Search

In coastal catchments, rainfall events primarily drive bacterial inputs to the sea by causing land runoff, surface leaching and sewer overflow. Under semi-arid climate, extensive dry periods are interspersed with extreme precipitation. This paper aims to assess the impact of intense summer rainstorms events on Fecal Indicator Bacteria loadings to Mediterranean seawaters. Firstly, explanatory relationships were derived between an Antecedent Precipitation Index and the loads of thermo-tolerant coliforms and intestinal enterococci measured at three catchment outlets in the Gulf of Aigues-Mortes (southern France). Secondly, fecal bacterial loadings were simulated during summer season from 2006–2016, with a confidence interval arising from measurements uncertainties. On average, more than two rainstorms per summer season elevate bacterial loads at least by one order of magnitude, potentially leading to the degradation of bathing and fishing water quality observed in regulatory monitoring data. The results highlight the crucial importance of considering hydrological conditions in coastal water quality management. [ABSTRACT FROM AUTHOR]

'Neighborhood approaches' have been used in two primary ways to postprocess and verify high-resolution ensemble output. While the two methods appear deceptively similar, they define events over different spatial scales and yield fields with different interpretations: the first produces probabilities interpreted as likelihood of event occurrence at the grid scale, while the second produces probabilities of event occurrence over spatial scales larger than the grid scale. Unfortunately, some studies have confused the two methods, while others did not acknowledge multiple possibilities of neighborhood approach application and simply stated, 'a neighborhood approach was applied' without supporting details. Thus, this paper reviews applications of neighborhood approaches to convection-allowing ensembles in hopes of clarifying the two methods and their different event definitions. Then, using real data, it is demonstrated how the two approaches can yield statistically significantly different objective conclusions about model performance, underscoring the critical need for thorough descriptions of how neighborhood approaches are implemented and events are defined. The authors conclude by providing some recommendations for application of neighborhood approaches to convection-allowing ensembles. [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]

This paper investigates the impact and potential use of the cut cell vertical discretisation for forecasts of 5 days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 by forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut cell model LMZ provides a much more accurate representation of mountains on model forecasts than the terrain following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalaya, over South East China, Korea and Japan. The LMZ has been tested so far extensively for one-day forecasts on an European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut cell discretisation on forecast quality. The cut cell model is available only of an older (2003) Version of the model LM. It was compared using a control model differing by the use of the terrain following coordinate only. The cut cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved version of the terrain following model LM has been developed since then under the name CLM. The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of cut cell model were compared also to the CLM. As the cut cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalaya, the cut cell model improved the prediction of the monthly precipitation forecast even in comparison with the modern model version CLM considerably. The cut cell discretisation seems to improve in particular the localisation of precipitation, while the improvements leading from LM to CLM had a positive effect mainly on amplitude. [ABSTRACT FROM AUTHOR]

It is now common knowledge that many water resources stresses relate to access to water within a basin. Yi River Basin, a typical river basin characterized by intensive agricultural processes, significant population growth, and water management, has been undergoing grave water problems. In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. Climate elasticity method and linear regression method were implemented to quantify the impact of precipitation and human activities on runoff and presented basically consistent results of the percentage change in an annual runoff for the postchange period. The results reveal that the decline of annual runoff in postchange period is mainly attributed to precipitation variability of 53.66–58.25% and human activities of 46.34–41.74%, as estimated by climate elasticity method and linear regression method, respectively. This study detected the changes in the precipitation-streamflow relationship and investigated the possible causes in the Yi River, which will be helpful for providing a reference for the management of regional water resources. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyse the water regime of soils under spruce ecosystems in relation to long-lasting humid and drought periods in the growing seasons 1991-2013. The dominant interval humidity in observing growing seasons is semiuvidic interval with soil moisture between hydro-limits maximal capillary capacity (MCC) and point of diminished availability (PDA). Gravitationally seepage concentrated from accumulated winter season, water from melting snow and existing atmospheric precipitation occurs in the soil only at the beginning of the growing season. The supplies of soil water are significantly decreasing in the warm climate and precipitant deficient days. The greatest danger from drought threatens Norway spruce during the summer months and it depends on the duration of dry days, water supply at the beginning of the dry days, air temperature and the intensity of evapotranspiration. In the surface layers of the soil, with the maximum occurrence of active roots, the water in semiarid interval area between hydro-limits PDA and wilting point (WP) decreases during the summer months. In the culminating phase occurs the drying to moisture state with capillary stationary and the insufficient supply of available water for the plants. Physiological weakening of Norway spruce caused by set of outlay components of the water balance is partially reduced by delivering of water by capillary action from deeper horizons. In extremely dry periods, soil moisture is decreasing also throughout the soil profile (0-100 cm) into the bottom third of the variation margin hydro-limits MCC-PDA in the category of capillary less moving and for plants of low supply of usable water (60-90 mm). The issue of deteriorated health state of spruce ecosystems is considered to be actual. Changes and developments of hydropedological conditions which interfere the mountain forests represent the increasing danger of the drought for the spruce. [ABSTRACT FROM AUTHOR]

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is "better" in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decompose the precipitation response in the RCP8.5 scenario into a CO2 portion and a non-CO2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO2-/non-CO2-forcing decomposition is applied. The methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change. [ABSTRACT FROM AUTHOR]

Mountainous regions experience complex phenological behavior along climatic, vegetational and topographic gradients. In this paper, we use a MODIS time series of the Normalized Difference Vegetation Index (NDVI) to understand the causes of variations in spring and autumn timing from 2000 to 2015, for a landscape renowned for its biological diversity. By filtering for cover type, topography and disturbance history, we achieved an improved understanding of the effects of seasonal weather variation on land surface phenology (LSP). Elevational effects were greatest in spring and were more important than site moisture effects. The spring and autumn NDVI of deciduous forests were found to increase in response to antecedent warm temperatures, with evidence of possible cross-seasonal lag effects, including possible accelerated green-up after cold Januarys and early brown-down following warm springs. Areas that were disturbed by the hemlock woolly adelgid and a severe tornado showed a weaker sensitivity to cross-year temperature and precipitation variation, while low severity wildland fire had no discernable effect. Use of ancillary datasets to filter for disturbance and vegetation type improves our understanding of vegetation’s phenological responsiveness to climate dynamics across complex environmental gradients. [ABSTRACT FROM AUTHOR]

