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Any hydro-meteorology variable includes different components, in general, such as periodicity, trend, possibly jump, and uncertain stochastic parts. Among these, the trend analysis gained importance in the last three decades due to global warming and climate change effects. The literature is full of monotonic trend applications by taking into consideration trend analysis methodologies such as Mann–Kendall trend identification, Sen trend slope calculation, and Şen innovative trend analysis (ITA). It is more important in practical studies to deal with less than one-year durations to assess the possible trend pieces for better practical uses such as agricultural productivity purposes. In this paper, a new concept is applied, known as the innovative polygon trend analysis (IPTA), to assess the trend component transitions between two successive months. The application of the methodology is presented for the coastal region of northeast Algerian precipitation records. The emanated results from this study provided information that El Taref station has the most unstable precipitation behavior among all the meteorology stations in the study area, moving from a month to another rather very unsystematically; whereas other meteorology stations have systematic movement from a month to the subsequent one. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to elucidate a potential use of the large samples of seasonal means that hindcasts provide for investigating different aspects of climate variability. This use of hindcasts complements their traditional uses in bias correction, real-time forecast calibration, and prediction skill assessment. For seasonal hindcast data from NCEP CFSv2 we show that a sample size 5208 for each target season is achievable. To demonstrate the utility of the proposed concept, we use this large sample dataset to illustrate how it could be used in documenting spatial variability in various moments of seasonal mean precipitation PDF over the US, and further, quantify nuances in the variations in precipitation PDF at different geographical locations with the amplitude of ENSO SSTs. It is our hope that analysis presented in this paper will accelerate utilization of seasonal hindcast datasets in furthering our understanding of different aspects of climate variability. With the advantage of the large sample size, we demonstrated that the precipitation PDF at the each grid of the CONUS can be represented by gamma distribution for a more concise and effective way to summarize precipitation variability. The availability of the large sample dataset also allowed us to analyze the statistical characteristic of the precipitation responses to the different amplitudes of ENSO SSTs. The results show that for strong warm events, enhancement in precipitation has larger amplitude than decrease in precipitation for cold events in the regions of Southern California and southeastern US. The variation of the precipitation signal over the other sub-regions including the southwestern US, mid-northwest, and mid-east shows more linear relationship with the ENSO SSTs. In response to anomalous ENSO SSTs, although the PDF of December-January-February seasonal mean precipitation anomaly is shifted from its climatological PDF, there is still a large overlap between precipitation PDFs for ENSO and its climatological counterpart. This uncertainty in seasonal mean outcomes of precipitation, therefore, limits the seasonal prediction skill. [ABSTRACT FROM AUTHOR]

How soil moisture affects precipitation is an important question-with far reaching consequences, from weather prediction to centennial climate change-, albeit a poorly understood one. In this paper, an analysis of soil moisture-precipitation interactions over France based on observations is presented. A first objective of this paper is to investigate how large scale circulation modulates soil moisture-precipitation interactions, thanks to a weather regime approach. A second objective is to study the influence of soil moisture not only on precipitation but also on the difference between precipitation and evapotranspiration. Indeed, to have a total positive soil moisture-precipitation feedback, the potential decrease in precipitation associated with drier soils should be larger than the decrease in evapotranspiration that drier soils may also cause. A potential limited impact of soil moisture on precipitation is found for some weather regimes, but its sign depends on large scale circulation. Indeed, antecedent dry soil conditions tend to lead to smaller precipitation for the negative phase of the North Atlantic Oscillation (NAO) regime but to larger precipitation for the Atlantic Low regime. This differential response of precipitation to soil moisture anomalies depending on large scale circulation is traced back to different responses of atmospheric stability. For all circulation regimes, dry soils tend to increase the lifted condensation level, which is unfavorable to precipitation. But for the negative phase of the NAO, low soil moisture tends to lead to an increase of atmospheric stability while it tends to lead to a decrease of stability for Atlantic Low. Even if the impact of soil moisture anomalies varies depending on large scale circulation (it is larger for Atlantic low and the positive phase of the NAO), dry soils always lead to a decrease in evapotranspiration. As the absolute effect of antecedent soil moisture on evapotranspiration is always much larger than its effects on precipitation, for all circulation regimes dry soil anomalies subsequently lead to positive precipitation minus evapotranspiration anomalies i.e. the total soil moisture feedback is found to be negative. This negative feedback is stronger for the Atlantic Low and the positive phase of the NAO regimes. [ABSTRACT FROM AUTHOR]

This paper presents the study of the impact of precipitation changes on alluvial aquifer systems in Xanthi Prefecture plain region, Greece. Two study areas were investigated, taking into account several hydrological and hydrogeological data for a time period of 23 years (1989-2011) measured and elaborated in the framework of the hydrogeological conceptual model assessment of the aquifer systems. It is considered that the evaluation and presentation of this kind of material is informative and quite necessary enforcing the reliability of the approach of the research presented in this paper. Graphs are designed showing precipitation monthly values and groundwater level fluctuation values recorded by three groundwater level loggers installed at the study areas. The conjunctive and synthetic assessment of the impact of precipitation on groundwater level fluctuation is carried out at three levels regarding precipitation moving average values fluctuation classified into thee time periods, high groundwater level values distinguished in three time periods, and correlation between precipitation moving average values and groundwater level values with temporal discrimination within specific hydrological years. It is concluded that the influence of precipitation on groundwater level fluctuation in the study area can almost responsibly be indicated based on original and reliable data contributing to better understanding and managing the functioning of the investigated aquifer system under several climate changes. [ABSTRACT FROM AUTHOR]

The Andes Cordillera plays a role in driving moisture and heat from tropical onto subtropical South America. It forces the development of a lee-side trough that covers most of western Argentina and a low-level jet that maximizes over Paraguay, eastern Bolivia and northern Argentina and is tightly linked to precipitation variability over much of central and southeastern South America. Its steep slopes and the large zonal gradients in topography between the Equator and 40°S are misrepresented in climate simulations using Global Climate Models (GCM) with resolutions coarser than about 100 km, since they naturally have a poor representation of the Andes and related circulation features. This paper analyses the impact of varying artificially the altitude of the Andes Cordillera in a GCM as well as increasing the horizontal resolution to study how these variations determine moisture fluxes and precipitation over selected regions of South America. Results show that the height of the Andes is crucial in shaping moisture fluxes pathways onto subtropical South America all year long. In particular, the low-level jet is only simulated when the Andes heights are doubled. At the same time, the relationship between the Andes shape and the location of the Bolivian High in summer is also discussed. In terms of precipitation, the lowest bias in the simulations is achieved when the horizontal resolution is increased, while in particular near the Andes foothills the simulated annual rainfall is largely determined by the Mountains shape. [ABSTRACT FROM AUTHOR]

