteristics of EASM. An investigation of uncertainty in precipitation shows larger values in the regions of high‐precipitation belt and low terrain. Future projections are categorized as near (2010–2039), mid (2040–2069) and far (2070–2100) futures. The model projects an increased summer precipitation of about 3.2% (2.3%) in near future, about 4.5% (4.5%) in mid‐future and about 2.4% (2.3%) in far future over East Asia region under RCP4.5 (RCP8.5) scenarios when compared to the reference period. As far as regional landmasses are concerned, model projects a gradual increase in the range of 5–15% over northeast China, coastal regions of southern China, Korea and Japan regions and a decrease of about 5–10% over southeastern and northwest parts of East Asia during the 21st century. The projected increase of EASM can be attributed to an increase in atmospheric moistures (relative humidity) over the east coast of China, Korea and northeast China and north and northwestwards enhancement of eddy geopotential height. Extreme events are examined by using various precipitation indices over EASM regions. Results indicate that the indices of heavy precipitation are projected to increase (both frequency and intensity) over Korea, Japan and northeast China in the range of 5–20%, indicating strong sensitivity of EASM to global warming. [ABSTRACT FROM AUTHOR]

Precipitation plays an essential role in hydrological cycle, water resource availability, and ecological economics sustainable development both within the Qilian Mountains (QM) and its surrounding. On the basis of meteorological station records and reanalysis data sets, we investigate the variations of precipitation in the QM during 1960–2014 and their connection to the shifts of regional atmospheric water vapour. Results show that precipitation in the QM as a whole has experienced pronounced wetting at an annual rate of 6.95 mm/decade. Significant (at 95% confidence level) precipitation increase mainly occurs in JJA (June–August) and slightly in DJF (December–February). The evident increase of precipitation appears in the mid‐east of the QM. Furthermore, the increasing rates of annual, JJA, and SON (September–November) precipitation increase with elevation, indicating obvious elevation‐dependent precipitation increase in the QM. The atmospheric precipitable water (PW) for annual, JJA, and SON time series over the targeted region generally shows significant increasing trends, especially during 1979–2014. The meridional and zonal water vapour budgets positively and negatively contribute to the regional net water vapour budget, respectively. Moreover, we demonstrate that the zonal water vapour budgets are strongly intensified and meanwhile the meridional ones except in transitional seasons are weakened. Thus, regional net water vapour budgets for annual and seasonal time series are increased. All in all, the shifts of the regional atmospheric water vapour, such as the increases of PW and water vapour budget (referring to the zonal and regional net water vapour budgets), agree with the result that the QM precipitation increases from 1960 to 2014, which suggests the QM wetting trend is in connection with the changes of the atmospheric water vapour. [ABSTRACT FROM AUTHOR]

Nepal is one of the most vulnerable countries to climate change impacts. Extreme weather events associated with heavy precipitations are the principal causes of landslides, debris flows and all types of floods disasters in the country, which by causing tremendous losses of life and property affects the socio‐economic development. Given the limited availability of knowledge in spatio‐temporal distribution of precipitation in Nepal, this study analyses the spatial distribution of monthly and annual precipitation and 1‐day extreme precipitation and their trends utilizing a large number of stations (291 stations for the first time) distributed across the country for the period of 1966–2015. This study focuses on the exploration of elevational dependencies of precipitation to demonstrate the effect of topographic heterogeneity caused by the numbers of broad and narrow river valleys and mountain slopes and ridges. Also, this study investigates the relation of 1‐day extreme precipitation with mean annual precipitation. Our results show the peak annual precipitation elevation between 2,000 and 3,500 m above sea level, while in contrast 1‐day extreme precipitation peaks are found at lower elevation in the southern foothills with its highest intensity in a central region of the country. The occurrence of 10% of mean annual precipitation in a single day has been observed in 75% of the analysed stations which in turn indicates the high likelihoods of initiation of landslides, soil erosions and floods in different parts of the country. There is no definitive countrywide decadal trend in extreme precipitation intensity and occurrence. A station‐wise trend clearly shows the increase in extreme precipitation events in western mountainous regions in the recent decades. In other locations, the mixed patterns of station‐wise increasing and decreasing trends are found. [ABSTRACT FROM AUTHOR]

A comprehensive analysis of the spatial and temporal variability of daily precipitation in Spain in the period 1950–2012 was carried out based on the high‐resolution gridded data set SPREAD at a 5 × 5 km spatial resolution. Temporal trends of 12 daily precipitation indices were computed by application of the Sen's slope and the Mann–Kendall tests. The spatial distribution of the trends showed (a) a global slight increase in the duration of the precipitation events, especially along the Mediterranean fringe; (b) an increase of the frequency of low precipitation events and a decrease of the frequency of high and very high events (inverse in the Mediterranean coast); and (c) a slight decrease of the intensity when considering single events (1‐ or 5‐day duration), but a significant negative trend in mean and median precipitation when considering all the precipitation days (p > 0), especially in the Mediterranean coast. [ABSTRACT FROM AUTHOR]

Climate inter‐annual variability over the North American monsoon (NAM) region is associated with El Niño‐Southern Oscillation (ENSO) and Pacific decadal variability (PDV), which drive a warm season atmospheric teleconnection response. Using the North American Regional Climate Change Assessment Program (NARCCAP) simulations, previous studies have found that regional models forced with an atmospheric reanalysis (NARCCAP Phase I) represent the NAM reasonably well as a climatological feature. However, when these same regional models are forced with global climate model projections (NARCCAP Phase II), their ability to represent the NAM as a salient feature substantially degrades. The present study evaluates NAM inter‐annual climate variability through the continental‐scale patterns of summer precipitation within the NARCCAP simulations (Phases I and II), in relation to ENSO–PDV, and the presence of the driving atmospheric teleconnection response. Multivariate statistical analyses are applied to sea surface temperature and precipitation data sets to determine dominant variability at continental scale, with focus on the southwest. The analysis reveals that NARCCAP Phase I simulations are able to portray the spatial pattern of precipitation associated with ENSO–PDV in a similar way to observations. However, all NARCCAP Phase II simulations, with the exception of the HRM(Hadcm3) regional–global model pair, fail to reproduce this climate variability. Although including all possible NARCCAP model simulations to generate a multi‐model ensemble mean would increase the statistical degree of confidence in climate projections, this type of result would not increase confidence in the physical climatology of model representations of warm season climate variability. More physically based, process‐oriented metrics are needed to evaluate model quality in assessing the uncertainty of future climate change in multi‐model ensemble products used for climate change impacts assessments. [ABSTRACT FROM AUTHOR]