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In this paper, we have analyzed the time series of daily values for three meteorological elements, two continuous and a discontinuous one, i.e., the maximum and minimum air temperature and the precipitation. The analysis was done based on the observations from seven stations in Serbia from the period 1951-2010. The main aim of this paper was to quantify the complexity of the annual values for the mentioned time series and to calculate the rate of its change. For that purpose, we have used the sample entropy and the Kolmogorov complexity as the measures which can indicate the variability and irregularity of a given time series. Results obtained show that the maximum temperature has increasing trends in the given period which points out a warming, ranged in the interval 1-2 °C. The increasing temperature indicates the higher internal energy of the atmosphere, changing the weather patterns, manifested in the time series. The Kolmogorov complexity of the maximum temperature time series has statistically significant increasing trends, while the sample entropy has increasing but statistically insignificant trend. The trends of complexity measures for the minimum temperature depend on the location. Both complexity measures for the precipitation time series have decreasing trends. [ABSTRACT FROM AUTHOR]

Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes, like heat and drought occurring simultaneously, may have a greater impact on society than their univariate counterparts and have recently become an active field of study. In this paper, we use a 12-member ensemble of high-resolution (7 km) regional climate simulations with the regional climate model COSMO-CLM over central Europe to analyze the climate change signal and its uncertainty for compound heat and drought extremes in summer by two different measures: one describing absolute (i.e., number of exceedances of absolute thresholds like hot days), the other relative (i.e., number of exceedances of time series intrinsic thresholds) compound extreme events. Changes are assessed between a reference period (1971–2000) and a projection period (2021–2050). Our findings show an increase in the number of absolute compound events for the whole investigation area. The change signal of relative extremes is more region-dependent, but there is a strong signal change in the southern and eastern parts of Germany and the neighboring countries. Especially the Czech Republic shows strong change in absolute and relative extreme events. [ABSTRACT FROM AUTHOR]

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies. [ABSTRACT FROM AUTHOR]

This paper analyzes climate variability and change in the Urmia Lake Basin, northwest of Iran. Annual average of the following data time series has been analyzed by statistical methods: dry bulb temperature, maximum and minimum temperature, precipitation, and number of rainy and snowy days. We have also used mean monthly temperature and precipitation data for analysis of drought spells for the period 1964-2005 to find out whether fluctuations in the lake level are attributable to natural drought. Our results indicate that mean precipitation has decreased by 9.2 % and the average maximum temperature has increased by 0.8°C over these four decades. The seasonal changes are particularly visible in winter and spring. Results of the Palmer Drought Severity Index show that on average, drought episodes have hit the Urmia Lake Basin every 5 years and most of them reached severe levels, but recent droughts have become more intense and last longer. [ABSTRACT FROM AUTHOR]

Long instrumental records of meteorological variables such as temperature and precipitation are very useful for studying regional climate in the past, present, and future. They can also be useful for understanding the influence of large-scale atmospheric circulation processes on the regional climate. This paper investigates the monthly, winter, and annual temperature time series obtained from the instrumental records in Zagreb, Croatia, for the period 1864-2010. Using wavelet analysis, the dominant modes of variability in these temperature series are identified, and the time intervals over which these modes may persist are delineated. The results reveal that all three temperature records exhibit low-frequency variability with a dominant periodicity at around 7.7 years. The 7.7-year cycle has also been observed in the temperature data recorded at several other stations in Europe, especially in Northern and Western Europe, and may be linked to the North Atlantic Oscillation (NAO) and/or solar/geomagnetic activity. [ABSTRACT FROM AUTHOR]

The Mediterranean region is an area potentially vulnerable to climatic changes. In fact, it is characterized by a significant precipitation variability resulting from synoptic dynamics of hazardous events moving and evolving along the Mediterranean basin. In this paper, the results of an investigation on rainfall trend in the Sardinia region are presented. The trend analysis has been performed by means of the Mann–Kendall test and of the Theil–Sen estimator applied on annual, seasonal, and monthly scales. To this aim, a monthly database of precipitation registered at 158 rain gauges, with an average observation of 84 years, was used for the analyses. The results mainly evidenced a rainfall amount reduction in the winter months and an increase during the summer months. The monthly rainfall distribution throughout the year was also investigated by means of the precipitation concentration index (PCI). A negative trend emerged and, more specifically, a tendency towards a more uniform rainfall distribution on the Sardinia region throughout the year. [ABSTRACT FROM AUTHOR]

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

In this paper, we quantify the changes in precipitation distribution in south-western Poland between the periods 1891-1930 and 1981-2010. The average monthly precipitation totals available for 368 and 245 stations, respectively, are spatially interpolated and processed to calculate maps of differences and pluvial continentality indices for both periods. The maps are analysed against changes in atmospheric circulation and take into account the potential role of the mountain barrier of the Sudetes. The main findings are (1) winter totals generally increased in conjunction with a higher frequency of zonal circulation; it is more pronounced in the upper parts of the Sudetes due to orographic effects; (2) a decreased frequency of zonal circulation together with an increased frequency of southern flows has likely led to the reduction of precipitation in spring and autumn. These changes have led to a significant modification of the region's pluvial regime, mostly by decreasing continentality features (especially in the Sudetes and the western lowlands). In addition, the strong sheltering influence of the mountain barrier is observed, driving the preservation or even the enhancement of the continental pluvial characteristics in the north-eastern to eastern foregrounds of the Sudetes. This leads to the conclusion that in areas where long-term observed trends or future projections of precipitation are ambiguous, there may occur significant modifications in regional characteristics, especially as a result of changes in atmospheric circulation modified by local orography. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) is responsible for the climatic variability in the Northern Hemisphere, in particular, in Europe and is related to extreme events, such as droughts. The purpose of this paper is to study the correlation between precipitation and winter (December-January-February-March (DJFM)) NAO both for the historical period (1951-2000) and two future periods (2001-2050 and 2051-2100). NAO is calculated for these three periods by using sea level pressure, while precipitation data from seven climate models following the representative concentration pathway (RCP) 8.5 are also used in this study. An increasing trend in years with positive DJFM NAO values in the future is defined by this data, along with higher average DJFM NAO values. The correlation between precipitation and DJFM NAO is high, especially in the Northern (high positive) and Southern Europe (high negative). Therefore, higher precipitation in Northern Europe and lower precipitation in Southern Europe are expected in the future. Cross-spectral analysis between precipitation and DJFM NAO time series in three different locations in Europe revealed the best coherence in a dominant cycle between 3 and 4 years. Finally, the maximum drought period in terms of consecutive months with drought is examined in these three locations. The results can be used for strategic planning in a sustainable water resources management plan, since there is a link between drought events and NAO. [ABSTRACT FROM AUTHOR]

