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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]

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 We compared the values calculated for the three future periods with those obtained for the historical reference period 1961–1990.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]

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]

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]

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 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]

ABSTRACT This paper describes the construction of an updated gridded climate dataset (referred to as CRU TS3.10) from monthly observations at meteorological stations across the world's land areas. Station anomalies (from 1961 to 1990 means) were interpolated into 0.5° latitude/longitude grid cells covering the global land surface (excluding Antarctica), and combined with an existing climatology to obtain absolute monthly values. The dataset includes six mostly independent climate variables (mean temperature, diurnal temperature range, precipitation, wet-day frequency, vapour pressure and cloud cover). Maximum and minimum temperatures have been arithmetically derived from these. Secondary variables (frost day frequency and potential evapotranspiration) have been estimated from the six primary variables using well-known formulae. Time series for hemispheric averages and 20 large sub-continental scale regions were calculated (for mean, maximum and minimum temperature and precipitation totals) and compared to a number of similar gridded products. The new dataset compares very favourably, with the major deviations mostly in regions and/or time periods with sparser observational data. CRU TS3.10 includes diagnostics associated with each interpolated value that indicates the number of stations used in the interpolation, allowing determination of the reliability of values in an objective way. This gridded product will be publicly available, including the input station series ( and ). © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

In this paper we compare the Central England Temperature (CET) and England and Wales Precipitation (EWP) series with temperature and precipitation records from 24 individual meteorological stations throughout the UK over a 41-year period 1964-2004. With a single exception, the correlation of CET monthly means with those of all local stations was highly significant ( p < 0.001). Correlations with EWP were not as large, but for the most part were highly significant; exceptions occurring increasingly in the most northerly stations. Because of their general availability, the CET and EWP series will continue to be popular, and their use in a range of broad studies of UK climate appears to be justified. Copyright © 2006 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

In this study, we have developed a global in situ daily precipitation dataset based on quasi‐real‐time sub‐daily observations of precipitation totals for the 0000–0000 UTC (Co‐ordinated Universal Time) day everywhere in the world. The sub‐daily precipitation data from meteorological stations are obtained via the World Meteorological Organization's (WMO) Global Telecommunication System (GTS) and China Meteorological Administration Net (CMANet) archived by the National Meteorological Information Centre (NMIC) in China and the Integrated Surface Database (ISD) released by the National Centers for Environmental Information (NCEI) in the USA. We have combined these three sources into a global dataset, referred to as NMIC. Accumulated precipitation totals (depending on the country and the WMO region) are transmitted at a variety of times on the GTS. Of these, about 4,500 stations report daily for the 0000–0000 UTC day. Here, we significantly add to this, by developing two‐way accumulation algorithms to decompose other reported sub‐daily totals to shorter intervals, and then re‐cumulate them where possible to the 0000–0000 UTC day. Using these algorithms, we increase by 51.1% of the number of stations during 2009–2016 to around 6,800 day−1. Additionally, date boundary adjustment (sliding between 1 and 6 hours either side of 0000 UTC) raises the data volume to between 7,800 and 8,700 day−1. We compare our NMIC product with the First Guess Daily (FGD) product from the Global Precipitation Climatology Centre (GPCC) and GHCN‐Daily from NCEI (National Centers for Environmental Information). Root mean square differences between our NMIC and GPCC FGD products over the 2009–2016 period are around 3.4–3.7 mm·day−1 and the average consistency percentage is about 75.1–76.8%. Greater differences between NMIC and GHCN‐daily are found which are probably due to the non‐uniform date boundary in GHCN‐Daily. [ABSTRACT FROM AUTHOR]

