Impacts of Irrigation on Daily Extremes in the Coupled Climate System

NASA Technical Reports Server (NTRS)

Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide

2014-01-01

Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

No evidence of the effect of extreme weather events on annual occurrence of four groups of ectothermic species.

PubMed

Malinowska, Agnieszka H; van Strien, Arco J; Verboom, Jana; WallisdeVries, Michiel F; Opdam, Paul

2014-01-01

Weather extremes may have strong effects on biodiversity, as known from theoretical and modelling studies. Predicted negative effects of increased weather variation are found only for a few species, mostly plants and birds in empirical studies. Therefore, we investigated correlations between weather variability and patterns in occupancy, local colonisations and local extinctions (metapopulation metrics) across four groups of ectotherms: Odonata, Orthoptera, Lepidoptera, and Reptilia. We analysed data of 134 species on a 1×1 km-grid base, collected in the last 20 years from the Netherlands, combining standardised data and opportunistic data. We applied dynamic site-occupancy models and used the results as input for analyses of (i) trends in distribution patterns, (ii) the effect of temperature on colonisation and persistence probability, and (iii) the effect of years with extreme weather on all the three metapopulation metrics. All groups, except butterflies, showed more positive than negative trends in metapopulation metrics. We did not find evidence that the probability of colonisation or persistence increases with temperature nor that extreme weather events are reflected in higher extinction risks. We could not prove that weather extremes have visible and consistent negative effects on ectothermic species in temperate northern hemisphere. These findings do not confirm the general prediction that increased weather variability imperils biodiversity. We conclude that weather extremes might not be ecologically relevant for the majority of species. Populations might be buffered against weather variation (e.g. by habitat heterogeneity), or other factors might be masking the effects (e.g. availability and quality of habitat). Consequently, we postulate that weather extremes have less, or different, impact in real world metapopulations than theory and models suggest.

No Evidence of the Effect of Extreme Weather Events on Annual Occurrence of Four Groups of Ectothermic Species

PubMed Central

Malinowska, Agnieszka H.; van Strien, Arco J.; Verboom, Jana; WallisdeVries, Michiel F.; Opdam, Paul

2014-01-01

Weather extremes may have strong effects on biodiversity, as known from theoretical and modelling studies. Predicted negative effects of increased weather variation are found only for a few species, mostly plants and birds in empirical studies. Therefore, we investigated correlations between weather variability and patterns in occupancy, local colonisations and local extinctions (metapopulation metrics) across four groups of ectotherms: Odonata, Orthoptera, Lepidoptera, and Reptilia. We analysed data of 134 species on a 1×1 km-grid base, collected in the last 20 years from the Netherlands, combining standardised data and opportunistic data. We applied dynamic site-occupancy models and used the results as input for analyses of (i) trends in distribution patterns, (ii) the effect of temperature on colonisation and persistence probability, and (iii) the effect of years with extreme weather on all the three metapopulation metrics. All groups, except butterflies, showed more positive than negative trends in metapopulation metrics. We did not find evidence that the probability of colonisation or persistence increases with temperature nor that extreme weather events are reflected in higher extinction risks. We could not prove that weather extremes have visible and consistent negative effects on ectothermic species in temperate northern hemisphere. These findings do not confirm the general prediction that increased weather variability imperils biodiversity. We conclude that weather extremes might not be ecologically relevant for the majority of species. Populations might be buffered against weather variation (e.g. by habitat heterogeneity), or other factors might be masking the effects (e.g. availability and quality of habitat). Consequently, we postulate that weather extremes have less, or different, impact in real world metapopulations than theory and models suggest. PMID:25330414

Causing Factors for Extreme Precipitation in the Western Saudi-Arabian Peninsula

NASA Astrophysics Data System (ADS)

Alharbi, M. M.; Leckebusch, G. C.

2015-12-01

In the western coast of Saudi Arabia the climate is in general semi-arid but extreme precipitation events occur on a regular basis: e.g., on 26th November 2009, when 122 people were killed and 350 reported missing in Jeddah following more than 90mm in just four hours. Our investigation will a) analyse major drivers of the generation of extremes and b) investigate major responsible modes of variability for the occurrence of extremes. Firstly, we present a systematic analysis of station based observations of the most relevant extreme events (1985-2013) for 5 stations (Gizan, Makkah, Jeddah, Yenbo and Wejh). Secondly, we investigate the responsible mechanism on the synoptic to large-scale leading to the generation of extremes and will analyse factors for the time variability of extreme event occurrence. Extreme events for each station are identified in the wet season (Nov-Jan): 122 events show intensity above the respective 90th percentile. The most extreme events are systematically investigated with respect to the responsible forcing conditions which we can identify as: The influence of the Soudan Low, active Red-Sea-Trough situations established via interactions with mid-latitude tropospheric wave activity, low pressure systems over the Mediterranean, the influence of the North Africa High, the Arabian Anticyclone and the influence of the Indian monsoon trough. We investigate the role of dynamical forcing factors like the STJ and the upper-troposphere geopotential conditions and the relation to smaller local low-pressure systems. By means of an empirical orthogonal function (EOF) analysis based on MSLP we investigate the possibility to objectively quantify the influence of existing major variability modes and their role for the generation of extreme precipitation events.

From Drought to Flood: Biological Responses of Large River Salmonids and Emergent Management Challenges Under California's Extreme Hydroclimatic Variability

NASA Astrophysics Data System (ADS)

Anderson, C.

2017-12-01

California's hydroclimatic regime is characterized by extreme interannual variability including periodic, multi-year droughts and winter flooding sequences. Statewide, water years 2012-2016 were characterized by extreme drought followed by likely one of the wettest years on record in water year 2017. Similar drought-flood patterns have occurred multiple times both in the contemporary empirical record and reconstructed climate records. Both the extreme magnitude and rapid succession of these hydroclimatic periods pose difficult challenges for water managers and regulatory agencies responsible for providing instream flows to protect and recover threatened and endangered fish species. Principal among these riverine fish species are federally listed winter-run and spring-run Chinook salmon (Oncorhynchus tshawytscha), Central Valley steelhead (Oncorhynchus mykiss), and the pelagic species Delta smelt (Hypomesus transpacificus). Poor instream conditions from 2012-2016 resulted in extremely low abundance estimates and poor overall fish health, and while fish monitoring results from water year 2017 are too preliminary to draw substantive conclusions, early indicators show continued downward population trends despite the historically wet conditions. This poster evaluates California's hydroclimatic conditions over the past decade and quantifies resultant impacts of the 2012-2016 drought and the extremely wet 2017 water year to both adult escapement and juvenile production estimates in California's major inland salmon rivers over that same time span. We will also examine local, state, and federal regulatory actions both in response to the extreme hydroclimatic variability and in preparation for future drought-flood sequences.

Embedded I&C for Extreme Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kisner, Roger A.

2016-04-01

This project uses embedded instrumentation and control (I&C) technologies to demonstrate potential performance gains of nuclear power plant components in extreme environments. Extreme environments include high temperature, radiation, high pressure, high vibration, and high EMI conditions. For extreme environments, performance gains arise from moment-to-moment sensing of local variables and immediate application of local feedback control. Planning for embedding I&C during early system design phases contrasts with the traditional, serial design approach that incorporates minimal I&C after mechanical and electrical design is complete. The demonstration application involves the development and control of a novel, proof-of-concept motor/pump design. The motor and pumpmore » combination operate within the fluid environment, eliminating the need for rotating seals. Actively controlled magnetic bearings also replace failure-prone mechanical contact bearings that typically suspend rotating components. Such as design has the potential to significantly enhance the reliability and life of the pumping system and would not be possible without embedded I&C.« less

Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Rychlik, Igor; Mao, Wengang

2018-02-01

The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute long-term wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind speed time series at a fixed location or spatio-temporal wind fields around that location.

To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

PubMed

Schaarup-Jensen, K; Rasmussen, M R; Thorndahl, S

2009-01-01

In urban drainage modelling long-term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties with regards to long-term prediction of maximum water levels and combined sewer overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO volumes. Traditionally, long-term rainfall series, from a local rain gauge, are unavailable. In the present case study, however, long and local rain series are available. 2 rainfall gauges have recorded events for approximately 9 years at 2 locations within the catchment. Beside these 2 gauges another 7 gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity can be handled, e.g. by introducing an "averaging procedure" based on the variability within the set of statistics. All simulations are performed by means of the MOUSE LTS model.

Variability of temperature sensitivity of extreme precipitation from a regional-to-local impact scale perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2016-12-01

Relating precipitation intensity to temperature is a popular approach to assess potential changes of extreme events in a warming climate. Potential increases in extreme rainfall induced hazards, such as flash flooding, serve as motivation. It has not been addressed whether the temperature-precipitation scaling approach is meaningful on a regional to local level, where the risk of climate and weather impact is dealt with. Substantial variability of temperature sensitivity of extreme precipitation has been found that results from differing methodological assumptions as well as from varying climatological settings of the study domains. Two aspects are consistently found: First, temperature sensitivities beyond the expected consistency with the Clausius-Clapeyron (CC) equation are a feature of short-duration, convective, sub-daily to sub-hourly high-percentile rainfall intensities at mid-latitudes. Second, exponential growth ceases or reverts at threshold temperatures that vary from region to region, as moisture supply becomes limited. Analyses of pooled data, or of single or dispersed stations over large areas make it difficult to estimate the consequences in terms of local climate risk. In this study we test the meaningfulness of the scaling approach from an impact scale perspective. Temperature sensitivities are assessed using quantile regression on hourly and sub-hourly precipitation data from 189 stations in the Austrian south-eastern Alpine region. The observed scaling rates vary substantially, but distinct regional and seasonal patterns emerge. High sensitivity exceeding CC-scaling is seen on the 10-minute scale more than on the hourly scale, in storms shorter than 2 hours duration, and in shoulder seasons, but it is not necessarily a significant feature of the extremes. To be impact relevant, change rates need to be linked to absolute rainfall amounts. We show that high scaling rates occur in lower temperature conditions and thus have smaller effect on absolute precipitation intensities. While reporting of mere percentage numbers can be misleading, scaling studies can add value to process understanding on the local scale, if the factors that influence scaling rates are considered from both a methodological and a physical perspective.

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE PAGES

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

2016-01-01

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Regional estimation of extreme suspended sediment concentrations using watershed characteristics

NASA Astrophysics Data System (ADS)

Tramblay, Yves; Ouarda, Taha B. M. J.; St-Hilaire, André; Poulin, Jimmy

2010-01-01

SummaryThe number of stations monitoring daily suspended sediment concentration (SSC) has been decreasing since the 1980s in North America while suspended sediment is considered as a key variable for water quality. The objective of this study is to test the feasibility of regionalising extreme SSC, i.e. estimating SSC extremes values for ungauged basins. Annual maximum SSC for 72 rivers in Canada and USA were modelled with probability distributions in order to estimate quantiles corresponding to different return periods. Regionalisation techniques, originally developed for flood prediction in ungauged basins, were tested using the climatic, topographic, land cover and soils attributes of the watersheds. Two approaches were compared, using either physiographic characteristics or seasonality of extreme SSC to delineate the regions. Multiple regression models to estimate SSC quantiles as a function of watershed characteristics were built in each region, and compared to a global model including all sites. Regional estimates of SSC quantiles were compared with the local values. Results show that regional estimation of extreme SSC is more efficient than a global regression model including all sites. Groups/regions of stations have been identified, using either the watershed characteristics or the seasonality of occurrence for extreme SSC values providing a method to better describe the extreme events of SSC. The most important variables for predicting extreme SSC are the percentage of clay in the soils, precipitation intensity and forest cover.

Weather extremes and the Romans - A marine palynological perspective on Italian temperature and precipitation between 200 BC and 500 AD

NASA Astrophysics Data System (ADS)

Zonneveld, Karin; Clotten, Caroline; Chen, Liang

2015-04-01

Sediments of a tephra-dated marine sediment core located at the distal part of the Po-river discharge plume (southern Italy) have been studied with a three annual resolution. Based on the variability in the dinoflagellate cyst content detailed reconstructions have been established of variability in precipitation related river discharge rates and local air temperature. Furthermore about the variability in distort water quality has been reconstructed. We show that both precipitation and temperature signals vary in tune with cyclic changes in solar insolation. On top of these cyclic changes, short term extremes in temperature and precipitation can be observed that can be interpreted to reflect periods of local weather extremes. Comparison of our reconstructions with historical information suggest that times of high temperatures and maximal precipitation corresponds to the period of maximal expansion of the Roman Empire. We have strong indications that at this time discharge waters might have contained higher nutrient concentrations compared to previous and later time intervals suggesting anthropogenic influence of the water quality. First pilot-results suggest that the decrease in temperature reconstructed just after the "Roman Optimum" corresponds to an increase in numbers of armored conflicts between the Roman and German cultures. Furthermore we observe a resemblance in timing of short-term intervals with cold weather spells during the early so called "Dark-Age-Period" to correspond to epidemic/pandemic events in Europe.

Distributions of eight meteorological variables at Cape Kennedy, Florida and Vandenberg Air Force Base, California

NASA Technical Reports Server (NTRS)

Graves, M. E.; King, R. L.; Brown, S. C.

1973-01-01

Extreme values, median values, and nine percentile values are tabulated for eight meteorological variables at Cape Kennedy, Florida and at Vandenberg Air Force Base, California. The variables are temperature, relative humidity, station pressure, water vapor pressure, water vapor mixing ratio, density, and enthalpy. For each month eight hours are tabulated, namely, 0100, 0400, 0700, 1000, 1300, 1600, 1900, and 2200 local time. These statistics are intended for general use for the space shuttle design trade-off analysis and are not to be used for specific design values.

Assessing Flood Risk Under Sea Level Rise and Extreme Sea Levels Scenarios: Application to the Ebro Delta (Spain)

NASA Astrophysics Data System (ADS)

Sayol, J. M.; Marcos, M.

2018-02-01

This study presents a novel methodology to estimate the impact of local sea level rise and extreme surges and waves in coastal areas under climate change scenarios. The methodology is applied to the Ebro Delta, a valuable and vulnerable low-lying wetland located in the northwestern Mediterranean Sea. Projections of local sea level accounting for all contributions to mean sea level changes, including thermal expansion, dynamic changes, fresh water addition and glacial isostatic adjustment, have been obtained from regionalized sea level projections during the 21st century. Particular attention has been paid to the uncertainties, which have been derived from the spread of the multi-model ensemble combined with seasonal/inter-annual sea level variability from local tide gauge observations. Besides vertical land movements have also been integrated to estimate local relative sea level rise. On the other hand, regional projections over the Mediterranean basin of storm surges and wind-waves have been used to evaluate changes in extreme events. The compound effects of surges and extreme waves have been quantified using their joint probability distributions. Finally, offshore sea level projections from extreme events superimposed to mean sea level have been propagated onto a high resolution digital elevation model of the study region in order to construct flood hazards maps for mid and end of the 21st century and under two different climate change scenarios. The effect of each contribution has been evaluated in terms of percentage of the area exposed to coastal hazards, which will help to design more efficient protection and adaptation measures.

Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2007-12-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

Dynamical systems proxies of atmospheric predictability and mid-latitude extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Faranda, Davide; Caballero, Rodrigo; Yiou, Pascal

2017-04-01

Extreme weather ocurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. Many extremes (for e.g. storms, heatwaves, cold spells, heavy precipitation) are tied to specific patterns of midlatitude atmospheric circulation. The ability to identify these patterns and use them to enhance the predictability of the extremes is therefore a topic of crucial societal and economic value. We propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We use two simple dynamical systems metrics - local dimension and persistence - to identify sets of similar large-scale atmospheric flow patterns which present a coherent temporal evolution. When these patterns correspond to weather extremes, they therefore afford a particularly good forward predictability. We specifically test this technique on European winter temperatures, whose variability largely depends on the atmospheric circulation in the North Atlantic region. We find that our dynamical systems approach provides predictability of large-scale temperature extremes up to one week in advance.

Interannual hydroclimatic variability and the 2009-2011 extreme ENSO phases in Colombia: from Andean glaciers to Caribbean lowlands

NASA Astrophysics Data System (ADS)

Bedoya-Soto, Juan Mauricio; Poveda, Germán; Trenberth, Kevin E.; Vélez-Upegui, Jorge Julián

2018-03-01

During 2009-2011, Colombia experienced extreme hydroclimatic events associated with the extreme phases of El Niño-Southern Oscillation (ENSO). Here, we study the dynamics of diverse land-atmosphere phenomena involved in such anomalous events at continental, regional, and local scales. Standardized anomalies of precipitation, 2-m temperature, total column water (TCW), volumetric soil water (VSW), temperature at 925 hPa, surface sensible heat (SSH), latent heat (SLH), evaporation (EVP), and liquid water equivalent thickness (LWET) are analyzed to assess atmosphere-land controls and relationships over tropical South America (TropSA) during 1986-2013 (long term) and 2009-2011 (ENSO extreme phases). An assessment of the interannual covariability between precipitation and 2-m temperature is performed using singular value decomposition (SVD) to identify the dominant spatiotemporal modes of hydroclimatic variability over the region's largest river basins (Amazon, Orinoco, Tocantins, Magdalena-Cauca, and Essequibo). ENSO, its evolution in time, and strong and consistent spatial structures emerge as the dominant mode of variability. In situ anomalies during both extreme phases of ENSO 2009-2011 over the Magdalena-Cauca River basins are linked at the continental scale. The ENSO-driven hydroclimatic effects extend from the diurnal cycle to interannual timescales, as reflected in temperature data from tropical glaciers and the rain-snow boundary in the highest peaks of the Central Andes of Colombia to river levels along the Caribbean lowlands of the Magdalena-Cauca River basin.

Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature

PubMed Central

Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R

2012-01-01

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events.

PubMed

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions.

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events

PubMed Central

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions. PMID:27532008

Rainfall extremes from TRMM data and the Metastatistical Extreme Value Distribution

NASA Astrophysics Data System (ADS)

Zorzetto, Enrico; Marani, Marco

2017-04-01

A reliable quantification of the probability of weather extremes occurrence is essential for designing resilient water infrastructures and hazard mitigation measures. However, it is increasingly clear that the presence of inter-annual climatic fluctuations determines a substantial long-term variability in the frequency of occurrence of extreme events. This circumstance questions the foundation of the traditional extreme value theory, hinged on stationary Poisson processes or on asymptotic assumptions to derive the Generalized Extreme Value (GEV) distribution. We illustrate here, with application to daily rainfall, a new approach to extreme value analysis, the Metastatistical Extreme Value Distribution (MEVD). The MEVD relaxes the above assumptions and is based on the whole distribution of daily rainfall events, thus allowing optimal use of all available observations. Using a global dataset of rain gauge observations, we show that the MEVD significantly outperforms the Generalized Extreme Value distribution, particularly for long average recurrence intervals and when small samples are available. The latter property suggests MEVD to be particularly suited for applications to satellite rainfall estimates, which only cover two decades, thus making extreme value estimation extremely challenging. Here we apply MEVD to the TRMM TMPA 3B42 product, an 18-year dataset of remotely-sensed daily rainfall providing a quasi-global coverage. Our analyses yield a global scale mapping of daily rainfall extremes and of their distributional tail properties, bridging the existing large gaps in ground-based networks. Finally, we illustrate how our global-scale analysis can provide insight into how properties of local rainfall regimes affect tail estimation uncertainty when using the GEV or MEVD approach. We find a dependence of the estimation uncertainty, for both the GEV- and MEV-based approaches, on the average annual number and on the inter-annual variability of rainy days. In particular, estimation uncertainty decreases 1) as the mean annual number of wet days increases, and 2) as the variability in the number of rainy days, expressed by its coefficient of variation, decreases. We tentatively explain this behavior in terms of the assumptions underlying the two approaches.

United States Temperature and Precipitation Extremes: Phenomenology, Large-Scale Organization, Physical Mechanisms and Model Representation

NASA Astrophysics Data System (ADS)

Black, R. X.

2017-12-01

We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.

Inter-Seasonal and Annual Co-Variation of Smallholder Production Portfolios, Volumes and Incomes with Rainfall and Flood Levels in the Amazon Estuary: Implications for Building Livelihood Resilience to Increasing Variability of Hydro-Climatic Regimes

NASA Astrophysics Data System (ADS)

Vogt, N. D.; Fernandes, K.; Pinedo-Vasquez, M.; Brondizio, E. S.; Almeida, O.; Rivero, S.; Rabelo, F. R.; Dou, Y.; Deadman, P.

2014-12-01

In this paper we investigate inter-seasonal and annual co-variations of rainfall and flood levels with Caboclo production portfolios, and proportions of it they sell and consume, in the Amazon Estuary from August 2012 to August 2014. Caboclos of the estuary maintain a diverse and flexible land-use portfolio, with a shift in dominant use from agriculture to agroforestry and forestry since WWII (Vogt et al., 2014). The current landscape is configured for acai, shrimp and fish production. In the last decade the frequency of wet seasons with anomalous flood levels and duration has increased primarily from changes in rainfall and discharge from upstream basins. Local rainfall, though with less influence on extreme estuarine flood levels, is reported to be more sporadic and intense in wet season and variable in both wet and dry seasons, for yet unknown reasons. The current production portfolio and its flexibility are felt to build resilience to these increases in hydro-climatic variability and extreme events. What is less understood, for time and costliness of daily measures at household levels, is how variations in flood and rainfall levels affect shifts in the current production portfolio of estuarine Caboclos, and the proportions of it they sell and consume. This is needed to identify what local hydro-climatic thresholds are extreme for current livelihoods, that is, that most adversely affect food security and income levels. It is also needed identify the large-scale forcings driving those extreme conditions to build forecasts for when they will occur. Here we present results of production, rainfall and flood data collected daily in households from both the North and South Channel of the Amazon estuary over last two years to identify how they co-vary, and robustness of current production portfolio under different hydro-climatic conditions.

The discrete and localized nature of the variable emission from active regions

NASA Technical Reports Server (NTRS)

Arndt, Martina Belz; Habbal, Shadia Rifai; Karovska, Margarita

1994-01-01

Using data from the Extreme Ultraviolet (EUV) Spectroheliometer on Skylab, we study the empirical characteristics of the variable emission in active regions. These simultaneous multi-wavelength observations clearly confirm that active regions consist of a complex of loops at different temperatures. The variable emission from this complex has very well-defined properties that can be quantitatively summarized as follows: (1) It is localized predominantly around the footpoints where it occurs at discrete locations. (2) The strongest variability does not necessarily coincide with the most intense emission. (3) The fraction of the area of the footpoints, (delta n)/N, that exhibits variable emission, varies by +/- 15% as a function of time, at any of the wavelengths measured. It also varies very little from footpoint to footpoint. (4) This fractional variation is temperature dependent with a maximum around 10(exp 5) K. (5) The ratio of the intensity of the variable to the average background emission, (delta I)/(bar-I), also changes with temperature. In addition, we find that these distinctive characteristics persist even when flares occur within the active region.

Hydrocentric view of Agro-ecosystem Resiliency to Extreme Hydrometeorological and Climate Events in the High Plains, US.

NASA Astrophysics Data System (ADS)

Munoz-Arriola, Francisco; Sharma, Ashutosh; Werner, Katherine; Chacon, Juan-Carlos; Corzo, Gerald; Goyal, Manish-Kumar

2017-04-01

An increasing incidence of Hydrometeorological and Climate Extreme Events (EHCEs) is challenging food, water, and ecosystem services security at local to global contexts. This study aims to understand how a large-scale representation of agroecosystems and ecosystems respond to EHCE in the Northern Highplains, US. To track such responses the Variable Infiltration Capacity model (VIC) Land Surface Hydrology model was used and two experiments were implemented. The first experiment uses the LAI MODIS15A2 product to capture dynamic responses of vegetation with a time span from 2000 to 2013. The second experiment used a climatological fixed seasonal cycle calculated as the average from the 2000-2013 dynamic MODIS15A2 product to isolate vegetation from soil physical responses. Based on the analyses of multiple hydrological variables and state variables and high-level organization of agroecosystems and ecosystems, we evidence how the influence of droughts and anomalously wet conditions affect hydrological resilience at large scale.

Biophysical feedbacks mediate carbonate chemistry in coastal ecosystems across spatiotemporal gradients.

PubMed

Silbiger, Nyssa J; Sorte, Cascade J B

2018-01-15

Ocean acidification (OA) projections are primarily based on open ocean environments, despite the ecological importance of coastal systems in which carbonate dynamics are fundamentally different. Using temperate tide pools as a natural laboratory, we quantified the relative contribution of community composition, ecosystem metabolism, and physical attributes to spatiotemporal variability in carbonate chemistry. We found that biological processes were the primary drivers of local pH conditions. Specifically, non-encrusting producer-dominated systems had the highest and most variable pH environments and the highest production rates, patterns that were consistent across sites spanning 11° of latitude and encompassing multiple gradients of natural variability. Furthermore, we demonstrated a biophysical feedback loop in which net community production increased pH, leading to higher net ecosystem calcification. Extreme spatiotemporal variability in pH is, thus, both impacting and driven by biological processes, indicating that shifts in community composition and ecosystem metabolism are poised to locally buffer or intensify the effects of OA.

Extreme dissolved oxygen variability in urbanised tropical wetlands: The need for detailed monitoring to protect nursery ground values

NASA Astrophysics Data System (ADS)

Dubuc, Alexia; Waltham, Nathan; Malerba, Martino; Sheaves, Marcus

2017-11-01

Little is known about levels of dissolved oxygen fish are exposed to daily in typical urbanised tropical wetlands found along the Great Barrier Reef coastline. This study investigates diel dissolved oxygen (DO) dynamics in one of these typical urbanised wetlands, in tropical North Queensland, Australia. High frequency data loggers (DO, temperature, depth) were deployed for several days over the summer months in different tidal pools and channels that fish use as temporal or permanent refuges. DO was extremely variable over a 24 h cycle, and across the small-scale wetland. The high spatial and temporal DO variability measured was affected by time of day and tidal factors, namely water depth, tidal range and tidal direction (flood vs ebb). For the duration of the logging time, DO was mainly above the adopted threshold for hypoxia (50% saturation), however, for around 11% of the time, and on almost every logging day, DO values fell below the threshold, including a severe hypoxic event (<5% saturation) that continued for several hours. Fish still use this wetland intensively, so must be able to cope with low DO periods. Despite the ability of fish to tolerate extreme conditions, continuing urban expansion is likely to lead to further water quality degradation and so potential loss of nursery ground value. There is a substantial discontinuity between the recommended DO values in the Australian and New Zealand Guidelines for Fresh and Marine Water Quality and the values observed in this wetland, highlighting the limited value of these guidelines for management purposes. Local and regional high frequency data monitoring programs, in conjunction with local exposure risk studies are needed to underpin the development of the management that will ensure the sustainability of coastal wetlands.

A Synoptic Weather Typing Approach and Its application to Assess Climate Change Impacts on Extreme Weather Events at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Shouquan Cheng, Chad; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada for several research projects to analyze climatic change impacts on a number of extreme weather events, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the extreme weather events, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projections of changes in frequency and intensity of future extreme weather events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and a number of linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into each of the three parts of the projects. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. The modeled results from these projects found that the frequency and intensity of future extreme weather events are projected to significantly increase under a changing climate in this century. This talk will introduce these research projects and outline the modeling exercise and result verification process. The major findings on future projections from the studies will be summarized in the presentation as well. One of the major conclusions from the studies is that the procedures (including synoptic weather typing) used in the studies are useful for climate change impact analysis on future extreme weather events. The implication of the significant increases in frequency and intensity of future extreme weather events would be useful to be considered when revising engineering infrastructure design standards and developing adaptation strategies and policies.

Detection of meteorological extreme effect on historical crop yield anomaly

NASA Astrophysics Data System (ADS)

Kim, W.; Iizumi, T.; Nishimori, M.

2017-12-01

Meteorological extremes of temperature and precipitation are a critical issue in the global climate change, and some studies investigating how the extreme changes in accordance with the climate change are continuously reported. However, it is rarely understandable that the extremes affect crop yield worldwide as heatwave, coolwave, drought, and flood, albeit some local or national reports are available. Therefore, we globally investigated the extremes effects on the variability of historical yield of maize, rice, soy, and wheat with a standardized index and a historical yield anomaly. For the regression analysis, the standardized index is annually aggregated in the consideration of a crop calendar, and the historical yield is detrended with 5-year moving average. Throughout this investigation, we found that the relationship between the aggregated standardized index and the historical yield anomaly shows not merely positive correlation but also negative correlation in all crops in the globe. Namely, the extremes cause decrease of crop yield as a matter of course, but increase in some regions contrastingly. These results help us to quantify the extremes effect on historical crop yield anomaly.

Compound extremes of summer temperature and precipitation leading to intensified departures from natural variability.

NASA Astrophysics Data System (ADS)

Mahony, C. R.; Cannon, A. J.

2017-12-01

Climate change can drive local climates outside the range of their historical year-to-year variability, straining the adaptive capacity of ecological and human communities. We demonstrate that interactions between climate variables can produce larger and earlier departures from natural variability than is detectable in individual variables. For example, summer temperature (Tx) and precipitation (Pr) are negatively correlated in most terrestrial regions, such that interannual variability lies along an axis from warm-and-dry to cool-and-wet conditions. A climate change trend perpendicular to this axis, towards warmer-wetter conditions, can depart more quickly from the range of natural variability than a warmer-drier trend. This multivariate "departure intensification" effect is evident in all six CMIP5 models that we examined: 23% (9-34%) of the land area of each model exhibits a pronounced increase in 2σ extremesin the Tx-Pr regime relative to Tx or Pr alone. Observational data suggest that Tx-Pr correlations are sufficient to produce departure intensification in distinct regions on all continents. Departures from the historical Tx-Pr regime may produce ecological disruptions, such as in plant-pathogen interactions and human diseases, that could offset the drought mitigation benefits of increased precipitation. Our study alerts researchers and adaptation practitioners to the presence of multivariate climate change signals and compound extremes that are not detectable in individual climate variables.

Estimation of local extreme suspended sediment concentrations in California Rivers.

PubMed

Tramblay, Yves; Saint-Hilaire, André; Ouarda, Taha B M J; Moatar, Florentina; Hecht, Barry

2010-09-01

The total amount of suspended sediment load carried by a stream during a year is usually transported during one or several extreme events related to high river flow and intense rainfall, leading to very high suspended sediment concentrations (SSCs). In this study quantiles of SSC derived from annual maximums and the 99th percentile of SSC series are considered to be estimated locally in a site-specific approach using regional information. Analyses of relationships between physiographic characteristics and the selected indicators were undertaken using the localities of 5-km radius draining of each sampling site. Multiple regression models were built to test the regional estimation for these indicators of suspended sediment transport. To assess the accuracy of the estimates, a Jack-Knife re-sampling procedure was used to compute the relative bias and root mean square error of the models. Results show that for the 19 stations considered in California, the extreme SSCs can be estimated with 40-60% uncertainty, depending on the presence of flow regulation in the basin. This modelling approach is likely to prove functional in other Mediterranean climate watersheds since they appear useful in California, where geologic, climatic, physiographic, and land-use conditions are highly variable. Copyright 2010 Elsevier B.V. All rights reserved.

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

Evidence of population resistance to extreme low flows in a fluvial-dependent fish species

USGS Publications Warehouse

Katz, Rachel A.; Freeman, Mary C.

2015-01-01

Extreme low streamflows are natural disturbances to aquatic populations. Species in naturally intermittent streams display adaptations that enhance persistence during extreme events; however, the fate of populations in perennial streams during unprecedented low-flow periods is not well-understood. Biota requiring swift-flowing habitats may be especially vulnerable to flow reductions. We estimated the abundance and local survival of a native fluvial-dependent fish species (Etheostoma inscriptum) across 5 years encompassing historic low flows in a sixth-order southeastern USA perennial river. Based on capturemark-recapture data, the study shoal may have acted as a refuge during severe drought, with increased young-of-the-year (YOY) recruitment and occasionally high adult immigration. Contrary to expectations, summer and autumn survival rates (30 days) were not strongly depressed during low-flow periods, despite 25%-80% reductions in monthly discharge. Instead, YOY survival increased with lower minimum discharge and in response to small rain events that increased low-flow variability. Age-1+ fish showed the opposite pattern, with survival decreasing in response to increasing low-flow variability. Results from this population dynamics study of a small fish in a perennial river suggest that fluvial-dependent species can be resistant to extreme flow reductions through enhanced YOY recruitment and high survival

Investigation of the relationship between hurricane waves and extreme runup

NASA Astrophysics Data System (ADS)

Thompson, D. M.; Stockdon, H. F.

2006-12-01

In addition to storm surge, the elevation of wave-induced runup plays a significant role in forcing geomorphic change during extreme storms. Empirical formulations for extreme runup, defined as the 2% exceedence level, are dependent on some measure of significant offshore wave height. Accurate prediction of extreme runup, particularly during hurricanes when wave heights are large, depends on selecting the most appropriate measure of wave height that provides energy to the nearshore system. Using measurements from deep-water wave buoys results in an overprediction of runup elevation. Under storm forcing these large waves dissipate across the shelf through friction, whitecapping and depth-limited breaking before reaching the beach and forcing swash processes. The use of a local, shallow water wave height has been shown to provide a more accurate estimate of extreme runup elevation (Stockdon, et. al. 2006); however, a specific definition of this local wave height has yet to be defined. Using observations of nearshore waves from the U.S. Army Corps of Engineers' Field Research Facility (FRF) in Duck, NC during Hurricane Isabel, the most relevant measure of wave height for use in empirical runup parameterizations was examined. Spatial and temporal variability of the hurricane wave field, which made landfall on September 18, 2003, were modeled using SWAN. Comparisons with wave data from FRF gages and deep-water buoys operated by NOAA's National Data Buoy Center were used for model calibration. Various measures of local wave height (breaking, dissipation-based, etc.) were extracted from the model domain and used as input to the runup parameterizations. Video based observations of runup collected at the FRF during the storm were used to ground truth modeled values. Assessment of the most appropriate measure of wave height can be extended over a large area through comparisons to observations of storm- induced geomorphic change.

A downscaling method for the assessment of local climate change

NASA Astrophysics Data System (ADS)

Bruno, E.; Portoghese, I.; Vurro, M.

2009-04-01

The use of complimentary models is necessary to study the impact of climate change scenarios on the hydrological response at different space-time scales. However, the structure of GCMs is such that their space resolution (hundreds of kilometres) is too coarse and not adequate to describe the variability of extreme events at basin scale (Burlando and Rosso, 2002). To bridge the space-time gap between the climate scenarios and the usual scale of the inputs for hydrological prediction models is a fundamental requisite for the evaluation of climate change impacts on water resources. Since models operate a simplification of a complex reality, their results cannot be expected to fit with climate observations. Identifying local climate scenarios for impact analysis implies the definition of more detailed local scenario by downscaling GCMs or RCMs results. Among the output correction methods we consider the statistical approach by Déqué (2007) reported as a ‘Variable correction method' in which the correction of model outputs is obtained by a function build with the observation dataset and operating a quantile-quantile transformation (Q-Q transform). However, in the case of daily precipitation fields the Q-Q transform is not able to correct the temporal property of the model output concerning the dry-wet lacunarity process. An alternative correction method is proposed based on a stochastic description of the arrival-duration-intensity processes in coherence with the Poissonian Rectangular Pulse scheme (PRP) (Eagleson, 1972). In this proposed approach, the Q-Q transform is applied to the PRP variables derived from the daily rainfall datasets. Consequently the corrected PRP parameters are used for the synthetic generation of statistically homogeneous rainfall time series that mimic the persistency of daily observations for the reference period. Then the PRP parameters are forced through the GCM scenarios to generate local scale rainfall records for the 21st century. The statistical parameters characterizing daily storm occurrence, storm intensity and duration needed to apply the PRP scheme are considered among STARDEX collection of extreme indices.

Extreme Events in Urban Streams Leading to Extreme Temperatures in Birmingham, UK

NASA Astrophysics Data System (ADS)

Rangecroft, S.; Croghan, D.; Van Loon, A.; Sadler, J. P.; Hannah, D. M.

2016-12-01

Extreme flows and high water temperature events act as critical stressors on the ecological health of rivers. Urban headwater streams are considered particularly vulnerable to the effects of these extreme events. Despite this, such catchments remain poorly characterised and the effect of differences in land use is rarely quantified, especially in relation to water temperature. Thus a key research gap has emerged in understanding the patterns of water temperature during extreme events within contrasting urban, headwater catchments. We studied the headwaters of two bordering urban catchments of contrasting land use within Birmingham, UK. To characterise response to extreme events, precipitation and flow were analysed for the period of 1970-2016. To analyse the effects of extreme events on water temperature, 10 temperature loggers recording at 15 minute intervals were placed within each catchment covering a range of land use for the period May 2016 - present. During peak over threshold flood events higher average peaks were observed in the less urbanised catchment; however highest maximum flow peaks took place in the more densely urbanised catchment. Very similar average drought durations were observed between the two catchments with average flow drought durations of 27 days in the most urbanised catchment, and 29 in the less urbanised catchment. Flashier water temperature regimes were observed within the more urbanised catchment and increases of up to 5 degrees were apparent within 30 minutes during certain storms at the most upstream sites. Only in the most extreme events did the more densely urban stream appear more susceptible to both extreme high flows and extreme water temperature events, possibly resultant from overland flow emerging as the dominant flow pathway during intense precipitation events. Water temperature surges tended to be highly spatially variable indicating the importance of local land use. During smaller events, water temperature was less changeable and spatially variable, suggesting that overland flow may not the dominant flow pathway in such events. During drought events, the effect of catchment land use on water temperature was less apparent.

Climate Resiliency Planning: Making Extreme Event Science Useful for Managers and Planners in Northern Nevada

NASA Astrophysics Data System (ADS)

McCarthy, M.; Kenneston, A.; Wall, T. U.; Brown, T. J.; Redmond, K. T.

2014-12-01

Effective climate resiliency planning at the regional level requires extensive interactive dialogue among climate scientists, emergency managers, public health officials, urban planners, social scientists, and policy makers. Engaging federal, tribal, state, local governments and private sector business and infrastructure owners/operators in defining, assessing and characterizing the impacts of extreme events allows communities to understand how different events "break the system" forcing local communities to seek support and resources from state/federal governments and/or the private sector and what actions can be taken proactively to mitigate consequences and accelerate recovery. The Washoe County Regional Resiliency Study was prepared in response to potential climate variability related impacts specific to the Northern Nevada Region. The last several decades have seen dramatic growth in the region, coupled with increased resource demands that have forced local governments to consider how those impacts will affect the region and may, in turn, impact the region's ability to provide essential services. The Western Regional Climate Center of the Desert Research Institute provided a synthesis of climate studies with predictions regarding plausible changes in the local climate of Northern California and Nevada for the next 50 years. In general, these predictions indicate that the region's climate is undergoing a gradual shift, which will primarily affect the frequency, amount, and form of precipitation in the Sierra Nevada and Great Basin. Changes in water availability and other extreme events may have serious and long lasting effects in the Northern Nevada Region, and create a variety of social, environmental and economic concerns. A range of extreme events were considered including Adverse Air Quality, Droughts, Floods, Heat Waves, High Wind, Structure Fires, Wildland Fires, and Major Winter Storms. Due to the complexity of our climate systems, and the difficulty in specifying how severe the climate effects may be or how those impacts compound existing hazards in the system, the Resiliency Study focused on identifying a variety of 'no regrets' policy options that can help the local communities anticipate, respond and recover faster and more efficiently to climate extremes.

Quantifying spatiotemporal variability of fine particles in an urban environment using combined fixed and mobile measurements

NASA Astrophysics Data System (ADS)

Sullivan, R. C.; Pryor, S. C.

2014-06-01

Spatiotemporal variability of fine particle concentrations in Indianapolis, Indiana is quantified using a combination of high temporal resolution measurements at four fixed sites and mobile measurements with instruments attached to bicycles during transects of the city. Average urban PM2.5 concentrations are an average of ˜3.9-5.1 μg m-3 above the regional background. The influence of atmospheric conditions on ambient PM2.5 concentrations is evident with the greatest temporal variability occurring at periods of one day and 5-10 days corresponding to diurnal and synoptic meteorological processes, and lower mean wind speeds are associated with episodes of high PM2.5 concentrations. An anthropogenic signal is also evident. Higher PM2.5 concentrations coincide with morning rush hour, the frequencies of PM2.5 variability co-occur with those for carbon monoxide, and higher extreme concentrations were observed mid-week compared to weekends. On shorter time scales (

Local increase of anticyclonic wave activity over northern Eurasia under amplified Arctic warming: WAVE ACTIVITY RESPONSE TO ARCTIC MELTING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xue, Daokai; Lu, Jian; Sun, Lantao

In an attempt to resolve the controversy as to whether Arctic sea ice loss leads to more mid-latitude extremes, a metric of finite-amplitude wave activity is adopted to quantify the midlatitude wave activity and its change during the observed period of the drastic Arctic sea ice decline in both ERA Interim reanalysis data and a set of AMIP-type of atmospheric model experiments. Neither the experiment with the trend in the SST or that with the declining trend of Arctic sea ice can simulate the sizable midlatitude-wide reduction in the total wave activity (Ae) observed in the reanalysis, leaving its explanationmore » to the atmospheric internal variability. On the other hand, both the diagnostics of the flux of the local wave activity and the model experiments lend evidence to a possible linkage between the sea ice loss near the Barents and Kara seas and the increasing trend of anticyclonic local wave activity over the northern part of the central Eurasia and the associated impacts on the frequency of temperature extremes.« less

People as sensors: mass media and local temperature influence climate change discussion on Twitter

NASA Astrophysics Data System (ADS)

Kirilenko, A.; Molodtsova, T.; Stepchenkova, S.

2014-12-01

We examined whether people living under significant temperature anomalies connect their sensory experiences to climate change and the role that media plays in this process. We used Twitter messages containing words "climate change" and "global warming" as the indicator of attention that public pays to the issue. Specifically, the goals were: (1) to investigate whether people immediately notice significant local weather anomalies and connect them to climate change and (2) to examine the role of mass media in this process. Over 2 million tweets were collected for a two-year period (2012 - 2013) and were assigned to 157 urban areas in the continental USA (Figure 1). Geographical locations of the tweets were identified with a geolocation resolving algorithm based the profile of the users. Daily number of tweets (tweeting rate) was computed for 157 conterminous USA urban areas and adjusted for data acquisition errors. The USHCN daily minimum and maximum temperatures were obtained for the station locations closest to the centers of the urban areas and the 1981-2010 30-year temperature mean and standard deviation were used as the climate normals. For the analysis, we computed the following indices for each day of 2012 - 2013 period: standardized temperature anomaly, absolute standardized temperature anomaly, and extreme cold and hot temperature anomalies for each urban zone. The extreme cold and hot temperature anomalies were then transformed into country-level values that represent the number of people living in extreme temperature conditions. The rate of tweeting on climate change was regressed on the time variables, number of climate change publications in the mass media, and temperature. In the majority of regression models, the mass media and temperature variables were significant at the p<0.001 level. Additionally, we did not find convincing evidence that the media acts as a mediator in the relationship between local weather and climate change discourse intensity. Our analysis of Twitter data confirmed that the public is able to recognize extreme temperature anomalies and connects these anomalies to climate change. Finally, we demonstrated the utility of social network data for research on public climate change perception.

Assessing changes in extreme convective precipitation from a damage perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Tye, M. R.

2016-12-01

Projected increases in high-intensity short-duration convective precipitation are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to which, not only are extreme events rare, but such small scale events are likely to be underreported where they don't coincide with the observation network. Rather than focus solely on the convective precipitation, understanding the characteristics of these extremes which drive damage may be more effective to assess future risks. Two sources of data are used in this study. First, sub-daily precipitation observations over the Southern Alps enable an examination of seasonal and regional patterns in high-intensity convective precipitation and their relationship with weather types. Secondly, reports of private loss and damage on a household scale are used to identify which events are most damaging, or what conditions potentially enhance the vulnerability to these extremes.This study explores the potential added value from including recorded loss and damage data to understand the risks from summertime convective precipitation events. By relating precipitation generating weather types to the severity of damage we hope to develop a mechanism to assess future risks. A further benefit would be to identify from damage reports the likely occurrence of precipitation extremes where no direct observations are available and use this information to validate remotely sensed observations.

Changes in Hydrological Extremes and its Relation to Climate Variability in Mountainous Watershed: A Case Study from Gandaki River Basin, Nepal

NASA Astrophysics Data System (ADS)

Shrestha, N. S.; Dahal, P.

2016-12-01

Changes in the hydrological extreme are expected due to climate variability and are needed to assess at local and regional scales since these changes are not uniform over the globe. This study analyses the changes in intensity, frequency and persistence hydrological extreme in Gandaki River Basin (GRB) Nepal over past and future and its relation to climate variability. Hydrological data of 12 different hydrological stations covering all the sub basins of Gandaki River Basin were analyzed. At least 1 hydrological station in each sub basin to the maximum of 3 was taken into consideration for this study. Results show that hydrological extreme have increased in intensity, frequency and persistence over recent year and are predicted to increase in future (2030-2060). The time-series analysis revealed an increase in the magnitude, frequency and duration of flood and drought. The instantaneous maximum flow, flood events and duration of flood events are found to have increasing trend. The minimum discharge was observed to be decreasing which entails that the water availability in the driest time is decreasing. Trend analysis of seasonal flow revealed an increase in monsoon flows and decreasing in post monsoon. Changes in climate variability over the same period shows higher anomalies in both temperature and precipitation in recent decades (1990s and 2000s) compared to the baseline period (1970-2000). Model suggests an increasing trend in annual flows with the increase more pronounced in 2060s. Significant increase in extreme flows and subsequent decrease in dependable flows suggest increase in frequency of isolated extreme flows followed by prolonged dry spells. Data also showed that the mean temperature will be increasing from 1.9 0C to 3.1 0C and precipitation will be changing by -8% to +12% in 2031-2060 compared to the baseline period. For long-term planning and management of water resources, current trend and future change in the pattern of water availability should be analysed well in advance. Climate change with intensifying extreme events will likely have serious consequences on the hydrological changes. Therefore, this study would be useful in understanding how the hydrological regime has been changing with climate change in mountainous watershed.

Reconstructing the 20th century high-resolution climate of the southeastern United States

NASA Astrophysics Data System (ADS)

Dinapoli, Steven M.; Misra, Vasubandhu

2012-10-01

We dynamically downscale the 20th Century Reanalysis (20CR) to a 10-km grid resolution from 1901 to 2008 over the southeastern United States and the Gulf of Mexico using the Regional Spectral Model. The downscaled data set, which we call theFlorida Climate Institute-Florida State University Land-Atmosphere Reanalysis for theSoutheastern United States at 10-km resolution (FLAReS1.0), will facilitate the study of the effects of low-frequency climate variability and major historical climate events on local hydrology and agriculture. To determine the suitability of the FLAReS1.0 downscaled data set for any subsequent applied climate studies, we compare the annual, seasonal, and diurnal variability of temperature and precipitation in the model to various observation data sets. In addition, we examine the model's depiction of several meteorological phenomena that affect the climate of the region, including extreme cold waves, summer sea breezes and associated convective activity, tropical cyclone landfalls, and midlatitude frontal systems. Our results show that temperature and precipitation variability are well-represented by FLAReS1.0 on most time scales, although systematic biases do exist in the data. FLAReS1.0 accurately portrays some of the major weather phenomena in the region, but the severity of extreme weather events is generally underestimated. The high resolution of FLAReS1.0 makes it more suitable for local climate studies than the coarser 20CR.

Modeling the impact of climate variability on diarrhea-associated diseases in Taiwan (1996-2007).

PubMed

Chou, Wei-Chun; Wu, Jiunn-Lin; Wang, Yu-Chun; Huang, Hsin; Sung, Fung-Chang; Chuang, Chun-Yu

2010-12-01

Diarrhea is an important public health problem in Taiwan. Climatic changes and an increase in extreme weather events (extreme heat, drought or rainfalls) have been strongly linked to the incidence of diarrhea-associated disease. This study investigated and quantified the relationship between climate variations and diarrhea-associated morbidity in subtropical Taiwan. Specifically, this study analyzed the local climatic variables and the number of diarrhea-associated infection cases from 1996 to 2007. This study applied a climate variation-guided Poisson regression model to predict the dynamics of diarrhea-associated morbidity. The proposed model allows for climate factors (relative humidity, maximum temperature and the numbers of extreme rainfall), autoregression, long-term trends and seasonality, and a lag-time effect. Results indicated that the maximum temperature and extreme rainfall days were strongly related to diarrhea-associated morbidity. The impact of maximum temperature on diarrhea-associated morbidity appeared primarily among children (0-14years) and older adults (40-64years), and had less of an effect on adults (15-39years). Otherwise, relative humidity and extreme rainfall days significantly contributed to the diarrhea-associated morbidity in adult. This suggested that children and older adults were the most susceptible to diarrhea-associated morbidity caused by climatic variation. Because climatic variation contributed to diarrhea morbidity in Taiwan, it is necessary to develop an early warning system based on the climatic variation information for disease control management. Copyright © 2010 Elsevier B.V. All rights reserved.

Assessment of the uncertainty in future projection for summer climate extremes over the East Asia

NASA Astrophysics Data System (ADS)

Park, Changyong; Min, Seung-Ki; Cha, Dong-Hyun

2017-04-01

Future projections of climate extremes in regional and local scales are essential information needed for better adapting to climate changes. However, future projections hold larger uncertainty factors arising from internal and external processes which reduce the projection confidence. Using CMIP5 (Coupled Model Intercomparison Project Phase 5) multi-model simulations, we assess uncertainties in future projections of the East Asian temperature and precipitation extremes focusing on summer. In examining future projection, summer mean and extreme projections of the East Asian temperature and precipitation would be larger as time. Moreover, uncertainty cascades represent wider scenario difference and inter-model ranges with increasing time. A positive mean-extreme relation is found in projections for both temperature and precipitation. For the assessment of uncertainty factors for these projections, dominant uncertainty factors from temperature and precipitation change as time. For uncertainty of mean and extreme temperature, contributions of internal variability and model uncertainty declines after mid-21st century while role of scenario uncertainty grows rapidly. For uncertainty of mean precipitation projections, internal variability is more important than the scenario uncertainty. Unlike mean precipitation, extreme precipitation shows that the scenario uncertainty is expected to be a dominant factor in 2090s. The model uncertainty holds as an important factor for both mean and extreme precipitation until late 21st century. The spatial changes for the uncertainty factors of mean and extreme projections generally are expressed according to temporal changes of the fraction of total variance from uncertainty factors in many grids of the East Asia. ACKNOWLEDGEMENTS The research was supported by the Korea Meteorological Administration Research and Development program under grant KMIPA 2015-2083 and the National Research Foundation of Korea Grant funded by the Ministry of Science, ICT and Future Planning of Korea (NRF-2016M3C4A7952637) for its support and assistant in completion of the study.

Assessment of floodplain vulnerability during extreme Mississippi River flood 2011

USGS Publications Warehouse

Goodwell, Allison E.; Zhu, Zhenduo; Dutta, Debsunder; Greenberg, Jonathan A.; Kumar, Praveen; Garcia, Marcelo H.; Rhoads, Bruce L.; Holmes, Robert R.; Parker, Gary; Berretta, David P.; Jacobson, Robert B.

2014-01-01

Regional change in the variability and magnitude of flooding could be a major consequence of future global climate change. Extreme floods have the capacity to rapidly transform landscapes and expose landscape vulnerabilities through highly variable spatial patterns of inundation, erosion, and deposition. We use the historic activation of the Birds Point-New Madrid Floodway during the Mississippi and Ohio River Flooding of 2011 as a scientifically unique stress experiment to analyze indicators of floodplain vulnerability. We use pre- and postflood airborne Light Detection and Ranging data sets to locate erosional and depositional hotspots over the 540 km2 agricultural Floodway. While riparian vegetation between the river and the main levee breach likely prevented widespread deposition, localized scour and deposition occurred near the levee breaches. Eroded gullies nearly 1 km in length were observed at a low ridge of a relict meander scar of the Mississippi River. Our flow modeling and spatial mapping analysis attributes this vulnerability to a combination of erodible soils, flow acceleration associated with legacy fluvial landforms, and a lack of woody vegetation to anchor soil and enhance flow resistance. Results from this study could guide future mitigation and adaptation measures in cases of extreme flooding.

Assessment of floodplain vulnerability during extreme Mississippi River flood 2011.

PubMed

Goodwell, Allison E; Zhu, Zhenduo; Dutta, Debsunder; Greenberg, Jonathan A; Kumar, Praveen; Garcia, Marcelo H; Rhoads, Bruce L; Holmes, Robert R; Parker, Gary; Berretta, David P; Jacobson, Robert B

2014-01-01

Regional change in the variability and magnitude of flooding could be a major consequence of future global climate change. Extreme floods have the capacity to rapidly transform landscapes and expose landscape vulnerabilities through highly variable spatial patterns of inundation, erosion, and deposition. We use the historic activation of the Birds Point-New Madrid Floodway during the Mississippi and Ohio River Flooding of 2011 as a scientifically unique stress experiment to analyze indicators of floodplain vulnerability. We use pre- and postflood airborne Light Detection and Ranging data sets to locate erosional and depositional hotspots over the 540 km(2) agricultural Floodway. While riparian vegetation between the river and the main levee breach likely prevented widespread deposition, localized scour and deposition occurred near the levee breaches. Eroded gullies nearly 1 km in length were observed at a low ridge of a relict meander scar of the Mississippi River. Our flow modeling and spatial mapping analysis attributes this vulnerability to a combination of erodible soils, flow acceleration associated with legacy fluvial landforms, and a lack of woody vegetation to anchor soil and enhance flow resistance. Results from this study could guide future mitigation and adaptation measures in cases of extreme flooding.

Modeling Compound Flood Hazards in Coastal Embayments

NASA Astrophysics Data System (ADS)

Moftakhari, H.; Schubert, J. E.; AghaKouchak, A.; Luke, A.; Matthew, R.; Sanders, B. F.

2017-12-01

Coastal cities around the world are built on lowland topography adjacent to coastal embayments and river estuaries, where multiple factors threaten increasing flood hazards (e.g. sea level rise and river flooding). Quantitative risk assessment is required for administration of flood insurance programs and the design of cost-effective flood risk reduction measures. This demands a characterization of extreme water levels such as 100 and 500 year return period events. Furthermore, hydrodynamic flood models are routinely used to characterize localized flood level intensities (i.e., local depth and velocity) based on boundary forcing sampled from extreme value distributions. For example, extreme flood discharges in the U.S. are estimated from measured flood peaks using the Log-Pearson Type III distribution. However, configuring hydrodynamic models for coastal embayments is challenging because of compound extreme flood events: events caused by a combination of extreme sea levels, extreme river discharges, and possibly other factors such as extreme waves and precipitation causing pluvial flooding in urban developments. Here, we present an approach for flood risk assessment that coordinates multivariate extreme analysis with hydrodynamic modeling of coastal embayments. First, we evaluate the significance of correlation structure between terrestrial freshwater inflow and oceanic variables; second, this correlation structure is described using copula functions in unit joint probability domain; and third, we choose a series of compound design scenarios for hydrodynamic modeling based on their occurrence likelihood. The design scenarios include the most likely compound event (with the highest joint probability density), preferred marginal scenario and reproduced time series of ensembles based on Monte Carlo sampling of bivariate hazard domain. The comparison between resulting extreme water dynamics under the compound hazard scenarios explained above provides an insight to the strengths/weaknesses of each approach and helps modelers choose the appropriate scenario that best fit to the needs of their project. The proposed risk assessment approach can help flood hazard modeling practitioners achieve a more reliable estimate of risk, by cautiously reducing the dimensionality of the hazard analysis.

Identifying climate analogues for precipitation extremes for Denmark based on RCM simulations from the ENSEMBLES database.

PubMed

Arnbjerg-Nielsen, K; Funder, S G; Madsen, H

2015-01-01

Climate analogues, also denoted Space-For-Time, may be used to identify regions where the present climatic conditions resemble conditions of a past or future state of another location or region based on robust climate variable statistics in combination with projections of how these statistics change over time. The study focuses on assessing climate analogues for Denmark based on current climate data set (E-OBS) observations as well as the ENSEMBLES database of future climates with the aim of projecting future precipitation extremes. The local present precipitation extremes are assessed by means of intensity-duration-frequency curves for urban drainage design for the relevant locations being France, the Netherlands, Belgium, Germany, the United Kingdom, and Denmark. Based on this approach projected increases of extreme precipitation by 2100 of 9 and 21% are expected for 2 and 10 year return periods, respectively. The results should be interpreted with caution as the best region to represent future conditions for Denmark is the coastal areas of Northern France, for which only little information is available with respect to present precipitation extremes.

Rainfall extremes, weather and climatic characterization over complex terrain: A data-driven approach based on signal enhancement methods and extreme value modeling

NASA Astrophysics Data System (ADS)

Pineda, Luis E.; Willems, Patrick

2017-04-01

Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather and climate drivers, allows identification of well-known features of the regional climate in a purely data-driven fashion. Thus, this approach shows potential for characterization of precipitation extremes in data-scarce and orographically complex regions in which model reconstructions are the only climate proxies References [1] Mínguez, R., F.J. Méndez, C. Izaguirre, M. Menéndez, and I.J. Losada (2010), Pseudooptimal parameter selection of non-stationary generalized extreme value models for environmental variables, Environ. Modell. Softw. 25, 1592-1607. [2] Pineda, L., P. Willems (2016), Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific-Andean River Basins in Ecuador and Peru using a non-homogenous hidden Markov model, J. Hydrometeor, 17(2), 481-498, doi:10.1175/JHM-D-15-0040.1, http://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0040.1

Local SAR in High Pass Birdcage and TEM Body Coils for Multiple Human Body Models in Clinical Landmark Positions at 3T

PubMed Central

Yeo, Desmond TB; Wang, Zhangwei; Loew, Wolfgang; Vogel, Mika W; Hancu, Ileana

2011-01-01

Purpose To use EM simulations to study the effects of body type, landmark position, and RF body coil type on peak local SAR in 3T MRI. Materials and Methods Numerically computed peak local SAR for four human body models (HBMs) in three landmark positions (head, heart, pelvic) were compared for a high-pass birdcage and a transverse electromagnetic 3T body coil. Local SAR values were normalized to the IEC whole-body average SAR limit of 2.0 W/kg for normal scan mode. Results Local SAR distributions were highly variable. Consistent with previous reports, the peak local SAR values generally occurred in the neck-shoulder area, near rungs, or between tissues of greatly differing electrical properties. The HBM type significantly influenced the peak local SAR, with stockier HBMs, extending extremities towards rungs, displaying the highest SAR. There was also a trend for higher peak SAR in the head-centric and heart-centric positions. The impact of the coil-types studied was not statistically significant. Conclusion The large variability in peak local SAR indicates the need to include more than one HBM or landmark position when evaluating safety of body coils. It is recommended that a HBM with arms near the rungs be included, to create physically realizable high-SAR scenarios. PMID:21509880

Extremal optimization for Sherrington-Kirkpatrick spin glasses

NASA Astrophysics Data System (ADS)

Boettcher, S.

2005-08-01

Extremal Optimization (EO), a new local search heuristic, is used to approximate ground states of the mean-field spin glass model introduced by Sherrington and Kirkpatrick. The implementation extends the applicability of EO to systems with highly connected variables. Approximate ground states of sufficient accuracy and with statistical significance are obtained for systems with more than N=1000 variables using ±J bonds. The data reproduces the well-known Parisi solution for the average ground state energy of the model to about 0.01%, providing a high degree of confidence in the heuristic. The results support to less than 1% accuracy rational values of ω=2/3 for the finite-size correction exponent, and of ρ=3/4 for the fluctuation exponent of the ground state energies, neither one of which has been obtained analytically yet. The probability density function for ground state energies is highly skewed and identical within numerical error to the one found for Gaussian bonds. But comparison with infinite-range models of finite connectivity shows that the skewness is connectivity-dependent.

Patterns of change in high frequency precipitation variability over North America.

PubMed

Roque-Malo, Susana; Kumar, Praveen

2017-09-18

Precipitation variability encompasses attributes associated with the sequencing and duration of events of the full range of magnitudes. However, climate change studies have largely focused on extreme events. Using analyses of long-term weather station data, we show that high frequency events, such as fraction of wet days in a year and average duration of wet and dry periods, are undergoing significant changes across North America. Further, these changes are more prevalent and larger than those associated with extremes. Such trends also exist for events of a range of magnitudes. Existence of localized clusters with opposing trend to that of broader geographic variation illustrates the role of microclimate and other drivers of trends. Such hitherto unknown patterns over the entire North American continent have the potential to significantly inform our characterization of the resilience and vulnerability of a broad range of ecosystems and agricultural and socio-economic systems. They can also set new benchmarks for climate model assessments.

Variability in Wheelchair Propulsion: A New Window into an Old Problem

PubMed Central

Sosnoff, Jacob J.; Rice, Ian M.; Hsiao-Wecksler, Elizabeth T.; Hsu, Iris M. K.; Jayaraman, Chandrasekaran; Moon, Yaejin

2015-01-01

Manual wheelchair users are at great risk for the development of upper extremity injury and pain. Any loss of upper limb function due to pain adversely impacts the independence and mobility of manual wheelchair users. There is growing theoretical and empirical evidence that fluctuations in movement (i.e., motor variability) are related to musculoskeletal pain. This perspectives paper discusses a local review on several investigations examining the association between variability in wheelchair propulsion and shoulder pain in manual wheelchair users. The experimental data reviewed highlights that the variability of wheelchair propulsion is impacted by shoulder pain in manual wheelchair users. We maintain that inclusion of these metrics in future research on wheelchair propulsion and upper limb pain may yield novel data. Several promising avenues for future research based on this collective work are discussed. PMID:26284239

Bayesian hierarchical modelling of North Atlantic windiness

NASA Astrophysics Data System (ADS)

Vanem, E.; Breivik, O. N.

2013-03-01

Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.

Estimating extreme river discharges in Europe through a Bayesian network

NASA Astrophysics Data System (ADS)

Paprotny, Dominik; Morales-Nápoles, Oswaldo

2017-06-01

Large-scale hydrological modelling of flood hazards requires adequate extreme discharge data. In practise, models based on physics are applied alongside those utilizing only statistical analysis. The former require enormous computational power, while the latter are mostly limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian networks (BNs), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables representing the geographical characteristics of their catchments. Annual maxima of daily discharges from more than 1800 river gauges (stations with catchment areas ranging from 1.4 to 807 000 km2) were collected, together with information on terrain, land use and local climate. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe and better than a comparable global statistical model. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and remains the same in a split-sample validation. Though discharge prediction under climate change is not the main scope of this paper, the BN was applied to a large domain covering all sizes of rivers in the continent both for present and future climate, as an example. Results show substantial variation in the influence of climate change on river discharges. The model can be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

Experimental droughts: Are precipitation variability and methodological trends hindering our understanding of ecological sensitivities to drought?

NASA Astrophysics Data System (ADS)

Hoover, D. L.; Wilcox, K.; Young, K. E.

2017-12-01

Droughts are projected to increase in frequency and intensity with climate change, which may have dramatic and prolonged effects on ecosystem structure and function. There are currently hundreds of published, ongoing, and new drought experiments worldwide aimed to assess ecosystem sensitivities to drought and identify the mechanisms governing ecological resistance and resilience. However, to date, the results from these experiments have varied widely, and thus patterns of drought sensitivities have been difficult to discern. This lack of consensus at the field scale, limits the abilities of experiments to help improve land surface models, which often fail to realistically simulate ecological responses to extreme events. This is unfortunate because models offer an alternative, yet complementary approach to increase the spatial and temporal assessment of ecological sensitivities to drought that are not possible in the field due to logistical and financial constraints. Here we examined 89 published drought experiments, along with their associated historical precipitation records to (1) identify where and how drought experiments have been imposed, (2) determine the extremity of drought treatments in the context of historical climate, and (3) assess the influence of precipitation variability on drought experiments. We found an overall bias in drought experiments towards short-term, extreme experiments in water-limited ecosystems. When placed in the context of local historical precipitation, most experimental droughts were extreme, with 61% below the 5th, and 43% below the 1st percentile. Furthermore, we found that interannual precipitation variability had a large and potentially underappreciated effect on drought experiments due to the co-varying nature of control and drought treatments. Thus detecting ecological effects in experimental droughts is strongly influenced by the interaction between drought treatment magnitude, precipitation variability, and key physiological thresholds. The results from this study have important implication for the design and interpretation of drought experiments as well as integrating field results with land surface models.

Species-specific responses to ocean acidification should account for local adaptation and adaptive plasticity.

PubMed

Vargas, Cristian A; Lagos, Nelson A; Lardies, Marco A; Duarte, Cristian; Manríquez, Patricio H; Aguilera, Victor M; Broitman, Bernardo; Widdicombe, Steve; Dupont, Sam

2017-03-13

Global stressors, such as ocean acidification, constitute a rapidly emerging and significant problem for marine organisms, ecosystem functioning and services. The coastal ecosystems of the Humboldt Current System (HCS) off Chile harbour a broad physical-chemical latitudinal and temporal gradient with considerable patchiness in local oceanographic conditions. This heterogeneity may, in turn, modulate the specific tolerances of organisms to climate stress in species with populations distributed along this environmental gradient. Negative response ratios are observed in species models (mussels, gastropods and planktonic copepods) exposed to changes in the partial pressure of CO 2 (pCO2) far from the average and extreme pCO2 levels experienced in their native habitats. This variability in response between populations reveals the potential role of local adaptation and/or adaptive phenotypic plasticity in increasing resilience of species to environmental change. The growing use of standard ocean acidification scenarios and treatment levels in experimental protocols brings with it a danger that inter-population differences are confounded by the varying environmental conditions naturally experienced by different populations. Here, we propose the use of a simple index taking into account the natural pCO2 variability, for a better interpretation of the potential consequences of ocean acidification on species inhabiting variable coastal ecosystems. Using scenarios that take into account the natural variability will allow understanding of the limits to plasticity across organismal traits, populations and species.

Using damage data to estimate the risk from summer convective precipitation extremes

NASA Astrophysics Data System (ADS)

Schroeer, Katharina; Tye, Mari

2017-04-01

This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical model to test whether the relationship between extreme rainfall events and damages is robust enough to estimate a potential underrepresentation of high intensity rainfall events in ungauged areas. Risk-relevant factors of socio-economic vulnerability, land cover, streamflow data, and weather type information are included to improve and sharpen the analysis. Within this study, we first aim to identify which rainfall events are most damaging and which factors affect the damages - seen as a proxy for the vulnerability - related to summer convective rainfall extremes in different catchment types. Secondly, we aim to detect potentially unreported damaging rainfall events and estimate the likelihood of such cases. We anticipate this damage perspective on summertime extreme convective precipitation to be beneficial for risk assessment, uncertainty management, and decision making with respect to weather and climate extremes on the regional-to-local level.

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Effects of local and widespread muscle fatigue on movement timing.

PubMed

Cowley, Jeffrey C; Dingwell, Jonathan B; Gates, Deanna H

2014-12-01

Repetitive movements can cause muscle fatigue, leading to motor reorganization, performance deficits, and/or possible injury. The effects of fatigue may depend on the type of fatigue task employed, however. The purpose of this study was to determine how local fatigue of a specific muscle group versus widespread fatigue of various muscle groups affected the control of movement timing. Twenty healthy subjects performed an upper extremity low-load work task similar to sawing for 5 continuous minutes both before and after completing a protocol that either fatigued all the muscles used in the task (widespread fatigue) or a protocol that selectively fatigued the primary muscles used to execute the pushing stroke of the sawing task (localized fatigue). Subjects were instructed to time their movements with a metronome. Timing error, movement distance, and speed were calculated for each movement. Data were then analyzed using a goal-equivalent manifold approach to quantify changes in goal-relevant and non-goal-relevant variability. We applied detrended fluctuation analysis to each time series to quantify changes in fluctuation dynamics that reflected changes in the control strategies used. After localized fatigue, subjects made shorter, slower movements and exerted greater control over non-goal-relevant variability. After widespread fatigue, subjects exerted less control over non-goal-relevant variability and did not change movement patterns. Thus, localized and widespread muscle fatigue affected movement differently. Local fatigue may reduce the available motor solutions and therefore cause greater movement reorganization than widespread muscle fatigue. Subjects altered their control strategies but continued to achieve the timing goal after both fatigue tasks.

Variability of Extreme Precipitation Events in Tijuana, Mexico During ENSO Years

NASA Astrophysics Data System (ADS)

Cavazos, T.; Rivas, D.

2007-05-01

We present the variability of daily precipitation extremes (top 10 percecnt) in Tijuana, Mexico during 1950-2000. Interannual rainfall variability is significantly modulated by El Nino/Southern Oscillation. The interannual precipitation variability exhibits a large change with a relatively wet period and more variability during 1976- 2000. The wettest years and the largest frequency of daily extremes occurred after 1976-1977, with 6 out of 8 wet years characterized by El Nino episodes and 2 by neutral conditions. However, more than half of the daily extremes during 1950-2000 occurred in non-ENSO years, evidencing that neutral conditions also contribute significantly to extreme climatic variability in the region. Extreme events that occur in neutral (strong El Nino) conditions are associated with a pineapple express and a neutral PNA (negative TNH) teleconnection pattern that links an anomalous tropical convective forcing west (east) of the date line with a strong subtropical jet over the study area. At regional scale, both types of extremes are characterized by a trough in the subtropical jet over California/Baja California, which is further intensified by thermal interaction with an anomalous warm California Current off Baja California, low-level moisture advection from the subtropical warm sea-surface region, intense convective activity over the study area and extreme rainfall from southern California to Baja California.