The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by − 2.15% under RCP 4.5 and − 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood. [ABSTRACT FROM AUTHOR]

In this paper, expected changes in the spatial and altitudinal distribution patterns of Holdridge life zone (HLZ) types are analysed to assess the possible ecological impacts of future climate change for the Carpathian Region, by using 11 bias-corrected regional climate model simulations of temperature and precipitation. The distribution patterns of HLZ types are characterized by the relative extent, the mean centre and the altitudinal range. According to the applied projections, the following conclusions can be drawn: (a) the altitudinal ranges are likely to expand in the future, (b) the lower and upper altitudinal limits as well as the altitudinal midpoints may move to higher altitudes, (c) a northward shift is expected for most HLZ types and (d) the magnitudes of these shifts can even be multiples of those observed in the last century. Related to the northward shifts, the HLZ types warm temperate thorn steppe and subtropical dry forest can also appear in the southern segment of the target area. However, a large uncertainty in the estimated changes of precipitation patterns was indicated by the following: (a) the expected change in the coverage of the HLZ type cool temperate steppe is extremely uncertain because there is no consensus among the projections even in terms of the sign of the change (high inter-model variability) and (b) a significant trend in the westward/eastward shift is simulated just for some HLZ types (high temporal variability). Finally, it is important to emphasize that the uncertainty of our results is further enhanced by the fact that some important aspects (e.g. seasonality of climate variables, direct CO effect, etc.) cannot be considered in the estimating process. [ABSTRACT FROM AUTHOR]

Large-scale atmospheric circulations significantly affect regional precipitation patterns. However, it is not well known whether and how these phenomena affect regional precipitation distribution in northern China. This paper reported the individual and coupled effects of El Niño-Southern Oscillation (ENSO), Indian summer monsoon (ISM), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO) on annual precipitation for the Ordos Basin, an arid and semi-arid basin, currently with major industries of coal, fossil oil, natural gas, and halite in north central China. Our results showed that ENSO and ISM exerted substantial impact on annual precipitation while the impact of PDO and AMO was relatively limited. There were 24 and 15 out of 33 stations showing significant differences ( p < 0.1) in annual precipitation (from 1950 to 2013) for ENSO and ISM, respectively. The median precipitation across the basin during El Niño years was 21.49 % higher than that during La Niña years and 17.28 % higher during the positive phase of ISM years compared to the negative phase of the ISM years. The impacts of ENSO and ISM on precipitation were enhanced during a PDO cold phase but weakened in a PDO warm phase. The impact of ENSO was still enhanced by an AMO warm phase. The effects of climatic phenomena on precipitation showed a strong spatial difference in the Ordos Basin. The impact of ENSO was mostly evident around the edges of the basin while the impact of ISM decreases from south to north. The deserts (i.e., Hobq Desert and Mu Us Sandy Land) in the center of the basin were less affected by these large-scale climatic phenomena. An improved understanding of such relationships would be helpful in water resource planning and disaster management for the Ordos Basin. [ABSTRACT FROM AUTHOR]

Mountain observatories around the world are unique sites for monitoring and investigating variations, trends, forcings and feedbacks in the climate system, which are of utmost interest for understanding global climate change. From the small number of these research platforms, Sonnblick Observatory (Austrian Alps) stands out because of its long time series dating back to 1886 at an elevation of 3,100 m a.s.l. The paper describes the contribution of mountain observatories to climatology by the example of Sonnblick Observatory. The observatory's scientific evolution is summarised, starting from the original idea of upper air atmospheric measurements to its recent role as an atmospheric background station and interdisciplinary research site. [ABSTRACT FROM AUTHOR]

This paper evaluates the performance of eight state-of-art IPCC-AR4 coupled atmosphere-ocean general circulation models in their representation of regional characteristics of atmospheric water balance over South Asia. The results presented here are the regional climate change scenarios of atmospheric water balance components, precipitation, moisture convergence and evaporation ( P, C and E) up to the end of the twenty-second century based on IPCC AR4 modelling experiments conducted for (A1B) future greenhouse gas emission scenario. The AOGCMs, despite their relatively coarse resolution, have shown a reasonable skill in depicting the hydrological cycle over the South Asian region. However, considerable biases do exist with reference to the observed atmospheric water balance and also inter-model differences. The monsoon rainfall and atmospheric water balance changes under A1B scenario are discussed in detail. Spatial patterns of rainfall change projections indicate maximum increase over northwest India in most of the models, but changes in the atmospheric water balance are generally widespread over South Asia. While the scenarios presented in this study are indicative of the expected range of rainfall and water balance changes, it must be noted that the quantitative estimates still have large uncertainties associated with them. [ABSTRACT FROM AUTHOR]

The parameterization of physical processes is one of the critical elements to properly simulate the regional climate over eastern China. It is essential to conduct detailed analyses on the effect of physical parameterization schemes on regional climate simulation, to provide more reliable regional climate change information. In this paper, we evaluate the 25-year (1983-2007) summer monsoon climate characteristics of precipitation and surface air temperature by using the regional spectral model (RSM) with different physical schemes. The ensemble results using the reliability ensemble averaging (REA) method are also assessed. The result shows that the RSM model has the capacity to reproduce the spatial patterns, the variations, and the temporal tendency of surface air temperature and precipitation over eastern China. And it tends to predict better climatology characteristics over the Yangtze River basin and the South China. The impact of different physical schemes on RSM simulations is also investigated. Generally, the CLD3 cloud water prediction scheme tends to produce larger precipitation because of its overestimation of the low-level moisture. The systematic biases derived from the KF2 cumulus scheme are larger than those from the RAS scheme. The scale-selective bias correction (SSBC) method improves the simulation of the temporal and spatial characteristics of surface air temperature and precipitation and advances the circulation simulation capacity. The REA ensemble results show significant improvement in simulating temperature and precipitation distribution, which have much higher correlation coefficient and lower root mean square error. The REA result of selected experiments is better than that of nonselected experiments, indicating the necessity of choosing better ensemble samples for ensemble. [ABSTRACT FROM AUTHOR]

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern. [ABSTRACT FROM AUTHOR]

In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments. [ABSTRACT FROM AUTHOR]

In mountain regions, important differences in the time trends of climate series can be detected even within relatively small areas, leading to uncertainty when assessing climate change. The paper deals with a structured algorithm for high-resolution downscaling of climate characterisation in a region (precipitation and temperature), leading to a twofold application: increasing spatial resolution of past climate definition for the area and attaining high-resolution downscaling for climate projections. In the first stage, multi-variate analysis ('partial least squares' regression) was applied to a number of time series (10) in order to obtain climate averages for a larger number of sites. Predictions made with single-site values (such as seasonal means) can in some cases be improved by applying 'random perturbation' of the value and averaging single predictions in the ensemble. This analysis laid the foundation for implementing the same technique to the output of statistical downscaling of multi-model climate projections. Climate shift in the study area (Trentino), located in the north-eastern Italian Alps, was simulated for two 30-year time windows: 2021-2050 and 2071-2099. Progressive warming is predicted, being stronger in the summer, along with a mixed, seasonally differentiated trend for precipitation. [ABSTRACT FROM AUTHOR]