Flood is define as a natural disaster that causes loss of life and property damages. Flash flood is an overflow of water that submerge lands and properties affecting lives and habitats all around the world due to climate change and heavy rainfalls. It is impossible to avoid risk or prevent their occurrence but we can reduce their effects by various engineering techniques. Incessant monsoon rains in the month of July 2016, triggered flash floods in several southern districts of Bhutan including Sarpang town affecting hundreds of people. The town was also wiped out after an overnight flash flood in 1996 and several minor flash flood kept on occurring particularly during monsoon. Hence, the present study aims to model the flash flood with respect to rainfall at Sarpang, Bhutan and to understand the suitability of methods in mountain terrain. Modelling was done by integrating ArcGIS and HEC-RAS modelling software. SRTM DEM and Landsat 8 OLI satellite image were used as base data. Meteorological data from Department of Hydro Met Services, Bhutan has been used to calculate average discharge of the river outlet. The model was validated with the recent flash flood event and also study shows that the methods and procedures adopted in this paper are suitable for carrying out similar kind of studies in mountain terrain like Sarpang where flash floods are very frequent and most common. [ABSTRACT FROM AUTHOR]

The 2015 release of the precipitation climatology from the Global Precipitation Climatology Centre (GPCC) for 1951-2000, based on climatological normals of about 75,100 rain gauges, allows for quantification of mean land surface precipitation as part of the global water cycle. In GPCC's 2011-release, a bulk climatological correction was applied to compensate for gauge undercatch. In this paper we derive an improved correction approach based on the synoptic weather reports for the period 1982-2015. The compared results show that the climatological approach tends to overestimate the correction for Central and Eastern Europe, especially in the northern winter, and in other regions throughout the year. Applying the mean weather-dependent correction to the GPCC's uncorrected precipitation climatology for 1951-2000 gives a value of 854.7 mm of precipitation per year (excluding Antarctica) or 790 mm for the global land surface. The warming of nearly 1 K relative to pre-industrial temperatures is expected to be accompanied by a 2%-3% increase in global (land and ocean) precipitation. However, a comparison of climatology for 30-year reference periods from 1931-1960 up to 1981-2010 reveals no significant trend for land surface precipitation. This may be caused by the large variability of precipitation, the varying data coverage over time and other issues related to the sampling of rain-gauge networks. The GPCC continues to enlarge and further improve the quality of its database, and will generate precipitation analyses with homogeneous data coverage over time. Another way to reduce the sampling issues is the combination of rain gauge-based analyses with remote sensing (i.e., satellite or radar) datasets. [ABSTRACT FROM AUTHOR]

The identification of homogeneous precipitation regions is essential in the planning, design and management of water resources systems. Regions are identified using a technique that partitions climate sites into groups based on the similarity of their attributes; the procedure is known as regionalization. In this paper the ability of four attribute sets to form large, coherent precipitation zones is assessed in terms of the regional homogeneity of precipitation statistics and computational efficiency. The outcomes provide guidance for effective attribute selection for future studies in Canada. The attributes under consideration include location parameters (latitude, longitude), distance to major water bodies, site elevation and atmospheric variables modelled at different pressure levels. The analysis is conducted in two diverse climate regions within Canada including the Prairie and the Great Lakes–St Lawrence lowlands regions. The method consists of four main steps: (i) formation of the attribute sets; (ii) determination of the preferred number of regions (selection of thec-value) into which the sites are partitioned; (iii) regionalization of climate sites using the fuzzyc-means clustering algorithm; and (iv) validation of regional homogeneity usingL-moment statistics. The results of the attribute formation,c-value selection, regionalization and validation processes are presented and discussed in a comparative analysis. Based on the results it is recommended for both regions to use location parameters including latitude, longitude and distance to water bodies (in the Great Lakes region) to form precipitation regions and to consider atmospheric variables for future (climate change) applications of the regionalization procedure. [ABSTRACT FROM PUBLISHER]

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]

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]

The Madden-Julian Oscillation (MJO) is the dominant mode of sub-seasonal climate variability in the global tropics. As such it represents an opportunity for intra-seasonal rainfall prediction and, perhaps, for explaining dynamics that underlie longer term variability and trends. This opportunity is of substantial interest for tropical Africa, where rainfall variability has significant impacts on agriculture, energy, and natural ecosystems. The objective of this review paper is to inventory and assess the state of knowledge of MJO influence on African rainfall. A number of studies have identified statistical links between MJO and sub-seasonal rainfall variability in West, East, and Southern Africa. The proposed mechanisms to explain this influence differ by region and by season, and they often involve multiscale interactions between local precipitation processes and MJO-associated atmospheric dynamics. Dynamically-based forecast systems have some skill in predicting MJO evolution to time horizons of 3–4 weeks, and some can capture teleconnections to Africa. On longer time scales, there is evidence that MJO activity both modulates and is modulated by the El Niño Southern Oscillation and the Indian Ocean Dipole. The implications of these interactions for MJO connections to Africa require further research, as does the potential for trends in MJO behavior and impacts on Africa under global climate change. [ABSTRACT FROM AUTHOR]

Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin. [ABSTRACT FROM AUTHOR]

The goal of the attribution of individual events is to estimate whether and to what extent the probability of an extreme climate event evolves when external conditions (e.g., due to anthropogenic forcings) change. Many types of climate extremes are linked to the variability of the large-scale atmospheric circulation. It is hence essential to decipher the roles of atmospheric variability and increasing mean temperature in the change of probabilities of extremes. It is also crucial to define a background state (or counterfactual) to which recent observations are compared. In this paper we present a statistical framework to determine the dynamical (linked to the atmospheric circulation) and thermodynamical (linked to slow forcings) contributions to the probability of extreme climate events. We illustrate this methodology on a record precipitation event that hit southern United Kingdom in January 2014. We compare possibilities for the creation of two states (or "worlds") in which probability change is determined. These two worlds are defined in a large ensemble of atmospheric model simulations (Weather@Home factual and counterfactual simulations) and separate periods (new: 1951-2014, and old: 1900- 1950) in reanalyses and observations. We discuss how the atmospheric circulation conditioning can affect the interpretation of extreme event attribution. We eventually show the qualitative coherence of results between the choice of worlds (factual/counterfactual vs. new/old). [ABSTRACT FROM AUTHOR]

