Search

In this paper we present the results of quality control and homogenization procedures applied to long time series of daily atmospheric precipitation sums (Rr) and daily mean (Tm), maximum (Tx) and minimum (Tn) air temperature collected in Ukraine. The daily data from 178 meteorological stations covering the period of 1946–2020 were analysed. In order to perform a thorough quality assurance check, we used the R package INQC, while the Climatol homogenization software was used to detect and remove breaks from the time series. The INQC quality assurance tests revealed a relatively small number of erroneous records (around 0.01% for each variable) and suspicious values (up to 0.09%). The application of Climatol resulted in 195, 296, 355 and 359 break points, detected for Rr, Tm, Tx and Tn, respectively. These quantities coincide roughly with the results of the HOMER homogenization procedure applied to monthly time series for the same stations and almost the same period (performed in the previous works of the authors). To verify the homogenization results, statistical comparison of the raw and homogenized time series was performed. The verification demonstrated that the quality control and homogenization procedures detected and removed errors and breaks very well, and air temperature and precipitation fields after the homogenization are more self‐consistent compared to the original raw data. [ABSTRACT FROM AUTHOR]

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]

The characterization of the alpine extreme precipitation is the basis to study the projected changes in frequency and intensity of heavy rainfall and is needed to improve the resilience of communities to high‐impact weather. Climatological features of extreme daily and sub‐daily precipitation are documented here for the Swiss Alps and surrounding regions at a high spatial resolution (1 km2). The basis is 12 years of data from rain gauges and CombiPrecip, a rainfall field produced by locally adjusting the radar precipitation map to the values measured by rain gauges. The agreement between rain gauges and CombiPrecip concerning both the timing and the magnitude of the extreme events is quantified by cross‐validation; overall, it increases with diminishing the severity of the extremes and increasing accumulation time. If the extremes represent on average the 10 most intense rainfall accumulations per year, in general 50–65% of rain gauges extremes are extremes also for CombiPrecip, 40–50% of CombiPrecip extremes are not extremes according to rain gauges, and CombiPrecip extremes are till 7% lower than rain gauges extremes. The maps presented in this paper show that both daily and sub‐daily extremes are more intense along the alpine slopes compared to the crest of the Alps in all seasons, with the Lago Maggiore region showing the largest values. The fraction of yearly rainfall due to extremes is generally smaller in the Alps than in flat terrain. Extreme 1‐hr precipitation is more clustered in time in the inner Alps, but is less frequent, and exhibits a strong diurnal cycle in summer. The paper also shows that sub‐daily and daily extremes occur essentially over the same 24‐hr period. [ABSTRACT FROM AUTHOR]

The roles of moisture sources and transport in intraseasonal precipitation variabilities during the preflood season over South China are complex and different. In this paper, ERA‐Interim reanalysis data that were collected four times daily from 1979 to 2017 are used to analyse the variation and influence of moisture transport in intraseasonal precipitation during the preflood season over South China. Using the Hybrid Single‐Particle Lagrangian Integrated Trajectory model, fixed atmospheric moisture sources are defined: land area source (LD source), Indian Ocean source (IO source), Pacific Ocean source (PO source), South China Sea source (SCS source), and South China source (SC source). Sea source moisture transport accounts for more than 75% of the total precipitation during the preflood season, which is the most important moisture source in South China. For April, southeasterly moisture transport, which includes PO source and SCS source moisture transports, is the major moisture transport over South China. Then, the IO source and SCS source precipitation increased significantly during May. During June, the IO source precipitation accounted for 43.75% of the total precipitation, thus dominating precipitation over South China. In addition, there is a significant difference in the interdecadal variation in the preflood season precipitation before and after the Indian summer monsoon onset. Before the Indian summer monsoon onset, the land‐sea thermal contrast decreased, which led to a significant interdecadal reduction in the IO source, PO source, and SCS source moisture transports. After the Indian summer monsoon onset, the increase in IO source moisture transport is the primary cause of the interdecadal increase in precipitation over South China. [ABSTRACT FROM AUTHOR]

Information on the variability of precipitation in time and space is critical for many water resource projects. However, precipitation records at the location of interest are often either limited or unavailable due to an inadequate network of rainfall measurements. To address this need, regionalization methods have been employed to characterize spatial patterns of precipitation and to transfer precipitation information from one location to another where records are scarce. Hence, the overall objective of the present paper is to propose a stochastic weather model for generating daily precipitation at ungauged locations. The proposed approach consists of two components: (a) a regionalization approach for identifying homogeneous groups of observed daily precipitation series, and (b) a stochastic model for constructing daily precipitation events at ungauged locations within homogeneous groups. This statistical approach identifies groups of precipitation stations with similar statistical characteristics based on the combination of two multivariate statistical techniques: principal component analysis (PCA) and ordinal factor analysis (OFA). While the application of PCA in climatological regionalization studies based on precipitation amount is common, the application of OFA to include precipitation occurrence in the identification of regions is unusual. The feasibility of the approach is assessed using daily precipitation data from a network of precipitation stations in the Catskill Mountain region of New York State, United States. [ABSTRACT FROM AUTHOR]

A characterization of the diurnal cycle of precipitation (DCP) over the whole South America is still lacking in the literature and the scarcity of sub‐daily rain ground measurements limits the data available for analysis and forbids a correct validation of alternative datasets. In this paper we analyse the climatological mean DCP during the monsoon active season using five gridded datasets: two satellite precipitation estimates, two regional climate models and one reanalysis. Amazonia, the Brazilian Highlands, the northeastern South American coast, the Andes and the western Colombian coast are identified as the areas with most prominent DCPs. The afternoon convection triggered by solar heating over land and the coastal and topographic effects are the main modes of sub‐daily variability, based on an EOF decomposition of the 3 hourly mean precipitation fields. We explore the contribution of mean frequency and intensity to amount of precipitation and nighttime–daytime differences. In general, both models precipitate earlier and more frequently than the satellite products and do not reproduce correctly areas of observed predominant nighttime precipitation where mesoscale convective systems are active, like La Plata Basin or Amazonia. Over the analysed areas, the high frequency of precipitation is the driving mechanism of total amount in the models, whereas in the satellite products there is also considerable contribution from intensity. Overall, the reanalysis shows features in between the models and the satellite estimates, sharing characteristics with both types of data. The results presented here point at the diversity of sub‐daily precipitation characteristics in South America, the issues with conventional climate models and the uncertainty in satellite products and reanalyses. The growing interest in the DCP by the scientific community and the development of new techniques like convection permitting modelling will hopefully continue to improve our knowledge of the precipitation dynamics and its influence on climate. [ABSTRACT FROM AUTHOR]