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

On a hemispheric scale, it is now well established that stratospheric ozone depletion has been the principal driver of externally forced atmospheric circulation changes south of the Equator in the last decades of the 20th Century. The impact of ozone depletion has been felt over the entire hemisphere, as reflected in the poleward drift of the midlatitude jet, the southward expansion of the summertime Hadley cell and accompanying precipitation trends deep into the subtropics. On a regional scale, however, surface impacts directly attributable to ozone depletion have yet to be identified. In this paper we focus on South Eastern South America (SESA), a region that has exhibited one of the largest wetting trends during the 20th Century. We study the impact of ozone depletion on SESA precipitation using output from 6 different climate models, spanning a wide range of complexity. In all cases we contrast pairs of model integrations with and without ozone depletion, but with all other forcings identically specified. This allows for unambiguous attribution of the computed precipitation trends. All 6 climate models consistently reveal that stratospheric ozone depletion results in a significant wetting of SESA over the period 1960-1999. Taken as a whole, these model results strongly suggest that the impact of ozone depletion on SESA precipitation has been as large as, and quite possibly larger than, the one caused by increasing greenhouse gases over the same period. [ABSTRACT FROM AUTHOR]

This paper examines an asymmetric spatiotemporal connection and climatic impact between the winter atmospheric blocking activity in the Euro-Atlantic sector and the life cycle of the North Atlantic Oscillation (NAO) during the period 1950-2012. Results show that, for positive NAO (NAO+) events, the instantaneous blocking (IB) frequency exhibits an enhancement along the southwest-northeast (SW-NE) direction from the eastern Atlantic to northeastern Europe (SW-NE pattern, hereafter), which is particularly evident during the NAO+ decaying stage. By contrast, for negative NAO (NAO−) events, the IB frequency exhibits a spatially asymmetric southeast-northwest (SE-NW) distribution from central Europe to the North Atlantic and Greenland (SE-NW pattern, hereafter). Moreover, for NAO− (NAO+) events, the most marked decrease (increase) in the surface air temperature (SAT) in winter over northern Europe is in the decaying stage. For NAO+ events, the dominant positive temperature and precipitation anomalies exhibit the SW-NE-oriented distribution from western to northeastern Europe, which is parallel to the NAO+-related blocking frequency distribution. For NAO- events, the dominant negative temperature anomaly is in northern and central Europe, whereas the dominant positive precipitation anomaly is distributed over southern Europe along the SW-NE direction. In addition, the downward infrared radiation controlled by the NAO’s circulation plays a crucial role in the SAT anomaly distribution. It is further shown that the NAO’s phase can act as an asymmetric impact on the European climate through producing this asymmetric spatiotemporal connection with the Euro-Atlantic IB frequency. [ABSTRACT FROM AUTHOR]

Global Climate Models (GCMs) have been extensively used in many climate change impact studies. However, the coarser resolution of these GCM outputs is not adequate to assess the potential effects of climate change on local scale. Downscaling techniques have thus been proposed to resolve this problem either by dynamical or statistical approaches. The statistical downscaling (SD) methods are widely privileged because of their simplicity of implementation and use. However, many of them ignore the observed spatial dependence between different locations, which significantly affects the impact study results. An improved multi-site SD approach is thus presented in this paper to downscaling of daily precipitation at many sites concurrently. This approach is based on a combination of multiple regression models for rainfall occurrences and amounts and the Singular Value Decomposition technique, which models the stochastic components of these regression models to preserve accurately the space-time statistical properties of the daily precipitation. Furthermore, this method was able to describe adequately the intermittency property of the precipitation processes. The proposed approach has been assessed using 10 rain gauges located in the southwest region of Quebec and southeast region of Ontario in Canada, and climate predictors from the National Centers for Environmental Prediction/National Centre for Atmospheric Research re-analysis data set. The results have indicated the ability of the proposed approach to reproduce accurately multiple observed statistical properties of the precipitation occurrences and amounts, the at-site temporal persistence, the spatial dependence between sites and the temporal variability and spatial intermittency of the precipitation processes. [ABSTRACT FROM AUTHOR]

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971-2000) and future A1B scenario (2021-2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of −2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. [ABSTRACT FROM AUTHOR]

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution. [ABSTRACT FROM AUTHOR]

The Arctic cell as a reversed and closed loop next to the Polar cell has been recently revealed in the Northern Hemisphere (NH). In this paper, we study the interannual variability of the Arctic and Polar cell strengths during 1979-2012, and their influence on surface air temperature (SAT), precipitation, and sea-ice concentration (SIC) at mid- and high-latitudes of the NH. We show that there is a significant negative correlation between the Arctic and Polar cell strengths. Both the Arctic and Polar cell strengths can well indicate the recurring climatic anomalies of SAT, precipitation, and SIC in their extreme winters. The surface large-scale cold-warm and dry-wet anomalous patterns in these extreme winters are directly linked with the vertical structure of height and temperature anomalies in the troposphere. Results suggest that the past climatic anomalies are better indicated by the strength anomalies of the Polar and Arctic cells than the traditional indices of mid-high latitude pattern such as the Arctic Oscillation and North Atlantic Oscillation. This study illustrates a three-dimensional picture of atmospheric variable anomalies in the troposphere that result in surface climatic anomalies. [ABSTRACT FROM AUTHOR]

The Eastern Mediterranean region has been exposed to drought episodes, which have been occurring more frequently during the last decades. The objective of the present paper is to study the precipitation regime of the Damascus (Mazzeh) meteoric station by analysing drought characteristics using the Standardized Precipitation Index (SPI) and comparing this with the drought in Cyprus. The cumulative drought conceptis proposed to characterize long-term hydrologic drought, which affects the shallow groundwater productivity in terms of quantity and quality. Gamma probability distribution was fitted to the long-term annual precipitation in Damascus from 1918-1919 to 2007-2008 ( n = 90 years). Generally, a decreasing trend of 17% to the mean annual rainfall of Damascus and 13% to the mean annual rainfall of Cyprus was estimated between 1970 and 2000. The SPI identifies three major extended drought periods: (1) 9 years of severe drought (1954-1963) with an average 20% precipitation deficit per year compared to the mean. (2) 8 years of severe drought (1983-1991) with a 27% deficit per year on average. (3) 9 years of extreme drought (1993-2002) with a 31% deficit per year on average. The cumulative standardized precipitation index (SPI 30) demonstrates positive values for the first period and is indicative of having no effect on the global water balance. SPI 30 exhibits sensitive equilibrium with near zero values / a near zero value (±1.5) for the second period. For the third period, however, the SPI 30 decreases below −10 indicating an extreme hydrological drought that has negative consequences on the recent groundwater recharge. It is required to develop and implement a sustainable groundwater management strategy to reduce long-terms drought risks. Generally, the SPI 30 in Cyprus is parallel to that in Damascus with a 3-5 year delay. Thus, the central zone of the Eastern Mediterranean region is facing big challenges and has been suffering from three decades of moderate to severe hydrological drought (SPI 30=−5 to −10) causing a severe decrease in springs discharges of the region. Therefore, in order to reduce the climate change effects on water resources, it is necessary to adopt a sustainable proactive management plan during the frequent severe droughts. [ABSTRACT FROM AUTHOR]