Climatological assessment of spatiotemporal trends in observational monthly snowfall totals and extremes over the Canadian Great Lakes Basin

NASA Astrophysics Data System (ADS)

Baijnath, Janine; Duguay, Claude; Sushama, Laxmi; Huziy, Oleksandr

2017-04-01

The Laurentian Great Lakes Basin (GLB) is susceptible to snowfall events that derive from extratropical cyclones and heavy lake effect snowfall (HLES). The former is generated by quasigeostropic forcing from positive temperature or vorticity advection associated with low-pressure centres. HLES is produced by planetary boundary layer (PBL) convection that is initiated as a result of cold and dry continental air mass advecting over relatively warm lakes and generating turbulent moisture and heat fluxes into the PBL. HLES events can have disastrous impacts on local communities such as the November 2014 Buffalo storm that caused 13 fatalities. Albeit the many HLES studies, most are focused on specific case study events with a discernible under examination of climatological HLES trend analyses for the Canadian GLB. The research objectives are to first determine the historical, climatological trends in monthly snowfall totals and to examine potential surface and atmospheric variables driving the resultant changes in HLES. The second aims to analyze the historical extremes in snowfall by assessing the intensity, frequency, and duration of snowfall within the domain of interest. Spatiotemporal snowfall and precipitation trends are computed for the 1982 to 2015 period using Daymet (Version 3) monthly gridded observational datasets from the Oak Ridge National Laboratory. The North American Regional Reanalysis (NARR), NOAA Optimum Interpolation Sea Surface Temperature (OISST), and the Canadian Ice Service (CIS) datasets are also used for evaluating trends in HLES driving variables such as air temperature, lake surface temperature (LST), ice cover concentration, omega, and vertical temperature gradient (VTGlst-850). Climatological trends in monthly snowfall totals show a significant decrease along the Ontario snowbelt of Lake Superior, Lake Huron and Georgian Bay at the 90 percent confidence level. These results are attributed to significant warming in LST, significant decrease in ice cover fraction, and an increase in VTGlst-850, which enhances evaporation into the lower PBL. It is suggested that inefficient moisture recycling and increase moisture storage in warmer air masses inhibits the development of HLES. The 99th percentile of snowfall events within the GLB suggests an extreme snowfall value equal to or exceeding 15 cm per day. Spatiotemporal snowfall patterns indicate that mostly lake effect processes and not extratropical cyclones drive the high intensity, frequency, and duration of these extreme events over the GLB. Furthermore, the Canadian snowbelt region of Lake Huron and Lake Superior exhibit different spatiotemporal trends in snowfall extremes but, even within a particular snowbelt region, trends in extreme snowfall are not spatially coherent. It is suggested that geographic location of the lakes, topography, lake bathymetry, and lake orientation can influence local and large scale surface-atmosphere variables.

Disentangling the relative role of climate change on tree growth in an extreme Mediterranean environment.

PubMed

Madrigal-González, Jaime; Andivia, Enrique; Zavala, Miguel A; Stoffel, Markus; Calatayud, Joaquín; Sánchez-Salguero, Raúl; Ballesteros-Cánovas, Juan

2018-06-14

Climate change can impair ecosystem functions and services in extensive dry forests worldwide. However, attribution of climate change impacts on tree growth and forest productivity is challenging due to multiple inter-annual patterns of climatic variability associated with atmospheric and oceanic circulations. Moreover, growth responses to rising atmospheric CO 2 , namely carbon fertilization, as well as size ontogenetic changes can obscure the climate change signature as well. Here we apply Structural Equation Models (SEM) to investigate the relative role of climate change on tree growth in an extreme Mediterranean environment (i.e., extreme in terms of the combination of sandy-unconsolidated soils and climatic aridity). Specifically, we analyzed potential direct and indirect pathways by which different sources of climatic variability (i.e. warming and precipitation trends, the North Atlantic Oscillation, [NAO]; the Mediterranean Oscillation, [MOI]; the Atlantic Mediterranean Oscillation, [AMO]) affect aridity through their control on local climate (in terms of mean annual temperature and total annual precipitation), and subsequently tree productivity, in terms of basal area increments (BAI). Our results support the predominant role of Diameter at Breast Height (DHB) as the main growth driver. In terms of climate, NAO and AMO are the most important drivers of tree growth through their control of aridity (via effects of precipitation and temperature, respectively). Furthermore and contrary to current expectations, our findings also support a net positive role of climate warming on growth over the last 50 years and suggest that impacts of climate warming should be evaluated considering multi-annual and multi-decadal periods of local climate defined by atmospheric and oceanic circulation in the North Atlantic. Copyright © 2018 Elsevier B.V. All rights reserved.

Bioclimatic changes and landslide recurrence in the mountainous region of Rio de Janeiro: are we ready to face the next landslide disaster?

NASA Astrophysics Data System (ADS)

Luiza Coelho Netto, Ana; Facadio, Ana Carolina; Pereira, Roberta; Lima, Pedro Henrique

2017-04-01

Paleo-environmental studies point out an alternation of wet and dry periods during the Holocene in southeastern Brazil, marked by the expansion and retraction of the humid tropical rainforest in alternation with the campos de altitude vegetation ('high altitude grassland'); successive episodes of natural fire were recorded from 10,000 to 4,000 years BP in the mountainous region of SE-Brazil, reflecting warm-dry conditions. Present seasonal climatic variability is indicated by an increasing dry spell frequency throughout the XX and early XXI centuries together with an increasing rainfall concentration in the summer when extreme daily totals (above 100 mm) become progressively more frequent. Historical land use changes, at both regional and local scales, are mostly related to this climatic variability. Therefore extreme rainfall induced landslides have been responsible for severe disasters as recorded along the Atlantic slopes of Serra do Mar. The extreme one occurred in January 2011, affecting the municipalities of Nova Friburgo, Teresópolis and Petrópolis. Studies in Nova Friburgo shown the occurrence of 3.622 landslides scars within an area of 421 km2; this rainfall event reached the expected average monthly rainfall (300 mm) in less than 10 hours. The D'Antas creek basin (53 km2) was the most affected area by landslides; 86% of 326 scars where associated with shallow translational mechanisms among which 67% occurred within shallow concave up topographic hollows of 32° slope angle in average. Most of these landslide scars occurred in granite rocks and degraded vegetation due to historical land use changes (last 200 years) including secondary forest (64%) and grasslands (25%). The present-day association between extreme rainfall induced landslides and human induced vegetation changes seem to reflect similar geomorphic responses to natural Holocene bioclimatic changes; a common phenomenon between the two periods is fire (natural fire in the past time and man-induced fire nowadays). Despite all field evidences on the relevance of landslides on hillslope evolution in the mountainous domain, local communities at risk and governmental institutions are not yet ready to face the next extreme rain event. Since November 2014 a new governance and risk management model has been developed in the Córrego D'Antas basin, through a multi-institutional network integrating local communities, university and governmental institutions as will be presented in this paper.

Astrophysical ZeV acceleration in the relativistic jet from an accreting supermassive blackhole

NASA Astrophysics Data System (ADS)

Ebisuzaki, Toshikazu; Tajima, Toshiki

2014-04-01

An accreting supermassive blackhole, the central engine of active galactic nucleus (AGN), is capable of exciting extreme amplitude Alfven waves whose wavelength (wave packet) size is characterized by its clumpiness. The pondermotive force and wakefield are driven by these Alfven waves propagating in the AGN (blazar) jet, and accelerate protons/nuclei to extreme energies beyond Zetta-electron volt (ZeV=1021 eV). Such acceleration is prompt, localized, and does not suffer from the multiple scattering/bending enveloped in the Fermi acceleration that causes excessive synchrotron radiation loss beyond 1019 eV. The production rate of ZeV cosmic rays is found to be consistent with the observed gamma-ray luminosity function of blazars and their time variabilities.

Characteristics of Extreme Geoelectric Fields and Their Possible Causes: Localized Peak Enhancements

NASA Astrophysics Data System (ADS)

Pulkkinen, A. A.; Ngwira, C. M.; Bernabeu, E.; Eichner, J.; Viljanen, A.; Crowley, G.

2015-12-01

One of the major challenges pertaining to extreme geomagnetic storms is to understand the basic processes associated with the development of dynamic magnetosphere-ionosphere currents, which generate large induced surface geoelectric fields. Previous studies point out the existence of localized peak geoelectric field enhancements during extreme storms. We examined induced global geoelectric fields derived from ground-based magnetometer recordings for 12 extreme geomagnetic storms between the years 1982--2005. However for the present study, an in-depth analysis was performed for two important extreme storms, October 29, 2003 and March 13, 1989. The primary purpose of this paper is to provide further evidence on the existence of localized peak geoelectric field enhancements, and to show that the structure of the geoelectric field during these localized extremes at single sites can differ greatly from globally and regionally averaged fields. Although the physical processes that govern the development of these localized extremes are still not clear, we discuss some possible causes.

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

Factors associated with the deposition of Cladophora on Lake Michigan beaches in 2012

USGS Publications Warehouse

Riley, Stephen C.; Tucker, Taaja R.; Adams, Jean V.; Fogarty, Lisa R.; Lafrancois, Brenda Moraska

2015-01-01

Deposition of the macroalgae Cladophora spp. was monitored on 18 beaches around Lake Michigan during 2012 at a high temporal frequency. We observed a high degree of spatial variability in Cladophora deposition among beaches on Lake Michigan, even within local regions, with no clear regional pattern in the intensity of Cladophora deposition. A strong seasonal pattern in Cladophora deposition was observed, with the heaviest deposition occurring during mid-summer. Several beaches exhibited high temporal variability in Cladophora deposition over short time scales, suggesting that drifting algal mats may be extremely dynamic in nearshore environments of the Great Lakes. Cladophora deposition on Lake Michigan beaches was primarily related to the presence of nearshore structures, local population density, and nearshore bathymetry. There was relatively little evidence that waves, winds, or currents were associated with Cladophora deposition on beaches, but this may be due to the relatively poor resolution of existing nearshore hydrodynamic data. Developing a predictive understanding of beach-cast Cladophora dynamics in Great Lakes environments may require both intensive Cladophora monitoring and fine-scale local hydrodynamic modeling efforts.

Spatio-Temporal Changes In Non-Extreme Precipitation Variability Over North America

NASA Astrophysics Data System (ADS)

Roque, S.

2016-12-01

Precipitation variability encompasses attributes associated with the sequencing and duration of events of the full range of magnitudes. However, climate change studies have largely focused on extreme events. Using analyses of long-term weather station data we show that high frequency events, such as fraction of wet days in a year and average duration of wet and dry periods, are undergoing significant changes across North America. The median increase in fraction of wet days in a year indicates that in 2010, North America experienced an additional 11 days of precipitation compared to 1960 (when the median number of wet days was 96), and wet periods that were 0.14 days longer than those in 1960 (when the median was 1.78 days). Further, these changes in high-frequency precipitation are more prevalent and larger than those associated with extremes. Such trends also exist for events of a range of magnitudes. Results reveal the existence of localized clusters with opposing trends to that of broader geographic variation, which illustrates the role of microclimate and other drivers of trends. Such hitherto unknown patterns have the potential to significantly inform our characterization of the resilience and vulnerability of a broad range of ecosystems, and agricultural and socio-economic systems. They can also set new benchmarks for climate model assessments.

Extreme Radio Flares and Associated X-Ray Variability from Young Stellar Objects in the Orion Nebula Cluster

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forbrich, Jan; Reid, Mark J.; Wolk, Scott J.

Young stellar objects are known to exhibit strong radio variability on timescales of weeks to months, and a few reports have documented extreme radio flares with at least an order of magnitude change in flux density on timescales of hours to days. However, there have been few constraints on the occurrence rate of such radio flares or on the correlation with pre-main sequence X-ray flares, although such correlations are known for the Sun and nearby active stars. Here we report simultaneous deep VLA radio and Chandra X-ray observations of the Orion Nebula Cluster, targeting hundreds of sources to look formore » the occurrence rate of extreme radio variability and potential correlation with the most extreme X-ray variability. We identify 13 radio sources with extreme radio variability, with some showing an order of magnitude change in flux density in less than 30 minutes. All of these sources show X-ray emission and variability, but we find clear correlations with extreme radio flaring only on timescales <1 hr. Strong X-ray variability does not predict the extreme radio sources and vice versa. Radio flares thus provide us with a new perspective on high-energy processes in YSOs and the irradiation of their protoplanetary disks. Finally, our results highlight implications for interferometric imaging of sources violating the constant-sky assumption.« less

The analysis of dependence between extreme rainfall and storm surge in the coastal zone

NASA Astrophysics Data System (ADS)

Zheng, F.; Westra, S.

2012-12-01

Flooding in coastal catchments can be caused by runoff generated by an extreme rainfall event, elevated sea levels due to an extreme storm surge event, or the combination of both processes occurring simultaneously or in close succession. Dependence in extreme rainfall and storm surge arises because common meteorological forcings often drive both variables; for example, cyclonic systems may produce extreme rainfall, strong onshore winds and an inverse barometric effect simultaneously, which the former factor influencing catchment discharge and the latter two factors influencing storm surge. Nevertheless there is also the possibility that only one of the variables is extreme at any given time, so that the dependence between rainfall and storm surge is not perfect. Quantification of the strength of dependence between these processes is critical in evaluating the magnitude of flood risk in the coastal zone. This may become more important in the future as the majority of the coastal areas are threatened by the sea level rise due to the climate change. This research uses the most comprehensive record of rainfall and storm surge along the coastline of Australia collected to-date to investigate the strength of dependence between the extreme rainfall and storm surge along the Australia coastline. A bivariate logistic threshold-excess model was employed to this end to carry out the dependence analysis. The strength of the estimated dependence is then evaluated as a function of several factors including: the distance between the tidal gauge and the rain gauge; the lag between the extreme precipitation event and extreme surge event; and the duration of the maximum storm burst. The results show that the dependence between the extreme rainfall and storm surge along the Australia coastline is statistically significant, although some locations clearly exhibit stronger dependence than others. We hypothesize that this is due to a combination of large-scale meteorological effects as well as local scale bathymetry. Additionally, significant dependence can be observed over spatial distances of up to several hundred kilometers, implying that meso-scale meteorological forcings may play an important role in driving the dependence. This is also consistent with the result which shows that significant dependence often remaining for lags of up to one or two days between extremal rainfall and storm surge events. The influence of storm burst duration can also be observed, with rainfall extremes lasting more than several hours typically being more closely associated with storm surge compared with sub-hourly rainfall extremes. These results will have profound implications for how flood risk is evaluated along the coastal zone in Australia, with the strength of dependence varying depending on: (1) the dominant meteorological conditions; (2) the local estuary configuration, influencing the strength of the surge; and (3) the catchment attributes, influencing the duration of the storm burst that will deliver the peak flood events. Although a strong random component remains, we show that the probability of an extreme storm surge during an extreme rainfall event (or vice versa) can be up to ten times greater than under the situation under which there is no dependence, suggesting that failure to account for these interactions can result in a substantial underestimation of flood risk.

High-grade extremity soft tissue sarcomas: factors predictive of local recurrence and its effect on morbidity and mortality.

PubMed

Eilber, Fritz C; Rosen, Gerald; Nelson, Scott D; Selch, Michael; Dorey, Frederick; Eckardt, Jeffery; Eilber, Frederick R

2003-02-01

To identify patient characteristics associated with the development of local recurrence and the effect of local recurrence on subsequent morbidity and mortality in patients with intermediate- to high-grade extremity soft tissue sarcomas. Numerous studies on extremity soft tissue sarcomas have consistently shown that presentation with locally recurrent disease is associated with the development of subsequent local recurrences and that large tumor size and high histologic grade are significant factors associated with decreased survival. However, the effect of local recurrence on patient survival remains unclear. From 1975 to 1997, 753 patients with intermediate- to high-grade extremity soft tissue sarcomas were treated at UCLA. Treatment outcomes and patient characteristics were analyzed to identify factors associated with both local recurrence and survival. Patients with locally recurrent disease were at a significantly increased risk of developing a subsequent local recurrence. Local recurrence was a morbid event requiring amputation in 38% of the cases. The development of a local recurrence was the most significant factor associated with decreased survival. Once a patient developed a local recurrence, he or she was about three times more likely to die of disease compared to similar patients who had not developed a local recurrence. Local recurrence in patients with intermediate- to high-grade extremity soft tissue sarcomas is associated with the development of subsequent local recurrences, a morbid event decreasing functional outcomes and the most significant factor associated with decreased survival. Although 85% to 90% of patients with high-grade extremity soft tissue sarcomas are treatable with a limb salvage approach, patients who develop a local recurrence need aggressive treatment and should be considered for trials of adjuvant systemic therapy.

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

NASA Astrophysics Data System (ADS)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

2017-06-01

The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

Sensitivity of UK butterflies to local climatic extremes: which life stages are most at risk?

PubMed

McDermott Long, Osgur; Warren, Rachel; Price, Jeff; Brereton, Tom M; Botham, Marc S; Franco, Aldina M A

2017-01-01

There is growing recognition as to the importance of extreme climatic events (ECEs) in determining changes in species populations. In fact, it is often the extent of climate variability that determines a population's ability to persist at a given site. This study examined the impact of ECEs on the resident UK butterfly species (n = 41) over a 37-year period. The study investigated the sensitivity of butterflies to four extremes (drought, extreme precipitation, extreme heat and extreme cold), identified at the site level, across each species' life stages. Variations in the vulnerability of butterflies at the site level were also compared based on three life-history traits (voltinism, habitat requirement and range). This is the first study to examine the effects of ECEs at the site level across all life stages of a butterfly, identifying sensitive life stages and unravelling the role life-history traits play in species sensitivity to ECEs. Butterfly population changes were found to be primarily driven by temperature extremes. Extreme heat was detrimental during overwintering periods and beneficial during adult periods and extreme cold had opposite impacts on both of these life stages. Previously undocumented detrimental effects were identified for extreme precipitation during the pupal life stage for univoltine species. Generalists were found to have significantly more negative associations with ECEs than specialists. With future projections of warmer, wetter winters and more severe weather events, UK butterflies could come under severe pressure given the findings of this study. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Functional genomics of physiological plasticity and local adaptation in killifish.

PubMed

Whitehead, Andrew; Galvez, Fernando; Zhang, Shujun; Williams, Larissa M; Oleksiak, Marjorie F

2011-01-01

Evolutionary solutions to the physiological challenges of life in highly variable habitats can span the continuum from evolution of a cosmopolitan plastic phenotype to the evolution of locally adapted phenotypes. Killifish (Fundulus sp.) have evolved both highly plastic and locally adapted phenotypes within different selective contexts, providing a comparative system in which to explore the genomic underpinnings of physiological plasticity and adaptive variation. Importantly, extensive variation exists among populations and species for tolerance to a variety of stressors, and we exploit this variation in comparative studies to yield insights into the genomic basis of evolved phenotypic variation. Notably, species of Fundulus occupy the continuum of osmotic habitats from freshwater to marine and populations within Fundulus heteroclitus span far greater variation in pollution tolerance than across all species of fish. Here, we explore how transcriptome regulation underpins extreme physiological plasticity on osmotic shock and how genomic and transcriptomic variation is associated with locally evolved pollution tolerance. We show that F. heteroclitus quickly acclimate to extreme osmotic shock by mounting a dramatic rapid transcriptomic response including an early crisis control phase followed by a tissue remodeling phase involving many regulatory pathways. We also show that convergent evolution of locally adapted pollution tolerance involves complex patterns of gene expression and genome sequence variation, which is confounded with body-weight dependence for some genes. Similarly, exploiting the natural phenotypic variation associated with other established and emerging model organisms is likely to greatly accelerate the pace of discovery of the genomic basis of phenotypic variation.

Functional Genomics of Physiological Plasticity and Local Adaptation in Killifish

PubMed Central

Galvez, Fernando; Zhang, Shujun; Williams, Larissa M.; Oleksiak, Marjorie F.

2011-01-01

Evolutionary solutions to the physiological challenges of life in highly variable habitats can span the continuum from evolution of a cosmopolitan plastic phenotype to the evolution of locally adapted phenotypes. Killifish (Fundulus sp.) have evolved both highly plastic and locally adapted phenotypes within different selective contexts, providing a comparative system in which to explore the genomic underpinnings of physiological plasticity and adaptive variation. Importantly, extensive variation exists among populations and species for tolerance to a variety of stressors, and we exploit this variation in comparative studies to yield insights into the genomic basis of evolved phenotypic variation. Notably, species of Fundulus occupy the continuum of osmotic habitats from freshwater to marine and populations within Fundulus heteroclitus span far greater variation in pollution tolerance than across all species of fish. Here, we explore how transcriptome regulation underpins extreme physiological plasticity on osmotic shock and how genomic and transcriptomic variation is associated with locally evolved pollution tolerance. We show that F. heteroclitus quickly acclimate to extreme osmotic shock by mounting a dramatic rapid transcriptomic response including an early crisis control phase followed by a tissue remodeling phase involving many regulatory pathways. We also show that convergent evolution of locally adapted pollution tolerance involves complex patterns of gene expression and genome sequence variation, which is confounded with body-weight dependence for some genes. Similarly, exploiting the natural phenotypic variation associated with other established and emerging model organisms is likely to greatly accelerate the pace of discovery of the genomic basis of phenotypic variation. PMID:20581107

Effect of active arm swing to local dynamic stability during walking.

PubMed

Wu, Yu; Li, Yue; Liu, An-Min; Xiao, Fei; Wang, Yin-Zhi; Hu, Fei; Chen, Jin-Ling; Dai, Ke-Rong; Gu, Dong-Yun

2016-02-01

Arm swing is an essential component in regulating dynamic stability of the whole body during walking, while the contribution of active arm swing to local dynamic stability of different motion segments remains unclear. This study investigated the effects of arm swing under natural arm swing condition and active arm swing condition on local dynamic stability and gait variability of the trunk segments (C7 and T10 joint) and lower extremity joints (hip, knee and ankle joint). The local divergence exponents (λs) and mean standard deviation over strides (MeanSD) of 24 young healthy adults were calculated while they were walking on treadmill with two arm swing conditions at their preferred walking speed (PWS). We found that in medial-lateral direction, both λs and MeanSD values of the trunk segments (C7 and T10 joint) in active arm swing condition were significantly lower than those in natural arm swing condition (p<0.05), while no significant difference of λs or MeanSD in lower extremity joints (hip, knee and ankle joint) was found between two arm swing conditions (p>0.05, respectively). In anterior-posterior and vertical direction, neither λs nor MeanSD values of all body segments showed significant difference between two arm swing conditions (p>0.05, respectively). These findings indicate that active arm swing may help to improve the local dynamic stability of the trunk segments in medial-lateral direction. Copyright © 2015 Elsevier B.V. All rights reserved.

A reconstruction of sea surface temperature variability in the southeastern Gulf of Mexico from 1734 to 2008 C.E. using cross-dated Sr/Ca records from the coral Siderastrea siderea

NASA Astrophysics Data System (ADS)

DeLong, Kristine L.; Flannery, Jennifer A.; Poore, Richard Z.; Quinn, Terrence M.; Maupin, Christopher R.; Lin, Ke; Shen, Chuan-Chou

2014-05-01

This study uses skeletal variations in coral Sr/Ca from three Siderastrea siderea coral colonies within the Dry Tortugas National Park in the southeastern Gulf of Mexico (24°42'N, 82°48'W) to reconstruct monthly sea surface temperature (SST) variations from 1734 to 2008 Common Era (C.E.). Calibration and verification of the replicated coral Sr/Ca-SST reconstruction with local, regional, and historical temperature records reveals that this proxy-temperature relationship is stable back to 1879 C.E. The coral SST reconstruction contains robust interannual ( 2.0°C) and multidecadal variability ( 1.5°C) for the past 274 years, the latter of which does not covary with the Atlantic Multidecadal Oscillation. Winter SST extremes are more variable than summer SST extremes (±2.2°C versus ±1.6°C, 2σ) suggesting that Loop Current transport in the winter dominates variability on interannual and longer time scales. Summer SST maxima are increasing (+1.0°C for 274 years, σMC = ±0.5°C, 2σ), whereas winter SST minima contain no significant trend. Colder decades ( 1.5°C) during the Little Ice Age (LIA) do not coincide with decades of sunspot minima. The coral SST reconstruction contains similar variability to temperature reconstructions from the northern Gulf of Mexico (planktic foraminifer Mg/Ca) and the Caribbean Sea (coral Sr/Ca) suggesting areal reductions in the Western Hemisphere Warm Pool during the LIA. Mean summer coral SST extremes post-1985 C.E. (29.9°C) exceeds the long-term summer average (29.2°C for 1734-2008 C.E.), yet the warming trend after 1985 C.E. (0.04°C for 24 years, σMC = ±0.5, 2σ) is not significant, whereas Caribbean coral Sr/Ca studies contain a warming trend for this interval.

Performance of the IRI-2007 Model for Equatorial Topside Ion Density in the African Sector for Low and Extremely Low Solar Activity

NASA Technical Reports Server (NTRS)

Klenzing, J.; Simoes, F.; Ivanov, S.; Bilitza, D.; Heelis, R. A.; Rowland, D.

2012-01-01

The recent availability of new data sets during the recent extreme solar minimum provides an opportunity for testing the performance of the International Reference Ionosphere in historically under-sampled regions. This study will present averages and variability of topside ionospheric densities over Africa as a function of season, local time, altitude, and magnetic dip latitude as measured by the Coupled Ion-Neutral Dynamics Investigation (CINDI) Mission of Opportunity on the C/NOFS satellite. The results will be compared to the three topside model options available in IRI-2007. Overall, the NeQuick model is found to have the best performance, though during the deepest part of the solar minimum all three options significantly overestimate density.

A quantitative microscopic approach to predict local recurrence based on in vivo intraoperative imaging of sarcoma tumor margins

PubMed Central

Mueller, Jenna L.; Fu, Henry L.; Mito, Jeffrey K.; Whitley, Melodi J.; Chitalia, Rhea; Erkanli, Alaattin; Dodd, Leslie; Cardona, Diana M.; Geradts, Joseph; Willett, Rebecca M.; Kirsch, David G.; Ramanujam, Nimmi

2015-01-01

The goal of resection of soft tissue sarcomas located in the extremity is to preserve limb function while completely excising the tumor with a margin of normal tissue. With surgery alone, one-third of patients with soft tissue sarcoma of the extremity will have local recurrence due to microscopic residual disease in the tumor bed. Currently, a limited number of intraoperative pathology-based techniques are used to assess margin status; however, few have been widely adopted due to sampling error and time constraints. To aid in intraoperative diagnosis, we developed a quantitative optical microscopy toolbox, which includes acriflavine staining, fluorescence microscopy, and analytic techniques called sparse component analysis and circle transform to yield quantitative diagnosis of tumor margins. A series of variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. For comparison, if pathology was used to predict local recurrence in this data set, it would achieve a sensitivity of 29% and a specificity of 71%. These results indicate a robust approach for detecting microscopic residual disease, which is an effective predictor of local recurrence. PMID:25994353

Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil.

PubMed

Eugenio, Fernando Coelho; dos Santos, Alexandre Rosa; Fiedler, Nilton Cesar; Ribeiro, Guido Assunção; da Silva, Aderbal Gomes; dos Santos, Áureo Banhos; Paneto, Greiciane Gaburro; Schettino, Vitor Roberto

2016-05-15

A forest fire risk map is a basic element for planning and protecting forested areas. The main goal of this study was to develop a statistical model for preparing a forest fire risk map using GIS. Such model is based on assigning weights to nine variables divided into two classes: physical factors of the site (terrain slope, land-use/occupation, proximity to roads, terrain orientation, and altitude) and climatic factors (precipitation, temperature, water deficit, and evapotranspiration). In regions where the climate is different from the conditions of this study, the model will require an adjustment of the variables weights according to the local climate. The study area, Espírito Santo State, exhibited approximately 3.81% low risk, 21.18% moderate risk, 30.10% high risk, 41.50% very high risk, and 3.40% extreme risk of forest fire. The areas classified as high risk, very high and extreme, contemplated a total of 78.92% of heat spots. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detection of the relationship between peak temperature and extreme precipitation

NASA Astrophysics Data System (ADS)

Yu, Y.; Liu, J.; Zhiyong, Y.

2017-12-01

Under the background of climate change and human activities, the characteristics and pattern of precipitation have changed significantly in many regions. As the political and cultural center of China, the structure and character of precipitation in Jingjinji District has varied dramatically in recent years. In this paper, the daily precipitation data throughout the period 1960-2013 are selected for analyzing the spatial-temporal variability of precipitation. The results indicate that the frequency and intensity of precipitation presents an increasing trend. Based on the precipitation data, the maximum, minimum and mean precipitation in different temporal and spatial scales is calculated respectively. The temporal and spatial variation of temperature is obtained by using statistical methods. The relationship between temperature and precipitation in different range is analyzed. The curve relates daily precipitation extremes with local temperatures has a peak structure, increasing at the low-medium range of temperature variations but decreasing at high temperatures. The relationship between extreme precipitation is stronger in downtown than that in suburbs.

Coping with droughts and floods: A Case study of Kanyemba, Mbire District, Zimbabwe

NASA Astrophysics Data System (ADS)

Bola, G.; Mabiza, C.; Goldin, J.; Kujinga, K.; Nhapi, I.; Makurira, H.; Mashauri, D.

Most of Southern Africa is affected by extreme weather events, droughts and floods being the most common. The frequency of floods and droughts in Southern Africa in general, of which the Zambezi River Basin is part of, has been linked to climate change. Droughts and floods impact on the natural environment, and directly and indirectly impact on livelihoods. In the Middle Zambezi River Basin, which is located between Kariba and Cahora Bassa dams, extreme weather events are exacerbated by human activities, in particular the operation of both the Kariba and the Cahora Bassa reservoirs. To understand better, whether, and in what ways extreme weather events impact on livelihoods, this study used both quantitative and qualitative research methods to analyse rainfall variability and coping strategies used by households in the river basin. Data collection was done using semi-structured interviews, focus group discussions and structured questionnaires which were administered to 144 households. An analysis of rainfall variability and Cahora Bassa water level over 23 years was carried out. The study found that perceptions of households were that average rainfall has decreased over the years, and dry-spells have become more frequent. Furthermore, households perceived flood events to have increased over the last two decades. However, the analysis of rainfall variability revealed that the average rainfall received between 1988 and 2011 had not changed but the frequency of dry-spells and floods had increased. The occurrence of floods in the study area was found to be linked to heavy local rain and backflow from Cahora Bassa dam. The study found that households adopted a number of strategies to cope with droughts and floods, such as vegetable farming and crop production in the floodplain, taking on local jobs that brought in wages, planting late and livestock disposals. Some households also resorted to out-migration on a daily basis to Zambia or Mozambique. The study concluded that coping mechanisms were found to be inflexible and poorly suited to adapt to floods and droughts. The study recommends the implementation of adaptation measures such as the cultivation of drought-resistant crop varieties, irrigation and off-farm employment opportunities.

Extreme weather conditions reduce the CO2 fertilization effect in temperate C3 grasslands

NASA Astrophysics Data System (ADS)

Obermeier, Wolfgang; Lehnert, Lukas; Kammann, Claudia; Müller, Christoph; Grünhage, Ludger; Luterbacher, Jürg; Erbs, Martin; Yuan, Naiming; Bendix, Jörg

2016-04-01

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of global climate change. The rising atmospheric carbon dioxide (CO2) concentrations may stimulate plant photosynthesis and, thus, cause a net sink effect in the global carbon cycle. As a consequence of an enhanced photosynthesis, an increase in the net primary productivity (NPP) of C3 plants (termed CO2 fertilization) is widely assumed. This process is associated with a reduced stomatal conductance of leaves as the carbon demand of photosynthesis is met earlier. This causes a higher water-use efficiency and, hence, may reduce water stress in plants exposed to elevated CO2 concentrations ([eCO2]). However, the magnitude and persistence of the CO2 fertilization effect under a future climate including more frequent weather extremes are controversial. To test the CO2 fertilization effect for Central European grasslands, a data set comprising 16 years of biomass samples and environmental variables such as local weather and soil conditions was analysed by means of a novel approach. The data set was recorded on a "Free Air Carbon dioxide Enrichment" (FACE) experimental site which allows to quantify the CO2 fertilization effect under naturally occurring climate variations. The results indicate that the CO2 fertilization effect on the aboveground biomass is strongest under local average environmental conditions. Such intermediate regimes were defined by the mean +/- 1 standard deviation of the long-term average in the respective variable three months before harvest. The observed CO2 fertilization effect was reduced or vanished under drier, wetter and hotter conditions when the respective variable exceeded the bounds of the intermediate regimes. Comparable conditions, characterized by a higher frequency of more extreme weather conditions, are predicted for the future by climate projections. Consequently, biogeochemical models may overestimate the future NPP sink capacity of temperate C3 grasslands. Because temperate grasslands represent an important part of the Earth's terrestrial surface and therefore the global carbon cycle, atmospheric CO2 concentrations [CO2] might increase faster than currently expected.

Forecasting European Wildfires Today and in the Future

NASA Astrophysics Data System (ADS)

Navarro Abellan, Maria; Porras Alegre, Ignasi; María Sole, Josep; Gálvez, Pedro; Bielski, Conrad; Nurmi, Pertti

2017-04-01

Society as a whole is increasingly exposed and vulnerable to natural disasters due to extreme weather events exacerbated by climate change. The increased frequency of wildfires is not only a result of a changing climate, but wildfires themselves also produce a significant amount of greenhouse gases that, in-turn, further contribute to global warming. I-REACT (Improving Resilience to Emergencies through Advanced Cyber Technologies) is an innovation project funded by the European Commission , which aims to use social media, smartphones and wearables to improve natural disaster management by integrating existing services, both local and European, into a platform that supports the entire emergency management cycle. In order to assess the impact of climate change on wildfire hazards, METEOSIM designed two different System Processes (SP) that will be integrated into the I-REACT service that can provide information on a variety of time scales. SP1 - Climate Change Impact The climate change impact on climate variables related to fires is calculated by building an ensemble based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CORDEX data. A validation and an Empirical-Statistical Downscaling (ESD) calibration are done to assess the changes in the past of the climatic variables related to wildfires (temperature, precipitation, wind, relative humidity and Fire Weather Index). Calculations in the trend and the frequency of extreme events of those variables are done for three time scales: near-term (2011-2040), mid-term (2041-2070) and long term (2071-2100). SP2 - Operational daily forecast of the Canadian Forest Fire Weather Index (FWI) Using ensemble data from the ECMWF and from the GLAMEPS (multi-model ensemble) models, both supplied by the Finnish Meteorological Institute (FMI), the Fire Weather Index (FWI) and its index components are produced for each ensemble member within a wide forecast time range, from a few hours up to 10 days resulting in a probabilistic output of the FWI for different regions in Europe. This work will improve the currently available information to various wildfire information users such as fire departments, the civil protection, local authorities, etc., where accurate and reliable information in extreme weather situations are vital for improving planning and risk management.

Food Price Volatility and Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Brown, M. E.

2013-12-01

The agriculture system is under pressure to increase production every year as global population expands and more people move from a diet mostly made up of grains, to one with more meat, dairy and processed foods. Weather shocks and large changes in international commodity prices in the last decade have increased pressure on local food prices. This paper will review several studies that link climate variability as measured with satellite remote sensing to food price dynamics in 36 developing countries where local monthly food price data is available. The focus of the research is to understand how weather and climate, as measured by variations in the growing season using satellite remote sensing, has affected agricultural production, food prices and access to food in agricultural societies. Economies are vulnerable to extreme weather at multiple levels. Subsistence small holders who hold livestock and consume much of the food they produce are vulnerable to food production variability. The broader society, however, is also vulnerable to extreme weather because of the secondary effects on market functioning, resource availability, and large-scale impacts on employment in trading, trucking and wage labor that are caused by weather-related shocks. Food price variability captures many of these broad impacts and can be used to diagnose weather-related vulnerability across multiple sectors. The paper will trace these connections using market-level data and analysis. The context of the analysis is the humanitarian aid community, using the guidance of the USAID Famine Early Warning Systems Network and the United Nation's World Food Program in their response to food security crises. These organizations have worked over the past three decades to provide baseline information on food production through satellite remote sensing data and agricultural yield models, as well as assessments of food access through a food price database. Econometric models and spatial analysis are used to describe the connection between shocks and food prices, and to demonstrate the importance of these metrics in overall outcomes in food-insecure communities.

Prognostic Factors and Expression of MDM2 in Patients with Primary Extremity Liposarcoma

PubMed Central

Júnior, Rosalvo Zósimo Bispo; de Camargo, Olavo Pires; de Oliveira, Cláudia Regina G. C. M.; Filippi, Renée Zon; Baptista, André Mathias; Caiero, Marcelo Tadeu

2008-01-01

OBJECTIVE The objective of this study was to investigate MDM2 (murine double minute 2) protein expression and evaluate its relationship with some anatomical and pathological aspects, aiming also to identify prognostic factors concerning local recurrence-free survival, metastasis-free survival and overall survival in patients with primary liposarcomas of the extremities. MATERIALS AND METHODS Of 50 patients with primary liposarcomas of the extremities admitted to a Reference Service, between 1968 and 2004, 25 were enrolled in the study, following eligibility and exclusion criteria. RESULTS The adverse factors that influenced the risk for local recurrence in the univariant analysis included male sex (P = 0.023), pleomorphic histological subtype (P = 0.027), and high histological grade (P = 0.007). Concerning metastasis-free survival, age less than 50 years (P = 0.040), male sex (P = 0.040), pleomorphic subtype (P < 0.001), and high histological grade (P = 0.003) had a worse prognosis. Adverse factors for overall survival were age under 50 years (P = 0.040), male sex (P = 0.040), pleomorphic subtype (P < 0.001), and high histological grade (P = 0.003). CONCLUSIONS There was no correlation between immunohistochemically observed MDM2 protein expressions and the anatomical and pathological variables studied. The immunohistochemical expression of MDM2 protein was not considered to have a prognostic value for any of the surviving patients in this study (local recurrence-free survival, metastasis-free survival, or overall survival). The immunoexpression of MDM2 protein was a frequent event in the different subtypes of liposarcomas. PMID:18438568

Broad Hβ Emission-line Variability in a Sample of 102 Local Active Galaxies

NASA Astrophysics Data System (ADS)

Runco, Jordan N.; Cosens, Maren; Bennert, Vardha N.; Scott, Bryan; Komossa, S.; Malkan, Matthew A.; Lazarova, Mariana S.; Auger, Matthew W.; Treu, Tommaso; Park, Daeseong

2016-04-01

A sample of 102 local (0.02 ≤ z ≤ 0.1) Seyfert galaxies with black hole masses MBH > 107M⊙ was selected from the Sloan Digital Sky Survey (SDSS) and observed using the Keck 10 m telescope to study the scaling relations between MBH and host galaxy properties. We study profile changes of the broad Hβ emission line within the three to nine year time frame between the two sets of spectra. The variability of the broad Hβ emission line is of particular interest, not only because it is used to estimate MBH, but also because its strength and width are used to classify Seyfert galaxies into different types. At least some form of broad-line variability (in either width or flux) is observed in the majority (∼66%) of the objects, resulting in a Seyfert-type change for ∼38% of the objects, likely driven by variable accretion and/or obscuration. The broad Hβ line virtually disappears in 3/102 (∼3%) extreme cases. We discuss potential causes for these changing look active galactic nuclei. While similar dramatic transitions have previously been reported in the literature, either on a case-by-case basis or in larger samples focusing on quasars at higher redshifts, our study provides statistical information on the frequency of Hβ line variability in a sample of low-redshift Seyfert galaxies.

Mesoscale disturbance and ecological response to decadal climatic variability in the American Southwest

USGS Publications Warehouse

Swetnam, T.W.; Betancourt, J.L.

1998-01-01

Ecological responses to climatic variability in the Southwest include regionally synchronized fires, insect outbreaks, and pulses in tree demography (births and deaths). Multicentury, tree-ring reconstructions of drought, disturbance history, and tree demography reveal climatic effects across scales, from annual to decadal, and from local (<102 km2) to mesoscale (104-106 km2). Climate-disturbance relations are more variable and complex than previously assumed. During the past three centuries, mesoscale outbreaks of the western spruce budworm (Choristoneura occidentalis) were associated with wet, not dry episodes, contrary to conventional wisdom. Regional fires occur during extreme droughts but, in some ecosystems, antecedent wet conditions play a secondary role by regulating accumulation of fuels. Interdecadal changes in fire-climate associations parallel other evidence for shifts in the frequency or amplitude of the Southern Oscillation (SO) during the past three centuries. High interannual, fire-climate correlations (r = 0.7 to 0.9) during specific decades (i.e., circa 1740-80 and 1830-60) reflect periods of high amplitude in the SO and rapid switching from extreme wet to dry years in the Southwest, thereby entraining fire occurrence across the region. Weak correlations from 1780 to 1830 correspond with a decrease in SO frequency or amplitude inferred from independent tree-ring width, ice core, and coral isotope reconstructions. Episodic dry and wet episodes have altered age structures and species composition of woodland and conifer forests. The scarcity of old, living conifers established before circa 1600 suggests that the extreme drought of 1575-95 had pervasive effects on tree populations. The most extreme drought of the past 400 years occurred in the mid-twentieth century (1942-57). This drought resulted in broadscale plant dieoffs in shrublands, woodlands, and forests and accelerated shrub invasion of grasslands. Drought conditions were broken by the post-1976 shift to the negative SO phase and wetter cool seasons in the Southwest. The post-1976 period shows up as an unprecedented surge in tree-ring growth within millennia-length chronologies. This unusual episode may have produced a pulse in tree recruitment and improved rangeland conditions (e.g., higher grass production), though additional study is needed to disentangle the interacting roles of land use and climate. The 1950s drought and the post-1976 wet period and their aftermaths offer natural experiments to study long-term ecosystem response to interdecadal climate variability.Ecological responses to climatic variability in the Southwest include regionally synchronized fires, insect outbreaks, and pulses in tree demography (births and deaths). Multicentury, tree-ring reconstructions of drought, disturbance history, and tree demography reveal climatic effects across scales, from annual to decadal, and from local (<102 km2) to mesoscale (104-106 km2). Climate-disturbance relations are more variable and complex than previously assumed. During the past three centuries, mesoscale outbreaks of the western spruce budworm (Choristoneura occidentalis) were associated with wet, not dry episodes, contrary to conventional wisdom. Regional fires occur during extreme droughts but, in some ecosystems, antecedent wet conditions play a secondary role by regulating accumulation of fuels. Interdecadal changes in fire-climate associations parallel other evidence for shifts in the frequency or amplitude of the Southern Oscillation (SO) during the past three centuries. High interannual, fire-climate correlations (r = 0.7 to 0.9) during specific decades (i.e., circa 1740-80 and 1830-60) reflect periods of high amplitude in the SO and rapid switching from extreme wet to dry years in the Southwest, thereby entraining fire occurrence across the region. Weak correlations from 1780 to 1830 correspond with a decrease in SO frequency or amplitude inferred from independent tree-ring width, ic

Exploring Local Approaches to Communicating Global Climate Change Information

NASA Astrophysics Data System (ADS)

Stevermer, A. J.

2002-12-01

Expected future climate changes are often presented as a global problem, requiring a global solution. Although this statement is accurate, communicating climate change science and prospective solutions must begin at local levels, each with its own subset of complexities to be addressed. Scientific evaluation of local changes can be complicated by large variability occurring over small spatial scales; this variability hinders efforts both to analyze past local changes and to project future ones. The situation is further encumbered by challenges associated with scientific literacy in the U.S., as well as by pressing economic difficulties. For people facing real-life financial and other uncertainties, a projected ``1.4 to 5.8 degrees Celsius'' rise in global temperature is likely to remain only an abstract concept. Despite this lack of concreteness, recent surveys have found that most U.S. residents believe current global warming science, and an even greater number view the prospect of increased warming as at least a ``somewhat serious'' problem. People will often be able to speak of long-term climate changes in their area, whether observed changes in the amount of snow cover in winter, or in the duration of extreme heat periods in summer. This work will explore the benefits and difficulties of communicating climate change from a local, rather than global, perspective, and seek out possible strategies for making less abstract, more concrete, and most importantly, more understandable information available to the public.

Extreme temperature events on Greenland in observations and the MAR regional climate model

NASA Astrophysics Data System (ADS)

Leeson, Amber A.; Eastoe, Emma; Fettweis, Xavier

2018-03-01

Meltwater from the Greenland Ice Sheet contributed 1.7-6.12 mm to global sea level between 1993 and 2010 and is expected to contribute 20-110 mm to future sea level rise by 2100. These estimates were produced by regional climate models (RCMs) which are known to be robust at the ice sheet scale but occasionally miss regional- and local-scale climate variability (e.g. Leeson et al., 2017; Medley et al., 2013). To date, the fidelity of these models in the context of short-period variability in time (i.e. intra-seasonal) has not been fully assessed, for example their ability to simulate extreme temperature events. We use an event identification algorithm commonly used in extreme value analysis, together with observations from the Greenland Climate Network (GC-Net), to assess the ability of the MAR (Modèle Atmosphérique Régional) RCM to reproduce observed extreme positive-temperature events at 14 sites around Greenland. We find that MAR is able to accurately simulate the frequency and duration of these events but underestimates their magnitude by more than half a degree Celsius/kelvin, although this bias is much smaller than that exhibited by coarse-scale Era-Interim reanalysis data. As a result, melt energy in MAR output is underestimated by between 16 and 41 % depending on global forcing applied. Further work is needed to precisely determine the drivers of extreme temperature events, and why the model underperforms in this area, but our findings suggest that biases are passed into MAR from boundary forcing data. This is important because these forcings are common between RCMs and their range of predictions of past and future ice sheet melting. We propose that examining extreme events should become a routine part of global and regional climate model evaluation and that addressing shortcomings in this area should be a priority for model development.

Dynamical properties and extremes of Northern Hemisphere climate fields over the past 60 years

NASA Astrophysics Data System (ADS)

Faranda, Davide; Messori, Gabriele; Alvarez-Castro, M. Carmen; Yiou, Pascal

2017-12-01

Atmospheric dynamics are described by a set of partial differential equations yielding an infinite-dimensional phase space. However, the actual trajectories followed by the system appear to be constrained to a finite-dimensional phase space, i.e. a strange attractor. The dynamical properties of this attractor are difficult to determine due to the complex nature of atmospheric motions. A first step to simplify the problem is to focus on observables which affect - or are linked to phenomena which affect - human welfare and activities, such as sea-level pressure, 2 m temperature, and precipitation frequency. We make use of recent advances in dynamical systems theory to estimate two instantaneous dynamical properties of the above fields for the Northern Hemisphere: local dimension and persistence. We then use these metrics to characterize the seasonality of the different fields and their interplay. We further analyse the large-scale anomaly patterns corresponding to phase-space extremes - namely time steps at which the fields display extremes in their instantaneous dynamical properties. The analysis is based on the NCEP/NCAR reanalysis data, over the period 1948-2013. The results show that (i) despite the high dimensionality of atmospheric dynamics, the Northern Hemisphere sea-level pressure and temperature fields can on average be described by roughly 20 degrees of freedom; (ii) the precipitation field has a higher dimensionality; and (iii) the seasonal forcing modulates the variability of the dynamical indicators and affects the occurrence of phase-space extremes. We further identify a number of robust correlations between the dynamical properties of the different variables.

An extreme magneto-ionic environment associated with the fast radio burst source FRB 121102

NASA Astrophysics Data System (ADS)

Michilli, D.; Seymour, A.; Hessels, J. W. T.; Spitler, L. G.; Gajjar, V.; Archibald, A. M.; Bower, G. C.; Chatterjee, S.; Cordes, J. M.; Gourdji, K.; Heald, G. H.; Kaspi, V. M.; Law, C. J.; Sobey, C.; Adams, E. A. K.; Bassa, C. G.; Bogdanov, S.; Brinkman, C.; Demorest, P.; Fernandez, F.; Hellbourg, G.; Lazio, T. J. W.; Lynch, R. S.; Maddox, N.; Marcote, B.; McLaughlin, M. A.; Paragi, Z.; Ransom, S. M.; Scholz, P.; Siemion, A. P. V.; Tendulkar, S. P.; van Rooy, P.; Wharton, R. S.; Whitlow, D.

2018-01-01

Fast radio bursts are millisecond-duration, extragalactic radio flashes of unknown physical origin. The only known repeating fast radio burst source—FRB 121102—has been localized to a star-forming region in a dwarf galaxy at redshift 0.193 and is spatially coincident with a compact, persistent radio source. The origin of the bursts, the nature of the persistent source and the properties of the local environment are still unclear. Here we report observations of FRB 121102 that show almost 100 per cent linearly polarized emission at a very high and variable Faraday rotation measure in the source frame (varying from +1.46 × 105 radians per square metre to +1.33 × 105 radians per square metre at epochs separated by seven months) and narrow (below 30 microseconds) temporal structure. The large and variable rotation measure demonstrates that FRB 121102 is in an extreme and dynamic magneto-ionic environment, and the short durations of the bursts suggest a neutron star origin. Such large rotation measures have hitherto been observed only in the vicinities of massive black holes (larger than about 10,000 solar masses). Indeed, the properties of the persistent radio source are compatible with those of a low-luminosity, accreting massive black hole. The bursts may therefore come from a neutron star in such an environment or could be explained by other models, such as a highly magnetized wind nebula or supernova remnant surrounding a young neutron star.

An extreme magneto-ionic environment associated with the fast radio burst source FRB 121102.

PubMed

Michilli, D; Seymour, A; Hessels, J W T; Spitler, L G; Gajjar, V; Archibald, A M; Bower, G C; Chatterjee, S; Cordes, J M; Gourdji, K; Heald, G H; Kaspi, V M; Law, C J; Sobey, C; Adams, E A K; Bassa, C G; Bogdanov, S; Brinkman, C; Demorest, P; Fernandez, F; Hellbourg, G; Lazio, T J W; Lynch, R S; Maddox, N; Marcote, B; McLaughlin, M A; Paragi, Z; Ransom, S M; Scholz, P; Siemion, A P V; Tendulkar, S P; Van Rooy, P; Wharton, R S; Whitlow, D

2018-01-10

Fast radio bursts are millisecond-duration, extragalactic radio flashes of unknown physical origin. The only known repeating fast radio burst source-FRB 121102-has been localized to a star-forming region in a dwarf galaxy at redshift 0.193 and is spatially coincident with a compact, persistent radio source. The origin of the bursts, the nature of the persistent source and the properties of the local environment are still unclear. Here we report observations of FRB 121102 that show almost 100 per cent linearly polarized emission at a very high and variable Faraday rotation measure in the source frame (varying from +1.46 × 10 5 radians per square metre to +1.33 × 10 5 radians per square metre at epochs separated by seven months) and narrow (below 30 microseconds) temporal structure. The large and variable rotation measure demonstrates that FRB 121102 is in an extreme and dynamic magneto-ionic environment, and the short durations of the bursts suggest a neutron star origin. Such large rotation measures have hitherto been observed only in the vicinities of massive black holes (larger than about 10,000 solar masses). Indeed, the properties of the persistent radio source are compatible with those of a low-luminosity, accreting massive black hole. The bursts may therefore come from a neutron star in such an environment or could be explained by other models, such as a highly magnetized wind nebula or supernova remnant surrounding a young neutron star.

Spatio-temporal variability of dry and wet periods in mainland Portugal and its relationships with teleconnection patterns

NASA Astrophysics Data System (ADS)

Espírito Santo, Fátima; de Lima, Isabel P.; Silva, Álvaro; Pires, Vanda; de Lima, João L. M. P.

2014-05-01

Large-scale atmospheric circulation patterns and their persistence are known to drive inter-annual variability of precipitation in Europe, although depending on geographical location; this includes precipitation extremes and their trends. The vast range of time and space scales involved leads sometimes to precipitation deficits and surpluses which might affect in a different way the society, the environment and the economy at the local and regional scales, depending on specific conditions. In addition, changes in the climate are expected to affect the occurrence of extreme weather and climate events that might influence significantly the distribution, availability and sustainability of regional water resources. The location of mainland Portugal on the Northeast Atlantic region, in South-western Europe, together with other geographical features, makes this territory vulnerable to extreme dry/wet hydro-meteorological events, driven by the strong variability in precipitation. In our study we discuss, for this territory, the relation between the spatio-temporal variability in those events, including their persistence at different scales, and the variability in several modes of low frequency variability; special attention is dedicated to the North Atlantic Oscillation (NAO) and Scandinavian pattern (SCAND). Some of these dry/wet episodes affect different aspects of the hydrologic cycle and are likely to lead to drought and soil wetness/saturation conditions that can enhance flood events. Such episodes were categorized here using the Standardized Precipitation Index (SPI), which was calculated at short (3 and 6-month) and long (12 and 24-month) time scales from monthly precipitation data recorded in the 1941-2012 period (72 years) at 50 precipitation stations scattered across the study area. Moreover, because SPI is a normalized index, it is also suitable to provide spatial representations of these conditions, allowing the comparison between areas within the same region. Thus, indices were interpolated for the whole territory using deterministic and geostatistical methods, and the zonal statistics results were mapped; the spatial interpolation, analysis and mapping were implemented in ArcGIS. Results confirm that the precipitation in this region is strongly influenced by the NAO and SCAND, in particular in the wettest months. Moreover, the annual SPI shows a significant increase in the extent of dry extremes and a non-significant decrease in the extent of wet extremes. For shorter time scales, the behaviour depends on the season. We discuss the observed SPI trends and the uncertainties for the precipitation regime in the southern and western parts of the Iberian Peninsula, which includes mainland Portugal. Results underline potential applications of SPI for water resources management, which is discussed in the context of the regional hydrological conditions and increasing demand for water for different uses.

Topography of sensory symptoms in patients with drug-naïve restless legs syndrome.

PubMed

Koo, Yong Seo; Lee, Gwan-Taek; Lee, Seo Young; Cho, Yong Won; Jung, Ki-Young

2013-12-01

We aimed to describe the sensory topography of restless legs syndrome (RLS) sensory symptoms and to identify the relationship between topography and clinical variables. Eighty adult patients with drug-naïve RLS who had symptoms for more than 1year were consecutively recruited. During face-to-face interviews using a structured paper and pencil questionnaire with all participants, we obtained clinical information and also marked the topography of RLS sensory symptoms on a specified body template, all of which were subsequently inputted into our in-house software. The RLS sensory topography patterns were classified according to localization, lateralization, and symmetry. We investigated if these sensory topography patterns differed according to various clinical variables. The lower extremities only (LE) were the most common location (72.5%), and 76.3% of participants exhibited symmetric sensory topography. Late-onset RLS showed more asymmetric sensory distribution compared with early-onset RLS (P=.024). Patients whose sensory symptoms involved the lower extremities in addition to other body parts (LE-PLUS) showed more severe RLS compared with those involving the LE (P=.037). RLS sensory symptoms typically were symmetrically located in the lower extremities. LE-PLUS or an asymmetric distribution more often occurred in patients with more severe RLS symptoms or late-onset RLS. Copyright © 2013 Elsevier B.V. All rights reserved.

Integrating new indicators of predictors that shape the public's perception of local extreme temperature in China.

PubMed

Ban, Jie; Huang, Lei; Chen, Chen; Guo, Yuming; He, Mike Z; Li, Tiantian

2017-02-01

The public's risk perception of local extreme heat or cold plays a critical role in community health and prevention under climate change. However, there is limited evidence on such issues in China where extreme weather is occurring more frequently due to climate change. Here, a total of 2500 residents were selected using a three-step sampling method and investigated by a questionnaire in two representative cities. We investigated risk perception of extreme heat in Beijing and extreme cold in Harbin in 2013, aiming to examine their possible correlations with multiple epidemiological factors. We found that exposure, vulnerability, and adaptive ability were significant predictors in shaping public risk perceptions of local extreme temperature. In particular, a 1°C increase in daily temperature resulted in an increased odds of perceiving serious extreme heat in Beijing (OR=1.091; 95% CI: 1.032, 1.153), while a 1°C increase in daily temperature resulted in a decreased odds of perceiving serious extreme cold in Harbin (OR=0.965; 95% CI: 0.939, 0.992). Therefore for both extreme heat and cold, frequent local extreme temperature exposure may amplify a stronger communication. Health interventions for extreme temperature should consider exposure, vulnerability, and adaptive ability factors. This will help improve the public's perception of climatic changes and their willingness to balance adaption and mitigation appropriately. Copyright © 2016 Elsevier B.V. All rights reserved.

Typical meteorological conditions associated with extreme nitrogen dioxide (NO2) pollution events over Scandinavia

NASA Astrophysics Data System (ADS)

Thomas, Manu Anna; Devasthale, Abhay

2017-10-01

Characterizing typical meteorological conditions associated with extreme pollution events helps to better understand the role of local meteorology in governing the transport and distribution of pollutants in the atmosphere. The knowledge of their co-variability could further help to evaluate and constrain chemistry transport models. Hence, in this study, we investigate the statistical linkages between extreme nitrogen dioxide (NO2) pollution events and meteorology over Scandinavia using observational and reanalysis data. It is observed that the south-westerly winds dominated during extreme events, accounting for 50-65 % of the total events depending on the season, while the second largest annual occurrence was from south-easterly winds, accounting for 17 % of total events. The specific humidity anomalies showed an influx of warmer and moisture-laden air masses over Scandinavia in the free troposphere. Two distinct modes in the persistency of circulation patterns are observed. The first mode lasts for 1-2 days, dominated by south-easterly winds that prevailed during 78 % of total extreme events in that mode, while the second mode lasted for 3-5 days, dominated by south-westerly winds that prevailed during 86 % of the events. The combined analysis of circulation patterns, their persistency, and associated changes in humidity and clouds suggests that NO2 extreme events over Scandinavia occur mainly due to long-range transport from the southern latitudes.

Large scale meteorological patterns and moisture sources during precipitation extremes over South Asia

NASA Astrophysics Data System (ADS)

Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H.

2017-12-01

Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms.

Variability in winter climate and winter extremes reduces population growth of an alpine butterfly.

PubMed

Roland, Jens; Matter, Stephen F

2013-01-01

We examined the long-term, 15-year pattern of population change in a network of 21 Rocky Mountain populations of Parnassius smintheus butterflies in response to climatic variation. We found that winter values of the broadscale climate variable, the Pacific Decadal Oscillation (PDO) index, were a strong predictor of annual population growth, much more so than were endogenous biotic factors related to population density. The relationship between PDO and population growth was nonlinear. Populations declined in years with extreme winter PDO values, when there were either extremely warm or extremely cold sea surface temperatures in the eastern Pacific relative to that in the western Pacific. Results suggest that more variable winters, and more frequent extremely cold or warm winters, will result in more frequent decline of these populations, a pattern exacerbated by the trend for increasingly variable winters seen over the past century.

Geographic dimensions of heat-related mortality in seven U.S. cities.

PubMed

Hondula, David M; Davis, Robert E; Saha, Michael V; Wegner, Carleigh R; Veazey, Lindsay M

2015-04-01

Spatially targeted interventions may help protect the public when extreme heat occurs. Health outcome data are increasingly being used to map intra-urban variability in heat-health risks, but there has been little effort to compare patterns and risk factors between cities. We sought to identify places within large metropolitan areas where the mortality rate is highest on hot summer days and determine if characteristics of high-risk areas are consistent from one city to another. A Poisson regression model was adapted to quantify temperature-mortality relationships at the postal code scale based on 2.1 million records of daily all-cause mortality counts from seven U.S. cities. Multivariate spatial regression models were then used to determine the demographic and environmental variables most closely associated with intra-city variability in risk. Significant mortality increases on extreme heat days were confined to 12-44% of postal codes comprising each city. Places with greater risk had more developed land, young, elderly, and minority residents, and lower income and educational attainment, but the key explanatory variables varied from one city to another. Regression models accounted for 14-34% of the spatial variability in heat-related mortality. The results emphasize the need for public health plans for heat to be locally tailored and not assume that pre-identified vulnerability indicators are universally applicable. As known risk factors accounted for no more than one third of the spatial variability in heat-health outcomes, consideration of health outcome data is important in efforts to identify and protect residents of the places where the heat-related health risks are the highest. Copyright © 2015 Elsevier Inc. All rights reserved.

Tectonics, orbital forcing, global climate change, and human evolution in Africa: introduction to the African paleoclimate special volume.

PubMed

Maslin, Mark A; Christensen, Beth

2007-11-01

The late Cenozoic climate of Africa is a critical component for understanding human evolution. African climate is controlled by major tectonic changes, global climate transitions, and local variations in orbital forcing. We introduce the special African Paleoclimate Issue of the Journal of Human Evolution by providing a background for and synthesis of the latest work relating to the environmental context for human evolution. Records presented in this special issue suggest that the regional tectonics, appearance of C(4) plants in East Africa, and late Cenozoic global cooling combined to produce a long-term drying trend in East Africa. Of particular importance is the uplift associated with the East African Rift Valley formation, which altered wind flow patterns from a more zonal to more meridinal direction. Results in this volume suggest a marked difference in the climate history of southern and eastern Africa, though both are clearly influenced by the major global climate thresholds crossed in the last 3 million years. Papers in this volume present lake, speleothem, and marine paleoclimate records showing that the East African long-term drying trend is punctuated by episodes of short, alternating periods of extreme wetness and aridity. These periods of extreme climate variability are characterized by the precession-forced appearance and disappearance of large, deep lakes in the East African Rift Valley and paralleled by low and high wind-driven dust loads reaching the adjacent ocean basins. Dating of these records show that over the last 3 million years such periods only occur at the times of major global climatic transitions, such as the intensification of Northern Hemisphere Glaciation (2.7-2.5 Ma), intensification of the Walker Circulation (1.9-1.7 Ma), and the Mid-Pleistocene Revolution (1-0.7 Ma). Authors in this volume suggest this onset occurs as high latitude forcing in both Hemispheres compresses the Intertropical Convergence Zone so that East Africa becomes locally sensitive to precessional forcing, resulting in rapid shifts from wet to dry conditions. These periods of extreme climate variability may have provided a catalyst for evolutionary change and driven key speciation and dispersal events amongst mammals and hominins in Africa. In particular, hominin species seem to differentially originate and go extinct during periods of extreme climate variability. Results presented in this volume may represent the basis of a new theory of early human evolution in Africa.

Assessment of Coastal and Urban Flooding Hazards Applying Extreme Value Analysis and Multivariate Statistical Techniques: A Case Study in Elwood, Australia

NASA Astrophysics Data System (ADS)

Guimarães Nobre, Gabriela; Arnbjerg-Nielsen, Karsten; Rosbjerg, Dan; Madsen, Henrik

2016-04-01

Traditionally, flood risk assessment studies have been carried out from a univariate frequency analysis perspective. However, statistical dependence between hydrological variables, such as extreme rainfall and extreme sea surge, is plausible to exist, since both variables to some extent are driven by common meteorological conditions. Aiming to overcome this limitation, multivariate statistical techniques has the potential to combine different sources of flooding in the investigation. The aim of this study was to apply a range of statistical methodologies for analyzing combined extreme hydrological variables that can lead to coastal and urban flooding. The study area is the Elwood Catchment, which is a highly urbanized catchment located in the city of Port Phillip, Melbourne, Australia. The first part of the investigation dealt with the marginal extreme value distributions. Two approaches to extract extreme value series were applied (Annual Maximum and Partial Duration Series), and different probability distribution functions were fit to the observed sample. Results obtained by using the Generalized Pareto distribution demonstrate the ability of the Pareto family to model the extreme events. Advancing into multivariate extreme value analysis, first an investigation regarding the asymptotic properties of extremal dependence was carried out. As a weak positive asymptotic dependence between the bivariate extreme pairs was found, the Conditional method proposed by Heffernan and Tawn (2004) was chosen. This approach is suitable to model bivariate extreme values, which are relatively unlikely to occur together. The results show that the probability of an extreme sea surge occurring during a one-hour intensity extreme precipitation event (or vice versa) can be twice as great as what would occur when assuming independent events. Therefore, presuming independence between these two variables would result in severe underestimation of the flooding risk in the study area.

Gaussian measures of entanglement versus negativities: Ordering of two-mode Gaussian states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adesso, Gerardo; Illuminati, Fabrizio; INFN Sezione di Napoli-Gruppo Collegato di Salerno, Via S. Allende, 84081 Baronissi, SA

2005-09-15

We study the entanglement of general (pure or mixed) two-mode Gaussian states of continuous-variable systems by comparing the two available classes of computable measures of entanglement: entropy-inspired Gaussian convex-roof measures and positive partial transposition-inspired measures (negativity and logarithmic negativity). We first review the formalism of Gaussian measures of entanglement, adopting the framework introduced in M. M. Wolf et al., Phys. Rev. A 69, 052320 (2004), where the Gaussian entanglement of formation was defined. We compute explicitly Gaussian measures of entanglement for two important families of nonsymmetric two-mode Gaussian state: namely, the states of extremal (maximal and minimal) negativities at fixedmore » global and local purities, introduced in G. Adesso et al., Phys. Rev. Lett. 92, 087901 (2004). This analysis allows us to compare the different orderings induced on the set of entangled two-mode Gaussian states by the negativities and by the Gaussian measures of entanglement. We find that in a certain range of values of the global and local purities (characterizing the covariance matrix of the corresponding extremal states), states of minimum negativity can have more Gaussian entanglement of formation than states of maximum negativity. Consequently, Gaussian measures and negativities are definitely inequivalent measures of entanglement on nonsymmetric two-mode Gaussian states, even when restricted to a class of extremal states. On the other hand, the two families of entanglement measures are completely equivalent on symmetric states, for which the Gaussian entanglement of formation coincides with the true entanglement of formation. Finally, we show that the inequivalence between the two families of continuous-variable entanglement measures is somehow limited. Namely, we rigorously prove that, at fixed negativities, the Gaussian measures of entanglement are bounded from below. Moreover, we provide some strong evidence suggesting that they are as well bounded from above.« less

The relative contribution of climatic, edaphic, and biotic drivers to risk of tree mortality from drought

NASA Astrophysics Data System (ADS)

March, R. G.; Moore, G. W.; Edgar, C. B.; Lawing, A. M.; Washington-Allen, R. A.

2015-12-01

In recorded history, the 2011 Texas Drought was comparable in severity only to a drought that occurred 300 years ago. By mid-September, 88% of the state experienced 'exceptional' conditions, with the rest experiencing 'extreme' or 'severe' drought. By recent estimates, the 2011 Texas Drought killed 6.2% of all the state's trees, at a rate nearly 9 times greater than average. The vast spatial scale and relatively uniform intensity of this drought has provided an opportunity to examine the comparative interactions among forest types, terrain, and edaphic factors across major climate gradients which in 2011 were subjected to extreme drought conditions that ultimately caused massive tree mortality. We used maximum entropy modeling (Maxent) to rank environmental landscape factors with the potential to drive drought-related tree mortality and test the assumption that the relative importance of these factors are scale-dependent. Occurrence data of dead trees were collected during the summer of 2012 from 599 field plots distributed across Texas with 30% used for model evaluation. Bioclimatic variables, ecoregions, soils characteristics, and topographic variables were modeled with drought-killed tree occurrence. Their relative contribution to the model was seen as their relative importance in driving mortality. To test determinants at a more local scale, we examined Landsat 7 scenes in East and West Texas with moderate-resolution data for the same variables above with the exception of climate. All models were significantly better than random in binomial tests of omission and receiver operating characteristic analyses. The modeled spatial distribution of probability of occurrence showed high probability of mortality in the east-central oak woodlands and the mixed pine-hardwood forest region in northeast Texas. Both regional and local models were dominated by biotic factors (ecoregion and forest type, respectively). Forest density and precipitation of driest month also contributed highly to the regional model. The local models gave more importance to available water storage at root zone and hillshade. Understanding how environmental factors drive drought-related mortality can help predict vulnerable landscapes and aid in preparing for future drought events.

Tying Variability in Summertime North American Extreme Weather Regimes to the Boreal Summer Intraseasonal Oscillation

NASA Astrophysics Data System (ADS)

Jenney, A. M.; Randall, D. A.

2017-12-01

Tropical intraseasonal oscillations are known to be a source of extratropical variability. We show that subseasonal variability in observed North American epidemiologically significant regional extreme weather regimes is teleconnected to the boreal summer intraseasonal oscillation (BSISO)—a complex tropical weather system that is active during the northern summer and has a 30-50 day timescale. The dynamics of the teleconnection are examined. We also find that interannual variability of the tropical mean-state can modulate the teleconnection. Our results suggest that the BSISO may enable subseasonal to seasonal predictions of North American summertime weather extremes.

Examining global extreme sea level variations on the coast from in-situ and remote observations

NASA Astrophysics Data System (ADS)

Menendez, Melisa; Benkler, Anna S.

2017-04-01

The estimation of extreme water level values on the coast is a requirement for a wide range of engineering and coastal management applications. In addition, climate variations of extreme sea levels on the coastal area result from a complex interacting of oceanic, atmospheric and terrestrial processes across a wide range of spatial and temporal scales. In this study, variations of extreme sea level return values are investigated from two available sources of information: in-situ tide-gauge records and satellite altimetry data. Long time series of sea level from tide-gauge records are the most valuable observations since they directly measure water level in a specific coastal location. They have however a number of sources of in-homogeneities that may affect the climate description of extremes when this data source is used. Among others, the presence of gaps, historical time in-homogeneities and jumps in the mean sea level signal are factors that can provide uncertainty in the characterization of the extreme sea level behaviour. Moreover, long records from tide-gauges are sparse and there are many coastal areas worldwide without in-situ available information. On the other hand, with the accumulating altimeter records of several satellite missions from the 1990s, approaching 25 recorded years at the time of writing, it is becoming possible the analysis of extreme sea level events from this data source. Aside the well-known issue of altimeter measurements very close to the coast (mainly due to corruption by land, wet troposphere path delay errors and local tide effects on the coastal area), there are other aspects that have to be considered when sea surface height values estimated from satellite are going to be used in a statistical extreme model, such as the use of a multi-mission product to get long observed periods and the selection of the maxima sample, since altimeter observations do not provide values uniform in time and space. Here, we have compared the extreme values of 'still water level' and 'non-tidal-residual' of in-situ records from the GESLA2 dataset (Woodworth et al. 2016) against the novel coastal altimetry datasets (Cipollini et al. 2016). Seasonal patterns, inter-annual variability and long-term trends are analyzed. Then, a time-dependent extreme model (Menendez et al. 2009) is applied to characterize extreme sea level return values and their variability on the coastal area around the world.