Global warming and climate change have increased the frequency of heavy precipitation. Heavy rainfall results in a large amount of water entering roadways within a short time period. Water remains in the pavement system for a certain time period, reduces strengths and moduli of granular bases and subgrades, and induces pavement distresses. Geotextiles are commonly used in roadways for drainage purposes, which require soil saturation. However, soil saturation does not always exist in roadways to enable gravity drainage of water by conventional geotextiles. Wicking geotextile, a new type of woven geotextile, was recently introduced to the market to remove moisture from unsaturated soils. The wicking geotextile includes special hydrophilic and hygroscopic 4 deep groove fibers with multichannel cross sections, which can induce high capillary force to wick water out of moist soil without saturation of soil. The ability and rate of this geotextile to remove water from moist soil depends on several factors, including temperature and relative humidity. In this study, a series of laboratory tests under controlled temperature and relative humidity were conducted to quantify the water removal rate of the wicking geotextile. A half length of the wicking geotextile was submerged in water tanks, and the other half was hung outside of the tanks. The water wicked from the tank into the geotextile evaporated into the air. Such tests were conducted under 12 different test conditions (i.e., different temperatures and relative humidities). Test results demonstrated that the wicking geotextile could remove water from the water tank at a certain rate. Three commonly used methods available in the literature were adopted to quantify the water removal rate of the wicking geotextile based on vapor pressure, temperature, and relative humidity. A new concept of equivalent water evaporation length of a wicking geotextile is proposed in this study. It should be pointed out that the tests presented in this paper aimed to determine the maximum water removal capacity of the geotextile given sufficient water supply. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to incorporate the non-stationarities characterised in the GCM outputs, into the Predictor-Predictand Relationships (PPRs) in statistical downscaling models. In this approach, a series of 42 PPRs based on multi-linear regression (MLR) technique were determined for each calendar month using a 20-year moving window moved at a 1-year time step on the predictor data obtained from the NCEP/NCAR reanalysis data archive and observations of precipitation at 3 stations located in Victoria, Australia, for the period 1950–2010. Then the relationships between the constants and coefficients in the PPRs and the statistics of reanalysis data of predictors were determined for the period 1950–2010, for each calendar month. Thereafter, using these relationships with the statistics of the past data of HadCM3 GCM pertaining to the predictors, new PPRs were derived for the periods 1950–69, 1970–89 and 1990–99 for each station. This process yielded a non-stationary downscaling model consisting of a PPR per calendar month for each of the above three periods for each station. The non-stationarities in the climate are characterised by the long-term changes in the statistics of the climate variables and above process enabled relating the non-stationarities in the climate to the PPRs. These new PPRs were then used with the past data of HadCM3, to reproduce the observed precipitation. It was found that the non-stationary MLR based downscaling model was able to produce more accurate simulations of observed precipitation more often than conventional stationary downscaling models developed with MLR and Genetic Programming (GP). [ABSTRACT FROM AUTHOR]

Pattern scaling is a well established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare three methods of pattern scaling for precipitation (regression, epoch difference, and a physically-based method) and evaluate which methods are "better" in particular circumstances by quantifying their robustness to interpolation/extrapolation, inter-model variations, and inter-scenario variations. Although the regression and epoch difference methods (the two most commonly used methods of pattern scaling) have better absolute performance in reconstructing the climate model output by two orders of magnitude (measured as an area-weighted root mean square error), the physically-based method shows a greater degree of robustness (less relative root-mean-square variation than the other two methods) and could be a particularly advantageous method if outstanding biases could be reduced. We decompose the precipitation response in the RCP8.5 scenario into a CO2 portion and a non-CO2 portion; these two patterns oppose each other in sign. Due to low signal-to-noise ratios, extrapolating RCP8.5 patterns to re-construct precipitation change in the RCP2.6 scenario results in double the error of reconstructing the RCP8.5 scenario for the regression and epoch difference methods. The methodologies discussed in this paper can help provide precipitation fields for other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change. [ABSTRACT FROM AUTHOR]

Global Circulation Models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, and including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern-scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in amount of warming over land and globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper we present a pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy balance model that calculates the amount of global warming. The set is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for CMIP5 ensemble. Critically it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impacts studies. Across models, the presented climate patterns represent consistent global mean trends, with maximum four GCMs exhibiting opposite sign of the trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and with decreased relative humidity. Overall, the patterns of the analysed variables explain one-third of regional change in decadal averages (mean Percentage Variance Explained, PVE, 34.25 ± 5.21), but signal in some models exhibits much more linearity (e.g. MIROC3.2(hires):41.53) than in others (GISS_ER: 22.67). The two most often considered variables: near-surface temperature and precipitation, have PVE of 85.44 ± 4.37 and 14.98 ± 4.61, respectively. The dataset is available for download and researchers in the areas of ecosystem modelling and climate change impact assessment are already starting to use it. Besides allowing time-efficient assessment for non-standard future scenarios of changed greenhouse gas (GHG) concentrations, it enables understanding of new representations of land surface processes, and including climate-carbon cycle feedbacks. Current and potential future applications of such modelling system are discussed. [ABSTRACT FROM AUTHOR]

The analysis of the tree radial growth response to climate is crucial for dendroclimatological research. However, the response relationships between tree-ring indices and climatic factors at different timescales are not yet clear. In this study, the tree-ring width of Huashan pine (Pinus armandii) from Huashan in the Qinling Mountains, north-central China, was used to explore the response differences of tree growth to climatic factors at daily, pentad (5 days), dekad (10 days) and monthly timescales. Correlation function and linear regression analysis were applied in this paper. The tree-ring width showed a more sensitive response to daily and pentad climatic factors. With the timescale decreasing, the absolute value of the maximum correlation coefficient between the tree-ring data and precipitation increases as well as temperature (mean, minimum and maximum temperature). Compared to the other three timescales, pentad was more suitable for analysing the response of tree growth to climate. Relative to the monthly climate data, the association between the tree-ring data and the pentad climate data was more remarkable and accurate, and the reconstruction function based on the pentad climate was also more reliable and stable. We found that the major climatic factor limiting Huashan pine growth was the precipitation of pentads 20–35 (from April 6 to June 24) rather than the well-known April–June precipitation. The pentad was also proved to be a better timescale for analysing the climate and tree growth in the western and eastern Qinling Mountains. The formation of the earlywood density of Chinese pine (Pinus tabulaeformis) from Shimenshan in western Qinling was mainly affected by the maximum temperature of pentads 28–32 (from May 16 to June 9). The maximum temperature of pentads 28–33 (from May 16 to June 14) was the major factor affecting the ring width of Chinese pine from Shirenshan in eastern Qinling. [ABSTRACT FROM AUTHOR]

