Sensitivity of Hydrologic Extremes to Spatial Resolution of Meteorological Forcings: A Case Study of the Conterminous United States

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.; Ashfaq, M.; Rastogi, D.

2016-12-01

The magnitude and frequency of hydroclimate extremes are projected to increase in the conterminous United States (CONUS) with significant implications for future water resource planning and flood risk management. Nevertheless, apart from the change of natural environment, the choice of model spatial resolution could also artificially influence the features of simulated extremes. To better understand how the spatial resolution of meteorological forcings may affect hydroclimate projections, we test the runoff sensitivity using the Variable Infiltration Capacity (VIC) model that was calibrated for each CONUS 8-digit hydrologic unit (HUC8) at 1/24° ( 4km) grid resolution. The 1980-2012 gridded Daymet and PRISM meteorological observations are used to conduct the 1/24° resolution control simulation. Comparative simulations are achieved by smoothing the 1/24° forcing into 1/12° and 1/8° resolutions which are then used to drive the VIC model for the CONUS. In addition, we also test how the simulated high and low runoff conditions would react to change in precipitation (±10%) and temperature (+1°C). The results are further analyzed for various types of hydroclimate extremes across different watersheds in the CONUS. This work helps us understand the sensitivity of simulated runoff to different spatial resolutions of climate forcings and also its sensitivity to different watershed sizes and characteristics of extreme events in the future climate conditions.

Spatial and temporal variation in daily temperature indices in summer and winter seasons over India (1969-2012)

NASA Astrophysics Data System (ADS)

Kumar, Naresh; Jaswal, A. K.; Mohapatra, M.; Kore, P. A.

2017-08-01

Spatial and temporal variations in summer and winter extreme temperature indices are studied by using daily maximum and minimum temperatures data from 227 surface meteorological stations well distributed over India for the period 1969-2012. For this purpose, time series for six extreme temperature indices namely, hot days (HD), very hot days (VHD), extremely hot days (EHD), cold nights (CN), very cold nights (VCN), and extremely cold nights (ECN) are calculated for all the stations. In addition, time series for mean extreme temperature indices of summer and winter seasons are also analyzed. Study reveals high variability in spatial distribution of threshold temperatures of extreme temperature indices over the country. In general, increasing trends are observed in summer hot days indices and decreasing trends in winter cold night indices over most parts of the country. The results obtained in this study indicate warming in summer maximum and winter minimum temperatures over India. Averaged over India, trends in summer hot days indices HD, VHD, and EHD are significantly increasing (+1.0, +0.64, and +0.32 days/decade, respectively) and winter cold night indices CN, VCN, and ECN are significantly decreasing (-0.93, -0.47, and -0.15 days/decade, respectively). Also, it is observed that the impact of extreme temperature is higher along the west coast for summer and east coast for winter.

Temporal and spatial scaling impacts on extreme precipitation

NASA Astrophysics Data System (ADS)

Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.

2015-01-01

Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.

Spatiotemporal variability of rainfall extremes in monsoonal climates - examples from the South American Monsoon and the Indian Monsoon Systems (Invited)

NASA Astrophysics Data System (ADS)

Bookhagen, B.; Boers, N.; Marwan, N.; Malik, N.; Kurths, J.

2013-12-01

Monsoonal rainfall is the crucial component for more than half of the world's population. Runoff associated with monsoon systems provide water resources for agriculture, hydropower, drinking-water generation, recreation, and social well-being and are thus a fundamental part of human society. However, monsoon systems are highly stochastic and show large variability on various timescales. Here, we use various rainfall datasets to characterize spatiotemporal rainfall patterns using traditional as well as new approaches emphasizing nonlinear spatial correlations from a complex networks perspective. Our analyses focus on the South American (SAMS) and Indian (ISM) Monsoon Systems on the basis of Tropical Rainfall Measurement Mission (TRMM) using precipitation radar and passive-microwave products with horizontal spatial resolutions of ~5x5 km^2 (products 2A25, 2B31) and 25x25 km^2 (3B42) and interpolated rainfall-gauge data for the ISM (APHRODITE, 25x25 km^2). The eastern slopes of the Andes of South America and the southern front of the Himalaya are characterized by significant orographic barriers that intersect with the moisture-bearing, monsoonal wind systems. We demonstrate that topography exerts a first-order control on peak rainfall amounts on annual timescales in both mountain belts. Flooding in the downstream regions is dominantly caused by heavy rainfall storms that propagate deep into the mountain range and reach regions that are arid and without vegetation cover promoting rapid runoff. These storms exert a significantly different spatial distribution than average-rainfall conditions and assessing their recurrence intervals and prediction is key in understanding flooding for these regions. An analysis of extreme-value distributions of our high-spatial resolution data reveal that semi-arid areas are characterized by low-frequency/high-magnitude events (i.e., are characterized by a ';heavy tail' distribution), whereas regions with high mean annual rainfall have a less skewed distribution. In a second step, an analysis of the spatial characteristics of extreme rainfall synchronicity by means of complex networks reveals patterns of the propagation of extreme rainfall events. These patterns differ substantially from those obtained from the mean annual rainfall distribution. In addition, we have developed a scheme to predict rainfall extreme events in the eastern Central Andes based on event synchronization and spatial patterns of complex networks. The presented methods and result will allow to critically evaluate data and models in space and time.

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

NASA Astrophysics Data System (ADS)

Mascaro, Giuseppe

2018-04-01

This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

High Spatial Resolution Thermal Satellite Technologies

NASA Technical Reports Server (NTRS)

Ryan, Robert

2003-01-01

This document in the form of viewslides, reviews various low-cost alternatives to high spatial resolution thermal satellite technologies. There exists no follow-on to Landsat 7 or ASTER high spatial resolution thermal systems. This document reviews the results of the investigation in to the use of new technologies to create a low-cost useful alternative. Three suggested technologies are examined. 1. Conventional microbolometer pushbroom modes offers potential for low cost Landsat Data Continuity Mission (LDCM) thermal or ASTER capability with at least 60-120 ground sampling distance (GSD). 2. Backscanning could produce MultiSpectral Thermal Imager performance without cooled detectors. 3. Cooled detector could produce hyperspectral thermal class system or extremely high spatial resolution class instrument.

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.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Soil variability along a nitrogen mineralization and nitrification gradient in a nitrogen-saturated hardwood forest

Treesearch

Frank S. Gilliam; Nikki L. Lyttle; Ashley Thomas; Mary Beth Adams

2005-01-01

Some N-saturated watersheds of the Fernow Experimental Forest (FEF), West Virginia, exhibit a high degree of spatial heterogeneity in soil N processing. We used soils from four sites at FEF representing a gradient in net N mineralization and nitrification to consider the causes and consequences of such spatial heterogeneity. We collected soils with extremely high vs....

Analysis and trends of precipitation lapse rate and extreme indices over north Sikkim eastern Himalayas under CMIP5ESM-2M RCPs experiments

NASA Astrophysics Data System (ADS)

Singh, Vishal; Goyal, Manish Kumar

2016-01-01

This paper draws attention to highlight the spatial and temporal variability in precipitation lapse rate (PLR) and precipitation extreme indices (PEIs) through the mesoscale characterization of Teesta river catchment, which corresponds to north Sikkim eastern Himalayas. A PLR rate is an important variable for the snowmelt runoff models. In a mountainous region, the PLR could be varied from lower elevation parts to high elevation parts. In this study, a PLR was computed by accounting elevation differences, which varies from around 1500 m to 7000 m. A precipitation variability and extremity were analysed using multiple mathematical functions viz. quantile regression, spatial mean, spatial standard deviation, Mann-Kendall test and Sen's estimation. For this reason, a daily precipitation, in the historical (years 1980-2005) as measured/observed gridded points and projected experiments for the 21st century (years 2006-2100) simulated by CMIP5 ESM-2 M model (Coupled Model Intercomparison Project Phase 5 Earth System Model 2) employing three different radiative forcing scenarios (Representative Concentration Pathways), utilized for the research work. The outcomes of this study suggest that a PLR is significantly varied from lower elevation to high elevation parts. The PEI based analysis showed that the extreme high intensity events have been increased significantly, especially after 2040s. The PEI based observations also showed that the numbers of wet days are increased for all the RCPs. The quantile regression plots showed significant increments in the upper and lower quantiles of the various extreme indices. The Mann-Kendall test and Sen's estimation tests clearly indicated significant changing patterns in the frequency and intensity of the precipitation indices across all the sub-basins and RCP scenario in an intra-decadal time series domain. The RCP8.5 showed extremity of the projected outcomes.

