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

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

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

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

The time of emergence (TOE) of climate change is defined as the time when a new climate state emerges from a prior one. TOE assessment is particularly relevant in West Africa, a region highly threatened by climate change and urgently needing trustworthy climate predictions. In this paper, the TOE of precipitation change in West Africa is assessed for the first time, by analyzing 6 precipitation metrics (cumulated precipitation, number of wet and very wet days, onset and length of the rainy season) computed from the output of 29 state-of-the-art climate models. In West Sahel, climate conditions characterized by reduced occurrence of wet days are likely to emerge before 2036, leading to the possible emergence of a dryer climate in 2028–2052. In East Sahel, a wetter precipitation regime characterized by increased occurrence of very wet days is likely to emerge before 2054. Results do not provide a clear indication about a possible climate shift in the onset and length of the rainy season. Although uncertainty in climate model future projections still limits the robust determination of TOE locally, this study provides reliable time constraints to the expected climate shift in West Africa at the sub-regional scale, supporting adaptation measures to the future change in the precipitation regime. [ABSTRACT FROM AUTHOR]

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

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

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

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

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

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

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Niño to Yangtze River basin rainfall meant that the strong El Niño in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements. [ABSTRACT FROM AUTHOR]

Summer precipitation anomalies over eastern China are characterized spatially by meridionally banded structures fluctuating on interannual and interdecadal timescales, leading to regional droughts and floods. In addition to long-term trends, how these patterns may change under global warming has important implications for agricultural planning and water resources over this densely populated area. Using the latest Hadley Centre climate model, HadGEM3-GC2, this paper investigates the potential response of summer precipitation patterns over this region, by comparing the leading modes between a 4×CO2 simulation and the model’s pre-industrial control simulation. Empirical Orthogonal Function (EOF) analyses show that the first two leading modes account for about 20% of summer rainfall variability. EOF1 is a monopole mode associated with the developing phase of ENSO events and EOF2 is a dipole mode associated with the decaying phase of ENSO. Under 4×CO2 forcing, the dipole mode with a south-north orientation becomes dominant because of a strengthened influence from excessive warming of the Indian Ocean. On interdecadal time scales, the first EOF looks very different from the control simulation, showing a dipole mode of east-west contrast with enhanced influence from high latitudes. [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]

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

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

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

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

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

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

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

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]

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

Earth's climate history is traced through the long-term covariance between the isotopic (δ18O) composition of archived meteoric waters (groundwater, ice cores) with air temperature (T) and amount of precipitation (P). To assess recent multi-decadal climatic changes, we analysed δ18O, T and P, and the relationships between these parameters at 20 stations having 60 years of continuous monthly isotopic records. Using nonparametric regressions and time series modelling we found significant linear and non-linear relationships for δ18O with T and P and showed that the δ18O dependency on these two parameters varied over decadal scales, thereby revealing complex relationships related to recycled moisture, large-scale convective processes and atmospheric-oceanic oscillations. Due to multiple factors controlling the δ18O composition of precipitation including P and T effects, we found that time-varying relationships between δ18O in precipitation P and T were better explained using the non-linear regressions. Our results affirmed that δ18O distributions in global precipitation are integrative indicators of climate dynamics whose patterns can be applied to better understand region-specific climatic changes in the present, past, and future. [ABSTRACT FROM AUTHOR]

The impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies. [ABSTRACT FROM AUTHOR]

Little is known about the diversity and distribution patterns of moths along latitudinal gradients. We studied macro-moths in Mongolia along an 860 km latitudinal climatic gradient to gain knowledge on community composition, alpha, beta, and gamma diversity as well as underlying factors, which can be used as baseline information for further studies related to climate change. We identified 236 species of moths of ten families. Our study shows that the diversity of moths increased with the latitude, i.e., low species richness in the south and higher richness in the north. Moth community composition changed along the gradient, and we revealed a breakpoint of beta diversity that divided grassland and desert communities. In the desert, beta diversity was driven by species loss (i.e., nestedness), and few tolerant species existed with high abundance. In contrast, in the grassland, beta diversity was driven by species replacement with more unique species, (i.e., species which occurred only in one site). We found the lowest species diversity in the transitional zones dominated by few generalist species such as Agrotis ripae and Anarta trifolii. Low precipitation and an increasing number of grazing goats are drivers of species loss. We suggest different conservation strategies regarding the contrasting patterns of beta diversity in desert and grassland. [ABSTRACT FROM AUTHOR]