Few if any high-resolution (annually resolved) paleoclimate records are available for the Hawaiian Islands prior to ~1850 CE, after which some instrumental records start to become available. This paper shows how atmospheric teleconnection patterns between North America and the northeastern North Pacific (NNP) allow for reconstruction of Hawaiian Islands rainfall using remote proxy information from North America. Based on a newly available precipitation dataset for the state of Hawaii and observed and reconstructed December-February (DJF) sea level pressures (SLPs) in the North Pacific Ocean, the authors make use of a strong relationship between winter SLP variability in the northeast Pacific and corresponding DJF Hawaii rainfall variations to reconstruct and evaluate that season's rainfall over the period 1500-2012 CE. A general drying trend, though with substantial decadal and longer-term variability, is evident, particularly during the last ~160 years. Hawaiian Islands rainfall exhibits strong modulation by El Niño-Southern Oscillation (ENSO), as well as in relation to Pacific decadal oscillation (PDO)-like variability. For significant periods of time, the reconstructed large-scale changes in the North Pacific SLP field described here and by construction the long-term decline in Hawaiian winter rainfall are broadly consistent with long-term changes in tropical Pacific sea surface temperature (SST) based on ENSO reconstructions documented in several other studies, particularly over the last two centuries. Also noted are some rather large multidecadal fluctuations in rainfall (and hence in NNP SLP) in the eighteenth century of undetermined provenance. [ABSTRACT FROM AUTHOR]

Abstract: Cities are becoming increasingly vulnerable to flooding because of rapid urbanization, installation of complex infrastructure, and changes in the precipitation patterns caused by anthropogenic climate change. The present paper provides a critical review of the current state-of-the-art methods for assessing the impacts of climate change on precipitation at the urban catchment scale. Downscaling of results from global circulation models or regional climate models to urban catchment scales are needed because these models are not able to describe accurately the rainfall process at suitable high temporal and spatial resolution for urban drainage studies. The downscaled rainfall results are however highly uncertain, depending on the models and downscaling methods considered. This uncertainty becomes more challenging for rainfall extremes since the properties of these extremes do not automatically reflect those of average precipitation. In this paper, following an overview of some recent advances in the development of innovative methods for assessing the impacts of climate change on urban rainfall extremes as well as on urban hydrology and hydraulics, several existing difficulties and remaining challenges in dealing with this assessment are discussed and further research needs are described. [Copyright &y& Elsevier]

Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

In a changing climate, there is an interest in predicting how extreme rainfall events may change. Using historical records, several recent papers have evaluated whether high-intensity precipitation scales with temperature in accordance with the Clausius--Clapeyron (C--C) relationship. For varying locations in Europe, these papers have identified both super C--C relationships as well as a breakdown of the C--C relationship under dry conditions. In this paper, a similar analysis is carried out for the United States using data from 14 weather stations clustered in four different hydroclimatic regions: the coastal northeast, interior New York, the central plains, and the western plains. In all regions except interior New York state, 99th percentile 1-h precipitation generally followed the C--C relation. In interior New York, there was evidence that intensity scaled with a super C--C relationship. For the 99.9th percentile precipitation, interior New York displayed some moderate evidence of a super C--C relationship, the western plains showed little relation between precipitation and temperature, and the remainder of sites generally scaled with the C--C relationship. Also, if only July, August, and September precipitation is considered, all stations except those in interior New York have little relation between temperature and precipitation, suggesting that precipitation intensity during summer months may not be well constrained by the C--C relationship. Overall, the C--C relationship (or a variation thereof) does not appear to constrain extreme precipitation in all regions and in all seasons, and its ability to aid in constraining future predictions of extreme precipitation may only be relevant to certain locales and time periods. [ABSTRACT FROM AUTHOR]

Abstract: There is growing interest in the impact of climate change on urban hydrological processes. Such assessment may be based on the precipitation output from climate models. To date, the model resolution in both time and space has been too low for proper assessment, but at least in time the resolution of available model output is approaching urban scales. In this paper, 30-min precipitation from a model grid box covering Kalmar City, Sweden, is compared with high-resolution (tipping-bucket) observations from a gauge in Kalmar. The model is found to overestimate the frequency of low rainfall intensities, and therefore the total volume, but reasonably well reproduce the highest intensities. Adapting climate model data to urban drainage applications can be done in several ways but a popular way is the so-called Delta Change (DC) method. In this method, relative changes in rainfall characteristics estimated from climate model output are transferred to an observed rainfall time series, generally by multiplicative factors. In this paper, a version of the method is proposed in which these DC factors (DCFs) are related to the rainfall intensity level. This is achieved by calculating changes in the probability distribution of rainfall intensities and modelling the DCFs as a function of percentile. Applying this method in Kalmar indicated that in summer and autumn, high intensities will increase by 20–60% by year 2100, whereas low intensities remain stable or decrease. In winter and spring, generally all intensity levels increase similarly. The results were transferred to the observed time series by varying the volume of the tipping bucket to reflect the estimated intensity changes on a 30-min time scale. In an evaluation of the transformed data at a higher 5-min resolution, effects on the intensity distribution as well as single precipitation events were demonstrated. In particular, qualitatively different changes in peak intensity and total volume are attainable, which is required in light of expected future changes of the precipitation process and a step forward as compared with simpler DC approaches. Using the DC transformed data as input in urban drainage simulations for a catchment in Kalmar indicated an increase of the number of surface floods by 20–45% during this century. [Copyright &y& Elsevier]