Analysis of the dependence of extreme rainfalls

NASA Astrophysics Data System (ADS)

Padoan, Simone; Ancey, Christophe; Parlange, Marc

2010-05-01

The aim of spatial analysis is to quantitatively describe the behavior of environmental phenomena such as precipitation levels, wind speed or daily temperatures. A number of generic approaches to spatial modeling have been developed[1], but these are not necessarily ideal for handling extremal aspects given their focus on mean process levels. The areal modelling of the extremes of a natural process observed at points in space is important in environmental statistics; for example, understanding extremal spatial rainfall is crucial in flood protection. In light of recent concerns over climate change, the use of robust mathematical and statistical methods for such analyses has grown in importance. Multivariate extreme value models and the class of maxstable processes [2] have a similar asymptotic motivation to the univariate Generalized Extreme Value (GEV) distribution , but providing a general approach to modeling extreme processes incorporating temporal or spatial dependence. Statistical methods for max-stable processes and data analyses of practical problems are discussed by [3] and [4]. This work illustrates methods to the statistical modelling of spatial extremes and gives examples of their use by means of a real extremal data analysis of Switzerland precipitation levels. [1] Cressie, N. A. C. (1993). Statistics for Spatial Data. Wiley, New York. [2] de Haan, L and Ferreria A. (2006). Extreme Value Theory An Introduction. Springer, USA. [3] Padoan, S. A., Ribatet, M and Sisson, S. A. (2009). Likelihood-Based Inference for Max-Stable Processes. Journal of the American Statistical Association, Theory & Methods. In press. [4] Davison, A. C. and Gholamrezaee, M. (2009), Geostatistics of extremes. Journal of the Royal Statistical Society, Series B. To appear.

Variations in extreme precipitation on the Loess Plateau using a high-resolution dataset and their linkages with atmospheric circulation indices

NASA Astrophysics Data System (ADS)

Zhao, Guangju; Zhai, Jianqing; Tian, Peng; Zhang, Limei; Mu, Xingmin; An, Zhengfeng; Han, Mengwei

2017-08-01

Assessing regional patterns and trends in extreme precipitation is crucial for facilitating flood control and drought adaptation because extreme climate events have more damaging impacts on society and ecosystems than simple shifts in the mean values. In this study, we employed daily precipitation data from 231 climate stations spanning 1961 to 2014 to explore the changes in precipitation extremes on the Loess Plateau, China. Nine of the 12 extreme precipitation indices suggested decreasing trends, and only the annual total wet-day precipitation (PRCPTOT) and R10 declined significantly: - 0.69 mm/a and - 0.023 days/a at the 95% confidence level. The spatial patterns in all of the extreme precipitation indices indicated mixed trends on the Loess Plateau, with decreasing trends in the precipitation extremes at the majority of the stations examined in the Fen-Wei River valley and high-plain plateau. Most of extreme precipitation indices suggested apparent regional differences, whereas R25 and R20 had spatially similar patterns on the Loess Plateau, with many stations revealing no trends. In addition, we found a potential decreasing trend in rainfall amounts and rainy days and increasing trends in rainfall intensities and storm frequencies in some regions due to increasing precipitation events in recent years. The relationships between extreme rainfall events and atmospheric circulation indices suggest that the weakening trend in the East Asia summer monsoon has limited the northward extension of the rainfall belt to northern China, thereby leading to a decrease in rainfall on the Loess Plateau.

High Spatial Resolution MRI of Cystic Adventitial Disease of the Iliofemoral Vein Communicating with the Hip Joint

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

Michaelides, Michael, E-mail: mihalismihailidis@gmail.com; Papas, Stylianos, E-mail: vascular@drpapas.com; Pantziara, Maria, E-mail: mgpantziara@gmail.com

2013-05-14

Venous cystic adventitial disease (CAD) is an extremely rare entity, and so far less than 20 cases have been described in the literature. Herein, we describe the imaging findings of CAD of iliofemoral vein in a 51-year-old woman who presented with leg swelling with special emphasis on high spatial resolution MRI, which demonstrated communication of the cyst with the hip joint. To our knowledge, this is the first description of high spatial resolution MRI findings in venous CAD supporting a new theory about the pathogenesis of venous CAD.

Characterizing the Spatial Contiguity of Extreme Precipitation over the US in the Recent Past

NASA Astrophysics Data System (ADS)

Touma, D. E.; Swain, D. L.; Diffenbaugh, N. S.

2016-12-01

The spatial characteristics of extreme precipitation over an area can define the hydrologic response in a basin, subsequently affecting the flood risk in the region. Here, we examine the spatial extent of extreme precipitation in the US by defining its "footprint": a contiguous area of rainfall exceeding a certain threshold (e.g., 90th percentile) on a given day. We first characterize the climatology of extreme rainfall footprint sizes across the US from 1980-2015 using Daymet, a high-resolution observational gridded rainfall dataset. We find that there are distinct regional and seasonal differences in average footprint sizes of extreme daily rainfall. In the winter, the Midwest shows footprints exceeding 500,000 sq. km while the Front Range exhibits footprints of 10,000 sq. km. Alternatively, the summer average footprint size is generally smaller and more uniform across the US, ranging from 10,000 sq. km in the Southwest to 100,000 sq. km in Montana and North Dakota. Moreover, we find that there are some significant increasing trends of average footprint size between 1980-2015, specifically in the Southwest in the winter and the Northeast in the spring. While gridded daily rainfall datasets allow for a practical framework in calculating footprint size, this calculation heavily depends on the interpolation methods that have been used in creating the dataset. Therefore, we assess footprint size using the GHCN-Daily station network and use geostatistical methods to define footprints of extreme rainfall directly from station data. Compared to the findings from Daymet, preliminary results using this method show fewer small daily footprint sizes over the US while large footprints are of similar number and magnitude to Daymet. Overall, defining the spatial characteristics of extreme rainfall as well as observed and expected changes in these characteristics allows us to better understand the hydrologic response to extreme rainfall and how to better characterize flood risks.

Real-time and sub-wavelength ultrafast coherent diffraction imaging in the extreme ultraviolet.

PubMed

Zürch, M; Rothhardt, J; Hädrich, S; Demmler, S; Krebs, M; Limpert, J; Tünnermann, A; Guggenmos, A; Kleineberg, U; Spielmann, C

2014-12-08

Coherent Diffraction Imaging is a technique to study matter with nanometer-scale spatial resolution based on coherent illumination of the sample with hard X-ray, soft X-ray or extreme ultraviolet light delivered from synchrotrons or more recently X-ray Free-Electron Lasers. This robust technique simultaneously allows quantitative amplitude and phase contrast imaging. Laser-driven high harmonic generation XUV-sources allow table-top realizations. However, the low conversion efficiency of lab-based sources imposes either a large scale laser system or long exposure times, preventing many applications. Here we present a lensless imaging experiment combining a high numerical aperture (NA = 0.8) setup with a high average power fibre laser driven high harmonic source. The high flux and narrow-band harmonic line at 33.2 nm enables either sub-wavelength spatial resolution close to the Abbe limit (Δr = 0.8λ) for long exposure time, or sub-70 nm imaging in less than one second. The unprecedented high spatial resolution, compactness of the setup together with the real-time capability paves the way for a plethora of applications in fundamental and life sciences.

Atomic force microscopy characterization of Zerodur mirror substrates for the extreme ultraviolet telescopes aboard NASA's Solar Dynamics Observatory.

PubMed

Soufli, Regina; Baker, Sherry L; Windt, David L; Gullikson, Eric M; Robinson, Jeff C; Podgorski, William A; Golub, Leon

2007-06-01

The high-spatial frequency roughness of a mirror operating at extreme ultraviolet (EUV) wavelengths is crucial for the reflective performance and is subject to very stringent specifications. To understand and predict mirror performance, precision metrology is required for measuring the surface roughness. Zerodur mirror substrates made by two different polishing vendors for a suite of EUV telescopes for solar physics were characterized by atomic force microscopy (AFM). The AFM measurements revealed features in the topography of each substrate that are associated with specific polishing techniques. Theoretical predictions of the mirror performance based on the AFM-measured high-spatial-frequency roughness are in good agreement with EUV reflectance measurements of the mirrors after multilayer coating.

Evaluating the extreme precipitation events using a mesoscale atmopshere model

NASA Astrophysics Data System (ADS)

Yucel, I.; Onen, A.

2012-04-01

Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. Mesoscale atmospheric models coupled with land surface models provide efficient forecasts for meteorological events in high lead time and therefore they should be used for flood forecasting and warning issues as they provide more continuous monitoring of precipitation over large areas. This study examines the performance of the Weather Research and Forecasting (WRF) model in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in West Black Sea Region of Turkey. Extreme precipitation events usually resulted in flood conditions as an associated hydrologic response of the basin. The performance of the WRF system is further investigated by using the three dimensional variational (3D-VAR) data assimilation scheme within WRF. WRF performance with and without data assimilation at high spatial resolution (4 km) is evaluated by making comparison with gauge precipitation and satellite-estimated rainfall data from Multi Precipitation Estimates (MPE). WRF-derived precipitation showed capabilities in capturing the timing of the precipitation extremes and in some extent spatial distribution and magnitude of the heavy rainfall events. These precipitation characteristics are enhanced with the use of 3D-VAR scheme in WRF system. Data assimilation improved area-averaged precipitation forecasts by 9 percent and at some points there exists quantitative match in precipitation events, which are critical for hydrologic forecast application.