Seasonality in Argentina is examined using precipitation observations from 56 weather stations north of 42°S and CRU gridded precipitation. The Walsh and Lawler Seasonality Index (SI) and Precipitation Concentration Index (PCI) are calculated to determine the different seasonality regimes. The main characteristic is an eastwest gradient, where precipitation tends to be more evenly distributed throughout the different months of the year in the east while rainfall in the west is concentrated in 3 months or less. High replicability values indicate that the wettest month generally occurs during a same period of months in central and northern Argentina. Several stations in eastern humid Argentina have significant positive changes in the mean of seasonality indices between 1961 and 1985 and 1986 and 2010, and increasing trend. In most cases this leads to a change in the regime from rather seasonal with a short dry season to a seasonal regime. Through a PAM Clustering technique a new regionalization of precipitation seasonality is obtained. The mean series in each cluster show a tendency towards more seasonal and highly seasonal regimes in all regions. The SI and PCI indices were calculated using the precipitation outputs of 18 global climate models (GCMs) from the Coupled Model Inter‐comparison Project Phase 5 (CMIP5) to examine the ability of these models to represent seasonality spatial distribution and changes in Argentina. To some extent the spatial distribution of seasonality is captured by models; however, there are considerable discrepancies in the location and extension of the eastwest gradient. The sign and location of trends and changes in the mean SI and PCI are adequately reproduced in only a few models. The low ability of GCMs to represent seasonality and its changes is a consequence of the difficulties GCMs have simulating precipitation characteristics in Argentina reported by different authors. [ABSTRACT FROM AUTHOR]

Drought being a complex natural hazard is challenging to monitor. Although standardized procedures for drought characterization are commonly used, the uncertainty about accurate drought characterization under various procedures always exists. Therefore, for effective drought mitigation policies, it is necessary to compare the performance of new and the existing drought procedures. In this study, we proposed a new procedure—The Drought Intensity Pattern Determinate (DIPD) to examine and compare the spatial‐temporal intensities of various drought episodes based on Standardized Drought Indices (SDI). The DIPD framework provides a new tool—The Drought Concentration Index (DCI) to understand the annual intensity of drought classes by alluding the observed frequencies of drought episodes. At the preliminary level of assessment, DIPD is employed at 52 meteorological stations of Pakistan, and compared three commonly used standardized drought indices: Standardized Precipitation Index (SPI), Standardized Evapotranspiration Index (SPEI) and Standardized Precipitation Temperature Index (SPTI). Exploratory analysis shows a mixed picture as all the drought indices behaving similar for some patterns of drought classes, while some classes show significant discrepancies. In addition, we assessed and compared the spatial distributions using spatial Poisson lognormal model by assuming SDI as a non‐Gaussian process for individual total classes of observed DCI. Results show that the proposed method has ability to incorporate the inner variability in patterns of drought classes. In summary, the DIPD provided a new regional based comparative framework, which accounts the all possible episodes of drought classes and effect of inner discrepancies among quantitative values of SDI. [ABSTRACT FROM AUTHOR]

The objective of this research was to estimate probable maximum precipitation (PMP) for the duration of 1 to 3 days in Thailand. Rainfall data were collected from 217 meteorological stations. Two methods for estimating PMP were applied: the generalized method which analysed actual storms data using meteorological process, and the Hershfield's statistical method which applied the frequency analysis of the annual maximum rainfall. Both methods were commonly used and were recommended by the World Meteorological Organization (WMO) for estimating PMP. PMP estimation results were presented as isohyetal maps. For the generalized method, most PMP values were found higher in the east and decreased towards the west. However, there was no clear trend with the statistical method in the PMP's spatial distribution. An analysis of the 3‐day PMP averages showed that PMP estimation using the generalized method is 10% higher than that of the statistical method. The study results were then applied to estimate PMP of six large dams in Thailand and compared with the ones used in the design of the spillways. It was found that PMP estimation based on the generalized method was closer to the value used in the spillway design of those dams than PMP estimation based on the statistical method. [ABSTRACT FROM AUTHOR]