This paper analyses the temporal and spatial changes in the amount and variability of rainfall in Scotland. The sequential Mann-Kendall test reveals that total annual precipitation has increased across Scotland since the 1970s with increasing trends in variability beginning between the mid-1960s and the mid-1970s. Whilst temporally consistent increasing trends in precipitation totals prevail in the West, many weather stations in the East have experienced subsequent trend turning points in the following two decades, explaining the larger magnitude of the trends in western Scotland in recent decades. Trend analyses on six measures of rainfall variability indicate an increase in rainfall variability during the period 1961-2000, as measured by the intra-annual variance, the winter to summer precipitation ratio and the annual cumulative sum range, with decreasing trends observed in the number of dry days. Periodicities associated with the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation could explain the observed temporal variability of rainfall. [ABSTRACT FROM AUTHOR]

The paper aims to study the variability of spring barley and winter wheat yields, the most important crops in the Czech Republic, with respect to the variability of weather and climatic factors. Yields of both crops have been studied for 13 districts in Southern Moravia for the 1961-2007 period. From detrended series of spring barley and winter wheat yields, years with very low (lower than the mean minus a 2.5-multiple of the standard deviation) and extremely low (interval given by the mean minus a 1.5- and 2.5-multiple of the standard deviation) yields were selected. Years in which at least one of the districts had extremely low/very low yields were further analyzed. From 10 such years selected separately for spring barley and winter wheat, six of them agreed for both crops. Extreme years were studied using NUTS4-level yield data with respect to temperature, precipitation, the self-calibrated Palmer Drought Severity Index (scPDSI), snow cover, frost patterns, and the onset and duration of select phenophases. Extremely/very low barley yields in 1993, 2000, and 2007 were related to high April-June (AMJ) temperatures, low AMJ precipitation totals, and negative AMJ scPDSI (indicating drought) with an earlier onset of flowering and full ripeness and shorter intervals from tillering to flowering and from flowering to full ripeness compared to the entire 1961-2007 mean. As for extremely/very low winter wheat yields, in addition to the previously mentioned factors, winter patterns also played an important role, particularly the occurrence of severe frosts with a coinciding lack of snow cover and a long-lasting snow cover (in highlands), indicating that low yields are the result of not only one unfavorable factor but a combination of several of them. [ABSTRACT FROM AUTHOR]

Weather modification activities are performed predominantly by cloud seeding. Some operational projects have been performed for more than half a century and cover planetary scales. These activities lead to a large amount of deposited chemical materials (seeding agents) at the ground level during precipitation. These deposits depend on the amount of the seeding agent. In the future, increased amounts of seeding agent deposits could be a serious problem due to various negative effects on the human environment. Therefore, the main intent of this paper is to determine trends for the seeding agent amount over certain areas of Serbia. Four areas covered by the Hail Suppression Project in Serbia are considered: the target area in central Serbia and areas in western and central Serbia, which are well-known hailfall regions. The annual seeding agent amounts show a slow decreasing trend because fewer seedings were performed during the last decade of the last century, which was due to economic reasons. In contrast, the annual seeding agent amounts of the other analysed areas indicate an increasing trend induced by the transfer of rockets to these hailfall regions. The main difference among small areas is the mean agent amount and its maximum time position as a consequence of the high spatial and time variability of the hail. However, a sharp decreasing trend that is influenced by the implementation of new methodologies, seeding agents and delivery tools may also be a factor in the implementation of cloud seeding projects. The given method is not only strictly applicable locally and may be applied to any other cloud seeding scenario and seeding area. Dominantly increasing trends in the agent amount indicate that the importance of weather modifications in the future will be greater than ever and will have both positive and negative effects. [ABSTRACT FROM AUTHOR]

Precipitation variability imposes significant pressure in areas where agricultural practice is dominated by smallholder farmers who are dependent on subsistence farming. Advances in the understanding of this variability, in both time and space, have an important role to play in increasing the resilience of agricultural systems. The need is particularly pressing in regions of the world such as the African continent, which is already affected by multiple stresses including poverty and economic and political instability. In this paper, we explore the use of generalised linear models (GLMs) for this purpose, via a case study from north-east South Africa. A GLM is used to link the local rainfall variability to large-scale climate drivers identified from previous subcontinental-scale analyses, and the ability of the resulting model to simulate precipitation features that are relevant in agricultural applications is evaluated. We focus in particular on a set of growing season indices, proposed for the investigation of intraseasonal characteristics relevant for maize production in the region. Seven indices were computed from spatially averaged daily rainfall series from nine stations in the study area. As a first attempt to use GLMs for this type of application, the results are encouraging and suggest that the models are able to reproduce a range of agriculture-relevant indices. However, further research into spatial correlation structure is recommended to improve the multisite generation of the rainfall-derived characteristics. [ABSTRACT FROM AUTHOR]

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration ( PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1-16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by −10.2 to −2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed. [ABSTRACT FROM AUTHOR]

Extreme weather exerts a huge impact on human beings and it is of vital importance to study the regular pattern of meteorological and hydrological factors. In this paper, a selection of seven extreme indices is used to analyze the trend of precipitation extremes of 18 meteorological stations located in Zhejiang Province, east China using the Mann-Kendall test. Then the precipitation trends in the plum season (from May to July) and typhoon season (from August to October) are studied separately. The results show that the precipitation trend varies from east to west. There is a positive trend in the east and a negative one in the west. The largest part of Zhejiang Province shows a positive trend in heavy precipitation and the most significant upward trend is detected in Dinghai with 3.4 mm/year for precipitation on very wet days. Although the upward trend of extreme precipitation is not prevailing, the range of increase in specific areas is apparent, like Dinghai with 1.3 mm/year. Precipitation intensity exhibits an upward trend in most areas and a typical upward trend can be found in Dachendao, Tianmushan, and Yuhuan with 0.04, 0.02, and 0.05 mm/year respectively. Precipitation intensity in both plum and typhoon seasons has increased too, especially for the coastal stations. [ABSTRACT FROM AUTHOR]

study of the variability of the extreme rainfall events in Bangladesh during the time period 1958-2007 has been carried out in this paper. Quality-controlled homogeneous daily precipitation records of nine stations distributed over Bangladesh are used for the study. A total of 15 annual and seasonal indices of rainfall are examined. Variability of annual and seasonal rainfall trends is also assessed. The Mann-Kendall statistic and Sen's Slope model are used to reveal the trends and estimate the magnitude of change, respectively. A significant increase of annual and pre-monsoon rainfall in Bangladesh is observed. In general, an increasing trend in heavy precipitation days and decreasing trends in consecutive dry days are observed. Significant change in most of the extreme rainfall indices are observed in Northwest Bangladesh. [ABSTRACT FROM AUTHOR]