This paper examines the controls on global precipitation that are evident in the transient experiments conducted using coupled climate models collected for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The change in precipitation, water vapor, clouds, and radiative heating of the atmosphere evident in the 1% increase in carbon dioxide until doubled (1pctto2x) scenario is examined. As noted in other studies, the ensemble-mean changes in water vapor as carbon dioxide is doubled occur at a rate similar to that predicted by the Clausius–Clapeyron relationship. The ratio of global changes in precipitation to global changes in water vapor offers some insight on how readily increased water vapor is converted into precipitation in modeled climate change. This ratio ℇ is introduced in this paper as a gross indicator of the global precipitation efficiency under global warming. The main findings of this paper are threefold. First, increases in the global precipitation track increase atmospheric radiative energy loss and the ratio of precipitation sensitivity to water vapor sensitivity is primarily determined by changes to this atmospheric column energy loss. A reference limit to this ratio is introduced as the rate at which the emission of radiation from the clear-sky atmosphere increases as water vapor increases. It is shown that the derived efficiency based on the simple ratio of precipitation to water vapor sensitivities of models in fact closely matches the sensitivity derived from simple energy balance arguments involving changes to water vapor emission alone. Second, although the rate of increase of clear-sky emission is the dominant factor in the change to the energy balance of the atmosphere, there are two important and offsetting processes that contribute to ℇ in the model simulations studied: One involves a negative feedback through cloud radiative heating that acts to reduce the efficiency; the other is the global reduction in sensible heating that counteracts the effects of the cloud feedback and increases the efficiency. These counteracting feedbacks only apply on the global scale. Third, the negative cloud radiative heating feedback occurs through reductions of cloud amount in the middle troposphere, defined as the layer between 680 and 440 hPa, and by slight global cloud decreases in the lower troposphere. These changes act in a manner to expose the warmer atmosphere below to high clouds, thus resulting in a net warming of the atmospheric column by clouds and a negative feedback on the precipitation. [ABSTRACT FROM AUTHOR]

This paper describes the Comprehensive Pacific Rainfall Database (PACRAIN), which contains daily and monthly precipitation records from the tropical Pacific basin. The database is a collection of observations from a variety of sources, including one, the Schools of the Pacific Rainfall Climate Experiment (SPaRCE), that is unique to PACRAIN. SPaRCE is a cooperative field project and involves schools from various Pacific island and atoll nations. Recent enhancements to the database, including improved quality control, observation and data entry standardization, expansion of the network, increased collaboration with local meteorological directors, and enhanced high-resolution data (e.g., on hourly or minute time scales), are discussed. This paper also outlines some of the internal data and Web-based access specifics of the database. To illustrate the potential usefulness of the data, two examples of research using the PACRAIN database are provided and discussed. The first is an analysis of temporal changes in the extreme event characteristics of daily precipitation across the region. The second is an illustration of how the PACRAIN database can be used to analyze satellite-based precipitation algorithms. [ABSTRACT FROM AUTHOR]

An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge. [ABSTRACT FROM AUTHOR]

Accurately forecasting snowfall is a challenge. In particular, one poorly understood component of snowfall forecasting is determining the snow ratio. The snow ratio is the ratio of snowfall to liquid equivalent and is inversely proportional to the snow density. In a previous paper, an artificial neural network was developed to predict snow ratios probabilistically in three classes: heavy (1:1 < ratio < 9:1), average (9:1 ≤ ratio ≤ 15:1), and light (ratio > 15:1). A Web-based application for the probabilistic prediction of snow ratio in these three classes based on operational forecast model soundings and the neural network is now available. The goal of this paper is to explore the statistical characteristics of the snow ratio to determine how temperature, liquid equivalent, and wind speed can be used to provide additional guidance (quantitative, wherever possible) for forecasting snowfall, especially for extreme values of snow ratio. Snow ratio tends to increase as the low-level (surface to roughly 850 mb) temperature decreases. For example, mean low-level temperatures greater than -2.7°C rarely (less than 5% of the time) produce snow ratios greater than 25:1, whereas mean low-level temperatures less than -10.1°C rarely produce snow ratios less than 10:1. Snow ratio tends to increase strongly as the liquid equivalent decreases, leading to a nomogram for probabilistic forecasting snowfall, given a forecasted value of liquid equivalent. For example, liquid equivalent amounts 2.8–4.1 mm (0.11–0.16 in.) rarely produce snow ratios less than 14:1, and liquid equivalent amounts greater than 11.2 mm (0.44 in.) rarely produce snow ratios greater than 26:1. The surface wind speed plays a minor role by decreasing snow ratio with increasing wind speed. Although previous research has shown simple relationships to determine the snow ratio are difficult to obtain, this note helps to clarify some situations where such relationships are possible. [ABSTRACT FROM AUTHOR]

A currently popular idea is that El Niño–Southern Oscillation (ENSO) can be viewed as a linear deterministic system forced by noise representing processes with periods shorter than ENSO. Also, there is observational evidence to suggest that the Madden–Julian oscillation (MJO) acts to trigger and/or amplify the warm phase of ENSO in this way. The feedback of the slower process, ENSO, to higher-frequency atmospheric phenomena, of which a large part of the variability in the intraseasonal band is due to the MJO, has received little attention. This paper considers the hypothesis that the probability of an El Niño event is modified by high MJO activity and that, in turn, the MJO is regulated by ENSO activity. If this is indeed the case, then viewing ENSO as a low-frequency oscillation forced by additive stochastic noise would not present a complete picture. This paper tests the above hypothesis using a stochastically forced intermediate coupled model by allowing ENSO to directly influence the stochastic forcing. The model response to a variety of stochastic forcing types is found to be sensitive to the type of forcing applied. When the model is operated beyond its intrinsic Hopf bifurcation, its probability distribution function (PDF) is fundamentally altered when the stochastic forcing is changed from additive to multiplicative. The model integration period also influences the shape of the PDF, which is also compared to the PDF derived from observations. It is found that multiplicative stochastic forcing reproduces some measures of the observations better than the additive stochastic forcing. [ABSTRACT FROM AUTHOR]