Extreme Response Style and the Measurement of Intra-Individual Variability

ERIC Educational Resources Information Center

Deng, Sien

2017-01-01

Psychologists have become increasingly interested in the intra-individual variability of psychological measures as a meaningful distinguishing characteristic of persons. Assessments of intra-individual variability are frequently based on the repeated administration of self-report rating scale instruments, and extreme response style (ERS) has the…

Inferring Spatio-temporal Variations in the Risk of Extreme Precipitation in the Western United States from Tree-ring Chronologies

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.

2017-12-01

This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.

Inferring Spatio-temporal Variations in the Risk of Extreme Precipitation in the Western United States from Tree-ring Chronologies

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.

2016-12-01

This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.

About climate variabilitiy leading the hydric condition of the soil in the rainfed region of Argentina

NASA Astrophysics Data System (ADS)

Pántano, V. C.; Penalba, O. C.

2013-05-01

Extreme events of temperature and rainfall have a socio-economic impact in the rainfed agriculture production region in Argentina. The magnitude of the impact can be analyzed through the water balance which integrates the characteristics of the soil and climate conditions. Changes observed in climate variables during the last decades affected the components of the water balance. As a result, a displacement of the agriculture border towards the west was produced, improving the agricultural production of the region. The objective of this work is to analyze how the variability of rainfall and temperature leads the hydric condition of the soil, with special focus on extreme events. The hydric conditions of the soil (HC= Excess- Deficit) were estimated from the monthly water balance (Thornthwaite and Mather method, 1957), using monthly potential evapotranspiration (PET) and monthly accumulated rainfall (R) for 33 stations (period 1970-2006). Information of temperature and rainfall was provided by National Weather Service and the effective capacity of soil water was considered from Forte Lay and Spescha (2001). An agricultural extreme condition occurs when soil moisture and rainfall are inadequate or excessive for the development of the crops. In this study, we define an extreme event when the variable is less (greater) than its 20% and 10% (80% and 90%) percentile. In order to evaluate how sensitive is the HC to water and heat stress in the region, different conditional probabilities were evaluated. There is a weaker response of HC to extreme low PET while extreme low R leads high values of HC. However, this behavior is not always observed, especially in the western region where extreme high and low PET show a stronger influence over the HC. Finally, to analyze the temporal variability of extreme PET and R, leading hydric condition of the soil, the number of stations presenting extreme conditions was computed for each month. As an example, interesting results were observed for April. During this month, the water recharge of the soil is crucial to let the winter crops manage with the scarce rainfalls occurring in the following months. In 1970, 1974, 1977, 1978 and 1997 more than 50% of the stations were under extreme high PET; while 1970, 1974, 1978 and 1988 presented more than 40% under extreme low R. Thus, the 70s was the more threatened decade of the period. Since the 80s (except for 1997), extreme dry events due to one variable or the other are mostly presented separately, over smaller areas. The response of the spatial distribution of HC is stronger when both variables present extreme conditions. In particular, during 1997 the region presents extreme low values of HC as a consequence of extreme low R and high PET. Communities dependent on agriculture are highly sensitive to climate variability and its extremes. In the studied region, it was shown that scarce water and heat stress contribute to the resulting hydric condition, producing strong impact over different productive activities. Extreme temperature seems to have a stronger influence over extreme unfavorable hydric conditions.

Towards a Unified Framework in Hydroclimate Extremes Prediction in Changing Climate

NASA Astrophysics Data System (ADS)

Moradkhani, H.; Yan, H.; Zarekarizi, M.; Bracken, C.

2016-12-01

Spatio-temporal analysis and prediction of hydroclimate extremes are of paramount importance in disaster mitigation and emergency management. The IPCC special report on managing the risks of extreme events and disasters emphasizes that the global warming would change the frequency, severity, and spatial pattern of extremes. In addition to climate change, land use and land cover changes also influence the extreme characteristics at regional scale. Therefore, natural variability and anthropogenic changes to the hydroclimate system result in nonstationarity in hydroclimate variables. In this presentation recent advancements in developing and using Bayesian approaches to account for non-stationarity in hydroclimate extremes are discussed. Also, implications of these approaches in flood frequency analysis, treatment of spatial dependence, the impact of large-scale climate variability, the selection of cause-effect covariates, with quantification of model errors in extreme prediction is explained. Within this framework, the applicability and usefulness of the ensemble data assimilation for extreme flood predictions is also introduced. Finally, a practical and easy to use approach for better communication with decision-makers and emergency managers is presented.

BROAD Hβ EMISSION-LINE VARIABILITY IN A SAMPLE OF 102 LOCAL ACTIVE GALAXIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Runco, Jordan N.; Cosens, Maren; Bennert, Vardha N.

2016-04-10

A sample of 102 local (0.02 ≤ z ≤ 0.1) Seyfert galaxies with black hole masses M{sub BH} > 10{sup 7}M{sub ⊙} was selected from the Sloan Digital Sky Survey (SDSS) and observed using the Keck 10 m telescope to study the scaling relations between M{sub BH} and host galaxy properties. We study profile changes of the broad Hβ emission line within the three to nine year time frame between the two sets of spectra. The variability of the broad Hβ emission line is of particular interest, not only because it is used to estimate M{sub BH}, but also because its strengthmore » and width are used to classify Seyfert galaxies into different types. At least some form of broad-line variability (in either width or flux) is observed in the majority (∼66%) of the objects, resulting in a Seyfert-type change for ∼38% of the objects, likely driven by variable accretion and/or obscuration. The broad Hβ line virtually disappears in 3/102 (∼3%) extreme cases. We discuss potential causes for these changing look active galactic nuclei. While similar dramatic transitions have previously been reported in the literature, either on a case-by-case basis or in larger samples focusing on quasars at higher redshifts, our study provides statistical information on the frequency of Hβ line variability in a sample of low-redshift Seyfert galaxies.« less

Long-Term Trends, Variability and Extremes of In Situ Sea Surface Temperature Measured Along the Eastern Adriatic Coast and its Relationship to Hemispheric Processes

NASA Astrophysics Data System (ADS)

Grbec, Branka; Matić, Frano; Beg Paklar, Gordana; Morović, Mira; Popović, Ružica; Vilibić, Ivica

2018-02-01

This paper examines long-term series of in situ sea surface temperature (SST) data measured at nine coastal and one open sea stations along the eastern Adriatic Sea for the period 1959-2015. Monthly and yearly averages were used to document SST trends and variability, while clustering and connections to hemispheric indices were achieved by applying the Principal Component Analysis (PCA) and Self-Organizing Maps (SOM) method. Both PCA and SOM revealed the dominance of temporal changes with respect to the effects of spatial differences in SST anomalies, indicating the prevalence of hemispheric processes over local dynamics, such as bora wind spatial inhomogeneity. SST extremes were connected with blocking atmospheric patterns. A substantial warming between 1979 and 2015, in total exceeding 1 °C, was preceded by a period with a negative SST trend, implying strong multidecadal variability in the Adriatic. The strongest connection was found between yearly SST and the East Atlantic (EA) pattern, while North Atlantic Oscillation (NAO) and East Atlantic/West Russia (EAWR) patterns were found to also affect February SST values. Quantification of the Adriatic SST and their connection to hemispheric indices allow for more precise projections of future SST, considered to be rather important for Adriatic thermohaline circulation, biogeochemistry and fisheries, and sensitive to ongoing climate change.

Linking North American Summer Ozone Pollution Episodes to Subseasonal Atmospheric Variability

NASA Astrophysics Data System (ADS)

White, E. C.; Watt-Meyer, O.; Kushner, P. J.; Jones, D. B. A.

2017-12-01

Ozone concentrations in the planetary boundary layer (PBL) are positively correlated with surface air temperature due to shared influences including incident solar radiation and PBL stagnancy, as well as the temperature-sensitive emission of ozone precursor compounds. While previous studies have linked heat waves in North America to modes of subseasonal atmospheric variability, such analyses have not been applied to summertime ozone pollution episodes. This study investigates a possible link between subseasonal atmospheric variability in reanalysis data and summertime ozone pollution episodes identified in almost thirty years of in-situ measurements from the Air Quality System (AQS) network in the United States. AQS stations are grouped into regions likely to experience simultaneous extreme ozone concentrations using statistical clustering methods. Composite meteorological patterns are calculated for ozone episodes in each of these regions. The same analysis is applied to heat waves identified in AQS temperature records for comparison. Local meteorological features during typical ozone episodes include extreme temperatures and reduced cloud cover related to anomalous synoptic-scale anticyclonic circulation aloft. These anticyclonic anomalies are typically embedded in wave trains extending from the North Pacific to North Atlantic. Spectral analysis of these wave trains reveals that low-frequency standing waves play a prominent role. These long-lived circulation patterns may provide a means to increase air quality prediction lead-times and to estimate the frequency of ozone pollution episodes under climate change.

Internal and forced eddy variability in the Labrador Sea

NASA Astrophysics Data System (ADS)

Bracco, A.; Luo, H.; Zhong, Y.; Lilly, J.

2009-04-01

Water mass transformation in the Labrador Sea, widely believed to be one of the key regions in the Atlantic Meridional Overturning Circulation (AMOC), now appears to be strongly impacted by vortex dynamics of the unstable boundary current. Large interannual variations in both eddy shedding and buoyancy transport from the boundary current have been observed but not explained, and are apparently sensitive to the state of the inflowing current. Heat and salinity fluxes associated with the eddies drive ventilation changes not accounted for by changes in local surface forcing, particularly during occasional years of extreme eddy activity, and constitute a predominant source of "internal" oceanic variability. The nature of this variable eddy-driven restratification is one of the outstanding questions along the northern transformation pathway. Here we investigate the eddy generation mechanism and the associated buoyancy fluxes by combining realistic and idealized numerical modeling, data analysis, and theory. Theory, supported by idealized experiments, provides criteria to test hypotheses as to the vortex formation process (by baroclinic instability linked to the bottom topography). Ensembles of numerical experiments with a high-resolution regional model (ROMS) allow for quantifying the sensitivity of eddy generation and property transport to variations in local and external forcing parameters. For the first time, we reproduce with a numerical simulation the observed interannual variability in the eddy kinetic energy in the convective region of the Labrador Basin and along the West Greenland Current.

Understanding spatial variability in extreme estuarine water levels to inform better coastal management practise.

NASA Astrophysics Data System (ADS)

Lyddon, Charlotte; Plater, Andy, ,, Prof.; Brown, Jenny, ,, Dr.; Leonardi, Nicoletta, ,, Dr.

2017-04-01

Coastal zones worldwide are subject to short term, local variations in sea-level, particularly communities and industries developed on estuaries. Astronomical high tides, meteorological storm surges and increased river flow present a combined flood hazard. This can elevate water level at the coast above predicted levels, generating extreme water levels. These contributions can also interact to alter the phase and amplitude of tides and surges, and thus cause significant mismatches between the predicted and observed water level. The combined effect of tide, surge, river flow and their interactions are the key to understanding and assessing flood risk in estuarine environments for design purposes. Delft3D-FLOW, a hydrodynamic model which solves the unsteady shallow-water equation, is used to access spatial variability in extreme water levels for a range of historical events of different severity within the Severn Estuary, southwest England. Long-term tide gauge records from Ilfracombe and Mumbles and river level data from Sandhurst are analysed to generate a series of extreme water level events, representing the 90th, 95th and 99th percentile conditions, to force the model boundaries. To separate out the time-varying contributions of tidal, fluvial, meteorological processes and their interactions the model is run with different physical forcing. A low pass filter is applied to "de-tide" the residual water elevation, to separate out the time-varying meteorological residual and the tide-surge interactions within the surge. The filtered surge is recombined with the predicted tide so the peak occurs at different times relative to high water. The resulting time series are used to force the model boundary to identify how the interactive processes influence the timing of extreme water level across the estuarine domain. This methodology is first validated using the most extreme event on record to ensure that modelled extreme water levels can be predicted with confidence. Changes in maximum water level are observed in areas where nuclear assets are located (Hinkley, Oldbury & Berkeley) and further upstream, e.g., close to the tidal limit of the Severn Estuary at Epney. Change in crest shape (area and duration above the MSHW) are analysed to understand changes to flood hazard around the peak of the tide. The work concludes that changes in maximum water level can be attributed to the change in time of the peak of the surge relative to high water, the surge shape (classified by skew and kurtosis) and severity of the event. The results can be used to understand the spatial variability in extreme water levels relative to a tide gauge location, which can then be applied to other management needs in hypertidal estuaries worldwide.

Microhabitats in the tropics buffer temperature in a globally coherent manner

PubMed Central

Scheffers, Brett R.; Evans, Theodore A.; Williams, Stephen E.; Edwards, David P.

2014-01-01

Vegetated habitats contain a variety of fine-scale features that can ameliorate temperate extremes. These buffered microhabitats may be used by species to evade extreme weather and novel climates in the future. Yet, the magnitude and extent of this buffering on a global scale remains unknown. Across all tropical continents and using 36 published studies, we assessed temperature buffering from within microhabitats across various habitat strata and structures (e.g. soil, logs, epiphytes and tree holes) and compared them to non-buffered macro-scale ambient temperatures (the thermal control). Microhabitats buffered temperature by 3.9°C and reduced maximum temperatures by 3.5°C. Buffering was most pronounced in tropical lowlands where temperatures were most variable. With the expected increase in extreme weather events, microhabitats should provide species with a local layer of protection that is not captured by traditional climate assessments, which are typically derived from macro-scale temperatures (e.g. satellites). Our data illustrate the need for a next generation of predictive models that account for species' ability to move within microhabitats to exploit favourable buffered microclimates. PMID:25540160

Evolution of a genetic polymorphism with climate change in a Mediterranean landscape

PubMed Central

Thompson, John; Charpentier, Anne; Bouguet, Guillaume; Charmasson, Faustine; Roset, Stephanie; Buatois, Bruno; Vernet, Philippe; Gouyon, Pierre-Henri

2013-01-01

Many species show changes in distribution and phenotypic trait variation in response to climatic warming. Evidence of genetically based trait responses to climate change is, however, less common. Here, we detected evolutionary variation in the landscape-scale distribution of a genetically based chemical polymorphism in Mediterranean wild thyme (Thymus vulgaris) in association with modified extreme winter freezing events. By comparing current data on morph distribution with that observed in the early 1970s, we detected a significant increase in the proportion of morphs that are sensitive to winter freezing. This increase in frequency was observed in 17 of the 24 populations in which, since the 1970s, annual extreme winter freezing temperatures have risen above the thresholds that cause mortality of freezing-sensitive morphs. Our results provide an original example of rapid ongoing evolutionary change associated with relaxed selection (less extreme freezing events) on a local landscape scale. In species whose distribution and genetic variability are shaped by strong selection gradients, there may be little time lag associated with their ecological and evolutionary response to long-term environmental change. PMID:23382198

Quantile regression of microgeographic variation in population characteristics of an invasive vertebrate predator

USGS Publications Warehouse

Siers, Shane R.; Savidge, Julie A.; Reed, Robert

2017-01-01

Localized ecological conditions have the potential to induce variation in population characteristics such as size distributions and body conditions. The ability to generalize the influence of ecological characteristics on such population traits may be particularly meaningful when those traits influence prospects for successful management interventions. To characterize variability in invasive Brown Treesnake population attributes within and among habitat types, we conducted systematic and seasonally-balanced surveys, collecting 100 snakes from each of 18 sites: three replicates within each of six major habitat types comprising 95% of Guam’s geographic expanse. Our study constitutes one of the most comprehensive and controlled samplings of any published snake study. Quantile regression on snake size and body condition indicated significant ecological heterogeneity, with a general trend of relative consistency of size classes and body conditions within and among scrub and Leucaena forest habitat types and more heterogeneity among ravine forest, savanna, and urban residential sites. Larger and more robust snakes were found within some savanna and urban habitat replicates, likely due to relative availability of larger prey. Compared to more homogeneous samples in the wet season, variability in size distributions and body conditions was greater during the dry season. Although there is evidence of habitat influencing Brown Treesnake populations at localized scales (e.g., the higher prevalence of larger snakes—particularly males—in savanna and urban sites), the level of variability among sites within habitat types indicates little ability to make meaningful predictions about these traits at unsampled locations. Seasonal variability within sites and habitats indicates that localized population characterization should include sampling in both wet and dry seasons. Extreme values at single replicates occasionally influenced overall habitat patterns, while pooling replicates masked variability among sites. A full understanding of population characteristics should include an assessment of variability both at the site and habitat level.

Quantile regression of microgeographic variation in population characteristics of an invasive vertebrate predator

PubMed Central

Siers, Shane R.; Savidge, Julie A.; Reed, Robert N.

2017-01-01

Localized ecological conditions have the potential to induce variation in population characteristics such as size distributions and body conditions. The ability to generalize the influence of ecological characteristics on such population traits may be particularly meaningful when those traits influence prospects for successful management interventions. To characterize variability in invasive Brown Treesnake population attributes within and among habitat types, we conducted systematic and seasonally-balanced surveys, collecting 100 snakes from each of 18 sites: three replicates within each of six major habitat types comprising 95% of Guam’s geographic expanse. Our study constitutes one of the most comprehensive and controlled samplings of any published snake study. Quantile regression on snake size and body condition indicated significant ecological heterogeneity, with a general trend of relative consistency of size classes and body conditions within and among scrub and Leucaena forest habitat types and more heterogeneity among ravine forest, savanna, and urban residential sites. Larger and more robust snakes were found within some savanna and urban habitat replicates, likely due to relative availability of larger prey. Compared to more homogeneous samples in the wet season, variability in size distributions and body conditions was greater during the dry season. Although there is evidence of habitat influencing Brown Treesnake populations at localized scales (e.g., the higher prevalence of larger snakes—particularly males—in savanna and urban sites), the level of variability among sites within habitat types indicates little ability to make meaningful predictions about these traits at unsampled locations. Seasonal variability within sites and habitats indicates that localized population characterization should include sampling in both wet and dry seasons. Extreme values at single replicates occasionally influenced overall habitat patterns, while pooling replicates masked variability among sites. A full understanding of population characteristics should include an assessment of variability both at the site and habitat level. PMID:28570632

Quantile regression of microgeographic variation in population characteristics of an invasive vertebrate predator.

PubMed

Siers, Shane R; Savidge, Julie A; Reed, Robert N

2017-01-01

Localized ecological conditions have the potential to induce variation in population characteristics such as size distributions and body conditions. The ability to generalize the influence of ecological characteristics on such population traits may be particularly meaningful when those traits influence prospects for successful management interventions. To characterize variability in invasive Brown Treesnake population attributes within and among habitat types, we conducted systematic and seasonally-balanced surveys, collecting 100 snakes from each of 18 sites: three replicates within each of six major habitat types comprising 95% of Guam's geographic expanse. Our study constitutes one of the most comprehensive and controlled samplings of any published snake study. Quantile regression on snake size and body condition indicated significant ecological heterogeneity, with a general trend of relative consistency of size classes and body conditions within and among scrub and Leucaena forest habitat types and more heterogeneity among ravine forest, savanna, and urban residential sites. Larger and more robust snakes were found within some savanna and urban habitat replicates, likely due to relative availability of larger prey. Compared to more homogeneous samples in the wet season, variability in size distributions and body conditions was greater during the dry season. Although there is evidence of habitat influencing Brown Treesnake populations at localized scales (e.g., the higher prevalence of larger snakes-particularly males-in savanna and urban sites), the level of variability among sites within habitat types indicates little ability to make meaningful predictions about these traits at unsampled locations. Seasonal variability within sites and habitats indicates that localized population characterization should include sampling in both wet and dry seasons. Extreme values at single replicates occasionally influenced overall habitat patterns, while pooling replicates masked variability among sites. A full understanding of population characteristics should include an assessment of variability both at the site and habitat level.

A reconstruction of sea surface temperature variability in the southeastern Gulf of Mexico from 1734 to 2008 C.E. using cross-dated Sr/Ca records from the coral Siderastrea siderea

USGS Publications Warehouse

DeLong, Kristine L.; Maupin, Christopher R.; Flannery, Jennifer A.; Quinn, Terrence M.; Shen, CC

2014-01-01

This study uses skeletal variations in coral Sr/Ca from three Siderastrea siderea coral colonies within the Dry Tortugas National Park in the southeastern Gulf of Mexico (24°42′N, 82°48′W) to reconstruct monthly sea surface temperature (SST) variations from 1734 to 2008 Common Era (C.E.). Calibration and verification of the replicated coral Sr/Ca-SST reconstruction with local, regional, and historical temperature records reveals that this proxy-temperature relationship is stable back to 1879 C.E. The coral SST reconstruction contains robust interannual (~2.0°C) and multidecadal variability (~1.5°C) for the past 274 years, the latter of which does not covary with the Atlantic Multidecadal Oscillation. Winter SST extremes are more variable than summer SST extremes (±2.2°C versus ±1.6°C, 2σ) suggesting that Loop Current transport in the winter dominates variability on interannual and longer time scales. Summer SST maxima are increasing (+1.0°C for 274 years, σMC = ±0.5°C, 2σ), whereas winter SST minima contain no significant trend. Colder decades (~1.5°C) during the Little Ice Age (LIA) do not coincide with decades of sunspot minima. The coral SST reconstruction contains similar variability to temperature reconstructions from the northern Gulf of Mexico (planktic foraminifer Mg/Ca) and the Caribbean Sea (coral Sr/Ca) suggesting areal reductions in the Western Hemisphere Warm Pool during the LIA. Mean summer coral SST extremes post-1985 C.E. (29.9°C) exceeds the long-term summer average (29.2°C for 1734–2008 C.E.), yet the warming trend after 1985 C.E. (0.04°C for 24 years, σMC = ±0.5, 2σ) is not significant, whereas Caribbean coral Sr/Ca studies contain a warming trend for this interval.

Contributions of natural climate changes and human activities to the trend of extreme precipitation

NASA Astrophysics Data System (ADS)

Gao, Lu; Huang, Jie; Chen, Xingwei; Chen, Ying; Liu, Meibing

2018-06-01

This study focuses on the analysis of the nonstationarity characteristics of extreme precipitation and their attributions in the southeastern coastal region of China. The maximum daily precipitation (MDP) series is extracted from observations at 79 meteorological stations in the study area during the first flood season (April-June) from 1960 to 2012. The trends of the mean (Mn) and variance (Var) of MDP are detected using the Generalized Additive Models for Location, Scale, and Shape parameters (GAMLSS) and Mann-Kendall test. The contributions of natural climate change and human activities to the Mn and Var changes of MDP are investigated using six large-scale circulation variables and emissions of four greenhouse gases based on GAMLSS and a contribution analysis method. The results demonstrate that the nonstationarity of extreme precipitation on local scales is significant. The Mn and Var of extreme precipitation increase in the north of Zhejiang, the middle of Fujian, and the south of Guangdong. In general, natural climate change contributes more to Mn from 1960 to 2012 than to Var. However, human activities cause a greater Var in the rapid socioeconomic development period (1986-2012) than in the slow socioeconomic development period (1960-1985), especially in Zhejiang and Guangdong. The community should pay more attention to the possibility of extreme precipitation events and associated disasters triggered by human activities.

A nonstationary analysis for the Northern Adriatic extreme sea levels

NASA Astrophysics Data System (ADS)

Masina, Marinella; Lamberti, Alberto

2013-09-01

The historical data from the Trieste, Venice, Porto Corsini, and Rimini tide gauges have been used to investigate the spatial and temporal changes in extreme high water levels in the Northern Adriatic. A detailed analysis of annual mean sea level evolution at the three longest operating stations shows a coherent behavior both on a regional and global scale. A slight increase in magnitude of extreme water elevations, after the removal of the regularized annual mean sea level necessary to eliminate the effect of local subsidence and sea level rise, is found at the Venice and Porto Corsini stations. It seems to be mainly associated with a wind regime change occurred in the 1990s, due to an intensification of Bora wind events after their decrease in frequency and intensity during the second half of the 20th century. The extreme values, adjusted for the annual mean sea level trend, are modeled using a time-dependent GEV distribution. The inclusion of seasonality in the GEV parameters considerably improves the data fitting. The interannual fluctuations of the detrended monthly maxima exhibit a significant correlation with the variability of the large-scale atmospheric circulation represented by the North Atlantic Oscillation and Arctic Oscillation indices. The different coast exposure to the Bora and Sirocco winds and their seasonal character explain the various seasonal patterns of extreme sea levels observed at the tide gauges considered in the present analysis.

Structurally Dynamic Spin Market Networks

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán

The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.

Significance of vapor phase chemical reactions on CVD rates predicted by chemically frozen and local thermochemical equilibrium boundary layer theories

NASA Technical Reports Server (NTRS)

Gokoglu, Suleyman A.

1988-01-01

This paper investigates the role played by vapor-phase chemical reactions on CVD rates by comparing the results of two extreme theories developed to predict CVD mass transport rates in the absence of interfacial kinetic barrier: one based on chemically frozen boundary layer and the other based on local thermochemical equilibrium. Both theories consider laminar convective-diffusion boundary layers at high Reynolds numbers and include thermal (Soret) diffusion and variable property effects. As an example, Na2SO4 deposition was studied. It was found that gas phase reactions have no important role on Na2SO4 deposition rates and on the predictions of the theories. The implications of the predictions of the two theories to other CVD systems are discussed.

Variability of extreme rainfall over La Plata Basin and Amazon Basin in South America in model simulations of the 20th century and projections under global warming

NASA Astrophysics Data System (ADS)

Cavalcanti, I. F.

2011-12-01

The two largest river basins in South America are Amazon Basin (AMB) in the tropical region and La Plata Basin (LPB) in subtropical and extratropical regions. Extreme droughts have occurred during this decade in Amazonia region which have affected the transportation, fishing activities with impacts in the local population, and also affecting the forest. Droughts or floods over LPB have impacts on agriculture, hydroelectricity power and social life. Therefore, monthly wet and dry extremes in these two regions have a profound effect on the economy and society. Observed rainfall over Amazon Basin (AMB) and La Plata Basin (LPB) is analyzed in monthly timescale using the Standardized Precipitation Index (SPI), from 1979 to 1999. This period is taken to compare GPCP data with HADCM3 simulations (Hadley Centre) of the 20th century and to analyze reanalyses data which have the contribution of satellite information after 1979. HADCM3 projections using SRES A2 scenario is analyzed in two periods: 2000 to 2020 and 2079 to 2099 to study the extremes frequency in a near future and in a longer timescale. Extreme, severe and moderate cases are identified in the northern and southern sectors of LPB and in the western and eastern sectors of AMB. The main objective is to analyze changes in the frequency of cases, considering the global warming and the associated mechanisms. In the observations for the 20th century, the number of extreme rainy cases is higher than the number of dry cases in both sectors of LPB and AMB. The model simulates this variability in the two sectors of LPB and in the west sector of AMB. In the near future 2000 to 2020 the frequency of wet and dry extremes does not change much in LPB and in the western sector of AMB, but the wet cases increase in the eastern AMB. However, in the period of 2079 to 2099 the projections indicate increase of wet cases in LPB and increase of dry cases in AMB. The influence of large scale features related to Sea Surface Temperature Anomalies, Walker and Hadley circulations, teleconnections, as well as the regional features related to humidity flux are discussed. The extreme droughts of 2005 and 2010 in Amazonia are show to be related to these features.

Nonparametric Regression Subject to a Given Number of Local Extreme Value

DTIC Science & Technology

2001-07-01

compilation report: ADP013708 thru ADP013761 UNCLASSIFIED Nonparametric regression subject to a given number of local extreme value Ali Majidi and Laurie...locations of the local extremes for the smoothing algorithm. 280 A. Majidi and L. Davies 3 The smoothing problem We make the smoothing problem precise...is the solution of QP3. k--oo 282 A. Majidi and L. Davies FiG. 2. The captions top-left, top-right, bottom-left, bottom-right show the result of the

EFFECT OF INTENSE FUNCTIONAL TASK TRAINING UPON TEMPORAL STRUCTURE OF VARIABILITY OF UPPER EXTREMITY POST STROKE

PubMed Central

Sethi, Amit; Davis, Sandra; McGuirk, Theresa; Patterson, Tara S.; Richards, Lorie G.

2012-01-01

Study Design Quasi-experimental design Introduction Although the effectiveness of constraint induced movement therapy (CIMT) in upper extremity (UE) rehabilitation post stroke is well known, the efficacy of CIMT to enhance the temporal structure of variability in upper extremity movement is not known. Purpose The purpose of this study was to investigate whether CIMT could enhance temporal structure of variability in upper extremity movement in individuals with chronic stroke. Methods Six participants with chronic stroke underwent CIMT for 4 hours/day for 2 weeks. Participants performed three trials of functional reach-to-grasp before and after CIMT. Temporal structure of variability was determined by calculating approximate entropy (ApEn) in shoulder, elbow and wrist flexion/extension joint angles. Results ApEn increased post CIMT, however, statistical significance was not achieved (p > 0.0167). Conclusion Future studies with larger sample size are warranted to investigate the effect of CIMT upon temporal structure of variability in UE movement. PMID:23084461

Global warming: it's not only size that matters

NASA Astrophysics Data System (ADS)

Hegerl, Gabriele C.

2011-09-01

Observed and model simulated warming is particularly large in high latitudes, and hence the Arctic is often seen as the posterchild of vulnerability to global warming. However, Mahlstein et al (2011) point out that the signal of climate change is emerging locally from that of climate variability earliest in regions of low climate variability, based on climate model data, and in agreement with observations. This is because high latitude regions are not only regions of strong feedbacks that enhance the global warming signal, but also regions of substantial climate variability, driven by strong dynamics and enhanced by feedbacks (Hall 2004). Hence the spatial pattern of both observed warming and simulated warming for the 20th century shows strong warming in high latitudes, but this warming occurs against a backdrop of strong variability. Thus, the ratio of the warming to internal variability is not necessarily highest in the regions that warm fastest—and Mahlstein et al illustrate that it is actually the low-variability regions where the signal of local warming emerges first from that of climate variability. Thus, regions with strongest warming are neither the most important to diagnose that forcing changes climate, nor are they the regions which will necessarily experience the strongest impact. The importance of the signal-to-noise ratio has been known to the detection and attribution community, but has been buried in technical 'optimal fingerprinting' literature (e.g., Hasselmann 1979, Allen and Tett 1999), where it was used for an earlier detection of climate change by emphasizing aspects of the fingerprint of global warming associated with low variability in estimates of the observed warming. What, however, was not discussed was that the local signal-to-noise ratio is of interest also for local climate change: where temperatures emerge from the range visited by internal climate variability, it is reasonable to assume that changes in climate will also cause more impacts than temperatures that have occurred frequently due to internal climate variability. Determining when exactly temperatures enter unusual ranges may be done in many different ways (and the paper shows several, and more could be imagined), but the main result of first local emergence in low latitudes remains robust. A worrying factor is that the regions where the signal is expected to emerge first, or is already emerging are largely regions in Africa, parts of South and Central America, and the Maritime Continent; regions that are vulnerable to climate change for a variety of regions (see IPCC 2007), and regions which contribute generally little to global greenhouse gas emissions. In contrast, strong emissions of greenhouse gases occur in regions of low warming-to-variability ratio. To get even closer to the relevance of this finding for impacts, it would be interesting to place the emergence of highly unusual summer temperatures in the context not of internal variability, but in the context of variability experienced by the climate system prior to the 20th century, as, e.g. documented in palaeoclimatic reconstructions and simulated in simulations of the last millennium (see Jansen et al 2007). External forcing has moved the temperature range around more strongly for some regions and in some seasons than others. For example, while reconstructions of summer temperatures in Europe appear to show small long-term variations, winter shows deep drops in temperature in the little Ice Age and a long-term increase since then (Luterbacher et al 2004), which was at least partly caused by external forcing (Hegerl et al 2011a) and therefore 'natural variability' may be different from internal variability. A further interesting question in attempts to provide a climate-based proxy for impacts of climate change is: to what extent does the rapidity of change matter, and how does it compare to trends due to natural variability? It is reasonable to assume that fast changes impact ecosystems and society more than slow, gradual ones. Also, is it really the mean seasonal temperature that counts, or should the focus change to extremes (see Hegerl et al 2011b)? Is seasonal mean exceedance of the prior temperature envelope a good and robust measure that also reflects these other, more complex diagnostics? Lots of food for thought and research! References Allen M R and Tett S F B 1999 Checking for model consistency in optimal finger printing Clim. Dyn. 15 419-34 Hall A 2004 The role of surface albedo feedback in climate J. Clim. 17 1550-68 Hasselmann K 1979 On the signal-to-noise problem in atmospheric response studies Meteorology of Tropical Oceans ed D B Shaw (Bracknell: Royal Meteorological Society) pp 251-9 Hegerl G C, Luterbacher J, Gonzalez-Ruoco F, Tett S F B and Xoplaki E 2011a Influence of human and natural forcing on European seasonal temperatures Nature Geoscience 4 99-103 Hegerl G, Hanlon H and Beierkuhnlein C 2011b Climate science: elusive extremes Nature Geoscience 4 142-3 IPCC 2007 Climate Change 2007: Impacts, Adaption and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed M L Parry, O F Canziani, J P Palutikof, P J van der Linden and C E Hanson (Cambridge: Cambridge University Press) Jansen E et al 2007 Palaeoclimate Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed S Solomon et al (Cambridge: Cambridge University Press) Luterbacher J et al 2004 European seasonal and annual temperature variability, trends, and extremes since 1500 Science 303 1499-503 Mahlstein I, Knutti R, Solomon S and Portmann R W 2011 Early onset of significant local warming in low latitude countries Environ. Res. Lett. 6 034009

Framework for Detection and Localization of Extreme Climate Event with Pixel Recursive Super Resolution

NASA Astrophysics Data System (ADS)

Kim, S. K.; Lee, J.; Zhang, C.; Ames, S.; Williams, D. N.

2017-12-01

Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramat- ically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia

NASA Astrophysics Data System (ADS)

Ganendran, L. B.; Sidhu, L. A.; Catchpole, E. A.; Chambers, L. E.; Dann, P.

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia.

PubMed

Ganendran, L B; Sidhu, L A; Catchpole, E A; Chambers, L E; Dann, P

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

Variability and Predictability of Land-Atmosphere Interactions: Observational and Modeling Studies

NASA Technical Reports Server (NTRS)

Roads, John; Oglesby, Robert; Marshall, Susan; Robertson, Franklin R.

2002-01-01

The overall goal of this project is to increase our understanding of seasonal to interannual variability and predictability of atmosphere-land interactions. The project objectives are to: 1. Document the low frequency variability in land surface features and associated water and energy cycles from general circulation models (GCMs), observations and reanalysis products. 2. Determine what relatively wet and dry years have in common on a region-by-region basis and then examine the physical mechanisms that may account for a significant portion of the variability. 3. Develop GCM experiments to examine the hypothesis that better knowledge of the land surface enhances long range predictability. This investigation is aimed at evaluating and predicting seasonal to interannual variability for selected regions emphasizing the role of land-atmosphere interactions. Of particular interest are the relationships between large, regional and local scales and how they interact to account for seasonal and interannual variability, including extreme events such as droughts and floods. North and South America, including the Global Energy and Water Cycle Experiment Continental International Project (GEWEX GCIP), MacKenzie, and LBA basins, are currently being emphasized. We plan to ultimately generalize and synthesize to other land regions across the globe, especially those pertinent to other GEWEX projects.

Quantification of long-term erosion rates from root exposure/tree age relationships in an alpine meadow catchment

NASA Astrophysics Data System (ADS)

Scuderi, Louis A.

2017-04-01

Erosion rates derived using dendrogeomorphology have been used to quantify slope degradation in many localities globally. However, with the exception of the western United States, most of these estimates are derived from short-lived trees whose lifetimes may not adequately reflect the complete range of slope processes which can include erosion, deposition, impacts of extreme events and even long-term hiatuses. Erosion rate estimates at a given site using standard techniques therefore reflect censored local point erosion estimates rather than long-term rates. We applied a modified dendrogeomorphic approach to rapidly estimate erosion rates from dbh/age relationships to assess the difference between short and long-term rates and found that the mean short-term rate was 0.13 cm/yr with high variability, while the uncensored long-term rate was 0.06 cm/yr. The results indicate that rates calculated from short-lived trees, while possibly appropriate for local short-term point estimates of erosion, are highly variable and may overestimate regional long-term rates by > 50%. While these findings do not invalidate the use of dendrogeomorphology to estimate erosion rates they do suggest that care must be taken to select older trees that incorporate a range of slope histories in order to best approximate regional long-term rates.

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

2015-01-01

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Evaluating historical climate and hydrologic trends in the Central Appalachian region of the United States

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

Climate change is surfacing as one of the most important environmental and social issues of the 21st century. Over the last 100 years, observations show increasing trends in global temperatures and intensity and frequency of precipitation events such as flooding, drought, and extreme storms. Global circulation models (GCM) show similar trends for historic and future climate indicators, albeit with geographic and topographic variability at regional and local scale. In order to assess the utility of GCM projections for hydrologic modeling, it is important to quantify how robust GCM outputs are compared to robust historical observations at finer spatial scales. Previous research in the United States has primarily focused on the Western and Northeastern regions due to dominance of snow melt for runoff and aquifer recharge but the impact of climate warming in the mountainous central Appalachian Region is poorly understood. In this research, we assess the performance of GCM-generated historical climate compared to historical observations primarily in the context of forcing data for macro-scale hydrologic modeling. Our results show significant spatial heterogeneity of modeled climate indices when compared to observational trends at the watershed scale. Observational data is showing considerable variability within maximum temperature and precipitation trends, with consistent increases in minimum temperature. The geographic, temperature, and complex topographic gradient throughout the central Appalachian region is likely the contributing factor in temperature and precipitation variability. Variable climate changes are leading to more severe and frequent climate events such as temperature extremes and storm events, which can have significant impacts on our drinking water supply, infrastructure, and health of all downstream communities.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

The Microphysical Structure of Extreme Precipitation as Inferred from Ground-Based Raindrop Spectra.

NASA Astrophysics Data System (ADS)

Uijlenhoet, Remko; Smith, James A.; Steiner, Matthias

2003-05-01

The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity-rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distributions corresponding to rain rates exceeding 100 mm h1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes in properties of raindrop size distributions in extreme rainfall are largely produced by varying raindrop concentrations. As a result, rainfall integral variables (such as radar reflectivity and rain rate) are roughly proportional to each other, which is consistent with the concept of the so-called equilibrium raindrop size distribution and has profound implications for radar measurement of extreme rainfall. A time series analysis for two contrasting extreme rainfall events supports the hypothesis that the variability of raindrop size distributions for extreme rain rates is strongly number controlled. However, this analysis also reveals that the actual shapes of the (measured and scaled) spectra may differ significantly from storm to storm. This implies that the exponents of power-law radar reflectivity-rain rate relationships may be similar, and close to unity, for different extreme rainfall events, but their prefactors may differ substantially. Consequently, there is no unique radar reflectivity-rain rate relationship for extreme rain rates, but the variability is essentially reduced to one free parameter (i.e., the prefactor). It is suggested that this free parameter may be estimated on the basis of differential reflectivity measurements in extreme rainfall.

Conservation at a slow pace: terrestrial gastropods facing fast-changing climate

PubMed Central

Ansart, Armelle

2017-01-01

Abstract The climate is changing rapidly, and terrestrial ectotherms are expected to be particularly vulnerable to changes in temperature and water regime, but also to an increase in extreme weather events in temperate regions. Physiological responses of terrestrial gastropods to climate change are poorly studied. This is surprising, because they are of biodiversity significance among litter-dwelling species, playing important roles in ecosystem function, with numerous species being listed as endangered and requiring efficient conservation management. Through a summary of our ecophysiological work on snail and slug species, we gained some insights into physiological and behavioural responses to climate change that we can organize into the following four threat categories. (i) Winter temperature and snow cover. Terrestrial gastropods use different strategies to survive sub-zero temperatures in buffered refuges, such as the litter or the soil. Absence of the insulating snow cover exposes species to high variability in temperature. The extent of specific cold tolerance might influence the potential of local extinction, but also of invasion. (ii) Drought and high temperature. Physiological responses involve high-cost processes that protect against heat and dehydration. Some species decrease activity periods, thereby reducing foraging and reproduction time. Related costs and physiological limits are expected to increase mortality. (iii) Extreme events. Although some terrestrial gastropod communities can have a good resilience to fire, storms and flooding, an increase in the frequency of those events might lead to community impoverishment. (iv) Habitat loss and fragmentation. Given that terrestrial gastropods are poorly mobile, landscape alteration generally results in an increased risk of local extinction, but responses are highly variable between species, requiring studies at the population level. There is a great need for studies involving non-invasive methods on the plasticity of physiological and behavioural responses and the ability for local adaptation, considering the spatiotemporally heterogeneous climatic landscape, to allow efficient management of ecosystems and conservation of biodiversity. PMID:28852510

Conservation at a slow pace: terrestrial gastropods facing fast-changing climate.

PubMed

Nicolai, Annegret; Ansart, Armelle

2017-01-01

The climate is changing rapidly, and terrestrial ectotherms are expected to be particularly vulnerable to changes in temperature and water regime, but also to an increase in extreme weather events in temperate regions. Physiological responses of terrestrial gastropods to climate change are poorly studied. This is surprising, because they are of biodiversity significance among litter-dwelling species, playing important roles in ecosystem function, with numerous species being listed as endangered and requiring efficient conservation management. Through a summary of our ecophysiological work on snail and slug species, we gained some insights into physiological and behavioural responses to climate change that we can organize into the following four threat categories. (i) Winter temperature and snow cover. Terrestrial gastropods use different strategies to survive sub-zero temperatures in buffered refuges, such as the litter or the soil. Absence of the insulating snow cover exposes species to high variability in temperature. The extent of specific cold tolerance might influence the potential of local extinction, but also of invasion. (ii) Drought and high temperature. Physiological responses involve high-cost processes that protect against heat and dehydration. Some species decrease activity periods, thereby reducing foraging and reproduction time. Related costs and physiological limits are expected to increase mortality. (iii) Extreme events. Although some terrestrial gastropod communities can have a good resilience to fire, storms and flooding, an increase in the frequency of those events might lead to community impoverishment. (iv) Habitat loss and fragmentation. Given that terrestrial gastropods are poorly mobile, landscape alteration generally results in an increased risk of local extinction, but responses are highly variable between species, requiring studies at the population level. There is a great need for studies involving non-invasive methods on the plasticity of physiological and behavioural responses and the ability for local adaptation, considering the spatiotemporally heterogeneous climatic landscape, to allow efficient management of ecosystems and conservation of biodiversity.

The balance between adaptation to catalysts and competition radius shapes the total wealth, time variability and inequality

NASA Astrophysics Data System (ADS)

Davidovich, Hadar; Louzoun, Yoram

2013-05-01

The globalization of modern markets has led to the emergence of competition between producers in ever growing distances. This opens the interesting question in population dynamics of the effect of long-range competition. We here study a model of non-local competition to test the effect of the competition radius on the wealth distribution, using the framework of a stochastic birth-death process, with non-local interactions. We show that this model leads to non-trivial dynamics that can have implications in other domains of physics. Competition is studied in the context of the catalyst induced growth of autocatalytic agents, representing the growth of capital in the presence of investment opportunities. These agents are competing with all other agents in a given radius on growth possibilities. We show that a large scale competition leads to an extreme localization of the agents, where typically a single aggregate of agents can survive within a given competition radius. The survival of these aggregates is determined by the diffusion rates of the agents and the catalysts. For high and low agent diffusion rates, the agent population is always annihilated, while for intermediate diffusion rates, a finite agent population persists. Increasing the catalyst diffusion rate always leads to a decrease in the average agent population density. The extreme localization of the agents leads to the emergence of intermittent fluctuations, when a large aggregate of agents disappear. As the competition radius increases, so does the average agent density and its spatial variance as well as the volatility.

Streamflow variability in the Chilean Temperate-Mediterranean climate transition (35°S-42°S) during the last 400 years inferred from tree-ring records

NASA Astrophysics Data System (ADS)

Muñoz, Ariel A.; González-Reyes, Alvaro; Lara, Antonio; Sauchyn, David; Christie, Duncan; Puchi, Paulina; Urrutia-Jalabert, Rocío; Toledo-Guerrero, Isadora; Aguilera-Betti, Isabella; Mundo, Ignacio; Sheppard, Paul R.; Stahle, Daniel; Villalba, Ricardo; Szejner, Paul; LeQuesne, Carlos; Vanstone, Jessica

2016-12-01

As rainfall in South-Central Chile has decreased in recent decades, local communities and industries have developed an understandable concern about their threatened water supply. Reconstructing streamflows from tree-ring data has been recognized as a useful paleoclimatic tool in providing long-term perspectives on the temporal characteristics of hydroclimate systems. Multi-century long streamflow reconstructions can be compared to relatively short instrumental observations in order to analyze the frequency of low and high water availability through time. In this work, we have developed a Biobío River streamflow reconstruction to explore the long-term hydroclimate variability at the confluence of the Mediterranean-subtropical and the Temperate-humid climate zones, two regions represented by previous reconstructions of the Maule and Puelo Rivers, respectively. In a suite of analyses, the Biobío River reconstruction proves to be more similar to the Puelo River than the Maule River, despite its closer geographic proximity to the latter. This finding corroborates other studies with instrumental data that identify 37.5°S as a latitudinal confluence of two climate zones. The analyzed rivers are affected by climate forcings on interannual and interdecadal time-scales, Tropical (El Niño Southern Oscillation) and Antarctic (Southern Annular Mode; SAM). Longer cycles found, around 80-years, are well correlated only with SAM variation, which explains most of the variance in the Biobío and Puelo rivers. This cycle also has been attributed to orbital forcing by other authors. All three rivers showed an increase in the frequency of extreme high and low flow events in the twentieth century. The most extreme dry and wet years in the instrumental record (1943-2000) were not the most extreme of the past 400-years reconstructed for the three rivers (1600-2000), yet both instrumental record years did rank in the five most extreme of the streamflow reconstructions as a whole. These findings suggest a high level of natural variability in the hydro-climatic conditions of the region, where extremes characterized the twentieth century. This information is particularly useful when evaluating and improving a wide variety of water management models that apply to water resources that are sensitive to agricultural and hydropower industries.

The role of climate variability in extreme floods in Europe

NASA Astrophysics Data System (ADS)

Guimarães Nobre, Gabriela; Aerts, Jeroen C. J. H.; Jongman, Brenden; Ward, Philip J.

2017-04-01

Between 1980 and 2015, Europe experienced 18% of worldwide weather-related loss events, which accounted for over US500 billion in damage. Consequently, it is urgent to further develop adaptation strategies to mitigate the consequences of weather-related disasters, such as floods. Europe's capability to prepare for such disasters is challenged by a large range of uncertainties and a limited understanding of the driving forces of hydrometeorological hazards. One of the major sources of uncertainty is the relationship between climate variability and weather-related losses. Previous studies show that climate variability drives temporal changes in hydrometereological variables in Europe. However, their influence on flood risk has received little attention. We investigated the influence of the positive and negative phases of El Niño Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO), on the seasonal frequency and intensity of extreme rainfall, and anomalies in flood occurrence and damage compared to the neutral phases of the indices of climate variability. Using statistical methods to analyze relationships between the indices of climate variability and four indicators of flooding, we found that positive and negative phases of NAO and AO are associated with more (or less) frequent and intense seasonal extreme rainfall over large areas of Europe. The relationship between ENSO and both the occurrence of extreme rainfall and intensity of extreme rainfall in Europe is much smaller than the relationship with NAO or AO, but still significant in some regions. We observe that flood damage and flood occurrence have strong links with climate variability, especially in southern and eastern Europe. Therefore, when investigating flooding across Europe, all three indices of climate variability should be considered. Seasonal forecasting of flooding could be enhanced by the inclusion of climate variability indicators .

Diagnosing causes of extreme aerosol optical depth events

NASA Astrophysics Data System (ADS)

Bernstein, D. N.; Sullivan, R.; Crippa, P.; Thota, A.; Pryor, S. C.

2017-12-01

Aerosol burdens and optical properties exhibit substantial spatiotemporal variability, and simulation of current and possible future aerosol burdens and characteristics exhibits relatively high uncertainty due to uncertainties in emission estimates and in chemical and physical processes associated with aerosol formation, dynamics and removal. We report research designed to improve understanding of the causes and characteristics of extreme aerosol optical depth (AOD) at the regional scale, and diagnose and attribute model skill in simulating these events. Extreme AOD events over the US Midwest are selected by identifying all dates on which AOD in a MERRA-2 reanalysis grid cell exceeds the local seasonally computed 90th percentile (p90) value during 2004-2016 and then finding the dates on which the highest number of grid cells exceed their local p90. MODIS AOD data are subsequently used to exclude events dominated by wildfires. MERRA-2 data are also analyzed within a synoptic classification to determine in what ways the extreme AOD events are atypical and to identify possible meteorological `finger-prints' that can be detected in regional climate model simulations of future climate states to project possible changes in the occurrence of extreme AOD. Then WRF-Chem v3.6 is applied at 12-km resolution and regridded to the MERRA-2 resolution over eastern North America to quantify model performance, and also evaluated using in situ measurements of columnar AOD (AERONET) and near-surface PM2.5 (US EPA). Finally the sensitivity to (i) spin-up time (including procedure used to spin-up the chemistry), (ii) modal versus sectional aerosol schemes, (iii) meteorological nudging, (iv) chemistry initial and boundary conditions, and (v) anthropogenic emissions is quantified. Despite recent declines in mean AOD, supraregional (> 1000 km) extreme AOD events continue to occur. During these events AOD exceeds 0.6 in many Midwestern grid cells for multiple consecutive days. In all seasons WRF-Chem exhibits some skill in reproducing the intensity of these events, but not the precise location of the AOD maximum. Model skill is generally (but not uniformly) highest for simulations employing MOZART LBC/IBC, modal aerosol description, meteorological nudging and a 3 day spin-up, with little or no sensitivity to longer spin up times.

Ground level measurements of air conductivities under Florida thunderstorms

NASA Technical Reports Server (NTRS)

Blakeslee, Richard J.; Krider, E. P.

1992-01-01

Values of the positive and negative polar conductivities under summer thunderstorms in Florida are highly variable and exhibit a significant electrode effect, but the total conductivity usually remains close to values found in fair weather, 0.4 to 1.8 x 10 exp -14 S/m. With these values a method proposed by Krider and Musser (1982) for estimating the total conductivity from changes in the slope of the electric field recovery following a lightning discharge will be extremely sensitive to small time variations in the local Maxwell current density and must be modified to include these effects.

Extreme air-sea surface turbulent fluxes in mid latitudes - estimation, origins and mechanisms

NASA Astrophysics Data System (ADS)

Gulev, Sergey; Natalia, Tilinina

2014-05-01

Extreme turbulent heat fluxes in the North Atlantic and North Pacific mid latitudes were estimated from the modern era and first generation reanalyses (NCEP-DOE, ERA-Interim, MERRA NCEP-CFSR, JRA-25) for the period from 1979 onwards. We used direct surface turbulent flux output as well as reanalysis state variables from which fluxes have been computed using COARE-3 bulk algorithm. For estimation of extreme flux values we analyzed surface flux probability density distribution which was approximated by Modified Fisher-Tippett distribution. In all reanalyses extreme turbulent heat fluxes amount to 1500-2000 W/m2 (for the 99th percentile) and can exceed 2000 W/m2 for higher percentiles in the western boundary current extension (WBCE) regions. Different reanalyses show significantly different shape of MFT distribution, implying considerable differences in the estimates of extreme fluxes. The highest extreme turbulent latent heat fluxes are diagnosed in NCEP-DOE, ERA-Interim and NCEP-CFSR reanalyses with the smallest being in MERRA. These differences may not necessarily reflect the differences in mean values. Analysis shows that differences in statistical properties of the state variables are the major source of differences in the shape of PDF of fluxes and in the estimates of extreme fluxes while the contribution of computational schemes used in different reanalyses is minor. The strongest differences in the characteristics of probability distributions of surface fluxes and extreme surface flux values between different reanalyses are found in the WBCE extension regions and high latitudes. In the next instance we analyzed the mechanisms responsible for forming surface turbulent fluxes and their potential role in changes of midlatitudinal heat balance. Midlatitudinal cyclones were considered as the major mechanism responsible for extreme turbulent fluxes which are typically occur during the cold air outbreaks in the rear parts of cyclones when atmospheric conditions provide locally high winds and air-sea temperature gradients. For this purpose we linked characteristics of cyclone activity over the midlatitudinal oceans with the extreme surface turbulent heat fluxes. Cyclone tracks and parameters of cyclone life cycle (deepening rates, propagation velocities, life time and clustering) were derived from the same reanalyses using state of the art numerical tracking algorithm. The main questions addressed in this study are (i) through which mechanisms extreme surface fluxes are associated with cyclone activity? and (ii) which types of cyclones are responsible for forming extreme turbulent fluxes? Our analysis shows that extreme surface fluxes are typically associated not with cyclones themselves but rather with cyclone-anticyclone interaction zones. This implies that North Atlantic and North Pacific series of intense cyclones do not result in the anomalous surface fluxes. Alternatively, extreme fluxes are most frequently associated with blocking situations, particularly with the intensification of the Siberian and North American Anticyclones providing cold-air outbreaks over WBC regions.

Changes in extremes due to half a degree warming in observations and models

NASA Astrophysics Data System (ADS)

Fischer, E. M.; Schleussner, C. F.; Pfleiderer, P.

2017-12-01

Assessing the climate impacts of half-a-degree warming increments is high on the post-Paris science agenda. Discriminating those effects is particularly challenging for climate extremes such as heavy precipitation and heat extremes for which model uncertainties are generally large, and for which internal variability is so important that it can easily offset or strongly amplify the forced local changes induced by half a degree warming. Despite these challenges we provide evidence for large-scale changes in the intensity and frequency of climate extremes due to half a degree warming. We first assess the difference in extreme climate indicators in observational data for the 1960s and 1970s versus the recent past, two periods differ by half a degree. We identify distinct differences for the global and continental-scale occurrence of heat and heavy precipitation extremes. We show that those observed changes in heavy precipitation and heat extremes broadly agree with simulated historical differences and are informative for the projected differences between 1.5 and 2°C warming despite different radiative forcings. We therefore argue that evidence from the observational record can inform the debate about discernible climate impacts in the light of model uncertainty by providing a conservative estimate of the implications of 0.5°C warming. A limitation of using the observational record arises from potential non-linearities in the response of climate extremes to a certain level of warming. We test for potential non-linearities in the response of heat and heavy precipitation extremes in a large ensemble of transient climate simulations. We further quantify differences between a time-window approach in a coupled model large ensemble vs. time-slice experiments using prescribed SST experiments performed in the context of the HAPPI-MIP project. Thereby we provide different lines of evidence that half a degree warming leads to substantial changes in the expected occurrence of heat and heavy precipitation extremes.

Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society.

PubMed

Santo, H; Taylor, P H; Gibson, R

2016-09-01

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958-2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different.

Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society

NASA Astrophysics Data System (ADS)

Santo, H.; Taylor, P. H.; Gibson, R.

2016-09-01

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958-2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different.

Inter-annual Variability of Temperature and Extreme Heat Events during the Nairobi Warm Season

NASA Astrophysics Data System (ADS)

Scott, A.; Misiani, H. O.; Zaitchik, B. F.; Ouma, G. O.; Anyah, R. O.; Jordan, A.

2016-12-01

Extreme heat events significantly stress all organisms in the ecosystem, and are likely to be amplified in peri-urban and urban areas. Understanding the variability and drivers behind these events is key to generating early warnings, yet in Equatorial East Africa, this information is currently unavailable. This study uses daily maximum and minimum temperature records from weather stations within Nairobi and its surroundings to characterize variability in daily minimum temperatures and the number of extreme heat events. ERA-Interim reanalysis is applied to assess the drivers of these events at event and seasonal time scales. At seasonal time scales, high temperatures in Nairobi are a function of large scale climate variability associated with the Atlantic Multi-decadal Oscillation (AMO) and Global Mean Sea Surface Temperature (GMSST). Extreme heat events, however, are more strongly associated with the El Nino Southern Oscillation (ENSO). For instance, the persistence of AMO and ENSO, in particular, provide a basis for seasonal prediction of extreme heat events/days in Nairobi. It is also apparent that the temporal signal from extreme heat events in tropics differs from classic heat wave definitions developed in the mid-latitudes, which suggests that a new approach for defining these events is necessary for tropical regions.

Analysis of walking variability through simultaneous evaluation of the head, lumbar, and lower-extremity acceleration in healthy youth

PubMed Central

Toda, Haruki; Nagano, Akinori; Luo, Zhiwei

2016-01-01

[Purpose] The purpose of this study was to clarify whether walking speed affects acceleration variability of the head, lumbar, and lower extremity by simultaneously evaluating of acceleration. [Subjects and Methods] Twenty young individuals recruited from among the staff at Kurashiki Heisei Hospital participated in this study. Eight accelerometers were used to measure the head, lumbar and lower extremity accelerations. The participants were instructed to walk at five walking speeds prescribed by a metronome. Acceleration variability was assessed by a cross-correlation analysis normalized using z-transform in order to evaluate stride-to-stride variability. [Results] Vertical acceleration variability was the smallest in all body parts, and walking speed effect had laterality. Antero-posterior acceleration variability was significantly associated with walking speed at sites other than the head. Medio-lateral acceleration variability of the bilateral hip alone was smaller than the antero-posterior variability. [Conclusion] The findings of this study suggest that the effect of walking speed changes on the stride-to-stride acceleration variability was individual for each body parts, and differs among directions. PMID:27390419

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

A new design approach based on differential evolution algorithm for geometric optimization of magnetorheological brakes

NASA Astrophysics Data System (ADS)

Le-Duc, Thang; Ho-Huu, Vinh; Nguyen-Thoi, Trung; Nguyen-Quoc, Hung

2016-12-01

In recent years, various types of magnetorheological brakes (MRBs) have been proposed and optimized by different optimization algorithms that are integrated in commercial software such as ANSYS and Comsol Multiphysics. However, many of these optimization algorithms often possess some noteworthy shortcomings such as the trap of solutions at local extremes, or the limited number of design variables or the difficulty of dealing with discrete design variables. Thus, to overcome these limitations and develop an efficient computation tool for optimal design of the MRBs, an optimization procedure that combines differential evolution (DE), a gradient-free global optimization method with finite element analysis (FEA) is proposed in this paper. The proposed approach is then applied to the optimal design of MRBs with different configurations including conventional MRBs and MRBs with coils placed on the side housings. Moreover, to approach a real-life design, some necessary design variables of MRBs are considered as discrete variables in the optimization process. The obtained optimal design results are compared with those of available optimal designs in the literature. The results reveal that the proposed method outperforms some traditional approaches.

Forecasting seasonal hydrologic response in major river basins

NASA Astrophysics Data System (ADS)

Bhuiyan, A. M.

2014-05-01

Seasonal precipitation variation due to natural climate variation influences stream flow and the apparent frequency and severity of extreme hydrological conditions such as flood and drought. To study hydrologic response and understand the occurrence of extreme hydrological events, the relevant forcing variables must be identified. This study attempts to assess and quantify the historical occurrence and context of extreme hydrologic flow events and quantify the relation between relevant climate variables. Once identified, the flow data and climate variables are evaluated to identify the primary relationship indicators of hydrologic extreme event occurrence. Existing studies focus on developing basin-scale forecasting techniques based on climate anomalies in El Nino/La Nina episodes linked to global climate. Building on earlier work, the goal of this research is to quantify variations in historical river flows at seasonal temporal-scale, and regional to continental spatial-scale. The work identifies and quantifies runoff variability of major river basins and correlates flow with environmental forcing variables such as El Nino, La Nina, sunspot cycle. These variables are expected to be the primary external natural indicators of inter-annual and inter-seasonal patterns of regional precipitation and river flow. Relations between continental-scale hydrologic flows and external climate variables are evaluated through direct correlations in a seasonal context with environmental phenomenon such as sun spot numbers (SSN), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO). Methods including stochastic time series analysis and artificial neural networks are developed to represent the seasonal variability evident in the historical records of river flows. River flows are categorized into low, average and high flow levels to evaluate and simulate flow variations under associated climate variable variations. Results demonstrated not any particular method is suited to represent scenarios leading to extreme flow conditions. For selected flow scenarios, the persistence model performance may be comparable to more complex multivariate approaches, and complex methods did not always improve flow estimation. Overall model performance indicates inclusion of river flows and forcing variables on average improve model extreme event forecasting skills. As a means to further refine the flow estimation, an ensemble forecast method is implemented to provide a likelihood-based indication of expected river flow magnitude and variability. Results indicate seasonal flow variations are well-captured in the ensemble range, therefore the ensemble approach can often prove efficient in estimating extreme river flow conditions. The discriminant prediction approach, a probabilistic measure to forecast streamflow, is also adopted to derive model performance. Results show the efficiency of the method in terms of representing uncertainties in the forecasts.

33 CFR 100.T01-0103 - Special Local Regulation; Extreme Sailing Series Boston; Boston Harbor; Boston, MA.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Sailing Series Boston; Boston Harbor; Boston, MA. 100.T01-0103 Section 100.T01-0103 Navigation and... NAVIGABLE WATERS § 100.T01-0103 Special Local Regulation; Extreme Sailing Series Boston; Boston Harbor... special local regulation area is designed to restrict vessel traffic, including all non-motorized vessels...

Climate Variability and Human Migration in the Netherlands, 1865–1937

PubMed Central

Jennings, Julia A.; Gray, Clark L.

2014-01-01

Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century. PMID:25937689

Extreme Value Analysis of hydro meteorological extremes in the ClimEx Large-Ensemble

NASA Astrophysics Data System (ADS)

Wood, R. R.; Martel, J. L.; Willkofer, F.; von Trentini, F.; Schmid, F. J.; Leduc, M.; Frigon, A.; Ludwig, R.

2017-12-01

Many studies show an increase in the magnitude and frequency of hydrological extreme events in the course of climate change. However the contribution of natural variability to the magnitude and frequency of hydrological extreme events is not yet settled. A reliable estimate of extreme events is from great interest for water management and public safety. In the course of the ClimEx Project (www.climex-project.org) a new single-model large-ensemble was created by dynamically downscaling the CanESM2 large-ensemble with the Canadian Regional Climate Model version 5 (CRCM5) for an European Domain and a Northeastern North-American domain. By utilizing the ClimEx 50-Member Large-Ensemble (CRCM5 driven by CanESM2 Large-Ensemble) a thorough analysis of natural variability in extreme events is possible. Are the current extreme value statistical methods able to account for natural variability? How large is the natural variability for e.g. a 1/100 year return period derived from a 50-Member Large-Ensemble for Europe and Northeastern North-America? These questions should be answered by applying various generalized extreme value distributions (GEV) to the ClimEx Large-Ensemble. Hereby various return levels (5-, 10-, 20-, 30-, 60- and 100-years) based on various lengths of time series (20-, 30-, 50-, 100- and 1500-years) should be analyzed for the maximum one day precipitation (RX1d), the maximum three hourly precipitation (RX3h) and the streamflow for selected catchments in Europe. The long time series of the ClimEx Ensemble (7500 years) allows us to give a first reliable estimate of the magnitude and frequency of certain extreme events.

Extreme Fire Severity Patterns in Topographic, Convective and Wind-Driven Historical Wildfires of Mediterranean Pine Forests

PubMed Central

Lecina-Diaz, Judit; Alvarez, Albert; Retana, Javier

2014-01-01

Crown fires associated with extreme fire severity are extremely difficult to control. We have assessed fire severity using differenced Normalized Burn Ratio (dNBR) from Landsat imagery in 15 historical wildfires of Pinus halepensis Mill. We have considered a wide range of innovative topographic, fuel and fire behavior variables with the purposes of (1) determining the variables that influence fire severity patterns among fires (considering the 15 wildfires together) and (2) ascertaining whether different variables affect extreme fire severity within the three fire types (topographic, convective and wind-driven fires). The among-fires analysis showed that fires in less arid climates and with steeper slopes had more extreme severity. In less arid conditions there was more crown fuel accumulation and closer forest structures, promoting high vertical and horizontal fuel continuity and extreme fire severity. The analyses carried out for each fire separately (within fires) showed more extreme fire severity in areas in northern aspects, with steeper slopes, with high crown biomass and in climates with more water availability. In northern aspects solar radiation was lower and fuels had less water limitation to growth which, combined with steeper slopes, produced more extreme severity. In topographic fires there was more extreme severity in northern aspects with steeper slopes and in areas with more water availability and high crown biomass; in convection-dominated fires there was also more extreme fire severity in northern aspects with high biomass; while in wind-driven fires there was only a slight interaction between biomass and water availability. This latter pattern could be related to the fact that wind-driven fires spread with high wind speed, which could have minimized the effect of other variables. In the future, and as a consequence of climate change, new zones with high crown biomass accumulated in non-common drought areas will be available to burn as extreme severity wildfires. PMID:24465492

Extreme fire severity patterns in topographic, convective and wind-driven historical wildfires of Mediterranean pine forests.

PubMed

Lecina-Diaz, Judit; Alvarez, Albert; Retana, Javier

2014-01-01

Crown fires associated with extreme fire severity are extremely difficult to control. We have assessed fire severity using differenced Normalized Burn Ratio (dNBR) from Landsat imagery in 15 historical wildfires of Pinus halepensis Mill. We have considered a wide range of innovative topographic, fuel and fire behavior variables with the purposes of (1) determining the variables that influence fire severity patterns among fires (considering the 15 wildfires together) and (2) ascertaining whether different variables affect extreme fire severity within the three fire types (topographic, convective and wind-driven fires). The among-fires analysis showed that fires in less arid climates and with steeper slopes had more extreme severity. In less arid conditions there was more crown fuel accumulation and closer forest structures, promoting high vertical and horizontal fuel continuity and extreme fire severity. The analyses carried out for each fire separately (within fires) showed more extreme fire severity in areas in northern aspects, with steeper slopes, with high crown biomass and in climates with more water availability. In northern aspects solar radiation was lower and fuels had less water limitation to growth which, combined with steeper slopes, produced more extreme severity. In topographic fires there was more extreme severity in northern aspects with steeper slopes and in areas with more water availability and high crown biomass; in convection-dominated fires there was also more extreme fire severity in northern aspects with high biomass; while in wind-driven fires there was only a slight interaction between biomass and water availability. This latter pattern could be related to the fact that wind-driven fires spread with high wind speed, which could have minimized the effect of other variables. In the future, and as a consequence of climate change, new zones with high crown biomass accumulated in non-common drought areas will be available to burn as extreme severity wildfires.

Response of Urban Systems to Climate Change in Europe: Heat Stress Exposure and the Effect on Human Health

NASA Astrophysics Data System (ADS)

Stevens, Catherine; Thomas, Bart; Grommen, Mart

2015-04-01

Climate change is driven by global processes such as the global ocean circulation and its variability over time leading to changing weather patterns on regional scales as well as changes in the severity and occurrence of extreme events such as heavy rain- and windstorms, floods, drought, heat waves, etc. The summer 2003 European heat wave was the hottest summer on record in Europe over the past centuries leading to health crises in several countries like France and caused up to 70.000 excess deaths over four months in Central and Western Europe. The main risks induced by global climate change in urbanised areas are considered to be overheating and resulting health effects, increased exposure to flood events, increased damage losses from extreme weather conditions but also shortages in the provision of life-sustaining services. Moreover, the cities themselves create specific or inherent risks and urban adaptation is often very demanding. As most of Europe's inhabitants live in cities, it is of particular relevance to examine the impact of climate variability on urban areas and their populations. The present study focusses on the identification of heat stress variables related to human health and the extraction of this information by processing daily temperature statistics of local urban climate simulations over multiple timeframes of 20 years and three different European cities based on recent, near future and far future global climate predictions. The analyses have been conducted in the framework of the NACLIM FP7 project funded by the European Commission involving local stakeholders such as the cities of Antwerp (Belgium), Berlin (Germany) and Almada (Portugal) represented by different climate and urban characteristics. Apart from the urban-rural temperature increment (urban heat island effect), additional heat stress parameters such as the average number of heat wave days together with their duration and intensities have been covered during this research. In a subsequent step, the heat stress variables are superposed on relevant socio-economic datasets targeting total population and its distribution per age class as well as vulnerable institutions such as hospitals, schools, rest homes and child/day care facilities in order to generate heat stress exposure maps for each use case city and various climate, urban planning and mitigation scenarios. The specifications and requirements for the various scenarios have been consolidated in close collaboration with the local stakeholders during dedicated end-users workshops. The results of this study will allow urban planners and policy makers facing the challenges of climate change and develop sound strategies for evolving towards sustainable and climate resilient cities.

Extreme Events and Energy Providers: Science and Innovation

NASA Astrophysics Data System (ADS)

Yiou, P.; Vautard, R.

2012-04-01

Most socio-economic regulations related to the resilience to climate extremes, from infrastructure or network design to insurance premiums, are based on a present-day climate with an assumption of stationarity. Climate extremes (heat waves, cold spells, droughts, storms and wind stilling) affect in particular energy production, supply, demand and security in several ways. While national, European or international projects have generated vast amounts of climate projections for the 21st century, their practical use in long-term planning remains limited. Estimating probabilistic diagnostics of energy user relevant variables from those multi-model projections will help the energy sector to elaborate medium to long-term plans, and will allow the assessment of climate risks associated to those plans. The project "Extreme Events for Energy Providers" (E3P) aims at filling a gap between climate science and its practical use in the energy sector and creating in turn favourable conditions for new business opportunities. The value chain ranges from addressing research questions directly related to energy-significant climate extremes to providing innovative tools of information and decision making (including methodologies, best practices and software) and climate science training for the energy sector, with a focus on extreme events. Those tools will integrate the scientific knowledge that is developed by scientific communities, and translate it into a usable probabilistic framework. The project will deliver projection tools assessing the probabilities of future energy-relevant climate extremes at a range of spatial scales varying from pan-European to local scales. The E3P project is funded by the Knowledge and Innovation Community (KIC Climate). We will present the mechanisms of interactions between academic partners, SMEs and industrial partners for this project. Those mechanisms are elementary bricks of a climate service.

The role of the subtropical North Atlantic water cycle in recent US extreme precipitation events

NASA Astrophysics Data System (ADS)

Li, Laifang; Schmitt, Raymond W.; Ummenhofer, Caroline C.