This paper discusses patterns of annual and monthly precipitation variability at seven weather stations in east central Europe (1851–2007). Precipitation patterns were compared to three simple regional indices of atmospheric circulation, i.e., western circulation, southern circulation and the cyclonicity (C) index and a relationship between precipitation and the North Atlantic Oscillation index was identified. Correlations of the monthly records and multiple regression, using a principal components’ analysis, helped determine the statistical significance of the dependence of precipitation on the circulation indices. The Mann–Kendall test revealed no trend to change in any of the precipitation series, but a certain spatial regularity could be discerned in the phase of the annual periodic component. A common feature of the variability in central European annual precipitation is the dry period identified in the 1980s and the first half of the 1990s. In the northern part of the region, above-average precipitation was noted from the 1960s through to the mid-1970s as a result of the frequent prevalence of depressions. South of the divide, the wettest period was recorded at the turn of 1930s/1940s. After a number of very wet years in the last decade of the twentieth century and the beginning of the twenty-first century, precipitation began to fall at all of the region’s weather stations. The C index is the strongest circulation-linked factor influencing precipitation in central Europe and it accounts for more than 40% of the variance in spatially averaged wintertime precipitation. [ABSTRACT FROM AUTHOR]

Snow is an important component of a climate system, and very sensitive to climate change, and it can be an indicator of checking and monitoring global change. This paper is concerned with identifying changes in the time series of snowfall in Qinghai, located in western China. We used the Mann-Kendall test to evaluate the annual and monthly trends in snowfall in Qinghai during the periods 1957/58–2006/07 based on data obtained from 25 stations. Significant positive and negative trends at the 90, 95, and 99 percent confidence levels were detected for numerous stations. In order to understand the regional pattern of snowfall in Qinghai, the detected trends are spatially interpolated using the inverse distance weighted interpolation method in a GIS environment. The results indicate that in January snowfall in the most area of Qinghai shows a significant upward trend, especially in the Delingha and Nomhon area in northern Qaidam Basin, as well as southeastern Qinghai, however, there is no significant downward trend area. The trend analysis indicates that annual snowfall has a significant upward trend in Delingha and Nomhon area in northern Qaidam Basin, and the downward trends occurred in the Qilian mountain area and Gonghe Basin. This is especially the case for highlighting the spatial structure of snowfall trends. The research results help in further understanding the regional pattern of snowfall in Qinghai and its response to global climatic warming. [ABSTRACT FROM AUTHOR]

Monthly precipitation data of 42 rain stations over the Pearl River basin for 1960–2005 were analyzed to classify anomalously wet and dry conditions by using the standardized precipitation index (SPI) and aridity index ( I) for the rainy season (April–September) and winter (December–February). Trends of the number of wet and dry months decided by SPI were detected with Mann-Kendall technique. Furthermore, we also investigated possible causes behind wet and dry variations by analyzing NCAR/NCEP reanalysis dataset. The results indicate that: (1) the Pearl River basin tends to be dryer in the rainy season and comes to be wetter in winter. However, different wetting and drying properties can be identified across the basin: west parts of the basin tend to be dryer; and southeast parts tend to be wetter; (2) the Pearl River basin is dominated by dry tendency in the rainy season and is further substantiated by aridity index ( I) variations; and (3) water vapor flux, moisture content changes in the rainy season and winter indicate different influences of moisture changes on wet and dry conditions across the Pearl River basin. Increasing moisture content gives rise to an increasing number of wet months in winter. However, no fixed relationships can be observed between moisture content changes and number of wet months in the rainy season, indicating that more than one factor can influence the dry or wet conditions of the study region. The results of this paper will be helpful for basin-scale water resource management under the changing climate. [ABSTRACT FROM AUTHOR]

The interannual to decadal variability of precipitation and daily maximum and daily minimum temperature (TMAX and TMIN) in southern Brazil for the 1913–2006 period is investigated using indices for these variables. Relations of these indices and the sea surface temperature (SST) variability in the eastern equatorial Pacific (Niño 3.4 index) and southwestern subtropical Atlantic (SSA index) are also investigated. Analyses are based on the Morlet wavelet transform. The interannual precipitation variability during the 1913–2006 period is mostly due to the high variances that occurred in specific sub-periods. The TMAX and TMIN indices also show significant interannual variability. The coherency and phase difference analyses of the precipitation index and the SST indices show higher coherency with the Niño 3.4 than with the SSA index. On the other hand, examining the coherencies and phase difference between the temperature indices and the SST indices, weaker coherencies with the Niño 3.4 index than with the SSA index are noted. These differences are discussed in the context of previous results. The new results here, with possible application for climate monitoring tasks, refer to the spectral differences between TMIN and TMAX. [ABSTRACT FROM AUTHOR]

Recent dry years (combined dry winter and summer months) within the UK (2005 and 2006) have enhanced concerns relating to long term water resources and future water provision in large conurbations. This paper examines the mechanisms responsible for precipitation variability for five different areas in Edinburgh (precipitation regions) using composite historic precipitation records for the period 1861–2005. Trend analysis and principal component analysis (PCA) were undertaken to examine precipitation variability over time and space. Annual correlation co-efficients were derived for relationships between precipitation areas, atmospheric–oceanographic variations and geographic parameters. Stepwise regression models were constructed to specify annual precipitation, through atmospheric variations, for each of the precipitation areas. Significant downward trends in precipitation ( p < 0.05) were noted in two out of the five precipitation areas, with one principal component representing precipitation variability over Edinburgh and the Pentland Hills. Precipitation variability is best explained by fluctuations in pressure, altitude and proximity to coast. Precipitation trends cannot be explained by changes in atmospheric circulation patterns. [ABSTRACT FROM AUTHOR]