The precipitation concentration index (PCI) is a powerful indicator for temporal precipitation distribution and is also very useful for the assessment of seasonal precipitation changes. The primary objectives of this study are to investigate and analyse the temporal–spatial variability patterns of annual and seasonal PCI values based on monthly precipitation data. These data were collected from 597 meteorological stations located throughout China, for the time period of 1960–2016, and were used to assess the impacts of geographical parameters (latitude, longitude, and altitude) on the PCI. Additionally, the possible teleconnection with the large‐scale circulation pattern was investigated. Our results reveal that the variation trend of annual PCI values has decreased significantly at a rate of −.234/10 year (α = .01) in China over the past 57 years. For all studied station records, 434 (72.7%) stations showed decreasing trends of PCI values, and these stations are distributed over large areas in China. On an annual scale, the average PCI value ranged from 11 in Hunan province to 44 in Qinghai province. The precipitation concentration in China can be described as strongly irregular in the western and northern parts of the northwest and in the northern region of the Tibetan Plateau, while it is irregular in the southwest and the north of China, and moderately irregular in some parts of the middle‐lower regions of the Yangtze River and southern China. The regularity of the annual precipitation pattern significantly decreased in spring, autumn, and winter from southeastern to northwestern China, and was the most in winter. However, the summer precipitation dispersion and the pattern in the considered period were more regular than those of the other seasons. Furthermore, changes in the PCI appear to be rather complex and possibly related to global atmospheric characteristics as well as geographical factors (latitude, longitude, and altitude). The results presented in this study indicate that the PCI is an essential feature for water resource planning, prediction of risk due to droughts or floods, and the management of natural resources. [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]

ABSTRACT: High‐resolution monthly precipitation climatologies for Italy are presented. They are based on 1961–1990 precipitation normals obtained from a quality‐controlled dataset of 6134 stations covering the Italian territory and part of the Northern neighbouring regions. The climatologies are computed by means of two interpolation methods modelling the precipitation‐elevation relationship at a local level, more precisely a local weighted linear regression (LWLR) and a local regression kriging (RK) are performed. For both methods, local optimisations are also applied in order to improve model performance. Model results are compared with those provided by two other widely used interpolation methods which do not consider elevation in modelling precipitation distribution: ordinary kriging and inverse distance weighting. Even though all the four models produce quite reasonable results, LWLR and RK show the best agreement with the observed station normals and leave‐one‐out‐estimated mean absolute errors ranging from 5.1 mm (July) to 11 mm (November) for both models. Their better performances are even clearer when specific clusters of stations (e.g. high‐elevation sites) are considered. Even though LWLR and RK provide very similar results both at station and at grid point level, they show some peculiar features. In particular, LWLR is found to have a better extrapolation ability at high‐elevation sites when data density is high enough, while RK is more robust in performing extrapolation over areas with complex orography and scarce data coverage, where LWLR may provide unrealistic precipitation values. However, by means of prediction intervals, LWLR provides a more straightforward approach to quantify the model uncertainty at any point of the study domain, which helps to identify the areas mainly affected by model instability. LWLR and RK high‐resolution climatologies exhibit a very heterogeneous and seasonal‐dependent precipitation distribution throughout the domain and allow to identify the main climatic zones of Italy. [ABSTRACT FROM AUTHOR]

ABSTRACT: Relative homogenization methods assume that measurements of nearby stations experience similar climate signals and rely therefore on dense station networks with high‐temporal correlations. In developing countries such as Peru, however, networks often suffer from low‐station density. The aim of this study is to quantify the influence of network density on homogenization. To this end, the homogenization method HOMER was applied to an artificially thinned Swiss network. Four homogenization experiments, reflecting different homogenization approaches, were examined. Such approaches include diverse levels of interaction of the homogenization operators with HOMER, and different application of metadata. To evaluate the performance of HOMER in the sparse networks, a reference series was built by applying HOMER under the best possible conditions. Applied in completely automatic mode, HOMER decreases the reliability of temperature records. Therefore, automatic use of HOMER is not recommended. If HOMER is applied in interactive mode, the reliability of temperature and precipitation data may be increased in sparse networks. However, breakpoints must be inserted conservatively. Information from metadata should be used only to determine the exact timing of statistically detected breaks. Insertion of additional breakpoints based solely on metadata may lead to harmful corrections due to the high noise in sparse networks. [ABSTRACT FROM AUTHOR]