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)-two contrasting SD methods-in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector. [ABSTRACT FROM AUTHOR]

Of particular current importance in the general problem of global climate change is the regional manifestation of this process. The focus of this paper is concentrated on the transitional natural zones: forest tundra (st. Salekhard), and forest-steppe (st. Omsk) of the West Siberian Plain. The study is based on data for ground air temperatures and precipitation at the mean-daily and mean annual level, covering the time interval from 1936 to 2012. The observations are grouped in three periods: from 1936 to 1970, from 1971 to 2006, and from 2001 to 2012 thus making it possible to identify trends in the behavior of mean annual indicators, examine the intra-annual and seasonal changes, and to carry out a typification according to thermal regime and humidification regime. Regional changes in mean annual air temperatures at st. Salekhard and st. Omsk are representative of the general features of temperature variation over the entire observing period. In the Subarctic, however, the warming period became more pronounced in 2001, whereas it started in the 1970s in the forest-steppe, which is borne out by an increase in the recurrence frequency of warm and normal (according to thermal regime) years during the aforementioned periods. The southern part of the West Siberian Plain has experienced a more intense warming than in the north. Analysis of the intra-annual behavior of mean daily temperatures at st. Omsk showed their steady increase during the time interval from 1971 to 2012; this is especially true in regard to a warm season. At st. Salekhard the dynamics of temperatures is more complicated in character. Observation showed comparable (in duration) time spans with alternating increases and decreases in air temperature. The annual precipitation amounts for the time intervals used in the comparison indicated that their mean long-term value in the zones under consideration has increased for the last 35 years by 26 mm at st. Salekhard, and by 15 mm at st. Omsk. Considerable changes of climate have been observed since the 1970s; in high and mid-latitudes, they differ greatly and have influence on phenological phenomena, the structure of seasonal rhythms, the conditions of functioning of landscapes, and on human economic activity. [ABSTRACT FROM AUTHOR]

This paper presents results of trend analysis and change point detection of annual and seasonal precipitation, and mean temperature (TM), maximum temperature (TMAX) and minimum temperature (TMIN) time series of the period 1950-2007. Investigations were carried out for 50 precipitation stations and 39 temperature stations located in southwest Iran. Three statistical tests including Pettitt's test, Sequential Mann-Kendall test (SQ-MK test) and Mann-Kendall rank test (MK-test) were used for the analysis. The results obtained for precipitation series indicated that most stations showed insignificant trends in annual and seasonal series. Out of the stations which showed significant trends, highest numbers were observed during winter season while no significant trends were detected in summer precipitation. Moreover, no decreasing significant trends were detected by statistical tests in annual and seasonal precipitation series. The analysis of temperature trends revealed a significant increase during summer and spring seasons. TMAX was more stable than TMIN and TM, and winter was stable compared to summer, spring and autumn seasons. The results of change point detection indicated that most of the positive significant mutation points in TM, TMAX and TMIN began in the 1990s. [ABSTRACT FROM AUTHOR]

Precipitation over the contiguous United States exhibits large multi-decadal oscillations since the early twentieth century, and they often lead to dry (e.g., 1946-1976 and 1999-present) and wet (e.g., 1977-1998) periods and apparent precipitation trends (e.g., from the 1950s to 1990s) over most of the western and central US. The exact cause of these inter-decadal variations is not fully understood. Using observational and reanalysis data and model simulations, this paper examines the influence of the Inter-decadal Pacific Oscillation (IPO) on US precipitation. The IPO is a leading mode of sea surface temperatures (SSTs) seen mostly in the Pacific Ocean. It is found that decadal precipitation variations over much of the West and Central US, especially the Southwest, closely follow the evolution of the IPO ( r = 0.85 during 1923-2010 for the Southwest US), and the dry and wet periods are associated, respectively, with the cold and warm phases of the IPO. In particular, the apparent upward trend from the 1950s-1990s and the dry decade thereafter in precipitation over much of the West and Central US are largely caused by the IPO cycles, which switched to a warm phase around 1977 and back to a cold phase around 1999. An atmospheric model forced with observed SSTs reproduces much of this association of US precipitation with the IPO ( r = 0.95 between smoothed observed and simulated Southwest US precipitation during 1950-2009 and r = 0.88 between the simulated Southwest US precipitation and the IPO). Atmospheric reanalysis and model data both show a strong high (low) pressure center and anti-cyclonic (cyclonic) anomaly circulation over the North Pacific in the lower troposphere during cold (warm) phases of the IPO, which lead to dry and cold northwesterly and northerly winds and below-normal precipitation over much of the West US during IPO cold periods. The IPO induced changes are most pronounced during the boreal cold season. The results reinforce the notion that tropical Pacific SSTs (and the accompanying SST anomalies in the North Pacific) have large impacts on US precipitation and highlight the need to understand and simulate the IPO for decadal prediction of US precipitation. [ABSTRACT FROM AUTHOR]

Runoffs in the Yellow River and Yangtze River basins, China, have been changing constantly during the last half century. In this paper, data from eight river gauging stations and 529 meteorological stations, inside and adjacent to the study basins, were analyzed and compared to quantify the hydrological processes involved, and to evaluate the role of human activities in changing river discharges. The Inverse Distance Weighted (IDW) interpolation method was used to obtain climatic data coverage from station observations. According to the runoff coefficient equation, the effect of human activities and climate can be expressed by changes in runoff coefficients and changes in precipitation, respectively. Annual runoff coefficients were calculated for the period 1950-2008, according to the correlation between respective hydrological series and regional precipitation. Annual precipitation showed no obvious trend in the upper reaches of the Yellow River but a marked downward trend in the middle and downstream reaches, with declines of 8.8 and 9.8 mm/10 a, respectively. All annual runoff series for the Yellow River basin showed a significant downward trend. Runoff declined by about 7.8 mm/10 a at Sanmenxia and 10.8 mm/10 a at Lijin. The series results indicated that an abrupt change occurred in the late 1980s to early 1990s. The trend of correlations between annual runoff and precipitation decreased significantly at the Yellow River stations, with rates ranging from 0.013/10 a to 0.019/10 a. For the hydrologic series, all precipitation series showed a downward trend in the Yangtze River basin with declines ranging from about 24.7 mm/10 a at Cuntan to 18.2 mm/10 a at Datong. Annual runoff series for the upper reaches of the Yangtze River decreased significantly, at rates ranging from 9.9 to 7.2 mm/10 a. In the middle and lower reaches, the runoff series showed no significant trend, with rates of change ranging from 2.1 to 2.9 mm/10 a. Human activities had the greatest influence on changes in the hydrological series of runoff, regardless of whether the effect was negative or positive. During 1970-2008, human activities contributed to 83% of the reduction in runoff in the Yellow River basin, and to 71% of the increase in runoff in the Yangtze River basin. Moreover, the impacts of human activities across the entire basin increased over time. In the 2000s, the impact of human activities exceeded that of climate change and was responsible for 84% of the decrease and 73% of the increase in runoff in the Yellow River and Yangtze River basins, respectively. The average annual runoff from 1980 to 2008 fell by about 97%, 83%, 83%, and 91%, compared with 1951-1969, at the Yellow River stations Lanzhou, Sanmenxia, Huayuankou and Lijin, respectively. Most of the reduction in runoff was caused by human activities. Changes in precipitation also caused reductions in runoff of about 3%, 17%, 17%, and 9% at these four stations, respectively. Falling precipitation rates were the main explanation for runoff changes at the Yangtze River stations Cuntan, Yichang, Hankou, and Datong, causing reductions in runoff of 89%, 74%, 43%, and 35%, respectively. Underlying surface changes caused decreases in runoff in the Yellow River basin and increases in runoff in the Yangtze River basin. Runoff decreased in arid areas as a result of increased water usage, but increased in humid and sub-humid areas as a result of land reclamation and mass urbanization leading to decreases in evaporation and infiltration. [ABSTRACT FROM AUTHOR]