A revised 25-point Shuman-Shapiro Spatial Filter (RSSSF) has been applied to six atmospheric circulation models and multi-model ensemble (MME) predictions, and its effect on the improvement of model forecast skill scores of the Asian summer precipitation anomaly is discussed in this paper. On the basis of 21-yr model ensemble predictions, the RSSSF can remove the unpredictable ‘noise’ with respect to the 2-grid wavelength in the model precipitation anomaly fields and maintain the large-scale counterpart, which is related to the response of the model to large-scale boundary forcing. Therefore, this could possibly enhance the forecast skill of the Asian summer rainfall anomaly in the models and the MME. The potential improvement of model forecasting skill is found in the Asian summer monsoon region, where the anomaly correlation coefficient (ACC) has been improved by 7–40%, corresponding to the decreased root mean square error (RMSE) in the model and the MME precipitation anomaly forecasts. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the role that horizontal resolution plays in the simulation of East Asia precipitation. Two sets of numerical experiments are performed using the Regional Climate Model (RegCM2) nested in one-way mode within the CSIRO global coupled atmosphere-ocean model. In the first set we use the actual RegCM2 topography at the selected model resolutions, which are 45, 60, 90, 120, 180, 240 and 360 km. In the second set of the experiments, the same coarse CSIRO model topography is used in all simulations using the different resolutions of the first set. The results demonstrate that the simulation of East Asian precipitation improves as the horizontal resolution is increased. Moreover, it is shown that the simulations using a higher resolution along with the coarse CSIRO topography perform better than the simulations using a coarser model resolution with corresponding model topography. This suggests that over East Asia adequate spatial resolution to resolve the physical and dynamical processes is more important than topography. Lastly, the results indicate that model resolutions of 60 km or higher are needed to accurately simulate the distribution of precipitation over China and East Asia. [ABSTRACT FROM AUTHOR]

The purposes of this paper are to evaluate the new version of the regional model, RegCM3, over South America for two test seasons, and to select a domain for use in an experimental nested prediction system, which incorporates RegCM3 and the European Community-Hamburg (ECHAM) general circulation model (GCM). To evaluate RegCM3, control experiments were completed with RegCM3 driven by both the NCEP/NCAR Reanalysis (NNRP) and ECHAM, using a small control domain (D-CTRL) and integration periods of January–March 1983 (El Niño) and January–March 1985 (La Niña). The new version of the regional model captures the primary circulation and rainfall differences between the two years over tropical and subtropical South America. Both the NNRP-driven and ECHAM-driven RegCM3 improve the simulation of the Atlantic intertropical convergence zone (ITCZ) compared to the GCM. However, there are some simulation errors. Irrespective of the driving fields, weak northeasterlies associated with reduced precipitation are observed over the Amazon. The simulation of the South Atlantic convergence zone is poor due to errors in the boundary condition forcing which appear to be amplified by the regional model. To select a domain for use in an experimental prediction system, sensitivity tests were performed for three domains, each of which includes important regional features and processes of the climate system. The domain sensitivity experiments were designed to determine how domain size and the location of the GCM boundary forcing affect the regional circulation, moisture transport, and rainfall in two years with different large scale conditions. First, the control domain was extended southward to include the exit region of the Andes low level jet (D-LLJ), then eastward to include the South Atlantic subtropical high (D-ATL), and finally westward to include the subsidence region of the South Pacific subtropical high and to permit the regional model more freedom to respond to the increased resolution of the Andes Mountains (D-PAC). In order to quantify differences between the domain experiments, measures of bias, root mean square error, and the spatial correlation pattern were calculated between the model results and the observed data for the seasonal average fields. The results show the GCM driving fields have remarkable control over the RegCM3 simulations. Although no single domain clearly outperforms the others in both seasons, the control domain, D-CTRL, compares most favorably with observations. Over the ITCZ region, the simulations were improved by including a large portion of the South Atlantic subtropical high (D-ATL). The methodology presented here provides a quantitative basis for evaluating domain choice in future studies. [ABSTRACT FROM AUTHOR]

The aim of the paper lies in the identification of possible significant linear trends at monthly, seasonal and annual timescales in the Mediterranean during the second half of the 20th century. Monthly and daily records of 63 stations have been used to elaborate several precipitation indices: sum of daily precipitation (SDP) for rainfall >0.1 mm, >10 mm and >95th percentile, of number of rainy days (RD) >0.1 mm and >10 mm and of mean daily precipitation (MDP) >0.1 mm and >10 mm. For each index the stations have been gathered together by Rotated Principal Component Analyses to determine 8 sub-areas which can be considered as identical for all the timescales at the spatial scale of the research. Trends have been estimated from the scores of each eigenvector retained in all RPCAs. They are mainly non existant or non significant decreasing, even if a few monthly trends appear to be significantly diminishing, primarily during winter months, March in the Atlantic region, October in the Mediterranean Spain, December in the Lions and Genoa Gulfs, January, winter and the year in Greece, winter and the year in Italy and winter in the Near East and increasing in April in the two gulfs. Correlation coefficients between SDP>0.1 mm and other indices have been computed: the significant trends seem mainly related to RD>10 mm, which represents a high percentage of the total rainfall amount. Greece is remarkable: SDP>0.1 mm and >10 mm decrease significantly during January, winter, the rainy season and the entire year whereas SDP>95th percentile increases significantly, in accordance with the climatic change scenarios for the end of this century as does the decreasing of the total monthly and seasonal rainfall. [ABSTRACT FROM AUTHOR]

We present an analysis of a present-day climate simulation (1990-2009) for the Southern Africa region with the RegCM4 regional climate model (RCM, dx = 25 km ~0.22°) driven by the Community Atmospheric Model version 4 (CAM4) global climate model (GCM, dx = 1°). We assess the capability of the models to simulate the observed climate of the region with emphasis on precipitation, 2-m mean, minimum, and maximum temperature and large-scale circulation. The analysis focuses on seasonal climatologies, annual cycles, interannual variability, and extreme events. In addition to evaluating the performance of the models, we also attempt to assess the added value of the regional model compared to the driving one. With a few exceptions, we find that the models reproduce reasonably well the mean spatial patterns of 2-m temperature and precipitation, along with the associated seasonal cycle and interannual variability over selected sub-regions. Extreme indices of temperature and precipitation are also reasonably well reproduced. However, the RegCM4 substantially improves the simulation of daily precipitation frequency and duration of dry and wet events compared to CAM4 due to its higher resolution. The global and regional models exhibit quite different patterns of bias, an indication of the importance of internal variability and process representation for the simulation of surface climate. Given the good performance shown by the nested CAM4-RegCM4 system, we plan to use these models to generate an ensemble of projections for use in impact assessment studies for the region. [ABSTRACT FROM AUTHOR]

Changes in precipitation exert an enormous impact on human life, and it is of vital importance to study regular patterns of meteorological and hydrological events. In order to explore the changing spatial and temporal patterns of precipitation amounts, precipitation extremes and precipitation concentration in Jiangxi province in southeast China between 1960 and 2008, several precipitation indices series were analysed using the Mann-Kendall test in this study. Our results indicate remarkable differences among the stations with negative and positive precipitation trends at the annual, seasonal and monthly scales, significant increasing trends are mainly found during January, August, winter and summer, while significant decreasing trends mostly are observed during October and autumn. For precipitation extremes, most precipitation indices suggest that both the intensity and the days of extreme precipitation are increasing; the mean precipitation amount, especially, on a wet day shows a significant positive trend. When it comes to precipitation concentration, the monthly rainfall heterogeneity shows an insignificant downward trend, while the contribution of the days with greatest rainfall displays an insignificant upward trend. Furthermore, the long-range persistence is detected for changing process of precipitation amount, extreme precipitation and precipitation concentration using the Rescaled Range Analysis. [ABSTRACT FROM AUTHOR]