ABSTRACT Using station data from the United States Historical Climatology Network, we preformed a running trend analysis of temperature, precipitation and drought in the Alabama-Coosa-Tallapoosa and Apalachicola-Chattahoochee-Flint river basins for the time period 1895-2012 on annual and monthly timescales. Our study found that long-term precipitation and temperature trends were statistically detectible but relatively slight in the order of an increase at 3 mm per decade for precipitation and a decline of 0.02 °C per decade for temperature. Running trend analyses for the time period 1895-2012 found field-significant and relatively large annual precipitation increases and temperature decreases between the 1950s and early 1980s associated with the 'warming hole'. The magnitude of precipitation trends for the aforementioned period was in the range of 7 mm per year for precipitation and 0.6 °C per decade for temperature. For temperature, we observed generally decreasing maximum, minimum and mean temperatures in the 1960s and 1970s and increasing temperatures from the 1970s to present. Minimum temperatures particularly showed a strong increase in recent summer months in the range of 0.3 °C per decade. Trends in the diurnal temperature range showed a recent narrowing during summer and fall months. Differences in the standardized precipitation index ( SPI) and standardized precipitation evapotranspiration index ( SPEI) did not show a strong effect of temperature on drought for this region. [ABSTRACT FROM AUTHOR]

ABSTRACT In 2015, large parts of Europe were characterized by extraordinary high summer temperatures, accompanied by very dry conditions, particularly in central-eastern Europe. Several major heat episodes occurred from the end of June until mid-September. We provide an ad-hoc evaluation of the observed climatological extremes in a secular context, by using a set of long station time series in daily resolution. Our data set comprises 42 temperature and 43 precipitation records, predominantly starting already in the 19th century. To investigate local record values, the individual full record length is analysed for each station, while regionally averaged analyses are presented for the core study period of 1901-2015. The study area covers Europe's central latitudes (44° to 52°N), extending from England in the west up to the central Ukraine in the east. During summer 2015, various indices representing extremely high maximum and minimum temperatures (strongly) exceeded previous record high values, mainly in an area extending from eastern Germany to western Ukraine. Additionally, severely to extremely dry conditions with unusually frequent dry days were prevailing particularly in the (central-) eastern part of the study area. Drought indices combining temperature and precipitation revealed drought conditions comparable or even worse than those of former extreme summers like 2003. [ABSTRACT FROM AUTHOR]

ABSTRACT Here, we present an analysis of monthly, seasonal, and annual long-term precipitation time-series compiled from coastal meteorological stations in Greenland and Greenland Ice Sheet ( GrIS) ice cores (including three new ice core records from ACT11D, Tunu2013, and Summit2010). The dataset covers the period from 1890 to 2012, a period of climate warming. For approximately the first decade of the new millennium (2001-2012) minimum and maximum mean annual precipitation conditions are found in Northeast Greenland (Tunu2013 c. 120 mm water equivalent (w.e.) year−1) and South Greenland (Ikerasassuaq: c. 2300 mm w.e. year−1), respectively. The coastal meteorological stations showed on average increasing trends for 1890-2012 (3.5 mm w.e. year−2) and 1961-2012 (1.3 mm w.e. year−2). Years with high coastal annual precipitation also had a: (1) significant high number of precipitation days ( r2 = 0.59); and (2) high precipitation intensity measured as 24-h precipitation ( r2 = 0.54). For the GrIS the precipitation estimated from ice cores increased on average by 0.1 mm w.e. year−2 (1890-2000), showing an antiphase variability in precipitation trends between the GrIS and the coastal regions. Around 1960 a major shift occurred in the precipitation pattern towards wetter precipitation conditions for coastal Greenland, while drier conditions became more prevalent on the GrIS. Differences in precipitation trends indicate a heterogeneous spatial distribution of precipitation in Greenland. An Empirical Orthogonal Function analysis reveals a spatiotemporal cycle of precipitation that is linked instantaneously to the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation and with an ∼6 years lag time response to the Greenland Blocking Index. [ABSTRACT FROM AUTHOR]