2018-02-01

The role of the oceanic water cycle in the record-breaking 2015 warm-season precipitation in the US is analyzed. The extreme precipitation started in the Southern US in the spring and propagated northward to the Midwest and the Great Lakes in the summer of 2015. This seasonal evolution of precipitation anomalies represents a typical mode of variability of US warm-season precipitation. Analysis of the atmospheric moisture flux suggests that such a rainfall mode is associated with moisture export from the subtropical North Atlantic. In the spring, excessive precipitation in the Southern US is attributable to increased moisture flux from the northwestern portion of the subtropical North Atlantic. The North Atlantic moisture flux interacts with local soil moisture which enables the US Midwest to draw more moisture from the Gulf of Mexico in the summer. Further analysis shows that the relationship between the rainfall mode and the North Atlantic water cycle has become more significant in recent decades, indicating an increased likelihood of extremes like the 2015 case. Indeed, two record-high warm-season precipitation events, the 1993 and 2008 cases, both occurred in the more recent decades of the 66 year analysis period. The export of water from the North Atlantic leaves a marked surface salinity signature. The salinity signature appeared in the spring preceding all three extreme precipitation events analyzed in this study, i.e. a saltier-than-normal subtropical North Atlantic in spring followed by extreme Midwest precipitation in summer. Compared to the various sea surface temperature anomaly patterns among the 1993, 2008, and 2015 cases, the spatial distribution of salinity anomalies was much more consistent during these extreme flood years. Thus, our study suggests that preseason salinity patterns can be used for improved seasonal prediction of extreme precipitation in the Midwest.

Does high diurnal variability in a reef flat from Ofu, American Samoa confer resistance to ocean acidification?

NASA Astrophysics Data System (ADS)

Koweek, D.; Samuel, L.; Mucciarone, D. A.; Woodson, C. B.; Monismith, S. G.; Dunbar, R. B.

2012-12-01

Forecasts for coral reefs under various ocean acidification scenarios are becoming increasingly complex due to significant inter-site variability in biogeochemistry, ecology, and physical oceanography. The reef flats of Ofu, American Samoa are a potential end-member of this vulnerability spectrum due to extremely high diurnal variability in their biogeochemistry. Here we present coupled biogeochemical and physical oceanographic measurements from a shallow reef flat on Ofu in November 2011. We observed diurnal temperature ranges of up to 7°C, along with diurnal pH and dissolved oxygen ranges of 0.6 units, and 160 percent of saturation, respectively. Carbon system measurements were less extreme. Alkalinity varied between 2240-2360 μmol/kg and total dissolved inorganic carbon (TDIC) ranged between 1850-2100 μmol/kg during the diurnal cycle. These observations suggest diurnal ranges of ~240ppm CO2 and 1.5 units of ΩAr. The larger diurnal range in TDIC relative to alkalinity suggests a reef environment dominated by photosynthesis. From these observations, we explore the balance between the dominant biogeochemical processes of production and calcification on the reef flat in more detail, along with its implication for conferring resistance to ocean acidification. We use calcification rate estimates to provide insight to patterns of day and night growth and/or dissolution on the reef. Finally, we present evidence of tidal modulation of the biogeochemical signals and discuss the role of localized physical circulation in helping to determine a reef's vulnerability to ocean acidification.

The impact of inter-annual rainfall variability on African savannas changes with mean rainfall.

PubMed

Synodinos, Alexis D; Tietjen, Britta; Lohmann, Dirk; Jeltsch, Florian

2018-01-21

Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520-780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580-780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during 'dry' extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating the ClimEx Single Model Large Ensemble in Comparison with EURO-CORDEX Results of Seasonal Means and Extreme Precipitation Indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Brisette, F.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several extreme indicators like R95pTOT, RX5day and others are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

NASA Astrophysics Data System (ADS)

Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Objective local weather types with applications on urban air pollution and on mortality with chronicle illnesses

NASA Astrophysics Data System (ADS)

Mika, Janos; Ivady, Anett; Fulop, Andrea; Makra, László

2010-05-01

Synoptic climatology i.e. classification of the endless variability of the everyday weather states according to the pressure configuration and frontal systems relative to the point, or region of interest has long history in meteorology. Its logical alternative, i.e. classification of weather according to the observed local weather elements was less popular until the recent times when the numerical weather forecasts became able to outline not only the synoptic situation, but the near-surface meteorological variables, as well. Nowadays the computer-based statistical facilities are able to operate with matrices of multivariate diurnal samples, as well. The paper presents an attempt to define a set of local weather types using point-wise series at five rural stations, Szombathely, Pécs, Budapest, Szeged és Debrecen in the 1961-1990 reference period. Ten local variables are used, i.e. the diurnal mean temperature, the diurnal temperature range; the cloudiness, the sunshine duration, the water vapour pressure, the precipitation in a logarithmic scale, also differing trace (below 0.1 mm) and no precipitation, the relative humidity and wind speed, including the more extremity indicators of the two latter parameters, i.e. number of hours with over 80 % relative humidity and over 15 m/s wind gusts. Factor analysis of these ten variables was performed leading to 5 fairly independent variables retained for cluster analysis to obtain the local weather types. Hierarchical cluster analysis was performed to classify the 840-930 days within each month of the 30 years period. Furthers neighbour approach was preferred based on Euclidean metrics to establish optimum number of types. The 12 months and the 5 stations exhibited slightly different results but the optimum number of the types was always between 4 and 12 which is a quite reasonable number from practical considerations. According to a further reasonable compromise, the common number of the types not too bad in either stations or months defines that the common optimum number of local weather types is nine. This set of weather types, specified for each station, was used to "explain" the possible portion of local inter-diurnal variance of seven daily urban air quality measurements, i.e. CO, NO, NO2, NOx, O3, SO2 and PM10. Another set of data for testing the types are the mortalities with chronicle illnesses, i.e. cardio-vascular and respiratory illnesses. This set of 35 years data (1971-2005) is layered for capital city (Budapest, 2 million inhabitants) and rest of the countries (max. 200 000 inhab.). The use of complex weather types is likely better than the common use of individual weather elements, e.g. diurnal mean temperature or a kind of bioclimatic index. The ability of the types to decrease the variability is also compared for both sets of target variables to the analogous ability of macrosynoptic classification by Peczely. The results are also discussed by grouping the investigated contaminants according to their origin.

Phase Locking between Atmospheric Convectively Coupled Equatorial Kelvin Waves and the Diurnal Cycle of Precipitation over the Maritime Continent

NASA Astrophysics Data System (ADS)

Flatau, M. K.; Baranowski, D. B.; Flatau, P. J.; Matthews, A. J.

2016-12-01

Although the importance of the Maritime Continent to the global atmospheric circulation has been long recognized, many researchers have argued that scale separation prevents local processes, such as the local diurnal cycle of precipitation, from directly influencing global scale phenomena such as the variability of atmospheric circulation associated with the equatorial waves. In our study we show that in fact multiscale interactions, which link processes in local and global scales, may play a crucial role for propagation of the CCKWs, which along with the Madden-Julian Oscillation (MJO) are the main eastward propagating component of intraseasonal variability. In our study, we show that not only do CCKWs bring excess amounts of precipitation to the Maritime Continent, but events which are phase locked with the local diurnal cycle of convection have a precipitation signal up to three times larger than average. That means that CCKWs are a primary candidate for extreme precipitation events over the densely populated areas of Indonesia and Malaysia. The complex terrain created by mixture of oceans and lands within the Maritime Continent is unique: the distance between the two main land masses at the equator (islands of Sumatra and Borneo) is approximately the same as the distance travelled by a CCKW in one day. Therefore a CCKW event that is synchronized with a local diurnal cycle over Sumatra is likely to be synchronized over Borneo as well. We find that CCKWs, which are in phase with the local diurnal cycle of precipitation over Sumatra, Borneo and surrounding seas, have a 40% larger chance to successfully cross the Maritime Continent than other CCKWs. That unique feature is a likely a clear example of a multiscale interaction within the region.

Reply to Stone Et Al.: Human-Made Role in Local Temperature Extremes

NASA Technical Reports Server (NTRS)

Hansen, James; Sato, Makiko; Ruedy, Reto A.

2013-01-01

Stone et al. find that their analysis is unable to show a causal relation of local temperature anomalies, such as in Texas in 2011, with global warming. It was because of limitations in such local analyses that we reframed the problem in our report, separating the task of attribution of the causes of global warming from the task of quantifying changes in the likelihood of extreme local temperature anomalies.

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity.

PubMed

Tsai, Kuo-Ting; Hu, Chin-Kun; Li, Kuan-Wei; Hwang, Wen-Liang; Chou, Ya-Hui

2018-05-23

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.

Characterization of extreme air-sea turbulent fluxes

NASA Astrophysics Data System (ADS)

Gulev, Sergey; Belyaev, Konstantin

2017-04-01

Extreme ocean-atmosphere turbulent fluxes play a critical role in the convective processes in the mid and subpolar latitudes and may also affect a variety of atmospheric processes, such as generation and re-intensification of extreme cyclones in the areas of the mid latitude storm tracks. From the ocean dynamics perspective, specifically for quantifying extreme vertical mixing, characterization of the extreme fluxes requires, besides estimation of the extreme events, also consideration of the relative extremeness of surface fluxes and their timing, e.g. the duration of periods of high surface fluxes. In order to comprehensively characterize extreme turbulent fluxes at sea surface we propose a formalism based upon probability density distributions of surface turbulent fluxes and flux-related variables. Individual absolute flux extremes were derived using Modified Fisher-Tippett (MFT) distribution of turbulent fluxes. Then, we extend this distribution to the fractional distribution, characterizing the fraction of time-integrated turbulent heat flux provided by the fluxes exceeding a given percentile. Finally, we consider the time durations during which fluxes of a given intensity provide extreme accumulations of heat loss from the surface. For estimation of these characteristics of surface fluxes we use fluxes recomputed from the state variables available from modern era reanalyses (ERA-Interim, MERRA and CFSR) for the period from 1979 onwards. Applications of the formalism to the VOS (Voluntary Observing Ship) - based surface fluxes are also considered. We discuss application of the new metrics of mesoscale and synoptic variability of surface fluxes to the dynamics of mixed layer depth in the North Atlantic.

Effect of elevation on extreme precipitation of short durations: evidences of orographic signature on the parameters of Depth-Duration-Frequency curves

NASA Astrophysics Data System (ADS)

Avanzi, Francesco; De Michele, Carlo; Gabriele, Salvatore; Ghezzi, Antonio; Rosso, Renzo

2015-04-01

Here, we show how atmospheric circulation and topography rule the variability of depth-duration-frequency (DDF) curves parameters, and we discuss how this variability has physical implications on the formation of extreme precipitations at high elevations. A DDF is a curve ruling the value of the maximum annual precipitation H as a function of duration D and the level of probability F. We consider around 1500 stations over the Italian territory, with at least 20 years of data of maximum annual precipitation depth at different durations. We estimated the DDF parameters at each location by using the asymptotic distribution of extreme values, i.e. the so-called Generalized Extreme Value (GEV) distribution, and considering a statistical simple scale invariance hypothesis. Consequently, a DDF curve depends on five different parameters. A first set relates H with the duration (namely, the mean value of annual maximum precipitation depth for unit duration and the scaling exponent), while a second set links H to F (namely, a scale, position and shape parameter). The value of the shape parameter has consequences on the type of random variable (unbounded, upper or lower bounded). This extensive analysis shows that the variability of the mean value of annual maximum precipitation depth for unit duration obeys to the coupled effect of topography and modal direction of moisture flux during extreme events. Median values of this parameter decrease with elevation. We called this phenomenon "reverse orographic effect" on extreme precipitation of short durations, since it is in contrast with general knowledge about the orographic effect on mean precipitation. Moreover, the scaling exponent is mainly driven by topography alone (with increasing values of this parameter at increasing elevations). Therefore, the quantiles of H(D,F) at durations greater than unit turn to be more variable at high elevations than at low elevations. Additionally, the analysis of the variability of the shape parameter with elevation shows that extreme events at high elevations appear to be distributed according to an upper bounded probability distribution. These evidences could be a characteristic sign of the formation of extreme precipitation events at high elevations.

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

Extreme coastal erosion enhanced by anomalous extratropical storm wave direction.

PubMed

Harley, Mitchell D; Turner, Ian L; Kinsela, Michael A; Middleton, Jason H; Mumford, Peter J; Splinter, Kristen D; Phillips, Matthew S; Simmons, Joshua A; Hanslow, David J; Short, Andrew D

2017-07-20

Extratropical cyclones (ETCs) are the primary driver of large-scale episodic beach erosion along coastlines in temperate regions. However, key drivers of the magnitude and regional variability in rapid morphological changes caused by ETCs at the coast remain poorly understood. Here we analyze an unprecedented dataset of high-resolution regional-scale morphological response to an ETC that impacted southeast Australia, and evaluate the new observations within the context of an existing long-term coastal monitoring program. This ETC was characterized by moderate intensity (for this regional setting) deepwater wave heights, but an anomalous wave direction approximately 45 degrees more counter-clockwise than average. The magnitude of measured beach volume change was the largest in four decades at the long-term monitoring site and, at the regional scale, commensurate with that observed due to extreme North Atlantic hurricanes. Spatial variability in morphological response across the study region was predominantly controlled by alongshore gradients in storm wave energy flux and local coastline alignment relative to storm wave direction. We attribute the severity of coastal erosion observed due to this ETC primarily to its anomalous wave direction, and call for greater research on the impacts of changing storm wave directionality in addition to projected future changes in wave heights.

A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). Formore » all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.« less

Role of Winter Weather Conditions and Slipperiness on Tourists' Accidents in Finland.

PubMed

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-08-15

(1) BACKGROUND: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists' health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) METHODS: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) RESULTS: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) CONCLUSIONS: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change.

Groundwater flood of a river terrace in southwest Wisconsin, USA

NASA Astrophysics Data System (ADS)

Gotkowitz, Madeline B.; Attig, John W.; McDermott, Thomas

2014-09-01

Intense rainstorms in 2008 resulted in wide-spread flooding across the Midwestern United States. In Wisconsin, floodwater inundated a 17.7-km2 area on an outwash terrace, 7.5 m above the mapped floodplain of the Wisconsin River. Surface-water runoff initiated the flooding, but results of field investigation and modeling indicate that rapid water-table rise and groundwater inundation caused the long-lasting flood far from the riparian floodplain. Local geologic and geomorphic features of the landscape lead to spatial variability in runoff and recharge to the unconfined sand and gravel aquifer, and regional hydrogeologic conditions increased groundwater discharge from the deep bedrock aquifer to the river valley. Although reports of extreme cases of groundwater flooding are uncommon, this occurrence had significant economic and social costs. Local, state and federal officials required hydrologic analysis to support emergency management and long-term flood mitigation strategies. Rapid, sustained water-table rise and the resultant flooding of this high-permeability aquifer illustrate a significant aspect of groundwater system response to an extreme precipitation event. Comprehensive land-use planning should encompass the potential for water-table rise and groundwater flooding in a variety of hydrogeologic settings, as future changes in climate may impact recharge and the water-table elevation.

Role of Winter Weather Conditions and Slipperiness on Tourists’ Accidents in Finland

PubMed Central

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-01-01

(1) Background: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists’ health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) Methods: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) Results: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) Conclusions: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change. PMID:27537899

Microhabitats in the tropics buffer temperature in a globally coherent manner.

PubMed

Scheffers, Brett R; Evans, Theodore A; Williams, Stephen E; Edwards, David P

2014-12-01

Vegetated habitats contain a variety of fine-scale features that can ameliorate temperate extremes. These buffered microhabitats may be used by species to evade extreme weather and novel climates in the future. Yet, the magnitude and extent of this buffering on a global scale remains unknown. Across all tropical continents and using 36 published studies, we assessed temperature buffering from within microhabitats across various habitat strata and structures (e.g. soil, logs, epiphytes and tree holes) and compared them to non-buffered macro-scale ambient temperatures (the thermal control). Microhabitats buffered temperature by 3.9 °C and reduced maximum temperatures by 3.5 °C. Buffering was most pronounced in tropical lowlands where temperatures were most variable. With the expected increase in extreme weather events, microhabitats should provide species with a local layer of protection that is not captured by traditional climate assessments, which are typically derived from macro-scale temperatures (e.g. satellites). Our data illustrate the need for a next generation of predictive models that account for species' ability to move within microhabitats to exploit favourable buffered microclimates. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Reduced CO2 fertilization effect in temperate C3 grasslands under more extreme weather conditions

NASA Astrophysics Data System (ADS)

Obermeier, W. A.; Lehnert, L. W.; Kammann, C. I.; Müller, C.; Grünhage, L.; Luterbacher, J.; Erbs, M.; Moser, G.; Seibert, R.; Yuan, N.; Bendix, J.

2017-02-01

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of recent global climate change. The stimulation of plant photosynthesis due to rising atmospheric carbon dioxide concentrations ([CO2]) is widely assumed to increase the net primary productivity (NPP) of C3 plants--the CO2 fertilization effect (CFE). However, the magnitude and persistence of the CFE under future climates, including more frequent weather extremes, are controversial. Here we use data from 16 years of temperate grassland grown under `free-air carbon dioxide enrichment’ conditions to show that the CFE on above-ground biomass is strongest under local average environmental conditions. The observed CFE was reduced or disappeared under wetter, drier and/or hotter conditions when the forcing variable exceeded its intermediate regime. This is in contrast to predictions of an increased CO2 fertilization effect under drier and warmer conditions. Such extreme weather conditions are projected to occur more intensely and frequently under future climate scenarios. Consequently, current biogeochemical models might overestimate the future NPP sink capacity of temperate C3 grasslands and hence underestimate future atmospheric [CO2] increase.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

Providing the Larger Climate Context During Extreme Weather - Lessons from Local Television News

NASA Astrophysics Data System (ADS)

Woods, M.; Cullen, H. M.

2015-12-01

Local television weathercasters, in their role as Station Scientists, are often called upon to educate viewers about the science and impacts of climate change. Climate Central supports these efforts through its Climate Matters program. Launched in 2010 with support from the National Science Foundation, the program has grown into a network that includes more than 245 weathercasters from across the country and provides localized information on climate and ready-to-use, broadcast quality graphics and analyses in both English and Spanish. This presentation will focus on discussing best practices for integrating climate science into the local weather forecast as well as advances in the science of extreme event attribution. The Chief Meteorologist at News10 (Sacramento, CA) will discuss local news coverage of the ongoing California drought, extreme weather and climate literacy.

Trends in the components of extreme water levels signal a rotation of winds in strong storms in the eastern Baltic Sea

NASA Astrophysics Data System (ADS)

Pindsoo, Katri; Soomere, Tarmo

2016-04-01

The water level time series and particularly temporal variations in water level extremes usually do not follow any simple rule. Still, the analysis of linear trends in extreme values of surge levels is a convenient tool to obtain a first approximation of the future projections of the risks associated with coastal floodings. We demonstrate how this tool can be used to extract essential information about concealed changes in the forcing factors of seas and oceans. A specific feature of the Baltic Sea is that sequences of even moderate storms may raise the average sea level by almost 1 m for a few weeks. Such events occur once in a few years. They substantially contribute to the extreme water levels in the eastern Baltic Sea: the most devastating coastal floodings occur when a strong storm from unfortunate direction arrives during such an event. We focus on the separation of subtidal (weekly-scale) processes from those which are caused by a single storm and on establishing how much these two kinds of events have contributed to the increase in the extreme water levels in the eastern Baltic Sea. The analysis relies on numerically reconstructed sea levels produced by the RCO (Rossby Center, Swedish Meteorological and Hydrological Institute) ocean model for 1961-2005. The reaction of sea surface to single storm events is isolated from the local water level time series using a running average over a fixed interval. The distribution of average water levels has an almost Gaussian shape for averaging lengths from a few days to a few months. The residual (total water level minus the average) can be interpreted as a proxy of the local storm surges. Interestingly, for the 8-day average this residual almost exactly follows the exponential distribution. Therefore, for this averaging length the heights of local storm surges reflect an underlying Poisson process. This feature is universal for the entire eastern Baltic Sea coast. The slopes of the exponential distribution for low and high water levels are different, vary markedly along the coast and provide a useful quantification of the vulnerability of single coastal segments with respect to coastal flooding. The formal linear trends in the extreme values of these water level components exhibit radically different spatial variations. The slopes of the trends in the weekly average are almost constant (~4 cm/decade for 8-day running average) along the entire eastern Baltic Sea coast. This first of all indicates that the duration of storm sequences has increased. The trends for maxima of local storm surge heights represent almost the entire spatial variability in the water level extremes. Their slopes are almost zero at the open Baltic Proper coasts of the Western Estonian archipelago. Therefore, an increase in wind speed in strong storms is unlikely in this area. In contrast, the slopes in question reach 5-7 cm/decade in the eastern Gulf of Finland and Gulf of Riga. This feature suggests that wind direction in strongest storms may have rotated in the northern Baltic Sea.

Influence of site on the therapeutic ratio of adjuvant radiotherapy in soft-tissue sarcoma of the extremity.

PubMed

Alektiar, Kaled M; Brennan, Murray F; Singer, Samuel

2005-09-01

The ultimate goal of adjuvant radiotherapy (RT) in soft-tissue sarcoma of the extremity is to improve the therapeutic ratio by increasing local control while minimizing morbidity. Most efforts in trying to improve this ratio have focused on the sequencing of RT and surgery, with little attention to the potential influence of the tumor site. The purpose of this study was to determine the influence of tumor site on local control and complications in a group of patients with primary high-grade soft-tissue sarcoma of the extremity treated at a single institution with postoperative RT. Between July 1982 and December 2000, 369 adult patients with primary high-grade soft-tissue sarcoma of the extremity were treated with limb-sparing surgery and postoperative RT. Patients who underwent surgery or RT outside our institution were excluded. The tumor site was the upper extremity (UE) in 103 (28%) and the lower extremity (LE) in 266 (72%). The tumor was < or = 5 cm in 98 patients (27%), and the microscopic margins were positive in 44 (12%). Of the 369 patients, 104 (28%) underwent postoperative external beam RT (EBRT), 233 (63%) postoperative brachytherapy (BRT), and 32 underwent a combination (9%); 325 (88%) received a "conventional" radiation dose, defined as 60-70 Gy for EBRT, 45 Gy for BRT, and 45-50 Gy plus 15-20 Gy for EBRT plus BRT. Complications were assessed in terms of wound complications requiring repeat surgery, fracture, joint stiffness, edema, and Grade 3 or worse peripheral nerve damage. The UE and LE groups were balanced with regard to age, depth, margin status, and type of RT (EBRT vs. BRT +/- EBRT). However, more patients in the UE group had tumors < or = 5 cm and more received a conventional radiation dose (p = 0.01 and P = 0.03, respectively). With a median follow-up of 50 months, the 5-year actuarial rate of local control, distant relapse-free survival, and overall survival for the whole population was 82% (95% confidence interval [CI], 77-86%), 61% (95% CI, 56-66%), and 71% (95% CI, 66-76%), respectively. The 5-year local control rate in patients with UE STS was 70% (95% CI, 60-80%) compared with 86% (95% CI, 81-91%) for LE STS (p = 0.0004). On multivariate analysis, an UE site (p = 0.001; relative risk [RR], 3; 95% CI, 2-5) and positive resection margins (p = 0.02; RR, 2; 95% CI, 1-4) were significant predictors of poor local control. The RT type or radiation dose, age, tumor depth, and size were not significant predictors of local control. The 5-year wound reoperation rate was 1% (95% CI, 0-3) in the UE compared with 11% (95% CI, 7-15) in the LE (p = 0.002). On multivariate analysis, the UE site retained its significance as a predictor of low wound complications (p = 0.001; RR, 0.08; 95% CI, 0.01-0.7). The site did not significantly influence the incidence of fracture (p = 0.7), joint stiffness (p = 0.2), edema (p = 0.5), or Grade 3 or worse peripheral nerve damage (p = 0.3). The UE site is associated with a greater rate of local recurrence compared with the LE. This difference was independent of other variables and could not be accounted for by an imbalance between the two groups. With a lower wound complication rate associated with an UE site, it would be of interest to determine whether preoperative RT and/or intensity-modulated RT can increase the local control in UE sarcomas, thus improving the therapeutic ratio.

A Multifactorial Analysis of Melanoma: Prognostic Histopathological Features Comparing Clark's and Breslow's Staging Methods

PubMed Central

Balch, Charles M.; Murad, Tariq M.; Soong, Seng-Jaw; Ingalls, Anna Lee; Halpern, Norman B.; Maddox, William A.

1978-01-01

A multifactorial analysis was used to identify the dominant prognostic variables affecting survival from a computerized data base of 339 melanoma patients treated at this institution during the past 17 years. Five of the 13 parameters examined simultaneously were found to independently influence five year survival rates: 1) pathological stage (I vs II, p = 0.0014), 2) lesion ulceration (present vs absent, p = 0.006), 3) surgical treatment (wide excision vs wide excision plus lymphadenectomy, p = 0.024), 4) melanoma thickness (p = 0.032), and 5) location (upper extremity vs lower extremity vs trunk vs head and neck, p = 0.038). Additional factors considered that had either indirect or no influence on survival rates were clinical stage of disease, age, sex, level of invasion, pigmentation, lymphocyte infiltration, growth pattern, and regression. Most of these latter variables derived their prognostic value from correlation with melanoma thickness, except sex which correlated with location (extremity lesions were more frequent on females, trunk lesions on males). This statistical analysis enabled us to derive a mathematical equation for predicting an individual patient's probability of five year survival. Three categories of risk were delineated by measuring tumor thickness (Breslow microstaging) in Stage I patients: 1) thin melanomas (<0.76 mm) were associated with localized disease and a 100% cure rate: 2) intermediate thickness melanomas (0.76-4.00 mm) had an increasing risk (up to 80%) of harboring regional and/or distant metastases and 3) thick melanomas (≥4.00 mm) had a 80% risk of occult distant metastases at the time of initial presentation. The level of invasion (Clark's microstaging) correlated with survival, but was less predictive than measuring tumor thickness. Within each of Clark's Level II, III and IV groups, there were gradations of thickness with statistically different survival rates. Both microstaging methods (Breslow and Clark) were less predictive factors in patients with lymph node or distant metastases. Clinical trials evaluating alternative surgical treatments or adjunctive therapy modalities for melanoma patients should incorporate these parameters into their assessment, especially in Stage I (localized) disease where tumor thickness and the anatomical site of the primary melanoma are dominant prognostic factors. PMID:736651

Regional changes in extreme monsoon rainfall deficit and excess in India

NASA Astrophysics Data System (ADS)

Pal, Indrani; Al-Tabbaa, Abir

2010-04-01

With increasing concerns about climate change, the need to understand the nature and variability of monsoon climatic conditions and to evaluate possible future changes becomes increasingly important. This paper deals with the changes in frequency and magnitudes of extreme monsoon rainfall deficiency and excess in India from 1871 to 2005. Five regions across India comprising variable climates were selected for the study. Apart from changes in individual regions, changing tendencies in extreme monsoon rainfall deficit and excess were also determined for the Indian region as a whole. The trends and their significance were assessed using non-parametric Mann-Kendall technique. The results show that intra-region variability for extreme monsoon seasonal precipitation is large and mostly exhibited a negative tendency leading to increasing frequency and magnitude of monsoon rainfall deficit and decreasing frequency and magnitude of monsoon rainfall excess.

Climate change and water availability for vulnerable agriculture

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Tarquis, Ana Maria

2017-04-01

Climatic projections for the Mediterranean basin indicate that the area will suffer a decrease in water resources due to climate change. The key climatic trends identified for the Mediterranean region are continuous temperature increase, further drying with precipitation decrease and the accentuation of climate extremes, such as droughts, heat waves and/or forest fires, which are expected to have a profound effect on agriculture. Indeed, the impact of climate variability on agricultural production is important at local, regional, national, as well as global scales. Agriculture of any kind is strongly influenced by the availability of water. Climate change will modify rainfall, evaporation, runoff, and soil moisture storage patterns. Changes in total seasonal precipitation or in its pattern of variability are both important. Similarly, with higher temperatures, the water-holding capacity of the atmosphere and evaporation into the atmosphere increase, and this favors increased climate variability, with more intense precipitation and more droughts. As a result, crop yields are affected by variations in climatic factors, such as air temperature and precipitation, and the frequency and severity of the above mentioned extreme events. The aim of this work is to briefly present the main effects of climate change and variability on water resources with respect to water availability for vulnerable agriculture, namely in the Mediterranean region. Results of undertaken studies in Greece on precipitation patterns and drought assessment using historical data records are presented. Based on precipitation frequency analysis, evidence of precipitation reductions is shown. Drought is assessed through an agricultural drought index, namely the Vegetation Health Index (VHI), in Thessaly, a drought-prone region in central Greece. The results justify the importance of water availability for vulnerable agriculture and the need for drought monitoring in the Mediterranean basin as part of an integrated climate adaptation strategy.

Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society

PubMed Central

Taylor, P. H.; Gibson, R.

2016-01-01

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958–2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different. PMID:27713662

Using Multiple Metrics to Analyze Trends and Sensitivity of Climate Variability in New York City

NASA Astrophysics Data System (ADS)

Huang, J.; Towey, K.; Booth, J. F.; Baez, S. D.

2017-12-01

As the overall temperature of Earth continues to warm, changes in the Earth's climate are being observed through extreme weather events, such as heavy precipitation events and heat waves. This study examines the daily precipitation and temperature record of the greater New York City region during the 1979-2014 period. Daily station observations from three greater New York City airports: John F. Kennedy (JFK), LaGuardia (LGA) and Newark (EWR), are used in this study. Multiple statistical metrics are used in this study to analyze trends and variability in temperature and precipitation in the greater New York City region. The temperature climatology reveals a distinct seasonal cycle, while the precipitation climatology exhibits greater annual variability. Two types of thresholds are used to examine the variability of extreme events: extreme threshold and daily anomaly threshold. The extreme threshold indicates how the strength of the overall maximum is changing whereas the daily anomaly threshold indicates if the strength of the daily maximum is changing over time. We observed an increase in the frequency of anomalous daily precipitation events over the last 36 years, with the greatest frequency occurring in 2011. The most extreme precipitation events occur during the months of late summer through early fall, with approximately four expected extreme events occurring per year during the summer and fall. For temperature, the greatest frequency and variation in temperature anomalies occur during winter and spring. In addition, temperature variance is also analyzed to determine if there is greater day-to-day temperature variability today than in the past.

Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

NASA Astrophysics Data System (ADS)

Silva, A. C. S.; Galvão, C. O.; Silva, G. N. S.

2015-06-01

Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom's framework for analyzing social-ecological systems (SES) was applied. Ostrom's framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997-2000, when Brazil's new water policy was very young, and the other one in 2012-2015. The analysis of SES considering Ostrom's principle "Clearly defined boundaries" showed that deficiencies in water management cause the intensification of drought's impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.

Hydroclimate variability in the Nile River Basin during the past 28,000 years

NASA Astrophysics Data System (ADS)

Castañeda, Isla S.; Schouten, Stefan; Pätzold, Jürgen; Lucassen, Friedrich; Kasemann, Simone; Kuhlmann, Holger; Schefuß, Enno

2016-03-01

It has long been known that extreme changes in North African hydroclimate occurred during the late Pleistocene yet many discrepancies exist between sites regarding the timing, duration and abruptness of events such as Heinrich Stadial (HS) 1 and the African Humid Period (AHP). The hydroclimate history of the Nile River is of particular interest due to its lengthy human occupation history yet there are presently few continuous archives from the Nile River corridor, and pre-Holocene studies are rare. Here we present new organic and inorganic geochemical records of Nile Basin hydroclimate from an eastern Mediterranean (EM) Sea sediment core spanning the past 28 ka BP. Our multi-proxy records reflect the fluctuating inputs of Blue Nile versus White Nile material to the EM Sea in response to gradual changes in local insolation and also capture abrupt hydroclimate events driven by remote climate forcings, such as HS1. We find strong evidence for extreme aridity within the Nile Basin evolving in two distinct phases during HS1, from 17.5 to 16 ka BP and from 16 to 14.5 ka BP, whereas peak wet conditions during the AHP are observed from 9 to 7 ka BP. We find that zonal movements of the Congo Air Boundary (CAB), and associated shifts in the dominant moisture source (Atlantic versus Indian Ocean moisture) to the Nile Basin, likely contributed to abrupt hydroclimate variability in northern East Africa during HS1 and the AHP as well as to non-linear behavior of hydroclimate proxies. We note that different proxies show variable gradual and abrupt responses to individual hydroclimate events, and thus might have different inherent sensitivities, which may be a factor contributing to the controversy surrounding the abruptness of past events such as the AHP. During the Late Pleistocene the Nile Basin experienced extreme hydroclimate fluctuations, which presumably impacted Paleolithic cultures residing along the Nile corridor.

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

Trends and variability of daily precipitation extremes during 1960-2012 in the Yangtze River Basin, China

USDA-ARS?s Scientific Manuscript database

Trends and variability of extreme precipitation events are important for water-related disaster prevention and mitigation as well as water resource management. Based on daily precipitation dataset from 143 meteorological stations in the Yangtze River Basin (YRB), a suite of precipitation indices rec...

Spatial variability in the trends in extreme storm surges and weekly-scale high water levels in the eastern Baltic Sea

NASA Astrophysics Data System (ADS)

Soomere, Tarmo; Pindsoo, Katri

2016-03-01

We address the possibilities of a separation of the overall increasing trend in maximum water levels of semi-enclosed water bodies into associated trends in the heights of local storm surges and basin-scale components of the water level based on recorded and modelled local water level time series. The test area is the Baltic Sea. Sequences of strong storms may substantially increase its water volume and raise the average sea level by almost 1 m for a few weeks. Such events are singled out from the water level time series using a weekly-scale average. The trends in the annual maxima of the weekly average have an almost constant value along the entire eastern Baltic Sea coast for averaging intervals longer than 4 days. Their slopes are ~4 cm/decade for 8-day running average and decrease with an increase of the averaging interval. The trends for maxima of local storm surge heights represent almost the entire spatial variability in the water level maxima. Their slopes vary from almost zero for the open Baltic Proper coast up to 5-7 cm/decade in the eastern Gulf of Finland and Gulf of Riga. This pattern suggests that an increase in wind speed in strong storms is unlikely in this area but storm duration may have increased and wind direction may have rotated.

The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.

Investigating synoptic-scale monsoonal disturbances in an idealized moist model

NASA Astrophysics Data System (ADS)

Clark, S.; Ming, Y.

2017-12-01

Recent studies have highlighted the potential utility of a theory for a "moisture-dynamical" instability in explaining the time and spatial scales of intra-seasonal variability associated with the Indian summer monsoon. These studies suggest that a localized region in the subtropics with mean low-level westerly winds and mean temperature increasing poleward will allow the formation of westward propagating precipitation anomalies associated with moist Rossby-like waves. Here we test this theory in an idealized moist model with realistic radiative transfer by inducing a local poleward-increasing temperature gradient by placing a continent with simplified hydrology in the subtropics. We experiment with different treatments of land-surface hydrology, ranging from the extreme (treating land as having the same heat capacity as the slab ocean used in the model, and turning off evaporation completely over land) to the more realistic (bucket hydrology, with a decreased heat capacity over land), and different continental shapes, ranging from a zonally-symmetric continent, to Earth-like continental geometry. Precipitation rates produced by the simulations are analyzed using space-time spectral analysis, and connected to variability in the winds through regression analysis. The observed behavior is discussed with respect to predictions from the theory.

Satellite-Enhanced Dynamical Downscaling of Extreme Events

NASA Astrophysics Data System (ADS)

Nunes, A.

2015-12-01

Severe weather events can be the triggers of environmental disasters in regions particularly susceptible to changes in hydrometeorological conditions. In that regard, the reconstruction of past extreme weather events can help in the assessment of vulnerability and risk mitigation actions. Using novel modeling approaches, dynamical downscaling of long-term integrations from global circulation models can be useful for risk analysis, providing more accurate climate information at regional scales. Originally developed at the National Centers for Environmental Prediction (NCEP), the Regional Spectral Model (RSM) is being used in the dynamical downscaling of global reanalysis, within the South American Hydroclimate Reconstruction Project. Here, RSM combines scale-selective bias correction with assimilation of satellite-based precipitation estimates to downscale extreme weather occurrences. Scale-selective bias correction is a method employed in the downscaling, similar to the spectral nudging technique, in which the downscaled solution develops in agreement with its coarse boundaries. Precipitation assimilation acts on modeled deep-convection, drives the land-surface variables, and therefore the hydrological cycle. During the downscaling of extreme events that took place in Brazil in recent years, RSM continuously assimilated NCEP Climate Prediction Center morphing technique precipitation rates. As a result, RSM performed better than its global (reanalysis) forcing, showing more consistent hydrometeorological fields compared with more sophisticated global reanalyses. Ultimately, RSM analyses might provide better-quality initial conditions for high-resolution numerical predictions in metropolitan areas, leading to more reliable short-term forecasting of severe local storms.

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

USGS Publications Warehouse

Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Magneto-transport properties of a random distribution of few-layer graphene patches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iacovella, Fabrice; Mitioglu, Anatolie; Pierre, Mathieu

In this study, we address the electronic properties of conducting films constituted of an array of randomly distributed few layer graphene patches and investigate on their most salient galvanometric features in the moderate and extreme disordered limit. We demonstrate that, in annealed devices, the ambipolar behaviour and the onset of Landau level quantization in high magnetic field constitute robust hallmarks of few-layer graphene films. In the strong disorder limit, however, the magneto-transport properties are best described by a variable-range hopping behaviour. A large negative magneto-conductance is observed at the charge neutrality point, in consistency with localized transport regime.

The environmental context for the origins of modern human diversity: a synthesis of regional variability in African climate 150,000-30,000 years ago.

PubMed

Blome, Margaret Whiting; Cohen, Andrew S; Tryon, Christian A; Brooks, Alison S; Russell, Joellen

2012-05-01

We synthesize African paleoclimate from 150 to 30 ka (thousand years ago) using 85 diverse datasets at a regional scale, testing for coherence with North Atlantic glacial/interglacial phases and northern and southern hemisphere insolation cycles. Two major determinants of circum-African climate variability over this time period are supported by principal components analysis: North Atlantic sea surface temperature (SST) variations and local insolation maxima. North Atlantic SSTs correlated with the variability found in most circum-African SST records, whereas the variability of the majority of terrestrial temperature and precipitation records is explained by local insolation maxima, particularly at times when solar radiation was intense and highly variable (e.g., 150-75 ka). We demonstrate that climates varied with latitude, such that periods of relatively increased aridity or humidity were asynchronous across the northern, eastern, tropical and southern portions of Africa. Comparisons of the archaeological, fossil, or genetic records with generalized patterns of environmental change based solely on northern hemisphere glacial/interglacial cycles are therefore imprecise. We compare our refined climatic framework to a database of 64 radiometrically-dated paleoanthropological sites to test hypotheses of demographic response to climatic change among African hominin populations during the 150-30 ka interval. We argue that at a continental scale, population and climate changes were asynchronous and likely occurred under different regimes of climate forcing, creating alternating opportunities for migration into adjacent regions. Our results suggest little relation between large scale demographic and climate change in southern Africa during this time span, but strongly support the hypothesis of hominin occupation of the Sahara during discrete humid intervals ~135-115 ka and 105-75 ka. Hominin populations in equatorial and eastern Africa may have been buffered from the extremes of climate change by locally steep altitudinal and rainfall gradients and the complex and variable effects of increased aridity on human habitat suitability in the tropics. Our data are consistent with hominin migrations out of Africa through varying exit points from ~140-80 ka. Copyright © 2012 Elsevier Ltd. All rights reserved.

A maximally stable extremal region based scene text localization method

NASA Astrophysics Data System (ADS)

Xiao, Chengqiu; Ji, Lixin; Gao, Chao; Li, Shaomei

2015-07-01

Text localization in natural scene images is an important prerequisite for many content-based image analysis tasks. This paper proposes a novel text localization algorithm. Firstly, a fast pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSER) as basic character candidates. Secondly, these candidates are filtered by using the properties of fitting ellipse and the distribution properties of characters to exclude most non-characters. Finally, a new extremal regions projection merging algorithm is designed to group character candidates into words. Experimental results show that the proposed method has an advantage in speed and achieve relatively high precision and recall rates than the latest published algorithms.

Global Floods and Water Availability Driven by Atmospheric Rivers

NASA Astrophysics Data System (ADS)

Paltan, Homero; Waliser, Duane; Lim, Wee Ho; Guan, Bin; Yamazaki, Dai; Pant, Raghav; Dadson, Simon

2017-10-01

While emerging regional evidence shows that atmospheric rivers (ARs) can exert strong impacts on local water availability and flooding, their role in shaping global hydrological extremes has not yet been investigated. Here we quantify the relative contribution of ARs variability to both flood hazard and water availability. We find that globally, precipitation from ARs contributes 22% of total global runoff, with a number of regions reaching 50% or more. In areas where their influence is strongest, ARs may increase the occurrence of floods by 80%, while absence of ARs may increase the occurrence of hydrological droughts events by up to 90%. We also find that 300 million people are exposed to additional floods and droughts due the occurrence of ARs. ARs provide a source of hydroclimatic variability whose beneficial or damaging effects depend on the capacity of water resources managers to predict and adapt to them.

Evaluation of the sensitivity of the Amazonian diurnal cycle to convective intensity in reanalyses

NASA Astrophysics Data System (ADS)

Itterly, Kyle F.; Taylor, Patrick C.

2017-02-01

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics—specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Evaluation of the Sensitivity of the Amazonian Diurnal Cycle to Convective Intensity in Reanalyses

NASA Technical Reports Server (NTRS)

Itterly, Kyle F.; Taylor, Patrick C.

2016-01-01

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics-specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Duplex sonography for detection of deep vein thrombosis of upper extremities: a 13-year experience.

PubMed

Chung, Amy S Y; Luk, W H; Lo, Adrian X N; Lo, C F

2015-04-01

To determine the prevalence and characteristics of sonographically evident upper-extremity deep vein thrombosis in symptomatic Chinese patients and identify its associated risk factors. Regional hospital, Hong Kong. Data on patients undergoing upper-extremity venous sonography examinations during a 13-year period from November 1999 to October 2012 were retrieved. Variables including age, sex, history of smoking, history of lower-extremity deep vein thrombosis, major surgery within 30 days, immobilisation within 30 days, cancer (history of malignancy), associated central venous or indwelling catheter, hypertension, diabetes mellitus, sepsis within 30 days, and stroke within 30 days were tested using binary logistic regression to understand the risk factors for upper-extremity deep vein thrombosis. The presence of upper-extremity deep vein thrombosis identified. Overall, 213 patients with upper-extremity sonography were identified. Of these patients, 29 (13.6%) had upper-extremity deep vein thrombosis. The proportion of upper-extremity deep vein thrombosis using initial ultrasound was 0.26% of all deep vein thrombosis ultrasound requests. Upper limb swelling was the most common presentation seen in a total of 206 (96.7%) patients. Smoking (37.9%), history of cancer (65.5%), and hypertension (27.6%) were the more prevalent conditions among patients in the upper-extremity deep vein thrombosis-positive group. No statistically significant predictor of upper-extremity deep vein thrombosis was noted if all variables were included. After backward stepwise logistic regression, the final model was left with only age (P=0.119), female gender (P=0.114), and history of malignancy (P=0.024) as independent variables. History of malignancy remained predictive of upper-extremity deep vein thrombosis. Upper-extremity deep vein thrombosis is uncommon among symptomatic Chinese population. The most common sign is swelling and the major risk factor for upper-extremity deep vein thrombosis identified in this study is malignancy.

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

2013-12-01

NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to provision of information that will help guide long-term preparedness for severe weather events and extreme conditions as well as climate variability and change GFCS recently summarized examples of existing initiatives to advance provision of climate services in the 2012 publication Climate ExChange. In this publication, NWS introduced the new Local Climate Analysis Tool (LCAT), a tool that is used to conduct local climate studies that are needed to create efficient and reliable guidance for DSS. LCAT allows for analyzing trends in local climate variables and identifying local impacts of climate variability (e.g., ENSO) on weather and water conditions. In addition to LCAT, NWS, working in partnership with the North East Regional Climate center, released xmACIS version 2, a climate data mining tool, for NWS field operations. During this talk we will demonstrate LCAT and xmACIS as well as outline several examples of their application to DSS and its potential use for achieving GFCS goals. The examples include LCAT-based temperature analysis for energy decisions, guidance on weather and water events leading to increased algal blooms and red tide months in advance, local climate sensitivities to droughts, probabilities of hot/cold conditions and their potential impacts on agriculture and fish kills or fish stress.

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

NASA Astrophysics Data System (ADS)

Adesso, Gerardo; Giampaolo, Salvatore M.; Illuminati, Fabrizio

2007-10-01

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1×M bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself and the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a , uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes.

Bayes plus Brass: Estimating Total Fertility for Many Small Areas from Sparse Census Data

PubMed Central

Schmertmann, Carl P.; Cavenaghi, Suzana M.; Assunção, Renato M.; Potter, Joseph E.

2013-01-01

Small-area fertility estimates are valuable for analysing demographic change, and important for local planning and population projection. In countries lacking complete vital registration, however, small-area estimates are possible only from sparse survey or census data that are potentially unreliable. Such estimation requires new methods for old problems: procedures must be automated if thousands of estimates are required, they must deal with extreme sampling variability in many areas, and they should also incorporate corrections for possible data errors. We present a two-step algorithm for estimating total fertility in such circumstances, and we illustrate by applying the method to 2000 Brazilian Census data for over five thousand municipalities. Our proposed algorithm first smoothes local age-specific rates using Empirical Bayes methods, and then applies a new variant of Brass’s P/F parity correction procedure that is robust under conditions of rapid fertility decline. PMID:24143946

Continuous relative phase variability during an exhaustive run in runners with a history of iliotibial band syndrome.

PubMed

Miller, Ross H; Meardon, Stacey A; Derrick, Timothy R; Gillette, Jason C

2008-08-01

Previous research has proposed that a lack of variability in lower extremity coupling during running is associated with pathology. The purpose of the study was to evaluate lower extremity coupling variability in runners with and without a history of iliotibial band syndrome (ITBS) during an exhaustive run. Sixteen runners ran to voluntary exhaustion on a motorized treadmill while a motion capture system recorded reflective marker locations. Eight runners had a history of ITBS. At the start and end of the run, continuous relative phase (CRP) angles and CRP variability between strides were calculated for key lower extremity kinematic couplings. The ITBS runners demonstrated less CRP variability than controls in several couplings between segments that have been associated with knee pain and ITBS symptoms, including tibia rotation-rearfoot motion and rearfoot motion-thigh ad/abduction, but more variability in knee flexion/extension-foot ad/abduction. The ITBS runners also demonstrated low variability at heel strike in coupling between rearfoot motion-tibia rotation. The results suggest that runners prone to ITBS use abnormal segmental coordination patterns, particular in couplings involving thigh ad/abduction and tibia internal/external rotation. Implications for variability in injury etiology are suggested.

Shifting patterns of mild weather in response to projected radiative forcing

NASA Astrophysics Data System (ADS)

van der Wiel, Karin; Kapnick, Sarah; Vecchi, Gabriel

2017-04-01

Traditionally, climate change research has focused on changes in mean climate (e.g. global mean temperature, sea level rise, glacier melt) or change in extreme events (e.g. hurricanes, extreme precipitation, droughts, heat waves, wild fires). Though extreme events have the potential to disrupt society, extreme conditions are rare by definition. In contrast, mild weather occurs frequently and many human activities are built around it. Examples of such activities include football games, dog walks, bike rides, and outdoor weddings, but also activities of direct economic impact, e.g. construction work, infrastructure projects, road or rail transportation, air travel, and landscaping projects. Absence of mild weather impacts society in various way, understanding current and future mild weather is therefore of high scientific interest. We present a global analysis of mild weather based on simple and relatable criteria and we explore changes in mild weather occurrence in response to radiative forcing. A high-resolution global climate model, GFDL HiFLOR, is used to allow for investigation of local features and changes. In response to RCP4.5, we find a slight global mean decrease in the annual number of mild days projected both in the near future (-4 d/yr, 2016-2035) and at the end of this century (-10 d/yr, 2081-2100). Projected regional and seasonal redistributions of mild days are substantially greater. Tropical regions are projected to see large decreases, in the mid-latitudes small increases in the number of mild days are projected. Mediterranean climates are projected to see a shift of mild weather away from the local summer to the shoulder seasons. These changes are larger than the interannual variability of mild weather caused by El Niño-Southern Oscillation. Finally, we use reanalysis data to show an observed global decrease in the recent past, and we verify that these observed regional changes in mild weather resemble the projections.

Extreme value analysis of the time derivative of the horizontal magnetic field and computed electric field

NASA Astrophysics Data System (ADS)

Wintoft, Peter; Viljanen, Ari; Wik, Magnus

2016-05-01

High-frequency ( ≈ minutes) variability of ground magnetic fields is caused by ionospheric and magnetospheric processes driven by the changing solar wind. The varying magnetic fields induce electrical fields that cause currents to flow in man-made conductors like power grids and pipelines. Under extreme conditions the geomagnetically induced currents (GIC) may be harmful to the power grids. Increasing our understanding of the extreme events is thus important for solar-terrestrial science and space weather. In this work 1-min resolution of the time derivative of measured local magnetic fields (|dBh/dt|) and computed electrical fields (Eh), for locations in Europe, have been analysed with extreme value analysis (EVA). The EVA results in an estimate of the generalized extreme value probability distribution that is described by three parameters: location, width, and shape. The shape parameter controls the extreme behaviour. The stations cover geomagnetic latitudes from 40 to 70° N. All stations included in the study have contiguous coverage of 18 years or more with 1-min resolution data. As expected, the EVA shows that the higher latitude stations have higher probability of large |dBh/dt| and |Eh| compared to stations further south. However, the EVA also shows that the shape of the distribution changes with magnetic latitude. The high latitudes have distributions that fall off faster to zero than the low latitudes, and upward bounded distributions can not be ruled out. The transition occurs around 59-61° N magnetic latitudes. Thus, the EVA shows that the observed series north of ≈ 60° N have already measured values that are close to the expected maxima values, while stations south of ≈ ° N will measure larger values in the future.

Trends and variability of daily temperature extremes during 1960-2012 in the Yangtze River Basin, China

USDA-ARS?s Scientific Manuscript database

The variability of temperature extremes has been the focus of attention during the past few decades, and may exert a great influence on the global hydrologic cycle and energy balance through thermal forcing. Based on daily minimum and maximum temperature observed by the China Meteorological Administ...

Validation of China-wide interpolated daily climate variables from 1960 to 2011

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

2015-02-01

Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based on the performance of these variables in estimating daily variations, interannual variability, and extreme events. Although longitude, latitude, and elevation data are included in the model, additional information, such as topography and cloud cover, should be integrated into the interpolation algorithm to improve performance in estimating wind speed, atmospheric pressure, and precipitation.

Extreme events, trends, and variability in Northern Hemisphere lake-ice phenology (1855-2005)

USGS Publications Warehouse

Benson, Barbara J.; Magnuson, John J.; Jensen, Olaf P.; Card, Virginia M.; Hodgkins, Glenn; Korhonen, Johanna; Livingstone, David M.; Stewart, Kenton M.; Weyhenmeyer, Gesa A.; Granin, Nick G.

2012-01-01

Often extreme events, more than changes in mean conditions, have the greatest impact on the environment and human well-being. Here we examine changes in the occurrence of extremes in the timing of the annual formation and disappearance of lake ice in the Northern Hemisphere. Both changes in the mean condition and in variability around the mean condition can alter the probability of extreme events. Using long-term ice phenology data covering two periods 1855–6 to 2004–5 and 1905–6 to 2004–5 for a total of 75 lakes, we examined patterns in long-term trends and variability in the context of understanding the occurrence of extreme events. We also examined patterns in trends for a 30-year subset (1975–6 to 2004–5) of the 100-year data set. Trends for ice variables in the recent 30-year period were steeper than those in the 100- and 150-year periods, and trends in the 150-year period were steeper than in the 100-year period. Ranges of rates of change (days per decade) among time periods based on linear regression were 0.3−1.6 later for freeze, 0.5−1.9 earlier for breakup, and 0.7−4.3 shorter for duration. Mostly, standard deviation did not change, or it decreased in the 150-year and 100-year periods. During the recent 50-year period, standard deviation calculated in 10-year windows increased for all ice measures. For the 150-year and 100-year periods changes in the mean ice dates rather than changes in variability most strongly influenced the significant increases in the frequency of extreme lake ice events associated with warmer conditions and decreases in the frequency of extreme events associated with cooler conditions.

Infrared Studies of the Variability and Mass Loss of Dusty Asymptotic Giant Branch Stars in the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Sargent, Benjamin; Groenewegen, M. A. T.

2018-01-01

The asymptotic giant branch (AGB) phase is one of the last phases of a star's life. AGB stars lose mass in an outflow in which dust condenses and is pushed away from the star. Extreme AGB stars are so named because their very red colors suggest very large amounts of dust, which in turn suggests extremely high mass loss rates. AGB stars also vary in brightness, and studies show that extreme AGB stars tend to have longer periods than other AGB stars and are more likely to be fundamental mode pulsators than other AGB stars. Extreme AGB stars are difficult to study, as their colors are so red due to their copious amounts of circumstellar dust that they are often not detected at optical wavelengths. Therefore, they must be observed at infrared wavelengths to explore their variability. Using the Spitzer Space Telescope, my team and I have observed a sample of extreme AGB stars in the Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC) over Cycles 9 through 12 during the Warm Spitzer mission. For each cycle, we typically observed a set of extreme AGB stars at both 3.6 and 4.5 microns wavelength approximately monthly for most of a year. These observations reveal a wide range of variability properties. I present results from our analysis of the data obtained from these Spitzer variability programs, including light curve analyses and comparison to period-luminosity diagrams. Funding is acknowledged from JPL RSA # 1561703.

Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

NASA Astrophysics Data System (ADS)

Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun

2017-10-01

Monitoring of fine particulate matter with diameter <2.5 μm (PM2.5) started from 1999 in the US and even later in many other countries. The lack of historical PM2.5 data limits epidemiological studies of long-term exposure of PM2.5 and health outcomes such as cancer. In this study, we aimed to design a flexible approach to reliably estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter <10 μm (PM10) and meteorological variables. Monitoring data of PM10, PM2.5, and meteorological variables covering the entire state of California were obtained from 1999 through 2013. We developed a spatiotemporal model that quantified non-linear associations between PM2.5 concentrations and the following predictor variables: spatiotemporal factors (PM10 and meteorological variables), spatial factors (land-use patterns, traffic, elevation, distance to shorelines, and spatial autocorrelation), and season. Our model accounted for regional-(county) scale spatial autocorrelation, using spatial weight matrix, and local-scale spatiotemporal variability, using local covariates in additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

NASA Astrophysics Data System (ADS)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.

Climate change hampers endangered species through intensified moisture-related plant stresses (Invited)

NASA Astrophysics Data System (ADS)

Bartholomeus, R.; Witte, J.; van Bodegom, P.; Dam, J. V.; Aerts, R.

2010-12-01

With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.

Comprehensive assessment of dam impacts on flow regimes with consideration of interannual variations

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Shao, Quanxi; Zhao, Tongtiegang

2017-09-01

Assessing the impact of human intervention on flow regimes is important in policy making and resource management. Previous impact assessments of dam regulation on flow regimes have focused on long-term average patterns, but interannual variations, which are important characteristics to be considered, have been ignored. In this study, the entire signatures of hydrograph variations of Miyun Reservoir in northern China were described by forty flow regime metrics that incorporate magnitude, variability and frequency, duration, timing, and rate of change for flow events based on a long-term synchronous observation series of inflow and outflow. Principal component analysis and cluster analysis were used to reduce the multidimensionality of the metrics and time and to determine impact patterns and their interannual shifts. Statistically significant driving factors of impact pattern variations were identified. We found that dam regulation resulted in four main impact classes on the flow regimes and that the regulated capacity was interannually attenuated from 1973 to 2010. The impact patterns alternated between the highly regulated class with extremely decreasing flow magnitude, slight variability, and extreme intermittency and the slightly regulated class with extremely increasing flow magnitude, slight variability, and extreme intermittency from 1973 to 1987 and then stabilized in the latter class from 1988 to 2001. After 2001, the pattern gradually changed from the moderately regulated class with moderately decreasing flow magnitude, extreme variability, and extreme intermittency to the slightly regulated class with slightly decreasing flow magnitude, slight variability, and no intermittency. Decreasing precipitation and increasing drought were the primary drivers for the interannual variations of the impact patterns, and inflow variability was the most significant factor affecting the patterns, followed by flow event frequency and duration, magnitude, and timing. This study shows that the use of interannual characteristics can help to gain more insight into the impact of dam regulation on flow regimes and will provide important information to scientifically guide the multi-purpose regulation of dams.

Refining multi-model projections of temperature extremes by evaluation against land-atmosphere coupling diagnostics

NASA Astrophysics Data System (ADS)

Sippel, Sebastian; Zscheischler, Jakob; Mahecha, Miguel D.; Orth, Rene; Reichstein, Markus; Vogel, Martha; Seneviratne, Sonia I.

2017-05-01

The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land-atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land-atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T) and evapotranspiration (ET) benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land-atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T-ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T-ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand, the differences between projected and present-day climate extremes are affected to a lesser extent by the applied constraint, i.e. projected changes are reduced locally by around 0.5 to 1 °C - but this remains a local effect in regions that are highly sensitive to land-atmosphere coupling. In summary, our approach offers a physically consistent, diagnostic-based avenue to evaluate multi-model ensembles and subsequently reduce model biases in simulated and projected extreme temperatures.

El Niño, Climate, and Cholera Associations in Piura, Peru, 1991-2001: A Wavelet Analysis.

PubMed

Ramírez, Iván J; Grady, Sue C

2016-03-01

In Peru, it was hypothesized that epidemic cholera in 1991 was linked to El Niño, the warm phase of El Niño-Southern Oscillation. While previous studies demonstrated an association in 1997-1998, using cross-sectional data, they did not assess the consistency of this relationship across the decade. Thus, how strong or variable an El Niño-cholera relationship was in Peru or whether El Niño triggered epidemic cholera early in the decade remains unknown. In this study, wavelet and mediation analyses were used to characterize temporal patterns among El Niño, local climate variables (rainfall, river discharge, and air temperature), and cholera incidence in Piura, Peru from 1991 to 2001 and to estimate the mediating effects of local climate on El Niño-cholera relationships. The study hypothesis is that El Niño-related connections with cholera in Piura were transient and interconnected via local climate pathways. Overall, our findings provide evidence that a strong El Niño-cholera link, mediated by local hydrology, existed in the latter part of the 1990s but found no evidence of an El Niño association in the earlier part of the decade, suggesting that El Niño may not have precipitated cholera emergence in Piura. Further examinations of cholera epicenters in Peru are recommended to support these results in Piura. For public health planning, the results may improve existing efforts that utilize El Niño monitoring for preparedness during future climate-related extremes in the region.

Advanced dielectric continuum model of preferential solvation

NASA Astrophysics Data System (ADS)

Basilevsky, Mikhail; Odinokov, Alexey; Nikitina, Ekaterina; Grigoriev, Fedor; Petrov, Nikolai; Alfimov, Mikhail

2009-01-01

A continuum model for solvation effects in binary solvent mixtures is formulated in terms of the density functional theory. The presence of two variables, namely, the dimensionless solvent composition y and the dimensionless total solvent density z, is an essential feature of binary systems. Their coupling, hidden in the structure of the local dielectric permittivity function, is postulated at the phenomenological level. Local equilibrium conditions are derived by a variation in the free energy functional expressed in terms of the composition and density variables. They appear as a pair of coupled equations defining y and z as spatial distributions. We consider the simplest spherically symmetric case of the Born-type ion immersed in the benzene/dimethylsulfoxide (DMSO) solvent mixture. The profiles of y(R ) and z(R ) along the radius R, which measures the distance from the ion center, are found in molecular dynamics (MD) simulations. It is shown that for a given solute ion z(R ) does not depend significantly on the composition variable y. A simplified solution is then obtained by inserting z(R ), found in the MD simulation for the pure DMSO, in the single equation which defines y(R ). In this way composition dependences of the main solvation effects are investigated. The local density augmentation appears as a peak of z(R ) at the ion boundary. It is responsible for the fine solvation effects missing when the ordinary solvation theories, in which z =1, are applied. These phenomena, studied for negative ions, reproduce consistently the simulation results. For positive ions the simulation shows that z ≫1 (z =5-6 at the maximum of the z peak), which means that an extremely dense solvation shell is formed. In such a situation the continuum description fails to be valid within a consistent parametrization.

A Data Centred Method to Estimate and Map Changes in the Full Distribution of Daily Precipitation and Its Exceedances

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2014-12-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles or thresholds in distributions of variables such as daily temperature or precipitation. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by 'heavy tailed' distributed variables such as daily precipitation. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those extreme precipitation days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results identify regionally consistent patterns which, dependent on location, show systematic increase in precipitation on the wettest days, shifts in precipitation patterns to less moderate days and more heavy days, and drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013 Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, S. C. Chapman, N. W. Watkins, 2013 Environ. Res. Lett. 8, 034031 [2] Haylock et al. 2008 J. Geophys. Res (Atmospheres), 113, D20119

Extremal entanglement and mixedness in continuous variable systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adesso, Gerardo; Serafini, Alessio; Illuminati, Fabrizio

2004-08-01

We investigate the relationship between mixedness and entanglement for Gaussian states of continuous variable systems. We introduce generalized entropies based on Schatten p norms to quantify the mixedness of a state and derive their explicit expressions in terms of symplectic spectra. We compare the hierarchies of mixedness provided by such measures with the one provided by the purity (defined as tr {rho}{sup 2} for the state {rho}) for generic n-mode states. We then review the analysis proving the existence of both maximally and minimally entangled states at given global and marginal purities, with the entanglement quantified by the logarithmic negativity.more » Based on these results, we extend such an analysis to generalized entropies, introducing and fully characterizing maximally and minimally entangled states for given global and local generalized entropies. We compare the different roles played by the purity and by the generalized p entropies in quantifying the entanglement and the mixedness of continuous variable systems. We introduce the concept of average logarithmic negativity, showing that it allows a reliable quantitative estimate of continuous variable entanglement by direct measurements of global and marginal generalized p entropies.« less

Motor-sensory confluence in tactile perception.

PubMed

Saig, Avraham; Gordon, Goren; Assa, Eldad; Arieli, Amos; Ahissar, Ehud

2012-10-03

Perception involves motor control of sensory organs. However, the dynamics underlying emergence of perception from motor-sensory interactions are not yet known. Two extreme possibilities are as follows: (1) motor and sensory signals interact within an open-loop scheme in which motor signals determine sensory sampling but are not affected by sensory processing and (2) motor and sensory signals are affected by each other within a closed-loop scheme. We studied the scheme of motor-sensory interactions in humans using a novel object localization task that enabled monitoring the relevant overt motor and sensory variables. We found that motor variables were dynamically controlled within each perceptual trial, such that they gradually converged to steady values. Training on this task resulted in improvement in perceptual acuity, which was achieved solely by changes in motor variables, without any change in the acuity of sensory readout. The within-trial dynamics is captured by a hierarchical closed-loop model in which lower loops actively maintain constant sensory coding, and higher loops maintain constant sensory update flow. These findings demonstrate interchangeability of motor and sensory variables in perception, motor convergence during perception, and a consistent hierarchical closed-loop perceptual model.

Hot spots of multivariate extreme anomalies in Earth observations

NASA Astrophysics Data System (ADS)

Flach, M.; Sippel, S.; Bodesheim, P.; Brenning, A.; Denzler, J.; Gans, F.; Guanche, Y.; Reichstein, M.; Rodner, E.; Mahecha, M. D.

2016-12-01

Anomalies in Earth observations might indicate data quality issues, extremes or the change of underlying processes within a highly multivariate system. Thus, considering the multivariate constellation of variables for extreme detection yields crucial additional information over conventional univariate approaches. We highlight areas in which multivariate extreme anomalies are more likely to occur, i.e. hot spots of extremes in global atmospheric Earth observations that impact the Biosphere. In addition, we present the year of the most unusual multivariate extreme between 2001 and 2013 and show that these coincide with well known high impact extremes. Technically speaking, we account for multivariate extremes by using three sophisticated algorithms adapted from computer science applications. Namely an ensemble of the k-nearest neighbours mean distance, a kernel density estimation and an approach based on recurrences is used. However, the impact of atmosphere extremes on the Biosphere might largely depend on what is considered to be normal, i.e. the shape of the mean seasonal cycle and its inter-annual variability. We identify regions with similar mean seasonality by means of dimensionality reduction in order to estimate in each region both the `normal' variance and robust thresholds for detecting the extremes. In addition, we account for challenges like heteroscedasticity in Northern latitudes. Apart from hot spot areas, those anomalies in the atmosphere time series are of particular interest, which can only be detected by a multivariate approach but not by a simple univariate approach. Such an anomalous constellation of atmosphere variables is of interest if it impacts the Biosphere. The multivariate constellation of such an anomalous part of a time series is shown in one case study indicating that multivariate anomaly detection can provide novel insights into Earth observations.

Snow-atmosphere coupling and its impact on temperature variability and extremes over North America

NASA Astrophysics Data System (ADS)

Diro, G. T.; Sushama, L.; Huziy, O.

2018-04-01

The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981-2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40-60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

Evaluating Coupled Human-Hydrologic Systems in High Altitude Regions: A Case Study of the Arun Watershed, Eastern Nepal

NASA Astrophysics Data System (ADS)

Voss, K.; Bookhagen, B.; Tague, C.; Lopez-Carr, D.

2014-12-01

The Himalaya exhibit dynamic ecological, hydrological, and climatic extremes that magnify the variability and extent of natural hazards, resulting in destruction to both physical and human landscapes. Coupled with poverty, these factors intensify local communities' vulnerability to climate change. This study highlights the Arun watershed in eastern Nepal as a case study to evaluate how local communities in high altitude regions are managing their water for domestic and agricultural needs while coping with extreme events, such as floods and landslides. Remotely-sensed precipitation, snowpack and glacial extent data from the past decade are combined with preliminary results from extensive field-based community surveys in the Arun watershed. The analysis of remotely-sensed data will describe seasonal trends in water availability, glacial lake growth, and the spatial variation of these trends within the basin. These hydrologic changes will be linked to the human survey analysis, which will provide an understanding of locals' perceptions of water challenges and the current water management strategies within the basin. Particular attention will be given to a comparison between the eastern and western tributaries of the Arun River, where the catchments are mainly rain-fed (eastern) versus glacial-fed (western). This contrast will highlight how different hydrologic scenarios evidenced from remote-sensing data motivate diverse human water management responses as defined in field surveys. A particular focus will be given to management decisions related to agriculture expansion and hydropower development. This synthesis of remote-sensing and social research methodologies provides a valuable perspective on coupled human-hydrologic systems.

A randomized, controlled, double-blind trial of fluoroscopic caudal epidural injections in the treatment of lumbar disc herniation and radiculitis.

PubMed

Manchikanti, Laxmaiah; Singh, Vijay; Cash, Kimberly A; Pampati, Vidyasagar; Damron, Kim S; Boswell, Mark V

2011-11-01

A randomized, controlled, double-blind trial. To assess the effectiveness of fluoroscopically directed caudal epidural injections in managing chronic low back and lower extremity pain in patients with disc herniation and radiculitis with local anesthetic with or without steroids. The available literature on the effectiveness of epidural injections in managing chronic low back pain secondary to disc herniation is highly variable. One hundred twenty patients suffering with low back and lower extremity pain with disc herniation and radiculitis were randomized to one of the two groups: group I received caudal epidural injections with an injection of local anesthetic, lidocaine 0.5%, 10 mL; group II patients received caudal epidural injections with 0.5% lidocaine, 9 mL, mixed with 1 mL of steroid. The Numeric Rating Scale (NRS), the Oswestry Disability Index 2.0 (ODI), employment status, and opioid intake were utilized with assessment at 3, 6, and 12 months posttreatment. The percentage of patients with significant pain relief of 50% or greater and/or improvement in functional status with 50% or more reduction in ODI scores was seen in 70% and 67% in group I and 77% and 75% in group II with average procedures per year of 3.8 ± 1.4 in group I and 3.6 + 1.1 in group II. However, the relief with first and second procedures was significantly higher in the steroid group. The number of injections performed was also higher in local anesthetic group even though overall relief was without any significant difference among the groups. There was no difference among the patients receiving steroids. Caudal epidural injection with local anesthetic with or without steroids might be effective in patients with disc herniation or radiculitis. The present evidence illustrates potential superiority of steroids compared with local anesthetic at 1-year follow-up.

Estimating meme fitness in adaptive memetic algorithms for combinatorial problems.

PubMed

Smith, J E

2012-01-01

Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each of a set of local improvement operators is applied, according to an estimate of their current value to the search process. This paper addresses the issue of how the current value should be estimated. Assuming the estimate occurs over several applications of a meme, we consider whether the extreme or mean improvements should be used, and whether this aggregation should be global, or local to some part of the solution space. To investigate these issues, we use the well-established COMA framework that coevolves the specification of a population of memes (representing different local search algorithms) alongside a population of candidate solutions to the problem at hand. Two very different memetic algorithms are considered: the first using adaptive operator pursuit to adjust the probabilities of applying a fixed set of memes, and a second which applies genetic operators to dynamically adapt and create memes and their functional definitions. For the latter, especially on combinatorial problems, credit assignment mechanisms based on historical records, or on notions of landscape locality, will have limited application, and it is necessary to estimate the value of a meme via some form of sampling. The results on a set of binary encoded combinatorial problems show that both methods are very effective, and that for some problems it is necessary to use thousands of variables in order to tease apart the differences between different reward schemes. However, for both memetic algorithms, a significant pattern emerges that reward based on mean improvement is better than that based on extreme improvement. This contradicts recent findings from adapting the parameters of operators involved in global evolutionary search. The results also show that local reward schemes outperform global reward schemes in combinatorial spaces, unlike in continuous spaces. An analysis of evolving meme behaviour is used to explain these findings.

The NOAA Local Climate Analysis Tool - An Application in Support of a Weather Ready Nation

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Horsfall, F. M.