Seasonal prediction of extreme precipitation has long been a challenge especially for the East Asian Summer Monsoon region, where extreme rains are often disastrous for the human society and economy. This paper introduces a decision‐tree (DT) method for predicting extreme precipitation in the rainy season over South China in April–June (SC‐AMJ) and the North China Plain in July–August (NCP‐JA). A number of preceding climate indices are adopted as predictors. In both cases, the DT models involving ENSO and NAO indices exhibit the best performance with significant skills among those with other combinations of predictors and are superior to their linear counterpart, the binary logistic regression model. The physical mechanisms for the DT results are demonstrated by composite analyses of the same DT path samples. For SC‐AMJ, an extreme season can be determined mainly via two paths: the first follows a persistent negative NAO phase in February–March; the second goes with decaying El Niño. For NCP‐JA, an extreme season can also be traced via two paths: the first is featured by "non El Niño" and an extremely negative NAO phase in the preceding winter; the second follows a shift from El Niño in the preceding winter to La Niña in the early summer. Most of the mechanisms underlying the decision rules have been documented in previous studies, while some need further studies. The present results suggest that the decision‐tree approach takes advantage of discovering and incorporating various nonlinear relationships in the climate system, hence is of great potential for improving the prediction of seasonal extreme precipitation for given regions with increasing sample observations. [ABSTRACT FROM AUTHOR]

Climate change has influenced the glaciers and water resources in the Hindukush‐Karakorum‐Himalaya region. The relatively short instrumental record of northern Pakistan makes long‐term climate change assessments difficult. In this paper, tree‐ring width chronologies were developed from two stands of spruce species (Picea smithiana) in the Karakoram region of northern Pakistan. The results of the correlation analysis revealed that tree‐ring growth of spruce was limited by annual (June–May) precipitation. Based on the regional chronology, we developed an annual precipitation reconstruction for the period 1540–2016 CE. The precipitation reconstruction equation accounts for 40% of the regional precipitation variance during the instrumental period 1946–2016. Dry episodes with rainfall below the 477‐year average occurred from 1569 to 1577, 1598 to 1612, 1621 to 1621, 1638 to 1654, 1673 to 1680, 1697 to 1720, 1728 to 1739, 1753 to 1761, 1777 to 1793, 1801 to 1840, 1860 to 1874, 1914 to 1932, 1960 to 1985, 1998 to 2011. Wet episodes occurred from 1540 to 1568, 1578 to 1597, 1613 to 1620, 1632 to 1637, 1655 to 1672, 1681 to 1696, 1721 to 1727, 1740 to 1752, 1762 to 1776, 1794 to 1800, 1841 to 1859, 1875 to 1913, 1933 to 1959, 1986 to 1997. Furthermore, the results of spatial correlation analyses show that the reconstructed precipitation represents the regional precipitation variations for northern Pakistan and nearby high‐altitude mountains. The out‐of‐phase relationship in tree‐ring records of the Karakoram region and surrounding areas suggests that the Karakoram was under the control of large‐scale ocean–atmosphere–land circulations on a decadal timescale in the past centuries. In addition, by the comparison between the precipitation reconstruction and the instrumental data, we found that the drought risk of Karakoram has increased in the past 70 years and that extreme events are likely to become more severe and more frequent under the backdrop of climatic warming. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study focused on the projected changes in extreme precipitation indices in Romania during three future periods: 2021–2040, 2041–2070, and 2071–2100. We investigated changes in future climate based on historical and modelled data sets of daily precipitation. We compared the values calculated for the three future periods with those obtained for the historical reference period 1961–1990. The historical observation data recorded at 30 weather stations and data extracted from six regional climate model outputs (ALADIN53, CCLM4‐8‐17, RACMO22E, RCA4, REMO2009, and WRF331F) under moderate (RCP4.5) and pessimistic (RCP8.5) scenarios were employed. Five indices established by the Expert Team for Climate Change Detection Monitoring and Indices were analysed: consecutive dry days, consecutive wet days, heavy precipitation days, very heavy precipitation days, and annual total wet‐day precipitation. The series of indices were generated using ClimPACT2 software. Based on bias correction methods, the quality of the modelled data considerably increased, and the errors obtained for the daily precipitation varied in the range of ±0.05 to ±1.22 mm/day. The main findings revealed an increase in three of the extreme precipitation indices based on all models considered compared to the historical period. The most important increase (more than 50%) compared to the historical period was detected in the frequency of very heavy precipitation days and the annual total wet‐day precipitation. They were followed by the heavy precipitation days index. The consecutive dry days index indicated mainly no change or a slow decrease, while inconsistencies among the results of regional climate models were detected for the consecutive wet days index. For all indices except the consecutive dry days index, the ALADIN53 and WRF331F models provided the highest projected values for both scenarios. The dispersion of values obtained as model output for each location was higher for RCP8.5 than for RCP4.5. [ABSTRACT FROM AUTHOR]

This paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion). [ABSTRACT FROM AUTHOR]

From 1961 to 2015, annual and seasonal precipitation have shown a significant increase over Northwest China (NW). The change of precipitation is a combination result of the changing recycling precipitation (Pw) contributed by local evapotranspiration (ET) and changing precipitation contributed by advection moisture (Po). In this paper, we calculated the ET based on the observation data of meteorological stations and the complementary relationship model. Then used an improved precipitation recycling model to analyse influential factors on the variation of precipitation over the NW from aspects of ET and advection moisture. The annual precipitation recycling ratio (ρ) fluctuates between 4% and 10% and shows an increasing trend at a rate of 0.3% /10a with a significance level of 0.01. ET, which is the internal supplier of the precipitable water, and advection moisture, which is the outside supplier of the precipitable water, both have displayed significantly increasing trends over the NW. The advection moisture contributes precipitation much more than ET, no matter in the annual scale or seasonal scales. In view of the spatial distribution, Pw shows an increasing trend over the whole NW, but distinctly opposite spatial patterns of Po are found between the western area of NW (WNW) and the eastern area of NW (ENW). Such differences caused the precipitation is characterized by a wetting trend in WNW but a drying trend in ENW. [ABSTRACT FROM AUTHOR]