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.

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).

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.

Effects of ignition location models on the burn patterns of simulated wildfires

USGS Publications Warehouse

Bar-Massada, A.; Syphard, A.D.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2011-01-01

Fire simulation studies that use models such as FARSITE often assume that ignition locations are distributed randomly, because spatially explicit information about actual ignition locations are difficult to obtain. However, many studies show that the spatial distribution of ignition locations, whether human-caused or natural, is non-random. Thus, predictions from fire simulations based on random ignitions may be unrealistic. However, the extent to which the assumption of ignition location affects the predictions of fire simulation models has never been systematically explored. Our goal was to assess the difference in fire simulations that are based on random versus non-random ignition location patterns. We conducted four sets of 6000 FARSITE simulations for the Santa Monica Mountains in California to quantify the influence of random and non-random ignition locations and normal and extreme weather conditions on fire size distributions and spatial patterns of burn probability. Under extreme weather conditions, fires were significantly larger for non-random ignitions compared to random ignitions (mean area of 344.5 ha and 230.1 ha, respectively), but burn probability maps were highly correlated (r = 0.83). Under normal weather, random ignitions produced significantly larger fires than non-random ignitions (17.5 ha and 13.3 ha, respectively), and the spatial correlations between burn probability maps were not high (r = 0.54), though the difference in the average burn probability was small. The results of the study suggest that the location of ignitions used in fire simulation models may substantially influence the spatial predictions of fire spread patterns. However, the spatial bias introduced by using a random ignition location model may be minimized if the fire simulations are conducted under extreme weather conditions when fire spread is greatest. ?? 2010 Elsevier Ltd.

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

Analysis of extreme rain and flood events using a regional hydrologically enhanced hydrometeorological system

NASA Astrophysics Data System (ADS)

Yucel, Ismail; Onen, Alper

2013-04-01

Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. Regional hydrometeorological system model which couples the atmosphere with physical and gridded based surface hydrology provide efficient predictions for extreme hydrological events. This modeling system can be used for flood forecasting and warning issues as they provide continuous monitoring of precipitation over large areas at high spatial resolution. This study examines the performance of the Weather Research and Forecasting (WRF-Hydro) model that performs the terrain, sub-terrain, and channel routing in producing streamflow from WRF-derived forcing of extreme precipitation events. The capability of the system with different options such as data assimilation is tested for number of flood events observed in basins of western Black Sea Region in Turkey. Rainfall event structures and associated flood responses are evaluated with gauge and satellite-derived precipitation and measured streamflow values. The modeling system shows skills in capturing the spatial and temporal structure of extreme rainfall events and resulted flood hydrographs. High-resolution routing modules activated in the model enhance the simulated discharges.

Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

NASA Astrophysics Data System (ADS)

Rupa, Chandra; Mujumdar, Pradeep

2016-04-01

In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings algorithm within a Gibbs sampler) is used to obtain the samples of parameters from the posterior distribution of parameters. The spatial maps of return levels for specified return periods, along with the associated uncertainties, are obtained for the summer, monsoon and annual maxima rainfall. Considering various covariates, the best fit model is selected using Deviance Information Criteria. It is observed that the geographical covariates outweigh the climatological covariates for the monsoon maxima rainfall (latitude and longitude). The best covariates for summer maxima and annual maxima rainfall are mean summer precipitation and mean monsoon precipitation respectively, including elevation for both the cases. The scale invariance theory, which states that statistical properties of a process observed at various scales are governed by the same relationship, is used to disaggregate the daily rainfall to hourly scales. The spatial maps of the scale are obtained for the study area. The spatial maps of IDF relationships thus generated are useful in storm water designs, adequacy analysis and identifying the vulnerable flooding areas.

Examining the Feasibility, Tolerability, and Preliminary Efficacy of Repetitive Task-Specific Practice for People With Unilateral Spatial Neglect

PubMed Central

Lang, Catherine E.; Birkenmeier, Rebecca; Holm, Margo; Rubinstein, Elaine; Van Swearingen, Jessie; Skidmore, Elizabeth R.

2016-01-01

OBJECTIVE. We examined the feasibility, tolerability, and preliminary efficacy of repetitive task-specific practice for people with unilateral spatial neglect (USN). METHOD. People with USN ≥6 mo poststroke participated in a single-group, repeated-measures study. Attendance, total repetitions, and satisfaction indicated feasibility and pain indicated tolerability. Paired t tests and effect sizes were used to estimate changes in upper-extremity use (Motor Activity Log), function (Action Research Arm Test), and attention (Catherine Bergego Scale). RESULTS. Twenty participants attended 99.4% of sessions and completed a high number of repetitions. Participants reported high satisfaction and low pain, and they demonstrated small, significant improvements in upper-extremity use (before Bonferroni corrections; t = –2.1, p = .04, d = .30), function (t = –3.0, p < .01, d = .20), and attention (t = –3.4, p < .01, d = –.44). CONCLUSION. Repetitive task-specific practice is feasible and tolerable for people with USN. Improvements in upper-extremity use, function, and attention may be attainable. PMID:27294994

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

PubMed Central

Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

2016-01-01

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

PubMed

Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S

2016-01-01

India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

On the nonlinearity of spatial scales in extreme weather attribution statements

NASA Astrophysics Data System (ADS)

Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; Alexander, Lisa V.; Wehner, Michael; Shiogama, Hideo; Wolski, Piotr; Ciavarella, Andrew; Christidis, Nikolaos

2018-04-01

In the context of ongoing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporal scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.

On the nonlinearity of spatial scales in extreme weather attribution statements

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

Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah

In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less

On the nonlinearity of spatial scales in extreme weather attribution statements

DOE PAGES

Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; ...

2017-06-17

In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less

Sideband-Separating, Millimeter-Wave Heterodyne Receiver

NASA Technical Reports Server (NTRS)

Ward, John S.; Bumble, Bruce; Lee, Karen A.; Kawamura, Jonathan H.; Chattopadhyay, Goutam; Stek, paul; Stek, Paul

2010-01-01

Researchers have demonstrated a submillimeter-wave spectrometer that combines extremely broad bandwidth with extremely high sensitivity and spectral resolution to enable future spacecraft to measure the composition of the Earth s troposphere in three dimensions many times per day at spatial resolutions as high as a few kilometers. Microwave limb sounding is a proven remote-sensing technique that measures thermal emission spectra from molecular gases along limb views of the Earth s atmosphere against a cold space background.

Long-term trend of satellite-observed significant wave height and impact on ecosystem in the East/Japan Sea

NASA Astrophysics Data System (ADS)

Woo, Hye-Jin; Park, Kyung-Ae

2017-09-01

Significant wave height (SWH) data of nine satellite altimeters were validated with in-situ SWH measurements from buoy stations in the East/Japan Sea (EJS) and the Northwest Pacific Ocean. The spatial and temporal variability of extreme SWHs was investigated by defining the 90th, 95th, and 99th percentiles based on percentile analysis. The annual mean of extreme SWHs was dramatically increased by 3.45 m in the EJS, which is significantly higher than the normal mean of about 1.44 m. The spatial distributions of SWHs showed significantly higher values in the eastern region of the EJS than those in the western part. Characteristic seasonality was found from the time-series SWHs with high SWHs (>2.5 m) in winter but low values (<1 m) in summer. The trends of the normal and extreme (99th percentile) SWHs in the EJS had a positive value of 0.0056 m year-1 and 0.0125 m year-1, respectively. The long-term trend demonstrated that higher SWH values were more extreme with time during the past decades. The predominant spatial distinctions between the coastal regions in the marginal seas of the Northwest Pacific Ocean and open ocean regions were presented. In spring, both normal and extreme SWHs showed substantially increasing trends in the EJS. Finally, we first presented the impact of the long-term trend of extreme SWHs on the marine ecosystem through vertical mixing enhancement in the upper ocean of the EJS.

Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

NASA Astrophysics Data System (ADS)

Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.

2017-12-01

Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed in this analysis, preliminary results from the development of a flexible categorization scheme, that scales with grid resolution, are presented.

Full Spatial Resolution Infrared Sounding Application in the Preconvection Environment

NASA Astrophysics Data System (ADS)

Liu, C.; Liu, G.; Lin, T.

