[1] We conducted two experiments, one long term with a 2°C increase (Experiment 1) and one short term with a 4.4°C increase (Experiment 2), to investigate main and interactive effects of warming, clipping, and doubled precipitation on soil CO2 efflux and its temperature sensitivity in a U.S. tallgrass prairie. On average, warming increased soil CO2 efflux by 13.0% (p < 0.01) in Experiment 1, by 22.9% (p < 0.0001) in Experiment 2, and by 26.6% (p < 0.0001) in the transient study of Experiment 2. Doubled precipitation resulted in an increase of 9.0% (p < 0.05) in soil CO2 efflux in Experiment 2. Yearly clipping did not significantly affect soil CO2 efflux (p = 0.66) in Experiment 1, while clipping decreased soil CO2 efflux by 16.1% (p < 0.05) in the transient study. Temperature sensitivity of soil CO2 efflux significantly decreased from an apparent Q10 value of 2.51 in unwarmed plots to 2.02 in warmed plots without extra precipitation and from 2.57 to 2.23 with doubled precipitation in Experiment 2. No significant interactive effects among the experimental factors were statistically found on soil CO2 efflux or their temperature sensitivities except for the warming × clipping interaction (p < 0.05) in the transient study. Our observed minor interactive effects relative to main ones suggest that results from single-factor experiments are useful in informing us of potential responses of soil CO2 efflux to multifactor global change, at least in our ecosystem.

[1] Analysis of the duration of wet spells (consequent days with significant precipitation) in Europe and associated precipitation is performed over the period 1950–2008 using daily rain gauge data. During the last 60 years wet periods have become longer over most of Europe by about 15– 20%. The lengthening of wet periods was not caused by an increase of the total number of wet days. Becoming longer, wet periods in Europe are now characterized by more abundant precipitation. Heavy precipitation events during the last two decades have become much more frequently associated with longer wet spells and intensified in com‐ parison with 1950s and 1960s. The changes in the distri‐ bution of temporal characteristics of precipitation towards longer events and higher intensities should have a significant impact on the terrestrial hydrologic cycle including sub‐ surface hydrodynamics, surface runoff and European flooding. Citation: Zolina, O., C. Simmer, S. K. Gulev, and S. Kollet (2010), Changing structure of European precipitation: Longer wet periods leading to more abundant rainfalls, Geophys. Res. Lett., 37, L06704, doi:10.1029/2010GL042468.

We used a daily time step, multi-layer simulation model of soil water dynamics to integrate effects of soils, vegetation, and climate on the recruitment of Bouteloua eriopoda (black grama), the historically dominant grass in the Chihuahuan Desert. We simulated landscapes at the Jornada ARS-LTER site with heterogeneous soil properties to compare: (1) a grass-dominated landscape in 1858 with the current shrub-dominated landscape (i.e., a change in vegetation structure), and (2) the current shrub-dominated landscape with future landscapes over a range of climate scenarios associated with the North American monsoon (i.e., a change in climate). A historic shift from high productivity grasslands to low productivity shrublands decreased simulated recruitment for most of the site; the amount of reduction depended on location-specific soil properties and changes in production. In some cases, soil properties interacted with vegetation structure: soils high in clay content maintained high recruitment even with a decrease in production. Wetter summers would increase recruitment in all vegetation types. Drier summers below 25% of current rainfall would decrease recruitment to negligible values (<0.03) throughout the landscape. We used our results to identify the conditions where recruitment of B. eriopoda is possible with and without significant modifications to soil and vegetation.

We defined the threshold of extreme precipitation using detrended fluctuation analysis based on daily precipitation during 1955–2013 in Kuandian County, Liaoning Province. Three-dimensional copulas were introduced to analyze the characteristics of four extreme precipitation factors: the annual extreme precipitation day, extreme precipitation amount, annual average extreme precipitation intensity, and extreme precipitation rate of contribution. The results show that (1) the threshold is 95.0 mm, extreme precipitation events generally occur 1–2 times a year, the average extreme precipitation intensity is 100–150 mm, and the extreme precipitation amount is 100–270 mm accounting for 10 to 37 % of annual precipitation. (2) The generalized extreme value distribution, extreme value distribution, and generalized Pareto distribution are suitable for fitting the distribution function for each element of extreme precipitation. The Ali-Mikhail-Haq (AMH) copula function reflects the joint characteristics of extreme precipitation factors. (3) The return period of the three types has significant synchronicity, and the joint return period and co-occurrence return period have long delay when the return period of the single factor is long. This reflects the inalienability of extreme precipitation factors. The co-occurrence return period is longer than that of the single factor and joint return period. (4) The single factor fitting only reflects single factor information of extreme precipitation but is unrelated to the relationship between factors. Three-dimensional copulas represent the internal information of extreme precipitation factors and are closer to the actual. The copula function is potentially widely applicable for the multiple factors of extreme precipitation.