This paper proposes an interpolation model for monthly rainfall in large areas of complex orography. It has been implemented in the Iberian Peninsula (continental territories of Spain and Portugal), Balearic and Canary Islands covering a territory of almost 600.000 km2. To do this a data set that comprises a total number of 11,822 monthly precipitation series has been created (11,042 provided by the Spanish Meteorological Agency and 780 provided by the National Water Resources Information System of the Portuguese Water Institute). The data set covers the period from October 1940 until September 2005. The interpolation model has been based on the assumption of two different components on monthly precipitation. The first component reflects local and seasonal characteristics and 24 different mean monthly precipitation maps (12) and SDs maps (12) compose it. It considers the varying influence of physiographic variables such as altitude and orientation. The second precipitation component reflects the synoptic pattern that dominated each month of the series and it is composed by series of anomalies of monthly precipitation (780). Anomalies have been interpolated by means of ordinary kriging once local spatial continuity was assumed. Gridded maps of each variable have been developed at 200 m resolution following a hybrid methodology that implements two different interpolation techniques. The first technique applies a regression analysis to derive maps depending on altitude and orientation; the second one is a weighting technique to consider the non‐linearity of the precipitation/altitude dependence. Cross validation has been applied to estimate the goodness of both techniques. Results show an average annual precipitation of 655 mm/year. Although this figure is only 4% less than the estimate of MAGRAMA (2004), regional and local differences are highlighted when the spatial distribution is considered. The model constitutes a comprehensive implementation considering the availability of historical records and the need of avoiding slow calculations in large territories. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate a 48‐member multiphysics ensemble using the Weather Research and Forecasting (WRF) model for the JJA extreme precipitation and temperature in 2003 over the CORDEX‐EA‐II domain. The simulated precipitation and temperature are reasonable in the subregions controlled by a large‐scale circulation, yet the biases for both precipitation and temperature are evident over the subregions where the effects of mesoscale processes are important. The performance of various combinations of WRF physical schemes for simulating the JJA precipitation is dependent on the region. Meanwhile, the cumulus and microphysical schemes have substantial influences on the simulation of precipitation, and the land surface models and cumulus schemes play crucial roles in the surface temperature. Our analysis shows that the combination of Noah for the land surface process, Lin for the microphysics, G3D for the cumulus parameterization, and CAM for the radiation scheme can provide the most reliable reproduction of both precipitation and temperature extremes over China. Ensemble analysis shows that the simulated climate extremes are usually accompanied by a large ensemble spread, implying sensitivities to the model physical processes in some subregions. The simulated wind fields at low‐to‐middle atmospheric levels display responses to the options of the land surface models and cumulus schemes. The essential impact of the land–atmospheric interaction on simulating the extremes can be largely attributed to the active convective processes. WRF has difficulties in reproducing the observed temporal evolution of the rainfall process, which consists of continuous large rainfall episodes in the observation data set during the simulation period. [ABSTRACT FROM AUTHOR]

Long‐term trends in equatorial African rainfall have proven difficult to determine because of a dearth in ground‐measured rainfall data. Multiple, satellite‐based products now provide daily rainfall estimates from 1983 to the present at relatively fine spatial resolutions, but in order to assess trends in rainfall, they must be validated alongside ground‐based measurements. The purpose of this paper is twofold: (a) to assess the accuracy of four rainfall products covering the past several decades in western Uganda; and (b) to ascertain recent, multi‐decadal trends in annual rainfall for the region. The four products are African Rainfall Climatology Version 2 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN‐CDR), and TAMSAT African Rainfall Climatology And Timeseries (TARCAT). The bias and accuracy of 10‐day, monthly, and seasonal rainfall totals of the four products were assessed using approximately 10 years of data from 10 rain gauges. The homogeneity of the products over multiple time periods was assessed using change‐point analysis. The accuracy of the four products increased with an increase in temporal scale, and CHIRPS was the only product that could be considered sufficiently accurate at estimating seasonal rainfall totals throughout most of the region. TARCAT tended to underestimate totals, and ARC2 and PERSIANN were in general the least accurate products. Only annual rainfall estimates from CHIRPS and TARCAT were significantly correlated with ground‐measured rainfall totals. TARCAT was the most homogeneous product, while ARC2, CHIRPS, and PERSIANN had significant negative change points that caused a drying bias over the 1983–2016 period. After adjusting the satellite‐based rainfall estimates based on the timing and magnitude of the change points, annual rainfall totals derived from all four products indicated that western Uganda experienced significantly increasing rainfall from 1983 to 2016. [ABSTRACT FROM AUTHOR]

This paper revisits teleconnections for three major rainy seasons at the Greater Horn of Africa for the period 1901–2013. Sea surface temperature‐based climate indices known to influence Short, Kiremt, and Long Rains are used in a comprehensive statistical analysis to detect non‐stationary behaviour in teleconnections and to split them into interannual and decadal time scales. Physical mechanisms are proposed for identified significant non‐stationary teleconnections. Interannual variability in the October–December Short Rains is predominantly influenced by the Indian Ocean Dipole (IOD) with a percent variance explained (PVE) of up to 80% in recent years. However, abrupt shifts in this teleconnection occurred around 1918, 1951, 1987, and recently. The Short Rains also correlate strongly with El Niño‐Southern Oscillation (ENSO). However, ENSO influence on Short Rains is mediated by in‐phase occurrence of IOD. Decadal variations in Short Rains are more directly explained by low‐frequency variability in the Pacific Ocean (PO). A hitherto undocumented non‐stationary relation was found between Atlantic Niño 3 and June–September Kiremt Rains. The non‐stationarity seems to be related to a decadal regime shift in the West African monsoon system in the late 1960s. The variability of Kiremt Rains is also strongly associated with ENSO, although the recent increased correlation is not non‐stationary. Consistent with recent studies, the post‐1998 March–May Long Rains decline is strongly associated with decadal variability in the PO. The PVEs in the stable correlations using Pacific Decadal Oscillation and Interdecadal Pacific Oscillation indices range from 25 to 64%, mostly due to low‐frequency variability (>8 years). The results have ramifications for seasonal‐to‐decadal forecasting and can be taken to design modelling studies to gain insights into the physical mechanisms. Annual mean precipitation from 1981 to 2013 in millimeter, derived from climate Hazard infrared precipitation with station version 2.0 (CHIRPS2.0). The boxes represent the regions for which seasonal SPIs are created: MAM precipitation over GHA (red), OND precipitation over equatorial East Africa (blue), and JJAS precipitation over the Ethiopian Highlands. The interannual and decadal relationships between these rainfall indices and SST‐based remote indices of climate variability are examined. The strength, non‐stationarity, and unknown physical explanations are also explored. [ABSTRACT FROM AUTHOR]