In this paper, variability in precipitation pattern of Pakistan due to environmental and climatic changes has been studied. Maps have been generated to depict global precipitation variation. Precipitation data of 25 stations of Pakistan have been used. These data were taken from Meteorological Department, Islamabad, Pakistan. The results of two global climate models, namely Australia's Commonwealth Scientific and Industrial Research's third generation general circulation model and National Center for Atmospheric Research's first generation precipitation circulation model for A2 scenario have been applied to investigate the changes. It is observed that precipitation pattern will change significantly in the future. The occurrence of precipitation in all seasons for Pakistan is expected to increase with almost uniform distribution across a season. Average annual precipitation of the country will undergo an increase in the range of +57 to +71 % as compared to average of the base period. [ABSTRACT FROM AUTHOR]

Global climate change could have important effects on various environmental variables in many countries around the world. Changes in precipitation regime directly affect water resources management. So that, it is important to analyze the changes in the spatial and temporal rainfall pattern in order to improve water resources management policies. For this reason, non-parametric Mann-Kendall rank correlation test is used in order to examine the existence of trends in annual and monthly rainfall distribution. To understand the regional differences of precipitation in Turkey, the detected trends are spatially interpolated using geostatistical techniques in a GIS environment. The main objective of this paper is to evaluate three interpolation methods, concerning their suitability for spatial prediction of temporal trends of Turkey's monthly and annual rainfall data. The study used a dense and homogeneous monthly precipitation database comprising 120 rain-gauge stations over a 32 years testing period of 1975-2009. The results conclusively show that significant positive trends are both infrequent and found only in outlying stations during March, April and October. In order to estimate and characterize the magnitude of observed changes at unmeasured locations, Ordinary Kriging, Inverse Distance Weighted and Completely Regularized Spline interpolation methods were employed and compared. A comparative analysis of interpolation techniques shows that Ordinary Kriging with having RMSE of 0.148 is the best choice. This is followed by Inverse Distance Weighted (RMSE 0.151), and Splines (RMSE 0.152). Cross validation of the results shows the largest over prediction at Kars rainfall station and largest under prediction at Burdur station. Upon for the examination of the cross-validation and spatial error clustering results, the Ordinary Kriging method was concluded to be the best algorithm in the interpolation process. [ABSTRACT FROM AUTHOR]

The accurate representation of rainfall in models of global climate has been a challenging task for climate modelers owing to its small space and time scales. Quantifying this variability is important for comparing simulations of atmospheric behavior with real time observations. In this regard, this paper compares both the statistical and dynamically forced aspects of precipitation variability simulated by the high-resolution (36 km) Nested Regional Climate Model (NRCM), with satellite observations from the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset and simulations from the Community Atmosphere Model (CAM) at T85 spatial resolution. Six years of rainfall rate data (2000-2005) from within the Tropics (30°S-30°N) have been used in the analysis and results are presented in terms of long-term mean rain rates, amplitude and phase of the annual cycle and seasonal mean maps of precipitation. Our primary focus is on characterizing the annual cycle of rainfall over four land regions of the Tropics namely, the Indian Monsoon, the Amazon, Tropical Africa and the North American monsoon. The lower tropospheric circulation patterns are analyzed in both the observations and the models to identify possible causes for biases in the simulated precipitation. The 6-year mean precipitation simulated by both models show substantial biases throughout the global Tropics with NRCM/CAM systematically underestimating/overestimating rainfall almost everywhere. The seasonal march of rainfall across the equator, following the motion of the sun, is clearly seen in the harmonic vector maps. The timing of peak rainfall (phase) produced by NRCM is in closer agreement with the observations compared to CAM. However like the long-time mean, the magnitude of seasonal mean rainfall is greatly underestimated by NRCM throughout the Tropical land mass. Some of these regional biases can be attributed to erroneous circulation and moisture surpluses/deficits in the lower troposphere in both models. Overall, the results seem to indicate that employing a higher spatial resolution (36 km) does not significantly improve simulation of precipitation. We speculate that a combination of several physics parameterizations and lack of model tuning gives rise to the observed differences between NRCM and the observations. [ABSTRACT FROM AUTHOR]

Interannual variability is an important modulator of synoptic and intraseasonal variability in South America. This paper seeks to characterize the main modes of interannual variability of seasonal precipitation and some associated mechanisms. The impact of this variability on the frequency of extreme rainfall events and the possible effect of anthropogenic climate change on this variability are reviewed. The interannual oscillations of the annual total precipitation are mainly due to the variability in austral autumn and summer. While autumn is the dominant rainy season in the northern part of the continent, where the variability is highest (especially in the northeastern part), summer is the rainy season over most of the continent, thanks to a summer monsoon regime. In the monsoon season, the strongest variability occurs near the South Atlantic Convergence Zone (SACZ), which is one of the most important features of the South American monsoon system. In all seasons but summer, the most important source of variability is ENSO (El Niño Southern Oscillation), although ENSO shows a great contribution also in summer. The ENSO impact on the frequency of extreme precipitation events is also important in all seasons, being generally even more significant than the influence on seasonal rainfall totals. Climate change associated with increasing emission of greenhouse gases shows potential to impact seasonal amounts of precipitation in South America, but there is still great uncertainty associated with the projected changes, since there is not much agreement among the models' outputs for most regions in the continent, with the exception of southeastern South America and southern Andes. Climate change can also impact the natural variability modes of seasonal precipitation associated with ENSO. [ABSTRACT FROM AUTHOR]