The Galapagos Islands are a global hotspot of environmental change. However, despite their potentially major repercussions, little is known about current and expected changes in regional terrestrial climate variables and sea surface temperatures (SST). Here, by analysing existing meteorological observations and secondary datasets, we find that the Islands have warmed by about 0.6 °C since the early 1980s, while at the same time becoming drier. In fact, the onset of the wet season is currently delayed 20 days. This drying trend may reverse, however, given that future climate projections for the region suggest mean annual precipitation may increase between 20 and 70%. This would also be accompanied by more extreme wet and hot conditions. Further, we find that regional SST has increased by 1.2 °C over the last two decades. These changes will, in turn, translate into deterioration of marine ecosystems and coral, proliferation of invasive species, and damages to human water, food, and infrastructure systems. Future projections, however, may be overestimated due to the poor capacity of climatic models to capture Eastern-Pacific ENSO dynamics. Our findings emphasize the need to design resilient climate adaptation policies that will remain robust in the face of a wide range of uncertain and changing climatic futures. [ABSTRACT FROM AUTHOR]

Accurate long-term global precipitation estimates, especially for heavy precipitation rates, at fine spatial and temporal resolutions is vital for a wide variety of climatological studies. Most of the available operational precipitation estimation datasets provide either high spatial resolution with short-term duration estimates or lower spatial resolution with long-term duration estimates. Furthermore, previous research has stressed that most of the available satellite-based precipitation products show poor performance for capturing extreme events at high temporal resolution. Therefore, there is a need for a precipitation product that reliably detects heavy precipitation rates with fine spatiotemporal resolution and a longer period of record. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR) is designed to address these limitations. This dataset provides precipitation estimates at 0.04° spatial and 3-hourly temporal resolutions from 1983 to present over the global domain of 60°S to 60°N. Evaluations of PERSIANN-CCS-CDR and PERSIANN-CDR against gauge and radar observations show the better performance of PERSIANN-CCS-CDR in representing the spatiotemporal resolution, magnitude, and spatial distribution patterns of precipitation, especially for extreme events. Measurement(s) volume of hydrological precipitation • spatial resolution • spatial coverage • temporal resolution • temporal coverage Technology Type(s) digital curation Sample Characteristic - Location 60°S - 60°N Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14656452 [ABSTRACT FROM AUTHOR]

In the past quarter-century, Eastern North Carolina (ENC) experienced several devastating tropical cyclones that led to widespread flooding and damage. Historical climate records reflect an increasing trend in the frequency and intensity of extreme rainfall events across the eastern U.S., which is projected to continue to increase throughout the twenty-first century. Potential changes to extreme rainfall across ENC are explored and quantified for 2025–2100 for three tropical cyclones using an approach based on relative changes in future extreme rainfall frequencies (return periods) from dynamically downscaled projections. Maximum rainfall intensities at '2100' could increase locally by 168%, with widespread regional increases in total rainfall up to 44%. Although these magnitudes exceed the consensus in the literature, the values here are comparable to the most extreme rainfall events observed in the U.S. during the early twenty-first century, which suggests that the intensity of projected future events is already a present-day reality. [ABSTRACT FROM AUTHOR]

Climate simulations often need to be adjusted (i.e., corrected) before any climate change impacts studies. However usual bias correction approaches do not differentiate the bias from the different uncertainties of the climate simulations: scenario uncertainty, model uncertainty and internal variability. In particular, in the case of a multi-run ensemble of simulations (i.e., multiple runs of one model), correcting, as usual, each member separately, would mix up the model biases with its internal variability. In this study, two ensemble bias correction approaches preserving the internal variability of the initial ensemble are proposed. These "Ensemble bias correction" (EnsBC) approaches are assessed and compared to the approach where each ensemble member is corrected separately, using precipitation and temperature series at two locations in North America from a multi-member regional climate ensemble. The preservation of the internal variability is assessed in terms of monthly mean and hourly quantiles. Besides, the preservation of the internal variability in a changing climate is evaluated. Results show that, contrary to the usual approach, the proposed ensemble bias correction approaches adequately preserve the internal variability even in changing climate. Moreover, the climate change signal given by the original ensemble is also conserved by both approaches. [ABSTRACT FROM AUTHOR]