2013-12-01

Advanced infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) provide atmospheric temperature and moisture profiles with high vertical resolution and high accuracy in preconvection environments. The derived atmospheric stability indices such as convective available potential energy (CAPE) and lifted index (LI) from advanced IR soundings can provide critical information 1 ; 6 h before the development of severe convective storms. Three convective storms are selected for the evaluation of applying AIRS full spatial resolution soundings and the derived products on providing warning information in the preconvection environments. In the first case, the AIRS full spatial resolution soundings revealed local extremely high atmospheric instability 3 h ahead of the convection on the leading edge of a frontal system, while the second case demonstrates that the extremely high atmospheric instability is associated with the local development of severe thunderstorm in the following hours. The third case is a local severe storm that occurred on 7-8 August 2010 in Zhou Qu, China, which caused more than 1400 deaths and left another 300 or more people missing. The AIRS full spatial resolution LI product shows the atmospheric instability 3.5 h before the storm genesis. The CAPE and LI from AIRS full spatial resolution and operational AIRS/AMSU soundings along with Geostationary Operational Environmental Satellite (GOES) Sounder derived product image (DPI) products were analyzed and compared. Case studies show that full spatial resolution AIRS retrievals provide more useful warning information in the preconvection environments for determining favorable locations for convective initiation (CI) than do the coarser spatial resolution operational soundings and lower spectral resolution GOES Sounder retrievals. The retrieved soundings are also tested in a regional data assimilation WRF 3D-var system to evaluate the potential assist in the NWP model.

Spatial dependence of extreme rainfall

NASA Astrophysics Data System (ADS)

Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

2017-05-01

This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

Atomic force microscopy characterization of Zerodur mirror substrates for the extreme ultraviolet telescopes aboard NASA's Solar Dynamics Observatory

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

Soufli, Regina; Baker, Sherry L.; Windt, David L.

2007-06-01

The high-spatial frequency roughness of a mirror operating at extreme ultraviolet (EUV)wavelengths is crucial for the reflective performance and is subject to very stringent specifications. To understand and predict mirror performance, precision metrology is required for measuring the surface roughness. Zerodur mirror substrates made by two different polishing vendors for a suite of EUV telescopes for solar physics were characterized by atomic force microscopy (AFM). The AFM measurements revealed features in the topography of each substrate that are associated with specific polishing techniques. Theoretical predictions of the mirror performance based on the AFM-measured high-spatial-frequency roughness are in good agreement withmore » EUV reflectance measurements of the mirrors after multilayer coating.« less

Changing Pattern of Indian Monsoon Extremes: Global and Local Factors

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Shastri, Hiteshri; Pathak, Amey; Paul, Supantha

2017-04-01

Indian Summer Monsoon Rainfall (ISMR) extremes have remained a major topic of discussion in the field of global change and hydro-climatology over the last decade. This attributes to multiple conclusions on changing pattern of extremes along with poor understanding of multiple processes at global and local scales associated with monsoon extremes. At a spatially aggregate scale, when number of extremes in the grids are summed over, a statistically significant increasing trend is observed for both Central India (Goswami et al., 2006) and all India (Rajeevan et al., 2008). However, such a result over Central India does not satisfy flied significance test of increase and no decrease (Krishnamurthy et al., 2009). Statistically rigorous extreme value analysis that deals with the tail of the distribution reveals a spatially non-uniform trend of extremes over India (Ghosh et al., 2012). This results into statistically significant increasing trend of spatial variability. Such an increase of spatial variability points to the importance of local factors such as deforestation and urbanization. We hypothesize that increase of spatial average of extremes is associated with the increase of events occurring over large region, while increase in spatial variability attributes to local factors. A Lagrangian approach based dynamic recycling model reveals that the major contributor of moisture to wide spread extremes is Western Indian Ocean, while land surface also contributes around 25-30% of moisture during the extremes in Central India. We further test the impacts of local urbanization on extremes and find the impacts are more visible over West central, Southern and North East India. Regional atmospheric simulations coupled with Urban Canopy Model (UCM) shows that urbanization intensifies extremes in city areas, but not uniformly all over the city. The intensification occurs over specific pockets of the urban region, resulting an increase in spatial variability even within the city. This also points to the need of setting up multiple weather stations over the city at a finer resolution for better understanding of urban extremes. We conclude that the conventional method of considering large scale factors is not sufficient for analysing the monsoon extremes and characterization of the same needs a blending of both global and local factors. Ghosh, S., Das, D., Kao, S-C. & Ganguly, A. R. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Clim. Change 2, 86-91 (2012) Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S. & Xavier, P. K. Increasing trend of extreme rain events over India in a warming environment. Science 314, 1442-1445 (2006). Krishnamurthy, C. K. B., Lall, U. & Kwon, H-H. Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Clim. 22, 4737-4746 (2009). Rajeevan, M., Bhate, J. & Jaswal, A. K. Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys. Res. Lett. 35, L18707 (2008).

Synoptic Conditions and Moisture Sources Actuating Extreme Precipitation in Nepal

NASA Astrophysics Data System (ADS)

Bohlinger, Patrik; Sorteberg, Asgeir; Sodemann, Harald

2017-12-01

Despite the vast literature on heavy-precipitation events in South Asia, synoptic conditions and moisture sources related to extreme precipitation in Nepal have not been addressed systematically. We investigate two types of synoptic conditions—low-pressure systems and midlevel troughs—and moisture sources related to extreme precipitation events. To account for the high spatial variability in rainfall, we cluster station-based daily precipitation measurements resulting in three well-separated geographic regions: west, central, and east Nepal. For each region, composite analysis of extreme events shows that atmospheric circulation is directed against the Himalayas during an extreme event. The direction of the flow is regulated by midtropospheric troughs and low-pressure systems traveling toward the respective region. Extreme precipitation events feature anomalous high abundance of total column moisture. Quantitative Lagrangian moisture source diagnostic reveals that the largest direct contribution stems from land (approximately 75%), where, in particular, over the Indo-Gangetic Plain moisture uptake was increased. Precipitation events occurring in this region before the extreme event likely provided additional moisture.

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.

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.

NLDAS Views of North American 2011 Extreme Events

NASA Technical Reports Server (NTRS)

Rui, Hualan; Teng, William L.; Vollmer, Bruce; Mocko, David; Lei, Guang-Dih

2014-01-01

2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http:ldas.gsfc.nasa.govnldas) data set, with high spatial and temporal resolutions (0.125 x 0.125, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

Analysis of Extreme Snow Water Equivalent Data in Central New Hampshire

NASA Astrophysics Data System (ADS)

Vuyovich, C.; Skahill, B. E.; Kanney, J. F.; Carr, M.

2017-12-01

Heavy snowfall and snowmelt-related events have been linked to widespread flooding and damages in many regions of the U.S. Design of critical infrastructure in these regions requires spatial estimates of extreme snow water equivalent (SWE). In this study, we develop station specific and spatially explicit estimates of extreme SWE using data from fifteen snow sampling stations maintained by the New Hampshire Department of Environmental Services. The stations are located in the Mascoma, Pemigewasset, Winnipesaukee, Ossipee, Salmon Falls, Lamprey, Sugar, and Isinglass basins in New Hampshire. The average record length for the fifteen stations is approximately fifty-nine years. The spatial analysis of extreme SWE involves application of two Bayesian Hierarchical Modeling methods, one that assumes conditional independence, and another which uses the Smith max-stable process model to account for spatial dependence. We also apply additional max-stable process models, albeit not in a Bayesian framework, that better model the observed dependence among the extreme SWE data. The spatial process modeling leverages readily available and relevant spatially explicit covariate data. The noted additional max-stable process models also used the nonstationary winter North Atlantic Oscillation index, which has been observed to influence snowy weather along the east coast of the United States. We find that, for this data set, SWE return level estimates are consistently higher when derived using methods which account for the observed spatial dependence among the extreme data. This is particularly significant for design scenarios of relevance for critical infrastructure evaluation.

Use of local Moran's I and GIS to identify pollution hotspots of Pb in urban soils of Galway, Ireland.

PubMed

Zhang, Chaosheng; Luo, Lin; Xu, Weilin; Ledwith, Valerie

2008-07-15

Pollution hotspots in urban soils need to be identified for better environmental management. It is important to know if there are hotspots and if the hotspots are statistically significant. In this study identification of pollution hotspots was investigated using Pb concentrations in urban soils of Galway City in Ireland as an example, and the influencing factors on results of hotspot identification were investigated. The index of local Moran's I is a useful tool for identifying pollution hotspots of Pb pollution in urban soils, and for classifying them into spatial clusters and spatial outliers. The results were affected by the definition of weight function, data transformation and existence of extreme values. Compared with the results for the positively skewed raw data, the transformed data and data with extreme values excluded revealed a larger area for the high value spatial clusters in the city centre. While it is hard to decide the best way of using this index, it is suggested that all these influencing factors should be considered until reasonable and reliable results are obtained. GIS mapping can be applied to help evaluate the results via visualization of the spatial patterns. Meanwhile, selected pollution hotspots (extreme values) in this study were confirmed by re-analyses and re-sampling.