ABSTRACT This study investigated spatial and temporal variations of extreme precipitation over Yunnan Province during 1960-2012. On the basis of a dataset from 120 meteorological stations covering the region, ten precipitation indices derived from daily precipitation were computed and analysed. Our results indicate the precipitation indices showed spatially complex trends. Most precipitation indices present increasing trends in western Yunnan and decreasing trends in eastern Yunnan. The western, southern and central regions experienced an increase in consecutive dry days (CDDs) and decrease in consecutive wet days (CWDs). In addition, a widespread increase was also found in precipitation intensity over Yunnan. On a region-wide scale, a weak decrease was observed in total precipitation, accompanied by an increase in precipitation intensity. CDDs tended to be prolonged while the CWDs tended to be shortened. The days with precipitation amounts totaling more than 10 mm and maximum 5-day precipitation amount had decreasing but not significant trends. In contrast, insignificant increases were found for the maximum 1-day precipitation and annual total precipitation exceeding 95th and 99th percentiles. The contribution of extreme precipitation to total precipitation increased during 1960-2012. Overall, occurrences of extreme precipitation are more concentrated in time. The weakening of the Asian summer monsoon strength and local topography had contribution to the variations of extreme precipitation over Yunnan. However, the forcing mechanisms are very complicated and need to be studied in subsequent work. [ABSTRACT FROM AUTHOR]

Landscape-scale ecological modelling has been hindered by suitable high-resolution surface meteorological datasets. To overcome these limitations, desirable spatial attributes of gridded climate data are combined with desirable temporal attributes of regional-scale reanalysis and daily gauge-based precipitation to derive a spatially and temporally complete, high-resolution (4-km) gridded dataset of surface meteorological variables required in ecological modelling for the contiguous United States from 1979 to 2010. Validation of the resulting gridded surface meteorological data, using an extensive network of automated weather stations across the western United States, showed skill comparable to that derived from interpolation using station observations, suggesting it can serve as suitable surrogate for landscape-scale ecological modelling across vast unmonitored areas of the United States. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Annual, seasonal and monthly rainfall trends from 1961 to 2006 period were analysed in this study by applying various statistical tools to data from 553 Spanish weather stations. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, while the statistical significance was determined using the non-parametric Mann-Kendall test. Geostatistical interpolation techniques were applied to generate rainfall trend surfaces. Combining classic trends tests and spatially interpolated precipitation permits the spatio-temporal visualization of detected trends. Updated trends reveal that rainfall is generally decreasing in January, February, March, April, and June. Around 61, 44 and 12% of the whole territory is evidencing significant negative trends in February, June and March, respectively. Significant precipitation decreases are also noted in more than 28% of Spain in summer and winter. On the contrary, rainfall is significantly increasing in October in more than 21% of Spain and areas mainly located in north-western areas. May, August, September and autumn also show significant positive trends in the period 1961-2006, although the percentages are lower than for negative trends. Finally, the annual precipitation is significantly decreasing in 11% of the territory. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article presents an analysis of annual and seasonal precipitation series of period 1961-2006 developed from 59 synoptic meteorological stations across Italy. It applied rotated principal component analysis (PCA) to monthly data and generated loading maps. The study found that annual cumulated precipitation series did not show significant levels of change and that only in winter was a precipitation trend seen in northern and Central Italy.

The article presents an analysis of spatial and temporal changes of temperature and precipitation at 143 weather stations in ten Asia-Pacific Network (APN) countries from 1955 until 2007. The study highlights annual and seasonal changes in temperature means and extreme events. Meanwhile, this researchdemonstrate shortcomings of indices based on set thresholds which investigate extreme climate events across the regions acquiring multiple climate zones.

The spatial variations of trends of relevant extreme precipitation indices were examined for 138 rainfall stations in South Africa for the period 1910 to 2004, a follow-up study of various others on precipitation trends in the region. This study aims to inform on trends in daily extreme precipitation indices, over as long a period with instrumental data as possible, while also retaining as sufficient a spatial coverage of results as possible. Data should also be forthcoming from climate stations with the time series spanning the complete study period, avoiding patching of data which can cause inhomogeneities. Some significant changes in indices, averaged over specific areas in South Africa, could be identified. These include areas with significant increases and decreases in annual precipitation, increases in the longest annual dry spell indicating more extreme dry seasons, increases in the longest annual wet spells indicating more extreme wet seasons, and increases in high daily precipitation amounts. The conclusion is that, while in the largest part of South Africa there has been no real evidence of changes in precipitation over the past century, there are however some identifiable areas where significant changes in certain characteristics of precipitation have occurred over the period 1910 to 2004. Copyright © 2006 Royal Meteorological Society [ABSTRACT FROM AUTHOR]