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447-463. DOI: 10.1111/j.1752-1688.2011.00540.x Abstract:  Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain-on-snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change-points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.

Variations and trends in extreme climate events have only recently received much attention. Exponentially increasing economic losses, coupled with an increase in deaths due to these events, have focused attention on the possibility that these events are increasing in frequency. One of the major problems in examining the climate record for changes in extremes is a lack of high-quality, long-term data. In some areas of the world increases in extreme events are apparent, while in others there appears to be a decline. Based on this information increased ability to monitor and detect multidecadal variations and trends is critical to begin to detect any observed changes and understand their origins.

Using fine-scale climate process, we investigated the relationship between extreme surface water runoff and property damages caused by flood in the U.S. Special attention was paid to disentangle effects of extreme weather and social wealth accumulation. We find it is still premature to claim that extreme weather events becomes more destructive due to anthropological climate change, if take into account the increasing values exposed to natural hazards.

To reduce the dependence on fossil fuel and imported energy resources, Taiwan has ever-increasing needs of renewable energy. With the rapid development of the technologies of wave energy converter, the wave energy source will be able to meet parts the demand. The Energy Research Laboratories of the Industrial Technology Research Institute, Taiwan (2005), based on the statistic of one-year wave data, stated that the mean wave energy at the northeast coast of Taiwan reaches 11.56 kW/m, giving it the potential of wave power utilization. However, one of the major obstacles with the wave energy utilization is lack of long-term ocean wave measurements. The long-term variations in wave parameters impose changes in wave energy converter outputs. Lack of long-term data makes it difficult to assess the cost-benefit of wave energy conversion projects for the policy and decision makers.

Ths report addresses the following two questions: 1) What are the loads (flux) of nutrients transported from the Mississippi-Atchafalaya River Basin to the Gulf of Mexico, and where do they come from within the basin? 2) What is the relative importance of specific human activities, such as agriculture, point-source discharges, and atmospheric deposition in contributing to these loads? These questions were addressed by first estimating the flux of nutrients from the Mississippi-Atchafalaya River Basin and about 50 interior basins in the Mississippi River system using measured historical streamflow and water quality data. Annual nutrient inputs and outputs to each basin were estimated using data from the National Agricultural Statistics Service, National Atmospheric Deposition Program, and point-source data provided by the USEPA. Next, a nitrogen mass balance was developed using agricultural statistics, estimates of nutrient cycling in agricultural systems, and a geographic information system. Finally, multiple regression models were developed to estimate the relative contributions of the major input sources to the flux of nitrogen and phosphorus to the Gulf of Mexico.

This paper provides an overview of the key processes that generate floods in Canada, and a context for the other papers in this special issue – papers that provide detailed examinations of specific floods and flood-generating processes. The historical context of flooding in Canada is outlined, followed by a summary of regional aspects of floods in Canada and descriptions of the processes that generate floods in these regions, including floods generated by snowmelt, rain-on-snow and rainfall. Some flood processes that are particularly relevant, or which have been less well studied in Canada, are described: groundwater, storm surges, ice-jams and urban flooding. The issue of climate change-related trends in floods in Canada is examined, and suggested research needs regarding flood-generating processes are identified.

This is the fourth in a series of four articles on historical and projected climate extremes in the United States. Here, we examine the results of historical and future climate model experiments from the phase 5 of the Coupled Model Intercomparison Project (CMIP5) based on work presented at the World Climate Research Programme (WCRP) Workshop on CMIP5 Climate Model Analyses held in March 2012. Our analyses assess the ability of CMIP5 models to capture observed trends, and we also evaluate the projected future changes in extreme events over the contiguous Unites States. Consistent with the previous articles, here we focus on model-simulated historical trends and projections for temperature extremes, heavy precipitation, large-scale drivers of precipitation variability and drought, and extratropical storms. Comparing new CMIP5 model results with earlier CMIP3 simulations shows that in general CMIP5 simulations give similar patterns and magnitudes of future temperature and precipitation extremes in the Unite...