Assessments of ecosystem service and function losses of wetlandscapes (i.e., wetlands and their hydrological catchments) suffer from knowledge gaps regarding impacts of ongoing hydro-climatic change. This study investigates hydro-climatic changes during 1976–2015 in 25 wetlandscapes distributed across the world's tropical, arid, temperate and cold climate zones. Results show that the wetlandscapes were subject to precipitation (P) and temperature (T) changes consistent with mean changes over the world's land area. However, arid and cold wetlandscapes experienced higher T increases than their respective climate zone. Also, average P decreased in arid and cold wetlandscapes, contrarily to P of arid and cold climate zones, suggesting that these wetlandscapes are located in regions of elevated climate pressures. For most wetlandscapes with available runoff (R) data, the decreases were larger in R than in P, which was attributed to aggravation of climate change impacts by enhanced evapotranspiration losses, e.g. caused by land-use changes. [ABSTRACT FROM AUTHOR]

The hydrological cycle is expected to intensify with global warming, which likely increases the intensity of extreme precipitation events and the risk of flooding. The changes, however, often differ from the theorized expectation of increases in water‐holding capacity of the atmosphere in the warmer conditions, especially when water availability is limited. Here, the relationships of changes in extreme precipitation and flood intensities for the end of the twenty-first century with spatial and seasonal water availability are quantified. Results show an intensification of extreme precipitation and flood events over all climate regions which increases as water availability increases from wet to dry regions. Similarly, there is an increase in the intensification of extreme precipitation and flood with the seasonal cycle of water availability. The connection between extreme precipitation and flood intensity changes and spatial and seasonal water availability becomes stronger as events become less extreme. [ABSTRACT FROM AUTHOR]

The Hydrometeorological Sandbox - École de technologie supérieure (HYSETS) is a rich, comprehensive and large-scale database for hydrological modelling covering 14425 watersheds in North America. The database includes data covering the period 1950–2018 depending on the type and source of data. The data include a wide array of hydrometeorological data required to perform hydrological and climate change impact studies: (1) watershed properties including boundaries, area, elevation slope, land use and other physiographic information; (2) hydrometric gauging station discharge time-series; (3) precipitation, maximum and minimum daily air temperature time-series from weather station records and from (4) the SCDNA infilled gauge meteorological dataset; (5) the NRCan and Livneh gridded interpolated products' meteorological data; (6) ERA5 and ERA5-Land reanalysis data; and (7) the SNODAS and ERA5-Land snow water equivalent estimates. All data have been processed and averaged at the watershed scale, and provides a solid basis for hydrological modelling, climate change impact studies, model calibration assessment, regionalization method evaluation and essentially any study requiring access to large amounts of spatiotemporally varied hydrometeorological data. Measurement(s) elevation • temperature • hydrological precipitation process • Fluid Discharge • climate • physiographic feature Technology Type(s) digital curation Sample Characteristic - Environment watershed Sample Characteristic - Location North America Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12600281 [ABSTRACT FROM AUTHOR]