The influence of increased horizontal resolution on regional climate models simulations of 1961-1990 period was investigated with a focus on precipitation. The main attention was paid to the annual cycle of precipitation described by a special characteristic, precipitation half-time. Two models (RegCM3 and ALADIN-CLIMATE/CZ), both of them in two horizontal resolutions (25 and 10 km), were used. An evaluation of model simulations with 25 km resolution on the European domain is presented as well as a more detailed evaluation of both 25 and 10 km versions on the area of the Czech Republic. Generally, the effects of increased horizontal resolution vary with climate model and evaluated characteristic. For the precipitation amount and the dependence of precipitation amount on altitude, the increase in horizontal resolution decreases the accuracy of results in both models. For the simulation of annual precipitation cycle and the precipitation half-time, RegCM3 results improved with the increased horizontal resolution, whereas ALADIN-CLIMATE/CZ results worsened. [ABSTRACT FROM AUTHOR]

In addition to air temperature at 2 m above ground, the following water balance components are considered: precipitation amount, potential and real evapotranspiration, surface runoff, recharge of water into the soil, loss of water from the soil, soil moisture content, and measured river discharge. Monthly air temperature and values of all water balance components (some of calculated using the Palmer method) have been considered for 24 weather stations across Croatia for the period 1951–2000, and for the Zagreb-Grič station for a much longer period, 1862–2000. The Sava River discharge for two hydrological stations (Zagreb and Županja) for the period 1931–2000 has also been used. Twenty-five year moving averages have been calculated from annual mean values and, – for air temperature only, a principal component analysis has been performed. We have found a long-term positive trend in air temperature, and potential and real evapotranspiration; and a negative trend in runoff (discharge) over almost the whole of Croatia, while the moving-average precipitation amounts show cyclical variation. No obvious trend for the recharge of water into the soil and its losses from the soil have been found, however, a negative trend in soil moisture content has been observed. The positive trends in air temperature and potential (real) evapotranspiration and the negative trends in soil moisture content and runoff (discharge) are consistent (to some degree) with recent global climate warming. This fact strengthens the importance of this study. [ABSTRACT FROM AUTHOR]

The spatial and temporal variability of winter precipitation and its links to the large-scale atmospheric circulation patterns in Romania are examined. The data set is composed of observed rainfall at 30 meteorological stations during the 1961–1996 period. The large-scale field is represented by the observed geopotential height at 500 hPa (Z500) over the same period, covering the latitudinal belt between 20° N–90° N (resolution 2.5°×2.5°). The Standard Normal Homogeneity Test (SNHT) is applied to detect inhomogeneities in the data, and the Mann-Kendall and Pettitt non-parametric tests are used in order to identify trends and change points in the winter precipitation time series. The empirical orthogonal functions (EOF) technique is used for data reduction in order to highlight the basic patterns of rainfall variability in Romania. The covariance map between precipitation EOF time series (PCs) and the Z500 field, as well as the correlation coefficients between the PCs and circulation indices are calculated in order to identify the influence of large-scale circulation patterns on winter precipitation in Romania. A significant decreasing trend is identified in winter precipitation with a downward shift in winter 1969/1970, most significant from a statistical point of view in the extra-Carpathian region. This change seems to be real since the SNHT test does not reveal any inhomogeneity during the period tested. Significant relationships are found between winter precipitation variability in Romania and the large-scale circulation pattern, such as the North Atlantic Oscillation and the blocking phenomenon in the Atlantic-European sector. The positive phase of the NAO and the reduction in blocking activity could be one of the causes of the decrease in winter precipitation in Romania. [ABSTRACT FROM AUTHOR]

Summary¶The variability of the winter mean precipitation observed at 40 rainfall stations in Emilia-Romagna (a region in northern Italy) from 1960 to 1995 is examined. The results are compared with those obtained for the whole of Italy using records from 32 stations. Temporal variability of the time series is investigated by means of Mann-Kendall and Pettitt tests, in order to estimate the presence of trends and “change points”. Before analysis the original precipitation data set have been tested to detect the inhomogeneity points, using the Standard Normal Homogeneity Test (SNHT). Almost all stations situated in Emilia Romagna exhibit a significant decreasing trend in winter precipitation during the 1960–1995 period. The same characteristics are revealed, more significant in the northern and central part of the region, when the stations for all Italy are analysed. A significant downward shift in the winter precipitation is detected through the Pettitt test in Emilia Romagna, around 1980 at some stations, while the rest of the stations reveal the shift point occurrence around 1985. A significant downward shift in the winter precipitation is detected around 1985, when analysing the time series for all Italy. Spatial variability of winter precipitation is studied using the Empirical Orthogonal Function. The first pattern indicates that a common large-scale process could be responsible for the winter precipitation variability. The second EOF pattern shows an opposite sign of climate variability, which highlights the influence of relief on the precipitation regime. The time series associated with the first precipitation pattern (PC1) at both scales emphasises a significant decreasing trend and a downward shift point around 1985. The internal structure analysis of the North Atlantic Oscillation (NAO) index during the 1960–1995 period reveals a significant increasing trend and an upward shift around 1980. Strong correlation is also detected between PC1 (Emilia Romagna and at the scale of all Italy) and the NAO index. Thus, the changes detected in the winter precipitation around 1985 could be due to an intensification of the positive phase of the [NAO], especially after 1980. [ABSTRACT FROM AUTHOR]

Changes in temperature and precipitation can have direct effects on a country's economic and sustainable development. This study presents the historical trends in daily extreme temperature and precipitation indices for Barbados, a Caribbean island, for the period 1969–2017. Linear trends were determined on monthly, seasonal, and annual indices derived from daily rainfall, and daily maximum and minimum temperatures collected at Husbands using the Mann-Kendall trend test and the Sen slope estimator. Annual precipitation total, the simple daily rainfall intensity index (SDII), and the total precipitation when daily rainfall was greater than the 95th percentile (R95P) changed significantly by 3.9% per decade, 0.38 mm day−1 per decade, and 2.9% per decade, respectively. Annual trends in mean maximum (TXmean) and mean minimum temperatures (TNmean), 0.06 °C decade−1 and 0.34 °C decade−1, respectively, mask stronger monthly warming trends: TXmean for September and October both warmed at a rate of approximately 0.17 °C decade−1 while TNmean for April warmed at 0.40 °C decade−1. In addition, warming manifests in the frequency of warm nights and cool days at rates of 4.23% per decade and − 2.34% per decade, respectively. Of the extreme temperature indices, the percentage of warm nights (TN90P), cool nights (TN10P), the maximum of the daily minimum temperature (TNX), and the minimum of the daily minimum temperature (TNn) show trends in their monthly indices. These trends indicate warming at Husbands, Barbados, to a greater degree in increasing nighttime temperatures than daytime temperatures. [ABSTRACT FROM AUTHOR]