An Inconvenient Truth (AIT) has earned Al Gore an Oscar and a share of the 2007 Nobel Peace Prize and has been widely acclaimed by the mass media. However, significant errors exist in the film, owing to alarmism and exaggeration. As this forum does not provide for a detailed examination of these errors, this paper will focus only on the portrayal of the hydrologic cycle by AIT--precipitation and floods, soil moisture and droughts, and storminess. AIT argues that precipitation and intense rainfalls, floods, droughts, and the total number, intensity, and duration of tropical cyclones have all increased due exclusively to anthropogenically-driven climate change; indeed, AIT paints a picture of near scientific certainty with an overwhelming bias toward catastrophe scenarios. A closer look at the science, however, reveals that the data do not support these claims and that the scientific community is divided as to what the impact of anthropogenic climate change on the hydrologic cycle will be. Thus, the film gives a false impression of both the current state of climate change and that 'the science is settled'. [ABSTRACT FROM AUTHOR]

Little guidance is available to assist wetland managers in developing climate adaptation plans. To facilitate development of recommendations for adaptation strategies, it is essential to first determine if or how wetland managers are addressing these challenges. We used an online survey to solicit feedback from wetland managers and biologists in the Southern Great Plains of North America to gain information on perceptions of wetland managers regarding climate change; assess how the effects of climate change are being addressed through management; and identify barriers to implementing climate change adaptation. The majority of wetland managers (63%) agreed they are currently experiencing effects of climate change in wetlands, and most respondents (76%) reported that changes in the timing of water availability throughout the year was the most likely impact. Managers reported using a diversity of approaches in managing for changing precipitation, with management of native and invasive plant species being the two most common practices. Lack of funding and personnel were the most commonly identified factors limiting manager's response to changing precipitation patterns. In addition, >50% of managers indicated uncertainty about the effects of climate change on wetlands as a barrier to management, which may relate to limited access to peer-reviewed science. While most of the management practices reported were short-term measures and may not reflect long-term adaptation for climate change, the fact that many managers are considering climate change in their management suggests that there is considerable opportunities to continue developing capacity for climate change adaptation in the region. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the performance of six models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in reproducing the monthly cycle of precipitation and maximum surface air temperature of the Hodna region in central Algeria during the baseline period 1901–2014. The six climate models selected are as follows: ACCESS-ESM4, BCC-CSM2-MR, CanESM5, GFDL-ESM1-5, IPSL-EM6A-LR, and MIROC6. The best-performing models are determined by comparing observation (CRU-TS) and historical data. The evaluation procedure is performed using the compromise programming method and multiple statistical metrics including mean bias error (MB), root mean square error (RMSE), and pattern determination coefficient (R2). The first two best-performing models are used for precipitation (IPSL-EM6A-LR) and maximum surface air temperature (GFDL-ESM4). Four future periods are considered: 2021–2040, 2041–2060, 2061–2080, and 2081–2100 for SSP1-2.6 and SSP3-7.0. For the most optimist scenario, the maximum surface air temperature may increase in the next decades in comparison with observed and simulated values by 2 °C, but then almost stabilizes and reaches an average monthly increase of 28.53 °C. The same is shown in the precipitation projection of 48.75 mm/month by 2100. Eventually, the SSP1-2.6 scenario does not show any current signs in the current Hodna basin climate on a global scale. Future precipitation projections under Hodna's SSP3-7.0 may decrease with an average value of 10 mm in a monthly scale. This decrease becomes mostly in the center and southeastern parts. Maximum surface air temperature can rise steadily from 28 to 31 °C and reach its maximum of 4.5 °C by 2100. The outcomes of this study will evaluate how projected changes will affect droughts and floods. [ABSTRACT FROM AUTHOR]

Climate change is projected to have serious environmental, economic, and social impacts on Ghana, particularly on rural farmers whose livelihoods depend largely on rainfall. The extent of these impacts depends largely on awareness and the level of adaptation in response to climate change. This study examines the perception of farmers in Sekyedumase district of Ashanti region of Ghana on climate change and analyzes farmers' adaptation responses to climate change. A hundred and eighty farming households were interviewed in February and October 2009. Results showed that about 92% of the respondents perceived increases in temperature, while 87% perceived decrease in precipitation over the years. The major adaptation strategies identified included crop diversification, planting of short season varieties, change in crops species, and a shift in planting date, among others. Results of logit regression analysis indicated that the access to extension services, credit, soil fertility, and land tenure are the four most important factors that influence farmers' perception and adaptation. The main barriers included lack of information on adaptation strategies, poverty, and lack of information about weather. Even though the communities are highly aware of climate issues, only 44.4% of farmers have adjusted their farming practices to reduce the impacts of increasing temperature and 40.6% to decreasing precipitation, giving lack of funds as the main barrier to implementing adaptation measure. Implications for policymaking will be to make credit facilities more flexible, to invest in training more extension officers and more education on climate change and adaptation strategies. [ABSTRACT FROM AUTHOR]

A persistent concern about the social consequences of climate change is that large, vulnerable populations will be involuntarily displaced. Existing evidence suggests that changes in precipitation and temperature can increase migration in particular contexts, but the potential for this relationship to evolve over time alongside processes of adaptation and development has not been widely explored. To address this issue, we link longitudinal data from 20 thousand Chinese adults from 1989 to 2011 to external data on climate anomalies and use this linked dataset to explore how climatic effects on internal migration have changed over time while controlling for potential spatial and temporal confounders. We find that temperature anomalies initially displaced permanent migrants at the beginning of our study period, but that this effect had reversed by the end of the study period. A parallel analysis of income shares suggests that the explanation might lie in climate vulnerability shifting from agricultural to non-agricultural livelihood activities. Taken together with evidence from previous case studies, our results open the door to a potential future in which development and in situ adaptation allow climate-induced migration to decline over time, even as climate change unfolds. [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]

General circulation models (GCMs) allow the analysis of potential changes in the climate system under different emissions scenarios. However, their spatial resolution is too coarse to produce useful climate information for impact/adaptation assessments. This is especially relevant for regions with complex orography and coastlines, such as in Chile. Downscaling techniques attempt to reduce the gap between global and regional/local scales; for instance, statistical downscaling methods establish empirical relationships between large-scale predictors and local predictands. Here, statistical downscaling was employed to generate climate change projections of daily maximum/minimum temperatures and precipitation in more than 400 locations in Chile using the analog method, which identifies the most similar or analog day based on similarities of large-scale patterns from a pool of historical records. A cross-validation framework was applied using different sets of potential predictors from the NCEP/NCAR reanalysis following the perfect prognosis approach. The best-performing set was used to downscale six different CMIP5 GCMs (forced by three representative concentration pathways, RCPs). As a result, minimum and maximum temperatures are projected to increase in the entire Chilean territory throughout all seasons. Specifically, the minimum (maximum) temperature is projected to increase by more than 2 °C (6 °C) under the RCP8.5 scenario in the austral winter by the end of the twenty-first century. Precipitation changes exhibit a larger spatial variability. By the end of the twenty-first century, a winter precipitation decrease exceeding 40% is projected under RCP8.5 in the central-southern zone, while an increase of over 60% is projected in the northern Andes. [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]