There has been a growing interest in whether established ecogeographical patterns, such as Bergmann's rule, explain changes in animal morphology related to climate change. Bergmann's rule has often been used to predict that body size will decrease as the climate warms, but the predictions about how body size will change are critically dependent on the mechanistic explanation behind the rule. To investigate change in avian body size in western North America, we used two long‐term banding data sets from central California, USA; the data spanned 40 years (1971–2010) at one site and 27 years (1983–2009) at the other. We found that wing length of birds captured at both sites has been steadily increasing at a rate of 0.024–0.084% per year. Although changes in body mass were not always significant, when they were, the trend was positive and the magnitudes of significant trends were similar to those for wing length (0.040–0.112% per year). There was no clear difference between the rates of change of long‐distance vs. short‐distance migrants or between birds that bred locally compared to those that bred to the north of the sites. Previous studies from other regions of the world have documented decreases in avian body size and have used Bergmann's rule and increases in mean temperature to explain these shifts. Because our results do not support this pattern, we propose that rather than responding to increasing mean temperatures, avian body size in central California may be influenced by changing climatic variability or changes in primary productivity. More information on regional variation in the rates of avian body size change will be needed to test these hypotheses.

The main objective of this study was to analyse the trends in 20 annual extreme indices of temperature and precipitation for Utah, USA. The analyses were conducted for 28 meteorological stations, during the period from 1930 to 2006, characterized by a long-term and high-quality dataset. The software used to process the data was the RClimdex 1.0. The analyses of extreme temperature indices have identified an increase in air temperature in Utah during the last century. Meanwhile, the analyses of precipitation indices showed a large variation throughout the studied area and time period, and, in general, with few statistically significant trends. Thus, it was not possible to conclude that significant changes in precipitation have occurred in this region over the last century. Copyright © 2010 Royal Meteorological Society

The first author's research was partially supported by National Science foundation CMG reserach grants DMS-0724704, ATM-0620624, and by Award Number KUS-CI-016-04 made by King Abdullah University of Science and Technology (KAUST). The second author's research was supported by National Science foundation CMG reserach grants ATM-0620624. They gratefully acknowledge two referees for their constructive suggestions that led to significant improvement of the paper.

The development of a hybrid clustering technique based on the geographic proximity of observing stations and some application-driven measure of statistical similarity (in this case rank correlation) is described. The procedure is then applied to temperature and precipitation data from the United States (US) Historical Climatology Network. The resulting station groups provide some insight into the number of observation stations that are necessary to monitor adequately the climate of the US. Based on temperature data alone, a 287-station subset of the original 1145 sites would be adequate to account for 80% of the spatial variability in seasonal temperature across the US. Geographically the distribution of these stations would be relatively sparse in the centre of the country with higher station density along the East Coast and from the Rocky Mountains to the West Coast. Generally, the temperature clusters match the existing US climate divisions to some extent. To monitor adequately the spatial variability of precipitation, a network of similar size could be used. However, such a network would only account for 65% of the spatial variability in precipitation. In this case, fairly uniform station density is indicated across the country with the highest station density in Florida and the Dakotas. A similar number of stations, but with slightly different geographic groupings would be adequate to monitor precipitation and temperature simultaneously. Copyright © 2001 Royal Meteorological Society

The design of stormwater infrastructure is based on an underlying assumption that the probability distribution of precipitation extremes is statistically stationary. This assumption is called into question by climate change, resulting in uncertainty about the future performance of systems constructed under this paradigm. We therefore examined both historical precipitation records and simulations of future rainfall to evaluate past and prospective changes in the probability distributions of precipitation extremes across Washington State. Our historical analyses were based on hourly precipitation records for the time period 1949–2007 from weather stations in and near the state’s three major metropolitan areas: the Puget Sound region, Vancouver (WA), and Spokane. Changes in future precipitation were evaluated using two runs of the Weather Research and Forecast (WRF) regional climate model (RCM) for the time periods 1970–2000 and 2020–2050, dynamically downscaled from the ECHAM5 and CCSM3 global climate models. Bias-corrected and statistically downscaled hourly precipitation sequences were then used as input to the HSPF hydrologic model to simulate streamflow in two urban watersheds in central Puget Sound. Few statistically significant changes were observed in the historical records, with the possible exception of the Puget Sound region. Although RCM simulations generally predict increases in extreme rainfall magnitudes, the range of these projections is too large at present to provide a basis for engineering design, and can only be narrowed through consideration of a larger sample of simulated climate data. Nonetheless, the evidence suggests that drainage infrastructure designed using mid-20th century rainfall records may be subject to a future rainfall regime that differs from current design standards.