2012-12-01

Citizens across the U.S., including decision makers from the local to the national level, have a multitude of questions about climate, such as the current state and how that state fits into the historical context, and more importantly, how climate will impact them, especially with regard to linkages to extreme weather events. Developing answers to these types of questions for locations has typically required extensive work to gather data, conduct analyses, and generate relevant explanations and graphics. Too frequently providers don't have ready access to or knowledge of reliable, trusted data sets, nor sound, scientifically accepted analysis techniques such that they can provide a rapid response to queries they receive. In order to support National Weather Service (NWS) local office forecasters with information they need to deliver timely responses to climate-related questions from their customers, we have developed the Local Climate Analysis Tool (LCAT). LCAT uses the principles of artificial intelligence to respond to queries, in particular, through use of machine technology that responds intelligently to input from users. A user translates customer questions into primary variables and issues and LCAT pulls the most relevant data and analysis techniques to provide information back to the user, who in turn responds to their customer. Most responses take on the order of 10 seconds, which includes providing statistics, graphical displays of information, translations for users, metadata, and a summary of the user request to LCAT. Applications in Phase I of LCAT, which is targeted for the NWS field offices, include Climate Change Impacts, Climate Variability Impacts, Drought Analysis and Impacts, Water Resources Applications, Attribution of Extreme Events, and analysis techniques such as time series analysis, trend analysis, compositing, and correlation and regression techniques. Data accessed by LCAT are homogenized historical COOP and Climate Prediction Center climate division data available at NCDC. Applications for other NOAA offices and Federal agencies are currently being investigated, such as incorporation of tidal data, fish stocks, sea surface temperature, health-related data, and analyses relevant to those datasets. We will describe LCAT, its basic functionality, examples of analyses, and progress being made to provide the tool to a broader audience in support of ocean, fisheries, and health applications.

Variability of temperature properties over Kenya based on observed and reanalyzed datasets

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie; Sagero, Phillip Obaigwa

2017-08-01

Updated information on trends of climate extremes is central in the assessment of climate change impacts. This work examines the trends in mean, diurnal temperature range (DTR), maximum and minimum temperatures, 1951-2012 and the recent (1981-2010) extreme temperature events over Kenya. The study utilized daily observed and reanalyzed monthly mean, minimum, and maximum temperature datasets. The analysis was carried out based on a set of nine indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The trend of the mean and the extreme temperature was determined using Mann-Kendall rank test, linear regression analysis, and Sen's slope estimator. December-February (DJF) season records high temperature while June-August (JJA) experiences the least temperature. The observed rate of warming is + 0.15 °C/decade. However, DTR does not show notable annual trend. Both seasons show an overall warming trend since the early 1970s with abrupt and significant changes happening around the early 1990s. The warming is more significant in the highland regions as compared to their lowland counterparts. There is increase variance in temperature. The percentage of warm days and warm nights is observed to increase, a further affirmation of warming. This work is a synoptic scale study that exemplifies how seasonal and decadal analyses, together with the annual assessments, are important in the understanding of the temperature variability which is vital in vulnerability and adaptation studies at a local/regional scale. However, following the quality of observed data used herein, there remains need for further studies on the subject using longer and more data to avoid generalizations made in this study.

Heat exposure in cities: combining the dynamics of temperature and population

NASA Astrophysics Data System (ADS)

Hu, L.; Wilhelmi, O.; Uejio, C. K.

2017-12-01

Assessment of human exposure to extreme heat requires the distributions of temperature and population. However, both variables are dynamic, thus presenting many challenges in capturing temperature and population patterns spatially and over time in an urban context. This study aims to improve the understanding of spatiotemporal patterns of urban population exposure to heat, taking Chicago, USA as an example. We estimate the hourly, geographically variable, population distribution considering commute of workers and students in a regular weekday and analyze the diurnal air temperature patterns during different meteorological conditions from satellite observations. The results show a relatively larger temperature increase in less urbanized areas during extreme heat events (EHEs), resulting in a spatially homogeneous temperature distribution over Chicago Metropolitan area. A lake cooling effect is weaker during EHEs. Population dynamics due to daily commute determine higher population density in more urbanized areas during daytime. The city-wide analysis reveals that the exposure is more sensitive to the nighttime temperature increases, and EHEs enhance this sensitivity. The high exposure hotspots are identified at the northwest Chicago, Cicero and Oak Park areas, where the influence from Lake Michigan is weakened, while the spatial extent of high outdoor exposure areas varies diurnally. This study's findings have potential to better inform general heat mitigation strategies during hot summer months and facilitate emergency response during EHEs. Availability of remotely-sensed temperature observations as well as the workers and students commute-adjusted population data allows for the adoption of this study's methodology in other major metropolitan areas. A better understanding of space-time patterns of urban population's exposure to heat will further enable local decision makers to mitigate extreme heat health risks and develop more targeted heat preparedness and response strategies.

The NASA Energy and Water Cycle Extreme (NEWSE) Integration Project

NASA Technical Reports Server (NTRS)

House, P. R.; Lapenta, W.; Schiffer, R.

2008-01-01

Skillful predictions of water and energy cycle extremes (flood and drought) are elusive. To better understand the mechanisms responsible for water and energy extremes, and to make decisive progress in predicting these extremes, the collaborative NASA Energy and Water cycle Extremes (NEWSE) Integration Project, is studying these extremes in the U.S. Southern Great Plains (SGP) during 2006-2007, including their relationships with continental and global scale processes, and assessment of their predictability on multiple space and time scales. It is our hypothesis that an integrative analysis of observed extremes which reflects the current understanding of the role of SST and soil moisture variability influences on atmospheric heating and forcing of planetary waves, incorporating recently available global and regional hydro- meteorological datasets (i.e., precipitation, water vapor, clouds, etc.) in conjunction with advances in data assimilation, can lead to new insights into the factors that lead to persistent drought and flooding. We will show initial results of this project, whose goals are to provide an improved definition, attribution and prediction on sub-seasonal to interannual time scales, improved understanding of the mechanisms of decadal drought and its predictability, including the impacts of SST variability and deep soil moisture variability, and improved monitoring/attributions, with transition to applications; a bridging of the gap between hydrological forecasts and stakeholders (utilization of probabilistic forecasts, education, forecast interpretation for different sectors, assessment of uncertainties for different sectors, etc.).

Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of climate extremes and associated impacts. [1] http://www.climateprediction.net/weatherathome/

Past climate variability inferred from statistical processing of documentary data: a case study on extreme meteorological events in western central France from 1500 to 2000 AD

NASA Astrophysics Data System (ADS)

Poirier, Clément; Chaumillon, Eric; Audé, Jean-Luc

2010-05-01

Recent human-induced climate changes are expected to have an impact on extreme events including shifts in storm tracks, heavier precipitations and more severe droughts (Planton, 2008). Although climate models successfully describe the past mean climate variability, they often fail to correctly reproduce such extreme events, mainly because of a low spatial and temporal resolution (Sánchez et al., 2004). Reports of extreme meteorological events gathered from documentary archives are be useful to fill this gap, and would also provide insights into local climatic variations (Leijonhufvud et al., 2008; Rodrigo, 2008; Wheeler, 2006). In this study, a local text book published by Audé (2006) was used as a source of climatic data. It consists of a list of extreme meteorological events recorded in historical archives (diaries mainly) in western central France, along the Bay of Biscay. From the book, 284 extreme meteorological events that occurred between 1500 and 2000 were selected. A presence-absence matrix was built, the events being classified in 7 distinct categories by Audé. A preliminary multivariate analysis (Principal Component Analysis) was used to group these categories into 4 classes of events. First axis (22.3% of explained variance) discriminated the events related to temperature, with frosts and snowfalls on one side, versus gales and storms on the other side. Second axis (18.5% of explained variance) discriminated the events related to precipitation, with floods and rainfalls on one side (humid), versus droughts on the other (dry). For each class, a 29-year running mean was computed to convert binary qualitative data to semi-quantitative curves. A spectral analysis was also performed on the same binary data to detect potential climatic cycles. Despite the randomness of the historical records reported in this book, that much relies on the subjective perception of meteorological events by past witnesses, the results obtained are consistent with existing data about past climate changes since 1500 AD. Temperature-related events show a significant negative correlation (R2 = -0.49, p = 0) with δ14C curve (Reimer et al., 2004), whereas precipitation-related events show a significant positive correlation (R2 = 0.66, p = 0) with the same curve. As an example, recurrent flood and rainfall events occurred from 1630 to 1720 and from 1800 to 1830, which corresponds to the Maunder and Dalton periods of minimum solar activity respectively. Spectral analysis carried out on the 4 classes of events revealed several cycles in the data, in particular a 11 year cycle that corresponds to the Schwabe cycle, and a 85 year cycle that might be related to Gleissberg cycle. The last 150 years display unusual conditions with increasing storms, gales and droughts. The documentary data analysed in the present study might provide interesting information about the consequences of human-induced global warming on extreme meteorological events. They would also be useful as a source of information about local climate variations. References: Audé J.L., 2006. Chronique du climat en Poitou-Charentes Vendée. Lonali Editions, France, 152 pp. Leijonhufvud L., Wilson R., Moberg A. 2008. The Holocene 18(2), 333-343 Planton S., Déqué M., Chauvin F., Terray L., 2008. Comptes Rendus Geosciences, 340 (9-10), 564-574. Reimer P.J. et al., 2004. Radiocarbon 46, 1029-1058. Rodrigo F.S., 2008. Climatic Change 87, 471-487. Sánchez E., Gallardo C., Gaertner M.A, Arribas A., Castro M., 2004. Global and Planetary Change 44, 163-180. Wheeler D., 2006. Archives 31, 119-132.

Global Weirding? - Using Very Large Ensembles and Extreme Value Theory to assess Changes in Extreme Weather Events Today

NASA Astrophysics Data System (ADS)

Otto, F. E. L.; Mitchell, D.; Sippel, S.; Black, M. T.; Dittus, A. J.; Harrington, L. J.; Mohd Saleh, N. H.

2014-12-01

A shift in the distribution of socially-relevant climate variables such as daily minimum winter temperatures and daily precipitation extremes, has been attributed to anthropogenic climate change for various mid-latitude regions. However, while there are many process-based arguments suggesting also a change in the shape of these distributions, attribution studies demonstrating this have not currently been undertaken. Here we use a very large initial condition ensemble of ~40,000 members simulating the European winter 2013/2014 using the distributed computing infrastructure under the weather@home project. Two separate scenarios are used:1. current climate conditions, and 2. a counterfactual scenario of "world that might have been" without anthropogenic forcing. Specifically focusing on extreme events, we assess how the estimated parameters of the Generalized Extreme Value (GEV) distribution vary depending on variable-type, sampling frequency (daily, monthly, …) and geographical region. We find that the location parameter changes for most variables but, depending on the region and variables, we also find significant changes in scale and shape parameters. The very large ensemble allows, furthermore, to assess whether such findings in the fitted GEV distributions are consistent with an empirical analysis of the model data, and whether the most extreme data still follow a known underlying distribution that in a small sample size might otherwise be thought of as an out-lier. The ~40,000 member ensemble is simulated using 12 different SST patterns (1 'observed', and 11 best guesses of SSTs with no anthropogenic warming). The range in SSTs, along with the corresponding changings in the NAO and high-latitude blocking inform on the dynamics governing some of these extreme events. While strong tele-connection patterns are not found in this particular experiment, the high number of simulated extreme events allows for a more thorough analysis of the dynamics than has been performed before. Therefore, combining extreme value theory with very large ensemble simulations allows us to understand the dynamics of changes in extreme events which is not possible just using the former but also shows in which cases statistics combined with smaller ensembles give as valid results as very large initial conditions.

Influence of quality control variables on failure of graphite/epoxy under extreme moisture conditions

NASA Technical Reports Server (NTRS)

Clements, L. L.; Lee, P. R.

1980-01-01

Tension tests on graphite/epoxy composites were performed to determine the influence of various quality control variables on failure strength as a function of moisture and moderate temperatures. The extremely high and low moisture contents investigated were found to have less effect upon properties than did temperature or the quality control variables of specimen flaws and prepreg batch to batch variations. In particular, specimen flaws were found to drastically reduce the predicted strength of the composite, whereas specimens from different batches of prepreg displayed differences in strength as a function of temperature and extreme moisture exposure. The findings illustrate the need for careful specimen preparation, studies of flaw sensitivity, and careful quality control in any study of composite materials.

High Resolution Spatiotemporal Climate Reconstruction and Variability in East Asia during Little Ice Age

NASA Astrophysics Data System (ADS)

Lin, K. H. E.; Wang, P. K.; Lee, S. Y.; Liao, Y. C.; Fan, I. C.; Liao, H. M.

2017-12-01

The Little ice Age (LIA) is one of the most prominent epochs in paleoclimate reconstruction of the Common Era. While the signals of LIA were generally discovered across hemispheres, wide arrays of regional variability were found, and the reconstructed anomalies were sometimes inconsistent across studies by using various proxy data or historical records. This inconsistency is mainly attributed to limited data coverage at fine resolution that can assist high-resolution climate reconstruction in the continuous spatiotemporal trends. Qing dynasty (1644-1911 CE) of China existed in the coldest period of LIA. Owing to a long-standing tradition that acquired local officials to record odds and social or meteorological events, thousands of local chronicles were left. Zhang eds. (2004) took two decades to compile all these meteorological records in a compendium, for which we then digitized and coded all records into our REACHS database system for reconstructing climate. There were in total 1,435 points (sites) in our database for over 80,000 events in the period of time. After implementing two-rounds coding check for data quality control (accuracy rate 87.2%), multiple indexes were retrieved for reconstructing annually and seasonally resolved temperature and precipitation series for North, Central, and South China. The reconstruction methods include frequency count and grading, with usage of multiple regression models to test sensitivity and to calculate correlations among several reconstructed series. Validation was also conducted through comparison with instrumental data and with other reconstructed series in previous studies. Major research results reveal interannual (3-5 years), decadal (8-12 years), and interdecadal (≈30 years) variabilities with strong regional expressions across East China. Cooling effect was not homogenously distributed in space and time. Flood and drought conditions frequently repeated but the spatiotemporal pattern was variant, indicating likely different climate regimes that can be linked to the dynamism of large atmospheric circulation and East Asian monsoon. Spatiotemporal analysis of extreme events such as typhoons and extreme droughts also indicated similar patterns. More detailed analysis are undertaken to explain the physical mechanisms that can drive these changes.

Forecasting of extreme events in Andes mountain basins using CFSv2

NASA Astrophysics Data System (ADS)

Castro, L.

2017-12-01

As has been shown in several recent studies related with climate change, there has been an increase in heavy daily precipitation events, and this is expected to continue in almost all areas of the globe. In central Chile, where the hydrological regime is influenced by snow accumulation, an increase in temperatures is expected due to CC, which in turn may cause an elevation of the freezing level. The impact on the freezing level increase is also significant because a larger area of the basin will be exposed to liquid precipitation rather than snow, and afterwards will have a strong impact on streamflow. The frequency of extreme precipitation events and freezing level increases have recently affected the north and central parts of Chile. In order to predict the severity of an extreme hydrometeorological event in a mountainous basin affected by rainfall and freezing level variations, this paper pose that it is necessary to know in advance the expected meteorology and the way it will affect the hydrological response of the basin. To achieve this purpose, it will be necessary to have meteorological forecasts of a numerical model for short-term prediction, corrected and disaggregated at local scale. The methodological process is as follows. First, we consider the generation of daily forecasts at local scale using statistical downscaling methods for the forecasts obtained from an NWP model. Second, we pose to improve our knowledge the spatial-temporal distribution of the meteorological forcings using a dense network of meteorological stations in a mountain basin. With the above, the statistical methods used to represent the spatial-temporal variability of the meteorological forcings at basin scale will be evaluated.

Understanding Extreme Precipitation Behaviour in British Columbia's Lower Mainland Using Historical and Proxy Records

NASA Astrophysics Data System (ADS)

Spry, Christina

In British Columbia, Pineapple Express storms can lead to flooding, slope failures and negative impacts to water quality. Mitigating the impacts of extreme weather events in a changing climate requires an understanding of how local climate responds to regional-toglobal climate forcing patterns. In this study, I use historical and proxy data to identify the distinguishing characteristics of Pineapple Express storms and to develop a tree ring oxygen isotope record (1960--1995) of local climate conditions in the Lower Mainland of British Columbia. I found that high magnitude Pineapple Express storms have significantly higher precipitation and streamflow than other storms types, which result in relatively high contributions of Pineapple Express storms to the annual water budget. As well, Pineapple Express precipitation is characterized by an enriched delta18O isotopic signature when compared to precipitation originating from the North Pacific Ocean. However, differences in source water do not appear to be driving the variability in tree ring delta18O ratios. Instead, tree ring isotopic values exhibit a regional climate pattern that is strongly driven by latitudinal temperature gradients and the Rayleigh distillation effect. Therefore, future warmer conditions may decrease the temperature gradient between the equator and the poles, which can be recorded in the tree ring isotope record. The results also suggest that warmer temperatures due to climate change could result in more active Pineapple Express storm seasons, with multiple PE storms happening over a short period of time. Concurrent storms significantly increase the risk to society because the resulting antecedent saturated soil conditions can trigger precipitationinduced natural hazards. Keywords: extreme weather; stable isotopes; Pineapple Express; British Columbia; climate change; tree rings.

Inter-model variability in hydrological extremes projections for Amazonian sub-basins

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

2014-05-01

Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.

The Discovery of a Microarcsecond Quasar: J1819+3845.

PubMed

Dennett-Thorpe; de Bruyn AG

2000-02-01

We report on the discovery of a source that exhibits over 300% amplitude changes in radio flux density on the period of hours. This source, J1819+3845, is the most extremely variable extragalactic source known in the radio sky. We believe these properties are due to interstellar scintillation and show that the source must emit at least 55% of its flux density within a radius of fewer than 16 µas at 5 GHz. The apparent brightness temperature is greater than 5x1012 K, and the source may be explained by a relativistically moving source with a Doppler factor of approximately 15. The scattering occurs predominantly in material only a few tens of parsecs from the Earth, which explains its unusually rapid variability. If the source PKS 0405-385 is similarly affected by local scattering material, Doppler factors of approximately 1000 are not required to explain this source. The discovery of a second source whose properties are well modeled by interstellar scintillation strengthens the argument for this as the cause for much of the variation seen in intraday variables.

Direct observations of ice seasonality reveal changes in climate over the past 320–570 years

USGS Publications Warehouse

Sharma, Sapna; Magnuson, John J.; Batt, Ryan D.; Winslow, Luke; Korhonen, Johanna; Yasuyuki Aono,

2016-01-01

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.

Direct observations of ice seasonality reveal changes in climate over the past 320–570 years

PubMed Central

Sharma, Sapna; Magnuson, John J.; Batt, Ryan D.; Winslow, Luke A.; Korhonen, Johanna; Aono, Yasuyuki

2016-01-01

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality. PMID:27113125

Mineralogical variation of skarn ore from the Tellerhäuser deposit, Pöhla, Germany

NASA Astrophysics Data System (ADS)

Simons, Bethany; Andersen, Jens Christian; Rollinson, Gavyn; Armstrong, Robin; Dolgopolova, Alla; Seltmann, Reimar; Stanley, Chris; Roscher, Marco

2017-04-01

The polymetallic Zn-Fe-Sn-Cu-In skarns at Pöhla Tellerhäuser in the western Erzgebirge represent some of the largest unexploited occurrences of Sn and In in Europe. The skarns developed in schists and gneisses at the margin of the Schwarzenberg Gneiss cupola and the Eibenstock granites. The flat-lying skarn layers display extreme mineralogical variability with alternating units of pyroxene, sphalerite, magnetite, amphibole and calc-silicate skarns with hanging wall schist and feeder stockwork. The polymetallic skarn ores represent a complex challenge for mineral processing, with fine-grained, locked target minerals and partitioning of target metals into silicates (e.g. Sn in malayaite). Optical microscopy, QEMSCAN® and electron-probe microanalysis have been used to determine the mineralogical variability of the skarn types with the aim to determine the deportment of the target metals to guide mineral processing test work. The composition of the skarns is extremely variable reflecting the complex mineralogy and indicating substantial variability associated with replacement reactions through the protolith(s). Cassiterite (SnO2) is the dominant Sn-bearing mineral in all the skarn types. However, the skarns also carry malayaite (CaSnO[SiO4], up to 0.03 vol%), which locally dominates over cassiterite. Cassiterite is intergrown with Fe-amphibole, grossular garnet, fluorite and magnetite. The cassiterite is unaltered, but some grains have rare iron oxide rims and inclusions. Malayaite shows a similar association to cassiterite and is intergrown as clusters of grains with silicate gangue, particularly Fe amphibole and grossular garnet and remains unaltered with no inclusions. Zinc is exclusively hosted in sphalerite and varies from 0.02 wt.% in the hanging wall schist to 36.5 wt.% in the sphalerite skarn. The high Zn values are accompanied by high values of Cd (locally in excess of 1000 ppm) and In (up to 180 ppm). Sphalerite grains are locally up to 4 mm, subhedral with chalcopyrite disease and pyrite epitaxial growth along contacts between sphalerite and magnetite. Inclusions in sphalerite include bornite, enargite, chalcocite and arsenopyrite. Magnetite comprises up to 94 vol% (mean 32 vol%) of the magnetite skarn and displays extensive haematite alteration. Intergrown with magnetite are subordinate cassiterite and sphalerite with chalcopyrite disease and high In concentrations. The mineralogical complexity is the most significant challenge for processing of the Tellerhäuser ore. Some Sn is locked within silicates leading to an expected loss in processing. The diverse gangue mineralogy is likely to interfere with traditional gravity and magnetic separation techniques. Biohydrometallurgy may offer a particularly attractive method of recovery for Zn, Cu and In. This contribution is sponsored by the EU Horizon 2020 project "FAME" (grant 641650)

Extreme Variability in a Broad Absorption Line Quasar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stern, Daniel; Jun, Hyunsung D.; Graham, Matthew J.

CRTS J084133.15+200525.8 is an optically bright quasar at z = 2.345 that has shown extreme spectral variability over the past decade. Photometrically, the source had a visual magnitude of V ∼ 17.3 between 2002 and 2008. Then, over the following five years, the source slowly brightened by approximately one magnitude, to V ∼ 16.2. Only ∼1 in 10,000 quasars show such extreme variability, as quantified by the extreme parameters derived for this quasar assuming a damped random walk model. A combination of archival and newly acquired spectra reveal the source to be an iron low-ionization broad absorption line quasar withmore » extreme changes in its absorption spectrum. Some absorption features completely disappear over the 9 years of optical spectra, while other features remain essentially unchanged. We report the first definitive redshift for this source, based on the detection of broad H α in a Keck/MOSFIRE spectrum. Absorption systems separated by several 1000 km s{sup −1} in velocity show coordinated weakening in the depths of their troughs as the continuum flux increases. We interpret the broad absorption line variability to be due to changes in photoionization, rather than due to motion of material along our line of sight. This source highlights one sort of rare transition object that astronomy will now be finding through dedicated time-domain surveys.« less

Musculoskeletal pain and re-employment among unemployed job seekers: a three-year follow-up study.

PubMed

Nwaru, Chioma A; Nygård, Clas-Håkan; Virtanen, Pekka

2016-07-08

Poor health is a potential risk factor for not finding employment among unemployed individuals. We investigated the associations between localized and multiple-site musculoskeletal pain and re-employment in a three-year follow-up of unemployed job seekers. Unemployed people (n = 539) from six localities in southern Finland who participated in various active labour market policy measures at baseline in 2002/2003 were recruited into a three-year health service intervention trial. A questionnaire was used to collect data on musculoskeletal health and background characteristics at baseline and on employment status at the end of the follow-up. We conducted a complete case (n = 284) and multiple imputation analyses using logistic regression to investigate the association between baseline musculoskeletal pain and re-employment after three years. Participants with severe pain in the lower back were less likely to become re-employed. This was independent of potential confounding variables. Pain in the hands/upper extremities, neck/shoulders, lower extremities, as well as multiple site were not determinants of re-employment. Our findings lend some support to the hypothesis that poor health can potentially cause health selection into employment. There is the need to disentangle health problems in order to clearly appreciate their putative impact on employment. This will allow for more targeted interventions for the unemployed.

2015-16 ENSO Drove Tropical Soil Moisture Dynamics and Methane Fluxes

NASA Astrophysics Data System (ADS)

Aronson, E. L.; Dierick, D.; Botthoff, J.; Swanson, A. C.; Johnson, R. F.; Allen, M. F.

2017-12-01

The El Niño/Southern Oscillation Event (ENSO) cycle drives large-scale climatic trends globally. Within the new world tropics, El Niño brings dryer weather than the counterpart La Niña. Atmospheric methane growth rates have shown extreme variability over the past three decades. One proposed driver is the proportion of tropical land surface saturated, affecting methane production or consumption. We measured methane flux bimonthly through the transition of 2015-16 ENSO. The date of measurement, across El Niño and La Niña within the typical "rainy" and "dry" seasons, to be the most significant driver of methane flux. Soil moisture varied across this time period, and regulated methane flux. During the strong El Niño, extreme dry soil conditions occurred in a typical "rainy" season month reducing soil moisture. Wetter than usual soil conditions appeared during the "rainy" season month of the moderate La Niña. The dry El Niño soils corresponded to greater methane consumption by tropical forest soils, and a reduced local atmospheric column methane concentration. Conversely, the wet La Niña soils had lower methane consumption and higher local atmospheric column methane concentrations. The ENSO cycle is a strong driver of tropical terrestrial and wetland soil moisture conditions, and can regulate global atmospheric methane dynamics.

Delineation of Spatial Variability in the Temperature-Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada.

PubMed

Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B

2017-01-01

Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998-2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Our methods provide a data-driven framework for spatial delineation of the temperature--mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature-mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66-75; http://dx.doi.org/10.1289/EHP224.

Delineation of Spatial Variability in the Temperature–Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada

PubMed Central

Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B.

2016-01-01

Background: Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. Objectives: We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Methods: Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998–2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. Results: The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Conclusions: Our methods provide a data-driven framework for spatial delineation of the temperature-–mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature–mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66–75; http://dx.doi.org/10.1289/EHP224 PMID:27346526

A systematic review of pathways to and processes associated with radicalization and extremism amongst Muslims in Western societies.

PubMed

McGilloway, Angela; Ghosh, Priyo; Bhui, Kamaldeep

2015-02-01

Following the terrorist attacks of 9/11 in the USA and 7/7 in the UK, academic interest in factors involved in radicalization and terrorism has increased dramatically. Many related social and psychological theories have been put forward, however terrorism literature still lacks empirical research. In particular, little is known about the early processes and pathways to radicalization. Our aim is to investigate original research on pathways and processes associated with radicalization and extremism amongst people of Muslim heritage living in Western societies, that is, the group prioritized by counter-terrorism policy. Studies included in the review were original qualitative or quantitative primary research published in peer-reviewed journals, identified by searching research databases. All disciplines of journals were included. No single cause or pathway was implicated in radicalization and violent extremism. Individuals may demonstrate vulnerabilities that increase exposure to radicalization; however, the only common characteristic determined that terrorists are generally well-integrated, 'normal' individuals. Engagement in such activity is dependent on a wide range of interacting variables influenced by personal, localized and externalized factors. Further research should examine broader determinants of radicalization in susceptible populations. Future policy should follow this public health approach rather than constructing from perpetrators already committed to engaging in terrorism.

Using Atmospheric Circulation Patterns to Detect and Attribute Changes in the Risk of Extreme Climate Events

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.; Horton, D. E.; Singh, D.; Swain, D. L.; Touma, D. E.; Mankin, J. S.

2015-12-01

Because of the high cost of extreme events and the growing evidence that global warming is likely to alter the statistical distribution of climate variables, detection and attribution of changes in the probability of extreme climate events has become a pressing topic for the scientific community, elected officials, and the public. While most of the emphasis has thus far focused on analyzing the climate variable of interest (most often temperature or precipitation, but also flooding and drought), there is an emerging emphasis on applying detection and attribution analysis techniques to the underlying physical causes of individual extreme events. This approach is promising in part because the underlying physical causes (such as atmospheric circulation patterns) can in some cases be more accurately represented in climate models than the more proximal climate variable (such as precipitation). In addition, and more scientifically critical, is the fact that the most extreme events result from a rare combination of interacting causes, often referred to as "ingredients". Rare events will therefore always have a strong influence of "natural" variability. Analyzing the underlying physical mechanisms can therefore help to test whether there have been changes in the probability of the constituent conditions of an individual event, or whether the co-occurrence of causal conditions cannot be distinguished from random chance. This presentation will review approaches to applying detection/attribution analysis to the underlying physical causes of extreme events (including both "thermodynamic" and "dynamic" causes), and provide a number of case studies, including the role of frequency of atmospheric circulation patterns in the probability of hot, cold, wet and dry events.

Climate variability and vulnerability to climate change: a review

PubMed Central

Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J

2014-01-01

The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802

Changes in Extremely Hot Summers over the Global Land Area under Various Warming Targets.

PubMed

Wang, Lei; Huang, Jianbin; Luo, Yong; Yao, Yao; Zhao, Zongci

2015-01-01

Summer temperature extremes over the global land area were investigated by comparing 26 models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with observations from the Goddard Institute for Space Studies (GISS) and the Climate Research Unit (CRU). Monthly data of the observations and models were averaged for each season, and statistics were calculated for individual models before averaging them to obtain ensemble means. The summers with temperature anomalies (relative to 1951-1980) exceeding 3σ (σ is based on the local internal variability) are defined as "extremely hot". The models well reproduced the statistical characteristics evolution, and partly captured the spatial distributions of historical summer temperature extremes. If the global mean temperature increases 2°C relative to the pre-industrial level, "extremely hot" summers are projected to occur over nearly 40% of the land area (multi-model ensemble mean projection). Summers that exceed 5σ warming are projected to occur over approximately 10% of the global land area, which were rarely observed during the reference period. Scenarios reaching warming levels of 3°C to 5°C were also analyzed. After exceeding the 5°C warming target, "extremely hot" summers are projected to occur throughout the entire global land area, and summers that exceed 5σ warming would become common over 70% of the land area. In addition, the areas affected by "extremely hot" summers are expected to rapidly expand by more than 25%/°C as the global mean temperature increases by up to 3°C before slowing to less than 16%/°C as the temperature continues to increase by more than 3°C. The area that experiences summers with warming of 5σ or more above the warming target of 2°C is likely to maintain rapid expansion of greater than 17%/°C. To reduce the impacts and damage from severely hot summers, the global mean temperature increase should remain low.

Extreme heat changes post-heat wave community reassembly

PubMed Central

Seifert, Linda I; Weithoff, Guntram; Vos, Matthijs

2015-01-01

Climate forecasts project further increases in extremely high-temperature events. These present threats to biodiversity, as they promote population declines and local species extinctions. This implies that ecological communities will need to rely more strongly on recovery processes, such as recolonization from a meta-community context. It is poorly understood how differences in extreme event intensity change the outcome of subsequent community reassembly and if such extremes modify the biotic environment in ways that would prevent the successful re-establishment of lost species. We studied replicated aquatic communities consisting of algae and herbivorous rotifers in a design that involved a control and two different heat wave intensity treatments (29°C and 39°C). Animal species that suffered heat-induced extinction were subsequently re-introduced at the same time and density, in each of the two treatments. The 39°C treatment led to community closure in all replicates, meaning that a previously successful herbivore species could not re-establish itself in the postheat wave community. In contrast, such closure never occurred after a 29°C event. Heat wave intensity determined the number of herbivore extinctions and strongly affected algal relative abundances. Re-introduced herbivore species were thus confronted with significantly different food environments. This ecological legacy generated by heat wave intensity led to differences in the failure or success of herbivore species re-introductions. Reassembly was significantly more variable, and hence less predictable, after an extreme heat wave, and was more canalized after a moderate one. Our results pertain to relatively simple communities, but they suggest that ecological legacies introduced by extremely high-temperature events may change subsequent ecological recovery and even prevent the successful re-establishment of lost species. Knowing the processes promoting and preventing ecological recovery is crucial to the success of species re-introduction programs and to our ability to restore ecosystems damaged by environmental extremes. PMID:26078851

Santa Ana Winds of Southern California: Their Climatology and Variability Spanning 6.5 Decades from Regional Dynamical Modelling

NASA Astrophysics Data System (ADS)

Guzman-Morales, J.; Gershunov, A.

2015-12-01

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region. In spite of their tremendous episodic impacts on the health, economy and mood of the region, climate-scale behavior of SAW is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis product and construct an hourly SAW catalogue spanning 65 years. We describe the long-term SAW climatology at relevant time-space resolutions, i.e, we developed local and regional SAW indices and analyse their variability on hourly, daily, annual, and multi-decadal timescales. Local and regional SAW indices are validated with available anemometer observations. Characteristic behaviors are revealed, e.g. the SAW intensity-duration relationship. At interdecadal time scales, we find that seasonal SAW activity is sensitive to prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system that are also known to affect the hydroclimate of this region. Lastly, we do not find any long-term trend in SAW frequency and intensity as previously reported. Instead, we identify a significant long-term trend in SAW behavior whereby contribution of extreme SAW events to total seasonal SAW activity has been increasing at the expense of moderate events. These findings motivate further investigation on SAW evolution in future climate and its impact on wildfires.

Variability of hydrological extreme events in East Asia and their dynamical control: a comparison between observations and two high-resolution global climate models

NASA Astrophysics Data System (ADS)

Freychet, N.; Duchez, A.; Wu, C.-H.; Chen, C.-A.; Hsu, H.-H.; Hirschi, J.; Forryan, A.; Sinha, B.; New, A. L.; Graham, T.; Andrews, M. B.; Tu, C.-Y.; Lin, S.-J.

2017-02-01

This work investigates the variability of extreme weather events (drought spells, DS15, and daily heavy rainfall, PR99) over East Asia. It particularly focuses on the large scale atmospheric circulation associated with high levels of the occurrence of these extreme events. Two observational datasets (APHRODITE and PERSIANN) are compared with two high-resolution global climate models (HiRAM and HadGEM3-GC2) and an ensemble of other lower resolution climate models from CMIP5. We first evaluate the performance of the high resolution models. They both exhibit good skill in reproducing extreme events, especially when compared with CMIP5 results. Significant differences exist between the two observational datasets, highlighting the difficulty of having a clear estimate of extreme events. The link between the variability of the extremes and the large scale circulation is investigated, on monthly and interannual timescales, using composite and correlation analyses. Both extreme indices DS15 and PR99 are significantly linked to the low level wind intensity over East Asia, i.e. the monsoon circulation. It is also found that DS15 events are strongly linked to the surface temperature over the Siberian region and to the land-sea pressure contrast, while PR99 events are linked to the sea surface temperature anomalies over the West North Pacific. These results illustrate the importance of the monsoon circulation on extremes over East Asia. The dependencies on of the surface temperature over the continent and the sea surface temperature raise the question as to what extent they could affect the occurrence of extremes over tropical regions in future projections.

Evaluation of uncertainty in capturing the spatial variability and magnitudes of extreme hydrological events for the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer

2018-02-01

Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

NASA Astrophysics Data System (ADS)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for better informed decision-making on adaptation strategies. References 1. Coumou, D. & Rahmstorf, S. A decade of extremes. Nature Clim. Change, 2, 491-496 (2012). 2. Rötter, R. P., Carter, T. R., Olesen, J. E. & Porter, J. R. Crop-climate models need an overhaul. Nature Clim. Change, 1, 175-177 (2011). 3. Asseng, S. et al., Uncertainty in simulating wheat yields under climate change. Nature Clim. Change. 10.1038/nclimate1916. (2013). 4. Porter, J.R., & Semenov, M., Crop responses to climatic variation . Trans. R. Soc. B., 360, 2021-2035 (2005). 5. Porter, J.R. & Christensen, S. Deconstructing crop processes and models via identities. Plant, Cell and Environment . doi: 10.1111/pce.12107 (2013). 6. Boogaard, H.L., van Diepen C.A., Rötter R.P., Cabrera J.M. & van Laar H.H. User's guide for the WOFOST 7.1 crop growth simulation model and Control Center 1.5, Alterra, Wageningen, The Netherlands. (1998) 7. Tao, F. & Zhang, Z. Climate change, wheat productivity and water use in the North China Plain: a new super-ensemble-based probabilistic projection. Agric. Forest Meteorol., 170, 146-165. (2013).

Generation of multivariate near shore extreme wave conditions based on an extreme value copula for offshore boundary conditions.

NASA Astrophysics Data System (ADS)

Leyssen, Gert; Mercelis, Peter; De Schoesitter, Philippe; Blanckaert, Joris

2013-04-01

Near shore extreme wave conditions, used as input for numerical wave agitation simulations and for the dimensioning of coastal defense structures, need to be determined at a harbour entrance situated at the French North Sea coast. To obtain significant wave heights, the numerical wave model SWAN has been used. A multivariate approach was used to account for the joint probabilities. Considered variables are: wind velocity and direction, water level and significant offshore wave height and wave period. In a first step a univariate extreme value distribution has been determined for the main variables. By means of a technique based on the mean excess function, an appropriate member of the GPD is selected. An optimal threshold for peak over threshold selection is determined by maximum likelihood optimization. Next, the joint dependency structure for the primary random variables is modeled by an extreme value copula. Eventually the multivariate domain of variables was stratified in different classes, each of which representing a combination of variable quantiles with a joint probability, which are used for model simulation. The main variable is the wind velocity, as in the area of concern extreme wave conditions are wind driven. The analysis is repeated for 9 different wind directions. The secondary variable is water level. In shallow waters extreme waves will be directly affected by water depth. Hence the joint probability of occurrence for water level and wave height is of major importance for design of coastal defense structures. Wind velocity and water levels are only dependent for some wind directions (wind induced setup). Dependent directions are detected using a Kendall and Spearman test and appeared to be those with the longest fetch. For these directions, wind velocity and water level extreme value distributions are multivariately linked through a Gumbel Copula. These distributions are stratified into classes of which the frequency of occurrence can be calculated. For the remaining directions the univariate extreme wind velocity distribution is stratified, each class combined with 5 high water levels. The wave height at the model boundaries was taken into account by a regression with the extreme wind velocity at the offshore location. The regression line and the 95% confidence limits where combined with each class. Eventually the wave period is computed by a new regression with the significant wave height. This way 1103 synthetic events were selected and simulated with the SWAN wave model, each of which a frequency of occurrence is calculated for. Hence near shore significant wave heights are obtained with corresponding frequencies. The statistical distribution of the near shore wave heights is determined by sorting the model results in a descending order and accumulating the corresponding frequencies. This approach allows determination of conditional return periods. For example, for the imposed univariate design return periods of 100 years for significant wave height and 30 years for water level, the joint return period for a simultaneous exceedance of both conditions can be computed as 4000 years. Hence, this methodology allows for a probabilistic design of coastal defense structures.

Influence of Climate Oscillations on Extreme Precipitation in Texas

NASA Astrophysics Data System (ADS)

Bhatia, N.; Singh, V. P.; Srivastav, R. K.

2016-12-01

Much research in the field of hydroclimatology is focusing on the impact of climate variability on hydrologic extremes. Recent studies show that the unique geographical location and the enormous areal extent, coupled with extensive variations in climate oscillations, have intensified the regional hydrologic cycle of Texas. The state-wide extreme precipitation events can actually be attributed to sea-surface pressure and temperature anomalies, such as Bermuda High and Jet Streams, which are further triggered by such climate oscillations. This study aims to quantify the impact of five major Atlantic and Pacific Ocean related climate oscillations: (i) Atlantic Multidecadal Oscillation (AMO), (ii) North Atlantic Oscillation (NAO), (iii) Pacific Decadal Oscillation (PDO), (iv) Pacific North American Pattern (PNA), and (v) Southern Oscillation Index (SOI), on extreme precipitation in Texas. Their respective effects will be determined for both climate divisions delineated by the National Climatic Data Centre (NCDC) and climate regions defined by the Köppen Climate Classification System. This study will adopt a weighted correlation approach to attain the robust correlation coefficients while addressing the regionally variable data outliers for extreme precipitation. Further, the variation of robust correlation coefficients across Texas is found to be related to the station elevation, historical average temperature, and total precipitation in the months of extremes. The research will shed light on the relationship between precipitation extremes and climate variability, thus aiding regional water boards in planning, designing, and managing the respective systems as per the future climate change.

Don't forget about syphilis.

PubMed

Chacon, Anna H

2015-08-01

Syphilis has extremely variable manifestations that produce an extremely broad differential diagnosis. Care must be taken to consider syphilis in dermatologic and other systemic disorders as is relevant.

Observation of Anderson localization in disordered nanophotonic structures

NASA Astrophysics Data System (ADS)

Sheinfux, Hanan Herzig; Lumer, Yaakov; Ankonina, Guy; Genack, Azriel Z.; Bartal, Guy; Segev, Mordechai

2017-06-01

Anderson localization is an interference effect crucial to the understanding of waves in disordered media. However, localization is expected to become negligible when the features of the disordered structure are much smaller than the wavelength. Here we experimentally demonstrate the localization of light in a disordered dielectric multilayer with an average layer thickness of 15 nanometers, deep into the subwavelength regime. We observe strong disorder-induced reflections that show that the interplay of localization and evanescence can lead to a substantial decrease in transmission, or the opposite feature of enhanced transmission. This deep-subwavelength Anderson localization exhibits extreme sensitivity: Varying the thickness of a single layer by 2 nanometers changes the reflection appreciably. This sensitivity, approaching the atomic scale, holds the promise of extreme subwavelength sensing.

AgMIP Regional Activities in a Global Framework: The Brazil Experience

NASA Technical Reports Server (NTRS)

Assad, Eduardo D.; Marin, Fabio R.; Valdivia, Roberto O.; Rosenzweig, Cynthia E.

2012-01-01

Climate variability and change are projected to increate the frequency of extreme high-temperature events, floods, and droughts, which can lead to subsequent changes in soil moister in many locations (Alexandrov and Hoogenboom, 2000). In Brazil, observations reveal a tendency for increasing frequency of extreme rainfall events particularly in south Brazil (Alexander et al., 2006; Carvalho et al., 2014; Groissman et al., 2005), as well as projections for increasing extremes in both maximum and minimum temperatures and high spatial variability for rainfall under the IPCC SRES A2 and B2 scenarios (Marengo et al., 2009).

Continued Analysis of EUVE Solar System Observations

NASA Technical Reports Server (NTRS)

Gladstone, G. Randall

2001-01-01

This is the final report for this project. We proposed to continue our work on extracting important results from the EUVE (Extreme UltraViolet Explorer) archive of lunar and jovian system observations. In particular, we planned to: (1) produce several monochromatic images of the Moon at the wavelengths of the brightest solar EUV emission lines; (2) search for evidence of soft X-ray emissions from the Moon and/or X-ray fluorescence at specific EUV wavelengths; (3) search for localized EUV and soft X-ray emissions associated with each of the Galilean satellites; (4) search for correlations between localized Io Plasma Torus (IPT) brightness and volcanic activity on Io; (5) search for soft X-ray emissions from Jupiter; and (6) determine the long term variability of He 58.4 nm emissions from Jupiter, and relate these to solar variability. However, the ADP review panel suggested that the work concentrate on the Jupiter/IPT observations, and provided half the requested funding. Thus we have performed no work on the first two tasks, and instead concentrated on the last three. In addition we used funds from this project to support reduction and analysis of EUVE observations of Venus. While this was not part of the original statement of work, it is entirely in keeping with extracting important results from EUVE solar system observations.

Mitochondrial genetic variability of Didelphis albiventris (Didelphimorphia, Didelphidae) in Brazilian localities

PubMed Central

Sousa, Luciene C.C.; Gontijo, Célia M.F.; Botelho, Helbert A.; Fonseca, Cleusa G.

2012-01-01

Didelphis albiventris is a well-known and common marsupial. Due to its high adaptability, this very widespread generalist species occurs under various environmental conditions, this even including protected regions and disturbed urban areas. We studied a 653 bp fragment of cytochrome oxidase c (COI) from 93 biological samples from seven Brazilian localities, with linear distances ranging between 58 and about 1800 km to analyze the effects of geographic distances on variability and genetic differentiation. The haplotype network presented nine haplotypes and two genetic clusters compatible with the two most distant geographic areas of the states of Minas Gerais, in the southeast, and Rio Grande do Sul, in the extreme south. As each cluster was characterized by low nucleotide and high haplotype diversities, their populations were obviously composed of closely related haplotypes. Surprisingly, moderate to high FST differentiation values and a very weak phylogeographic signal characterizes interpopulation comparisons within Minas Gerais interdemes, these being correlated with the presence of privative haplotypes. On a large rgeographic scale, a comparison between demes from Minas Gerais and Rio Grande do Sul presented high FST values and a robust phylogeographic pattern. This unexpected scenario implies that mtDNA gene flow was insufficient to maintain population cohesion, reflected by the observed high differentiation. PMID:22888303

Understanding extreme quasar optical variability with CRTS - I. Major AGN flares

NASA Astrophysics Data System (ADS)

Graham, Matthew J.; Djorgovski, S. G.; Drake, Andrew J.; Stern, Daniel; Mahabal, Ashish A.; Glikman, Eilat; Larson, Steve; Christensen, Eric

2017-10-01

There is a large degree of variety in the optical variability of quasars and it is unclear whether this is all attributable to a single (set of) physical mechanism(s). We present the results of a systematic search for major flares in active galactic nucleus (AGN) in the Catalina Real-time Transient Survey as part of a broader study into extreme quasar variability. Such flares are defined in a quantitative manner as being atop of the normal, stochastic variability of quasars. We have identified 51 events from over 900 000 known quasars and high-probability quasar candidates, typically lasting 900 d and with a median peak amplitude of Δm = 1.25 mag. Characterizing the flare profile with a Weibull distribution, we find that nine of the sources are well described by a single-point single-lens model. This supports the proposal by Lawrence et al. that microlensing is a plausible physical mechanism for extreme variability. However, we attribute the majority of our events to explosive stellar-related activity in the accretion disc: superluminous supernovae, tidal disruption events and mergers of stellar mass black holes.

The Great Plains low-level jet in 1.5C and 2C HAPPI simulations: Implications for changes in extreme climate events

NASA Astrophysics Data System (ADS)

Weaver, S. J.; Barcikowska, M. J.

2017-12-01

Global temperature targets have become the cornerstone for global climate policy discussions. Given the goal of the Paris Accord to limit the rise in global mean temperature to well below 2.0oC above pre-industrial levels, and pursue efforts toward the more ambitious 1.5oC goal, there is increasing focus in the climate science community on what the relative changes in regional climate extremes may be for these two scenarios. Despite the successes of major climate science modeling efforts, there is still a significant information gap regarding the regional and seasonal changes in some climate extremes over the U.S. as a function of these global mean temperature targets.During the spring and summer, large amounts of heat and moisture are transported northward into the central and eastern U.S. by the Great Plains Low-Level Jet (GPLLJ) - an atmospheric river which dominates the subcontinental scale climate variability during the warm half of the year. Accordingly, the GPLLJ and its vast spatiotemporal variability is highly influential over several types of extreme climate anomalies east of the Rocky Mountains, including, drought and pluvial events, tornadic activity, and the evolution of central U.S warming hole. Changes in the GPLLJ and its variability are probed from the perspective of several hundred climate realizations afforded by the availability of climate model experiments from the Half a degree additional warming, Prognosis, and Projected Impacts (HAPPI) effort - a suite of multi-model ensemble AMIP simulations forced by 1.5oC and 2oC levels of global warming. The multimodel analysis focuses on the variable magnitude of the seasonal changes in the mean GPLLJ and shifts in the extremes of the prominent modes of GPLLJ variability - both of which have implications for the future shifts in extreme climate events over the Great Plains, Midwest, and southeast regions of the U.S.

Means and extremes: building variability into community-level climate change experiments.

PubMed

Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

2013-06-01

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.

Musculoskeletal MRI findings of juvenile localized scleroderma.

PubMed

Eutsler, Eric P; Horton, Daniel B; Epelman, Monica; Finkel, Terri; Averill, Lauren W

2017-04-01

Juvenile localized scleroderma comprises a group of autoimmune conditions often characterized clinically by an area of skin hardening. In addition to superficial changes in the skin and subcutaneous tissues, juvenile localized scleroderma may involve the deep soft tissues, bones and joints, possibly resulting in functional impairment and pain in addition to cosmetic changes. There is literature documenting the spectrum of findings for deep involvement of localized scleroderma (fascia, muscles, tendons, bones and joints) in adults, but there is limited literature for the condition in children. We aimed to document the spectrum of musculoskeletal magnetic resonance imaging (MRI) findings of both superficial and deep juvenile localized scleroderma involvement in children and to evaluate the utility of various MRI sequences for detecting those findings. Two radiologists retrospectively evaluated 20 MRI studies of the extremities in 14 children with juvenile localized scleroderma. Each imaging sequence was also given a subjective score of 0 (not useful), 1 (somewhat useful) or 2 (most useful for detecting the findings). Deep tissue involvement was detected in 65% of the imaged extremities. Fascial thickening and enhancement were seen in 50% of imaged extremities. Axial T1, axial T1 fat-suppressed (FS) contrast-enhanced and axial fluid-sensitive sequences were rated most useful. Fascial thickening and enhancement were the most commonly encountered deep tissue findings in extremity MRIs of children with juvenile localized scleroderma. Because abnormalities of the skin, subcutaneous tissues and fascia tend to run longitudinally in an affected limb, axial T1, axial fluid-sensitive and axial T1-FS contrast-enhanced sequences should be included in the imaging protocol.

Localized Multi-Model Extremes Metrics for the Fourth National Climate Assessment

NASA Astrophysics Data System (ADS)

Thompson, T. R.; Kunkel, K.; Stevens, L. E.; Easterling, D. R.; Biard, J.; Sun, L.

2017-12-01

We have performed localized analysis of scenario-based datasets for the Fourth National Climate Assessment (NCA4). These datasets include CMIP5-based Localized Constructed Analogs (LOCA) downscaled simulations at daily temporal resolution and 1/16th-degree spatial resolution. Over 45 temperature and precipitation extremes metrics have been processed using LOCA data, including threshold, percentile, and degree-days calculations. The localized analysis calculates trends in the temperature and precipitation extremes metrics for relatively small regions such as counties, metropolitan areas, climate zones, administrative areas, or economic zones. For NCA4, we are currently addressing metropolitan areas as defined by U.S. Census Bureau Metropolitan Statistical Areas. Such localized analysis provides essential information for adaptation planning at scales relevant to local planning agencies and businesses. Nearly 30 such regions have been analyzed to date. Each locale is defined by a closed polygon that is used to extract LOCA-based extremes metrics specific to the area. For each metric, single-model data at each LOCA grid location are first averaged over several 30-year historical and future periods. Then, for each metric, the spatial average across the region is calculated using model weights based on both model independence and reproducibility of current climate conditions. The range of single-model results is also captured on the same localized basis, and then combined with the weighted ensemble average for each region and each metric. For example, Boston-area cooling degree days and maximum daily temperature is shown below for RCP8.5 (red) and RCP4.5 (blue) scenarios. We also discuss inter-regional comparison of these metrics, as well as their relevance to risk analysis for adaptation planning.

Assessing the impact of local meteorological variables on surface ozone in Hong Kong during 2000-2015 using quantile and multiple line regression models

NASA Astrophysics Data System (ADS)

Zhao, Wei; Fan, Shaojia; Guo, Hai; Gao, Bo; Sun, Jiaren; Chen, Laiguo

2016-11-01

The quantile regression (QR) method has been increasingly introduced to atmospheric environmental studies to explore the non-linear relationship between local meteorological conditions and ozone mixing ratios. In this study, we applied QR for the first time, together with multiple linear regression (MLR), to analyze the dominant meteorological parameters influencing the mean, 10th percentile, 90th percentile and 99th percentile of maximum daily 8-h average (MDA8) ozone concentrations in 2000-2015 in Hong Kong. The dominance analysis (DA) was used to assess the relative importance of meteorological variables in the regression models. Results showed that the MLR models worked better at suburban and rural sites than at urban sites, and worked better in winter than in summer. QR models performed better in summer for 99th and 90th percentiles and performed better in autumn and winter for 10th percentile. And QR models also performed better in suburban and rural areas for 10th percentile. The top 3 dominant variables associated with MDA8 ozone concentrations, changing with seasons and regions, were frequently associated with the six meteorological parameters: boundary layer height, humidity, wind direction, surface solar radiation, total cloud cover and sea level pressure. Temperature rarely became a significant variable in any season, which could partly explain the peak of monthly average ozone concentrations in October in Hong Kong. And we found the effect of solar radiation would be enhanced during extremely ozone pollution episodes (i.e., the 99th percentile). Finally, meteorological effects on MDA8 ozone had no significant changes before and after the 2010 Asian Games.

Adaptive data-driven models for estimating carbon fluxes in the Northern Great Plains

USGS Publications Warehouse

Wylie, B.K.; Fosnight, E.A.; Gilmanov, T.G.; Frank, A.B.; Morgan, J.A.; Haferkamp, Marshall R.; Meyers, T.P.

2007-01-01

Rangeland carbon fluxes are highly variable in both space and time. Given the expansive areas of rangelands, how rangelands respond to climatic variation, management, and soil potential is important to understanding carbon dynamics. Rangeland carbon fluxes associated with Net Ecosystem Exchange (NEE) were measured from multiple year data sets at five flux tower locations in the Northern Great Plains. These flux tower measurements were combined with 1-km2 spatial data sets of Photosynthetically Active Radiation (PAR), Normalized Difference Vegetation Index (NDVI), temperature, precipitation, seasonal NDVI metrics, and soil characteristics. Flux tower measurements were used to train and select variables for a rule-based piece-wise regression model. The accuracy and stability of the model were assessed through random cross-validation and cross-validation by site and year. Estimates of NEE were produced for each 10-day period during each growing season from 1998 to 2001. Growing season carbon flux estimates were combined with winter flux estimates to derive and map annual estimates of NEE. The rule-based piece-wise regression model is a dynamic, adaptive model that captures the relationships of the spatial data to NEE as conditions evolve throughout the growing season. The carbon dynamics in the Northern Great Plains proved to be in near equilibrium, serving as a small carbon sink in 1999 and as a small carbon source in 1998, 2000, and 2001. Patterns of carbon sinks and sources are very complex, with the carbon dynamics tilting toward sources in the drier west and toward sinks in the east and near the mountains in the extreme west. Significant local variability exists, which initial investigations suggest are likely related to local climate variability, soil properties, and management.

Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

PubMed

Kara, Fatih; Yucel, Ismail

2015-09-01

This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.

The Challenges from Extreme Climate Events for Sustainable Development in Amazonia: the Acre State Experience

NASA Astrophysics Data System (ADS)

Araújo, M. D. N. M.

2015-12-01

In the past ten years Acre State, located in Brazil´s southwestern Amazonia, has confronted sequential and severe extreme events in the form of droughts and floods. In particular, the droughts and forest fires of 2005 and 2010, the 2012 flood within Acre, the 2014 flood of the Madeira River which isolated Acre for two months from southern Brazil, and the most severe flooding throughout the state in 2015 shook the resilience of Acrean society. The accumulated costs of these events since 2005 have exceeded 300 million dollars. For the last 17 years, successive state administrations have been implementing a socio-environmental model of development that strives to link sustainable economic production with environmental conservation, particularly for small communities. In this context, extreme climate events have interfered significantly with this model, increasing the risks of failure. The impacts caused by these events on development in the state have been exacerbated by: a) limitations in monitoring; b) extreme events outside of Acre territory (Madeira River Flood) affecting transportation systems; c) absence of reliable information for decision-making; and d) bureaucratic and judicial impediments. Our experience in these events have led to the following needs for scientific input to reduce the risk of disasters: 1) better monitoring and forecasting of deforestation, fires, and hydro-meteorological variables; 2) ways to increase risk perception in communities; 3) approaches to involve more effectively local and regional populations in the response to disasters; 4) more accurate measurements of the economic and social damages caused by these disasters. We must improve adaptation to and mitigation of current and future extreme climate events and implement a robust civil defense, adequate to these new challenges.

How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?

DOE PAGES

Hagos, Samson; Ruby Leung, L.; Zhao, Chun; ...

2018-02-10

Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less

How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson; Ruby Leung, L.; Zhao, Chun

Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less

[Soft tissue sarcoma of the upper extremities. Analysis of factors relevant for prognosis in 160 patients].

PubMed

Lehnhardt, M; Hirche, C; Daigeler, A; Goertz, O; Ring, A; Hirsch, T; Drücke, D; Hauser, J; Steinau, H U

2012-02-01

Soft tissue sarcomas (STS) are a rare entity with reduced prognosis due to their aggressive biology. For an optimal treatment of STS identification of independent prognostic factors is crucial in order to reduce tumor-related mortality and recurrence rates. The surgical oncological concept includes wide excisions with resection safety margins >1 cm which enables acceptable functional results and reduced rates of amputation of the lower extremities. In contrast, individual anatomy of the upper extremities, in particular of the hand, leads to an intentional reduction of resection margins in order to preserve the extremity and its function with the main intention of tumor-free resection margins. In this study, the oncological safety and outcome as well as functional results were validated by a retrospective analysis of survival rate, recurrence rate and potential prognostic factors. A total of 160 patients who had been treated for STS of the upper extremities were retrospectively included. Independent prognostic factors were analyzed (primary versus recurrent tumor, tumor size, resection status, grade of malignancy, additional therapy, localization in the upper extremity). Kaplan-Meier analyses for survival rate and local control were calculated. Further outcome measures were functional results validated by the DASH score and rate of amputation. In 130 patients (81%) wide tumor excision (R0) was performed and in 19 patients (12%) an amputation was necessary. The 5-year overall survival rate was 70% and the 5-year survival rate in primary tumors was 81% whereas in recurrences 55% relapsed locally. The 10-year overall survival rate was 45% and the 5-year recurrence rate was 18% for primary STS and 43% for recurrent STS. Variance analysis revealed primary versus recurrent tumor, tumor size, resection status and grade of malignancy as independent prognostic factors. Analysis of functional results showed a median DASH score of 37 (0-100; 0=contralateral extremity). The 5-year survival and local recurrence rates are comparable to STS wide resections with safety margins >1 cm for the lower extremities and the trunk. Analysis of prognostic factors revealed resection status and the tumor-free resection margins to be the main goals in STS resection of upper extremity.

Making Energy-Water Nexus Scenarios more Fit-for-Purpose through Better Characterization of Extremes

NASA Astrophysics Data System (ADS)

Yetman, G.; Levy, M. A.; Chen, R. S.; Schnarr, E.

2017-12-01

Often quantitative scenarios of future trends exhibit less variability than the historic data upon which the models that generate them are based. The problem of dampened variability, which typically also entails dampened extremes, manifests both temporally and spatially. As a result, risk assessments that rely on such scenarios are in danger of producing misleading results. This danger is pronounced in nexus issues, because of the multiple dimensions of change that are relevant. We illustrate the above problem by developing alternative joint distributions of the probability of drought and of human population totals, across U.S. counties over the period 2010-2030. For the dampened-extremes case we use drought frequencies derived from climate models used in the U.S. National Climate Assessment and the Environmental Protection Agency's population and land use projections contained in its Integrated Climate and Land Use Scenarios (ICLUS). For the elevated extremes case we use an alternative spatial drought frequency estimate based on tree-ring data, covering a 555-year period (Ho et al 2017); and we introduce greater temporal and spatial extremes in the ICLUS socioeconomic projections so that they conform to observed extremes in the historical U.S. spatial census data 1790-present (National Historical Geographic Information System). We use spatial and temporal coincidence of high population and extreme drought as a proxy for energy-water nexus risk. We compare the representation of risk in the dampened-extreme and elevated-extreme scenario analysis. We identify areas of the country where using more realistic portrayals of extremes makes the biggest difference in estimate risk and suggest implications for future risk assessments. References: Michelle Ho, Upmanu Lall, Xun Sun, Edward R. Cook. 2017. Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow. Water Resources Research. . doi: 10.1002/2016WR019632

Min and Max Exponential Extreme Interval Values and Statistics

ERIC Educational Resources Information Center

Jance, Marsha; Thomopoulos, Nick

2009-01-01

The extreme interval values and statistics (expected value, median, mode, standard deviation, and coefficient of variation) for the smallest (min) and largest (max) values of exponentially distributed variables with parameter ? = 1 are examined for different observation (sample) sizes. An extreme interval value g[subscript a] is defined as a…

Climate network analysis of regional precipitation extremes: The true story told by event synchronization

NASA Astrophysics Data System (ADS)

Odenweller, Adrian; Donner, Reik V.

2017-04-01

Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two events to be considered potentially related. Both measures are then used to generate climate networks from parts of the satellite-based TRMM precipitation data set at daily resolution covering the Indian and East Asian monsoon domains, respectively, thereby reanalysing previously published results. The obtained spatial patterns of degree densities and local clustering coefficients exhibit marked differences between both similarity measures. Specifically, we demonstrate that there exists a strong relationship between the fraction of extremes occurring at subsequent days and the degree density in the event synchronization based networks, suggesting that the spatial patterns obtained using this approach are strongly affected by the presence of serial dependencies between events. Given that a manual selection of the maximally tolerable delay between two events can be guided by a priori climatological knowledge and even used for systematic testing of different hypotheses on climatic processes underlying the emergence of spatio-temporal patterns of extreme precipitation, our results provide evidence that event coincidence rates are a more appropriate statistical characteristic for similarity assessment and network construction for climate extremes, while results based on event synchronization need to be interpreted with great caution.

Adapting to extreme events related to natural variability and climate change: the imperative of coupling technology with strong regulation and governance.

PubMed

Kythreotis, A P; Mercer, T G; Frostick, L E

2013-09-03

In recent years there has been an increase in extreme events related to natural variability (such as earthquakes, tsunamis and hurricanes) and climate change (such as flooding and more extreme weather). Developing innovative technologies is crucial in making society more resilient to such events. However, little emphasis has been placed on the role of human decision-making in maximizing the positive impacts of technological developments. This is exacerbated by the lack of appropriate adaptation options and the privatization of existing infrastructure, which can leave people exposed to increasing risk. This work examines the need for more robust government regulation and legislation to complement developments and innovations in technology in order to protect communities against such extreme events.

Large-scale drivers of local precipitation extremes in convection-permitting climate simulations

NASA Astrophysics Data System (ADS)

Chan, Steven C.; Kendon, Elizabeth J.; Roberts, Nigel M.; Fowler, Hayley J.; Blenkinsop, Stephen

2016-04-01

The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.

Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes remote SST anomalies.

Patterns of amino acid conservation in human and animal immunodeficiency viruses.

PubMed

Voitenko, Olga S; Dhroso, Andi; Feldmann, Anna; Korkin, Dmitry; Kalinina, Olga V

2016-09-01

Due to their high genomic variability, RNA viruses and retroviruses present a unique opportunity for detailed study of molecular evolution. Lentiviruses, with HIV being a notable example, are one of the best studied viral groups: hundreds of thousands of sequences are available together with experimentally resolved three-dimensional structures for most viral proteins. In this work, we use these data to study specific patterns of evolution of the viral proteins, and their relationship to protein interactions and immunogenicity. We propose a method for identification of two types of surface residues clusters with abnormal conservation: extremely conserved and extremely variable clusters. We identify them on the surface of proteins from HIV and other animal immunodeficiency viruses. Both types of clusters are overrepresented on the interaction interfaces of viral proteins with other proteins, nucleic acids or low molecular-weight ligands, both in the viral particle and between the virus and its host. In the immunodeficiency viruses, the interaction interfaces are not more conserved than the corresponding proteins on an average, and we show that extremely conserved clusters coincide with protein-protein interaction hotspots, predicted as the residues with the largest energetic contribution to the interaction. Extremely variable clusters have been identified here for the first time. In the HIV-1 envelope protein gp120, they overlap with known antigenic sites. These antigenic sites also contain many residues from extremely conserved clusters, hence representing a unique interacting interface enriched both in extremely conserved and in extremely variable clusters of residues. This observation may have important implication for antiretroviral vaccine development. A Python package is available at https://bioinf.mpi-inf.mpg.de/publications/viral-ppi-pred/ voitenko@mpi-inf.mpg.de or kalinina@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Completely preserved cockroaches of the family Mesoblattinidae from the Upper Jurassic-Lower Cretaceous Yixian Formation (Liaoning Province, NE China)

NASA Astrophysics Data System (ADS)

Wei, Dandan; Ren, Dong

2013-08-01

Although cockroaches were the dominant insects in various Paleozoic and Mesozoic insect assemblages, their general morphology was extremely conservative. One of the most common of them, the Jurassic-Cretaceous family Mesoblattinidae, is described here for the first time on the basis of completely preserved specimens. Ninety-two specimens of Perlucipecta aurea gen. et sp. n. reveal details of head, mandible, male tergal glands and terminal hook; cercal, leg and antennal sensilla. Its congener, P. vrsanskyi is described from the same sediments of the Yixian Formation (Upper Jurassic-Lower Cretaceous). The forewing venation variability of P. aurea, analysed for the first time in this family is nearly identical (CV = 6.23 %) with variability of two species of family Blattulidae that occur at the same locality (CV = 6.22 %; 5.72 %). The transitional nature of morphological characters represented by asymmetry between left and right wings (simple/branched forewing SC and hind wing M) in P. aurea documents the phylogenetic relation between the families Mesoblattinidae and Ectobiidae

Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

NASA Astrophysics Data System (ADS)

Walz, M. A.; Donat, M.; Leckebusch, G. C.

2017-12-01

As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adesso, Gerardo; CNR-INFM Coherentia, Naples; CNISM, Unita di Salerno, Salerno

2007-10-15

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1xM bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself andmore » the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a, uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes.« less

Identifying Population Vulnerable to Extreme Heat Events in San Jose, California.

NASA Astrophysics Data System (ADS)

Rivera, A. L.

2016-12-01

The extreme heat days not only make cities less comfortable for living but also they are associated with increased morbidity and mortality. Mapping studies have demonstrated spatial variability in heat vulnerability. A study conducted between 2000 and 2011 in New York City shows that deaths during heat waves was more likely to occur in black individuals, at home in census tracts which received greater public assistance. This map project intends to portray areas in San Jose California that are vulnerable to extreme heat events. The variables considered to build a vulnerability index are: land surface temperature, vegetated areas (NDVI), and people exposed to these area (population density).

Linking storm surge activity and circulation variability along the Spanish coast through a synoptic pattern classification

NASA Astrophysics Data System (ADS)

Rasilla Álvarez, Domingo; Garcia Codrón, Juan Carlos

2010-05-01

The potentially negative consequences resulting from the estimations of global sea level rising along the current century are a matter of serious concern in many coastal areas worldwide. Most of the negative consequences of the sea level variability, such as flooding or erosion, are linked to episodic events of strong atmospheric forcing represented by deep atmospheric disturbances, especially if they combine with extreme astronomical high tides. Moreover, the interaction between the prevailing flows during such events and the actual orientation of the coast line might accelerate or mitigate such impacts. This contribution analyses sea surge variations measured at five tide-gauge stations located around the Iberian Peninsula and their relationships with regional scale circulation patterns with local-scale winds. Its aim is to improve the knowledge of surge related-coastal-risks by analysing the relationship between surges and their atmospheric forcing factors at different spatial scales. The oceanographic data set consists of hourly data from 5 tide gauge stations (Santander, Vigo, Bonanza, Málaga, Valencia and Barcelona) disseminated along the Spanish coastline, provided by Puertos del Estado. To explore the atmospheric mechanisms responsible for the sign and magnitude of sea surges, a regional Eulerian approach (a synoptic typing) were combined with a larger-scale Lagrangian method, based on the analysis of storm-tracks over the Atlantic and local information (synop reports) obtained from the closest meteorological stations to the tide gauges. The synoptic catalogue was obtained following a procedure that combines Principal Component Analysis (PCA) for reduction purposes and clustering (Ward plus K-means) to define the circulation types. Sea level pressure, surface 10m U and V wind components gridded data were obtained from NCEP Reanalysis, while storm tracks and cyclone statistics were extracted from the CDC Map Room Climate Products Storm Track Data (http://www.cdc.noaa.gov/map/clim/st_data.html). The second task was to evaluate the performance of each circulation type on the spatial patterns of a daily fire danger risk index (Canadian Fire Weather Index, FWI). Finally, anomaly maps of several surface and low level climate variables, corresponding to the dates of ignition of the very large forest fires within each synoptic pattern, were calculated to provide insight of the specific conditions associated to those extreme events. A principal component analysis upon 6 hourly residuals highlighted the homogeneous behaviour of the tide gauges and provided a regional quantitative index to identify the largest storm surges. The leading PCA displayed a homogeneous spatial pattern, describing the low frequency variability along the entire coast, in spite of different orientations of the coast, accounting for more than 80% of the total variability. The second PCA displayed opposite phases between the Atlantic and the Mediterranean. Furthermore, the results suggest that surges are a regional rather than local phenomenon, probably related to the same single physical forcing. The comparison between extreme surge events and circulation patterns highlighted that single physical mechanism is represented by extratropical cyclonic disturbances located at the north-western corner of the Iberian Peninsula, responsible for an environment characterized by low pressure readings and westerly-southwesterly winds. That wind pattern acquires an onshore component in the Atlantic coast, but becomes offshore in the Mediterranean. So, the main mechanism responsible for those storm surges is the inverse barometer effect, being the wind dragging secondary. The main physical forcing of the storm surges, the extratropical cyclones, have experience a reduction of this frequency and a marked reduction in their strength since 1950, replaced by stable circulations. Both conditions suggest a long term reduction of the frequency and the magnitude of storm surges.

Dryland ecosystem responses to precipitation extremes and wildfire at a long-term rainfall manipulation experiment

NASA Astrophysics Data System (ADS)

Brown, R. F.; Collins, S. L.