Using 5-day averaged precipitation from all initial condition realizations of 33 CMIP5 models for the Historical and RCP8.5 scenarios, we performed an assessment of summer precipitation in terms of amount, onset date, withdrawal date, and length of season using probability distributions of interannual anomalies. Climate change projections were generated using all models, one model per modelling group to account for overconfidence, and sub-selecting models on annual cycle fidelity. Compared to using all models, sub-selecting on annual cycle fidelity has a large impact on the climate change perturbation of the fractional change in precipitation, with differences between the two projections of up to ± 50%, especially in the tropics and subtropics. Sensitivity testing indicates that the Gaussian t-test and the non-parametric Mann–Whitney U-test (the latter using Monte Carlo sampling) yield consistent results for assessing where the climate change perturbation is significant at the 1% level, even in cases where skewness and excess kurtosis indicate non-Gaussian behavior. Similarly, in terms of climate change induced perturbations to below-normal, normal, and above-normal categorical probabilities, the Gaussian results are typically consistent with the non-parametric estimates. These sensitivity results promote the use of Gaussian statistics to present global maps of the lower-bound and upper-bound of the climate change response, given that the non-parametric calculation of confidence intervals would otherwise not be tractable in a desktop computing environment due to its CPU intensive requirement. [ABSTRACT FROM AUTHOR]

Changing precipitation patterns caused by climate change are expected to have major impacts on food security and nutrition in agrarian areas in developing countries. However, the linkages between the duration and severity of precipitation shocks and their effects on child nutrition and household food security metrics remain underexplored. In this study, we used Feed the Future datasets from Ghana and Bangladesh to examine the impact of precipitation extremes on nutrition, measured by children's height-for-age and weight-for-height Z-scores, and food security, measured by the Household Hunger Scale. We used a spatial error regression to control for the effects of spatial autocorrelation, and we found an association between precipitation shocks and household hunger in both Ghana and Bangladesh, as well as an association between higher rainfall and worse child nutrition in Ghana. [ABSTRACT FROM AUTHOR]

Regional Climate Models (RCMs) are increasingly used to add small-scale processes at higher grid resolution that are not represented by their Lateral Boundary Conditions (LBCs). Rossby Centre regional atmospheric model, RCA4, has downscaled three Global Climate Models (GCMs), namely, CNRM-CM5, EC-EARTH and GFDL-ESM2M in the COordinated Regional climate Downscaling EXperiment (CORDEX) framework for Middle East North Africa (MENA) and South Asia (SA) domains. Arabian Peninsula is covered in both MENA and SA simulations, which gives a unique opportunity to study the effects of CORDEX domain and LBCs on the simulation of temperature and precipitation by RCM. It is examined by calculating the differences between MENA and SA simulations for different driving GCMs in the historical (1976–2005) and future (2071–2100) periods under RCP8.5 emission scenario, for both summer (dry) and winter (wet) seasons. RCA4 performs generally well when simulating the observed temperature and precipitation patterns, with some local wet biases over Asir Mountains and cold bias over the north eastern parts of Saudi Arabia. The simulations of temperature seem to be very sensitive to the simulation domain (i.e., MENA and SA) and less sensitive to different LBCs, whereas in case of precipitation LBCs seems to play a dominant role. The MENA simulations generally project about 2 °C warmer and drier climate compared to SA simulations by the end of this century, which is comparable to the differences arising due to different LBCs and climate change. [ABSTRACT FROM AUTHOR]

The biannual seasonal rainfall regime over the southern part of West Africa is characterised by two wet seasons, separated by the 'Little Dry Season' in July–August. Lower rainfall totals during this intervening dry season may be detrimental for crop yields over a region with a dense population that depends on agricultural output. Coupled Model Intercomparison Project Phase 5 (CMIP5) models do not correctly capture this seasonal regime, and instead generate a single wet season, peaking at the observed timing of the Little Dry Season. Hence, the realism of future climate projections over this region is questionable. Here, the representation of the Little Dry Season in coupled model simulations is investigated, to elucidate factors leading to this misrepresentation. The Global Ocean Mixed Layer configuration of the Met Office Unified Model is particularly useful for exploring this misrepresentation, as it enables separating the effects of coupled model ocean biases in different ocean basins while maintaining air–sea coupling. Atlantic Ocean SST biases cause the incorrect seasonal regime over southern West Africa. Upper level descent in August reduces ascent along the coastline, which is associated with the observed reduction in rainfall during the Little Dry Season. When coupled model Atlantic Ocean biases are introduced, ascent over the coastline is deeper and rainfall totals are higher during July–August. Hence, this study indicates detrimental impacts introduced by Atlantic Ocean biases, and highlights an area of model development required for production of meaningful climate change projections over the West Africa region. [ABSTRACT FROM AUTHOR]

The assessment of predictability for decadal predictions of quantities like temperature and precipitation typically focuses on regional and temporal mean values. However, changes in extremes can be different to changes in mean climate, and accordingly their predictability may be different. We use simulations from CSIRO-Mk3-6-0 (CMIP5 archive) to set up a 'perfect model' experiment to compare the predictability for mean and extreme temperature and precipitation on interannual to decadal time-scales. The results show that both the mean and likelihood of near-surface temperature extremes is potentially predictable in many regions in the first lead year, while the areas with precipitation predictability tend to be mostly in low-latitude regions during this period. On decadal time scales, significant potential skill for mean and extreme temperatures is found over the North Atlantic and Southern Ocean but also over some land areas including North Africa, Europe and North America. The general spatial patterns of predictability are very similar between the mean and extremes. However, indices of moderate temperature extremes in particular show a tendency towards higher predictability than the mean. The approach to studying predictability presented here uses international coordinated model intercomparison project simulations. However a larger number of different initializations would be required from more models to allow improved robustness of the results. [ABSTRACT FROM AUTHOR]

The precipitation record taken by J.B. Beccari in Bologna from 1723 to 1765, with three observations a day, has been recovered from the original Logs and analysed. Although metadata are scarce or even missing, a thorough investigation of the contemporary sources, the interactions between Beccari, his colleagues in Padua, and the Royal Society London, as well as the record analysis, have allowed reconstruction of most of the information concerning the instrument, its location and exposure, the measuring protocol and units. Daily, monthly and yearly amounts and frequencies, as well as extreme events, have been analysed. The first decade (i.e. 1723–1733) was drier than the 1961–1990 reference period and the subsequent decades wetter. During the calendar year, summer was dryer and October was characterized by a stronger activity of Atlantic perturbations. [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]