Biotic interactions play an important role in species distribution models, whose ignorance may cause an overestimation of species' potential distributions. Species of the family Orchidaceae are almost totally dependent on mycorrhizal symbionts and pollinators, with sexually deceptive orchids being often highly specialized, and thus the interactions with their pollinators are expected to strongly affect distribution predictions. We used Maxent algorithm to explore the extent of current and future habitat suitability for two Greek endemic sexually deceptive orchids (Ophrys argolica and Ophrys delphinensis) in relation to the potential distribution of their unique pollinator (Anthophora plagiata). Twelve climate change scenarios were used to predict future distributions. Results indicated that the most important factors determining potential distribution were precipitation seasonality for O. argolica and geological substrate for O. delphinensis. The current potential distribution of the two orchids was almost of the same extent but spatially different, without accounting for their interaction with A. plagiata. When the interaction was included in the models, their potentially suitable area decreased for both species. Under future climatic conditions, the effects of the orchid-pollinator interaction were more intense. Specifically, O. argolica was restricted in specific areas of southern Greece, whereas O. delphinensis was expected to become extinct. Our findings highlighted the significant role of plant–pollinator interactions in species distribution models. Failing to study such interactions might expose plant species to serious conservation issues. [ABSTRACT FROM AUTHOR]

The sequence of wildfires followed by debris flows, frequently affects southern California, reflecting its drought-heavy precipitation climate bipolarity. Organic debris from incomplete burning is lighter than inorganic matter, and partially inviscid. Hence lower rainfall totals can trigger downslope motion than typically required by the underlying clasts of loose inorganic granular material. After advection downslope, the pebble-laden organic debris has a higher capacity for rilling; a positive feedback process. A mechanism is proposed whereby boulders are 'rafted' by organic debris. This coordinated movement of boulders greatly enhances the debris flow erosion capacity. This climate change sensitive debris flow enhancing mechanism, through organic–inorganic granular material interaction, is supported by observations and the numerical simulations. Using a model explicitly parameterizing erosion processes, including runoff entrainment, rilling incision, and bank collapse, the lifecycle of the Montecito debris flow of January 9, 2018 is simulated, providing quantitative estimates of mass conveyed and debris sorting at the terminus. Peak rafting speeds are ~ 12.9 m/s at ~ 300 m asl. Total boulder (effective diameter > 25 cm) volume involved for the Ysidro Creek area alone is ~ 5 × 104 m3, scattered between the region 50–260 m asl. Debris flows are highly repeatable and locations prone to debris flows are identified and their likelihood of realization estimated. [ABSTRACT FROM AUTHOR]

Both seasonal and annual mean precipitation and evaporation influence patterns of water availability impacting society and ecosystems. Existing global climate studies rarely consider such patterns from non-parametric statistical standpoint. Here, we employ a non-parametric analysis framework to analyze seasonal hydroclimatic regimes by classifying global land regions into nine regimes using late 20th century precipitation means and seasonality. These regimes are used to assess implications for water availability due to concomitant changes in mean and seasonal precipitation and evaporation changes using CMIP5 model future climate projections. Out of 9 regimes, 4 show increased precipitation variation, while 5 show decreased evaporation variation coupled with increasing mean precipitation and evaporation. Increases in projected seasonal precipitation variation in already highly variable precipitation regimes gives rise to a pattern of "seasonally variable regimes becoming more variable". Regimes with low seasonality in precipitation, instead, experience increased wet season precipitation. Adequate water availability is key to human and ecosystem sustainability. Here, the authors show that seasonally variable regimes become more variable, and the combined influence of seasonality and magnitude of climate variables will affect future water availability. [ABSTRACT FROM AUTHOR]

Earth System Models (ESMs) are the state of the art for projecting the effects of climate change. However, longstanding uncertainties in their ability to simulate regional and local precipitation extremes and related processes inhibit decision making. Existing state-of-the art approaches for uncertainty quantification use Bayesian methods to weight ESMs based on a balance of historical skills and future consensus. Here we propose an empirical Bayesian model that extends an existing skill and consensus based weighting framework and examine the hypothesis that nontrivial, physics-guided measures of ESM skill can help produce reliable probabilistic characterization of climate extremes. Specifically, the model leverages knowledge of physical relationships between temperature, atmospheric moisture capacity, and extreme precipitation intensity to iteratively weight and combine ESMs and estimate probability distributions of return levels. Out-of-sample validation suggests that the proposed Bayesian method, which incorporates physics-guidance, has the potential to derive reliable precipitation projections, although caveats remain and the gain is not uniform across all cases. [ABSTRACT FROM AUTHOR]