The present study analyzed precipitation and temperature trends of 45 years (1971–2015) over two protected areas (Kanha Tiger Reserve representing Sal forest and Satpura Tiger Reserve representing Teak forest) in Central India. The specific trends (decadal, annual, and seasonal) are calculated from various available data sources (IMD, REMO, and Station) which are at different horizontal resolutions. The non-parametric Mann–Kendall test statistic and Sen's estimate methods are used to detect the presence and quantum of a trend. The results indicate significant decrease in post-monsoon and winter precipitation and an increasing significant temperature trend (Tmean, Tmax, Tmin) at seasonal, annual, and decadal scale, with a maximum increase during post-monsoon. Also, the last decade (2001–2010) was warmer than the previous three decades. The presence of break points and structural changes in climatic variables are analyzed using OLS-CUSUM and MOSUM tests available in "strucchange" package in R. A structural change in precipitation was observed only in REMO dataset over Satpura Tiger Reserve, whereas significant structural change in temperature was observed in REMO dataset over both the regions. These findings are useful for assessing precipitation and temperature trends in protected areas. In particular, it can aid in understanding the impact of climate change on forest/species. On comparative analysis among different data sources at varying resolutions, the study recommends the use of finer resolution datasets for regional/micro-scale studies for formulating and planning effective adaptation strategies. [ABSTRACT FROM AUTHOR]

The vast areal extent of Texas, USA, observes acute variations in extreme precipitation, which result in devastating floods in various regions. Hydrometeorological literature suggests that these precipitation extremes are driven by the changes in global-scale climatic cycles. This study analyzed potential statistical links between Atlantic- and Pacific Ocean-based climatic cycles and annual precipitation extremes in Köppen–Geiger climate regions of Texas. Sensitivity analysis was done for annual precipitation extremes and differing phases of the most correlated climatic cycles. The study also analyzed the spatial variation of climatic indices and determined the projected increments in annual precipitation extremes as per the highest historically recorded increments or decrements in the most correlated climatic cycles in consecutive months. Weather stations with lower elevation and higher average precipitation are likely to observe higher extreme precipitation events in the warmer AMO state. Sensitivity analysis showed that a 20% decrement in empirical probabilities of projected precipitation extreme events corresponded to a decline of 35% in the same for humid subtropical climate region. The humid subtropical climate region is highly prone to devastating floods after heavy precipitation events. Results of the study will help prepare regional water boards for extreme precipitation events with reliable long-term forecasts of climatic cycles. [ABSTRACT FROM AUTHOR]

Global warming has substantial impacts on the hydrologic cycle and precipitation characteristics. This study aimed to explore variability in the form of precipitation by analysis of trends in the snowfall-day (SD)/total precipitation-day (PD) ratio across Iran. To this end, the PD and SD records were acquired from 33 synoptic stations during 1965–2014. The Mann-Kendall (MK) test was the main method used for trend detection. Analyzing data exposed that the annual SD/PD ratio was less than 25% in a plethora of the stations. The MK test findings indicated downward tendencies in the SD/PD ratio over most regions of the country; although in many cases, the observed trends were not statistically significant. The changes in the annual SD/PD ratio were estimated down to − 2% per decade over ~ 70% of Iran's total area. Further studies are required to ascertain the linkages between the large-scale climate oscillations and the form of precipitation across this region. Also, using remotely sensed data (e.g., obtained from the MODIS) and fine-resolution gridded data (e.g., global and regional reanalysis data) in future research could improve the findings of such studies and dwindle the uncertainties caused by the scanty site-based observations. [ABSTRACT FROM AUTHOR]

Stochastic weather simulation models are used to generate data for hydrologic and agricultural applications. In recent years, stochastic downscaling has been employed in downscaling scenarios-based GCM or RCM output data, especially highly unpredictable hydrometeorological variables (e.g., precipitation). However, downscaling produces a number of traces to apply. In practice, multiple scenarios are difficult to handle. To overcome this difficulty, trace selection methods (TSMs) were proposed and tested in the current study, based on the mean and standard deviation (MS), empirical cumulative distribution function (Ecdf), and density estimate (Dens) methods. Simulation results indicated that key statistics were well preserved by the selected trace with the MS and Ecdf methods, while the Dens method did not show a reasonable performance in selecting a representative trace. The MS and Ecdf methods preserved well the mean and standard deviation of the average of these statistics from all simulated series and the Ecdf method was superior in preserving extrema, such as maximum and minimum. In a real application involving over 62 weather stations from South Korea, results showed that the MS and Ecdf methods were feasible ways to select the best trace to represent all temporally downscaled hourly precipitation from daily data. Overall, the MS and Ecdf can be both good alternatives as a trace selection method (TSM). The MS method can be used in general cases and the Ecdf can be employed in extreme analysis, such as estimating design rainfall with selected traces. [ABSTRACT FROM AUTHOR]

Gridded climatic datasets with fine spatial resolution can potentially be used to depict the climatic characteristics across the complex topography of China. In this study, we collected records of monthly temperature at 1153 stations and precipitation at 1202 stations in China and neighboring countries to construct a monthly climate dataset in China with a 0.025° resolution (~ 2.5 km). The dataset, named LZU0025, was designed by Lanzhou University and used a partial thin plate smoothing method embedded in the ANUSPLIN software. The accuracy of LZU0025 was evaluated based on three aspects: (1) Diagnostic statistics from the surface fitting model during 1951–2011. The results indicate a low mean square root of generalized cross validation (RTGCV) for the monthly air temperature surface (1.06 °C) and monthly precipitation surface (1.97 mm1/2). The method used variable square root transformation for the spline surface fitting to reduce positive skewness in the measured precipitation values and no variable transformation in air temperature case. This indicates that the surface fitting models are accurate. (2) Error statistics of comparisons between interpolated monthly LZU0025 with the withholding of climatic data from 265 stations during 1951–2011. The results show that the predicted values closely tracked the real true values with values of mean absolute error (MAE) of 0.59 °C and 70.5 mm and standard deviation of the mean error (STD) of 1.27 °C and 122.6 mm. In addition, the monthly STDs exhibited a consistent pattern of variation with RTGCV. (3) Comparison with other datasets. This was done in two ways. The first was via comparison of standard deviation, mean, and time trend derived from all datasets to a reference dataset released by the China Meteorological Administration (CMA), using Taylor diagrams. The second was to compare LZU0025 with the station dataset in the Tibetan Plateau. Taylor diagrams show that the standard deviation derived from LZU had a higher correlation with that produced by the CMA (R = 0.76 for air temperature, and R = 0.96 for precipitation) compared to those from other datasets. The standard deviation for the index derived from LZU was more close to that induced from CMA, and the centered normalized root-mean-square difference for this index derived from LZU and CMA was lower. A similar superior performance of LZU was found in the comparison of mean and time trend derived from LZU and those from other datasets. LZU0025 had high correlation with the Coordinated Energy and Water Cycle Observation Project (CEOP)—Asian Monsoon Project (CAMP) Tibet surface meteorology station dataset for air temperature, despite a non-significant correlation for precipitation at a few stations. Based on this comprehensive analysis, we conclude that LZU0025 is a reliable dataset. LZU0025, which has a fine resolution, can be used to identify a greater number of climate types, such as tundra and subpolar continental, along the Himalayan Mountain. We anticipate that LZU0025 can be used for the monitoring of regional climate change and precision agriculture modulation under global climate change. [ABSTRACT FROM AUTHOR]