The current techniques for flood frequency analysis presented in Bulletin 17B assume annual maximum floods are stationary, meaning that the distribution of flood flows is not significantly affected by climatic trends or long-term cycles (i.e. decadal variations). Observed trends in stream flows raise concern as to whether or not this assumption is valid. This paper considers how the Bulletin 17B framework might be modified to account for nonstationarity in flood records due to climate variability. In order to improve estimates/forecasts obtained using the LP3 model, the effects of climate variability may be incorporated into updated estimates of the mean, standard deviation, and perhaps the skew by regressing the LP3 parameters on climatic indices describing the Pacific Decadal Oscillation and Northern Atlantic Oscillation. The effects of climatic cycles occurring over a shorter time frame, such as El Nino, are averaged into estimates made using the procedures of Bulletin 17B . However, the effects of El Nino are likely to affect the magnitude of annual maximum stream flows, and thus would impact flood risk in a given year. El Nino effects are incorporated into forecasts by regressing the LP3 parameters on sea surface temperatures.

The changing risk of extreme precipitation is difficult to project. Events are rare by definition, and return periods of heavy precipitation events are often calculated assuming a stationary climate. Furthermore, ensembles of climate model projections are not large enough to fully categorize the tails of the distribution. To address this, we cluster the contiguous United States into self‐similar hydroclimates to estimate changes in the expected frequency of extremely rare events under scenarios of global mean temperature change. We find that, although there is some regional variation, record events are projected in general to become more intense, with 500‐year events intensifying by 10–50% under 2 °C of warming and by 40–100% under 4 °C of warming. This analysis could provide information to inform regional prioritization of resources to improve the resilience of U.S. infrastructure.

The authors examine the hydroclimatology, hydrometeorology, and hydrology of flooding in the Milwaukee metropolitan region of the upper midwestern United States. The objectives of this study are 1) to assess nonstationarities in flood frequency associated with urban transformation of land surface properties and climate change and 2) to examine how spatial heterogeneity in land surface properties and heavy rainfall climatology interact to determine floods in urbanizing areas. The authors focus on the Menomonee River basin, which drains much of the urban core of Milwaukee, and the adjacent Cedar Creek basin, where agricultural land use dominates. Results are based on analyses of bias-corrected, high-resolution (1-km 2 spatial resolution and 15-min time resolution) radar rainfall fields that are developed using the Hydro-NEXRAD system, rainfall observations from a network of 21 rain gauges in the Milwaukee metropolitan region, and discharge observations from 11 U.S. Geological Survey stream gauging stations. Both annual flood peak magnitudes and annual peaks over threshold flood counts have increased for the Menomonee River basin during the past five decades, and these trends are accompanied by a transition of flood events dominated by snowmelt (March‐April floods) to a regime in which warm season thunderstorms are the dominant floodproducing agents. The frequency of heavy rainfall events has increased significantly. The spatial distribution of rainfall for flood-producing storms in the Milwaukee study region exhibits striking spatial heterogeneity, with a maximum in the central portion of the Menomonee River basin. Storm event hydrologic response is determined by the interactions of spatial patterns of urbanization and rainfall distribution in the Menomonee River basin.

The assessment of the surface runoff capacity of storms is essential for the design of drainage infrastructure, for the management of rainfall excesses and the control of soil erosion. The knowledge of precipitation intensity values at scales larger than the daily is a key in this process. However, the available information in the region is reduced, due to the lack of instruments and historical data. An alternative to solve this problem consists of the search of mathematical relations for the scale change from daily values, more common and available, to sub-hourly values, necessary for the estimation of runoff volumes in small basins as well as erosive power of rainfall. The first results obtained in the experimentation and search of mathematical relations for the change of temporal scale for values of intensity of precipitation, valid for a wide territory with clear climatic and ecological variability are presented in this paper. The main objective of this work was to investigate the property of scale invariance in rainfall intensity and its application to the construction of IDF curves by simple scaling. The regionalization of the values obtained in the areas of study was established as a complementary objective. The hypothesis of the scale invariance and the possibility of applying simple scaling to precipitation intensity values have been verified using both pluviographic and pluviometric data recorded over the Argentina's Pampean region in climatically and ecologically different localities. The present work provides the criteria and reference values for the construction and updating of the IDF curves in the region, where they are highly necessary, leading to advances in hydrology in areas with little or no rainfall information. The results provide new evidence on scaling relations in hydrological variables, which are useful for application in cases where reference information is scarce. This contributes to the knowledge of local precipitation characteristics and provides reference values to be used in practical applications.