An increasing population in conjunction with a changing climate necessitates a detailed understanding of water abundance at multiple spatial and temporal scales. Remote sensing has provided massive data volumes to track fluctuations in water quantity, yet contextualizing water abundance with other local, regional, and global trends remains challenging by often requiring large computational resources to combine multiple data sources into analytically-friendly formats. To bridge this gap and facilitate future freshwater research opportunities, we harmonized existing global datasets to create the Global Lake area, Climate, and Population (GLCP) dataset. The GLCP is a compilation of lake surface area for 1.42 + million lakes and reservoirs of at least 10 ha in size from 1995 to 2015 with co-located basin-level temperature, precipitation, and population data. The GLCP was created with FAIR (findable, accessible, interoperable, reusable) data principles in mind and retains unique identifiers from parent datasets to expedite interoperability. The GLCP offers critical data for basic and applied investigations of lake surface area and water quantity at local, regional, and global scales. Measurement(s) area of open water • temperature of air • volume of hydrological precipitation • population Technology Type(s) digital curation Factor Type(s) year • geographic location Sample Characteristic - Environment lake Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12328214 [ABSTRACT FROM AUTHOR]

Substantial palsa degradation has occurred in Fennoscandia, which is considered to be driven by global climate change. Deeper understanding of the role of different climatic drivers on palsa decay, however, is lacking. We use meteorological data and aerial photographs from 1955 to 2016 to statistically identify the most important climatic drivers affecting changes in lateral-temporal palsa decay rates in the largest coherent palsa complex in Sweden, Vissátvuopmi. We show that wetter, warmer and shorter winters are the main causes of large and rapid changes in lateral-palsa extent since the mid-1950s. By analyzing meteorological data from the 1880s to present, we show that average annual temperature conditions have been unfavourable for palsas for more than a century and average annual precipitation conditions have been unfavourable since the 1940s. The decay rates have likely been amplified over the past 50-60 years, and in particular over the most recent decades, due to the combined effect of adverse air temperature and precipitation conditions. Palsa loss is expected to continue, most likely at a higher rate than today, with serious ecological impacts as a consequence. [ABSTRACT FROM AUTHOR]

The history of climate is crucially important for any part of the world to understand the nature of climate change. In this context, precipitation reconstruction is still lacking in northern Kazakhstan. The purpose of this study is to present a reconstruction for the total precipitation of October of the previous year to July of the current year in northern Kazakhstan. Pinus sylvestris L. (Scots pine) forests in Burabai Region are quite important to collect samples to study the climate history. A regional chronology, covering the years of 1702–2014 of Pinus sylvestris constructed by using 289/466 trees/cores was used in the reconstruction. The gridded climate data for the years of 1950–2014 were used in the calibration and verification process. High and significant correlations were obtained between tree-ring widths and October to July precipitation in Burabai Region. Based on this significant relationship, reconstruction was performed for the years of 1744–2014. Adjusted R2, F-value, sign test, and r value were found as 0.38, 39.7 (P ≤ 0.001), 47+/17, and 0.62 for reconstruction, respectively. The reconstruction showed that 43 dry and 42 wet years occurred during the years of 1744–2014. Only a one-time four-year duration of the wet period was determined covering the years 1978–1981. However, three of six very dry years occurred after the 1950s. As a conclusion, extremity in recent decades is getting an increase in Burabai region. [ABSTRACT FROM AUTHOR]

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

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

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

Size-resolved aerosol samples were collected in Metro Manila between July 2018 and October 2019. Two Micro-Orifice Uniform Deposit Impactors (MOUDI) were deployed at Manila Observatory in Quezon City, Metro Manila with samples collected on a weekly basis for water-soluble speciation and mass quantification. Additional sets were collected for gravimetric and black carbon analysis, including during special events such as holidays. The unique aspect of the presented data is a year-long record with weekly frequency of size-resolved aerosol composition in a highly populated megacity where there is a lack of measurements. The data are suitable for research to understand the sources, evolution, and fate of atmospheric aerosols, as well as studies focusing on phenomena such as aerosol-cloud-precipitation-meteorology interactions, regional climate, boundary layer processes, and health effects. The dataset can be used to initialize, validate, and/or improve models and remote sensing algorithms. Measurement(s) ion concentration • concentration of water-soluble element • particulate matter • size distribution • mass concentration of black carbon Technology Type(s) ion chromatography • inductively coupled plasma mass spectrometry • Micro-Orifice Uniform Deposit Impactors (MOUDI) • Multi-wavelength Absorption Black Carbon Instrument (MABI) • gravimetric analysis Factor Type(s) geographic location Sample Characteristic - Location National Capital Region Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12037197 [ABSTRACT FROM AUTHOR]