Precipitation is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment’s impact on precipitation (land use, aerosols, thermal properties) will be increasingly important in ongoing climate diagnostics and prediction, Global Water and Energy Cycle (GWEC) analysis and modeling, weather forecasting, freshwater resource management, urban planning–design, and land–atmosphere–ocean interface processes. These facts are particularly critical if current projections for global urban growth are accurate. The goal of this paper is to provide a concise review of recent (1990–present) studies related to how the urban environment affects precipitation. In addition to providing a synopsis of current work, recent findings are placed in context with historical investigations such as Metropolitan Meteorological Experiment (METROMEX) studies. Both observational and modeling studies of urban-induced rainfall are discussed. Additionally, a discussion of the relative roles of urban dynamic and microphysical (e.g., aerosol) processes is presented. The paper closes with a set of recommendations for what observations and capabilities are needed in the future to advance our understanding of the processes. [ABSTRACT FROM AUTHOR]

Subgrid variability in rainfall distribution has been widely recognized as an important factor to include in the representation of land surface hydrology within climate models. In this paper, using West Africa as a case study, the impact of the subgrid variability in rainfall interception on the modeling of the biosphere--atmosphere system is investigated. According to the authors' results, when neglecting the rainfall spatial variability, even if the impact on the total evapotranspiration is negligible, significant errors may result in the representation of surface hydrological processes and surface energy balance. These findings are consistent with the results of previous studies. However, in this paper, this issue is further explored and it is demonstrated that the extent of the resulting errors is not limited to the land surface processes. They extend to the atmosphere via the low-level cloud feedback to impact solar radiation, boundary layer energy, atmospheric circulation, and the distribution of precipitation. The same errors also propagate into the biosphere through vegetation dynamics and can eventually lead to a significantly different biosphere--atmosphere equilibrium state. This study provides a good example for the need to have physical realism in modeling the subgrid variability and most other details of the complex biosphere-- atmosphere--ocean system. [ABSTRACT FROM AUTHOR]

Subgrid variability in rainfall distribution has been widely recognized as an important factor to include in the representation of land surface hydrology within climate models. In this paper, using West Africa as a case study, the impact of the subgrid variability in rainfall interception on the modeling of the biosphere--atmosphere system is investigated. According to the authors results, when neglecting the rainfall spatial variability, even if the impact on the total evapotranspiration is negligible, significant errors may result in the representation of surface hydrological processes and surface energy balance. These findings are consistent with the results of previous studies. However, in this paper, this issue is further explored and it is demonstrated that the extent of the resulting errors is not limited to the land surface processes. They extend to the atmosphere via the low-level cloud feedback to impact solar radiation, boundary layer energy, atmospheric circulation, and the distribution of precipitation. The same errors also propagate into the biosphere through vegetation dynamics and can eventually lead to a significantly different biosphere--atmosphere equilibrium state. This study provides a good example for the need to have physical realism in modeling the subgrid variability and most other details of the complex biosphere-- atmosphere--ocean system. [ABSTRACT FROM AUTHOR]

The intertropical convergence zone (ITCZ) has been the focus of considerable research in recent years, with much of this work concerned with how the latitude of maximum tropical precipitation responds to natural climate variability and to radiative forcing. The width of the ITCZ, however, has received little attention despite its importance for regional climate and for understanding the general circulation of the atmosphere. This paper investigates the ITCZ width in simulations with an idealized general circulation model over a wide range of climates. The ITCZ, defined as the tropical region where there is time-mean ascent, displays rich behavior as the climate varies, widening with warming in cool climates, narrowing in temperate climates, and maintaining a relatively constant width in hot climates. The mass and energy budgets of the Hadley circulation are used to derive expressions for the area of the ITCZ relative to the area of the neighboring descent region, and for the sensitivity of the ITCZ area to changes in climate. The ITCZ width depends primarily on four quantities: the net energy input to the tropical atmosphere, the advection of moist static energy by the Hadley circulation, the transport of moist static energy by transient eddies, and the gross moist stability. Different processes are important for the ITCZ width in different climates, with changes in gross moist stability generally having a weak influence relative to the other processes. The results are likely to be useful for analyzing the ITCZ width in complex climate models and for understanding past and future climate change in the tropics. [ABSTRACT FROM AUTHOR]

Solar radiation management (SRM) has been proposed as a form of geoengineering to reduce the climate effects of anthropogenic greenhouse gas emissions. Modeling studies have concluded that SRM, through a reduction in total solar irradiance by approximately 2%, roughly compensates for global mean temperature changes from a doubling of carbon dioxide concentrations. This paper examines the impact of SRM on the terrestrial hydrologic cycle using the Community Land Model, version 4, coupled to the Community Atmosphere Model, version 4, with reductions in solar radiation relative to simulations with present-day and elevated CO2 concentrations. There are significant global and regional impacts due to vegetation-climate interactions that are not compensated when reductions in total solar irradiance of 1%, 2%, and 3% are imposed on top of a doubling of present-day CO2 concentrations. Water cycling slows down under SRM, including decreases in global mean precipitation and evapotranspiration. Changes in runoff and soil moisture are spatially and temporally variable, with implications for local water availability. In the tropics, evapotranspiration decreases because of increases in vegetation water use efficiency. In northern midlatitudes, soil moisture increases when evapotranspiration decreases, with some exceptions during boreal summer. Changes in soil evaporation influence water cycling in the southern subtropics, rather than changes in transpiration. The hydrologic response to SRM is nonlinear, with global mean decreases greater than expected. These results imply that SRM may not compensate for higher greenhouse gas concentrations when one considers land-atmosphere interactions. [ABSTRACT FROM AUTHOR]

Based on the analysis of the feature of Asian continent becoming cold in the early 21st century winter under the background of global warming, the Asian Warming Hole (AWH) index is proposed in this paper to measure the intensity during the cold events process. Result shows that the Asian continent is indeed experiencing a cold stage in the early 21st century winter, but it is just in a cold phase and will become warmer in the future. In recent years the activity of the winter cold events has an obvious quasi-four-year cycle, which can be reflected by atmospheric circulation, and AO (Arctic Oscillation) may play a very important role. It is credible that Asian surface temperature will be higher in the coming 3-4 years compared with 2011 winter, signifying that the precipitation may increase correspondingly. [ABSTRACT FROM AUTHOR]