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Coronal Heating and the Need for High-Resolution Observations

NASA Technical Reports Server (NTRS)

Klimchuk, James A.

2008-01-01

Despite excellent progress in recent years in understanding coronal heating, there remain many crucial questions that are still unanswered. Limitations in the observations are one important reason. Both theoretical and observational considerations point to the importance of small spatial scales, impulsive energy release, strong dynamics, and extreme plasma nonuniformity. As a consequence, high spatial resolution, broad temperature coverage, high temperature fidelity, and sensitivity to velocities and densities are all critical observational parameters. Current instruments lack one or more of these properties, and this has led to considerable ambiguity and confusion. In this talk, I will discuss recent ideas about coronal heating and emphasize that high spatial resolution observations, especially spectroscopic observations, are needed to make major progress on this important problem.

Visuo-spatial processing in autism--testing the predictions of extreme male brain theory.

PubMed

Falter, Christine M; Plaisted, Kate C; Davis, Greg

2008-03-01

It has been hypothesised that autism is an extreme version of the male brain, caused by high levels of prenatal testosterone (Baron-Cohen 1999). To test this proposal, associations were assessed between three visuo-spatial tasks and prenatal testosterone, indexed in second-to-fourth digit length ratios (2D:4D). The study included children with Autism Spectrum Disorder, ASD (N = 28), and chronological as well as mental age matched typically-developing children (N = 31). While the group with ASD outperformed the control group at Mental Rotation and Figure-Disembedding, these group differences were not related to differences in prenatal testosterone level. Previous findings of an association between Targeting and 2D:4D were replicated in typically-developing children and children with ASD. The implications of these results for the extreme male brain (EMB) theory of autism are discussed.

Spatial Ecology of the Critically Endangered Fijian Crested Iguana, Brachylophus vitiensis, in an Extremely Dense Population: Implications for Conservation

PubMed Central

Morrison, Suzanne F.; Biciloa, Pita; Harlow, Peter S.; Keogh, J. Scott

2013-01-01

The Critically Endangered Fijian crested iguana, Brachylophus vitiensis, occurs at extreme density at only one location, with estimates of >10,000 iguanas living on the 70 hectare island of Yadua Taba in Fiji. We conducted a mark and recapture study over two wet seasons, investigating the spatial ecology and intraspecific interactions of the strictly arboreal Fijian crested iguana. This species exhibits moderate male-biased sexual size dimorphism, which has been linked in other lizard species to territoriality, aggression and larger male home ranges. We found that male Fijian crested iguanas exhibit high injury levels, indicative of frequent aggressive interactions. We did not find support for larger home range size in adult males relative to adult females, however male and female residents were larger than roaming individuals. Males with established home ranges also had larger femoral pores relative to body size than roaming males. Home range areas were small in comparison to those of other iguana species, and we speculate that the extreme population density impacts considerably on the spatial ecology of this population. There was extensive home range overlap within and between sexes. Intersexual overlap was greater than intrasexual overlap for both sexes, and continuing male-female pairings were observed among residents. Our results suggest that the extreme population density necessitates extensive home range overlap even though the underlying predictors of territoriality, such as male biased sexual size dimorphism and high aggression levels, remain. Our findings should be factored in to conservation management efforts for this species, particularly in captive breeding and translocation programs. PMID:24019902

Assessing the impact of future climate extremes on the US corn and soybean production

NASA Astrophysics Data System (ADS)

Jin, Z.

2015-12-01

Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.

Spatial ecology of the critically endangered Fijian crested iguana, Brachylophus vitiensis, in an extremely dense population: implications for conservation.

PubMed

Morrison, Suzanne F; Biciloa, Pita; Harlow, Peter S; Keogh, J Scott

2013-01-01

The Critically Endangered Fijian crested iguana, Brachylophus vitiensis, occurs at extreme density at only one location, with estimates of >10,000 iguanas living on the 70 hectare island of Yadua Taba in Fiji. We conducted a mark and recapture study over two wet seasons, investigating the spatial ecology and intraspecific interactions of the strictly arboreal Fijian crested iguana. This species exhibits moderate male-biased sexual size dimorphism, which has been linked in other lizard species to territoriality, aggression and larger male home ranges. We found that male Fijian crested iguanas exhibit high injury levels, indicative of frequent aggressive interactions. We did not find support for larger home range size in adult males relative to adult females, however male and female residents were larger than roaming individuals. Males with established home ranges also had larger femoral pores relative to body size than roaming males. Home range areas were small in comparison to those of other iguana species, and we speculate that the extreme population density impacts considerably on the spatial ecology of this population. There was extensive home range overlap within and between sexes. Intersexual overlap was greater than intrasexual overlap for both sexes, and continuing male-female pairings were observed among residents. Our results suggest that the extreme population density necessitates extensive home range overlap even though the underlying predictors of territoriality, such as male biased sexual size dimorphism and high aggression levels, remain. Our findings should be factored in to conservation management efforts for this species, particularly in captive breeding and translocation programs.

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

NASA Astrophysics Data System (ADS)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2018-03-01

Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

Spatial variation in extreme winds predicts large wildfire locations in chaparral ecosystems

NASA Astrophysics Data System (ADS)

Moritz, Max A.; Moody, Tadashi J.; Krawchuk, Meg A.; Hughes, Mimi; Hall, Alex

2010-02-01

Fire plays a crucial role in many ecosystems, and a better understanding of different controls on fire activity is needed. Here we analyze spatial variation in fire danger during episodic wind events in coastal southern California, a densely populated Mediterranean-climate region. By reconstructing almost a decade of fire weather patterns through detailed simulations of Santa Ana winds, we produced the first high-resolution map of where these hot, dry winds are consistently most severe and which areas are relatively sheltered. We also analyzed over half a century of mapped fire history in chaparral ecosystems of the region, finding that our models successfully predict where the largest wildfires are most likely to occur. There is a surprising lack of information about extreme wind patterns worldwide, and more quantitative analyses of their spatial variation will be important for effective fire management and sustainable long-term urban development on fire-prone landscapes.

NLDAS Views of North American 2011 Extreme Events

NASA Technical Reports Server (NTRS)

Rui, Hualan; Teng, William; Vollmer, Bruce; Mocko, David; Lei, Guang-Dih

2012-01-01

2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data set, with high spatial and temporal resolutions (0.125? x 0.125?, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

Spatial drought reconstructions for central High Asia based on tree rings

NASA Astrophysics Data System (ADS)

Fang, Keyan; Davi, Nicole; Gou, Xiaohua; Chen, Fahu; Cook, Edward; Li, Jinbao; D'Arrigo, Rosanne

2010-11-01

Spatial reconstructions of drought for central High Asia based on a tree-ring network are presented. Drought patterns for central High Asia are classified into western and eastern modes of variability. Tree-ring based reconstructions of the Palmer drought severity index (PDSI) are presented for both the western central High Asia drought mode (1587-2005), and for the eastern central High Asia mode (1660-2005). Both reconstructions, generated using a principal component regression method, show an increased variability in recent decades. The wettest epoch for both reconstructions occurred from the 1940s to the 1950s. The most extreme reconstructed drought for western central High Asia was from the 1640s to the 1650s, coinciding with the collapse of the Chinese Ming Dynasty. The eastern central High Asia reconstruction has shown a distinct tendency towards drier conditions since the 1980s. Our spatial reconstructions agree well with previous reconstructions that fall within each mode, while there is no significant correlation between the two spatial reconstructions.

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.

Spatial extremes modeling applied to extreme precipitation data in the state of Paraná

NASA Astrophysics Data System (ADS)

Olinda, R. A.; Blanchet, J.; dos Santos, C. A. C.; Ozaki, V. A.; Ribeiro, P. J., Jr.

2014-11-01

Most of the mathematical models developed for rare events are based on probabilistic models for extremes. Although the tools for statistical modeling of univariate and multivariate extremes are well developed, the extension of these tools to model spatial extremes includes an area of very active research nowadays. A natural approach to such a modeling is the theory of extreme spatial and the max-stable process, characterized by the extension of infinite dimensions of multivariate extreme value theory, and making it possible then to incorporate the existing correlation functions in geostatistics and therefore verify the extremal dependence by means of the extreme coefficient and the Madogram. This work describes the application of such processes in modeling the spatial maximum dependence of maximum monthly rainfall from the state of Paraná, based on historical series observed in weather stations. The proposed models consider the Euclidean space and a transformation referred to as space weather, which may explain the presence of directional effects resulting from synoptic weather patterns. This method is based on the theorem proposed for de Haan and on the models of Smith and Schlather. The isotropic and anisotropic behavior of these models is also verified via Monte Carlo simulation. Estimates are made through pairwise likelihood maximum and the models are compared using the Takeuchi Information Criterion. By modeling the dependence of spatial maxima, applied to maximum monthly rainfall data from the state of Paraná, it was possible to identify directional effects resulting from meteorological phenomena, which, in turn, are important for proper management of risks and environmental disasters in countries with its economy heavily dependent on agribusiness.