2017-12-01

Climate is becoming increasingly more variable due to global environmental change, which is evidenced by fewer, but more extreme precipitation events, changes in precipitation seasonality, and longer, higher severity droughts. These changes, combined with a rising incidence of wildfire, have the potential to strongly impact net primary production (NPP) and key biogeochemical cycles, particularly in dryland ecosystems where NPP is sequentially limited by water and nutrient availability. Here we utilize a ten-year dataset from an ongoing long-term field experiment established in 2007 in which we experimentally altered monsoon rainfall variability to examine how our manipulations, along with naturally occurring events, affect NPP and associated biogeochemical cycles in a semi-arid grassland in central New Mexico, USA. Using long-term regional averages, we identified extremely wet monsoon years (242.8 mm, 2013), and extremely dry monsoon years (86.0 mm, 2011; 80.0 mm, 2015) and water years (117.0 mm, 2011). We examined how changes in precipitation variability and extreme events affected ecosystem processes and function particularly in the context of ecosystem recovery following a 2009 wildfire. Response variables included above- and below-ground plant biomass (ANPP & BNPP) and abundance, soil nitrogen availability, and soil CO2 efflux. Mean ANPP ranged from 3.6 g m-2 in 2011 to 254.5 g m-2 in 2013, while BNPP ranged from 23.5 g m-2 in 2015 to 194.2 g m-2 in 2013, demonstrating NPP in our semi-arid grassland is directly linked to extremes in both seasonal and annual precipitation. We also show increased nitrogen deposition positively affects NPP in unburned grassland, but has no significant impact on NPP post-fire except during extremely wet monsoon years. While soil respiration rates reflect lower ANPP post-fire, patterns in CO2 efflux have not been shown to change significantly in that efflux is greatest following large precipitation events preceded by longer drying periods. Current land surface models poorly represent dryland ecosystems, which frequently undergo extreme weather events. Our long-term experiment provides key insights into ecosystem processes and function, thereby providing capacity for model improvement particularly in the context of future environmental change.

Climate extremes in Malaysia and the equatorial South China Sea

NASA Astrophysics Data System (ADS)

Salahuddin, Ahmed; Curtis, Scott

2011-08-01

The southern extent of the South China Sea (SCS) is an important natural resource epicenter for Malaysia which experiences climate extremes. This paper documents the variability of extremes in the equatorial SCS through selected ground-based observations of precipitation in Malaysia and ship-based observations of wind data in the Maritime Continent region, to elucidate the interrelationship between precipitation variability over Malaysia and wind variability over the ocean. The data have been carefully inspected and analyzed, and related to the real-time multivariate Madden-Julian Oscillation (MJO) time series. The analysis suggests that the northeast or boreal winter monsoon dominates extreme rainfall in eastern Malaysian cities. Further, the west coast of Peninsular Malaysia and Borneo Malaysia are affected by the MJO differently than the east coast of Peninsular Malaysia. From the wind analysis we found that average zonal wind is westerly from May to September and easterly from November to April. When the active (convective) phase of the MJO is centered over the Maritime Continent, the strong westerly wind bursts are more frequent in the South China Sea. While more investigation is needed, these results suggest that the status of the Madden-Julian Oscillation can be used to help forecast climate extremes in areas of Malaysia.

Timing of floods in southeastern China: Seasonal properties and potential causes

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Gu, Xihui; Singh, Vijay P.; Shi, Peijun; Luo, Ming

2017-09-01

Flood hazards and flood risks in southeastern China have been causing increasing concerns due to dense population and highly-developed economy. This study attempted to address changes of seasonality, timing of peak floods and variability of occurrence date of peak floods using circular statistical methods and the modified Mann-Kendall trend detection method. The causes of peak flood changes were also investigated. Results indicated that: (1) floods were subject to more seasonality and temporal clustering when compared to precipitation extremes. However, seasonality of floods and extreme precipitation was subject to spatial heterogeneity in northern Guangdong. Similar changing patterns of peak floods and extreme precipitation were found in coastal regions; (2) significant increasing/decreasing seasonality, but no confirmed spatial patterns, were observed for peak floods and extreme precipitation. Peak floods in northern Guangdong province had decreasing variability, but had larger variability in coastal regions; (3) tropical cyclones had remarkable impacts on extreme precipitation changes in coastal regions of southeastern China, and peak floods as well. The landfalling of tropical cyclones was decreasing and concentrated during June-September; this is the major reason for earlier but enhanced seasonality of peak floods in coastal regions. This study sheds new light on flood behavior in coastal regions in a changing environment.

Variability and Extremes of Precipitation in the Global Climate as Determined by the 25-Year GEWEX/GPCP Data Set

NASA Technical Reports Server (NTRS)

Adler, R. F.; Gu, G.; Curtis, S.; Huffman, G. J.; Bolvin, D. T.; Nelkin, E. J.

2005-01-01

The Global Precipitation Climatology Project (GPCP) 25-year precipitation data set is used to evaluate the variability and extremes on global and regional scales. The variability of precipitation year-to-year is evaluated in relation to the overall lack of a significant global trend and to climate events such as ENSO and volcanic eruptions. The validity of conclusions and limitations of the data set are checked by comparison with independent data sets (e.g., TRMM). The GPCP data set necessarily has a heterogeneous time series of input data sources, so part of the assessment described above is to test the initial results for potential influence by major data boundaries in the record. Regional trends, or inter-decadal changes, are also analyzed to determine validity and correlation with other long-term data sets related to the hydrological cycle (e.g., clouds and ocean surface fluxes). Statistics of extremes (both wet and dry) are analyzed at the monthly time scale for the 25 years. A preliminary result of increasing frequency of extreme monthly values will be a focus to determine validity. Daily values for an eight-year are also examined for variation in extremes and compared to the longer monthly-based study.

Combination of a total free forearm flap and a sensate local flap for preservation of the shoulder girdle in massive, nonreplantable upper extremity injuries.

PubMed

Jakubietz, Rafael G; Jakubietz, Michael G; Kloss, Danni F; Gruenert, Joerg G

2009-02-01

After massive upper extremity injuries, prosthetic use might be complicated by the formation of pressure ulcerations. Especially the coverage with insensate free flaps may predispose the patient for developing chronic ulcerations when using an upper extremity prosthesis. This complication may be reduced when sensate local flaps are used to cover bony prominences. A new operative technique is described. Immediate sensate soft tissue coverage improves prosthetic fitting. Successful manipulation of the prosthesis can be quickly achieved with a decreased risk for pressure ulceration. This challenging procedure helps to achieve durable and sensate coverage of bony prominences. The use of local sensate tissue to cover bony prominences reduces the risk for pressure ulceration when wearing a prosthesis. Areas where prosthetic use causes only low pressure and shearing forces are adequately covered with free flaps. Immediate sensibility of local flaps allows prosthetic fitting and use as soon as wound healing has occurred. Return to work is thus expedited.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

PubMed

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Whole-body heating decreases skin vascular response to low orthostatic stress in the lower extremities.

PubMed

Yamazaki, Fumio; Nakayama, Yoshiro; Sone, Ryoko

2006-04-01

To elucidate the influence of heat stress on cutaneous vascular response in the lower extremities during orthostatic stress, a head-up tilt (HUT) test at angles of 15 degrees, 30 degrees, 45 degrees, and 60 degrees for 4 min each was conducted under normothermic control conditions followed by whole-body heat stress produced by a hot water-perfused suit in healthy volunteers. Skin blood flows (SkBF) in the forearm, thigh, and calf were monitored using laser-Doppler flowmetry throughout the experiment. Furthermore, to elucidate the effects of increased core and local skin temperatures on the local vascular response in calf skin under increasing orthostatic stress, the thigh was occluded at 20, 30, 50, 70, and 80 mmHg with a cuff in both the normothermic condition and the whole-body or local heating condition. Significant decreases in forearm SkBF during HUT were observed at an angle of 60 degrees during normothermia and at 30 degrees or more during heating. SkBF in the thigh and calf was decreased significantly by HUT at 15 degrees and above during normothermia, and there was no significant reduction of SkBF in these sites during HUT at the lower angles (15 degrees -45 degrees ) during whole-body heating. Significant decreases of calf SkBF were observed at cuff pressures of 20 mmHg and above during normothermia and of 30 mmHg and above during whole-body and local heating, respectively. These results suggest that SkBF in the lower extremities shows a marked reduction compared with the upper extremities during low orthostatic stress in normothermia, and the enhanced skin vasoconstrictor response in the lower extremities is diminished by both whole-body and local heat stress.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events

PubMed Central

Vincenzi, Simone

2014-01-01

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an ‘extinction window’ of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the ‘extinction window’, although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. PMID:24920116

Characterization of extreme sea level at the European coast

NASA Astrophysics Data System (ADS)

Elizalde, Alberto; Jorda, Gabriel; Mathis, Moritz; Mikolajewicz, Uwe

2015-04-01

Extreme high sea levels arise as a combination of storm surges and particular high tides events. Future climate simulations not only project changes in the atmospheric circulation, which induces changes in the wind conditions, but also an increase in the global mean sea level by thermal expansion and ice melting. Such changes increase the risk of coastal flooding, which represents a possible hazard for human activities. Therefore, it is important to investigate the pattern of sea level variability and long-term trends at coastal areas. In order to analyze further extreme sea level events at the European coast in the future climate projections, a new setup for the global ocean model MPIOM coupled with the regional atmosphere model REMO is prepared. The MPIOM irregular grid has enhanced resolution in the European region to resolve the North and the Mediterranean Seas (up to 11 x 11 km at the North Sea). The ocean model includes as well the full luni-solar ephemeridic tidal potential for tides simulation. To simulate the air-sea interaction, the regional atmospheric model REMO is interactively coupled to the ocean model over Europe. Such region corresponds to the EuroCORDEX domain with a 50 x 50 km resolution. Besides the standard fluxes of heat, mass (freshwater), momentum and turbulent energy input, the ocean model is also forced with sea level pressure, in order to be able to capture the full variation of sea level. The hydrological budget within the study domain is closed using a hydrological discharge model. With this model, simulations for present climate and future climate scenarios are carried out to study transient changes on the sea level and extreme events. As a first step, two simulations (coupled and uncoupled ocean) driven by reanalysis data (ERA40) have been conducted. They are used as reference runs to evaluate the climate projection simulations. For selected locations at the coast side, time series of sea level are separated on its different components: tides, short time atmospheric process influence (1-30 days), seasonal cycle and interannual variability. Every sea level component is statistically compared with data from local tide gauges.

Current and future pluvial flood hazard analysis for the city of Antwerp

NASA Astrophysics Data System (ADS)

Willems, Patrick; Tabari, Hossein; De Niel, Jan; Van Uytven, Els; Lambrechts, Griet; Wellens, Geert

2016-04-01

For the city of Antwerp in Belgium, higher rainfall extremes were observed in comparison with surrounding areas. The differences were found statistically significant for some areas and may be the result of the heat island effect in combination with the higher concentrations of aerosols. A network of 19 rain gauges but with varying records length (the longest since the 1960s) and continuous radar data for 10 years were combined to map the spatial variability of rainfall extremes over the city at various durations from 15 minutes to 1 day together with the uncertainty. The improved spatial rainfall information was used as input in the sewer system model of the city to analyze the frequency of urban pluvial floods. Comparison with historical flood observations from various sources (fire brigade and media) confirmed that the improved spatial rainfall information also improved sewer impact results on both the magnitude and frequency of the sewer floods. Next to these improved urban flood impact results for recent and current climatological conditions, the new insights on the local rainfall microclimate were also helpful to enhance future projections on rainfall extremes and pluvial floods in the city. This was done by improved statistical downscaling of all available CMIP5 global climate model runs (160 runs) for the 4 RCP scenarios, as well as the available EURO-CORDEX regional climate model runs. Two types of statistical downscaling methods were applied for that purpose (a weather typing based method, and a quantile perturbation approach), making use of the microclimate results and its dependency on specific weather types. Changes in extreme rainfall intensities were analyzed and mapped as a function of the RCP scenario, together with the uncertainty, decomposed in the uncertainties related to the climate models, the climate model initialization or limited length of the 30-year time series (natural climate variability) and the statistical downscaling (albeit limited to two types of methods). These were finally transferred into future pluvial flash flood hazard maps for the city together with the uncertainties, and are considered as basis for spatial planning and adaptation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghosh, Subimal; Das, Debasish; Kao, Shih-Chieh

Recent studies disagree on how rainfall extremes over India have changed in space and time over the past half century, as well as on whether the changes observed are due to global warming or regional urbanization. Although a uniform and consistent decrease in moderate rainfall has been reported, a lack of agreement about trends in heavy rainfall may be due in part to differences in the characterization and spatial averaging of extremes. Here we use extreme value theory to examine trends in Indian rainfall over the past half century in the context of long-term, low-frequency variability.We show that when generalizedmore » extreme value theory is applied to annual maximum rainfall over India, no statistically significant spatially uniform trends are observed, in agreement with previous studies using different approaches. Furthermore, our space time regression analysis of the return levels points to increasing spatial variability of rainfall extremes over India. Our findings highlight the need for systematic examination of global versus regional drivers of trends in Indian rainfall extremes, and may help to inform flood hazard preparedness and water resource management in the region.« less

Temporal and spatial characteristics of extreme precipitation events in the Midwest of Jilin Province based on multifractal detrended fluctuation analysis method and copula functions

NASA Astrophysics Data System (ADS)

Guo, Enliang; Zhang, Jiquan; Si, Ha; Dong, Zhenhua; Cao, Tiehua; Lan, Wu

2017-10-01

Environmental changes have brought about significant changes and challenges to water resources and management in the world; these include increasing climate variability, land use change, intensive agriculture, and rapid urbanization and industrial development, especially much more frequency extreme precipitation events. All of which greatly affect water resource and the development of social economy. In this study, we take extreme precipitation events in the Midwest of Jilin Province as an example; daily precipitation data during 1960-2014 are used. The threshold of extreme precipitation events is defined by multifractal detrended fluctuation analysis (MF-DFA) method. Extreme precipitation (EP), extreme precipitation ratio (EPR), and intensity of extreme precipitation (EPI) are selected as the extreme precipitation indicators, and then the Kolmogorov-Smirnov (K-S) test is employed to determine the optimal probability distribution function of extreme precipitation indicators. On this basis, copulas connect nonparametric estimation method and the Akaike Information Criterion (AIC) method is adopted to determine the bivariate copula function. Finally, we analyze the characteristics of single variable extremum and bivariate joint probability distribution of the extreme precipitation events. The results show that the threshold of extreme precipitation events in semi-arid areas is far less than that in subhumid areas. The extreme precipitation frequency shows a significant decline while the extreme precipitation intensity shows a trend of growth; there are significant differences in spatiotemporal of extreme precipitation events. The spatial variation trend of the joint return period gets shorter from the west to the east. The spatial distribution of co-occurrence return period takes on contrary changes and it is longer than the joint return period.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Relationships between interdecadal variability and extreme precipitation events in South America during the monsoon season

NASA Astrophysics Data System (ADS)

Grimm, Alice; Laureanti, Nicole; Rodakoviski, Rodrigo

2016-04-01

This study aims to clarify the impact of interdecadal climate oscillations (periods of 8 years and longer) on the frequency of extreme precipitation events over South America in the monsoon season (austral spring and summer), and determine the influence of these oscillations on the daily precipitation frequency distribution. Interdecadal variability modes of precipitation during the monsoon season are provided by a continental-scale rotated empirical orthogonal function analysis for the 60 years period 1950-2009. The main disclosed modes are robust, since they are reproduced for different periods. They can produce differences around 50% in monthly precipitation between opposite phases. Oceanic and atmospheric anomalous fields associated with these modes indicate that they have physical basis. The first modes in spring and summer display highest correlation with the Interdecadal Pacific Oscillation (IPO) SST mode, while the second modes have strongest correlation with the Atlantic Multidecadal Oscillation (AMO) SST mode. However, there are also other influences on these modes. As the most dramatic consequences of climate variability stem from its influence on the frequency of extreme precipitation events, it is important to also assess this influence, since variations in monthly or seasonal precipitation do not necessarily imply significant alterations in their extreme events. This study seeks to answer the questions: i) Do opposite phases of the main interdecadal modes of seasonal precipitation produce significant anomalies in the frequency of extreme events? ii) Does the interdecadal variability of the frequency of extreme events show similar spatial and temporal structure as the interdecadal variability of the seasonal precipitation? iii) Does the interdecadal variability change the daily precipitation probability distribution between opposite phases? iv) In this case, which ranges of daily precipitation are most affected? The significant anomalies of the extreme events frequency in opposite phases of the interdecadal oscillations display spatial patterns very similar to those of the corresponding modes. In addition, the modes of extreme events frequency bear similarity to the modes of seasonal precipitation, although a complete assessment of this similarity is not possible with the daily data available. The Kolmogorov-Smirnov test is applied to the daily precipitation series for positive and negative phases of the interdecadal modes, in regions with high factor loadings. It shows, with significance level better than 0.01, that daily precipitation from opposite phases pertains to different frequency distributions. Further analyses disclose clearly that there is much greater relative impact of the interdecadal oscillations on the extreme ranges of daily rainfall than in the ranges of moderate and light rainfall. This impact is more linear is spring than in summer. Acknowledgments: This work was supported by: Inter-American Institute for Global Change Research (IAI) CRN3035 which is supported by the US National Science Foundation (Grant GEO-1128040), European Community's Seventh Framework Programme under Grant Agreement n° 212492 (CLARIS LPB), and CNPq-Brazil (National Council for Scientific and Technologic Development).

Multi-model analysis of precipitation-related climatological extremes for the Carpathian Region

NASA Astrophysics Data System (ADS)

Kis, Anna; Pongracz, Rita; Bartholy, Judit

2015-04-01

As a consequence of global climate change, both frequency and intensity of climatological and meteorological extremes are likely to change. These will certainly further induce various effects on hydrological extremes. Although more frequent hot weather in summer and overall warmer climatic conditions compared to the past decades are quite straightforward direct consequences of global warming, the effects on precipitation might be less clear because the higher spatial and temporal variabilities might hide robust changing signals. Nevertheless, precipitation is one of the most important meteorological variables since it considerably affects natural ecosystems and cultivated vegetation as well, as most of human activities. Extreme precipitation events - both excessive, intense rainfalls and severe droughts - may result in severe environmental, agricultural, and economical disasters. For instance, excessive precipitation may induce floods, flash-floods, landslides, traffic accidents. On the other hand, the lack of precipitation for extended period and coincidental intense heat wave often lead to severe drought events, which certainly affect agricultural production negatively, and hence, food safety might also be threatened. In order to avoid or at least reduce the effects of these precipitation-related hazards, national and local communities need to develop regional adaptation strategies, and then, act according to them. For this purpose, climatological projections are needed as a scientific basis. Coarse resolution results of global climate model (GCM) simulations must be downscaled to regional and local scales, hence better serving decision-makers' and end-users' needs. Dynamical downscaling technique applies regional climate model (RCM) to provide fine resolution climatological estimations for the future. Thus, in this study 11 completed RCM simulations with 25 km horizontal resolution are used from the ENSEMBLES database taking into account SRES A1B scenario for the 21st century. Before the thorough analysis of several drought- and precipitation-related climate indices (i.e., describing drought events, or intensity of precipitation exceeding different percentile-based or absolute threshold values, respectively), a percentile-based bias correction method was applied to the raw RCM output data, for which the homogenized daily gridded CarpatClim database (1961-2010) served as a reference. Absolute and relative seasonal mean changes of the climate indices are calculated for two future time periods (2021-2050 and 2071-2100) and for three subregions (i.e., Slovakia, Hungary, and Romania) within the entire Carpathian Region. According to our results, longer dry periods are estimated for the summer season, mainly in the southern parts of the domain, while precipitation intensity is likely to increase. Heavy precipitation days and high percentile values are projected to increase in the Carpathian Region, especially, in winter and autumn.

Adapting to the unpredictable: reproductive biology of vertebrates in the Australian wet-dry tropics.

PubMed

Shine, Richard; Brown, Gregory P

2008-01-27

In the wet-dry tropics of northern Australia, temperatures are high and stable year-round but monsoonal rainfall is highly seasonal and variable both annually and spatially. Many features of reproduction in vertebrates of this region may be adaptations to dealing with this unpredictable variation in precipitation, notably by (i) using direct proximate (rainfall-affected) cues to synchronize the timing and extent of breeding with rainfall events, (ii) placing the eggs or offspring in conditions where they will be buffered from rainfall extremes, and (iii) evolving developmental plasticity, such that the timing and trajectory of embryonic differentiation flexibly respond to local conditions. For example, organisms as diverse as snakes (Liasis fuscus, Acrochordus arafurae), crocodiles (Crocodylus porosus), birds (Anseranas semipalmata) and wallabies (Macropus agilis) show extreme annual variation in reproductive rates, linked to stochastic variation in wet season rainfall. The seasonal timing of initiation and cessation of breeding in snakes (Tropidonophis mairii) and rats (Rattus colletti) also varies among years, depending upon precipitation. An alternative adaptive route is to buffer the effects of rainfall variability on offspring by parental care (including viviparity) or by judicious selection of nest sites in oviparous taxa without parental care. A third type of adaptive response involves flexible embryonic responses (including embryonic diapause, facultative hatching and temperature-dependent sex determination) to incubation conditions, as seen in squamates, crocodilians and turtles. Such flexibility fine-tunes developmental rates and trajectories to conditions--especially, rainfall patterns--that are not predictable at the time of oviposition.

High-Resolution Regional Reanalysis in China: Evaluation of 1 Year Period Experiments

NASA Astrophysics Data System (ADS)

Zhang, Qi; Pan, Yinong; Wang, Shuyu; Xu, Jianjun; Tang, Jianping

2017-10-01

Globally, reanalysis data sets are widely used in assessing climate change, validating numerical models, and understanding the interactions between the components of a climate system. However, due to the relatively coarse resolution, most global reanalysis data sets are not suitable to apply at the local and regional scales directly with the inadequate descriptions of mesoscale systems and climatic extreme incidents such as mesoscale convective systems, squall lines, tropical cyclones, regional droughts, and heat waves. In this study, by using a data assimilation system of Gridpoint Statistical Interpolation, and a mesoscale atmospheric model of Weather Research and Forecast model, we build a regional reanalysis system. This is preliminary and the first experimental attempt to construct a high-resolution reanalysis for China main land. Four regional test bed data sets are generated for year 2013 via three widely used methods (classical dynamical downscaling, spectral nudging, and data assimilation) and a hybrid method with data assimilation coupled with spectral nudging. Temperature at 2 m, precipitation, and upper level atmospheric variables are evaluated by comparing against observations for one-year-long tests. It can be concluded that the regional reanalysis with assimilation and nudging methods can better produce the atmospheric variables from surface to upper levels, and regional extreme events such as heat waves, than the classical dynamical downscaling. Compared to the ERA-Interim global reanalysis, the hybrid nudging method performs slightly better in reproducing upper level temperature and low-level moisture over China, which improves regional reanalysis data quality.

Importance of anthropogenic climate impact, sampling error and urban development in sewer system design.

PubMed

Egger, C; Maurer, M

2015-04-15

Urban drainage design relying on observed precipitation series neglects the uncertainties associated with current and indeed future climate variability. Urban drainage design is further affected by the large stochastic variability of precipitation extremes and sampling errors arising from the short observation periods of extreme precipitation. Stochastic downscaling addresses anthropogenic climate impact by allowing relevant precipitation characteristics to be derived from local observations and an ensemble of climate models. This multi-climate model approach seeks to reflect the uncertainties in the data due to structural errors of the climate models. An ensemble of outcomes from stochastic downscaling allows for addressing the sampling uncertainty. These uncertainties are clearly reflected in the precipitation-runoff predictions of three urban drainage systems. They were mostly due to the sampling uncertainty. The contribution of climate model uncertainty was found to be of minor importance. Under the applied greenhouse gas emission scenario (A1B) and within the period 2036-2065, the potential for urban flooding in our Swiss case study is slightly reduced on average compared to the reference period 1981-2010. Scenario planning was applied to consider urban development associated with future socio-economic factors affecting urban drainage. The impact of scenario uncertainty was to a large extent found to be case-specific, thus emphasizing the need for scenario planning in every individual case. The results represent a valuable basis for discussions of new drainage design standards aiming specifically to include considerations of uncertainty. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genetic, environmental, and epigenetic factors in the development of personality disturbance.

PubMed

Depue, Richard A

2009-01-01

A dimensional model of personality disturbance is presented that is defined by extreme values on interacting subsets of seven major personality traits. Being at the extreme has marked effects on the threshold for eliciting those traits under stimulus conditions: that is, the extent to which the environment affects the neurobiological functioning underlying the traits. To explore the nature of development of extreme values on these traits, each trait is discussed in terms of three major issues: (a) the neurobiological variables associated with the trait, (b) individual variation in this neurobiology as a function of genetic polymorphisms, and (c) the effects of environmental adversity on these neurobiological variables through the action of epigenetic processes. It is noted that gene-environment interaction appears to be dependent on two main factors: (a) both genetic and environmental variables appear to have the most profound and enduring effects when they exert their effects during early postnatal periods, times when the forebrain is undergoing exuberant experience-expectant dendritic and axonal growth; and (b) environmental effects on neurobiology are strongly modified by individual differences in "traitlike" functioning of neurobiological variables. A model of the nature of the interaction between environmental and neurobiological variables in the development of personality disturbance is presented.

In situ scanning tunneling microscope tip treatment device for spin polarization imaging

DOEpatents

Li, An-Ping [Oak Ridge, TN; Jianxing, Ma [Oak Ridge, TN; Shen, Jian [Knoxville, TN

2008-04-22

A tip treatment device for use in an ultrahigh vacuum in situ scanning tunneling microscope (STM). The device provides spin polarization functionality to new or existing variable temperature STM systems. The tip treatment device readily converts a conventional STM to a spin-polarized tip, and thereby converts a standard STM system into a spin-polarized STM system. The tip treatment device also has functions of tip cleaning and tip flashing a STM tip to high temperature (>2000.degree. C.) in an extremely localized fashion. Tip coating functions can also be carried out, providing the tip sharp end with monolayers of coating materials including magnetic films. The device is also fully compatible with ultrahigh vacuum sample transfer setups.

Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

NASA Astrophysics Data System (ADS)

Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

2017-10-01

In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Adler, David; Peters-Lidard, Christa; Huffman, George

2012-01-01

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides worldwide. While research has evaluated the spatiotemporal distribution of extreme rainfall and landslides at local or regional scales using in situ data, few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This study uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from TRMM data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurrence of precipitation and landslides globally. Evaluation of the GLC indicates that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This study characterizes the variability of satellite precipitation data and reported landslide activity at the globally scale in order to improve landslide cataloging, forecasting and quantify potential triggering sources at daily, monthly and yearly time scales.

Climate Variability and Weather Extremes: Model-Simulated and Historical Data. Chapter 9

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Lim, Young-Kwon

2012-01-01

Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).

Extreme scattering events towards two young pulsars

NASA Astrophysics Data System (ADS)

Kerr, M.; Coles, W. A.; Ward, C. A.; Johnston, S.; Tuntsov, A. V.; Shannon, R. M.

2018-03-01

We have measured the scintillation properties of 151 young, energetic pulsars with the Parkes radio telescope and have identified two extreme scattering events (ESEs). Towards PSR J1057-5226, we discovered a 3 yr span of strengthened scattering during which the variability in flux density and the scintillation bandwidth decreased markedly. The transverse size of the scattering region is ˜23 au, and strong flux density enhancement before and after the ESE may arise from refractive focusing. Long observations reveal scintillation arcs characteristic of interference between rays scattered at large angles, and the clearest arcs appear during the ESE. The arcs suggest scattering by a screen 100-200 pc from the Earth, perhaps ionized filamentary structure associated with the boundary of the local bubble(s). Towards PSR J1740-3015, we observed a `double dip' in the measured flux density similar to ESEs observed towards compact extragalactic radio sources. The observed shape is consistent with that produced by a many-au scale diverging plasma lens with electron density ˜500 cm-3. The continuing ESE is at least 1500 d long, making it the longest detected event to date. These detections, with materially different observational signatures, indicate that well-calibrated pulsar monitoring is a keen tool for ESE detection and interstellar medium (ISM) diagnostics. They illustrate the strong role au-scale non-Kolmogorov density fluctuations and the local ISM structure play in such events and are key to understanding both their intrinsic physics and their impact on other phenomena, particularly fast radio bursts.

Hurricane Risk Variability along the Gulf of Mexico Coastline

PubMed Central

Trepanier, Jill C.; Ellis, Kelsey N.; Tucker, Clay S.

2015-01-01

Hurricane risk characteristics are examined across the U. S. Gulf of Mexico coastline using a hexagonal tessellation. Using an extreme value model, parameters are collected representing the rate or λ (frequency), the scale or σ (range), and the shape or ξ (intensity) of the extreme wind distribution. These latent parameters and the 30-year return level are visualized across the grid. The greatest 30-year return levels are located toward the center of the Gulf of Mexico, and for inland locations, along the borders of Louisiana, Mississippi, and Alabama. Using a geographically weighted regression model, the relationship of these parameters to sea surface temperature (SST) is found to assess sensitivity to change. It is shown that as SSTs increase near the coast, the frequency of hurricanes in these grids decrease significantly. This reinforces the importance of SST in areas of likely tropical cyclogenesis in determining the number of hurricanes near the coast, along with SSTs along the lifespan of the storm, rather than simply local SST. The range of hurricane wind speeds experienced near Florida is shown to increase with increasing SSTs (insignificant), suggesting that increased temperatures may allow hurricanes to maintain their strength as they pass over the Florida peninsula. The modifiable areal unit problem is assessed using multiple grid sizes. Moran’s I and the local statistic G are calculated to examine spatial autocorrelation in the parameters. This research opens up future questions regarding rapid intensification and decay close to the coast and the relationship to changing SSTs. PMID:25767885

Evaluation of friction heating in cavitating high pressure Diesel injector nozzles

NASA Astrophysics Data System (ADS)

Salemi, R.; Koukouvinis, P.; Strotos, G.; McDavid, R.; Wang, Lifeng; Li, Jason; Marengo, M.; Gavaises, M.

2015-12-01

Variation of fuel properties occurring during extreme fuel pressurisation in Diesel fuel injectors relative to those under atmospheric pressure and room temperature conditions may affect significantly fuel delivery, fuel injection temperature, injector durability and thus engine performance. Indicative results of flow simulations during the full injection event of a Diesel injector are presented. In addition to the Navier-Stokes equations, the enthalpy conservation equation is considered for predicting the fuel temperature. Cavitation is simulated using an Eulerian-Lagrangian cavitation model fully coupled with the flow equations. Compressible bubble dynamics based on the R-P equation also consider thermal effects. Variable fuel properties function of the local pressure and temperature are taken from literature and correspond to a reference so-called summer Diesel fuel. Fuel pressurisation up to 3000bar pressure is considered while various wall temperature boundary conditions are tested in order to compare their effect relative to those of the fuel heating caused during the depressurisation of the fuel as it passes through the injection orifices. The results indicate formation of strong temperature gradients inside the fuel injector while heating resulting from the extreme friction may result to local temperatures above the fuel's boiling point. Predictions indicate bulk fuel temperature increase of more than 100°C during the opening phase of the needle valve. Overall, it is concluded that such effects are significant for the injector performance and should be considered in relevant simulation tools.

Hurricane risk variability along the Gulf of Mexico coastline.

PubMed

Trepanier, Jill C; Ellis, Kelsey N; Tucker, Clay S

2015-01-01

Hurricane risk characteristics are examined across the U. S. Gulf of Mexico coastline using a hexagonal tessellation. Using an extreme value model, parameters are collected representing the rate or λ (frequency), the scale or σ (range), and the shape or ξ (intensity) of the extreme wind distribution. These latent parameters and the 30-year return level are visualized across the grid. The greatest 30-year return levels are located toward the center of the Gulf of Mexico, and for inland locations, along the borders of Louisiana, Mississippi, and Alabama. Using a geographically weighted regression model, the relationship of these parameters to sea surface temperature (SST) is found to assess sensitivity to change. It is shown that as SSTs increase near the coast, the frequency of hurricanes in these grids decrease significantly. This reinforces the importance of SST in areas of likely tropical cyclogenesis in determining the number of hurricanes near the coast, along with SSTs along the lifespan of the storm, rather than simply local SST. The range of hurricane wind speeds experienced near Florida is shown to increase with increasing SSTs (insignificant), suggesting that increased temperatures may allow hurricanes to maintain their strength as they pass over the Florida peninsula. The modifiable areal unit problem is assessed using multiple grid sizes. Moran's I and the local statistic G are calculated to examine spatial autocorrelation in the parameters. This research opens up future questions regarding rapid intensification and decay close to the coast and the relationship to changing SSTs.

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

PubMed

Ho, Hung Chak; Knudby, Anders; Huang, Wei

2015-12-18

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

Changes in the genetic structure of Atlantic salmon populations over four decades reveal substantial impacts of stocking and potential resiliency

PubMed Central

Perrier, Charles; Guyomard, René; Bagliniere, Jean-Luc; Nikolic, Natacha; Evanno, Guillaume

2013-01-01

While the stocking of captive-bred fish has been occurring for decades and has had substantial immediate genetic and evolutionary impacts on wild populations, its long-term consequences have only been weakly investigated. Here, we conducted a spatiotemporal analysis of 1428 Atlantic salmon sampled from 1965 to 2006 in 25 populations throughout France to investigate the influence of stocking on the neutral genetic structure in wild Atlantic salmon (Salmo salar) populations. On the basis of the analysis of 11 microsatellite loci, we found that the overall genetic structure among populations dramatically decreased over the period studied. Admixture rates among populations were highly variable, ranging from a nearly undetectable contribution from donor stocks to total replacement of the native gene pool, suggesting extremely variable impacts of stocking. Depending on population, admixture rates either increased, remained stable, or decreased in samples collected between 1998 and 2006 compared to samples from 1965 to 1987, suggesting either rising, long-lasting or short-term impacts of stocking. We discuss the potential mechanisms contributing to this variability, including the reduced fitness of stocked fish and persistence of wild locally adapted individuals. PMID:23919174

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Arrangement of Renal Arteries in Guinea Pig.

PubMed

Mazensky, David; Flesarova, Slavka

2017-03-01

The aim of this study was to describe origin, localization, and variations of renal arteries in guinea pig. The study was carried out on 26 adult guinea pigs. We prepared corrosion casts of the guinea pig arterial system. Batson's corrosion casting kit no. 17 was used as the casting medium. In 57.7% of specimens, a. renalis dextra was present as a single vessel with different level of its origin from aorta abdominalis. In 38.5% of specimens, two aa. renales dextrae were present with variable origin and arrangement. The presence of three aa. renales dextrae we found in one specimen. In 76.9% of specimens, a. renalis sinistra was present as a single vessel with different level of its origin from aorta abdominalis and variable arrangement. In 23.1% of specimens, we found two aa. renales sinistrae with variable origin and arrangement. The anatomical knowledge of the renal arteries, and its variations are of extreme importance for the surgeon that approaches the retroperitoneal region in several experiments, results of which are extrapolated in human. This is the first work dealing with the description of renal arteries arrangement in guinea pig. Anat Rec, 300:556-559, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Observed and predicted sensitivities of extreme surface ozone to meteorological drivers in three US cities

NASA Astrophysics Data System (ADS)

Fix, Miranda J.; Cooley, Daniel; Hodzic, Alma; Gilleland, Eric; Russell, Brook T.; Porter, William C.; Pfister, Gabriele G.

2018-03-01

We conduct a case study of observed and simulated maximum daily 8-h average (MDA8) ozone (O3) in three US cities for summers during 1996-2005. The purpose of this study is to evaluate the ability of a high resolution atmospheric chemistry model to reproduce observed relationships between meteorology and high or extreme O3. We employ regional coupled chemistry-transport model simulations to make three types of comparisons between simulated and observational data, comparing (1) tails of the O3 response variable, (2) distributions of meteorological predictor variables, and (3) sensitivities of high and extreme O3 to meteorological predictors. This last comparison is made using two methods: quantile regression, for the 0.95 quantile of O3, and tail dependence optimization, which is used to investigate even higher O3 extremes. Across all three locations, we find substantial differences between simulations and observational data in both meteorology and meteorological sensitivities of high and extreme O3.

A predictive model for spotted wilt epidemics in peanut based on local weather conditions and the tomato spotted wilt virus risk index.

PubMed

Olatinwo, R O; Paz, J O; Brown, S L; Kemerait, R C; Culbreath, A K; Beasley, J P; Hoogenboom, G

2008-10-01

Tomato spotted wilt virus (TSWV), a member of the genus Tospovirus (family Bunyaviridae), is an important plant virus that causes severe damage to peanut (Arachis hypogaea) in the southeastern United States. Disease severity has been extremely variable in individual fields in Georgia, due to several factors including variability in weather patterns. A TSWV risk index has been developed by the University of Georgia to aid peanut growers with the assessment and avoidance of high risk situations. This study was conducted to examine the relationship between weather parameters and spotted wilt severity in peanut, and to develop a predictive model that integrates localized weather information into the risk index. On-farm survey data collected during 1999, 2002, 2004, and 2005 growing seasons, and derived weather variables during the same years were analyzed using nonlinear and multiple regression analyses. Meteorological data were obtained from the Georgia Automated Environmental Monitoring Network. The best model explained 61% of the variation in spotted wilt severity (square root transformed) as a function of the interactions between the TSWV risk index, the average daily temperature in April (TavA), the average daily minimum temperature between March and April (TminMA), the accumulated rainfall in March (RainfallM), the accumulated rainfall in April (RainfallA), the number of rain days in April (RainDayA), evapotranspiration in April (EVTA), and the number of days from 1 January to the planting date (JulianDay). Integrating this weather-based model with the TSWV risk index may help peanut growers more effectively manage tomato spotted wilt disease.

Geo(spatial) Health Investigation of Rotavirus in an Endemic Region: Hydroclimatic Influences and Epidemiology of Rotavirus in Bangladesh

NASA Astrophysics Data System (ADS)

Hasan, M. A.; Akanda, A. S.; Jutla, A.; Colwell, R. R.

2016-12-01

Rotavirus is the leading cause of severe dehydrating diarrhea among children under 5. Over 80% of the approximate half a million child deaths every year occur in South Asia and sub-Saharan Africa alone. Although less explored than cholera as a climate driven and influenced global health problem, recent studies have showed that the disease shown strong seasonality and spatio-temporal variability depending on regional hydroclimatic and local environmental conditions. Understanding the epidemiology of this disease, especially the spatio-temporal incidence patterns with respect to environmental factors is vitally important to allow for identification of "hotspots", preventative preparations, and vaccination strategies to improve wellbeing of the vulnerable populations. With climate change, spatio-temporal signatures and footprints of the disease are changing along with increasing burden. However, a robust understanding of the relationships between rotavirus epidemiology and hydroclimatic drivers is yet to be developed. In this study, we evaluate the seasonality and epidemiologic characteristics of rotavirous infection and its spatio-temporal incidence patterns with respect to regional hydroclimatic variables and their extremes in an endemic region in South Asia. Hospital-based surveillance data from different geographic locations allowed us to explore the detailed spatial and temporal characteristics of rotavirus propagation under the influence of climate variables in both coastal and inland areas. The rotavirus transmission patterns show two peaks in a year in the capital city of Dhaka, where winter season (highest in January) shows a high peak and the July-August monsoon season shows a smaller peak. Correlation with climate variables revealed that minimum temperature has strong influence on the winter season outbreak, while rainfall extremes show a strong positive association with the secondary monsoon peak. Spatial analysis also revealed that humidity and soil wetness may influence the timing as drier areas experience earlier outbreaks than wetter areas. Accurate understanding of rotavirus propagation with respect to hydroclimatic and environmental variability can be utilized to establish global surveillance and forecast imminent risk of diarrheal outbreaks in vulnerable regions.

Contrasting seasonal and aseasonal environments across stages of the annual cycle in the Rufous-collared Sparrow, Zonotrichia capensis: differences in endocrine function, proteome, and body condition.

PubMed

González-Gómez, Paulina L; Echeverria, Valentina; Estades, Cristian F; Perez, Jonathan H; Krause, Jesse S; Sabat, Pablo; Li, Jonathon; Kültz, Dietmar; Wingfield, John C

2018-05-09

1.The timing and duration of life history stages (LHS) within the annual cycle can be affected by local environmental cues which are integrated through endocrine signaling mechanisms and changes in protein function. Most animals express a single LHS within a given period of the year because synchronous expression of LHSs is thought to be too costly energetically. However, in very rare and extremely stable conditions, breeding and molt have been observed to overlap extensively in Rufous-collared sparrows (Zonotrichia capensis) living in valleys of the Atacama Desert - one of the most stable and aseasonal environments on Earth. 2.To examine how LHS traits at different levels of organization are affected by environmental variability we compared the temporal organization and duration of LHSs in populations in the Atacama Desert with those in the semiarid Fray Jorge National Park in the north of Chile - an extremely seasonal climate but with unpredictable droughts and heavy rainy seasons. 3.We studied the effects of environmental variability on morphological variables related to body condition, endocrine traits, and proteome. Birds living in the seasonal environment had a strict temporal division LHSs while birds living in the aseasonal environment failed to maintain a temporal division of LHSs resulting in direct overlap of breeding and molt. Further, higher circulating glucocorticoids and androgen concentrations were found in birds from seasonal compared to aseasonal populations. Despite these differences, body condition variables and protein expression were not related to the degree of seasonality but rather showed a strong relationship with hormone levels. 4.These results suggest that animals adjust to their environment through changes in behavioral and endocrine traits and may be limited by less labile traits such as morphological variables or expression of specific proteins under certain circumstances. These data on free-living birds shed light on how different levels of life history organization within an individual are linked to increasing environmental heterogeneity. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Estimation of Atlantic-Mediterranean netflow variability

NASA Astrophysics Data System (ADS)

Guerreiro, Catarina; Peliz, Alvaro; Miranda, Pedro

2016-04-01

The exchanges at the Strait of Gibraltar are extremely difficult to measure due to the strong temporal and across-strait variabilities; yet the Atlantic inflow into the Mediterranean is extremely important both for climate and to ecosystems. Most of the published numerical modeling studies do not resolve the Strait of Gibraltar realistically. Models that represent the strait at high resolution focus primarily in high frequency dynamics, whereas long-term dynamics are studied in low resolution model studies, and for that reason the Strait dynamics are poorly resolved. Estimating the variability of the exchanges requires long term and high-resolutions studies, thus an improved simulation with explicit and realistic representation of the Strait is necessary. On seasonal to inter-annual timescales the flow is essentially driven by the net evaporation contribution and consequently realistic fields of precipitation and evaporation are necessary for model setup. A comparison between observations, reanalysis and combined products shows ERA-Interim Reanalysis has the most suitable product for Mediterranean Sea. Its time and space variability are in close agreement with NOC 1.1 for the common period (1980 - 1993) and also with evaporation from OAFLUX (1989 - 2014). Subinertial fluctuations, periods from days to a few months, are the second most energetic, after tides, and are the response to atmospheric pressure fluctuations and local winds. Atmospheric pressure fluctuations in the Mediterranean cause sea level oscillations that induce a barotropic flow through the Strait. Candela's analytical model has been used to quantify this response in later studies, though comparison with observations points to an underestimation of the flow at strait. An improved representation of this term contribution to the Atlantic - Mediterranean exchange must be achieved on longer time-scales. We propose a new simulation for the last 36 years (1979 - 2014) for the Mediterranean - Atlantic domain with explicit representation of the Strait. The simulations are performed using the Regional Ocean Modeling System (ROMS) and forced with the different contributions of the freshwater budget, sea level pressure fluctuations and winds from ERA-Interim Reanalysis. The model of sea level pressure induced barotropic fluctuations simulates the barotropic variability at the Strait of Gibraltar for the last decades.

Long-term trends and variability of total and extreme precipitation in Thailand

NASA Astrophysics Data System (ADS)

Limsakul, Atsamon; Singhruck, Patama

2016-03-01

Based on quality-controlled daily station data, long-term trends and variability of total and extreme precipitation indices during 1955-2014 were examined for Thailand. An analysis showed that while precipitation events have been less frequent across most of Thailand, they have become more intense. Moreover, the indices measuring the magnitude of intense precipitation events indicate a trend toward wetter conditions, with heavy precipitation contributing a greater fraction to annual totals. One consequence of this change is the increased frequency and severity of flash floods as recently evidenced in many parts of Thailand. On interannual-to-interdecadal time scales, significant relationships between variability of precipitation indices and the indices for the state of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) were found. These results provide additional evidence that large-scale climate phenomena in the Pacific Ocean are remote drivers of variability in Thailand's total and extreme precipitation. Thailand tended to have greater amounts of precipitation and more extreme events during La Niña years and the PDO cool phase, and vice versa during El Niño years and the PDO warm phase. Another noteworthy finding is that in 2011 Thailand experienced extensive flooding in a year characterized by exceptionally extreme precipitation events. Our results are consistent with the regional studies for the Asia-Pacific Network. However, this study provides a more detailed picture of coherent trends at a station scale and documents changes that have occurred in the twenty-first century, both of which help to inform decisions concerning effective management strategies.

Multiscaling properties of tropical rainfall: Analysis of rain gauge datasets in Lesser Antilles island environment

NASA Astrophysics Data System (ADS)

Bernard, Didier C.; Pasquier, Raphaël; Cécé, Raphaël; Dorville, Jean-François

2014-05-01

Changes in rainfall seem to be the main impact of climate change in the Caribbean area. The last conclusions of IPCC (2013), indicate that the end of this century will be marked by a rise of extreme rainfalls in tropical areas, linked with increase of the mean surface temperature. Moreover, most of the Lesser Antilles islands are characterized by a complex topography which tends to enhance the rainfall from synoptic disturbances by orographic effects. In the past five years, out of hurricanes passage, several extreme rainy events (approx. 16 mm in 6 minutes), including fatal cases, occurred in the Lesser Antilles Arc: in Guadeloupe (January 2011, May 2012 and 2013), in Martinique (May 2009, April 2011 and 2013), in Saint-Lucia (December 2013). These phenomena inducing floods, loss of life and material damages (agriculture sector and public infrastructures), inhibit the development of the islands. At this time, numerical weather prediction models as WRF, which are based on the equations of the atmospheric physics, do not show great results in the focused area (Bernard et al., 2013). Statistical methods may be used to examine explicitly local rainy updrafts, thermally and orographically induced at micro-scale. The main goal of the present insular tropical study is to characterize the multifractal symmetries occurring in the 6-min rainfall time series, registered since 2006 by the French Met. Office network weather stations. The universal multifractal model (Schertzer and Lovejoy, 1991) is used to define the statistical properties of measured rainfalls at meso-scale and micro-scale. This model is parametrized by a fundamental exponents set (H,a,C1,q) which are determined and compared with values found in the literature. The first three parameters characterize the mean pattern and the last parameter q, the extreme pattern. The occurrence ranges of multifractal regime are examined. The suggested links between the internal variability of the tropical rainy events and the multifractal properties found, are preliminary discussed. References Bernard, D., R. Cécé and J.-F. Dorville (2013). High resolution numerical simulation (WRF V3) of an extrem rainy event over the Guadeloupe archipelago: Case of 3-5 January 2011. EGU General Assembly 2013, Geophysical Research Abstracts, Vol. 15, EGU2013-9988, Vienna, April 2013. Schertzer, D., S. Lovejoy (1991). Nonlinear geodynamical variability: Multiple singularities, universality and observables. Scaling, fractals and non-linear variability in geophysics, D. Schertzer, S. Lovejoy eds.,41-82, Kluwer.

On exact correlation functions of chiral ring operators in 2 d N=(2, 2) SCFTs via localization

NASA Astrophysics Data System (ADS)

Chen, Jin

2018-03-01

We study the extremal correlation functions of (twisted) chiral ring operators via superlocalization in N=(2, 2) superconformal field theories (SCFTs) with central charge c ≥ 3, especially for SCFTs with Calabi-Yau geometric phases. We extend the method in arXiv: 1602.05971 with mild modifications, so that it is applicable to disentangle operators mixing on S 2 in nilpotent (twisted) chiral rings of 2 d SCFTs. With the extended algorithm and technique of localization, we compute exactly the extremal correlators in 2 d N=(2, 2) (twisted) chiral rings as non-holomorphic functions of marginal parameters of the theories. Especially in the context of Calabi-Yau geometries, we give an explicit geometric interpretation to our algorithm as the Griffiths transversality with projection on the Hodge bundle over Calabi-Yau complex moduli. We also apply the method to compute extremal correlators in Kähler moduli, or say twisted chiral rings, of several interesting Calabi-Yau manifolds. In the case of complete intersections in toric varieties, we provide an alternative formalism for extremal correlators via localization onto Higgs branch. In addition, as a spinoff we find that, from the extremal correlators of the top element in twisted chiral rings, one can extract chiral correlators in A-twisted topological theories.

Climate Exposure of US National Parks in a New Era of Change

PubMed Central

Monahan, William B.; Fisichelli, Nicholas A.

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901–2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change. PMID:24988483

Climate exposure of US national parks in a new era of change.

PubMed

Monahan, William B; Fisichelli, Nicholas A

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901-2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change.

Extreme Heat and Health: Perspectives from Health Service Providers in Rural and Remote Communities in South Australia

PubMed Central

Williams, Susan; Bi, Peng; Newbury, Jonathan; Robinson, Guy; Pisaniello, Dino; Saniotis, Arthur; Hansen, Alana

2013-01-01

Among the challenges for rural communities and health services in Australia, climate change and increasing extreme heat are emerging as additional stressors. Effective public health responses to extreme heat require an understanding of the impact on health and well-being, and the risk or protective factors within communities. This study draws on lived experiences to explore these issues in eleven rural and remote communities across South Australia, framing these within a socio-ecological model. Semi-structured interviews with health service providers (n = 13), and a thematic analysis of these data, has identified particular challenges for rural communities and their health services during extreme heat. The findings draw attention to the social impacts of extreme heat in rural communities, the protective factors (independence, social support, education, community safety), and challenges for adaptation (vulnerabilities, infrastructure, community demographics, housing and local industries). With temperatures increasing across South Australia, there is a need for local planning and low-cost strategies to address heat-exacerbating factors in rural communities, to minimise the impact of extreme heat in the future. PMID:24173140

On Light-Like Extremal Surfaces in Curved Spacetimes

NASA Astrophysics Data System (ADS)

Huang, Shou-Jun; He, Chun-Lei

2014-01-01

In this paper, we are concerned with light-like extremal surfaces in curved spacetimes. It is interesting to find that under a diffeomorphic transformation of variables, the light-like extremal surfaces can be described by a system of nonlinear geodesic equations. Particularly, we investigate the light-like extremal surfaces in Schwarzschild spacetime in detail and some new special solutions are derived systematically with aim to compare with the known results and to illustrate the method.

Understanding extreme rainfall events in Australia through historical data

NASA Astrophysics Data System (ADS)

Ashcroft, Linden; Karoly, David John

2016-04-01

Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this relationship has remained stable since the early to mid-19th century. Ashcroft, L., Gergis, J., Karoly, D.J., 2014a. A historical climate dataset for southeastern Australia, 1788-1859. Geosci. Data J. 1, 158-178. doi:10.1002/gdj3.19 Ashcroft, L., Karoly, D.J., Gergis, J., 2014b. Southeastern Australian climate variability 1860-2009: A multivariate analysis. Int. J. Climatol. 34, 1928-1944. doi:10.1002/joc.3812

Adaptation to Climatic Hazards in the Savannah Ecosystem: Improving Adaptation Policy and Action

NASA Astrophysics Data System (ADS)

Yiran, Gerald A. B.; Stringer, Lindsay C.

2017-10-01

People in Ghana's savannah ecosystem have historically experienced a range of climatic hazards that have affected their livelihoods. In view of current climate variability and change, and projected increases in extreme events, adaptation to climate risks is vital. Policies have been put in place to enhance adaptation across sub-Saharan Africa in accordance with international agreements. At the same time, local people, through experience, have learned to adapt. This paper examines current policy actions and their implementation alongside an assessment of barriers to local adaptation. In doing so it links adaptation policy and practice. Policy documents were analysed that covered key livelihood sectors, which were identified as climate sensitive. These included agriculture, water, housing and health policies, as well as the National Climate Change Policy. In-depth interviews and focus group discussions were also held with key stakeholders in the Upper East Region of Ghana. Analyses were carried using thematic content analysis. Although policies and actions complement each other, their integration is weak. Financial, institutional, social, and technological barriers hinder successful local implementation of some policy actions, while lack of local involvement in policy formulation also hinders adaptation practice. Integration of local perspectives into policy needs to be strengthened in order to enhance adaptation. Coupled with this is a need to consider adaptation to climate change in development policies and to pursue efforts to reduce or remove the key barriers to implementation at the local level.

Identifying evidence of climate change impact on extreme events in permeable chalk catchments

NASA Astrophysics Data System (ADS)

Butler, A. P.; Nubert, S.

2009-12-01

The permeable chalk catchments of southern England are vital for the economy and well being of the UK. Not only important as a water resource, their freely draining soils support intensive agricultural production, and the rolling downs and chalk streams provide important habitants for many protected plant and animal species. Consequently, there are concerns about the potential impact of climate change on such catchments, particularly in relation to groundwater recharge. Of major concern are possible changes in extreme events, such as groundwater floods and droughts, as any increase in the frequency and/or severity of these has important consequences for water resources, ecological systems and local infrastructure. Studies of climate change impact on extreme events for such catchments have indicated that, under medium and high emissions scenarios, droughts are likely to become more severe whilst floods less so. However, given the uncertainties in such predictions and the inherent variability in historic data, producing definitive evidence of changes in flood/drought frequency/severity poses a significant challenge. Thus, there is a need for specific extreme event statistics that can be used as indicators of actual climate change in streamflow and groundwater level observations. Identifying such indicators that are sufficiently robust requires catchments with long historic time series data. One such catchment is the River Lavant, an intermittent chalk stream in West Sussex, UK. Located within this catchment is Chilgrove House, the site of the UK’s longest groundwater monitoring well (with a continuous record of water level observations of varying frequency dating back to 1836). Using a variety of meteorological datasets, the behaviour of the catchment has been modelled, from 1855 to present, using a 'leaky aquifer' conceptual model. Model calibration was based on observed daily streamflow, at a gauging station just outside the town of Chichester, from 1970. Long-term performance was assessed using groundwater levels at various long period observation wells, including Chilgrove. Extreme event analyses (annual maximum daily flow, annual minimum groundwater level) based on historic model runs, looking at successive 30 year time periods, show high variability in the values of extreme events, However, there is far less (by an order of magnitude) variation in more frequent (i.e. less extreme) events with a recurrence interval of around 0.6 (i.e. a return period of around 1.67 years). Simulations of climate change impact for 2020 emission scenarios using UKCIP02 data give 0.6 recurrence estimates that are significantly different (at the 1% confidence level) than those obtained from historic data, which is not the case for more extreme events. It is proposed that, at least for such permeable catchments, deviations from historic values of this relatively frequent recurrence interval provide a more robust indicator for detecting evidence of climate change than focusing on much rarer, albeit more dramatic, events.

The Peak Structure and Future Changes of the Relationships Between Extreme Precipitation and Temperature

NASA Technical Reports Server (NTRS)

Wang, Guiling; Wang, Dagang; Trenberth, Kevin E.; Erfanian, Amir; Yu, Miao; Bosilovich, Michael G.; Parr, Dana T.

2017-01-01

Theoretical models predict that, in the absence of moisture limitation, extreme precipitation intensity could exponentially increase with temperatures at a rate determined by the Clausius-Clapeyron (C-C) relationship. Climate models project a continuous increase of precipitation extremes for the twenty-first century over most of the globe. However, some station observations suggest a negative scaling of extreme precipitation with very high temperatures, raising doubts about future increase of precipitation extremes. Here we show for the present-day climate over most of the globe,the curve relating daily precipitation extremes with local temperatures has a peak structure, increasing as expected at the low medium range of temperature variations but decreasing at high temperatures. However, this peak-shaped relationship does not imply a potential upper limit for future precipitation extremes. Climate models project both the peak of extreme precipitation and the temperature at which it peaks (T(sub peak)) will increase with warming; the two increases generally conform to the C-C scaling rate in mid- and high-latitudes,and to a super C-C scaling in most of the tropics. Because projected increases of local mean temperature (T(sub mean)) far exceed projected increases of T(sub peak) over land, the conventional approach of relating extreme precipitation to T(sub mean) produces a misleading sub-C-C scaling rate.

Heavy Tail Behavior of Rainfall Extremes across Germany

NASA Astrophysics Data System (ADS)

Castellarin, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.

2017-12-01

Distributions are termed heavy-tailed if extreme values are more likely than would be predicted by probability distributions that have exponential asymptotic behavior. Heavy-tail behavior often leads to surprise, because historical observations can be a poor guide for the future. Heavy-tail behavior seems to be widespread for hydro-meteorological extremes, such as extreme rainfall and flood events. To date there have been only vague hints to explain under which conditions these extremes show heavy-tail behavior. We use an observational data set consisting of 11 climate variables at 1440 stations across Germany. This homogenized, gap-free data set covers 110 years (1901-2010) at daily resolution. We estimate the upper tail behavior, including its uncertainty interval, of daily precipitation extremes for the 1,440 stations at the annual and seasonal time scales. Different tail indicators are tested, including the shape parameter of the Generalized Extreme Value distribution, the upper tail ratio and the obesity index. In a further step, we explore to which extent the tail behavior can be explained by geographical and climate factors. A large number of characteristics is derived, such as station elevation, degree of continentality, aridity, measures for quantifying the variability of humidity and wind velocity, or event-triggering large-scale atmospheric situation. The link between the upper tail behavior and these characteristics is investigated via data mining methods capable of detecting non-linear relationships in large data sets. This exceptionally rich observational data set, in terms of number of stations, length of time series and number of explaining variables, allows insights into the upper tail behavior which is rarely possible given the typical observational data sets available.

A Tree-Ring Based Reconstruction (1725-present) of the Position of the Summer North Atlantic Jet Shows a 20th Century Northward Shift

NASA Astrophysics Data System (ADS)

Trouet, V.; Babst, F.

2014-12-01

The position and strength of the Northern Hemisphere polar jet are important modulators of mid-latitude weather extremes and the societal, ecosystem, and economic damage related to them. The position of the North Atlantic jet (NAJ) controls the location of the Atlantic storm track and anomalies in the NAJ position have been related to temperature and precipitation extremes over Europe. In summer, a southern NAJ regime can result in floods in the British Isles (BRIT) and increasing odds of heat waves in the northeastern Mediterranean (NEMED). Variability in the amplitude and speed of the Northern Hemisphere jet stream is hotly debated as a potential mechanism linking recent mid-latitude weather extremes to anthropogenic warming. However, the hypothesis of jet stream variability as a possible mechanism linking Arctic amplification to mid-latitude weather extremes is largely based on data sets with limited temporal extent that do not warrant robust results from a statistical significance perspective. Here, we combined two summer temperature-sensitive tree-ring records from BRIT and NEMED to reconstruct interannual variability in the latitudinal position of the summer NAJ back to 1725. The two well-replicated temperature proxies counter-correlate significantly over the full period and thus illustrate the temperature dipole generated by anomalous NAJ positions. Positive extremes in the NAJ reconstruction correspond to heatwaves recorded in the historical Central England temperature record and negative extremes correspond to reconstructed fire years in Greece. The reconstruction shows a northward shift in the latitudinal NAJ position since the 1930s that is most pronounced in the northern NAJ extremes, suggesting a more frequent occurrence of BRIT hot summers in the 20th century compared to previous centuries.

Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Bruce T.

2015-12-11

Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantiallymore » from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred through a change in the underlying climate. As such, this method is capable of detecting “hot spot” regions—as well as “flare ups” within the hot spot regions—that have experienced interannual to multi-decadal scale variations and trends in seasonal-mean precipitation and extreme events. Further by applying the same methods to numerical climate models we can discern the fidelity of the current-generation climate models in representing detectability within the observed climate system. In this way, we can objectively determine the utility of these model systems for performing detection studies of historical and future climate change.« less

Main processes of the Atlantic cold tongue interannual variability

NASA Astrophysics Data System (ADS)

Planton, Yann; Voldoire, Aurore; Giordani, Hervé; Caniaux, Guy

2018-03-01

The interannual variability of the Atlantic cold tongue (ACT) is studied by means of a mixed-layer heat budget analysis. A method to classify extreme cold and warm ACT events is proposed and applied to ten various analysis and reanalysis products. This classification allows 5 cold and 5 warm ACT events to be selected over the period 1982-2007. Cold (warm) ACT events are defined by the presence of negative (positive) sea surface temperature (SST) anomalies at the center of the equatorial Atlantic in late boreal spring, preceded by negative (positive) zonal wind stress anomalies in the western equatorial Atlantic. An ocean general circulation model capable of reconstructing the interannual variability of the ACT correctly is used to demonstrate that cold ACT events develop rapidly from May to June mainly due to intense cooling by vertical mixing and horizontal advection. The simulated cooling at the center of the basin is the result of the combined effects of non-local and local processes. The non-local process is an upwelling associated with an eastward-propagating Kelvin wave, which makes the mixed-layer more shallow and preconditions the upper layers to be cooled by an intense heat loss at the base of the mixed-layer, which is amplified by a stronger local injection of energy from the atmosphere. The early cooling by vertical mixing in March is also shown to be a good predictor of June cooling. In July, horizontal advection starts to warm the mixed-layer abnormally and damps SST anomalies. The advection anomalies, which result from changes in the horizontal temperature gradient, are associated in some cases with the propagation of Rossby waves along the equator. During warm ACT events, processes are reversed, generating positive SST anomalies: a downwelling Kelvin wave triggers stratification anomalies and mixed-layer depth anomalies, amplified by a weaker injection of energy from the atmosphere in May-June. In July, warm ACT events are abnormally cooled due to negative horizontal advection anomalies resulting from processes similar to those that occur during cold ACT events. This additional cooling process extends the period of cooling of the ACT, reducing SST anomalies.

Outcome of multimodality treatment of Ewing's sarcoma of the extremities.

PubMed

Tiwari, Akshay; Gupta, Himesh; Jain, Sandeep; Kapoor, Gauri

2010-10-01

The management of Ewing's sarcoma family of tumors (ESFT, Ewing's sarcoma/primitive neuroectodermal tumor) has been established as a multimodality treatment. Advances in imaging and diagnostics, chemotherapy, surgical techniques, radiotherapy and prosthetic technology have resulted in drastic changes in the outcome of this disease, with most of the recent studies having 5-year survival rates of more than 60%. The Indian patients present at a more advanced stage and the compliance of treatment is suboptimal. While there is plenty of data in the world literature on the outcome of Ewing's sarcoma, there is paucity of data in Indian patients. Therefore, we conducted the present study to analyze the outcome of multimodality treatment of ESFT of the extremities at a tertiary nonprofit institute over a decade. 34 patients who had histopathologically proven diagnosis of Ewing's sarcoma of the extremities and had received treatment at our institute from 1997 through 2007 were included for analysis. The majority of patients had involvement of the femur (35%), followed by tibia (17%), fibula and foot (15% each), humerus (12%) and soft tissue of thigh (6%). Twenty-nine patients presented with localized disease (Enneking stage II B) while five patients presented with metastases (Enneking stage III). All patients received Vincristine, Actinomycin D, Cyclofosfamide + Ifosfamide and Etoposide (VAC+IE)-based chemotherapy and local treatment was offered to all but three patients having multicentric disease. The local treatment offered were, radiation (n= 15), surgery (n= 12) both surgery and radiation (n=4). All patients were analyzed for oncological outcome (event-free and overall survival, local and systemic relapses) by clinical and imaging evaluation and functional outcome by using the musculoskeletal tumor society (MSTS) score. These outcomes were correlated with age, sex, size of tumor, stage at presentation, modality of local treatment and site of relapse. At the final follow-up (mean, 26 months; median, 17 months; range, 3-97 months), the overall and event-free survivals were 47 ± 12% and 34 ± 9%, respectively. Sixty-two percent of the patients presented with a tumor size more than 8 cm. On correlation with age, sex, size of tumor, stage at presentation, modality of local treatment and site of relapse, no correlation of survival was seen with any of the variables except event-free survival with size of the tumor. The functional outcome of all the patients was satisfactory (MSTS score >16 out of 30). No patient underwent amputation. Although the demographic profile, stage at presentation and the local and systemic treatment regimen followed in our study was similar to the world literature, the outcome of Ewing's sarcoma in Indian patients were found to be inferior to that reported in the western literature. Larger multicentric studies with longer follow-up are required to exactly determine the key areas crucial in improving this outcome.

Exploring local perceptions and attributions of 'extreme' wildfire impacts in Rural Montana

NASA Astrophysics Data System (ADS)

Carroll, M.; Paveglio, T.; Kallman, D.

2013-12-01

To date there have been few systematic efforts to uncover the criteria that local stakeholders use to perceive of and make judgments about the severity of wildfire impacts to the social-ecological systems they are a part of. The study presented here sought to uncover expanded understandings of perceived social and ecological impacts from a wildfire in rural Montana and the underlying causes for those perceived impacts. Such efforts could lead to more comprehensive social impact assessment concerning wildfires or other hazards and help better understand how local perceptions might influence residents' ongoing attitudes toward fire risk or mitigation efforts. The study presented here explored local perceptions of impact from the 2012 Dahl fire near Roundup, MT. The Dahl Fire burned 73 permanent structures, 150 outbuilding and 22,000 acres of predominantly private lands in the rural Bull Mountains. Members of the project team interviewed approximately 50 stakeholders impacted by or involved in the management for the Dahl Fire. Interviews took place in the summer of 2013 and included a variety of residents, emergency personnel, firefighters, local community officials and land management professionals. Results suggest that residents considered the Dahl fire especially impactful given the number of private residences and structures that were burned and the number of people displaced or disrupted by the event (either directly, through efforts to help those affected, or through indirect impacts to community function). The extremity of the firefighting conditions (e.g. wind, relative humidity, terrain), the rapidity of fire spread through populated areas and the damages sustained given previous fires in the area all surprised stakeholders and contributed to their perceptions of impact severity. Conflicts over access to properties during and immediately following the fire, and the variable perception that personal wildfire mitigations did little to reduce damages from the fire also contributed to perceptions about the level of wildfire impact. Many respondents felt that impacts from the Dahl Fire were the result of historic development patterns that allowed for mid-sized, rural subdivisions in heavily forested draws and along rough roads. Residents in these areas often moved to the Bull Mountains for privacy and to exercise significant property rights. Other residents felt the fire was not attacked quickly enough. Resident response to the impacts was almost universally perceived as well organized and effective. It was predicated on the collaborative capacity of local groups, community ties and experience with historic floods the year prior to the fire. Unexpected longer-term impacts such as high levels of erosion and flash-flooding have kept the fire in the minds of residents and contributed to their perceptions of impact. Respondents (including those with homes that burned) indicated that a significant portion of those whose property was damaged did not intend to return or rebuild. This is somewhat unique in response to wildfires and should be explored in future fires perceived by locals as extreme in order to test for emerging trends.

A new framework for estimating return levels using regional frequency analysis

NASA Astrophysics Data System (ADS)

Winter, Hugo; Bernardara, Pietro; Clegg, Georgina

2017-04-01

We propose a new framework for incorporating more spatial and temporal information into the estimation of extreme return levels. Currently, most studies use extreme value models applied to data from a single site; an approach which is inefficient statistically and leads to return level estimates that are less physically realistic. We aim to highlight the benefits that could be obtained by using methodology based upon regional frequency analysis as opposed to classic single site extreme value analysis. This motivates a shift in thinking, which permits the evaluation of local and regional effects and makes use of the wide variety of data that are now available on high temporal and spatial resolutions. The recent winter storms over the UK during the winters of 2013-14 and 2015-16, which have caused wide-ranging disruption and damaged important infrastructure, provide the main motivation for the current work. One of the most impactful natural hazards is flooding, which is often initiated by extreme precipitation. In this presentation, we focus on extreme rainfall, but shall discuss other meteorological variables alongside potentially damaging hazard combinations. To understand the risks posed by extreme precipitation, we need reliable statistical models which can be used to estimate quantities such as the T-year return level, i.e. the level which is expected to be exceeded once every T-years. Extreme value theory provides the main collection of statistical models that can be used to estimate the risks posed by extreme precipitation events. Broadly, at a single site, a statistical model is fitted to exceedances of a high threshold and the model is used to extrapolate to levels beyond the range of the observed data. However, when we have data at many sites over a spatial domain, fitting a separate model for each separate site makes little sense and it would be better if we could incorporate all this information to improve the reliability of return level estimates. Here, we use the regional frequency analysis approach to define homogeneous regions which are affected by the same storms. Extreme value models are then fitted to the data pooled from across a region. We find that this approach leads to more spatially consistent return level estimates with reduced uncertainty bounds.

Growing hair on the extremal BTZ black hole

NASA Astrophysics Data System (ADS)

Harms, B.; Stern, A.

2017-06-01

We show that the nonlinear σ-model in an asymptotically AdS3 space-time admits a novel local symmetry. The field action is assumed to be quartic in the nonlinear σ-model fields and minimally coupled to gravity. The local symmetry transformation simultaneously twists the nonlinear σ-model fields and changes the space-time metric, and it can be used to map the extremal BTZ black hole to infinitely many hairy black hole solutions.

The role of extreme orbits in the global organization of periodic regions in parameter space for one dimensional maps

NASA Astrophysics Data System (ADS)

da Costa, Diogo Ricardo; Hansen, Matheus; Guarise, Gustavo; Medrano-T, Rene O.; Leonel, Edson D.

2016-04-01

We show that extreme orbits, trajectories that connect local maximum and minimum values of one dimensional maps, play a major role in the parameter space of dissipative systems dictating the organization for the windows of periodicity, hence producing sets of shrimp-like structures. Here we solve three fundamental problems regarding the distribution of these sets and give: (i) their precise localization in the parameter space, even for sets of very high periods; (ii) their local and global distributions along cascades; and (iii) the association of these cascades to complicate sets of periodicity. The extreme orbits are proved to be a powerful indicator to investigate the organization of windows of periodicity in parameter planes. As applications of the theory, we obtain some results for the circle map and perturbed logistic map. The formalism presented here can be extended to many other different nonlinear and dissipative systems.