Recent climate change is characterized (among other things) by changes in the frequency of some meteorological phenomena. This paper deals with the long-term changes in various precipitation types, and the connection between their variability and cloud type frequencies, at 11 meteorological stations from Eastern Romania over 1961–2008. These stations were selected with respect to data record completeness for all considered variables (weather phenomena and cloud type). The meteorological variables involved in the present study are: monthly number of days with rain, snowfall, snow showers, rain and snow (sleet), sleet showers and monthly frequency of the Cumulonimbus, Nimbostratus and Stratus clouds. Our results show that all stations present statistically significant decreasing trends in the number of days with rain in the warm period of the year. Changes in the frequency of days for each precipitation type show statistically significant decreasing trends for non-convective (stratiform) precipitation – rain, drizzle, sleet and snowfall –, while the frequencies of rain shower and snow shower (convective precipitation) are increasing. Cloud types show decreasing trends for Nimbostratus and Stratus, and increasing trends for Cumulonimbus. [ABSTRACT FROM AUTHOR]

The assessment of future precipitation variations prevailing in an area is essential for the research regarding climate and climate change. The current paper focuses on 3 selected areas in Greece that present different climatic characteristics due to their location and aims to assess and compare the future variation of annual and seasonal precipitation. Future precipitation data from the ENSEMBLES anthropogenic climate-change (ACC) global simulations and the Climate version of the Local Model (CLM) were obtained and analyzed. The climate simulations were performed for the future periods 2021–2050 and 2071–2100 under the A1B and B1 scenarios. Mann–Kendall test was applied to investigate possible trends. Spatial distribution of precipitation was performed using a combination of dynamic and statistical downscaling techniques and Kriging method within ArcGIS 10.2.1. The results indicated that for both scenarios, reference periods and study areas, precipitation is expected to be critically decreased. Additionally, Mann–Kendall test application showed a strong downward trend for every study area. Furthermore, the decrease in precipitation for the Ardas River basin characterized by the continental climate will be tempered, while in the Sperchios River basin it will be smoother due to the influence of some minor climatic variations in the basins' springs in the highlands where milder conditions occur. Precipitation decrease in the Geropotamos River basin which is characterized by Mediterranean climate will be more vigorous. B1 scenario appeared more optimistic for the Ardas and Sperchios River basins, while in the Geropotamos River basin, both applied scenarios brought similar results, in terms of future precipitation response. [ABSTRACT FROM AUTHOR]

This paper analyzes climatological characteristics and temporal variation of the start and end dates of the rainy season over East Asia using a daily precipitation dataset for the time period 1951-2009. The rainy season is defined by a 5-day rainfall standard, and the regional average time series is constructed by applying the weighted-average method. Results show that the rainy season starts later, ends earlier and lasts shorter from southeast to northwest. In spring, the rainy belt slowly moves northward from 30 to 33°N in China and from 33 to 36°N on the Korean Peninsula and Japanese Islands. From 1951 to 2009, the rainy season generally began earlier in China but later in Korea and Japan, and it ended earlier at latitudes north of 35°N and later south of 35°N. The region-averaged start and end dates of the rainy season in the study region insignificantly advanced, and the duration of the rainy season insignificantly increased from 1951 to 2009. The rainy season duration slightly decreased in the Russian Far East and in northern and western China, and significantly decreased on the Korean Peninsula and the southern Hokkaido Islands, though it obviously increased in the Yangtze--Huaihe River Basins. [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]

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]

This paper investigates climate change signals of Southern Hemisphere (SH) moisture flux simulated by three members of one CMIP3 coupled atmosphere-ocean general circulation model (AOGCM) and a multimodel ensemble of CMIP5 simulations. Generally, flux changes are dominated by increased atmospheric moisture due to temperature increase in the future climate projections. An approach is presented to distinguish between thermodynamical and dynamical influences on moisture flux. Furthermore, a physical interpretation of the transport changes due to dynamics is investigated by decomposing atmospheric waves into different length scales and temporal variations. Signals of moisture flux are compared with fluctuations of geopotential height fields as well as climate signals of extratropical cyclones. Moisture flux variability in the synoptic length scale with temporal variations shorter than 8 days can be assigned to the SH storm track. Climate change signals of these atmospheric waves show a distinctive poleward shift. This can be attributed to the climate change signal of extratropical cyclones. Furthermore, the climate change signal of atmospheric waves can be better understood if strong cyclones that intensify especially on the Eastern Hemisphere are taken into account. Antarctic net precipitation is calculated by means of the vertically integrated moisture flux. Future projections show increasing signals of net precipitation, whereas the dynamical part of net precipitation decreases. This can be understood by means of the low-variability component of synoptic-scale waves, which show a decreasing signal, especially off the coast of West Antarctica. This is shown to be due to changing variability of the Amundsen-Bellingshausen Seas low. [ABSTRACT FROM AUTHOR]

Virtual species are simplified models of real species that codify the response of those species to the climatic conditions. Virtual species have been used to quantify the response of species to climatic changes, to predict potential shifts in species’ geographic ranges and to test the methods used to predict the geographic ranges of species (Ecological Niche Models). Today, there are different methods used to construct virtual species for biogeographic analysis. All of those methods combine partial suitabilities across variables (temperature, precipitation, etc.) to create one multi-variable habitat suitability index. The normal procedure for combining partial suitabilities is to sum or multiply the individual layers. However, this procedure might yield misleading results. In this paper, we run several analyses that indicate that those methods underestimate the role of the limitation factors (factors with unsuitable conditions that should decrease the habitat suitability index to zero). To solve this problem we programmed an algorithm—the Niche Limitation algorithm (NicheLim). NicheLim uses the same philosophy as the BIOCLIM model: species have independent physiological tolerances to the environmental variables. This means that we must first transform each continuous layer into a presence-absence variable, and then combine them. Here, we discuss the current framework for constructing virtual species in biogeography and its main drawbacks. We then explain the improvements of using NicheLim to create our virtual species and test biogeographic hypotheses. [ABSTRACT FROM AUTHOR]

This paper clarifies that the skillful time-scale characteristic of a model is one of the key factors to reproduce the amount precipitation at a specific location with the model. A comparison with data from an operational weather station of the Japan Meteorological Agency in Tokyo (Ote-machi) revealed that a model needed That a model requires 5-km-grid resolution and below to represent the power spectrum of hourly precipitation. A model with a higher resolution is probably needed to simulate hourly precipitation in Tokyo during the summer monsoon season. [ABSTRACT FROM AUTHOR]