Climate Change and Hydrological Extreme Events - Risks and Perspectives for Water Management in Bavaria and Québec

NASA Astrophysics Data System (ADS)

Ludwig, R.

2017-12-01

There is as yet no confirmed knowledge whether and how climate change contributes to the magnitude and frequency of hydrological extreme events and how regional water management could adapt to the corresponding risks. The ClimEx project (2015-2019) investigates the effects of climate change on the meteorological and hydrological extreme events and their implications for water management in Bavaria and Québec. High Performance Computing is employed to enable the complex simulations in a hydro-climatological model processing chain, resulting in a unique high-resolution and transient (1950-2100) dataset of climatological and meteorological forcing and hydrological response: (1) The climate module has developed a large ensemble of high resolution data (12km) of the CRCM5 RCM for Central Europe and North-Eastern North America, downscaled from 50 members of the CanESM2 GCM. The dataset is complemented by all available data from the Euro-CORDEX project to account for the assessment of both natural climate variability and climate change. The large ensemble with several thousand model years provides the potential to catch rare extreme events and thus improves the process understanding of extreme events with return periods of 1000+ years. (2) The hydrology module comprises process-based and spatially explicit model setups (e.g. WaSiM) for all major catchments in Bavaria and Southern Québec in high temporal (3h) and spatial (500m) resolution. The simulations form the basis for in depth analysis of hydrological extreme events based on the inputs from the large climate model dataset. The specific data situation enables to establish a new method for `virtual perfect prediction', which assesses climate change impacts on flood risk and water resources management by identifying patterns in the data which reveal preferential triggers of hydrological extreme events. The presentation will highlight first results from the analysis of the large scale ClimEx model ensemble, showing the current and future ratio of natural variability and climate change impacts on meteorological extreme events. Selected data from the ensemble is used to drive a hydrological model experiment to illustrate the capacity to better determine the recurrence periods of hydrological extreme events under conditions of climate change.

Impacts of ozone air pollution and temperature extremes on crop yields: Spatial variability, adaptation and implications for future food security

NASA Astrophysics Data System (ADS)

Tai, Amos P. K.; Val Martin, Maria

2017-11-01

Ozone air pollution and climate change pose major threats to global crop production, with ramifications for future food security. Previous studies of ozone and warming impacts on crops typically do not account for the strong ozone-temperature correlation when interpreting crop-ozone or crop-temperature relationships, or the spatial variability of crop-to-ozone sensitivity arising from varietal and environmental differences, leading to potential biases in their estimated crop losses. Here we develop an empirical model, called the partial derivative-linear regression (PDLR) model, to estimate the spatial variations in the sensitivities of wheat, maize and soybean yields to ozone exposures and temperature extremes in the US and Europe using a composite of multidecadal datasets, fully correcting for ozone-temperature covariation. We find generally larger and more spatially varying sensitivities of all three crops to ozone exposures than are implied by experimentally derived concentration-response functions used in most previous studies. Stronger ozone tolerance is found in regions with high ozone levels and high consumptive crop water use, reflecting the existence of spatial adaptation and effect of water constraints. The spatially varying sensitivities to temperature extremes also indicate stronger heat tolerance in crops grown in warmer regions. The spatial adaptation of crops to ozone and temperature we find can serve as a surrogate for future adaptation. Using the PDLR-derived sensitivities and 2000-2050 ozone and temperature projections by the Community Earth System Model, we estimate that future warming and unmitigated ozone pollution can combine to cause an average decline in US wheat, maize and soybean production by 13%, 43% and 28%, respectively, and a smaller decline for European crops. Aggressive ozone regulation is shown to offset such decline to various extents, especially for wheat. Our findings demonstrate the importance of considering ozone regulation as well as ozone and climate change adaptation (e.g., selecting heat- and ozone-tolerant cultivars, irrigation) as possible strategies to enhance future food security in response to imminent environmental threats.

Application of travel time information for traffic management : technical summary.

DOT National Transportation Integrated Search

2012-01-01

Using conventional methods, it is extremely costly to measure detailed traffic characteristics in high quality spatial or temporal resolution. For analyzing travel characteristics on roadways, the floating car method, developed in the 1920s, has hist...

Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

USGS Publications Warehouse

Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

2016-01-01

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

Estimation of reactogenicity of preparations produced on the basis of photoinactivated live vaccines against brucellosis and tularaemia on the organismic level.2. Using the method of speckle-microscopy with high spatial resolution

NASA Astrophysics Data System (ADS)

Ulianova, O. V.; Uianov, S. S.; Li, Pengcheng; Luo, Qingming

2011-04-01

The method of speckle microscopy was adapted to estimate the reactogenicity of the prototypes of vaccine preparations against extremely dangerous infections. The theory is proposed to describe the mechanism of formation of the output signal from the super-high spatial resolution speckle microscope. The experimental studies show that bacterial suspensions, irradiated in different regimes of inactivation, do not exert negative influence on the blood microcirculations in laboratory animals.

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

The effect of spatial organization of targets and distractors on the capacity to selectively memorize objects in visual short-term memory.

PubMed

Abbes, Aymen Ben; Gavault, Emmanuelle; Ripoll, Thierry

2014-01-01

We conducted a series of experiments to explore how the spatial configuration of objects influences the selection and the processing of these objects in a visual short-term memory task. We designed a new experiment in which participants had to memorize 4 targets presented among 4 distractors. Targets were cued during the presentation of distractor objects. Their locations varied according to 4 spatial configurations. From the first to the last configuration, the distance between targets' locations was progressively increased. The results revealed a high capacity to select and memorize targets embedded among distractors even when targets were extremely distant from each other. This capacity is discussed in relation to the unitary conception of attention, models of split attention, and the competitive interaction model. Finally, we propose that the spatial dispersion of objects has different effects on attentional allocation and processing stages. Thus, when targets are extremely distant from each other, attentional allocation becomes more difficult while processing becomes easier. This finding implicates that these 2 aspects of attention need to be more clearly distinguished in future research.

Dynamically-downscaled projections of changes in temperature extremes over China

NASA Astrophysics Data System (ADS)

Guo, Junhong; Huang, Guohe; Wang, Xiuquan; Li, Yongping; Lin, Qianguo

2018-02-01

In this study, likely changes in extreme temperatures (including 16 indices) over China in response to global warming throughout the twenty-first century are investigated through the PRECIS regional climate modeling system. The PRECIS experiment is conducted at a spatial resolution of 25 km and is driven by a perturbed-physics ensemble to reflect spatial variations and model uncertainties. Simulations of present climate (1961-1990) are compared with observations to validate the model performance in reproducing historical climate over China. Results indicate that the PRECIS demonstrates reasonable skills in reproducing the spatial patterns of observed extreme temperatures over the most regions of China, especially in the east. Nevertheless, the PRECIS shows a relatively poor performance in simulating the spatial patterns of extreme temperatures in the western mountainous regions, where its driving GCM exhibits more uncertainties due to lack of insufficient observations and results in more errors in climate downscaling. Future spatio-temporal changes of extreme temperature indices are then analyzed for three successive periods (i.e., 2020s, 2050s and 2080s). The projected changes in extreme temperatures by PRECIS are well consistent with the results of the major global climate models in both spatial and temporal patterns. Furthermore, the PRECIS demonstrates a distinct superiority in providing more detailed spatial information of extreme indices. In general, all extreme indices show similar changes in spatial pattern: large changes are projected in the north while small changes are projected in the south. In contrast, the temporal patterns for all indices vary differently over future periods: the warm indices, such as SU, TR, WSDI, TX90p, TN90p and GSL are likely to increase, while the cold indices, such as ID, FD, CSDI, TX10p and TN10p, are likely to decrease with time in response to global warming. Nevertheless, the magnitudes of changes in all indices tend to decrease gradually with time, indicating the projected warming will begin to slow down in the late of this century. In addition, the projected range of changes for all indices would become larger with time, suggesting more uncertainties would be involved in long-term climate projections.

Large scale variability, long-term trends and extreme events in total ozone over the northern mid-latitudes based on satellite time series

NASA Astrophysics Data System (ADS)

Rieder, H. E.; Staehelin, J.; Maeder, J. A.; Ribatet, M.; Davison, A. C.