Multidecadal oscillations in rainfall and hydrological extremes

NASA Astrophysics Data System (ADS)

Willems, Patrick

2013-04-01

Many studies have anticipated a worldwide increase in the frequency and intensity of precipitation extremes and floods since the last decade(s). Natural variability by climate oscillations partly determines the observed evolution of precipitation extremes. Based on a technique for the identification and analysis of changes in extreme quantiles, it is shown that hydrological extremes have oscillatory behaviour at multidecadal time scales. Results are based on nearly independent extremes extracted from long-term historical time series of precipitation intensities and river flows. Study regions include Belgium - The Netherlands (Meuse basin), Ethiopia (Blue Nile basin) and Ecuador (Paute basin). For Belgium - The Netherlands, the past 100 years showed larger and more hydrological extremes around the 1910s, 1950-1960s, and more recently during the 1990-2000s. Interestingly, the oscillations for southwestern Europe are anti-correlated with these of northwestern Europe, thus with oscillation highs in the 1930-1940s and 1970s. The precipitation oscillation peaks are explained by persistence in atmospheric circulation patterns over the North Atlantic during periods of 10 to 15 years. References: Ntegeka V., Willems P. (2008), 'Trends and multidecadal oscillations in rainfall extremes, based on a more than 100 years time series of 10 minutes rainfall intensities at Uccle, Belgium', Water Resources Research, 44, W07402, doi:10.1029/2007WR006471 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water Resources Research, 48, W03513, 13p. Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012), 'Impacts of climate change on rainfall extremes and urban drainage', IWA Publishing, 252p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263

Significance of Environmental Variables on Flight Electronics and Design Concerns for Extreme Environments

NASA Astrophysics Data System (ADS)

Hazeli, K.; Kingstedt, O. T.

2017-05-01

It is critical to investigate the performance of electronic systems and their components under the environments experienced during proposed missions to improve spacecraft and robotic vehicle functionality and performance in extreme environments.

Northern Eurasian Heat Waves and Droughts

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Wang, Hailan; Koster, Randal; Suarez, Max; Groisman, Pavel

2013-01-01

This article reviews our understanding of the characteristics and causes of northern Eurasian summertime heat waves and droughts. Additional insights into the nature of temperature and precipitation variability in Eurasia on monthly to decadal time scales and into the causes and predictability of the most extreme events are gained from the latest generation of reanalyses and from supplemental simulations with the NASA GEOS-5 AGCM. Key new results are: 1) the identification of the important role of summertime stationary Rossby waves in the development of the leading patterns of monthly Eurasian surface temperature and precipitation variability (including the development of extreme events such as the 2010 Russian heat wave), 2) an assessment of the mean temperature and precipitation changes that have occurred over northern Eurasia in the last three decades and their connections to decadal variability and global trends in SST, and 3) the quantification (via a case study) of the predictability of the most extreme simulated heat wave/drought events, with some focus on the role of soil moisture in the development and maintenance of such events. A literature survey indicates a general consensus that the future holds an enhanced probability of heat waves across northern Eurasia, while there is less agreement regarding future drought, reflecting a greater uncertainty in soil moisture and precipitation projections. Substantial uncertainties remain in our understanding of heat waves and drought, including the nature of the interactions between the short-term atmospheric variability associated with such extremes and the longer-term variability and trends associated with soil moisture feedbacks, SST anomalies, and an overall warming world.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events.

PubMed

Vincenzi, Simone

2014-08-06

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an 'extinction window' of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the 'extinction window', although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Logit-normal mixed model for Indian Monsoon rainfall extremes

NASA Astrophysics Data System (ADS)

Dietz, L. R.; Chatterjee, S.

2014-03-01

Describing the nature and variability of Indian monsoon rainfall extremes is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Several GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data procured from the National Climatic Data Center. The logit-normal model was applied with fixed covariates of latitude, longitude, elevation, daily minimum and maximum temperatures with a random intercept by weather station. In general, the estimation methods concurred in their suggestion of a relationship between the El Niño Southern Oscillation (ENSO) and extreme rainfall variability estimates. This work provides a valuable starting point for extending GLMM to incorporate the intricate dependencies in extreme climate events.

Extreme Ultraviolet Variability Experiment (EVE) Multiple EUV Grating Spectrographs (MEGS): Radiometric Calibrations and Results

NASA Technical Reports Server (NTRS)

Hock, R. A.; Woods, T. N.; Crotser, D.; Eparvier, F. G.; Woodraska, D. L.; Chamberlin, P. C.; Woods, E. C.

2010-01-01

The NASA Solar Dynamics Observatory (SDO), scheduled for launch in early 2010, incorporates a suite of instruments including the Extreme Ultraviolet Variability Experiment (EVE). EVE has multiple instruments including the Multiple Extreme ultraviolet Grating Spectrographs (MEGS) A, B, and P instruments, the Solar Aspect Monitor (SAM), and the Extreme ultraviolet SpectroPhotometer (ESP). The radiometric calibration of EVE, necessary to convert the instrument counts to physical units, was performed at the National Institute of Standards and Technology (NIST) Synchrotron Ultraviolet Radiation Facility (SURF III) located in Gaithersburg, Maryland. This paper presents the results and derived accuracy of this radiometric calibration for the MEGS A, B, P, and SAM instruments, while the calibration of the ESP instrument is addressed by Didkovsky et al. . In addition, solar measurements that were taken on 14 April 2008, during the NASA 36.240 sounding-rocket flight, are shown for the prototype EVE instruments.

Changes in Extremely Hot Summers over the Global Land Area under Various Warming Targets

PubMed Central

Wang, Lei; Huang, Jianbin; Luo, Yong; Yao, Yao; Zhao, Zongci

2015-01-01

Summer temperature extremes over the global land area were investigated by comparing 26 models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with observations from the Goddard Institute for Space Studies (GISS) and the Climate Research Unit (CRU). Monthly data of the observations and models were averaged for each season, and statistics were calculated for individual models before averaging them to obtain ensemble means. The summers with temperature anomalies (relative to 1951–1980) exceeding 3σ (σ is based on the local internal variability) are defined as “extremely hot”. The models well reproduced the statistical characteristics evolution, and partly captured the spatial distributions of historical summer temperature extremes. If the global mean temperature increases 2°C relative to the pre-industrial level, “extremely hot” summers are projected to occur over nearly 40% of the land area (multi-model ensemble mean projection). Summers that exceed 5σ warming are projected to occur over approximately 10% of the global land area, which were rarely observed during the reference period. Scenarios reaching warming levels of 3°C to 5°C were also analyzed. After exceeding the 5°C warming target, “extremely hot” summers are projected to occur throughout the entire global land area, and summers that exceed 5σ warming would become common over 70% of the land area. In addition, the areas affected by “extremely hot” summers are expected to rapidly expand by more than 25%/°C as the global mean temperature increases by up to 3°C before slowing to less than 16%/°C as the temperature continues to increase by more than 3°C. The area that experiences summers with warming of 5σ or more above the warming target of 2°C is likely to maintain rapid expansion of greater than 17%/°C. To reduce the impacts and damage from severely hot summers, the global mean temperature increase should remain low. PMID:26090931

Climate forecasting services: coming down from the ivory tower

NASA Astrophysics Data System (ADS)

Doblas-Reyes, F. J.; Caron, L. P.; Cortesi, N.; Soret, A.; Torralba, V.; Turco, M.; González Reviriego, N.; Jiménez, I.; Terrado, M.

2016-12-01

Subseasonal-to-seasonal (S2S) climate forecasts are increasingly used across a range of application areas (energy, water management, agriculture, health, insurance) through tailored services using the climate services paradigm. In this contribution we show the value of climate forecasting services through several examples of their application in the energy, reinsurance and agriculture sectors. Climate services aim at making climate information action oriented. In a climate forecasting context the task starts with the identification of climate variables, thresholds and events relevant to the users. These elements are then analysed to determine whether they can be both reliably and skilfully predicted at appropriate time scales. In this contribution we assess climate predictions of precipitation, temperature and wind indices from state-of-the-art operational multi-model forecast systems and if they respond to the expectations and requests from a range of users. This requires going beyond the more traditional assessment of monthly mean values to include assessments of global forecast quality of the frequency of warm, cold, windy and wet extremes (e.g. [1], [2]), as well as of using tools like the Euro-Atlantic weather regimes [3]. The forecast quality of extremes is generally similar to or slightly lower than that of monthly or seasonal averages, but offers a kind of information closer to what some users require. In addition to considering local climate variables, we also explore the use of large-scale climate indices, such as ENSO and NAO, that are associated with large regional synchronous variations of wind or tropical storm frequency. These indices help illustrating the relative merits of climate forecast information to users and are the cornerstone of climate stories that engage them in the co-production of climate information. [1] Doblas-Reyes et al, WIREs, 2013 [2] Pepler et al, Weather and Climate Extremes, 2015 [3] Pavan and Doblas-Reyes, Clim Dyn, 2013

Dependence of drivers affects risks associated with compound events

NASA Astrophysics Data System (ADS)

Zscheischler, Jakob; Seneviratne, Sonia I.

2017-04-01

Compound climate extremes are receiving increasing attention because of their disproportionate impacts on humans and ecosystems. Risks assessments, however, generally focus on univariate statistics even when multiple stressors are considered. Concurrent extreme droughts and heatwaves have been observed to cause a suite of extreme impacts on natural and human systems alike. For example, they can substantially affect vegetation health, prompting tree mortality, and thereby facilitating insect outbreaks and fires. In addition, hot droughts have the potential to trigger and intensify fires and can cause severe economical damage. By promoting disease spread, extremely hot and dry conditions also strongly affect human health. We analyse the co-occurrence of dry and hot summers and show that these are strongly correlated for many regions, inducing a much higher frequency of concurrent hot and dry summers than what would be assumed from the independent combination of the univariate statistics. Our results demonstrate how the dependence structure between variables affects the occurrence frequency of multivariate extremes. Assessments based on univariate statistics can thus strongly underestimate risks associated with given extremes, if impacts depend on multiple (dependent) variables. We conclude that a multivariate perspective is necessary in order to appropriately assess changes in climate extremes and their impacts, and to design adaptation strategies.

Goal oriented soil mapping: applying modern methods supported by local knowledge: A review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Oliva, Marc; Estebaranz, Ferran; Depellegrin, Daniel; Novara, Agata; Cerda, Artemi; Menshov, Oleksandr

2017-04-01

In the recent years the amount of soil data available increased importantly. This facilitated the production of better and accurate maps, important for sustainable land management (Pereira et al., 2017). Despite these advances, the human knowledge is extremely important to understand the natural characteristics of the landscape. The knowledge accumulated and transmitted generation after generation is priceless, and should be considered as a valuable data source for soil mapping and modelling. The local knowledge and wisdom can complement the new advances in soil analysis. In addition, farmers are the most interested in the participation and incorporation of their knowledge in the models, since they are the end-users of the study that soil scientists produce. Integration of local community's vision and understanding about nature is assumed to be an important step to the implementation of decision maker's policies. Despite this, many challenges appear regarding the integration of local and scientific knowledge, since in some cases there is no spatial correlation between folk and scientific classifications, which may be attributed to the different cultural variables that influence local soil classification. The objective of this work is to review how modern soil methods incorporated local knowledge in their models. References Pereira, P., Brevik, E., Oliva, M., Estebaranz, F., Depellegrin, D., Novara, A., Cerda, A., Menshov, O. (2017) Goal Oriented soil mapping: applying modern methods supported by local knowledge. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Bilateral macrodystrophia lipomatosa of the upper extremities with syndactyly and multiple lipomas.

PubMed

van der Meer, Saskia; Nicolai, Jean-Philippe A; Schut, Simone M; Meek, Marcel F

2011-12-01

Macrodystrophia lipomatosa is a rare disease that causes congenital local gigantism of part of an extremity, which is characterised by an increase in all mesenchymal elements, particularly fibroadipose tissue. This is the first report to our knowledge of a case of histologically confirmed bilateral macrodystrophia lipomatosa of the upper extremities with syndactyly and multiple lipomas.

Management of Chronic Pain of Cervical Disc Herniation and Radiculitis with Fluoroscopic Cervical Interlaminar Epidural Injections

PubMed Central

Manchikanti, Laxmaiah; Cash, Kimberly A.; Pampati, Vidyasagar; Wargo, Bradley W.; Malla, Yogesh

2012-01-01

Study Design: A randomized, double-blind, active controlled trial. Objective: To evaluate the effectiveness of cervical interlaminar epidural injections of local anesthetic with or without steroids in the management of chronic neck pain and upper extremity pain in patients with disc herniation and radiculitis. Summary of Background Data: Epidural injections in managing chronic neck and upper extremity pain are commonly employed interventions. However, their long-term effectiveness, indications, and medical necessity, of their use and their role in various pathologies responsible for persistent neck and upper extremity pain continue to be debated, even though, neck and upper extremity pain secondary to disc herniation and radiculitis, is described as the common indication. There is also paucity of high quality literature. Methods: One-hundred twenty patients were randomly assigned to one of 2 groups: Group I patients received cervical interlaminar epidural injections of local anesthetic (lidocaine 0.5%, 5 mL); Group II patients received 0.5% lidocaine, 4 mL, mixed with 1 mL of nonparticulate betamethasone. Primary outcome measure was ≥ 50 improvement in pain and function. Outcome assessments included Numeric Rating Scale (NRS), Oswestry Disability Index (ODI), opioid intake, employment, and changes in weight. Results: Significant pain relief and functional status improvement (≥ 50%) was demonstrated in 72% of patients who received local anesthetic only and 68% who received local anesthetic and steroids. In the successful group of participants, significant improvement was illustrated in 77% in local anesthetic group and 82% in local anesthetic with steroid group. Conclusions: Cervical interlaminar epidural injections with or without steroids may provide significant improvement in pain and function for patients with cervical disc herniation and radiculitis. PMID:22859902

Management of chronic pain of cervical disc herniation and radiculitis with fluoroscopic cervical interlaminar epidural injections.

PubMed

Manchikanti, Laxmaiah; Cash, Kimberly A; Pampati, Vidyasagar; Wargo, Bradley W; Malla, Yogesh

2012-01-01

A randomized, double-blind, active controlled trial. To evaluate the effectiveness of cervical interlaminar epidural injections of local anesthetic with or without steroids in the management of chronic neck pain and upper extremity pain in patients with disc herniation and radiculitis. Epidural injections in managing chronic neck and upper extremity pain are commonly employed interventions. However, their long-term effectiveness, indications, and medical necessity, of their use and their role in various pathologies responsible for persistent neck and upper extremity pain continue to be debated, even though, neck and upper extremity pain secondary to disc herniation and radiculitis, is described as the common indication. There is also paucity of high quality literature. One-hundred twenty patients were randomly assigned to one of 2 groups: Group I patients received cervical interlaminar epidural injections of local anesthetic (lidocaine 0.5%, 5 mL); Group II patients received 0.5% lidocaine, 4 mL, mixed with 1 mL of nonparticulate betamethasone. Primary outcome measure was ≥ 50 improvement in pain and function. Outcome assessments included Numeric Rating Scale (NRS), Oswestry Disability Index (ODI), opioid intake, employment, and changes in weight. Significant pain relief and functional status improvement (≥ 50%) was demonstrated in 72% of patients who received local anesthetic only and 68% who received local anesthetic and steroids. In the successful group of participants, significant improvement was illustrated in 77% in local anesthetic group and 82% in local anesthetic with steroid group. Cervical interlaminar epidural injections with or without steroids may provide significant improvement in pain and function for patients with cervical disc herniation and radiculitis.

The Portuguese Climate Portal

NASA Astrophysics Data System (ADS)

Gomes, Sandra; Deus, Ricardo; Nogueira, Miguel; Viterbo, Pedro; Miranda, Miguel; Antunes, Sílvia; Silva, Alvaro; Miranda, Pedro

2016-04-01

The Portuguese Local Warming Website (http://portaldoclima.pt) has been developed in order to support the society in Portugal in preparing for the adaptation to the ongoing and future effects of climate change. The climate portal provides systematic and easy access to authoritative scientific data ready to be used by a vast and diverse user community from different public and private sectors, key players and decision makers, but also to high school students, contributing to the increase in knowledge and awareness on climate change topics. A comprehensive set of regional climate variables and indicators are computed, explained and graphically presented. Variables and indicators were built in agreement with identified needs after consultation of the relevant social partners from different sectors, including agriculture, water resources, health, environment and energy and also in direct cooperation with the Portuguese National Strategy for Climate Change Adaptation (ENAAC) group. The visual interface allows the user to dynamically interact, explore, quickly analyze and compare, but also to download and import the data and graphics. The climate variables and indicators are computed from state-of-the-art regional climate model (RCM) simulations (e.g., CORDEX project), at high space-temporal detail, allowing to push the limits of the projections down to local administrative regions (NUTS3) and monthly or seasonal periods, promoting local adaptation strategies. The portal provides both historical data (observed and modelled for the 1971-2000 period) and future climate projections for different scenarios (modelled for the 2011-2100 period). A large effort was undertaken in order to quantify the impacts of the risk of extreme events, such as heavy rain and flooding, droughts, heat and cold waves, and fires. Furthermore the different climate scenarios and the ensemble of RCM models, with high temporal (daily) and spatial (~11km) detail, is taken advantage in order to quantify a plausible evolution of climate impacts and its uncertainties. Clear information on the data value and limitations is also provided. The portal is expected to become a reference tool for evaluation of impacts and vulnerabilities due to climate change, increased awareness and promotion of local adaptation and sustainable development in Portugal. The Portuguese Local Warming Website is part of the ADAPT programme, and is co-funded by the EEA financial mechanism and the Portuguese Carbon Fund.

Mapping the world's tropical cyclone rainfall contribution over land using TRMM satellite data: precipitation budget and extreme rainfall

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2012-12-01

A study was performed to characterize over-land precipitation associated with tropical cyclones (TCs) for basins around the world gathered in the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2010, rainfall data from TRMM 3B42, showed that TCs accounted for 8-, 11-, 7-, 10-, and 12-% of the annual over-land precipitation for North America, East Asia, Northern Indian Ocean, Australia, and South-West Indian Ocean respectively, and that TC-contribution decreased importantly within the first 150-km from the coast. At the local scale, TCs contributed on average to more than 40% and up to 77% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. The East Asia domain presented the higher and most constant TC-rain (170±23%-mm/yr) normalized over the area impacted, while the Southwest Indian domain presented the highest variability (130±48%-mm/yr), and the North American domain displayed the lowest average TC-rain (77±27%-mm/yr) despite a higher TC-activity. The maximum monthly TC-contribution (11-15%) was found later in the TC-season and was a conjunction between the peak of TC-activity, TC-rainfall, and the domain annual antagonism between dry and wet regimes if any. Furthermore, TC-days that accounted globally for 2±0.5% of all precipitation events for all basins, represented between 11-30% of rainfall extremes (>101.6mm/day). Locally, TC-rainfall was linked with the majority (>70%) or the quasi-totality (≈100%) of extreme rainfall. Finally, because of their importance in terms of rainfall amount, the contribution of tropical cyclones is provided for a selection of fifty urban areas experiencing cyclonic activity. Cases studies conducted at the regional scale will focus on the link between TC-activity, water resources, and hydrohazards such as floods and droughts.

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America.

PubMed

Vörösmarty, Charles J; Bravo de Guenni, Lelys; Wollheim, Wilfred M; Pellerin, Brian; Bjerklie, David; Cardoso, Manoel; D'Almeida, Cassiano; Green, Pamela; Colon, Lilybeth

2013-11-13

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960-2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

Regionally dependent summer heat wave response to increased surface temperature in the US

NASA Astrophysics Data System (ADS)

Lopez, H.; Dong, S.; Kirtman, B. P.; Goni, G. J.; Lee, S. K.; Atlas, R. M.; West, R.

2017-12-01

Climate projections for the 21st Century suggest an increase in the occurrence of heat waves. However, the time it takes for the externally forced signal of climate change to emerge against the background of natural variability (i.e., Time of Emergence, ToE) particularly on the regional scale makes reliable future projection of heat waves challenging. Here, we combine observations and model simulations under present and future climate forcing to assess internal variability versus external forcing in modulating US heat waves. We characterized the most common heat wave patterns over the US by the use of clustering of extreme events by their spatial distribution. For each heat wave cluster, we assess changes in the probability density function (PDF) of summer temperature extremes by modeling the PDF as a stochastically generated skewed (SGS) distribution. The probability of necessary causation for each heat wave cluster was also quantified, allowing to make assessments of heat extreme attribution to anthropogenic climate change. The results suggest that internal variability will dominate heat wave occurrence over the Great Plains with ToE occurring in the 2050s (2070s) and of occurrence of ratio of warm-to-cold extremes of 1.7 (1.7) for the Northern (Southern) Plains. In contrast, external forcing will dominate over the Western (Great Lakes) region with ToE occurring as early as in the 2020s (2030s) and warm-to-cold extremes ratio of 6.4 (10.2), suggesting caution in attributing heat extremes to external forcing due to their regional dependence.

Spatiotemporal variation in heat-related out-of-hospital cardiac arrest during the summer in Japan.

PubMed

Onozuka, Daisuke; Hagihara, Akihito

2017-04-01

Although several studies have reported the impacts of extremely high temperature on cardiovascular diseases, few studies have investigated the spatiotemporal variation in the incidence of out-of-hospital cardiac arrest (OHCA) due to extremely high temperature in Japan. Daily OHCA data from 2005 to 2014 were acquired from all 47 prefectures of Japan. We used time-series Poisson regression analysis combined with a distributed lag non-linear model to assess the temporal variability in the effects of extremely high temperature on OHCA incidence in each prefecture, adjusted for time trends. Spatial variability in the relationships between extremely high temperature and OHCA between prefectures was estimated using a multivariate random-effects meta-analysis. We analyzed 166,496 OHCA cases of presumed cardiac origin occurring during the summer (June to September) that met the inclusion criteria. The minimum morbidity percentile (MMP) was the 51st percentile of temperature during the summer in Japan. The overall cumulative relative risk at the 99th percentile vs. the MMP over lags 0-10days was 1.21 (95% CI: 1.12-1.31). There was also a strong low temperature effect during the summer periods. No substantial difference in spatial or temporal variability was observed over the study period. Our study demonstrated spatiotemporal homogeneity in the risk of OHCA during periods of extremely high temperature between 2005 and 2014 in Japan. Our findings suggest that public health strategies for OHCA due to extremely high temperatures should be finely adjusted and should particularly account for the unchanging risk during the summer. Copyright © 2017 Elsevier B.V. All rights reserved.

Seasonal precipitation extreme indices in mainland Portugal: trends and variability in the period 1941-2007

NASA Astrophysics Data System (ADS)

Santo, Fátima E.; Ramos, Alexandre M.; de Lima, M. Isabel P.; Trigo, Ricardo M.

2013-04-01

Changes in the precipitation regimes are expected to be accompanied by variations in the occurrence of extreme events, which in turn could be related to low frequency variability. The impact on the society and environment requires that the regional specificities are understood. For mainland Portugal, this work reports the results of the analysis of trends in selected precipitation indices calculated from daily precipitation data from 57 meteorological stations, recorded in the period 1941-2007; additionally we have also investigated the correlations between these indices and several modes of low frequency variability over the area. We focus on exploring regional differences and seasonal variations in the intensity, frequency and duration of extreme precipitation events. The precipitation indices were assessed at the seasonal scale and calculated at both the station and regional scales. Results sometimes highlight marked changes in seasonal precipitation and show that: i) trends in spring and autumn have opposite signals: statistically significant drying trends in the spring are accompanied by a reduction in precipitation extremes; in autumn, wetting trends are detected for all precipitation indices, although overall they are not significant at the 5% level; ii) there seems to be a tendency for a reduction in the duration of the rainy season; iii) the North Atlantic Oscillation (NAO) is the mode of variability that has the highest influence on precipitation extremes over mainland Portugal, particularly in the winter and autumn, and is one of the most important teleconnection patterns in all seasons. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) through project STORMEx FCOMP-01-0124-FEDER-019524 (PTDC/AAC-CLI/121339/2010).

Observed variability of summer precipitation pattern and extreme events in East China associated with variations of the East Asian summer monsoon: VARIABILITY OF SUMMER PRECIPITATION AND EXTREME EVENT IN EAST CHINA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Lei; Qian, Yun; Zhang, Yaocun

This paper presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in China associated with variations of the East Asian summer monsoon (EASM) from 1979-2012. A high-quality daily precipitation dataset covering 2287 weather stations in China is analyzed. Based on the precipitation pattern analysis using empirical orthogonal functions, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation,more » the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport that contributes most to the precipitation anomalies. Lastly, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean that influences deep convection over the oceans.« less

Evaluating wind extremes in CMIP5 climate models

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Mishra, Vimal; Ganguly, Auroop R.

2015-07-01

Wind extremes have consequences for renewable energy sectors, critical infrastructures, coastal ecosystems, and insurance industry. Considerable debates remain regarding the impacts of climate change on wind extremes. While climate models have occasionally shown increases in regional wind extremes, a decline in the magnitude of mean and extreme near-surface wind speeds has been recently reported over most regions of the Northern Hemisphere using observed data. Previous studies of wind extremes under climate change have focused on selected regions and employed outputs from the regional climate models (RCMs). However, RCMs ultimately rely on the outputs of global circulation models (GCMs), and the value-addition from the former over the latter has been questioned. Regional model runs rarely employ the full suite of GCM ensembles, and hence may not be able to encapsulate the most likely projections or their variability. Here we evaluate the performance of the latest generation of GCMs, the Coupled Model Intercomparison Project phase 5 (CMIP5), in simulating extreme winds. We find that the multimodel ensemble (MME) mean captures the spatial variability of annual maximum wind speeds over most regions except over the mountainous terrains. However, the historical temporal trends in annual maximum wind speeds for the reanalysis data, ERA-Interim, are not well represented in the GCMs. The historical trends in extreme winds from GCMs are statistically not significant over most regions. The MME model simulates the spatial patterns of extreme winds for 25-100 year return periods. The projected extreme winds from GCMs exhibit statistically less significant trends compared to the historical reference period.

Trends in Cold Extremes and Winter Weather for the SPTC Region

DOT National Transportation Integrated Search

2017-05-31

Extreme weather poses multifaceted hazards to transportation. There is now increased awareness of the threats of climate variability and change on transportation safety and state of good repair. In particular, a non-stationary climate will potentiall...

Climate models predict increasing temperature variability in poor countries.

PubMed

Bathiany, Sebastian; Dakos, Vasilis; Scheffer, Marten; Lenton, Timothy M

2018-05-01

Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C -1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate.

Climate models predict increasing temperature variability in poor countries

PubMed Central

Dakos, Vasilis; Scheffer, Marten

2018-01-01

Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C−1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate. PMID:29732409

Asymmetrical Responses of Ecosystem Processes to Positive Versus Negative Precipitation Extremes: a Replicated Regression Experimental Approach

NASA Astrophysics Data System (ADS)

Felton, A. J.; Smith, M. D.

2016-12-01

Heightened climatic variability due to atmospheric warming is forecast to increase the frequency and severity of climate extremes. In particular, changes to interannual variability in precipitation, characterized by increases in extreme wet and dry years, are likely to impact virtually all terrestrial ecosystem processes. However, to date experimental approaches have yet to explicitly test how ecosystem processes respond to multiple levels of climatic extremity, limiting our understanding of how ecosystems will respond to forecast increases in the magnitude of climate extremes. Here we report the results of a replicated regression experimental approach, in which we imposed 9 and 11 levels of growing season precipitation amount and extremity in mesic grassland during 2015 and 2016, respectively. Each level corresponded to a specific percentile of the long-term record, which produced a large gradient of soil moisture conditions that ranged from extreme wet to extreme dry. In both 2015 and 2016, asymptotic responses to water availability were observed for soil respiration. This asymmetry was driven in part by transitions between soil moisture versus temperature constraints on respiration as conditions became increasingly dry versus increasingly wet. In 2015, aboveground net primary production (ANPP) exhibited asymmetric responses to precipitation that largely mirrored those of soil respiration. In total, our results suggest that in this mesic ecosystem, these two carbon cycle processes were more sensitive to extreme drought than to extreme wet years. Future work will assess ANPP responses for 2016, soil nutrient supply and physiological responses of the dominant plant species. Future efforts are needed to compare our findings across a diverse array of ecosystem types, and in particular how the timing and magnitude of precipitation events may modify the response of ecosystem processes to increasing magnitudes of precipitation extremes.

Temperature extremes in Alaska: temporal variability and circulation background

NASA Astrophysics Data System (ADS)

Sulikowska, Agnieszka; Walawender, Jakub P.; Walawender, Ewelina

2018-06-01

The aims of this study are to characterize the spatial and temporal variability of extremely warm days (WDs) and warm spells (WSs) in summer as well as extremely cold days (CDs) and cold spells (CSs) in winter in Alaska in the years 1951-2015 and to determine the role of atmospheric circulation in their occurrence. The analysis is performed using daily temperature maxima (T MAX) and minima (T MIN) measured at 10 weather stations in Alaska as well as mean daily values of sea level pressure and wind direction at the 850 hPa isobaric level. WD (CD) is defined as a day with T MAX above the 95th (T MIN below the 5th) percentile of a probability density function calculated from observations, and WS (CS) equals at least three consecutive WDs (CDs). Frequency of the occurrence and severity of warm and cold extremes as well as duration of WSs and CSs is analyzed. In order to characterize synoptic conditions during temperature extremes, the objective classification scheme of advection types considering jointly the direction of the air influx and type of pressure system is employed. The results show that the general trend is towards the warmer temperatures, and the warming is greater in the winter than summer and for T MAX as opposed to T MIN. This is reflected in changes in the frequency of occurrence and intensity of temperature extremes which are much more pronounced in the case of winter cold extremes (decreasing tendencies) than summer warm extremes (increasing tendencies). The occurrence of temperature extremes is generally favored by anticyclonic weather with advection direction indicating air mass flows from the interior of the North American continent as well as the south (warm extremes in summer) and north (cold extremes in winter).

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

NASA Astrophysics Data System (ADS)

Lenderink, Geert; Attema, Jisk

2015-08-01

Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change.

A dependence modelling study of extreme rainfall in Madeira Island

NASA Astrophysics Data System (ADS)

Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

2016-08-01

The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

Mitigating Climate Change with Earth Orbital Sunshades

NASA Technical Reports Server (NTRS)

Coverstone, Victoria; Johnson, Les

2015-01-01

An array of rotating sunshades based on emerging solar sail technology will be deployed in a novel Earth orbit to provide near-continuous partial shading of the Earth, reducing the heat input to the atmosphere by blocking a small percentage of the incoming sunlight, and mitigating local weather effects of anticipated climate change over the next century. The technology will provide local cooling relief during extreme heat events (and heating relief during extreme cold events) thereby saving human lives, agriculture, livestock, water and energy needs. A synthesis of the solar sail design, the sails' operational modes, and the selected orbit combine to provide local weather modification.

A Projection of Changes in Landfilling Atmospheric River Frequency and Extreme Precipitation over Western North America from the Large Ensemble CESM Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson M.; Leung, Lai-Yung R.; Yoon, Jin-Ho

Simulations from the Community Earth System Model Large Ensemble project are analyzed to investigate the impact of global warming on atmospheric rivers (ARs). The model has notable biases in simulating the subtropical jet position and the relationship between extreme precipitation and moisture transport. After accounting for these biases, the model projects an ensemble mean increase of 35% in the number of landfalling AR days between the last twenty years of the 20th and 21st centuries. However, the number of AR associated extreme precipitation days increases only by 28% because the moisture transport required to produce extreme precipitation also increases withmore » warming. Internal variability introduces an uncertainty of ±8% and ±7% in the projected changes in AR days and associated extreme precipitation days. In contrast, accountings for model biases only change the projected changes by about 1%. The significantly larger mean changes compared to internal variability and to the effects of model biases highlight the robustness of AR responses to global warming.« less

The Second American Society of Regional Anesthesia and Pain Medicine Evidence-Based Medicine Assessment of Ultrasound-Guided Regional Anesthesia: Executive Summary.

PubMed

Neal, Joseph M; Brull, Richard; Horn, Jean-Louis; Liu, Spencer S; McCartney, Colin J L; Perlas, Anahi; Salinas, Francis V; Tsui, Ban Chi-Ho

2016-01-01

In 2009 and again in 2012, the American Society of Regional Anesthesia and Pain Medicine assembled an expert panel to assess the evidence basis for ultrasound guidance as a nerve localization tool for regional anesthesia. The 2012 panel reviewed evidence from the first advisory but focused primarily on new information that had emerged since 2009. A new section was added regarding the accuracy and reliability of ultrasound for determining needle-to-nerve proximity. Jadad scores are used to rank study quality. Grades of recommendations consistent with their level of evidence are provided. The panel offers recommendations based on synthesis and analysis of literature related to (1) the technical capabilities of ultrasound equipment and its operators, (2) comparison of ultrasound to other methods of nerve localization with regard to block characteristics, (3) comparison of block techniques where ultrasound is the sole nerve localization modality, and (4) major complications. Assessment of evidence strength and recommendations are made for upper- and lower-extremity, truncal, neuraxial, and pediatric blocks. Scientific evidence from the past 5 years has clarified and strengthened our understanding of ultrasound-guided regional anesthesia as a nerve localization tool. High-level evidence supports ultrasound guidance contributing to superior characteristics with selected blocks, although absolute differences with the comparator technique are often relatively small (especially for upper-extremity blocks). The clinical meaningfulness of these differences is likely of variable importance to individual practitioners. The use of ultrasound significantly reduces the risk of local anesthetic systemic toxicity as well as the incidence and intensity of hemidiaphragmatic paresis, but has no significant effect on the incidence of postoperative neurologic symptoms. WHAT'S NEW IN THIS UPDATE?: This evidence-based assessment of ultrasound-guided regional anesthesia reviews findings from our 2010 publication and focuses on new meta-analyses, randomized controlled trials, and large case series published since 2009. New to this exercise is an in-depth analysis of the accuracy and reliability of ultrasound guidance for identifying needle-to-nerve relationships. This version no longer addresses ultrasound for interventional pain medicine procedures, because the growth of that field demands separate consideration. Since our 2010 publication, new information has either supported or strengthened our original conclusions. There is no evidence that ultrasound is inferior to alternative nerve localization methods.

The photonic device for integrated evaluation of collateral circulation of lower extremities in patients with local hypertensive-ischemic pain syndrome

NASA Astrophysics Data System (ADS)

Pavlov, Volodymyr S.; Bezsmernyi, Yurii O.; Zlepko, Sergey M.; Bezsmertna, Halyna V.

2017-08-01

The given paper analyzes principles of interaction and analysis of the reflected optical radiation from biotissue in the process of assessment of regional hemodynamics state in patients with local hypertensive- ischemic pain syndrome of amputation stumps of lower extremities, applying the method of photoplethysmography. The purpose is the evaluation of Laser photoplethysmography (LPPG) diagnostic value in examination of patients with chronic ischemia of lower extremities. Photonic device is developed to determine the level of the peripheral blood circulation, which determines the basic parameters of peripheral blood circulation and saturation level. Device consists of two sensors: infrared sensor, which contains the infrared laser radiation source and photodetector, and red sensor, which contains the red radiation source and photodetector. LPPG method allows to determined pulsatility of blood flow in different areas of the foot and lower leg, the degree of compensation and conservation perspectives limb. Surgical treatment of local hypertensive -ischemic pain syndrome of amputation stumps of lower extremities by means of semiclosed fasciotomy in combination with revasculating osteotrepanation enabled to improve considerably regional hemodynamics in the tissues of the stump and decrease pain and hypostatic disorders.

Enhanced hydrological extremes in the western United States under global warming through the lens of water vapor wave activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Jian; Xue, Daokai; Gao, Yang

Understanding how regional hydrological extremes would respond to warming is a grand challenge to the community of climate change research. To address this challenge, we construct an analysis framework based on column integrated water vapor (CWV) wave activity to diagnose the wave component of the hydrological cycle that contributes to hydrological extremes. By applying the analysis to the historical and future climate projections from the CMIP5 models, we found that the wet-versus-dry disparity of daily net precipitation along a zonal band can increase at a super Clausius-Clapeyron rate due to the enhanced stirring length of wave activity at the polewardmore » flank of the mean storm track. The local variant of CWV wave activity reveals the unique characteristics of atmospheric rivers (ARs) in terms of their transport function, enhanced mixing and hydrological cycling rate (HC). Under RCP8.5, the local moist wave activity increases by ~40% over the northeastern Pacific by the end of the 21st century, indicating more ARs hitting the west coast, giving rise to a ~20% increase in the related hydrological extremes - $ despite a weakening of the local HC.« less

Investigating Extreme Lifestyles through Mangrove Transcriptomics

ERIC Educational Resources Information Center

Dassanayake, Maheshi

2009-01-01

Mangroves represent phylogenetically diverse taxa in tropical coastal terrestrial habitats. They are extremophiles, evolutionarily adapted to tolerate flooding, anoxia, high temperatures, wind, and high and extremely variable salt conditions in typically resource-poor environments. The genetic basis for these adaptations is, however, virtually…

Steroid Signaling and Temperature-Dependent Sex Determination – Reviewing the Evidence for Early Action of Estrogen during Ovarian Determination in the Red-Eared Slider Turtle (Trachemys scripta elegans)

PubMed Central

Ramsey, Mary; Crews, David

2009-01-01

The developmental processes underlying gonadal differentiation are conserved across vertebrates, but the triggers initiating these trajectories are extremely variable. The red-eared slider turtle (Trachemys scripta elegans) exhibits temperature-dependent sex determination (TSD), a system where incubation temperature during a temperature-sensitive period of development determines offspring sex. However, gonadal sex is sensitive to both temperature and hormones during this period – particularly estrogen. We present a model for temperature-based differences in aromatase expression as a critical step in ovarian determination. Localized estrogen production facilitates ovarian development while inhibiting male-specific gene expression. At male-producing temperatures aromatase is not upregulated, thereby allowing testis development. PMID:18992835

Impacts of climate extremes on gross primary production under global warming

DOE PAGES

Williams, I. N.; Torn, M. S.; Riley, W. J.; ...

2014-09-24

The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at themore » warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections, and the time taken to return to locally optimal climates for GPP following climate extremes increases by more than 25% over many land regions.« less

Impacts of climate extremes on gross primary production under global warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, I. N.; Torn, M. S.; Riley, W. J.

The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at themore » warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections, and the time taken to return to locally optimal climates for GPP following climate extremes increases by more than 25% over many land regions.« less

Variations/Changes in Daily Precipitation Extremes Derived from Satellite-Based Products

NASA Astrophysics Data System (ADS)

Gu, G.; Adler, R. F.

2017-12-01

Interannual/decadal-scale variations/changes in daily precipitation extremes are investigated by means of satellite-based high-spatiotemporal resolution precipitation products, including TRMM-TMPA, PERSIANN-CDR-Daily, GPCP 1DD, etc. Extreme precipitation indices at grids are first defined, including the maximum daily precipitation amount (Rx1day), the simple precipitation intensity index (SDII), the conditional (Rcond) daily precipitation rate (Pr>0 mm day-1), and monthly frequencies of rainy (FOCc) and wet (FOCw) days. Other two precipitation intensity indices, i.e., mean daily precipitation rates for Pr ≥10 mm day-1 (Pr10II) and for Pr ≥ 20 mm day-1 (Pr20II), are also constructed. Consistency analyses of daily extreme indices among these data sets are then performed by comparing corresponding averages over large domains such as tropical (30oN-30oS) land, ocean, land+ocean, for their common period (post-1997). This can provide a preliminary uncertainty analysis of these data sets in describing daily extreme precipitation events. Discrepancies can readily be found among these products regarding the magnitudes of area-averaged extreme indices. However, generally consistent temporal variations can be found among the indices derived from different satellite products. Interannual variability in daily precipitation extremes are then examined and compared at grids by exploring their relations with the El Nino-Southern Oscillation (ENSO). Linear correlation and composite analyses are used to examine the impact of ENSO on these extreme indices at grids and over large domains during the post-1997 period. Decadal-scale variability/change in daily extreme events is further examined by using the PERSIANN-CDR-Daily that can cover the entire post-1983 period, based on its general consistency with other two products during the post-1979 period. We specifically focus on exploring and discriminating the effects of decadal-scale internal variability such as the Pacific Decadal Oscillation (PDO) and anthropogenic forcings including the greenhouse-gases (GHG) related warming. Comparisons are also made over global land with the results from two gridded daily rain-gauge products, GPCC Full-record daily (1988-2013) and NOAA/CPC Unified daily (1979-present).

Climate-water quality relationships in Texas reservoirs

USGS Publications Warehouse

Gelca, Rodica; Hayhoe, Katharine; Scott-Fleming, Ian; Crow, Caleb; Dawson, D.; Patino, Reynaldo

2015-01-01

Water temperature, dissolved oxygen, and concentrations of salts in surface water bodies can be affected by the natural environment, local human activities such as surface and ground water withdrawals, land use, and energy extraction, and variability and long-term trends in atmospheric conditions including temperature and precipitation. Here, we quantify the relationship between 121 indicators of mean and extreme temperature and precipitation and 24 water quality parameters in 57 Texas reservoirs using observational data records covering the period 1960 to 2010. We find that water temperature, dissolved oxygen, pH, specific conductance, chloride, sulfate, and phosphorus all show consistent correlations with atmospheric predictors, including high and low temperature extremes, dry days, heavy precipitation events, and mean temperature and precipitation over time scales ranging from one week to two years. Based on this analysis and published future projections for this region, we expect climate change to increase water temperatures, decrease dissolved oxygen levels, decrease pH, increase specific conductance, and increase levels of sulfate, chloride in Texas reservoirs. Over decadal time scales, this may affect aquatic ecosystems in the reservoirs, including altering the risk of conditions conducive to algae occurrence, as well as affecting the quality of water available for human consumption and recreation.

Depth as an organizer of fish assemblages in floodplain lakes

USGS Publications Warehouse

Miranda, L.E.

2011-01-01

Depth reduction is a natural process in floodplain lakes, but in many basins has been accelerated by anthropogenic disturbances. A diverse set of 42 floodplain lakes in the Yazoo River Basin (Mississippi, USA) was examined to test the hypothesis of whether depth reduction was a key determinant of water quality and fish assemblage structure. Single and multiple variable analyses were applied to 10 commonly monitored water variables and 54 fish species. Results showed strong associations between depth and water characteristics, and between depth and fish assemblages. Deep lakes provided less variable environments, clearer water, and a wider range of microhabitats than shallow lakes. The greater environmental stability was reflected by the dominant species in the assemblages, which included a broader representation of large-body species, species less tolerant of extreme water quality, and more predators. Stability in deep lakes was further reflected by reduced among-lake variability in taxa representation. Fish assemblages in shallow lakes were more variable than deep lakes, and commonly dominated by opportunistic species that have early maturity, extended breeding seasons, small adult size, and short lifespan. Depth is a causal factor that drives many physical and chemical variables that contribute to organizing fish assemblages in floodplain lakes. Thus, correlations between fish and water transparency, temperature, oxygen, trophic state, habitat structure, and other environmental descriptors may ultimately be totally or partly regulated by depth. In basins undergoing rapid anthropogenic modifications, local changes forced by depth reductions may be expected to eliminate species available from the regional pool and could have considerable ecological implications. ?? 2010 Springer Basel AG (outside the USA).

Vegetation change, malnutrition and violence in the Horn of Africa

NASA Astrophysics Data System (ADS)

Rowhani, P.; Degomme, O.; Linderman, M.; Guha-Sapir, D.; Lambin, E.

2008-12-01

In certain circumstances, climate change in association with a broad range of social factors may increase the risk of famines and subsequently, violent conflict. The impacts of climate change on society will be experienced both through changes in mean conditions over long time periods and through increases in extreme events. Recent studies have shown the historical effects of long term climate change on societies and the importance of short term climatic triggers on armed conflict. However, most of these studies are at the state level ignoring local conditions. Here we use detailed information extracted from wide-swath satellite data (MODIS) to analyze the impact of climate variability change on malnutrition and violent conflict. More specifically, we perform multivariate logistic regression analysis in order to explain the geographical distribution of malnutrition and conflict in the Horn of Africa on a sub-national level. This region, constituted by several unstable and poor states, has been affected by droughts, floods, famines, and violence in the past few years. Three commonly used nutrition and mortality indicators are used to characterize the health situation (CE-DAT database). To map violence we use the georeferenced Armed Conflicts dataset developed by the Center for the Study of Civil War. Explanatory variables include several socio-economic variables and environmental variables characterizing land degradation, vegetation activity, and interannual variability in land-surface conditions. First results show that interannual variability in land-surface conditions is associated with malnutrition but not with armed conflict. Furthermore, land degradation seems not to be associated with either malnutrition or armed conflict.

Past exposure to climate extremes can inform future projections and guide management: coral reefs as a model system

NASA Astrophysics Data System (ADS)

Donner, S. D.

2016-12-01

Coral reefs are thought to be more sensitive to climate change than any other marine ecosystem. Episodes of mass coral bleaching, due to anomalously warm water temperatures, have led to coral mortality, declines in coral cover and shifts in the population of other reef-dwelling organisms. The onset of mass bleaching is typically predicted using accumulated heat stress, specifically when the SST exceeds a local climatological maximum by 1-2 °C for a month or more. However, recent evidence suggests that the threshold at which bleaching occurs depends on the past thermal experience of the coral reef and the composition of the coral community. This presentation describes the results of a long-term field and modelling research program evaluating the influence of climate experience on the susceptibility of coral reef ecosystems to future climate extremes. Modeling work identified Kiribati's equatorial Gilbert Islands, where the El Niño / Southern Oscillation drives year-to-year shifts in current strength, current direction and consequently ocean temperatures, as an ideal natural laboratory for studying ocean climate extremes. The field program then tracked changes in the coral communities over multiple heat stress events (e.g. 2004-5, 2009-10 El Niño) at a matrix of sites exposed to different levels of historical climate variability and human disturbance. Among the results is evidence that coral bleaching patterns are best predicted by the coefficient of variation of past SST, light exposure, and the presence of particular resilient coral taxa, rather than the standard heat stress metrics. The lessons of this research can be applicable other systems where past experience influences the response to climate extremes

Impacts of climate change on the world's most exceptional ecoregions

PubMed Central

Beaumont, Linda J.; Pitman, Andrew; Perkins, Sarah; Zimmermann, Niklaus E.; Yoccoz, Nigel G.; Thuiller, Wilfried

2011-01-01

The current rate of warming due to increases in greenhouse gas (GHG) emissions is very likely unprecedented over the last 10,000 y. Although the majority of countries have adopted the view that global warming must be limited to <2 °C, current GHG emission rates and nonagreement at Copenhagen in December 2009 increase the likelihood of this limit being exceeded by 2100. Extensive evidence has linked major changes in biological systems to 20th century warming. The “Global 200” comprises 238 ecoregions of exceptional biodiversity [Olson DM, Dinerstein E (2002) Ann Mo Bot Gard 89:199–224]. We assess the likelihood that, by 2070, these iconic ecoregions will regularly experience monthly climatic conditions that were extreme in 1961–1990. Using >600 realizations from climate model ensembles, we show that up to 86% of terrestrial and 83% of freshwater ecoregions will be exposed to average monthly temperature patterns >2 SDs (2σ) of the 1961–1990 baseline, including 82% of critically endangered ecoregions. The entire range of 89 ecoregions will experience extreme monthly temperatures with a local warming of <2 °C. Tropical and subtropical ecoregions, and mangroves, face extreme conditions earliest, some with <1 °C warming. In contrast, few ecoregions within Boreal Forests and Tundra biomes will experience such extremes this century. On average, precipitation regimes do not exceed 2σ of the baseline period, although considerable variability exists across the climate realizations. Further, the strength of the correlation between seasonal temperature and precipitation changes over numerous ecoregions. These results suggest many Global 200 ecoregions may be under substantial climatic stress by 2100. PMID:21262825

The nonstationary impact of local temperature changes and ENSO on extreme precipitation at the global scale

NASA Astrophysics Data System (ADS)

Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun

2017-12-01

The El Niño-Southern Oscillation (ENSO) and local temperature are important drivers of extreme precipitation. Understanding the impact of ENSO and temperature on the risk of extreme precipitation over global land will provide a foundation for risk assessment and climate-adaptive design of infrastructure in a changing climate. In this study, nonstationary generalized extreme value distributions were used to model extreme precipitation over global land for the period 1979-2015, with ENSO indicator and temperature as covariates. Risk factors were estimated to quantify the contrast between the influence of different ENSO phases and temperature. The results show that extreme precipitation is dominated by ENSO over 22% of global land and by temperature over 26% of global land. With a warming climate, the risk of high-intensity daily extreme precipitation increases at high latitudes but decreases in tropical regions. For ENSO, large parts of North America, southern South America, and southeastern and northeastern China are shown to suffer greater risk in El Niño years, with more than double the chance of intense extreme precipitation in El Niño years compared with La Niña years. Moreover, regions with more intense precipitation are more sensitive to ENSO. Global climate models were used to investigate the changing relationship between extreme precipitation and the covariates. The risk of extreme, high-intensity precipitation increases across high latitudes of the Northern Hemisphere but decreases in middle and lower latitudes under a warming climate scenario, and will likely trigger increases in severe flooding and droughts across the globe. However, there is some uncertainties associated with the influence of ENSO on predictions of future extreme precipitation, with the spatial extent and risk varying among the different models.

Multiple approaches to detect outliers in a genome scan for selection in ocellated lizards (Lacerta lepida) along an environmental gradient.

PubMed

Nunes, Vera L; Beaumont, Mark A; Butlin, Roger K; Paulo, Octávio S

2011-01-01

Identification of loci with adaptive importance is a key step to understand the speciation process in natural populations, because those loci are responsible for phenotypic variation that affects fitness in different environments. We conducted an AFLP genome scan in populations of ocellated lizards (Lacerta lepida) to search for candidate loci influenced by selection along an environmental gradient in the Iberian Peninsula. This gradient is strongly influenced by climatic variables, and two subspecies can be recognized at the opposite extremes: L. lepida iberica in the northwest and L. lepida nevadensis in the southeast. Both subspecies show substantial morphological differences that may be involved in their local adaptation to the climatic extremes. To investigate how the use of a particular outlier detection method can influence the results, a frequentist method, DFDIST, and a Bayesian method, BayeScan, were used to search for outliers influenced by selection. Additionally, the spatial analysis method was used to test for associations of AFLP marker band frequencies with 54 climatic variables by logistic regression. Results obtained with each method highlight differences in their sensitivity. DFDIST and BayeScan detected a similar proportion of outliers (3-4%), but only a few loci were simultaneously detected by both methods. Several loci detected as outliers were also associated with temperature, insolation or precipitation according to spatial analysis method. These results are in accordance with reported data in the literature about morphological and life-history variation of L. lepida subspecies along the environmental gradient. © 2010 Blackwell Publishing Ltd.

Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors.

PubMed

Heddam, Salim; Kisi, Ozgur

2017-07-01

In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R-ELM performed the best at one station. The OS-ELM models performed the worst and provided the lowest accuracy; (iii) for predicting DO without water quality variables, the R-ELM performed the best at seven stations followed by the S-ELM in the second place and the OP-ELM performed the worst with low accuracy; (iv) for the final application where training ELM models with validation dataset and testing with training dataset, the OP-ELM provided the best accuracy using water quality variables and the R-ELM performed the best at all eight stations without water quality variables. Fourthly, and finally, we compared the results obtained from different ELM models with those obtained using multiple linear regression (MLR) and multilayer perceptron neural network (MLPNN). Results obtained using MLPNN and MLR models reveal that: (i) using water quality variables as predictors, the MLR performed the worst and provided the lowest accuracy in all stations; (ii) MLPNN was ranked in the second place at two stations, in the third place at four stations, and finally, in the fourth place at two stations, (iii) for predicting DO without water quality variables, MLPNN is ranked in the second place at five stations, and ranked in the third, fourth, and fifth places in the remaining three stations, while MLR was ranked in the last place with very low accuracy at all stations. Overall, the results suggest that the ELM is more effective than the MLPNN and MLR for modelling DO concentration in river ecosystems.

Evaluation of the DSM-5 Severity Indicator for Bulimia Nervosa

PubMed Central

Grilo, Carlos M.; Ivezaj, Valentina; White, Marney A.

2015-01-01

This study examined the DSM-5 severity criterion for bulimia nervosa (BN) based on the frequency of inappropriate weight compensatory behaviors. 199 community volunteers classified with BN were categorized using DSM-5 severity levels and compared on demographic and clinical variables. 77 (39%) participants were categorized as mild, 68 (34%) as moderate, 32 (16%) as severe, and 22 (11%) as extreme. The severity groups did not differ significantly in demographic variables or body mass index. Shape and Weight concerns did not differ significantly across severity groups. Binge eating differed with the extreme group having higher frequency than the severe, moderate, and mild groups, which did not differ from each other. Restraint differed with the extreme group having significantly higher levels than the mild group. Eating concerns differed with the extreme group having higher levels than moderate and mild groups. Depression differed with the extreme group having higher levels than severe, moderate, and mild groups, which did not differ from each other. Findings from this non-clinical group provide new, albeit modest, support for DSM-5 severity rating for BN based on frequency of inappropriate weight compensatory behaviors. Statistical findings indicate that differences in collateral clinical variables associated with the DSM-5 severity ratings reflect small effect sizes. Further research is needed with treatment-seeking patient groups with BN to establish the validity of the DSM-5 severity specifier and should include broader clinical and functional validators. PMID:25744910

Evaluation of the DSM-5 severity indicator for bulimia nervosa.

PubMed

Grilo, Carlos M; Ivezaj, Valentina; White, Marney A

2015-04-01

This study examined the DSM-5 severity criterion for bulimia nervosa (BN) based on the frequency of inappropriate weight compensatory behaviors. 199 community volunteers classified with BN were categorized using DSM-5 severity levels and compared on demographic and clinical variables. 77 (39%) participants were categorized as mild, 68 (34%) as moderate, 32 (16%) as severe, and 22 (11%) as extreme. The severity groups did not differ significantly in demographic variables or body mass index. Shape and Weight concerns did not differ significantly across severity groups. Binge eating differed with the extreme group having significantly higher frequency than the severe, moderate, and mild groups, which did not differ from each other. Restraint differed with the extreme group having significantly higher levels than the mild group. Eating concerns differed with the extreme group having significantly higher levels than moderate and mild groups. Depression differed with the extreme group having significantly higher levels than severe, moderate, and mild groups, which did not differ from each other. Findings from this non-clinical group provide new, albeit modest, support for DSM-5 severity rating for BN based on frequency of inappropriate weight compensatory behaviors. Statistical findings indicate that differences in collateral clinical variables associated with the DSM-5 severity ratings reflect small effect sizes. Further research is needed with treatment-seeking patient groups with BN to establish the validity of the DSM-5 severity specifier and should include broader clinical and functional validators. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Variable-Selection Heuristic for K-Means Clustering.

ERIC Educational Resources Information Center

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

New Southern Cataclysmic Variables: Discoveries from MASTER-SAAO

NASA Astrophysics Data System (ADS)

Buckley, D. A. H.; Potter, S. B.; Kniazev, A.; Lipunov, V.; Gorbovskoy, E.; Tiurina, N.

2017-03-01

In this paper we report on new cataclysmic variables (CVs) discovered by the first local optical transient detection system established at the SAAO Sutherland station, namely MASTER-SAAO. The characteristics of the MASTER-SAAO system are described and the parameters of the survey compared to the Catalina Real Time Survey (CRTS). To date MASTER-SAAO has discovered over 200 (non-Solar System) optical transients with about 75% of these being likely new CVs, most being dwarf novae (DNe). Approximately 50% of the DNe have outburst amplitudes in excess of 4 magnitudes, with some extreme amplitude (> 7 mag), probable WZ Sge systems. The MASTER-SAAO detection limit of B = 19-20 is comparable to the ˜20 magnitude limit of the CRTS (depending on CV colour). Based on the CV detection statistics of CRTS, we believe that MASTER-SAAO is detecting essentially the same CV population as CRTS, for a detection outburst amplitude threshold >2.2 magnitudes. We also present results of the initial follow-up program on CVs discovered by MASTER, including dwarf novae, a bright new VY Scl system and a new eclipsing polar.

Noise-induced transitions and shifts in a climate-vegetation feedback model.

PubMed

Alexandrov, Dmitri V; Bashkirtseva, Irina A; Ryashko, Lev B

2018-04-01

Motivated by the extremely important role of the Earth's vegetation dynamics in climate changes, we study the stochastic variability of a simple climate-vegetation system. In the case of deterministic dynamics, the system has one stable equilibrium and limit cycle or two stable equilibria corresponding to two opposite (cold and warm) climate-vegetation states. These states are divided by a separatrix going across a point of unstable equilibrium. Some possible stochastic scenarios caused by different externally induced natural and anthropogenic processes inherit properties of deterministic behaviour and drastically change the system dynamics. We demonstrate that the system transitions across its separatrix occur with increasing noise intensity. The climate-vegetation system therewith fluctuates, transits and localizes in the vicinity of its attractor. We show that this phenomenon occurs within some critical range of noise intensities. A noise-induced shift into the range of smaller global average temperatures corresponding to substantial oscillations of the Earth's vegetation cover is revealed. Our analysis demonstrates that the climate-vegetation interactions essentially contribute to climate dynamics and should be taken into account in more precise and complex models of climate variability.

Scale problems in assessment of hydrogeological parameters of groundwater flow models

NASA Astrophysics Data System (ADS)

Nawalany, Marek; Sinicyn, Grzegorz

2015-09-01

An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i) spatial extent and geometry of hydrogeological system, (ii) spatial continuity and granularity of both natural and man-made objects within the system, (iii) duration of the system and (iv) continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale - scale of pores, meso-scale - scale of laboratory sample, macro-scale - scale of typical blocks in numerical models of groundwater flow, local-scale - scale of an aquifer/aquitard and regional-scale - scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical) block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here). Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.

Parametric Sensitivity Analysis of Precipitation at Global and Local Scales in the Community Atmosphere Model CAM5

DOE PAGES

Qian, Yun; Yan, Huiping; Hou, Zhangshuan; ...

2015-04-10

We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics.more » Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.« less

Extreme Precipitation and High-Impact Landslides

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa

2012-01-01

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing teleconnections from ENSO as likely contributors to regional precipitation variability. This work demonstrates the potential for using satellite-based precipitation estimates to identify potentially active landslide areas at the global scale in order to improve landslide cataloging and quantify landslide triggering at daily, monthly and yearly time scales.

Assessment and comparison of extreme sea levels and waves during the 2013/14 storm season in two UK coastal regions

NASA Astrophysics Data System (ADS)

Wadey, M. P.; Brown, J. M.; Haigh, I. D.; Dolphin, T.; Wisse, P.

2015-10-01

The extreme sea levels and waves experienced around the UK's coast during the 2013/14 winter caused extensive coastal flooding and damage. Coastal managers seek to place such extremes in relation to the anticipated standards of flood protection, and the long-term recovery of the natural system. In this context, return periods are often used as a form of guidance. This paper provides these levels for the winter storms, and discusses their application to the given data sets for two UK case study sites: Sefton, northwest England, and Suffolk, east England. Tide gauge records and wave buoy data were used to compare the 2013/14 storms with return periods from a national data set, and also joint probabilities of sea level and wave heights were generated, incorporating the recent events. The 2013/14 high waters and waves were extreme due to the number of events, as well as the extremity of the 5 December 2013 "Xaver" storm, which had a high return period at both case study sites. The national-scale impact of this event was due to its coincidence with spring high tide at multiple locations. Given that this event is such an outlier in the joint probability analyses of these observed data sets, and that the season saw several events in close succession, coastal defences appear to have provided a good level of protection. This type of assessment could in the future be recorded alongside defence performance and upgrade. Ideally other variables (e.g. river levels at estuarine locations) would also be included, and with appropriate offsetting for local trends (e.g. mean sea-level rise) so that the storm-driven component of coastal flood events can be determined. This could allow long-term comparison of storm severity, and an assessment of how sea-level rise influences return levels over time, which is important for consideration of coastal resilience in strategic management plans.

Studying Weather and Climate Extremes in a Non-stationary Framework

NASA Astrophysics Data System (ADS)

Wu, Z.

2010-12-01

The study of weather and climate extremes often uses the theory of extreme values. Such a detection method has a major problem: to obtain the probability distribution of extremes, one has to implicitly assume the Earth’s climate is stationary over a long period within which the climatology is defined. While such detection makes some sense in a purely statistical view of stationary processes, it can lead to misleading statistical properties of weather and climate extremes caused by long term climate variability and change, and may also cause enormous difficulty in attributing and predicting these extremes. To alleviate this problem, here we report a novel non-stationary framework for studying weather and climate extremes in a non-stationary framework. In this new framework, the weather and climate extremes will be defined as timescale-dependent quantities derived from the anomalies with respect to non-stationary climatologies of different timescales. With this non-stationary framework, the non-stationary and nonlinear nature of climate system will be taken into account; and the attribution and the prediction of weather and climate extremes can then be separated into 1) the change of the statistical properties of the weather and climate extremes themselves and 2) the background climate variability and change. The new non-stationary framework will use the ensemble empirical mode decomposition (EEMD) method, which is a recent major improvement of the Hilbert-Huang Transform for time-frequency analysis. Using this tool, we will adaptively decompose various weather and climate data from observation and climate models in terms of the components of the various natural timescales contained in the data. With such decompositions, the non-stationary statistical properties (both spatial and temporal) of weather and climate anomalies and of their corresponding climatologies will be analyzed and documented.

Intra-seasonal Characteristics of Wintertime Extreme Cold Events over South Korea

NASA Astrophysics Data System (ADS)

Park, Taewon; Jeong, Jeehoon; Choi, Jahyun

2017-04-01

The present study reveals the changes in the characteristics of extreme cold events over South Korea for boreal winter (November to March) in terms of the intra-seasonal variability of frequency, duration, and atmospheric circulation pattern. Influences of large-scale variabilities such as the Siberian High activity, the Arctic Oscillation (AO), and the Madden-Julian Oscillation (MJO) on extreme cold events are also investigated. In the early and the late of the winter during November and March, the upper-tropospheric wave-train for a life-cycle of the extreme cold events tends to pass quickly over East Asia. In addition, compared with the other months, the intensity of the Siberian High is weaker and the occurrences of strong negative AO are less frequent. It lead to events with weak amplitude and short duration. On the other hand, the amplified Siberian High and the strong negative AO occur more frequently in the mid of the winter from December to February. The extreme cold events are mainly characterized by a well-organized anticyclonic blocking around the Ural Mountain and the Subarctic. These large-scale circulation makes the extreme cold events for the midwinter last long with strong amplitude. The MJO phases 2-3 which provide a suitable condition for the amplification of extreme cold events occur frequently for November to January when the frequencies are more than twice those for February and March. While the extreme cold events during March have the least frequency, the weakest amplitude, and the shortest duration due to weak impacts of the abovementioned factors, the strong activities of the factors for January force the extreme cold events to be the most frequent, the strongest, and the longest among the boreal winter. Keywords extreme cold event, wave-train, blocking, Siberian High, AO, MJO

Heterogeneous Sensitivity of Tropical Precipitation Extremes during Growth and Mature Phases of Atmospheric Warming

NASA Astrophysics Data System (ADS)

Parhi, P.; Giannini, A.; Lall, U.; Gentine, P.

2016-12-01

Assessing and managing risks posed by climate variability and change is challenging in the tropics, from both a socio-economic and a scientific perspective. Most of the vulnerable countries with a limited climate adaptation capability are in the tropics. However, climate projections, particularly of extreme precipitation, are highly uncertain there. The CMIP5 (Coupled Model Inter- comparison Project - Phase 5) inter-model range of extreme precipitation sensitivity to the global temperature under climate change is much larger in the tropics as compared to the extra-tropics. It ranges from nearly 0% to greater than 30% across models (O'Gorman 2012). The uncertainty is also large in historical gauge or satellite based observational records. These large uncertainties in the sensitivity of tropical precipitation extremes highlight the need to better understand how tropical precipitation extremes respond to warming. We hypothesize that one of the factors explaining the large uncertainty is due to differing sensitivities during different phases of warming. We consider the `growth' and `mature' phases of warming under climate variability case- typically associated with an El Niño event. In the remote tropics (away from tropical Pacific Ocean), the response of the precipitation extremes during the two phases can be through different pathways: i) a direct and fast changing radiative forcing in an atmospheric column, acting top-down due to the tropospheric warming, and/or ii) an indirect effect via changes in surface temperatures, acting bottom-up through surface water and energy fluxes. We also speculate that the insights gained here might be useful in interpreting the large sensitivity under climate change scenarios, since the physical mechanisms during the two warming phases under climate variability case, have some correspondence with an increasing and stabilized green house gas emission scenarios.

Local Climate Experts: The Influence of Local TV Weather Information on Climate Change Perceptions

PubMed Central

Bloodhart, Brittany; Maibach, Edward; Myers, Teresa; Zhao, Xiaoquan

2015-01-01

Individuals who identify changes in their local climate are also more likely to report that they have personally experienced global climate change. One way that people may come to recognize that their local climate is changing is through information provided by local TV weather forecasters. Using random digit dialing, 2,000 adult local TV news viewers in Virginia were surveyed to determine whether routine exposure to local TV weather forecasts influences their perceptions of extreme weather in Virginia, and their perceptions about climate change more generally. Results indicate that paying attention to TV weather forecasts is associated with beliefs that extreme weather is becoming more frequent in Virginia, which in turn is associated with stronger beliefs and concerns about climate change. These associations were strongest for individuals who trust their local TV weathercaster as a source of information about climate change, and for those who identify as politically conservative or moderate. The findings add support to the literature suggesting that TV weathercasters can play an important role in educating the public about climate change. PMID:26551357

Local Climate Experts: The Influence of Local TV Weather Information on Climate Change Perceptions.

PubMed

Bloodhart, Brittany; Maibach, Edward; Myers, Teresa; Zhao, Xiaoquan

2015-01-01

Individuals who identify changes in their local climate are also more likely to report that they have personally experienced global climate change. One way that people may come to recognize that their local climate is changing is through information provided by local TV weather forecasters. Using random digit dialing, 2,000 adult local TV news viewers in Virginia were surveyed to determine whether routine exposure to local TV weather forecasts influences their perceptions of extreme weather in Virginia, and their perceptions about climate change more generally. Results indicate that paying attention to TV weather forecasts is associated with beliefs that extreme weather is becoming more frequent in Virginia, which in turn is associated with stronger beliefs and concerns about climate change. These associations were strongest for individuals who trust their local TV weathercaster as a source of information about climate change, and for those who identify as politically conservative or moderate. The findings add support to the literature suggesting that TV weathercasters can play an important role in educating the public about climate change.

Attributing regional effects of the 2014 Jordanian extreme drought to external climate drivers

NASA Astrophysics Data System (ADS)

Bergaoui, Karim; Mitchell, Dann; Zaaboul, Rashyd; Otto, Friederike; McDonnell, Rachael; Dadson, Simon; Allen, Myles

2015-04-01

Throughout 2014, the regions of Jordan, Israel, Lebanon and Syria have experienced a persistent draught with clear impacts on the local populations. In this study we perform an extreme event attribution analysis of how such a draught has changed under climate change, with a specific focus on the flow rate of the Upper Jordan river and the water level of Lake Tiberious (AKA the Sea of Galilee). Both of which hold major societal, political and religious importance. To perform the analysis we make use of distributed computing power to run thousands of modelled years of 2014 with slightly different initial conditions. We use an atmosphere only model (HadAM3p) with a nested 50 km regional model covering Africa and the Middle East. The 50 km model atmospheric variables will be used directly to force offline our 1 km LIS surface model. Two separate experiments and simulations are performed, 1. for all known climate forcings that are present in 2014, and 2. for a naturalised 2014 scenario where we assume humans never impacted the climate. We perform sensitivity analyses on the observed precipitation over the regions of interest, and determine that the TRMM data is in good agreement with station data obtained from the Jordanian Ministry of Water. Using a combination of the TRMM and model data we are able to make clear statements on the attribution of a 2014-like extreme draught event to human causal factors.

Climate change. Six centuries of variability and extremes in a coupled marine-terrestrial ecosystem.

PubMed

Black, Bryan A; Sydeman, William J; Frank, David C; Griffin, Daniel; Stahle, David W; García-Reyes, Marisol; Rykaczewski, Ryan R; Bograd, Steven J; Peterson, William T

2014-09-19

Reported trends in the mean and variability of coastal upwelling in eastern boundary currents have raised concerns about the future of these highly productive and biodiverse marine ecosystems. However, the instrumental records on which these estimates are based are insufficiently long to determine whether such trends exceed preindustrial limits. In the California Current, a 576-year reconstruction of climate variables associated with winter upwelling indicates that variability increased over the latter 20th century to levels equaled only twice during the past 600 years. This modern trend in variance may be unique, because it appears to be driven by an unprecedented succession of extreme, downwelling-favorable, winter climate conditions that profoundly reduce productivity for marine predators of commercial and conservation interest. Copyright © 2014, American Association for the Advancement of Science.

Erosion and sediment yields in the Transverse Ranges, Southern California

USGS Publications Warehouse

Scott, Kevin M.; Williams, Rhea P.

1978-01-01

Major-storm and long-term erosion rates in mountain watersheds of the western Transverse Ranges of Ventura County, Calif., are estimated to range from low values that would not require the construction of catchments or channel-stabilization structures to values as high as those recorded anywhere for comparable bedrock erodibilities. A major reason for this extreme variability is the high degree of tectonic activity in the area--watersheds are locally being uplifted by at least as much as 25 feet per 1,000 years, yet the maximum extrapolated rate of denudation measured over the longest available period of record is 7.5 feet per 1,000 years adjusted to a drainage area of 0.5 square mile. Evidence of large amounts of uplift continuing into historic time includes structurally overturned strata of Pleistocene age, active thrust faulting, demonstrable stream antecedence, uplifted and deformed terraces, and other results of base-level change seen in stream channels. Such evidence is widespread in the Transverse Ranges, and aspects of the landscape are locally more a function of tectonic activity than of the denudational process. (Woodard-USGS)

The Effects of a Local Negative Feedback Function between Choice and Relative Reinforcer Rate

PubMed Central

Davison, Michael; Elliffe, Douglas; Marr, M. Jackson

2010-01-01

Four pigeons were trained on two-key concurrent variable-interval schedules with no changeover delay. In Phase 1, relative reinforcers on the two alternatives were varied over five conditions from .1 to .9. In Phases 2 and 3, we instituted a molar feedback function between relative choice in an interreinforcer interval and the probability of reinforcers on the two keys ending the next interreinforcer interval. The feedback function was linear, and was negatively sloped so that more extreme choice in an interreinforcer interval made it more likely that a reinforcer would be available on the other key at the end of the next interval. The slope of the feedback function was −1 in Phase 2 and −3 in Phase 3. We varied relative reinforcers in each of these phases by changing the intercept of the feedback function. Little effect of the feedback functions was discernible at the local (interreinforcer interval) level, but choice measured at an extended level across sessions was strongly and significantly decreased by increasing the negative slope of the feedback function. PMID:21451748

Assessment of spatial variation of risks in small populations.