The 1981–2010 monthly precipitation climatologies for Norway at 1 km resolution are presented. They are computed by an interpolation procedure (HCLIM+RK) combining the output from a numerical model with the in situ observations. Specifically, the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis onto 2.5 km resolution, is considered together with 2009 rain‐gauges located within the model domain. The precipitation climatologies are defined by superimposing the grid of 1981–2010 monthly normals from the numerical model and the kriging interpolation of station residuals. The combined approach aims at improving the quality of gridded climatologies and at providing reliable precipitation gradients also over those remote Norwegian regions not covered by observations, especially over the northernmost mountainous areas. The integration of rain‐gauge data greatly reduces the original HCLIM‐AROME biases. The HCLIM+RK errors obtained from the leave‐one‐out station validation turn out to be lower than those provided by two considered interpolation schemes based on observations only: a multi‐linear local regression kriging (MLRK) and a local weighted linear regression (LWLR). As average over all months, the mean absolute (percentage) error is 10.0 mm (11%) for HCLIM+RK, and 11.4 (12%) and 11.6 mm (12%) for MLRK and LWLR, respectively. In addition, by comparing the results at both station and grid cell level, the accuracy of MLRK and LWLR is more sensitive to the spatial variability of station distribution over the domain and their interpolated fields are more affected by discontinuities and outliers, especially over those areas not covered by the rain‐gauge network. The obtained HCLIM+RK climatologies clearly depict the main west‐to‐east gradient occurring from the orographic precipitation regime of the coast to the more continental climate of the inland and it allows to point out the features of the climatic subzones of Norway. The paper presents the 1981–2010 monthly precipitation climatologies over Norway at 1‐km grid spacing. The climatologies are computed by an interpolation scheme (HCLIM+RK) combining the in situ observations with the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis. The comparison with methods using observations only proved that HCLIM+RK improves the accuracy of Norwegian climatologies and provides reliable precipitation patterns also over the remote areas not covered by rain‐gauges. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the variability and its temporal‐scale components of daily air temperature and precipitation simulated by two regional climate models (RCMs) and two driving global climate models (GCMs) from the EURO‐CORDEX and CMIP5 projects. The analysis was performed for eight geographical areas of central Europe for the period 1971–2000. After a brief evaluation of total variance, we focus on the ability of the simulations to represent short‐term, seasonal and long‐term variability components. This analysis was carried out for original time series as well as for series with the annual cycle removed. A fast Fourier transformation and a Kolmogorov–Zurbenko filter were used to separate the three temporal components. The two methods of time series decomposition generally agree, which confirms the robustness of the results. Although the observed total variability of daily air temperature and precipitation is not well represented in many cases and considerable differences among simulations exist, the separation of total variance into the three components is well represented. Regarding the air temperature, the results for the time series with the annual cycle removed are generally somewhat worse than for original series. The simulations tend to underestimate the short‐term component of temperature variability, while the results for the other two components are inconclusive. Moreover, it was found that temperature variability caused by the annual cycle is overestimated by the simulation of HadGEM2 GCM and CCLM4‐8‐17 RCM driven by HadGEM2, which explains the relatively poor results of these simulations regarding air temperature total variance and short‐term as well as seasonal components in the original temperature series. The RCMs provide better results than GCMs for temperature total variance but our results are rather inconclusive in the case of precipitation total variance and distribution of the variance of both studied variables into the three temporal components. Although the observed total variability of daily air temperature and precipitation over selected European areas is not well represented in many cases and considerable differences among simulations exist, the separation of total variance into the three components is well represented. The RCMs provide better results than GCMs for temperature total variance but our results are rather inconclusive in the case of precipitation total variance and distribution of the variance of both studied variables into the three temporal components. In the figure, location of the eight studied areas situated in the vicinity of central Europe and the orography of the E‐OBS data set. [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 characteristics of the northern and southern modes of the East Asian winter monsoon (EAWM) and their relationships with El Niño‐Southern Oscillation (ENSO) are further investigated in this paper using reanalysis data. The results demonstrate that the northern mode shows strong inter‐decadal variations, whereas the southern mode is marked by noticeable inter‐annual variations. The west–east pressure gradient plays a leading role in influencing northern mode, and both the west–east and north–south pressure gradients have significant impacts on the southern mode. The two modes are closely related, but their relationship shows inter‐decadal variations. The relationship between the southern mode and ENSO is significant and stable, but the relationship between the northern mode and ENSO is unstable and shows obvious inter‐decadal variations. The relationship between the northern mode and ENSO is significant before the late 1960s and after late 1990s, but it is not significant during the period between the late 1960s and late 1990s. ENSO influences the activity of northern mode mainly by changing the west–east pressure gradient. During the periods of a weak relationship between northern mode and ENSO, the variations in west–east pressure gradient may be dominated by the climate systems at mid–high latitudes, and the effects of ENSO are confined or offset. The inter‐decadal variations in the relationship between northern mode and ENSO may be modulated by the Pacific Decadal Oscillation (PDO) and Atlantic Multi‐decadal Oscillation (AMO), but their roles and importance have varied over time. The relationship between EAWM and ENSO and its inter‐decadal variations vary with the EAWM index, which is induced by the differences between the northern and southern modes. When the EAWM index is more closely correlated with the southern (northern) mode, its relationship with ENSO is (not) significant and stable (unstable). [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]