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

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

Climatic factors can influence the establishment and growth of wood species, but little is known about the effect of these factors on monodominant communities in wetlands. Therefore, we asked how climatic factors, such as ENSO (El Niño-Southern Oscillation), precipitation and flooding, influence growth and establishment of the dominant species Erythrina fusca in the Pantanal. We determined the age of sampled individuals, the age of the population and evaluated the effects of climate on tree growth. We obtained samples for dendrochronological analyses using destructive (seven individuals) and non-destructive methods. We cross-dated and built a chronology, correlating results with climatic factors. We sampled 0.6 ha of the population and separated individuals into diameter classes to determine age based on diameter/age ratio obtained through dendrochronological analyses. We obtained a chronology with individuals up to 34 years old, while in the population sample, the oldest individual was 54 years old. The factors that influenced growth during the study period were precipitation (positive correlation) and El Niño (negative correlation). E. fusca individuals seem to grow more during the period of highest precipitation, and El Niño events reduce precipitation in the Pantanal, resulting in a decrease in the growth of E. fusca individuals. We detected a decrease of young individuals in the last nine years, which seems to be related to the decrease in minimum flood levels. This indicates a future decline in the number of individuals. These results allow us to propose measures to protect these monodominant formations, which mainly involve avoiding further anthropic activities, that could reduce flooding levels. [ABSTRACT FROM AUTHOR]

Projections of climate change are available at coarse scales (70–400 km). But agricultural and species models typically require finer scale climate data to model climate change impacts. Here, we present a global database of future climates developed by applying the delta method –a method for climate model bias correction. We performed a technical evaluation of the bias-correction method using a 'perfect sibling' framework and show that it reduces climate model bias by 50–70%. The data include monthly maximum and minimum temperatures and monthly total precipitation, and a set of bioclimatic indices, and can be used for assessing impacts of climate change on agriculture and biodiversity. The data are publicly available in the World Data Center for Climate (WDCC; cera-www.dkrz.de), as well as in the CCAFS-Climate data portal (http://ccafs-climate.org). The database has been used up to date in more than 350 studies of ecosystem and agricultural impact assessment. Measurement(s) climate change • precipitation process • precipitation amount • consecutive dry months index per time period • temperature of air Technology Type(s) computational modeling technique Factor Type(s) spatial region Sample Characteristic - Environment climate system Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11353664 [ABSTRACT FROM AUTHOR]

The present work aims to quantify the impact of climate change (CC) on the grain yields of irrigated cereals and their water requirements in the Tensift region of Morocco. The Med-CORDEX (MEDiterranean COordinated Regional Climate Downscaling EXperiment) ensemble runs under scenarios RCP4.5 (Representative Concentration Pathway) and RCP8.5 are first evaluated and disaggregated using the quantile-quantile approach. The impact of CC on the duration of the main wheat phenological stages based on the degree-day approach is then analyzed. The results show that the rise in air temperature causes a shortening of the development cycle of up to 50 days. The impacts of rising temperature and changes in precipitation on wheat yields are next evaluated, based on the AquaCrop model, both with and without taking into account the fertilizing effect of CO2. As expected, optimal wheat yields will decrease on the order of 7 to 30% if CO2 concentration rise is not considered. The fertilizing effect of CO2 can counterbalance yield losses, since optimal yields could increase by 7% and 13% respectively at mid-century for the RCP4.5 and RCP8.5 scenarios. Finally, water requirements are expected to decrease by 13 to 42%, mainly in response to the shortening of the cycle. This decrease is associated with a change in temporal patterns, with the requirement peak coming two months earlier than under current conditions. [ABSTRACT FROM AUTHOR]