PubMed Central

Riggan, W B; Manton, K G; Creason, J P; Woodbury, M A; Stallard, E

1991-01-01

Often environmental hazards are assessed by examining the spatial variation of disease-specific mortality or morbidity rates. These rates, when estimated for small local populations, can have a high degree of random variation or uncertainty associated with them. If those rate estimates are used to prioritize environmental clean-up actions or to allocate resources, then those decisions may be influenced by this high degree of uncertainty. Unfortunately, the effect of this uncertainty is not to add "random noise" into the decision-making process, but to systematically bias action toward the smallest populations where uncertainty is greatest and where extreme high and low rate deviations are most likely to be manifest by chance. We present a statistical procedure for adjusting rate estimates for differences in variability due to differentials in local area population sizes. Such adjustments produce rate estimates for areas that have better properties than the unadjusted rates for use in making statistically based decisions about the entire set of areas. Examples are provided for county variation in bladder, stomach, and lung cancer mortality rates for U.S. white males for the period 1970 to 1979. PMID:1820268

Rapid localized spread and immunologic containment define Herpes simplex virus-2 reactivation in the human genital tract.

PubMed

Schiffer, Joshua T; Swan, David; Al Sallaq, Ramzi; Magaret, Amalia; Johnston, Christine; Mark, Karen E; Selke, Stacy; Ocbamichael, Negusse; Kuntz, Steve; Zhu, Jia; Robinson, Barry; Huang, Meei-Li; Jerome, Keith R; Wald, Anna; Corey, Lawrence

2013-04-16

Herpes simplex virus-2 (HSV-2) is shed episodically, leading to occasional genital ulcers and efficient transmission. The biology explaining highly variable shedding patterns, in an infected person over time, is poorly understood. We sampled the genital tract for HSV DNA at several time intervals and concurrently at multiple sites, and derived a spatial mathematical model to characterize dynamics of HSV-2 reactivation. The model reproduced heterogeneity in shedding episode duration and viral production, and predicted rapid early viral expansion, rapid late decay, and wide spatial dispersion of HSV replication during episodes. In simulations, HSV-2 spread locally within single ulcers to thousands of epithelial cells in <12 hr, but host immune responses eliminated infected cells in <24 hr; secondary ulcers formed following spatial propagation of cell-free HSV-2, allowing for episode prolongation. We conclude that HSV-2 infection is characterized by extremely rapid virological growth and containment at multiple contemporaneous sites within genital epithelium. DOI:http://dx.doi.org/10.7554/eLife.00288.001.

Rapid localized spread and immunologic containment define Herpes simplex virus-2 reactivation in the human genital tract

PubMed Central

Schiffer, Joshua T; Swan, David; Al Sallaq, Ramzi; Magaret, Amalia; Johnston, Christine; Mark, Karen E; Selke, Stacy; Ocbamichael, Negusse; Kuntz, Steve; Zhu, Jia; Robinson, Barry; Huang, Meei-Li; Jerome, Keith R; Wald, Anna; Corey, Lawrence

2013-01-01

Herpes simplex virus-2 (HSV-2) is shed episodically, leading to occasional genital ulcers and efficient transmission. The biology explaining highly variable shedding patterns, in an infected person over time, is poorly understood. We sampled the genital tract for HSV DNA at several time intervals and concurrently at multiple sites, and derived a spatial mathematical model to characterize dynamics of HSV-2 reactivation. The model reproduced heterogeneity in shedding episode duration and viral production, and predicted rapid early viral expansion, rapid late decay, and wide spatial dispersion of HSV replication during episodes. In simulations, HSV-2 spread locally within single ulcers to thousands of epithelial cells in <12 hr, but host immune responses eliminated infected cells in <24 hr; secondary ulcers formed following spatial propagation of cell-free HSV-2, allowing for episode prolongation. We conclude that HSV-2 infection is characterized by extremely rapid virological growth and containment at multiple contemporaneous sites within genital epithelium. DOI: http://dx.doi.org/10.7554/eLife.00288.001 PMID:23606943

Geomagnetically Induced Currents: Principles

NASA Astrophysics Data System (ADS)

Oliveira, Denny M.; Ngwira, Chigomezyo M.

2017-10-01

The geospace, or the space environment near Earth, is constantly subjected to changes in the solar wind flow generated at the Sun. The study of this environment variability is called Space Weather. Examples of effects resulting from this variability are the occurrence of powerful solar disturbances, such as coronal mass ejections (CMEs). The impact of CMEs on the Earth's magnetosphere very often greatly perturbs the geomagnetic field causing the occurrence of geomagnetic storms. Such extremely variable geomagnetic fields trigger geomagnetic effects measurable not only in the geospace but also in the ionosphere, upper atmosphere, and on and in the ground. For example, during extreme cases, rapidly changing geomagnetic fields generate intense geomagnetically induced currents (GICs). Intense GICs can cause dramatic effects on man-made technological systems, such as damage to high-voltage power transmission transformers leading to interruption of power supply, and/or corrosion of oil and gas pipelines. These space weather effects can in turn lead to severe economic losses. In this paper, we supply the reader with theoretical concepts related to GICs as well as their general consequences. As an example, we discuss the GIC effects on a North American power grid located in mid-latitude regions during the 13-14 March 1989 extreme geomagnetic storm. That was the most extreme storm that occurred in the space era age.

Extreme events in total ozone: Spatio-temporal analysis from local to global scale

NASA Astrophysics Data System (ADS)

Rieder, Harald E.; Staehelin, Johannes; Maeder, Jörg A.; Ribatet, Mathieu; di Rocco, Stefania; Jancso, Leonhardt M.; Peter, Thomas; Davison, Anthony C.

2010-05-01

Recently tools from extreme value theory (e.g. Coles, 2001; Ribatet, 2007) have been applied for the first time in the field of stratospheric ozone research, as statistical analysis showed that previously used concepts assuming a Gaussian distribution (e.g. fixed deviations from mean values) of total ozone data do not address the internal data structure concerning extremes adequately (Rieder et al., 2010a,b). A case study the world's longest total ozone record (Arosa, Switzerland - for details see Staehelin et al., 1998a,b) illustrates that tools based on extreme value theory are appropriate to identify ozone extremes and to describe the tails of the total ozone record. Excursions in the frequency of extreme events reveal "fingerprints" of dynamical factors such as ENSO or NAO, and chemical factors, such as cold Arctic vortex ozone losses, as well as major volcanic eruptions of the 20th century (e.g. Gunung Agung, El Chichón, Mt. Pinatubo). Furthermore, atmospheric loading in ozone depleting substances led to a continuous modification of column ozone in the northern hemisphere also with respect to extreme values (partly again in connection with polar vortex contributions). It is shown that application of extreme value theory allows the identification of many more such fingerprints than conventional time series analysis of annual and seasonal mean values. Especially, the extremal analysis shows the strong influence of dynamics, revealing that even moderate ENSO and NAO events have a discernible effect on total ozone (Rieder et al., 2010b). Overall the extremes concept provides new information on time series properties, variability, trends and the influence of dynamics and chemistry, complementing earlier analyses focusing only on monthly (or annual) mean values. Findings described above could be proven also for the total ozone records of 5 other long-term series (Belsk, Hohenpeissenberg, Hradec Kralove, Potsdam, Uccle) showing that strong influence of atmospheric dynamics (NAO, ENSO) on total ozone is a global feature in the northern mid-latitudes (Rieder et al., 2010c). In a next step frequency distributions of extreme events are analyzed on global scale (northern and southern mid-latitudes). A specific focus here is whether findings gained through analysis of long-term European ground based stations can be clearly identified as a global phenomenon. By showing results from these three types of studies an overview of extreme events in total ozone (and the dynamical and chemical features leading to those) will be presented from local to global scales. References: Coles, S.: An Introduction to Statistical Modeling of Extreme Values, Springer Series in Statistics, ISBN:1852334592, Springer, Berlin, 2001. Ribatet, M.: POT: Modelling peaks over a threshold, R News, 7, 34-36, 2007. Rieder, H.E., Staehelin, J., Maeder, J.A., Ribatet, M., Stübi, R., Weihs, P., Holawe, F., Peter, T., and A.D., Davison (2010): Extreme events in total ozone over Arosa - Part I: Application of extreme value theory, to be submitted to ACPD. Rieder, H.E., Staehelin, J., Maeder, J.A., Ribatet, M., Stübi, R., Weihs, P., Holawe, F., Peter, T., and A.D., Davison (2010): Extreme events in total ozone over Arosa - Part II: Fingerprints of atmospheric dynamics and chemistry and effects on mean values and long-term changes, to be submitted to ACPD. Rieder, H.E., Jancso, L., Staehelin, J., Maeder, J.A., Ribatet, Peter, T., and A.D., Davison (2010): Extreme events in total ozone over the northern mid-latitudes: A case study based on long-term data sets from 5 ground-based stations, in preparation. Staehelin, J., Renaud, A., Bader, J., McPeters, R., Viatte, P., Hoegger, B., Bugnion, V., Giroud, M., and Schill, H.: Total ozone series at Arosa (Switzerland): Homogenization and data comparison, J. Geophys. Res., 103(D5), 5827-5842, doi:10.1029/97JD02402, 1998a. Staehelin, J., Kegel, R., and Harris, N. R.: Trend analysis of the homogenized total ozone series of Arosa (Switzerland), 1929-1996, J. Geophys. Res., 103(D7), 8389-8400, doi:10.1029/97JD03650, 1998b.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

Detecting Biosphere anomalies hotspots

NASA Astrophysics Data System (ADS)

Guanche-Garcia, Yanira; Mahecha, Miguel; Flach, Milan; Denzler, Joachim

2017-04-01

The current amount of satellite remote sensing measurements available allow for applying data-driven methods to investigate environmental processes. The detection of anomalies or abnormal events is crucial to monitor the Earth system and to analyze their impacts on ecosystems and society. By means of a combination of statistical methods, this study proposes an intuitive and efficient methodology to detect those areas that present hotspots of anomalies, i.e. higher levels of abnormal or extreme events or more severe phases during our historical records. Biosphere variables from a preliminary version of the Earth System Data Cube developed within the CAB-LAB project (http://earthsystemdatacube.net/) have been used in this study. This database comprises several atmosphere and biosphere variables expanding 11 years (2001-2011) with 8-day of temporal resolution and 0.25° of global spatial resolution. In this study, we have used 10 variables that measure the biosphere. The methodology applied to detect abnormal events follows the intuitive idea that anomalies are assumed to be time steps that are not well represented by a previously estimated statistical model [1].We combine the use of Autoregressive Moving Average (ARMA) models with a distance metric like Mahalanobis distance to detect abnormal events in multiple biosphere variables. In a first step we pre-treat the variables by removing the seasonality and normalizing them locally (μ=0,σ=1). Additionally we have regionalized the area of study into subregions of similar climate conditions, by using the Köppen climate classification. For each climate region and variable we have selected the best ARMA parameters by means of a Bayesian Criteria. Then we have obtained the residuals by comparing the fitted models with the original data. To detect the extreme residuals from the 10 variables, we have computed the Mahalanobis distance to the data's mean (Hotelling's T^2), which considers the covariance matrix of the joint distribution. The proposed methodology has been applied to different areas around the globe. The results show that the method is able to detect historic events and also provides a useful tool to define sensitive regions. This method and results have been developed within the framework of the project BACI (http://baci-h2020.eu/), which aims to integrate Earth Observation data to monitor the earth system and assessing the impacts of terrestrial changes. [1] V. Chandola, A., Banerjee and v., Kumar. Anomaly detection: a survey. ACM computing surveys (CSUR), vol. 41, n. 3, 2009. [2] P. Mahalanobis. On the generalised distance in statistics. Proceedings National Institute of Science, vol. 2, pp 49-55, 1936.

Evaluating the ClimEx Single Model large ensemble in comparison with EURO-CORDEX results of heatwave and drought indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several indicators concerning heatwave frequency, duration and mean temperature a well as number and maximum length of dry periods (cons. days <1mm) are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

USGS Publications Warehouse

Vorosmarty, Charles J.; de Guenni, Lelys Bravo; Wollheim, Wilfred M.; Pellerin, Brian A.; Bjerklie, David M.; Cardoso, Manoel; D'Almeida, Cassiano; Colon, Lilybeth

2013-01-01

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

Variable postpartum responsiveness among humans and other primates with "cooperative breeding": A comparative and evolutionary perspective.

PubMed

Hrdy, Sarah B

2016-01-01

This article is part of a Special Issue "Parental Care".Until recently, evolutionists reconstructing mother-infant bonding among human ancestors relied on nonhuman primate models characterized by exclusively maternal care, overlooking the highly variable responsiveness exhibited by mothers in species with obligate reliance on allomaternal care and provisioning. It is now increasingly recognized that apes as large-brained, slow maturing, and nutritionally dependent for so long as early humans were, could not have evolved unless "alloparents" (group members other than genetic parents), in addition to parents, had helped mothers to care for and provision offspring, a rearing system known as "cooperative breeding." Here I review situation-dependent maternal responses ranging from highly possessive to permissive, temporarily distancing, rejecting, or infanticidal, documented for a small subset of cooperatively breeding primates. As in many mammals, primate maternal responsiveness is influenced by physical condition, endocrinological priming, prior experience and local environments (especially related to security). But mothers among primates who evolved as cooperative breeders also appear unusually sensitive to cues of social support. In addition to more "sapient" or rational decision-making, humankind's deep history of cooperative breeding must be considered when trying to understand the extremely variable responsiveness of human mothers. Copyright © 2015 Elsevier Inc. All rights reserved.

Eastern South African hydroclimate over the past 270,000 years

NASA Astrophysics Data System (ADS)

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J. C.; Hall, Ian R.

2015-12-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years.

PubMed

Simon, Margit H; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J C; Hall, Ian R

2015-12-21

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years

PubMed Central

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J.C.; Hall, Ian R.

2015-01-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique. PMID:26686943

Changes in seasonal streamflow extremes experienced in rivers of Northwestern South America (Colombia)

NASA Astrophysics Data System (ADS)

Pierini, J. O.; Restrepo, J. C.; Aguirre, J.; Bustamante, A. M.; Velásquez, G. J.

2017-04-01

A measure of the variability in seasonal extreme streamflow was estimated for the Colombian Caribbean coast, using monthly time series of freshwater discharge from ten watersheds. The aim was to detect modifications in the streamflow monthly distribution, seasonal trends, variance and extreme monthly values. A 20-year length time moving window, with 1-year successive shiftments, was applied to the monthly series to analyze the seasonal variability of streamflow. The seasonal-windowed data were statistically fitted through the Gamma distribution function. Scale and shape parameters were computed using the Maximum Likelihood Estimation (MLE) and the bootstrap method for 1000 resample. A trend analysis was performed for each windowed-serie, allowing to detect the window of maximum absolute values for trends. Significant temporal shifts in seasonal streamflow distribution and quantiles (QT), were obtained for different frequencies. Wet and dry extremes periods increased significantly in the last decades. Such increase did not occur simultaneously through the region. Some locations exhibited continuous increases only at minimum QT.

Flexible stocking as a strategy for enhancing ranch profitability in the face of a changing and variable climate

USDA-ARS?s Scientific Manuscript database

Predicted climate change impacts include increased weather variability and increased occurrences of extreme events such as drought. Such climate changes potentially affect cattle performance as well as pasture and range productivity. These climate induced risks are often coupled with variable market...

Ensemble-based evaluation of extreme water levels for the eastern Baltic Sea

NASA Astrophysics Data System (ADS)

Eelsalu, Maris; Soomere, Tarmo

2016-04-01

The risks and damages associated with coastal flooding that are naturally associated with an increase in the magnitude of extreme storm surges are one of the largest concerns of countries with extensive low-lying nearshore areas. The relevant risks are even more contrast for semi-enclosed water bodies such as the Baltic Sea where subtidal (weekly-scale) variations in the water volume of the sea substantially contribute to the water level and lead to large spreading of projections of future extreme water levels. We explore the options for using large ensembles of projections to more reliably evaluate return periods of extreme water levels. Single projections of the ensemble are constructed by means of fitting several sets of block maxima with various extreme value distributions. The ensemble is based on two simulated data sets produced in the Swedish Meteorological and Hydrological Institute. A hindcast by the Rossby Centre Ocean model is sampled with a resolution of 6 h and a similar hindcast by the circulation model NEMO with a resolution of 1 h. As the annual maxima of water levels in the Baltic Sea are not always uncorrelated, we employ maxima for calendar years and for stormy seasons. As the shape parameter of the Generalised Extreme Value distribution changes its sign and substantially varies in magnitude along the eastern coast of the Baltic Sea, the use of a single distribution for the entire coast is inappropriate. The ensemble involves projections based on the Generalised Extreme Value, Gumbel and Weibull distributions. The parameters of these distributions are evaluated using three different ways: maximum likelihood method and method of moments based on both biased and unbiased estimates. The total number of projections in the ensemble is 40. As some of the resulting estimates contain limited additional information, the members of pairs of projections that are highly correlated are assigned weights 0.6. A comparison of the ensemble-based projection of extreme water levels and their return periods with similar estimates derived from local observations reveals an interesting pattern of match and mismatch. The match is almost perfect in measurement sites where local effects (e.g., wave-induced set-up or local surge in very shallow areas that are not resolved by circulation models) do not contribute to the observed values of water level. There is, however, substantial mismatch between projected and observed extreme values for most of the Estonian coast. The mismatch is largest for sections that are open to high waves and for several bays that are deeply cut into mainland but open for predominant strong wind directions. Detailed quantification of this mismatch eventually makes it possible to develop substantially improved estimates of extreme water levels in sections where local effects considerably contribute into the total water level.

Interplay of Anderson localization and quench dynamics

NASA Astrophysics Data System (ADS)

Rahmani, Armin; Vishveshwara, Smitha

2018-06-01

In the context of an isolated three-dimensional noninteracting fermionic lattice system, we study the effects of a sudden quantum quench between a disorder-free situation and one in which disorder results in a mobility edge and associated Anderson localization. Salient post-quench features hinge upon the overlap between momentum states and post-quench eigenstates and whether these latter states are extended or localized. We find that the post-quench momentum distribution directly reflects these overlaps. For the local density, we show that disorder generically prevents the equilibration of quantum expectation values to a steady state and that the persistent fluctuations have a nonmonotonic dependence on the strength of disorder. We identify two distinct types of fluctuations, namely, temporal fluctuations describing the time-dependent fluctuations of the local density around its time average and sample-to-sample fluctuations characterizing the variations of these time averages from one realization of disorder to another. We demonstrate that both of these fluctuations vanish for extremely extended as well as extremely localized states, peaking at some intermediate value.

Trading Space for Time in Design Storm Estimation Using Radar Data

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Berndt, C.

2017-12-01

Intensity-duration-frequency (IDF) curves are frequently used for the derivation of design storms. These curves are usually estimated from rain gauges and are valid for extreme rainfall at local observed points. Two common problems are involved. Regionalization of rainfall statistics for unobserved locations and the use of areal reduction factors (ARF) for the adjustment to larger catchments are required. Weather radar data are available with large spatial coverage and high resolution in space and could be used for a direct derivation of areal design storms for any location and catchment size. However, one problem with radar data is the relatively short observation period for the estimation of extreme events. This study deals with the estimation of area-intensity-duration-frequency (AIDF) curves and areal-reduction-factors (ARF) directly from weather radar data. The main objective is to answer the question if it is possible to trade space for time in the estimation of both characteristics to compensate for the short radar observation periods. In addition, a stratification of the temporal sample according to annual temperature indices is tried to distinguish "colder" and "warmer" climate years. This might eventually show a way for predicting future changes in AIDF curves and ARFs. First, radar data are adjusted with rainfall observations from the daily station network. Thereafter, AIDF curves and ARFs are calculated for different spatial and temporal sample sizes. The AIDF and ARFs are compared regarding their temporal and spatial variability considering also the temperature conditions. In order to reduce spatial variability a grouping of locations according to their climatological and physiographical characteristics is carried out. The data used for this study cover about 20 years of observations from the radar device located near Hanover in Northern Germany and 500 non-recording rain gauges as well as a set of 8 recording rain gauges for validation. AIDF curves and ARFS are analyzed for rainfall durations from 5 minutes to 24 hours and return periods from 1 year to 30 years. It is hypothesized, that the spatial variability of AIDF and ARF characteristics decreases with increasing sample size, grouping and normalization and is finally comparable to temporal variability.

When time affects space: Dispersal ability and extreme weather events determine metacommunity organization in marine sediments.

PubMed

Corte, Guilherme N; Gonçalves-Souza, Thiago; Checon, Helio H; Siegle, Eduardo; Coleman, Ross A; Amaral, A Cecília Z

2018-05-01

Community ecology has traditionally assumed that the distribution of species is mainly influenced by environmental processes. There is, however, growing evidence that environmental (habitat characteristics and biotic interactions) and spatial processes (factors that affect a local assemblage regardless of environmental conditions - typically related to dispersal and movement of species) interactively shape biological assemblages. A metacommunity, which is a set of local assemblages connected by dispersal of individuals, is spatial in nature and can be used as a straightforward approach for investigating the interactive and independent effects of both environmental and spatial processes. Here, we examined (i) how environmental and spatial processes affect the metacommunity organization of marine macroinvertebrates inhabiting the intertidal sediments of a biodiverse coastal ecosystem; (ii) whether the influence of these processes is constant through time or is affected by extreme weather events (storms); and (iii) whether the relative importance of these processes depends on the dispersal abilities of organisms. We found that macrobenthic assemblages are influenced by each of environmental and spatial variables; however, spatial processes exerted a stronger role. We also found that this influence changes through time and is modified by storms. Moreover, we observed that the influence of environmental and spatial processes varies according to the dispersal capabilities of organisms. More effective dispersers (i.e., species with planktonic larvae) are more affected by spatial processes whereas environmental variables had a stronger effect on weaker dispersers (i.e. species with low motility in larval and adult stages). These findings highlight that accounting for spatial processes and differences in species life histories is essential to improve our understanding of species distribution and coexistence patterns in intertidal soft-sediments. Furthermore, it shows that storms modify the structure of coastal assemblages. Given that the influence of spatial and environmental processes is not consistent through time, it is of utmost importance that future studies replicate sampling over different periods so the influence of temporal and stochastic factors on macrobenthic metacommunities can be better understood. Copyright © 2018 Elsevier Ltd. All rights reserved.

Climate change, extreme weather events, and us health impacts: what can we say?

PubMed

Mills, David M

2009-01-01

Address how climate change impacts on a group of extreme weather events could affect US public health. A literature review summarizes arguments for, and evidence of, a climate change signal in select extreme weather event categories, projections for future events, and potential trends in adaptive capacity and vulnerability in the United States. Western US wildfires already exhibit a climate change signal. The variability within hurricane and extreme precipitation/flood data complicates identifying a similar climate change signal. Health impacts of extreme events are not equally distributed and are very sensitive to a subset of exceptional extreme events. Cumulative uncertainty in forecasting climate change driven characteristics of extreme events and adaptation prevents confidently projecting the future health impacts from hurricanes, wildfires, and extreme precipitation/floods in the United States attributable to climate change.

Socio-ecological Typologies for Understanding Adaptive Capacity of a Region to Natural Disasters

NASA Astrophysics Data System (ADS)

Surendran Nair, S.; Preston, B. L.; King, A. W.; Mei, R.

2015-12-01

It is expected that the frequency and magnitude of extreme climatic events will increase in coming decades with an anticipated increase in losses from climate hazards. In the Gulf Coastal region of the United States, climate hazards/disasters are common including hurricanes, drought and flooding. However, the capacity to adapt to extreme climatic events varies across the region. This adaptive capacity is linked to the magnitude of the extreme event, exposed infrastructure, and the socio-economic conditions across the region. This study uses hierarchical clustering to quantitatively integrates regional socioeconomic and biophysical factors and develop socio-ecological typologies (SET). The biophysical factors include climatic and topographic variables, and the socio-economic variables include human capital, social capital and man-made resources (infrastructure) of the region. The types of the SET are independent variables in a statistical model of a regional variable of interest. The methodology was applied to US Gulf States to evaluate the social and biophysical determinants of the regional variation in social vulnerability and economic loss to climate hazards. The results show that the SET explains much of the regional variation in social vulnerability, effectively capturing its determinants. In addition, the SET also explains of the variability in economic loss to hazards across of the region. The approach can thus be used to prioritize adaptation strategies to reduce vulnerability and loss across the region.

The relative importance among anthropogenic forcings of land use/land cover change in affecting temperature extremes

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.

2018-05-01

Land use/land cover change (LULCC) exerts significant influence on regional climate extremes, but its relative importance compared with other anthropogenic climate forcings has not been thoroughly investigated. This study compares land use forcing with other forcing agents in explaining the simulated historical temperature extreme changes since preindustrial times in the CESM-Last Millennium Ensemble (LME) project. CESM-LME suggests that the land use forcing has caused an overall cooling in both warm and cold extremes, and has significantly decreased diurnal temperature range (DTR). Due to the competing effects of the GHG and aerosol forcings, the spatial pattern of changes in 1850-2005 climatology of temperature extremes in CESM-LME can be largely explained by the land use forcing, especially for hot extremes and DTR. The dominance of land use forcing is particularly evident over Europe, eastern China, and the central and eastern US. Temporally, the land-use cooling is relatively stable throughout the historical period, while the warming of temperature extremes is mainly influenced by the enhanced GHG forcing, which has gradually dampened the local dominance of the land use effects. Results from the suite of CMIP5 experiments partially agree with the local dominance of the land use forcing in CESM-LME, but inter-model discrepancies exist in the distribution and sign of the LULCC-induced temperature changes. Our results underline the overall importance of LULCC in historical temperature extreme changes, implying land use forcing should be highlighted in future climate projections.

A stochastic-geometric model of soil variation in Pleistocene patterned ground

NASA Astrophysics Data System (ADS)

Lark, Murray; Meerschman, Eef; Van Meirvenne, Marc

2013-04-01

In this paper we examine the spatial variability of soil in parent material with complex spatial structure which arises from complex non-linear geomorphic processes. We show that this variability can be better-modelled by a stochastic-geometric model than by a standard Gaussian random field. The benefits of the new model are seen in the reproduction of features of the target variable which influence processes like water movement and pollutant dispersal. Complex non-linear processes in the soil give rise to properties with non-Gaussian distributions. Even under a transformation to approximate marginal normality, such variables may have a more complex spatial structure than the Gaussian random field model of geostatistics can accommodate. In particular the extent to which extreme values of the variable are connected in spatially coherent regions may be misrepresented. As a result, for example, geostatistical simulation generally fails to reproduce the pathways for preferential flow in an environment where coarse infill of former fluvial channels or coarse alluvium of braided streams creates pathways for rapid movement of water. Multiple point geostatistics has been developed to deal with this problem. Multiple point methods proceed by sampling from a set of training images which can be assumed to reproduce the non-Gaussian behaviour of the target variable. The challenge is to identify appropriate sources of such images. In this paper we consider a mode of soil variation in which the soil varies continuously, exhibiting short-range lateral trends induced by local effects of the factors of soil formation which vary across the region of interest in an unpredictable way. The trends in soil variation are therefore only apparent locally, and the soil variation at regional scale appears random. We propose a stochastic-geometric model for this mode of soil variation called the Continuous Local Trend (CLT) model. We consider a case study of soil formed in relict patterned ground with pronounced lateral textural variations arising from the presence of infilled ice-wedges of Pleistocene origin. We show how knowledge of the pedogenetic processes in this environment, along with some simple descriptive statistics, can be used to select and fit a CLT model for the apparent electrical conductivity (ECa) of the soil. We use the model to simulate realizations of the CLT process, and compare these with realizations of a fitted Gaussian random field. We show how statistics that summarize the spatial coherence of regions with small values of ECa, which are expected to have coarse texture and so larger saturated hydraulic conductivity, are better reproduced by the CLT model than by the Gaussian random field. This suggests that the CLT model could be used to generate an unlimited supply of training images to allow multiple point geostatistical simulation or prediction of this or similar variables.

The Women's Role in the Adaptation to Climate Variability and Climate Change: Its Contribution to the Risk Management

NASA Astrophysics Data System (ADS)

Quintero Angel, M.; Carvajal Escobar, Y.; Garcia Vargas, M.

2007-05-01

Recently, there is evidence of an increase in the amount of severity in extreme events associated with the climate variability or climate change; which demonstrates that climate in this planet is changing. There is an observation of increasing damages, and of social economical cost associated with these phenomena's, mostly do to more people are living in hazard vulnerable conditions. The victims of natural disasters have increase from 147 to 211 million between 1991 and 2000. In same way more than 665.000 people have died in 2557 natural disasters, which 90% are associated with water and climate. (UNESCO & WWAP, 2003). The actual tendency and the introduction of new factors of risk, suggest lost increase in the future, obligating actions to manage and reduce risk of disaster. Bind work, health, poverty, education, water, climate, and disasters is not an error, is an obligation. Vulnerability of society to natural hazards and to poverty are bond, to reduce the risk of disasters is frequently united with the reduction of poverty and in the other way too (Sen, 2000). In this context, extreme events impact societies in all the world, affecting differently men and women, do to the different roles they play in the society, the different access in the control of resources, the few participation that women have in taking decisions with preparedness, mitigation, rehabilitation of disasters, impacting more women in developing countries. Although, women understand better the causes and local consequences in changes of climate conditions. They have a pile of knowledge and abilities for guiding adaptation, playing a very important role in vulnerable communities. This work shows how these topics connect with the millennium development goals; particularly how it affects its accomplishment. It also describes the impact of climate variability and climate change in developing countries. Analyzing adaptation responses that are emerging; especially from women initiation.

Decision-support tools for Extreme Weather and Climate Events in the Northeast United States

NASA Astrophysics Data System (ADS)

Kumar, S.; Lowery, M.; Whelchel, A.

2013-12-01

Decision-support tools were assessed for the 2013 National Climate Assessment technical input document, "Climate Change in the Northeast, A Sourcebook". The assessment included tools designed to generate and deliver actionable information to assist states and highly populated urban and other communities in assessment of climate change vulnerability and risk, quantification of effects, and identification of adaptive strategies in the context of adaptation planning across inter-annual, seasonal and multi-decadal time scales. State-level adaptation planning in the Northeast has generally relied on qualitative vulnerability assessments by expert panels and stakeholders, although some states have undertaken initiatives to develop statewide databases to support vulnerability assessments by urban and local governments, and state agencies. The devastation caused by Superstorm Sandy in October 2012 has raised awareness of the potential for extreme weather events to unprecedented levels and created urgency for action, especially in coastal urban and suburban communities that experienced pronounced impacts - especially in New Jersey, New York and Connecticut. Planning approaches vary, but any adaptation and resiliency planning process must include the following: - Knowledge of the probable change in a climate variable (e.g., precipitation, temperature, sea-level rise) over time or that the climate variable will attain a certain threshold deemed to be significant; - Knowledge of intensity and frequency of climate hazards (past, current or future events or conditions with potential to cause harm) and their relationship with climate variables; - Assessment of climate vulnerabilities (sensitive resources, infrastructure or populations exposed to climate-related hazards); - Assessment of relative risks to vulnerable resources; - Identification and prioritization of adaptive strategies to address risks. Many organizations are developing decision-support tools to assist in the urban planning process by addressing some of these needs. In this paper we highlight the decision tools available today, discuss their application in selected case studies, and present a gap analysis with opportunities for innovation and future work.

Changes in extreme events and the potential impacts on human health.

PubMed

Bell, Jesse E; Brown, Claudia Langford; Conlon, Kathryn; Herring, Stephanie; Kunkel, Kenneth E; Lawrimore, Jay; Luber, George; Schreck, Carl; Smith, Adam; Uejio, Christopher

2018-04-01

Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future. Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.

Ground-water flow and quality in Wisconsin's shallow aquifer system

USGS Publications Warehouse

Kammerer, P.A.

1995-01-01

In terms of chemical quality, the water is suitable for potable supply and most other uses, but objectionable hardness in large areas and concen- trations of iron and manganese that exceed State drinking-water standards cause aesthetic problems that may require treatment of the water for some uses. Concentrations of major dissolved constitu- ents (calcium, magnesium, and bicarbonate), hard- ness, alkalinity, and dissolved solids are highest where the bedrock component of the aquifer is dolo- mite and lowest where the shallow aquifer is almost entirely sand and gravel. Concentrations of other minor constituents (sodium, potassium, sulfate, chloride, and fluoride) are less closely related to common minerals that compose the aquifer system. Sulfate and fluoride concentrations exceed State drinking-water standards locally. Extreme variability in concentrations of iron and manganese are common locally. Iron and manganese concentra- tions exceed State drinking-water standards in water from one-third and one-quarter of the wells, respectively. Likely causes of nitrate-nitrogen con- centrations that exceed State drinking-water stan- dards include local contamination from plant fertilizers, animal wastes, waste water disposed of on land, and septic systems. Water quality in the shallow aquifer system has been affected by saline water from underlying aquifers, primarily along the eastern and western boundaries of the State where the thickness of Paleozoic rocks is greatest.

Uncertainty in projected point precipitation extremes for hydrological impact analysis of climate change

NASA Astrophysics Data System (ADS)

Van Uytven, Els; Willems, Patrick

2017-04-01

Current trends in the hydro-meteorological variables indicate the potential impact of climate change on hydrological extremes. Therefore, they trigger an increased importance climate adaptation strategies in water management. The impact of climate change on hydro-meteorological and hydrological extremes is, however, highly uncertain. This is due to uncertainties introduced by the climate models, the internal variability inherent to the climate system, the greenhouse gas scenarios and the statistical downscaling methods. In view of the need to define sustainable climate adaptation strategies, there is a need to assess these uncertainties. This is commonly done by means of ensemble approaches. Because more and more climate models and statistical downscaling methods become available, there is a need to facilitate the climate impact and uncertainty analysis. A Climate Perturbation Tool has been developed for that purpose, which combines a set of statistical downscaling methods including weather typing, weather generator, transfer function and advanced perturbation based approaches. By use of an interactive interface, climate impact modelers can apply these statistical downscaling methods in a semi-automatic way to an ensemble of climate model runs. The tool is applicable to any region, but has been demonstrated so far to cases in Belgium, Suriname, Vietnam and Bangladesh. Time series representing future local-scale precipitation, temperature and potential evapotranspiration (PET) conditions were obtained, starting from time series of historical observations. Uncertainties on the future meteorological conditions are represented in two different ways: through an ensemble of time series, and a reduced set of synthetic scenarios. The both aim to span the full uncertainty range as assessed from the ensemble of climate model runs and downscaling methods. For Belgium, for instance, use was made of 100-year time series of 10-minutes precipitation observations and daily temperature and PET observations at Uccle and a large ensemble of 160 global climate model runs (CMIP5). They cover all four representative concentration pathway based greenhouse gas scenarios. While evaluating the downscaled meteorological series, particular attention was given to the performance of extreme value metrics (e.g. for precipitation, by means of intensity-duration-frequency statistics). Moreover, the total uncertainty was decomposed in the fractional uncertainties for each of the uncertainty sources considered. Research assessing the additional uncertainty due to parameter and structural uncertainties of the hydrological impact model is ongoing.

VeriML: A Dependently-Typed, User-Extensible and Language-Centric Approach to Proof Assistants

DTIC Science & Technology

2013-01-01

the locally nameless approach [McKinna and Pollack, 1993]. The former two techniques replace all variables by numbers, whereas the locally nameless ...needs to be reasoned about together with shifting. This complicates both the statements and proofs of related lemmas. The locally nameless approach...the locally nameless approach, we separate free variables from bound variables and use deBruijn indices for bound variables (denoted as bi in Table 3.1

Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brunsell, Nathaniel; Mechem, David; Ma, Chunsheng

Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive tomore » alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the validity of an innovative multi–resolution information theory approach, and the ability of the RCM modeling framework to represent the low-frequency modulation of extreme climate events. Once the skill of the modeling and analysis methodology has been established, we will apply the same approach for the AR5 (IPCC Fifth Assessment Report) climate change scenarios in order to assess how climate extremes and the the influence of lowfrequency variability on climate extremes might vary under changing climate. The research specifically addresses the DOE focus area 2. Simulation of climate extremes under a changing climate. Specific results will include (1) a better understanding of the spatial and temporal structure of extreme events, (2) a thorough quantification of how extreme values are impacted by low-frequency climate teleconnections, (3) increased knowledge of current regional climate models ability to ascertain these influences, and (4) a detailed examination of the how the distribution of extreme events are likely to change under different climate change scenarios. In addition, this research will assess the ability of the innovative wavelet information theory approach to characterize extreme events. Any and all of these results will greatly enhance society’s ability to understand and mitigate the regional ramifications of future global climate change.« less

Quantifying the role of climate variability on extreme total water level impacts: An application of a full simulation model to Ocean Beach, California

NASA Astrophysics Data System (ADS)

Serafin, K.; Ruggiero, P.; Stockdon, H. F.; Barnard, P.; Long, J.

2014-12-01

Many coastal communities worldwide are vulnerable to flooding and erosion driven by extreme total water levels (TWL), potentially dangerous events produced by the combination of large waves, high tides, and high non-tidal residuals. The West coast of the United States provides an especially challenging environment to model these processes due to its complex geological setting combined with uncertain forecasts for sea level rise (SLR), changes in storminess, and possible changes in the frequency of major El Niños. Our research therefore aims to develop an appropriate methodology to assess present-day and future storm-induced coastal hazards along the entire U.S. West coast, filling this information gap. We present the application of this framework in a pilot study at Ocean Beach, California, a National Park site within the Golden Gate National Recreation Area where existing event-scale coastal change data can be used for model calibration and verification. We use a probabilistic, full simulation TWL model (TWL-FSM; Serafin and Ruggiero, in press) that captures the seasonal and interannual climatic variability in extremes using functions of regional climate indices, such as the Multivariate ENSO index (MEI), to represent atmospheric patterns related to the El Niño-Southern Oscillation (ENSO). In order to characterize the effect of climate variability on TWL components, we refine the TWL-FSM by splitting non-tidal residuals into low (monthly mean sea level anomalies) and high frequency (storm surge) components. We also develop synthetic climate indices using Markov sequences to reproduce the autocorrelated nature of ENSO behavior. With the refined TWL-FSM, we simulate each TWL component, resulting in synthetic TWL records providing robust estimates of extreme return level events (e.g., the 100-yr event) and the ability to examine the relative contribution of each TWL component to these extreme events. Extreme return levels are then used to drive storm impact models to examine the probability of coastal change (Stockdon et al., 2013) and thus, the vulnerability to storm-induced coastal hazards that Ocean Beach faces. Future climate variability is easily incorporated into this framework, allowing us to quantify how an evolving climate will alter future extreme TWLs and their related coastal impacts.

Biodiversity Sampling Using a Global Acoustic Approach: Contrasting Sites with Microendemics in New Caledonia

PubMed Central

Gasc, Amandine; Sueur, Jérôme; Pavoine, Sandrine; Pellens, Roseli; Grandcolas, Philippe

2013-01-01

New Caledonia is a Pacific island with a unique biodiversity showing an extreme microendemism. Many species distributions observed on this island are extremely restricted, localized to mountains or rivers making biodiversity evaluation and conservation a difficult task. A rapid biodiversity assessment method based on acoustics was recently proposed. This method could help to document the unique spatial structure observed in New Caledonia. Here, this method was applied in an attempt to reveal differences among three mountain sites (Mandjélia, Koghis and Aoupinié) with similar ecological features and species richness level, but with high beta diversity according to different microendemic assemblages. In each site, several local acoustic communities were sampled with audio recorders. An automatic acoustic sampling was run on these three sites for a period of 82 successive days. Acoustic properties of animal communities were analysed without any species identification. A frequency spectral complexity index (NP) was used as an estimate of the level of acoustic activity and a frequency spectral dissimilarity index (Df) assessed acoustic differences between pairs of recordings. As expected, the index NP did not reveal significant differences in the acoustic activity level between the three sites. However, the acoustic variability estimated by the index Df, could first be explained by changes in the acoustic communities along the 24-hour cycle and second by acoustic dissimilarities between the three sites. The results support the hypothesis that global acoustic analyses can detect acoustic differences between sites with similar species richness and similar ecological context, but with different species assemblages. This study also demonstrates that global acoustic methods applied at broad spatial and temporal scales could help to assess local biodiversity in the challenging context of microendemism. The method could be deployed over large areas, and could help to compare different sites and determine conservation priorities. PMID:23734245

Biodiversity sampling using a global acoustic approach: contrasting sites with microendemics in New Caledonia.

PubMed

Gasc, Amandine; Sueur, Jérôme; Pavoine, Sandrine; Pellens, Roseli; Grandcolas, Philippe

2013-01-01

New Caledonia is a Pacific island with a unique biodiversity showing an extreme microendemism. Many species distributions observed on this island are extremely restricted, localized to mountains or rivers making biodiversity evaluation and conservation a difficult task. A rapid biodiversity assessment method based on acoustics was recently proposed. This method could help to document the unique spatial structure observed in New Caledonia. Here, this method was applied in an attempt to reveal differences among three mountain sites (Mandjélia, Koghis and Aoupinié) with similar ecological features and species richness level, but with high beta diversity according to different microendemic assemblages. In each site, several local acoustic communities were sampled with audio recorders. An automatic acoustic sampling was run on these three sites for a period of 82 successive days. Acoustic properties of animal communities were analysed without any species identification. A frequency spectral complexity index (NP) was used as an estimate of the level of acoustic activity and a frequency spectral dissimilarity index (Df ) assessed acoustic differences between pairs of recordings. As expected, the index NP did not reveal significant differences in the acoustic activity level between the three sites. However, the acoustic variability estimated by the index Df , could first be explained by changes in the acoustic communities along the 24-hour cycle and second by acoustic dissimilarities between the three sites. The results support the hypothesis that global acoustic analyses can detect acoustic differences between sites with similar species richness and similar ecological context, but with different species assemblages. This study also demonstrates that global acoustic methods applied at broad spatial and temporal scales could help to assess local biodiversity in the challenging context of microendemism. The method could be deployed over large areas, and could help to compare different sites and determine conservation priorities.

When do Indians feel hot? Internet searches indicate seasonality suppresses adaptation to heat

NASA Astrophysics Data System (ADS)

Singh, Tanya; Siderius, Christian; Van der Velde, Ype

2018-05-01

In a warming world an increasing number of people are being exposed to heat, making a comfortable thermal environment an important need. This study explores the potential of using Regional Internet Search Frequencies (RISF) for air conditioning devices as an indicator for thermal discomfort (i.e. dissatisfaction with the thermal environment) with the aim to quantify the adaptation potential of individuals living across different climate zones and at the high end of the temperature range, in India, where access to health data is limited. We related RISF for the years 2011–2015 to daily daytime outdoor temperature in 17 states and determined at which temperature RISF for air conditioning starts to peak, i.e. crosses a ‘heat threshold’, in each state. Using the spatial variation in heat thresholds, we explored whether people continuously exposed to higher temperatures show a lower response to heat extremes through adaptation (e.g. physiological, behavioural or psychological). State-level heat thresholds ranged from 25.9 °C in Madhya Pradesh to 31.0 °C in Orissa. Local adaptation was found to occur at state level: the higher the average temperature in a state, the higher the heat threshold; and the higher the intra-annual temperature range (warmest minus coldest month) the lower the heat threshold. These results indicate there is potential within India to adapt to warmer temperatures, but that a large intra-annual temperature variability attenuates this potential to adapt to extreme heat. This winter ‘reset’ mechanism should be taken into account when assessing the impact of global warming, with changes in minimum temperatures being an important factor in addition to the change in maximum temperatures itself. Our findings contribute to a better understanding of local heat thresholds and people’s adaptive capacity, which can support the design of local thermal comfort standards and early heat warning systems.

Statistical Extremes of Turbulence and a Cascade Generalisation of Euler's Gyroscope Equation

NASA Astrophysics Data System (ADS)

Tchiguirinskaia, Ioulia; Scherzer, Daniel

2016-04-01

Turbulence refers to a rather well defined hydrodynamical phenomenon uncovered by Reynolds. Nowadays, the word turbulence is used to designate the loss of order in many different geophysical fields and the related fundamental extreme variability of environmental data over a wide range of scales. Classical statistical techniques for estimating the extremes, being largely limited to statistical distributions, do not take into account the mechanisms generating such extreme variability. An alternative approaches to nonlinear variability are based on a fundamental property of the non-linear equations: scale invariance, which means that these equations are formally invariant under given scale transforms. Its specific framework is that of multifractals. In this framework extreme variability builds up scale by scale leading to non-classical statistics. Although multifractals are increasingly understood as a basic framework for handling such variability, there is still a gap between their potential and their actual use. In this presentation we discuss how to dealt with highly theoretical problems of mathematical physics together with a wide range of geophysical applications. We use Euler's gyroscope equation as a basic element in constructing a complex deterministic system that preserves not only the scale symmetry of the Navier-Stokes equations, but some more of their symmetries. Euler's equation has been not only the object of many theoretical investigations of the gyroscope device, but also generalised enough to become the basic equation of fluid mechanics. Therefore, there is no surprise that a cascade generalisation of this equation can be used to characterise the intermittency of turbulence, to better understand the links between the multifractal exponents and the structure of a simplified, but not simplistic, version of the Navier-Stokes equations. In a given way, this approach is similar to that of Lorenz, who studied how the flap of a butterfly wing could generate a cyclone with the help of a 3D ordinary differential system. Being well supported by the extensive numerical results, the cascade generalisation of Euler's gyroscope equation opens new horizons for predictability and predictions of processes having long-range dependences.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

Detecting potential anomalies in projections of rainfall trends and patterns using human observations

NASA Astrophysics Data System (ADS)

Kohfeld, K. E.; Savo, V.; Sillmann, J.; Morton, C.; Lepofsky, D.

2016-12-01

Shifting precipitation patterns are a well-documented consequence of climate change, but their spatial variability is particularly difficult to assess. While the accuracy of global models has increased, specific regional changes in precipitation regimes are not well captured by these models. Typically, researchers who wish to detect trends and patterns in climatic variables, such as precipitation, use instrumental observations. In our study, we combined observations of rainfall by subsistence-oriented communities with several metrics of rainfall estimated from global instrumental records for comparable time periods (1955 - 2005). This comparison was aimed at identifying: 1) which rainfall metrics best match human observations of changes in precipitation; 2) areas where local communities observe changes not detected by global models. The collated observations ( 3800) made by subsistence-oriented communities covered 129 countries ( 1830 localities). For comparable time periods, we saw a substantial correspondence between instrumental records and human observations (66-77%) at the same locations, regardless of whether we considered trends in general rainfall, drought, or extreme rainfall. We observed a clustering of mismatches in two specific regions, possibly indicating some climatic phenomena not completely captured by the currently available global models. Many human observations also indicated an increased unpredictability in the start, end, duration, and continuity of the rainy seasons, all of which may hamper the performance of subsistence activities. We suggest that future instrumental metrics should capture this unpredictability of rainfall. This information would be important for thousands of subsistence-oriented communities in planning, coping, and adapting to climate change.

The distribution and hydrogeological controls of fluoride in the groundwater of central Ethiopian rift and adjacent highlands

NASA Astrophysics Data System (ADS)

Ayenew, Tenalem

2008-05-01

Occurrence of fluoride (F) in groundwater has drawn worldwide attention, since it has considerable impact on human health. In Ethiopia high concentrations of F in groundwaters used for community water supply have resulted in extensive dental and skeletal fluorosis. As a part of a broader study, the distribution of F in groundwater has been investigated, and compared with bedrock geology and pertinent hydrochemical variables. The result indicates extreme spatial variations. High F concentration is often associated with active and sub-active regional thermal fields and acidic volcanics within high temperature rift floor. Variations in F can also be related to changes in calcium concentration resulting from dissolution of calcium minerals and mixing with waters of different chemical composition originated from variable hydrogeological environment across the rift valley. The concentration of F dramatically declines from the rift towards the highlands with the exception of scattered points associated with thermal springs confined in local volcanic centers. There are also interactions of F-rich alkaline lakes and the surrounding groundwater. Meteoric waters recharging volcanic aquifers become enriched with respect to F along the groundwater flow path from highland recharge areas to rift discharge areas. Locally wells drilled along large rift faults acting as conduits of fresh highland waters show relatively lower F. These areas are likely to be possible sources of better quality waters within the rift. The result of this study has important implications on site selection for water well drilling.

Extreme Weather Years Drive Episodic Acidification and Brownification in Lakes in the Northeast US: Implications for Long-term Shifts in Dissolved Organic Carbon, Water Clarity, and Thermal Structure

NASA Astrophysics Data System (ADS)

Strock, K.; Saros, J. E.

2017-12-01

Interannual climate variability is expected to increase over the next century, but the extent to which hydroclimatic variability influences biogeochemical processes is unclear. To determine the effects of extreme weather on surface water chemistry, a 30-year record of surface water geochemistry for 84 lakes in the northeastern U.S. was combined with landscape data and watershed-specific weather data. With these data, responses in sulfate and dissolved organic carbon (DOC) concentrations were characterized during extreme wet and extreme dry conditions. Episodic acidification during drought and episodic brownification (increased DOC) during wet years were detected broadly across the northeastern U.S. Episodic chemical response was linearly related to wetland coverage in lake watersheds only during extreme wet years. The results of a redundancy analysis suggest that topographic features also need to be considered and that the interplay between wetlands and their degree of connectivity to surface waters could be driving episodic acidification in this region. A subset of lakes located in Acadia National Park, Maine U.S.A. were studied to better understand the implications of regional increases of DOC in lakes. Water transparency declined across six study sites since 1995 as DOC increased. As clarity declined, some lakes experienced reduced epilimnion thickness. The degree to which transparency changed across the lakes was dependent on DOC concentration, with a larger decline in transparency occurring in clear water lakes than brown water lakes. The results presented here help to clarify the variability observed in long-term recovery from acidification and regional increases in DOC. Specifically, an increased frequency of extreme wet years may be contributing to a recent acceleration in the recovery of lake ecosystems from acidification; however, increased frequency of wet years may also lead to reduced water clarity and altered physical lake habitat. Clarifying the response of DOC, a pivotal regulator of aquatic ecosystems, to extreme weather events across gradients of landscape position and atmospheric deposition, is increasingly important for policy and management decisions as the frequency of extreme events continues to increase in this region.

16 CFR 1207.4 - Recommended standards for materials of manufacture.

Code of Federal Regulations, 2011 CFR

2011-01-01

... exposure to rain, snow, ice, sunlight, local, normal temperature extremes, local normal wind variations... be toxic to man or harmful to the environment under intended use and reasonably foreseeable abuse or...

16 CFR 1207.4 - Recommended standards for materials of manufacture.

Code of Federal Regulations, 2012 CFR

2012-01-01

... exposure to rain, snow, ice, sunlight, local, normal temperature extremes, local normal wind variations... be toxic to man or harmful to the environment under intended use and reasonably foreseeable abuse or...

16 CFR 1207.4 - Recommended standards for materials of manufacture.

Code of Federal Regulations, 2014 CFR

2014-01-01

... exposure to rain, snow, ice, sunlight, local, normal temperature extremes, local normal wind variations... be toxic to man or harmful to the environment under intended use and reasonably foreseeable abuse or...

16 CFR 1207.4 - Recommended standards for materials of manufacture.

Code of Federal Regulations, 2010 CFR

2010-01-01

... exposure to rain, snow, ice, sunlight, local, normal temperature extremes, local normal wind variations... be toxic to man or harmful to the environment under intended use and reasonably foreseeable abuse or...

Local adaptation along an environmental cline in a species with an inversion polymorphism.

PubMed

Wellenreuther, M; Rosenquist, H; Jaksons, P; Larson, K W

2017-06-01

Polymorphic inversions are ubiquitous across the animal kingdom and are frequently associated with clines in inversion frequencies across environmental gradients. Such clines are thought to result from selection favouring local adaptation; however, empirical tests are scarce. The seaweed fly Coelopa frigida has an α/β inversion polymorphism, and previous work demonstrated that the α inversion frequency declines from the North Sea to the Baltic Sea and is correlated with changes in tidal range, salinity, algal composition and wrackbed stability. Here, we explicitly test the hypothesis that populations of C. frigida along this cline are locally adapted by conducting a reciprocal transplant experiment of four populations along this cline to quantify survival. We found that survival varied significantly across treatments and detected a significant Location x Substrate interaction, indicating local adaptation. Survival models showed that flies from locations at both extremes had highest survival on their native substrates, demonstrating that local adaptation is present at the extremes of the cline. Survival at the two intermediate locations was, however, not elevated at the native substrates, suggesting that gene flow in intermediate habitats may override selection. Together, our results support the notion that population extremes of species with polymorphic inversions are often locally adapted, even when spatially close, consistent with the growing view that inversions can have direct and strong effects on the fitness of species. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Bivariate extreme value distributions

NASA Technical Reports Server (NTRS)

Elshamy, M.

1992-01-01

In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given.

The importance of extreme weight percentile in postoperative morbidity in children.

PubMed

Stey, Anne M; Moss, R Lawrence; Kraemer, Kari; Cohen, Mark E; Ko, Clifford Y; Lee Hall, Bruce

2014-05-01

Anthropometric data are important indicators of child health. This study sought to determine whether anthropometric data of extreme weight were significant predictors of perioperative morbidity in pediatric surgery. This was a cohort study of children 29 days up to 18 years of age undergoing surgical procedures at participating American College of Surgeons' NSQIP Pediatric hospitals in 2011 and 2012. The primary outcomes were composite morbidity and surgical site infection. The primary predictor of interest was weight percentile, which was divided into the following categories: ≤5(th) percentile, 6(th) to 94(th), or ≥95(th) percentile. A hierarchical multivariate logistic model, adjusting for procedure case mix, demographic, and clinical patient characteristic variables, was used to quantify the relationship between weight percentile category and outcomes. Children in the ≤5th weight percentile had 1.19-fold higher odds of overall postoperative morbidity developing than children in the nonextreme range (95% CI, 1.10-1.30) when controlling for clinical variables. Yet these children did not have higher odds of surgical site infection developing. Children in the ≥95(th) weight percentile did not have a significant increase in overall postoperative morbidity. However, they were at 1.35-fold increased odds of surgical site infection compared with those in the nonextreme range when controlling for clinical variables (95% CI, 1.16-1.57). Both extremely high and extremely low weight percentile scores can be associated with increased postoperative complications after controlling for clinical variables. Copyright © 2014 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Winter storms drive rapid phenotypic, regulatory, and genomic shifts in the green anole lizard.

PubMed

Campbell-Staton, Shane C; Cheviron, Zachary A; Rochette, Nicholas; Catchen, Julian; Losos, Jonathan B; Edwards, Scott V

2017-08-04

Extreme environmental perturbations offer opportunities to observe the effects of natural selection in wild populations. During the winter of 2013-2014, the southeastern United States endured an extreme cold event. We used thermal performance, transcriptomics, and genome scans to measure responses of lizard populations to storm-induced selection. We found significant increases in cold tolerance at the species' southern limit. Gene expression in southern survivors shifted toward patterns characteristic of northern populations. Comparing samples before and after the extreme winter, 14 genomic regions were differentiated in the surviving southern population; four also exhibited signatures of local adaptation across the latitudinal gradient and implicate genes involved in nervous system function. Together, our results suggest that extreme winter events can rapidly produce strong selection on natural populations at multiple biological levels that recapitulate geographic patterns of local adaptation. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Heat Vulnerability Index Mapping for Milwaukee and Wisconsin.

PubMed

Christenson, Megan; Geiger, Sarah Dee; Phillips, Jeffrey; Anderson, Ben; Losurdo, Giovanna; Anderson, Henry A

Extreme heat waves elevate the population's risk for heat-related morbidity and mortality, specifically for vulnerable groups such as older adults and young children. In this context, we developed 2 Heat Vulnerability Indices (HVIs), one for the state of Wisconsin and one for the Milwaukee metropolitan area. Through the creation of an HVI, state and local agencies will be able to use the indices as a planning tool for extreme heat events. Data used for the HVIs were grouped into 4 categories: (1) population density; (2) health factors; (3) demographic and socioeconomic factors; and (4) natural and built environment factors. These categories were mapped at the Census block group level. Unweighted z-score data were used to determine index scores, which were then mapped by quantiles ranging from "high" to "low" vulnerability. Statewide, Menominee County exhibited the highest vulnerability to extreme heat. Milwaukee HVI findings indicated high vulnerability in the city's inner core versus low vulnerability along the lakeshore. Visualization of vulnerability could help local public health agencies prepare for future extreme heat events.

Cool-Season Moisture Delivery and Multi-Basin Streamflow Anomalies in the Western United States

NASA Astrophysics Data System (ADS)

Malevich, Steven B.

Widespread droughts can have a significant impact on western United States streamflow, but the causes of these events are not fully understood. This dissertation examines streamflow from multiple western US basins and establishes the robust, leading modes of variability in interannual streamflow throughout the past century. I show that approximately 50% of this variability is associated with spatially widespread streamflow anomalies that are statistically independent from streamflow's response to the El Nino-Southern Oscillation (ENSO). The ENSO-teleconnection accounts for approximately 25% of the interannual variability in streamflow, across this network. These atmospheric circulation anomalies associated with the most spatially widespread variability are associated with the Aleutian low and the persistent coastal atmospheric ridge in the Pacific Northwest. I use a watershed segmentation algorithm to explicitly track the position and intensity of these features and compare their variability to the multi-basin streamflow variability. Results show that latitudinal shifts in the coastal atmospheric ridge are more strongly associated with streamflow's north-south dipole response to ENSO variability while more spatially widespread anomalies in streamflow most strongly relate to seasonal changes in the coastal ridge intensity. This likely reflects persistent coastal ridge blocking of cool-season precipitation into western US river basins. I utilize the 35 model runs of the Community Earth System Model Large Ensemble (CESMLE) to determine whether the model ensemble simulates the anomalously strong coastal ridges and extreme widespread wintertime precipitation anomalies found in the observation record. Though there is considerable bias in the CESMLE, the CESMLE runs simulate extremely widespread dry precipitation anomalies with a frequency of approximately one extreme event per century during the historical simulations (1920 - 2005). These extremely widespread dry events correspond significantly with anomalously intense coastal atmospheric ridges. The results from these three papers connect widespread interannual streamflow anomalies in the western US--and especially extremely widespread streamflow droughts--with semi-permanent atmospheric ridge anomalies near the coastal Pacific Northwest. This is important to western US water managers because these widespread events appear to have been a robust feature of the past century. The semi-permanent atmospheric features associated with these widespread dry streamflow anomalies are projected to change position significantly in the next century as a response to global climate change. This may change widespread streamflow anomaly characteristic in the western US, though my results do not show evidence of these changes within the instrument record of last century.

A Generalized Framework for Non-Stationary Extreme Value Analysis

NASA Astrophysics Data System (ADS)

Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.

2017-12-01

Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA accessible to a broader audience.

Do Atmospheric Rivers explain the extreme precipitation events over East Asia?

NASA Astrophysics Data System (ADS)

Dairaku, K.; Nayak, S.

2017-12-01

Extreme precipitation events are now of serious concern due to their damaging societal impacts over last few decades. Thus, climate indices are widely used to identify and quantify variability and changes in particular aspects of the climate system, especially when considering extremes. In our study, we focus on few climate indices of annual precipitation extremes for the period 1979-2013 over East Asia to discuss some straightforward information and interpretation of certain aspects of extreme precipitation events that occur over the region. To do so, we first discuss different percentiles of precipitation and maximum length of wet spell with different thresholds from a regional climate model (NRAMS) simulation at 20km. Results indicate that the 99 percentile of precipitation events correspond to about 80mm/d over few regions of East Asia during 1979-2013 and maximum length of wet spell with minimum 20mm precipitation corresponds to about 10days (Figure 1). We then linked the extreme precipitation events with the intense moisture transport events associated with atmospheric rivers (ARs). The ARs are identified by computing the vertically integrated horizontal water vapor transport (IVT) between 1000hpa and 300hpa with IVT ≥ 250 kg/m/s and 2000 km minimum long. With this threshold and condition (set by previous research), our results indicate that some extreme propitiation events are associated with some ARs over East Asia, while some events are not associated with any ARs. Similarly, some ARs are associated with some extreme precipitation events, while some ARs are not associated with any events. Since the ARs are sensitive to the threshold and condition depending on region, so we will analyze the characteristics of ARs (frequency, duration, and annual variability) with different thresholds and discuss their relationship with extreme precipitation events over East Asia.

A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation

NASA Astrophysics Data System (ADS)

Byun, K.; Hamlet, A. F.

2017-12-01

There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.

Projected changes in snowfall extremes and interannual variability of snowfall in the western United States

NASA Astrophysics Data System (ADS)

Lute, A. C.; Abatzoglou, J. T.; Hegewisch, K. C.

2015-02-01

Projected warming will have significant impacts on snowfall accumulation and melt, with implications for water availability and management in snow-dominated regions. Changes in snowfall extremes are confounded by projected increases in precipitation extremes. Downscaled climate projections from 20 global climate models were bias-corrected to montane Snowpack Telemetry stations across the western United States to assess mid-21st century changes in the mean and variability of annual snowfall water equivalent (SFE) and extreme snowfall events, defined by the 90th percentile of cumulative 3 day SFE amounts. Declines in annual SFE and number of snowfall days were projected for all stations. Changes in the magnitude of snowfall event quantiles were sensitive to historical winter temperature. At climatologically cooler locations, such as in the Rocky Mountains, changes in the magnitude of snowfall events mirrored changes in the distribution of precipitation events, with increases in extremes and less change in more moderate events. By contrast, declines in snowfall event magnitudes were found for all quantiles in warmer locations. Common to both warmer and colder sites was a relative increase in the magnitude of snowfall extremes compared to annual SFE and a larger fraction of annual SFE from snowfall extremes. The coefficient of variation of annual SFE increased up to 80% in warmer montane regions due to projected declines in snowfall days and the increased contribution of snowfall extremes to annual SFE. In addition to declines in mean annual SFE, more frequent low-snowfall years and less frequent high-snowfall years were projected for every station.

Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices

NASA Astrophysics Data System (ADS)

Seo, Seung Beom; Kim, Young-Oh; Kim, Youngil; Eum, Hyung-Il

2018-04-01

When selecting a subset of climate change scenarios (GCM models), the priority is to ensure that the subset reflects the comprehensive range of possible model results for all variables concerned. Though many studies have attempted to improve the scenario selection, there is a lack of studies that discuss methods to ensure that the results from a subset of climate models contain the same range of uncertainty in hydrologic variables as when all models are considered. We applied the Katsavounidis-Kuo-Zhang (KKZ) algorithm to select a subset of climate change scenarios and demonstrated its ability to reduce the number of GCM models in an ensemble, while the ranges of multiple climate extremes indices were preserved. First, we analyzed the role of 27 ETCCDI climate extremes indices for scenario selection and selected the representative climate extreme indices. Before the selection of a subset, we excluded a few deficient GCM models that could not represent the observed climate regime. Subsequently, we discovered that a subset of GCM models selected by the KKZ algorithm with the representative climate extreme indices could not capture the full potential range of changes in hydrologic extremes (e.g., 3-day peak flow and 7-day low flow) in some regional case studies. However, the application of the KKZ algorithm with a different set of climate indices, which are correlated to the hydrologic extremes, enabled the overcoming of this limitation. Key climate indices, dependent on the hydrologic extremes to be projected, must therefore be determined prior to the selection of a subset of GCM models.

High resolution numerical simulation (WRF V3) of an extreme rainy event over the Guadeloupe archipelago: Case of 3-5 january 2011.

NASA Astrophysics Data System (ADS)

Bernard, Didier C.; Cécé, Raphaël; Dorville, Jean-François

2013-04-01

During the dry season, the Guadeloupe archipelago may be affected by extreme rainy disturbances which may induce floods in a very short time. C. Brévignon (2003) considered a heavy rain event for rainfall upper 100 mm per day (out of mountainous areas) for this tropical region. During a cold front passage (3-5 January 2011), torrential rainfalls caused floods, major damages, landslides and five deaths. This phenomenon has put into question the current warning system based on large scale numerical models. This low-resolution forecasting (around 50-km scale) has been unsuitable for small tropical island like Guadeloupe (1600 km2). The most affected area was the middle of Grande-Terre island which is the main flat island of the archipelago (area of 587 km2, peak at 136 m). It is the most populated sector of Guadeloupe. In this area, observed rainfall have reached to 100-160 mm in 24 hours (this amount is equivalent to two months of rain for January (C. Brévignon, 2003)), in less 2 hours drainage systems have been saturated, and five people died in a ravine. Since two years, the atmospheric model WRF ARW V3 (Skamarock et al., 2008) has been used to modeling meteorological variables fields observed over the Guadeloupe archipelago at high resolution 1-km scale (Cécé et al., 2011). The model error estimators show that meteorological variables seem to be properly simulated for standard types of weather: undisturbed, strong or weak trade winds. These simulations indicate that for synoptic winds weak to moderate, a small island like Grande-Terre is able to generate inland convergence zones during daytime. In this presentation, we apply this high resolution model to simulate this extreme rainy disturbance of 3-5 January 2011. The evolution of modeling meteorological variable fields is analyzed in the most affected area of Grande-Terre (city of Les Abymes). The main goal is to examine local quasi-stationary updraft systems and highlight their convective mechanisms. The spatio-temporal distribution of simulated rainfall could help to design the prevention and evacuation plan, particularly for the flooding areas. The meteorological variable fields simulated are evaluated by comparison with observed data of meteorological weather stations (French Met. Office) available in the area. Brévignon, C., 2003: Atlas climatique: l'environnement atmosphérique de la Guadeloupe, de Saint-Barthélémy et Saint-martin. Météo-France, Service Régional de Guadeloupe, 92 pp. Cécé, R., T. Plocoste, C. D'Alexis, D. Bernard and J.-F. Dorville, 2012: Modélisation numérique à l'échelle locale des situations météorologiques observées au cours de la transition saison sèche - saison humide à l'aide de WRF ARW V3 : cas de l'archipel de la Guadeloupe. AMA 2012, Toulouse. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A Description of the Advanced Research WRF Version 3.Tech. Rep., National Center for Atmospheric Research.

Multivariate hydrological frequency analysis for extreme events using Archimedean copula. Case study: Lower Tunjuelo River basin (Colombia)

NASA Astrophysics Data System (ADS)

Gómez, Wilmar

2017-04-01

By analyzing the spatial and temporal variability of extreme precipitation events we can prevent or reduce the threat and risk. Many water resources projects require joint probability distributions of random variables such as precipitation intensity and duration, which can not be independent with each other. The problem of defining a probability model for observations of several dependent variables is greatly simplified by the joint distribution in terms of their marginal by taking copulas. This document presents a general framework set frequency analysis bivariate and multivariate using Archimedean copulas for extreme events of hydroclimatological nature such as severe storms. This analysis was conducted in the lower Tunjuelo River basin in Colombia for precipitation events. The results obtained show that for a joint study of the intensity-duration-frequency, IDF curves can be obtained through copulas and thus establish more accurate and reliable information from design storms and associated risks. It shows how the use of copulas greatly simplifies the study of multivariate distributions that introduce the concept of joint return period used to represent the needs of hydrological designs properly in frequency analysis.

Early prediction of extreme stratospheric polar vortex states based on causal precursors

NASA Astrophysics Data System (ADS)

Kretschmer, Marlene; Runge, Jakob; Coumou, Dim

2017-08-01

Variability in the stratospheric polar vortex (SPV) can influence the tropospheric circulation and thereby winter weather. Early predictions of extreme SPV states are thus important to improve forecasts of winter weather including cold spells. However, dynamical models are usually restricted in lead time because they poorly capture low-frequency processes. Empirical models often suffer from overfitting problems as the relevant physical processes and time lags are often not well understood. Here we introduce a novel empirical prediction method by uniting a response-guided community detection scheme with a causal discovery algorithm. This way, we objectively identify causal precursors of the SPV at subseasonal lead times and find them to be in good agreement with known physical drivers. A linear regression prediction model based on the causal precursors can explain most SPV variability (r2 = 0.58), and our scheme correctly predicts 58% (46%) of extremely weak SPV states for lead times of 1-15 (16-30) days with false-alarm rates of only approximately 5%. Our method can be applied to any variable relevant for (sub)seasonal weather forecasts and could thus help improving long-lead predictions.

Multi-hazard Assessment and Scenario Toolbox (MhAST): A Framework for Analyzing Compounding Effects of Multiple Hazards

NASA Astrophysics Data System (ADS)

Sadegh, M.; Moftakhari, H.; AghaKouchak, A.

2017-12-01

Many natural hazards are driven by multiple forcing variables, and concurrence/consecutive extreme events significantly increases risk of infrastructure/system failure. It is a common practice to use univariate analysis based upon a perceived ruling driver to estimate design quantiles and/or return periods of extreme events. A multivariate analysis, however, permits modeling simultaneous occurrence of multiple forcing variables. In this presentation, we introduce the Multi-hazard Assessment and Scenario Toolbox (MhAST) that comprehensively analyzes marginal and joint probability distributions of natural hazards. MhAST also offers a wide range of scenarios of return period and design levels and their likelihoods. Contribution of this study is four-fold: 1. comprehensive analysis of marginal and joint probability of multiple drivers through 17 continuous distributions and 26 copulas, 2. multiple scenario analysis of concurrent extremes based upon the most likely joint occurrence, one ruling variable, and weighted random sampling of joint occurrences with similar exceedance probabilities, 3. weighted average scenario analysis based on a expected event, and 4. uncertainty analysis of the most likely joint occurrence scenario using a Bayesian framework.