Over the last decades, general circulation model (GCM) simulations have been regularly evaluated in terms of their ability to reproduce the historical frequency of significantly recurrent weather patterns (WP) observed at the regional scale. Thus, a good simulation of the frequency of these particular WP by the GCM is generally conditioning the good representation of the regional statistics of surface variables such as temperature and precipitation. In this paper, the seasonal frequency of eight particular WP have been calculated using the daily geopotential height fields simulated by an ensemble of 26 Coupled Model Intercomparison Project Phase 5 (CMIP5) GCM. These WP are known as significantly influencing the French regional hydro‐climatology in terms of both frequency of low‐flows and high‐precipitation events. Four different bias correction methods have been applied on the simulated geopotential height fields before the calculation of the seasonal WP frequencies. The GCM ensemble showed overall good performances in terms of the simulation of WP seasonal frequencies. The application of a spatially and temporally non‐homogenous correction of simulated geopotential height fields improved significantly the simulation of WP frequencies for the four seasons. Finally, the evolution of the WP frequencies over the next century has been quantified. Three WP (WP2, WP4 and WP8) have pronounced seasonal changes, with WP2 and WP4 being less frequent in summer and autumn seasons, respectively, while WP8 being more frequent over spring, summer and autumn seasons. The strong simulated frequency evolution of WP2 and WP8 is an interesting result, which predicts the climate to be drier with time for France. Thus, WP2 (western oceanic circulation), grouping rainy days over the northern France region, is simulated as less frequent in future summers, while WP8 (anticyclonic situations), which groups non‐rainy days over France, is simulated as more frequent in future summers. [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 Water scarcity is a critical issue in Iberia but few studies have investigated future drought over the region. The few that do are continental or global studies and do not report the range of possible future projections. In this paper, historical drought and future projections of drought were examined, using observed and downscaled rainfall data from climate models, for the main Iberian international basins (Douro, Tagus and Guadiana). Two drought indices were used, the standardized precipitation index ( SPI) and the drought severity index ( DSI). However, problems were found in the distribution fitting required for the calculation of SPI which render this index inadequate for assessing droughts in Iberia. The skill of CMIP5 climate models in representing historical drought for the Douro, Tagus and Guadiana is very variable with some not showing enough persistence of dry conditions, and others simulating droughts that are too long and too severe. Nevertheless, the observed range of drought conditions for these basins was encompassed by the ensemble members. Furthermore, we found no relationship between performance in simulating mean large-scale circulation and model ability to reproduce the historical drought characteristics for the region. All models project an intensification of drought conditions for the three basins. However, some only project small increases, while most project extreme multi-year droughts by the end of the century. We found that climate model future projections are neither related to their performance in simulating historical drought nor to their large-scale circulation patterns. This result emphasises the need for climate change impact studies to take into account the whole range of climate model projections in order to provide the best information for robust adaptation. Choosing one or a subset of climate models based on historical performance would not lead to a credible and justified reduction in uncertainty. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents a regional and seasonal study of extreme point rainfall scaling from 10 min to 2 years. To do this, the highest point-based rainfall list based on these temporal periods was calculated from the Spanish Meteorological Service ( AEMET) precipitation databases with more than 11 000 rain-gauge stations, with the longest series ranging from 1805 to 2014 (209 years). This list constitutes the register of single station largest amounts of precipitation in Spain ever recorded for selected periods, including for example the values for 2 h (193 mm), 24 h (817 mm) or 1 year (5503 mm). Rainfall extremes for 10 min periods are evenly distributed in coastal and inland areas. Daily precipitation extremes are mostly concentrated over the Mediterranean coast while from durations from one month to two years, extremes are located in southern and northwest Spain. Extreme data obtained were compared with existing worldwide rainfall records for equivalent periods. Results indicate that Spanish extreme rainfall scaling relating R depth (in mm) against D duration (in minutes) may be expressed as a potential law R = 21.8 D0.422 ( R = 43.6 D0.507 for worldwide data). We propose the upper envelope line (greater or equal to extreme rainfall values) parallel to the potential fit law as a simple method to estimate possible extreme records for different time scales. Using this method, worldwide envelope may be expressed as R = 60.5 D0.507 and the Spanish envelope as R = 39.3 D0.422. Further analysis stratifying results by season and region show that seasonal scaling has more variability than regional scaling. The methodology described can be readily applied to other regions for which detailed rainfall databases exist. Applications of the results include using the scaling found as a reference for classification of heavy precipitation events for temporal scales. [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 The development of Adapted Caussinus-Mestre Algorithm for homogenising Networks of Temperature series ( ACMANT), one of the most successful homogenisation methods tested by the European project COST ES0601 ( HOME) has been continued. The third generation of the software package ' ACMANT3' contains six programmes for homogenising temperature values or precipitation totals. These incorporate two models of the annual cycle of temperature biases and homogenisation either on a monthly or daily time scale. All ACMANT3 programmes are fully automatic and the method is therefore suitable for homogenising large datasets. This paper describes the theoretical background of ACMANT and the recent developments, which extend the capabilities, and hence, the application of the method. The most important novelties in ACMANT3 are: the ensemble pre-homogenisation with the exclusion of one potential reference composite in each ensemble member; the use of ordinary kriging for weighting reference composites; the assessment of seasonal cycle of temperature biases in case of irregular-shaped seasonal cycles. ACMANT3 also allows for homogenisation on the daily scale including for break timing assessment, gap filling and ANOVA application on the daily time scale. Examples of efficiency tests of monthly temperature homogenisation using artificially developed but realistic test datasets are presented. ACMANT3 can be characterized by improved efficiency in comparison with earlier ACMANT versions, high missing data tolerance and improved user friendliness. Discussion concerning when the use of an automatic homogenisation method is recommended is included, and some caveats in relation to how and when ACMANT3 should be applied are provided. [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 It is known that the El Niño - Southern Oscillation ( ENSO) episodes have a great influence on South American precipitation and its extreme events during austral autumn (from March until May, MAM) and winter (from June until August, JJA) that occur after the ENSO peak (normally this happens on austral summer). Recent papers have studied the two types of ENSO and their influence on atmosphere-ocean system. This study analysed the influence of Central and East equatorial Pacific ENSO on South American seasonal/monthly mean precipitation and its extreme events during MAM and JJA. The composites of precipitation anomalies, during these two types of ENSO, show that there are different, even opposite patterns over South America. In MAM, there is an increased precipitation in southeastern South America and a decrease in the northeast South America during East El Niño ( EEN) and an increased precipitation in central Brazil during Central El Niño ( CEN). In JJA, the signs of anomaly precipitation are opposite between CEN (less precipitation) and EEN (more precipitation) over southeastern South America. The extreme precipitation events show patterns consistent with the precipitation anomaly patterns, but, normally, the changes in the frequency of extremes precipitation events affect more extensive areas than the total precipitation. If monthly or seasonal atmospheric anomalies in a certain region during one of the types of ENSO are similar (opposite) to the atmospheric anomalies associated with extreme precipitation events in this region, then there is enhancement (suppression) of the frequency of extreme events in this region during this type of ENSO. [ABSTRACT FROM AUTHOR]