2009-04-01

Various generations of satellites (e.g. TOMS, GOME, OMI) made spatial datasets of column ozone available to the scientific community. This study has a special focus on column ozone over the northern mid-latitudes. Tools from geostatistics and extreme value theory are applied to analyze variability, long-term trends and frequency distributions of extreme events in total ozone. In a recent case study (Rieder et al., 2009) new tools from extreme value theory (Coles, 2001; Ribatet, 2007) have been applied to the world's longest total ozone record from Arosa, Switzerland (e.g. Staehelin 1998a,b), in order to describe extreme events in low and high total ozone. Within the current study this analysis is extended to satellite datasets for the northern mid-latitudes. Further special emphasis is given on patterns and spatial correlations and the influence of changes in atmospheric dynamics (e.g. tropospheric and lower stratospheric pressure systems) on column ozone. 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 Davison, A.C.: From ozone mini holes and mini highs towards extreme value theory: New insights from extreme events and non stationarity, submitted to J. Geophys. Res., 2009. 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, 1998a. 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, 1998b.

Quantifying Observed Temperature Extremes in the Southeastern United States

NASA Astrophysics Data System (ADS)

Sura, P.; Stefanova, L. B.; Griffin, M.; Worsnop, R.

2011-12-01

There is broad consensus that the most hazardous effects of climate change are related to a potential increase (in frequency and/or intensity) of extreme weather and climate events. In particular, the statistics of regional daily temperature extremes are of practical interest for the agricultural community and energy suppliers. This is notably true for the Southeastern United States where winter hard freezes are a relatively rare and potentially catastrophic event. Here we use a long record of quality-controlled observations collected from 272 National Weather Service (NWS) Cooperative Observing Network (COOP) stations throughout Florida, Georgia, Alabama, and South and North Carolina to provide a detailed climatology of temperature extremes in the Southeastern United States. We employ two complementary approaches. First, we analyze the effect of El Nino-Southern Oscillation (ENSO) and the Arctic Oscillation (AO) on the non-Gaussian (i.e. higher order) statistics of wintertime daily minimum and maximum temperatures. We find a significant and spatially varying impact of ENSO and AO on the non-Gaussian statistics of daily maximum and minimum temperatures throughout the domain. Second, the extremes of the temperature distributions are studied by calculating the 1st and 99th percentiles, and then analyzing the number of days with record low/high temperatures per season. This analysis of daily temperature extremes reveals oscillating, multi-decadal patterns with spatially varying centers of action.

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.

Identification of Extreme Events Under Climate Change Conditions Over Europe and The Northwest-atlantic Region: Spatial Patterns and Time Series Characteristics

NASA Astrophysics Data System (ADS)

Leckebusch, G.; Ulbrich, U.; Speth, P.

In the context of climate change and the resulting possible impacts on socio-economic conditions for human activities it seems that due to a changed occurrence of extreme events more severe consequences have to be expected than from changes in the mean climate. These extreme events like floods, excessive heats and droughts or windstorms possess impacts on human social and economic life in different categories such as forestry, agriculture, energy use, tourism and the reinsurance business. Reinsurances are affected by nearly 70% of all insured damages over Europe in the case of wind- storms. Especially the December 1999 French windstorms caused damages about 10 billion. A new EU-founded project (MICE = Modelling the Impact of Climate Ex- tremes) will focus on these impacts caused by changed occurrences of extreme events over Europe. Based upon the output of general circulation models as well as regional climate models, investigations are carried out with regard to time series characteristics as well as the spatial patterns of extremes under climate changed conditions. After the definition of specific thresholds for climate extremes, in this talk we will focus on the results of the analysis for the different data sets (HadCM3 and CGCMII GCM's and RCM's, re-analyses, observations) with regard to windstorm events. At first the results of model outputs are validated against re-analyses and observations. Especially a comparison of the stormtrack (2.5 to 8 day bandpass filtered 500 hPa geopotential height), cyclone track, cyclone frequency and intensity is presented. Highly relevant to damages is the extreme wind near the ground level, so the 10 m wind speed will be investigated additionally. of special interest to possible impacts is the changed spatial occurrence of windspeed maxima under 2xCO2-induced climate change.

Evaluation of satellite-retrieved extreme precipitation using gauge observations

NASA Astrophysics Data System (ADS)

Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

2012-04-01

Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

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.

Patterns of precipitation and soil moisture extremes in Texas, US: A complex network analysis

NASA Astrophysics Data System (ADS)

Sun, Alexander Y.; Xia, Youlong; Caldwell, Todd G.; Hao, Zengchao

2018-02-01

Understanding of the spatial and temporal dynamics of extreme precipitation not only improves prediction skills, but also helps to prioritize hazard mitigation efforts. This study seeks to enhance the understanding of spatiotemporal covariation patterns embedded in precipitation (P) and soil moisture (SM) by using an event-based, complex-network-theoretic approach. Events concurrences are quantified using a nonparametric event synchronization measure, and spatial patterns of hydroclimate variables are analyzed by using several network measures and a community detection algorithm. SM-P coupling is examined using a directional event coincidence analysis measure that takes the order of event occurrences into account. The complex network approach is demonstrated for Texas, US, a region possessing a rich set of hydroclimate features and is frequented by catastrophic flooding. Gridded daily observed P data and simulated SM data are used to create complex networks of P and SM extremes. The uncovered high degree centrality regions and community structures are qualitatively in agreement with the overall existing knowledge of hydroclimate extremes in the study region. Our analyses provide new visual insights on the propagation, connectivity, and synchronicity of P extremes, as well as the SM-P coupling, in this flood-prone region, and can be readily used as a basis for event-driven predictive analytics for other regions.

Long-term Changes in Extreme Air Pollution Meteorology and the Implications for Air Quality.

PubMed

Hou, Pei; Wu, Shiliang

2016-03-31

Extreme air pollution meteorological events, such as heat waves, temperature inversions and atmospheric stagnation episodes, can significantly affect air quality. Based on observational data, we have analyzed the long-term evolution of extreme air pollution meteorology on the global scale and their potential impacts on air quality, especially the high pollution episodes. We have identified significant increasing trends for the occurrences of extreme air pollution meteorological events in the past six decades, especially over the continental regions. Statistical analysis combining air quality data and meteorological data further indicates strong sensitivities of air quality (including both average air pollutant concentrations and high pollution episodes) to extreme meteorological events. For example, we find that in the United States the probability of severe ozone pollution when there are heat waves could be up to seven times of the average probability during summertime, while temperature inversions in wintertime could enhance the probability of severe particulate matter pollution by more than a factor of two. We have also identified significant seasonal and spatial variations in the sensitivity of air quality to extreme air pollution meteorology.

Precipitation extremes and their relation to climatic indices in the Pacific Northwest USA

NASA Astrophysics Data System (ADS)

Zarekarizi, Mahkameh; Rana, Arun; Moradkhani, Hamid

2018-06-01

There has been focus on the influence of climate indices on precipitation extremes in the literature. Current study presents the evaluation of the precipitation-based extremes in Columbia River Basin (CRB) in the Pacific Northwest USA. We first analyzed the precipitation-based extremes using statistically (ten GCMs) and dynamically downscaled (three GCMs) past and future climate projections. Seven precipitation-based indices that help inform about the flood duration/intensity are used. These indices help in attaining first-hand information on spatial and temporal scales for different service sectors including energy, agriculture, forestry etc. Evaluation of these indices is first performed in historical period (1971-2000) followed by analysis of their relation to large scale tele-connections. Further we mapped these indices over the area to evaluate the spatial variation of past and future extremes in downscaled and observational data. The analysis shows that high values of extreme indices are clustered in either western or northern parts of the basin for historical period whereas the northern part is experiencing higher degree of change in the indices for future scenario. The focus is also on evaluating the relation of these extreme indices to climate tele-connections in historical period to understand their relationship with extremes over CRB. Various climate indices are evaluated for their relationship using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD). Results indicated that, out of 13 climate tele-connections used in the study, CRB is being most affected inversely by East Pacific (EP), Western Pacific (WP), East Atlantic (EA) and North Atlaentic Oscillation (NAO).

Extreme Heterogeneity in Parasitism Despite Low Population Genetic Structure among Monarch Butterflies Inhabiting the Hawaiian Islands

PubMed Central

Pierce, Amanda A.; de Roode, Jacobus C.; Altizer, Sonia; Bartel, Rebecca A.