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 climate of the circumpolar Boreal forest is changing rapidly, resulting in a growing frequency of wildfires and changing precipitation patterns. These climate-related stressors may influence the cycling of nutrients within, and overall ecosystem condition of, Boreal watersheds. However, long-term perspectives of concurrent climate-related impacts on the cycling of nutrients in watersheds are rare. We present multi-decadal terrestrial and lake mass budgets of nitrogen, phosphorus and carbon within a headwater Boreal Shield watershed that was recovering from an extensive wildfire while experiencing measureable increases in annual precipitation. We used these budgets to quantify associations between nutrient retention in each ecosystem and changes in metrics defining landscape recovery after wildfire or precipitation. The terrestrial watershed retained over half of all nitrogen and phosphorus delivered to it by the atmosphere. Strong nutrient retention occurred despite ongoing landscape recovery from wildfire, measurable increases in precipitation, a forest tent caterpillar defoliation and rising atmospheric deposition. A downstream headwater lake was also a strong and consistent sink of nitrogen and phosphorus, highlighting a whole-watershed resistance to environmental disturbances. However, carbon was strongly lost downstream from the terrestrial ecosystem in close and positive association with precipitation, resulting in a darkening of the headwater lake over time with implications for the functioning of its ecosystem. Long-term mass budget monitoring of a Boreal catchment has provided insight into the resistances and dynamic changes within a northern watershed exposed to concurrent wildfire and increasing precipitation conditions. [ABSTRACT FROM AUTHOR]

Responses to future changes in climatic and socio-economic conditions can be expected to vary between sectors and regions, reflecting differential sensitivity to these highly uncertain factors. A sensitivity analysis was conducted using a suite of impact models (for health, agriculture, biodiversity, land use, floods and forestry) across Europe with respect to changes in key climate and socio-economic variables. Depending on the indicators, aggregated grid or indicative site results are reported for eight rectangular sub-regions that together span Europe from northern Finland to southern Spain and from western Ireland to the Baltic States and eastern Mediterranean, each plotted as scenario-neutral impact response surfaces (IRSs). These depict the modelled behaviour of an impact variable in response to changes in two key explanatory variables. To our knowledge, this is the first time the IRS approach has been applied to changes in socio-economic drivers and over such large regions. The British Isles region showed the smallest sensitivity to both temperature and precipitation, whereas Central Europe showed the strongest responses to temperature and Eastern Europe to precipitation. Across the regions, sensitivity to temperature was lowest for the two indicators of river discharge and highest for Norway spruce productivity. Sensitivity to precipitation was lowest for intensive agricultural land use, maize and potato yields and Scots pine productivity, and highest for Norway spruce productivity. Under future climate projections, North-eastern Europe showed increases in yields of all crops and productivity of all tree species, whereas Central and East Europe showed declines. River discharge indicators and forest productivity (except Holm oak) were projected to decline over southern European regions. Responses were more sensitive to socio-economic than to climate drivers for some impact indicators, as demonstrated for heat-related mortality, coastal flooding and land use. [ABSTRACT FROM AUTHOR]

We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes. [ABSTRACT FROM AUTHOR]

We examine long-term trends in the historical record of extreme precipitation events occurring over the French Mediterranean area. Extreme events are considered in terms of their intensity, frequency, extent and precipitated volume. Changes in intensity are analysed via an original statistical approach where the annual maximum rainfall amounts observed at each measurement station are aggregated into a univariate time-series according to their dependence. The mean intensity increase is significant and estimated at + 22% (+ 7 to + 39% at the 90% confidence level) over the 1961-2015 period. Given the observed warming over the considered area, this increase is consistent with a rate of about one to three times that implied by the Clausius-Clapeyron relationship. Changes in frequency and other spatial features are investigated through a Generalised Linear Model. Changes in frequency for events exceeding high thresholds (about 200 mm in 1 day) are found to be significant, typically near a doubling of the frequency, but with large uncertainties in this change ratio. The area affected by severe events and the water volume precipitated during those events also exhibit significant trends, with an increase by a factor of about 4 for a 200 mm threshold, again with large uncertainties. All diagnoses consistently point toward an intensification of the most extreme events over the last decades. We argue that it is difficult to explain the diagnosed trends without invoking the human influence on climate. [ABSTRACT FROM AUTHOR]

Due to spatial and temporal heterogeneity in moisture conditions, the responses of arid/humid climate regions (AHCR) to climate change are complex. In this study, we delineated the AHCR of China using information about the balance of the atmospheric water supply and demand collected from 581 meteorological stations over the past 50 years. We also analyzed inter-decadal shifts and linear trends in the AHCR and examined the influence of precipitation and reference evapotranspiration. The results indicate that the semi-arid region expanded significantly over the last five decades, mainly in northwest China, northern China, and the Tibetan Plateau and, by the 2000s, had increased by 33.53% relative to its extent in the 1960s; in contrast, the arid region shrank by 20.75%. The semi-arid region grew mainly because of transfers from the arid region in western China and the sub-humid region in eastern China. The decreased reference evapotranspiration and significantly increased precipitation together contributed to the expansion of the semi-arid region in northwest China and the Tibetan Plateau over the last 50 years. In contrast, the expansion of the semi-arid region in Inner Mongolia and northern China reflects the counteractive influence of decreased reference evapotranspiration and decreased precipitation. [ABSTRACT FROM AUTHOR]

Decomposition of plant litter is an important process in the terrestrial carbon cycle and makes up approximately 70% of the global carbon flux from soils to the atmosphere. Climate change is expected to have significant direct and indirect effects on the litter decomposition processes at various timescales. Using the TeaBag Index, we investigated the impact on decomposition of short-term direct effects of temperature and precipitation by comparing temporal variability over years, versus long-term climate impacts that incorporate indirect effects mediated through environmental changes by comparing sites along climatic gradients. We measured the initial decomposition rate (k) and the stabilization factor (S; amount of labile litter stabilizing) across a climate grid combining three levels of summer temperature (6.5-10.5°C) with four levels of annual precipitation (600-2700 mm) in three summers with varying temperature and precipitation. Several (a)biotic factors were measured to characterize environmental differences between sites. Increased temperatures enhanced k, whereas increased precipitation decreased k across years and climatic regimes. In contrast, S showed diverse responses to annual changes in temperature and precipitation between climate regimes. Stabilization of labile litter fractions increased with temperature only in boreal and sub-alpine sites, while it decreased with increasing precipitation only in sub-alpine and alpine sites. Environmental factors such as soil pH, soil C/N, litter C/N, and plant diversity that are associated with long-term climate variation modulate the response of k and S. This highlights the importance of long-term climate in shaping the environmental conditions that influences the response of decomposition processes to climate change. [ABSTRACT FROM AUTHOR]