ABSTRACT The study of weather extremes is critical because of their great impact on the environment, economy and society. The identification of areas at greater risk of extreme conditions, and of meteorological situations that give rise to such conditions, enhances the understanding of climate risks and helps establish measures to reduce adverse impacts. In the current paper, precipitation extreme events ( PEEs) in Spain between 1960 and 2011 were analysed. Thresholds for determining event severity were defined using 99th percentiles. First, regions of extreme weather risk were identified and then trends of extreme precipitation index were analysed using the Mann-Kendall test. To better understand atmospheric processes associated with extreme weather events in each season, synoptic-scale fields of events exceeding the 99th percentile were analysed. By applying non-hierarchical K-means clustering, we defined six large-scale atmospheric patterns that largely explain the spatiotemporal distribution of PEEs in the study area. PEEs on the western Iberian Peninsula mainly occurred with zonal flow, with a long Atlantic fetch generating moisture advection towards that area. On the eastern peninsula, the most important pattern for PEE production is characterized by a cutoff low at mid-levels together with easterly moisture flow. The relationship of PEEs with teleconnection patterns, such as the North Atlantic Oscillation ( NAO), Mediterranean Oscillation ( MO) and Western Mediterranean Oscillation ( WeMO), showed that nearly all the events over the southwestern peninsula were during the NAO- and MO-negative phases. However, on the Mediterranean coast, the negative WeMO phase had greater influence. By contrast, the northwestern peninsula and eastern Cantabrian coast showed weaker relationships between these indices and PEEs. The results show a clear ability to identify regions exposed to extreme precipitation hazards. The correct identification of synoptic patterns associated with each type of weather extreme will assist the prediction of such events, thereby providing useful information for decision making and warning systems. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper is concentrated on the evaluation of circulation type classifications (CTCs) from the European Action COST733 catalogue version 2.0 in terms of their ability to capture winter precipitation, expressed as percentage, over Spanish Iberia and the Balearic Islands. The explained variation, the pseudo-F statistics and the Brier skill score are used to quantify the explanatory power of circulation classifications. As secondary aims, the impact of using different number of circulation types, additional types of variables and 4-day sequences in the generation of classifications is analysed. Although no optimal method has been found, nevertheless, the results suggest that the use of CTCs based on optimization algorithms are, in general, performing better than those which are based on other algorithms (i.e. leader algorithms). Distinct variations in skill exist not only among classifications from different groups of basic methods but as well between classifications from the same method group; being remarkable the behaviour of the optimum random centroid method. Results are very dependent on the metric, for the explained variation, and the Brier skill score, the larger the number of circulation types, the better the performance; contrary to the behaviour of the pseudo-F statistic. The inclusion of 500 hPa vorticity in the generation of classifications improves results while a general deterioration is observed when considering 4-day sequences. These results are only valid for the selected season and cannot be transferred to other locations and seasons. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper investigates the interannual variability of precipitation over the South Asian monsoonal region in May, during which the South Asian summer monsoon is generally established. The South Asian monsoonal region in this study is referred to as a broad area that includes the Arabian Sea, the Indian peninsula, the Bay of Bengal, and the Indochina peninsula. The precipitation exhibits a significant enhancement in May, compared to that in the previous month. The present results indicate that the interannual variability of May precipitation in this region is significantly regulated by two independent factors: The Europe-West Asia ( EWA) teleconnection and El Niño Southern Oscillation. The EWA teleconnection pattern is characterized by the see-saw pattern of upper-tropospheric geopotential height anomalies between the Europe and the Iranian plateau. Both the factors modulate the meridional gradient of tropospheric temperature and lower-tropospheric zonal winds, and thus affect the rainfall in the monsoonal region. Therefore, both the extratropical circulation teleconnection and tropical forcing are crucial for inducing rainfall variability in May over the monsoonal region. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, we analyse observed changes in characteristics of sub-daily heavy summer precipitation and erosive precipitation events for the Czech Republic, taking into consideration 51 years of data (1961-2011) for 17 stations. The sub-daily data were checked for consistency with the daily control records, and unreliable data were removed from the data set. Subsequently, four statistical tests were applied to assess the homogeneity of the data set. The trend magnitude was estimated using the Theil-Sen slope estimator, and two tests were applied to evaluate its significance. For most of the indices, the tests did not indicate inhomogeneity, with the exception of characteristics related to rainfall intensity. The trends are positive for most of the stations and most precipitation characteristics, and significant positive trends are much more frequent than negative trends. The analysis revealed a significant increase in the contribution of heavy precipitation to the precipitation total in half of the stations at short aggregation levels. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper examines the skill of seasonal precipitation forecasts over Iran using one two-tiered model, three National Multi-Model Ensemble ( NMME) models, and two coupled ocean-atmosphere or one-tiered models. These models are, respectively, the ECHAM4.5 atmospheric model that is forced with sea surface temperature ( SST) anomalies forecasted using constructed analogue SSTs ( ECHAM4.5- SSTCA); the IRI-ECHAM4.5-DirectCoupled, the NASA-GMAO-062012 and the NCEP-CFSv2; and the ECHAM4.5 Modular Ocean Model version 3 ( ECHAM4.5- MOM3-DC2) and the ECHAM4.5- GML-NCEP Coupled Forecast System ( CFSSST). The precipitation and 850 hPa geopotential height fields of the forecast models are statistically downscaling to the 0.5° × 0.5° spatial resolution of the Global Precipitation Climatology Centre ( GPCC) Version 6 gridded precipitation data, using model output statistics ( MOS) developed through the canonical correlation analysis ( CCA) option of the Climate Predictability Tool ( CPT). Retroactive validations for lead times of up to 3 months are performed using the relative operating characteristic ( ROC) and reliability diagrams, which are evaluated for above- and below-normal categories and defined by the upper and lower 75th and 25th percentiles of the data record over the 15-year test period of 1995/1996 to 2009/2010. The forecast models' skills are also compared with skills obtained by (a) downscaling simulations produced by forcing the ECHAM4.5 with simultaneously observed SST, and (b) the 850 hPa geopotential height NCEP-NCAR (National Centers for Environmental Prediction-National Center for Atmospheric Research) reanalysis data. Downscaling forecasts from most models generally produce the highest skill forecast at lead times of up to 3 months for autumn precipitation - the October-November-December ( OND) season. For most seasons, a high skill is obtained from ECHAM4.5- MOM3-DC2 forecasts at a 1-month lead time when the models' 850 hPa geopotential height fields are used as the predictor fields. For this model and lead time, the Pearson correlation between the area-averaged of the observed and forecasts over the study area for the OND, November-December-January ( NDJ), December-January-February ( DJF) and January-February-March ( JFM) seasons were 0.68, 0.62, 0.42 and 0.43, respectively. [ABSTRACT FROM AUTHOR]