Shifts in precipitation regimes have been given increased attention along with climate trends in the arid and semiarid Mongolian Plateau (MP), because precipitation is the dominant factor that controls vegetation growth and land-use practices in the region. However, the temporal variability and spatial heterogeneity of decadal trends in summer precipitation fraction have not been well understood. In this study, the temporal variability and spatial heterogeneity of annual and summer precipitation change were investigated with the major focus on the summer precipitation fraction across the entire MP, using monthly precipitation data from 141 meteorological stations and the Tropical Rainfall Measuring Mission (TRMM) precipitation data. The Mann–Kendall trend test, Sen's regression, and Spatial Analyst methods were used for time series analysis. Results show that the regional summer precipitation fraction declined significantly at a rate of − 1.0%/decade (p < 0.05) during 1961–2010, which was supported by TRMM satellite data with a rate of − 2.86%/decade over 1998–2016. Interestingly, rates of decrease in the summer precipitation fraction varied by ecoregion. Spatially, trend in summer precipitation fraction was very heterogeneous, with significant decreasing trends in the eastern typical steppe and southeastern agro-pastoral ecotone, but increasing trends in the southwestern desert and Gobi desert region. In conclusion, the summer precipitation fraction declined because of the asymmetric decreasing or increasing rates in summer and non-summer precipitation during both 1961–2010 and 1998–2010. This implies a major shift of precipitation regime in the region. This is likely driven by decadal changes of the East Asia monsoon system. [ABSTRACT FROM AUTHOR]

The existence of significant trend and change point in the aridity index (AI), precipitation, and reference evapotranspiration (ET0) was evaluated using the Mann-Kendall and Pettitt tests, respectively, over 22 semi-arid, humid, and sub-humid sites of Iran during 1966–2012. Detrending method was also employed to quantify each factor's contribution to the AI and ET0 trends. The ET0 and AI sensitivity to their input perturbations was analyzed using a derivative sensitivity coefficient. The results indicated a downward trend in precipitation and AI and an upward trend in ET0 on both seasonal and annual scales for majority of sites. Compared with AI and precipitation, more significant change points were detected, mainly during the 1990s, in the ET0 series. Except for wintertime, solar radiation (SR) was found as the most sensitive factor on the AI and ET0 dynamics in the semi-arid regions. However, with an exception for summertime, AI and ET0 exhibited greater sensitivity to the RH changes followed by the SR changes in the humid/sub-humid areas. For more than 70% of semi-arid stations and Gorgan (a sub-humid location), wind speed (U) was the most important variable contributing to seasonal and annual ET0 trends. However, the ET0 trend was primarily caused by the mean temperature (Tmean) changes for the humid environments. Further, the precipitation changes made the largest contribution to seasonal and annual AI trends for most cases followed by the U changes. An integrated water resource management is required to be implemented to reduce negative impacts of decreased AI and ET0 increment over Iran. [ABSTRACT FROM AUTHOR]

Future changes projected in surface temperature and precipitation behave differently in different regions or watersheds and vary greatly in space and time, even within the same region under climate change. This study aims to detect and compare differences in the climatological characteristics in response to climate change in arid and humid areas. Based on the CN05.1 reanalysis gridded dataset (high-resolution climate model validation launched by China Meteorological Administration) and output from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), the projected responses of temperature and precipitation to climate change under three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) in the arid basin (the Tarim River Basin, the TRB) and the humid basin (the Yangtze River Basin, the YRB) were characterized. Our results show that the swings of annual temperature and precipitation will extend with the rising emission scenarios in the future, while those are more vulnerable in the TRB. The topography-related changes of temperature and precipitation were further evaluated to explore the uncertainty. The elevation-dependent warming (EDW) may be weakened but still hold in the future at the watershed scale. Change in precipitation will decrease with increase in elevation in the TRB, while it will increase in the YRB. Compared with the general growth in seasonal temperature, precipitation shows more striking changes during spring and winter under climate change. Further researches to improve our understanding of the projected changes in temperature and precipitation are needed for better prediction of extreme weather conditions, such as drought and floods. [ABSTRACT FROM AUTHOR]

The Hengduan Mountains and Tibetan Plateau possess unique topographical characteristics that serve as an effective blocking of the movement of the westerly wind in the middle and lower troposphere towards East China. This study examines results from a regional climate model (REMO) at the resolutions of 25 and 50 km for the period 1980–2012. The model is run using lateral boundary conditions from ERA-Interim (European Centre for Medium-Range Weather Forecasts interim reanalysis). There are only a few differences between 25 and 50 km in land surface/vegetation characteristics, but the major differences in this region are due to the orography. Results show that the high-resolution simulation performance is poor in winter, when southwesterly wind prevails, whereas it performs well in summer, when the westerly wind is substantially weakened in southern China. In comparison to the ERA-Interim wind field, the high-resolution simulation overestimates the air flow over the Hengduan Mountains near the ground surface, which influences the transport of atmospheric water vapor in the downstream region, i.e., over southern China. Specifically, with the help of the overestimated southwesterly wind, the amount of atmospheric water vapor transported increases considerably perennially by up to 20% in southern China, while it decreases remarkably by more than 5% throughout the year in a large area of Central and North China. These features lead to excessive precipitation and underestimated cloud cover in southern China, which probably causes the overestimated 2-m temperature in southern China. Our study emphasizes that, in such high-resolution-model studies for East Asia, special attention should be paid to the near-surface winds over the Hengduan Mountains. [ABSTRACT FROM AUTHOR]