As the first purely multi-decadal satellite-based soil moisture product that spans over 35 years (from November 1978 to December 2013) on a daily basis designed for climate application, the applicability of the European Space Agency (ESA) soil moisture product, including the hydrological consistency between the product and the observed precipitation and the product continuity on the Tibetan Plateau (TP) were investigated. The results show that there is significant degree between the ESA soil moisture product and the observed precipitation. The positive anomaly of the ESA soil moisture product can reflect the occurrences of precipitation, but the precipitation may not definitely lead to soil moisture anomaly, which largely depends on the precipitation amounts. For climate application, large number of missing gaps was shown on the west of the TP, where it is considered that the retrieval algorithms are largely affected by the permafrost covered in this region, leaving the ESA soil moisture product for further improvement. In application, the ESA soil moisture product was used to study the response of surface soil moisture to climate change on the TP. With the rapid warming and the overall wetting of the TP, soil moisture increases on the central of the TP with the increase of precipitation, and decreases in the southeast TP with the precipitation deduction. However, it decreases in the west TP, where it was probably influenced by both the insignificant precipitation changes and the significant increase of evaporation. [ABSTRACT FROM AUTHOR]

We analyse the impact of the North Atlantic Oscillation (NAO) on the climate of East Asia at subseasonal time scales during both winter and summer. These teleconections have mainly been investigated at seasonal and longer time scales, while higher-frequency links are largely unexplored. The NAO is defined using extended empirical orthogonal functions on pentad-mean observations, which allows to elucidate the oscillation’s spatial and temporal evolution and clearly separate the development and decay phases. The downstream dynamical imprint and associated temperature and precipitation anomalies are quantified by means of a linear regression analysis. It is shown that the NAO generates a significant climate response over East Asia during both the dry and wet seasons, whose spatial pattern is highly dependent on the phase of the NAO’s life cycle. Temperature and precipitation anomalies develop concurrently with the NAO mature phase, and reach maximum amplitude 5-10 days later. These are shown to be systematically related to mid and high-latitude teleconnections across the Eurasian continent via eastward-propagating quasi-stationary Rossby waves instigated over the Atlantic and terminating in the northeastern Pacific. These findings underscore the importance of rapidly evolving dynamical processes in governing the NAO’s downstream impacts and teleconnections with East Asia. [ABSTRACT FROM AUTHOR]

This study conducted an updated time of emergence (ToE) analysis of regional precipitation changes over land regions across the globe using multiple climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5). ToEs were estimated for 14 selected hotspots over two seasons of April to September (AS) and October to March (OM) from three RCP scenarios representing low (RCP2.6), medium (RCP4.5), and high (RCP8.5) emissions. Results from the RCP8.5 scenario indicate that ToEs would occur before 2040 over seven hotspots including three northern high-latitude regions (OM wettening), East Africa (OM wettening), South Asia (AS wettening), East Asia (AS wettening) and South Africa (AS drying). The Mediterranean (both OM and AS drying) is expected to experience ToEs in the mid-twenty-first century (2040-2080). In order to measure possible benefits from taking low-emission scenarios, ToE differences were examined between the RCP2.6 scenario and the RCP4.5 and RCP8.5 scenarios. Significant ToE delays from 26 years to longer than 67 years were identified over East Africa (OM wettening), the Mediterranean (both AS and OM drying), South Asia (AS wettening), and South Africa (AS drying). Further, we investigated ToE differences between CMIP3-based and CMIP5-based models using the same number of models for the comparable scenario pairs (SRESA2 vs. RCP8.5, and SRESB1 vs. RCP4.5). Results were largely consistent between two model groups, indicating the robustness of ToE results. Considerable differences in ToEs (larger than 20 years) between two model groups appeared over East Asia and South Asia (AS wettening) and South Africa (AS drying), which were found due to stronger signals in CMIP5 models. Our results provide useful information on the timing of emerging signals in regional and seasonal hydrological changes, having important implications for associated adaptation and mitigation plans. [ABSTRACT FROM AUTHOR]

Climate change is a global phenomenon. Its impact on economic growth must therefore be analyzed in accordance with its (time-varying) common effects. We present an econometric analysis that evaluates this effect taking into account its global nature. Contrary to previous evidence that ignores the global effects, we obtain that the rising temperature has not decreased growth in real GDP per capita in the second half of the twentieth century for the world countries. However, we obtain a negative effect of rising temperatures and a positive effect of rising precipitation in poor countries. This positive effect of rising precipitation is also confirmed for hot and temperate countries. [ABSTRACT FROM AUTHOR]

Present study has assessed different sources of uncertainties in multi-model precipitation projection using Global Climate Models (GCMs) from coupled model inter-comparison project phase five (CMIP5) experiment over seven homogeneous rainfall zones of India namely North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI), and South Peninsular India (SPI). A relatively new method has been employed to separate out internal variability and climate change signal from precipitation time series before quantifying the uncertainties. In our method, signal has been defined as dynamic trend instead of considering a fixed trend line. Three different types of weighting namely equal weighting, independence based weighting and performance based weighting have been employed to assess the uncertainties of GCM projection over different zones. It has been found that ensemble with performance based weighting has produced smaller inter-model uncertainty but the patterns of temporal evolution of uncertainties have been quite irregular compared to other two ensembles. On the other hand, it has been noticed that bias correction using quantile mapping can effectively reduce the range of uncertainty in a systematic way. It has been observed that inter-model uncertainties over NEI has been relatively lower compared to other zones indicating more robust projection over this zone. A dynamic threshold on signal-to-internal variability ratio (S/I) has been used for estimating time of emergence (TOE) at 95% confidence level over each zone. TOE would be earlier in case of NEI and late in NMI. However no zone may experience TOE in first half of the present century. [ABSTRACT FROM AUTHOR]

Precipitation frequency (F) and intensity (I) are important characteristics that climate models often fail to simulate realistically. Their estimates are highly sensitive to the spatial and temporal resolutions of the input data and this further complicates the comparison between models and observations. Here, we analyze 3-hourly precipitation data on a 0.25° grid from two satellite-derived datasets, namely TRMM 3B42 and CMORPH_V1.0, to quantify this dependence of the estimated precipitation F and I on data resolution. We then develop a simple probability-based relationship to explain this dependence, and examine the spatial and seasonal variations in the estimated F and I fields. As expected, precipitation F (I) increases (decreases) with the size of the grid box or time interval over which the data are averaged, but the magnitude of this change varies with location, and is strongest in the tropics and weakest in the subtropics. Our simple relationship can quantitatively explain this dependence of the estimated F and I on the spatial or temporal resolution of the input data. This demonstrates that large differences in the estimated F and I can arise purely from the differences in the spatial or temporal resolution of the input data. The results highlight the need to have similar resolution in comparing two datasets or between observations and models. Our estimates show that extremely low frequencies (<1%) are seen over the subtropics while the highest frequencies (20-40%) are located mostly over the tropics, and that the high frequency results from both longer and more frequent precipitation events. Precipitation intensity is more uniformly distributed than frequency. Strong correlations between the amount and frequency confirm the notion that the frequency plays a bigger role than intensity in determining precipitation variations. [ABSTRACT FROM AUTHOR]