ABSTRACT Land and water management in semi-arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya region, encompassing around 50 stations with at least 30 years of data. We describe the data set, including quality control procedures and statistical break detection. Trends in mean precipitation and extreme indices calculated from these data for individual rainy seasons are compared with corresponding trends in reanalysis products. From 1979 to 2011, mean precipitation decreased at 75% of the stations during the 'long rains' (March to May) and increased at 70% of the stations during the 'short rains' (October to December). Corresponding trends are found in the number of heavy precipitation days, and maximum of consecutive 5-day precipitation. Conversely, an increase in consecutive dry days within both main rainy seasons is found. However, trends are only statistically significant in very few cases. Reanalysis data sets agree with observations with respect to interannual variability, while correlations are considerably lower for monthly deviations (ratios) from the mean annual cycle. While some products well reproduce the rainfall climatology and some the spatial trend pattern, no product reproduces both. [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]

ABSTRACT The prospects of validating areal data from climate models by site observations depend critically on the spatial representativeness of the sites. This paper introduces a simple parameter-free approach to quantify the spatial representativeness of single stations with an application to time series of daily near surface air temperature and precipitation at European weather stations. Complementing classical methods such as spatial auto-correlation and variogram, our approach provides a well defined area around each station for which the station is representative, based on a similarity threshold but otherwise without any limiting assumptions about distribution or spatial stationarity of the data. This area is interpreted as the station's 'inverse footprint' and its areal extent provides a measure of representativeness. We find a generally higher representativeness for temperature compared to precipitation, but also a strong seasonal dependence. For instance, temperature representativeness in boreal winter is related to the influence of circulation with large 'inverse footprints' over Central and Eastern Europe and Scandinavia. Representativeness in summer exhibits similar patterns but is lower. Precipitation representativeness displays related patterns of representativeness and circulation control in winter, but vanishes in summer, probably due to the small-scale characteristics of convective precipitation. Precipitation representativeness is strikingly high around the Mediterranean, which is a consequence of the large numbers of synchronous dry days in this region. The physical plausibility of the results underlines the applicability of our approach. Although not investigated here, the 'inverse footprint' also provides information on the directional dependence of representativeness at the station level. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents an analysis of winter climate variability based on daily mean temperature and precipitation data since 1970 in the Chic-Chocs Mountain range (located in the Gaspé Peninsula, Eastern Quebec, Canada). Mountain environments are particularly sensitive to rapid climate change and are therefore good indicators of recent global warming. The main goal of this study is to demonstrate how joint probability temperature/precipitation distributions can be used to estimate winter condition changes (trends) for six meteorological stations in the study area (the altitudinal range for the stations is from 5 to 574 m). The presence and persistence of snow cover was also estimated. Previous studies have shown a lack of evidence of significant trends in snow-cover characteristics (density, depth and snow water equivalent (SWE)) from the early 1980s to the present, despite an increase in temperature over the same period. A reanalysis of these data sets in addition to the use of a combination of temperature and precipitation data categorized into four modes (warm/wet, warm/dry, cold/wet and cold/dry) was also performed. Despite this new analysis, no clear evidence of climate change could be found in the study area over the last four decades. The results revealed that patterns and trends are quite different from one station to another, but when the environment is taken into account (valley or plateau, coastal versus inland) some apparent patterns emerge. [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]

After the frequent and long drought episodes of the 1980s, a plethora of case studies have shown that West Africa remains a hot spot in the continent where despite its numerous water resources, extreme rainfall variability remains a profound challenge to the availability of freshwater for agriculture and ecosystem services. In this paper, we assess the recent flux in water availability over West Africa by investigating variations in net-precipitation (i.e. the maximum available freshwater flux) using wavelet analysis. Net-precipitation was obtained as a residual of the atmospheric water balance, and its variability compared to precipitation, temperature, evaporation, soil moisture and normalized difference vegetation index using wavelet power transforms and coherence analysis. Results from the study indicate that the variance in water flux over the region has been progressively reducing, suggesting a relative reduction in extreme hydrological conditions. Also, the wavelet coherence analysis revealed that the observed decreasing rate of available freshwater is highly coupled to a low frequency modulating El-Nino activity that induced lower changes in rainfall variance, as well as higher evaporation variance. Spatial trends in the annual-scaled average wavelet power indicated that the south-western parts of the region experienced the most reduction in rainfall flux. The highest deficit in net-precipitation flux was found in the dry sub-humid climatic zone, which is drained by major regional rivers, including the Niger and Volta. Considering the long-term variability in freshwater (i.e. from 1979 to 2010), we found the 1980s to be the driest decade and the 1990s being its recovery period, while the 2000s proved to be a considerably dry decade, suggesting a strong multi-decadal variability. [ABSTRACT FROM AUTHOR]