Planning adaptation strategies in response to climate change (CC) can be a daunting task, especially in regions such as the Koshi Basin in the Himalayas, where CC impacts are still uncertain. This paper recommends targeting adaptation strategies by focusing on changes in variability between the past and future climates at smaller scales. The Soil and Water Assessment Tool (SWAT) and the Indicators of Hydrologic Alteration (IHA) are used for analysis. The results show: (a) higher maximum precipitation during monsoon and post-monsoon, and lower maximum precipitation during winter; (b) increase in precipitation and flows in the Trans-mountain region during all seasons, except for flows during monsoon; (c) increase in post-monsoon precipitation and routed flow volumes; (d) decrease in precipitation during winter and routed flow volumes in all the regions, except the Trans-mountain region; and (e) increase in frequency of high peak flows and decrease in baseflows.Editor Z.W. Kundzewicz Associate editor S. Kanae; [ABSTRACT FROM AUTHOR]

Climate changes are expected to be greatest in the polar and temperate areas, where predictions point to an increase in freeze-thaw events and changes in precipitation, evaporation, and salinity patterns. These events will therefore affect biological activity of the soil compartment that may result in large impacts in ecosystem functioning and dynamics therein. This concern becomes even more important when considering the presence of contaminants due to intense anthropogenic activity, which may lead to synergistic or antagonistic effects and increase or decrease the impact on natural ecosystems. This paper reviews the effect of physical and chemical stressors on enchytraeids, with special emphasis on Enchytraeus albidus because most relevant studies have involved this species. E. albidus is a freeze-tolerant and euryhaline organism and several studies suggest that the absence of salinity may have important (negative) consequences not only for their freeze tolerance ability but also for their reproduction and capacity to deal with the presence of contaminants, such as metals and fungicides. Single and joint effects of constant freezing or freeze-thaw cycles and surfactants, such as 4-nonylphenol, affected negatively E. albidus freeze tolerance by decreasing the levels of cryoprotectants, membrane fluidity and interfering with cellular energy allocation. Because enchytraeids are of ecological significance in many important habitats along the Artic and cold-temperate environments, a reduction in abundance may result in disturbances of the decomposition processes in soils. The knowledge of the biological, physiological, and biochemical limits of enchytraeids to combined effect of physical and chemical stressors are crucial to provide a scientific basis for improving the setting of safety factors when extrapolating from controlled (and optimal) laboratory conditions to natural soil ecosystems. Therefore, there is a need to expand and evolve experiments that more realistically mimic the situation in the field, where interactions between factors are highly relevant. The synergistic or antagonistic interactions identified in the present review may also represent a stepping stone in the evaluation and possible inclusion of natural factors, like cold and salinity, in standardized enchytraeid test guidelines and consequently in risk assessment of chemicals. [ABSTRACT FROM AUTHOR]

The paper has examined the impact of variations of Atlantic multidecadal oscillation on the change in air temperature during the summer season on the territory of Montenegro. Starting from the fact that in recent years more and more extreme weather events occur, as well as from the intention to comprehensively consider the temperature conditions in the territory of Montenegro, first analysis is of changes in air temperature in 8 parameters, of which 5 climate indices; connections with Atlantic multidecadal oscillation have also been analyzed. To study changes in temperature extreme indexes proposed by the WMO CCL/CLIVAR are used. Research within the listed topics was realized using data from 23 meteorological stations for the period 1951-2010 and the calculations are done for the summer season. The results show that there is increased number of maximum and minimum daily temperatures of warmer value. The impact assessment Atlantic multidecadal oscillation, teleconnection pattern that is quite distant, showed that its variability affects changes in summer temperatures in Montenegro, both in terms of mean values, and the frequency of extreme actions presented by climate indices. [ABSTRACT FROM AUTHOR]

The study of climate changes is most often based on the analysis of time series of temperature and precipitation in urban areas and the increase in the emission of gases having a greenhouse effect. On the other hand, the selection of representative and relevant stations and comprehensive analysis of climate indicators lead to better and more exact assessments on climate changes at the regional level. In order to connect climate changes with agricultural, biological, socio-economic, and tourism databases, the paper deals with the dynamic analysis of changes in thermal component expressed through the values of regional climate indices in four climatological stations with different geographical positions in Serbia. There are significant differences between the two time series data (1961-1990 and 1991-2013) on temperature and humidity, precipitation, insolation, and wind speed. However, after using the climatic indices as a tool for assessing climate changes, the results of the study suggest the relative influence of the thermal component on the change of climate indices, with a slight increase in the index of significance for human activities. Relying on the results of this alternative approach to the study of climate changes, the fact remains that the climate is not fixed but highly variable factor that should be taken into consideration in terms of monitoring, evaluation, and management of the area. [ABSTRACT FROM AUTHOR]

Background and Aims: Much evidence suggests that plant communities on infertile soils are relatively insensitive to increased water deficit caused by increasing temperature and/or decreasing precipitation. However, a multidecadal study of community change in the western USA does not support this conclusion. This paper tests explanations related to macroclimatic differences, overstorey effects on microclimate, variation in soil texture and plant functional traits. Methods: A re-analysis was undertaken of the changes in the multi-decadal study, which concerned forest understorey communities on infertile (serpentine) and fertile soils in an aridifying climate (southern Oregan) from 1949-1951 to 2007-2008. Macroclimatic variables, overstorey cover and soil texture were used as new covariates. As an alternative measure of climate-related change, the community mean value of specific leaf area was used, a functional trait measuring drought tolerance. We investigated whether these revised analyses supported the prediction of lesser sensitivity to climate change in understorey communities on infertile serpentine soils. Key Results: Overstorey cover, but not macroclimate or soil texture, was a significant covariate of community change over time. It strongly buffered understorey temperatures, was correlated with less change and averaged >50% lower on serpentine soils, thereby counteracting the lower climate sensitivity of understorey herbs on these soils. Community mean specific leaf area showed the predicted pattern of less change over time in serpentine than non-serpentine communities. Conclusions: Based on the current balance of evidence, plant communities on infertile serpentine soils are less sensitive to changes in the climatic water balance than communities on more fertile soils. However, this advantage may in some cases be lessened by their sparser overstorey cover. [ABSTRACT FROM AUTHOR]