The South Pacific region is an area affected by characteristic precipitation patterns undergoing extreme events such as tropical cyclones and droughts. First, a daily weather typing of precipitation is presented, based on principal component analysis and k‐means clustering using precipitation and atmospheric circulation variables derived from sea‐level pressure and wind reanalysis fields. As a result, five weather types (WTs) are presented, able to capture distinct precipitation spatiotemporal patterns, interpretable in terms of salient regional climate features. Second, we undertake the calibration of the TRMM precipitation product using a set of rain gauge stations as reference and scaling and empirical quantile mapping (eQM) as calibration techniques. Furthermore, we build upon the weather‐type classification to compare the results with a WT‐conditioned calibration approach. Overall, our results underpin the need of adjusting the existing TRMM biases, mostly relevant for the upper tail of their distribution, and advocate the use of correction techniques able to deal with quantile‐dependent biases—such as eQM—instead of a simple scaling, in order to obtain a more realistic representation of extreme precipitation events. The conditioning has shown only a marginal added value over the simple approach, although this minor improvement may prove relevant for applications focused on extreme event analysis. Furthermore, the weather types created can be applied to a wide variety of conditioned analyses in this region. [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 This paper examines the climate variability modes in the South American/Atlantic sector accompanying dry and wet years over north-eastern Brazil ( NEB) in which the tropical Pacific and Atlantic oceanic-atmospheric conditions usually associated, respectively, with dryness and wetness are absent. The analyses are for several variables and take into account the warm and cold Atlantic Multidecadal Oscillation ( AMO) phases ( WAMO and CAMO). Four cases are analysed: DRY-WAMO, DRY-CAMO, WET-WAMO and WET-CAMO. The main difference in the sea surface temperature ( SST) anomaly patterns in the tropics between the AMO phases responsible for the differences in the precipitation anomaly patterns is the differential longitude positioning of the warming or cooling of the surface waters in the equatorial Atlantic. In consequence, the anomalous Atlantic Hadley and Walker circulations also show differences between the AMO phases, which justify the observed precipitation anomalies over tropical South America for the analysed cases. The strong anomalous Atlantic Hadley cell determines the dipolar structure of the precipitation anomalies between NEB and northern South America for the DRY-WAMO and WET-WAMO cases. The strong anomalous Atlantic Walker cell defines the dryness over NEB for the DRY-CAMO, and both the strong anomalous Atlantic Hadley and Walker cells act together to yield an anomalous dry condition over NEB and wet condition over northern South America. Therefore, the results here provided clear indications that for climate monitoring and forecasting tasks, the AMO phases should be considered. These are new aspects of the tropical Atlantic variability that might be useful for climate monitoring purposes. [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]

This study aims to assess the performance of European Center for Medium‐Range Weather Forecasting (ECMWF) Reanalysis fifth generation (ERA5) in terms of the progress made over its predecessor, ERA‐Interim, over East Africa (EA) in reproducing observed rainfall. The observed rainfall used as reference rainfall are Global Precipitation Climatology Center (GPCC) and Climate Research Unit Time Series (CRU‐TS). The performance of ERA5 to its predecessor is evaluated using root‐mean‐square error (RMSE), correlation, and bias. The reductions of wet bias from ERA‐Interim to ERA5 are 16.81–6.94% from June to September (JJAS), 31.99–19.33% from September to December (SOND), and 29.24–17.69% from December to February (DJF) over most of EA relative to CRU‐TS. Similar reductions in the wet bias relative to GPCC are also noted. Spatially, notable reductions are observed over western Ethiopia, Sudan Republic, South Sudan, and Uganda. The decreasing trends revealed in the bias of seasonal ERA5 rainfall relative to CRU‐TS and GPCC are attributed to an increase in the number and quality of assimilated observations in ERA5 over its predecessors. RMSE of ERA5 rainfall relative to the two reference rainfall and correlations with the two reference rainfall are consistent with spatial and temporal features captured in the bias. Specifically, the correlation of the monthly time series of ERA5 ranges from 0.90 with CRU‐TS over equatorial EA (EEA) to 0.98 with GPCC over southern EA (SEA) in contrast to that of ERA‐Interim which ranges from 0.84 with CRU‐TS over EEA to 0.93 with CRU‐TS over SEA. However, the wet bias in ERA5 along the Great Rift Valley remained the same as in ERA‐Interim whereas spatial correlation of ERA5 with the two reference rainfall is relatively weaker than that of ERA‐Interim. [ABSTRACT FROM AUTHOR]

This paper presents key results from analysis of surface meteorological observations collected in the Northern Arabian/Persian Gulf (N Gulf; Kuwait, Bahrain, and NE Saudi Arabia), which spans a 40-years period (1973-2012). The first part of this study analyzes climate variability in the N Gulf, and relates them to teleconnection patterns (North Atlantic Oscillation, El Nino Southern Oscillation, and Indian Ocean Dipole). Results of the analysis indicate that during the study period the climate in the region experienced a general trend of increase in temperature (0.8°C), decrease in barometric pressure (1 mbar), reduction in humidity (6%), and decrease in visibility (9%). Significant correlations were found between the three teleconnection patterns and the meteorological conditions suggesting that seasonal variabilities in air temperature, barometric pressure, and precipitation are closely related to the teleconnection patterns. The second part of this study examines the 40-year variability of Shamal events (strong NW winds that commonly generate significant dust storms). The data suggests that on average Shamal events occur at a rate of 10 events year-1 with 85% of the events occurring during the summer and winter. The number of these events has increased in the past 14 years of the study period. These events resulted in abrupt changes in meteorological conditions: an increase in wind speed of 2.7 m s-1, a decrease in visibility of 1.7 km, and reduction in humidity of 4.3%. Seasonal variations in temperature (an increase in temperature during summer of 0.8°C, and a decrease of 1.5°C during winter) and barometric pressure (a decrease in barometric pressure during summer of 0.6 mbar and an increase of 7.8 mbar during winter) were observed during Shamal events. [ABSTRACT FROM AUTHOR]