2014-01-01

Host movement and spatial structure can strongly influence the ecology and evolution of infectious diseases, with limited host movement potentially leading to high spatial heterogeneity in infection. Monarch butterflies (Danaus plexippus) are best known for undertaking a spectacular long-distance migration in eastern North America; however, they also form non-migratory populations that breed year-round in milder climates such as Hawaii and other tropical locations. Prior work showed an inverse relationship between monarch migratory propensity and the prevalence of the protozoan parasite, Ophryocystis elektroscirrha. Here, we sampled monarchs from replicate sites within each of four Hawaiian Islands to ask whether these populations show consistently high prevalence of the protozoan parasite as seen for monarchs from several other non-migratory populations. Counter to our predictions, we observed striking spatial heterogeneity in parasite prevalence, with infection rates per site ranging from 4–85%. We next used microsatellite markers to ask whether the observed variation in infection might be explained by limited host movement and spatial sub-structuring among sites. Our results showed that monarchs across the Hawaiian Islands form one admixed population, supporting high gene flow among sites. Moreover, measures of individual-level genetic diversity did not predict host infection status, as might be expected if more inbred hosts harbored higher parasite loads. These results suggest that other factors such as landscape-level environmental variation or colonization-extinction processes might instead cause the extreme heterogeneity in monarch butterfly infection observed here. PMID:24926796

The analyses of extreme climate events over China based on CMIP5 historical and future simulations

NASA Astrophysics Data System (ADS)

Yang, S.; Dong, W.; Feng, J.; Chou, J.

2013-12-01

The extreme climate events have a serious influence on human society. Based on observations and 12 simulations from Coupled Model Intercomparison Project Phase 5 (CMIP5), Climatic extremes and their changes over china in history and future scenarios of three Representative Concentration Pathways (RCPs) are analyzed. Because of the background of global warming, in observations, the frost days (FD) and low-temperature threshold days (TN10P) have decreasing trend, and summer days (SU), high-temperature threshold days (TX90P), the heavy precipitation days (R20) and contribution of heavy precipitation days (P95T) show an increasing trend. Most coupled models can basically simulate main characteristics of most extreme indexes. The models reproduce the mean FD and TX90P value best and can give basic trends of the FD, TN10P, SU and TX90P. High correlation coefficients between simulated results and observation are found in FD, SU and P95T. For FD and SU index, most of the models have good ability to capture the spatial differences between the mean state of the 1986-2005 and 1961-1980 periods, but for other indexes, most of models' simulation ability for spatial disparity are not so satisfactory and have to be promoted. Under the high emission scenario of RCP8.5, the century-scale linear changes of Multi-Model Ensembles (MME) for FD, SU, TN10P, TX90P, R20 and P95T are -46.9, 46.0, -27.1, 175.4, 2.9 days and 9.9%, respectively. Due to the complexities of physical process parameterizations and the limitation of forcing data, a large uncertainty still exists in the simulations of climatic extremes. Fig.1 Observed and modeled multi-year average for each index (Dotted line: observation) Table1. Extreme index definition

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.

The spatial distribution of threats to plant species with extremely small populations

NASA Astrophysics Data System (ADS)

Wang, Chunjing; Zhang, Jing; Wan, Jizhong; Qu, Hong; Mu, Xianyun; Zhang, Zhixiang

2017-03-01

Many biological conservationists take actions to conserve plant species with extremely small populations (PSESP) in China; however, there have been few studies on the spatial distribution of threats to PSESP. Hence, we selected distribution data of PSESP and made a map of the spatial distribution of threats to PSESP in China. First, we used the weight assignment method to evaluate the threat risk to PSESP at both country and county scales. Second, we used a geographic information system to map the spatial distribution of threats to PSESP, and explored the threat factors based on linear regression analysis. Finally, we suggested some effective conservation options. We found that the PSESP with high values of protection, such as the plants with high scientific research values and ornamental plants, were threatened by over-exploitation and utilization, habitat fragmentation, and a small sized wild population in broad-leaved forests and bush fallows. We also identified some risk hotspots for PSESP in China. Regions with low elevation should be given priority for ex- and in-situ conservation. Moreover, climate change should be considered for conservation of PSESP. To avoid intensive over-exploitation or utilization and habitat fragmentation, in-situ conservation should be practiced in regions with high temperatures and low temperature seasonality, particularly in the high risk hotspots for PSESP that we proposed. Ex-situ conservation should be applied in these same regions, and over-exploitation and utilization of natural resources should be prevented. It is our goal to apply the concept of PSESP to the global scale in the future.

Influence of spatial and temporal scales in identifying temperature extremes

NASA Astrophysics Data System (ADS)

van Eck, Christel M.; Friedlingstein, Pierre; Mulder, Vera L.; Regnier, Pierre A. G.

2016-04-01

Extreme heat events are becoming more frequent. Notable are severe heatwaves such as the European heatwave of 2003, the Russian heat wave of 2010 and the Australian heatwave of 2013. Surface temperature is attaining new maxima not only during the summer but also during the winter. The year of 2015 is reported to be a temperature record breaking year for both summer and winter. These extreme temperatures are taking their human and environmental toll, emphasizing the need for an accurate method to define a heat extreme in order to fully understand the spatial and temporal spread of an extreme and its impact. This research aims to explore how the use of different spatial and temporal scales influences the identification of a heat extreme. For this purpose, two near-surface temperature datasets of different temporal scale and spatial scale are being used. First, the daily ERA-Interim dataset of 0.25 degree and a time span of 32 years (1979-2010). Second, the daily Princeton Meteorological Forcing Dataset of 0.5 degree and a time span of 63 years (1948-2010). A temperature is considered extreme anomalous when it is surpassing the 90th, 95th, or the 99th percentile threshold based on the aforementioned pre-processed datasets. The analysis is conducted on a global scale, dividing the world in IPCC's so-called SREX regions developed for the analysis of extreme climate events. Pre-processing is done by detrending and/or subtracting the monthly climatology based on 32 years of data for both datasets and on 63 years of data for only the Princeton Meteorological Forcing Dataset. This results in 6 datasets of temperature anomalies from which the location in time and space of the anomalous warm days are identified. Comparison of the differences between these 6 datasets in terms of absolute threshold temperatures for extremes and the temporal and spatial spread of the extreme anomalous warm days show a dependence of the results on the datasets and methodology used. This stresses the need for a careful selection of data and methodology when identifying heat extremes.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

NASA Astrophysics Data System (ADS)

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao

2017-12-01

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary conditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045-2054 and 2085-2094) are compared with a historical decade (1995-2004). Probability density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5-10 times per year in most CONUS and ≥95°F days will increase by 1-2 months by the end of the century.

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.

Circulation controls of the spatial structure of maximum daily precipitation over Poland

NASA Astrophysics Data System (ADS)

Stach, Alfred

2015-04-01

Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.

A case study of an extremely luminous, highly spatially extended starburst only 1.7Gyr after the Big Bang

NASA Astrophysics Data System (ADS)

Farrah, Duncan

2017-08-01

Luminous starbursts, systems with SFRs exceeding 1000Msun yr-1, are predicted to be extremely rare at z>3. However, recent observations find such systems at rates of tens to hundreds above predictions. This discrepancy is extremely difficult to explain. Case studies of such luminous starbursts are thus of profound importance to understand how star formation is triggered and quenched at z > 3, and help reconcile models with observations. Our group has been intensively studying the quasar SDSS J160705.16, at z = 3.65 (or 1.7Gyr after the Big Bang). This quasar is an excellent case study of luminous star formation at z > 3, and how AGN activity may affect such star formation. SDSS J160705.16 harbors both a broad-line, luminous quasar and an extremely high star formation rate, with an AGN luminosity of 10^47 ergs s-1 and an SFR of 2000 Msol yr-1. Sub-mm interferometry has further revealed that the star formation is highly spatially extended on scales up to 40kpc. Furthermore, VLA observations show an emerging 4kpc radio jet.We here propose WFC3 imaging with the following goals: (1) to set precise constraints on any lensing magnification, (2) to determine the morphology and color structure of the extended star formation, (3) to compare the optical morphology of the star formation to that seen in the sub-mm data, and (4) to search for evidence that SDSS J160705.16 resides in a protocluster.

EUNIS; Extreme-Ultraviolet Normal-Incidence Spectrometer

NASA Technical Reports Server (NTRS)

Thomas, Roger J.; Davila, Joseph M.; Fisher, Richard R. (Technical Monitor)

2001-01-01

GSFC is in the process of assembling an Extreme-Ultraviolet Normal Incidence Spectrometer called EUNIS, to be flown as a sounding rocket payload. The instrument builds on the many technical innovations pioneered by our highly successful SERTS experiment, which has now flown a total of ten times, most recently last summer. The new design will have somewhat improved spatial and spectral resolutions, as well as two orders of magnitude greater sensitivity, permitting high signal/noise EUV spectroscopy with a temporal resolution near 1 second for the first time ever. In order to achieve such high time cadence, a novel detector system is being developed, based on Active-Pixel-Sensor electronics, a key component of our design.

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.

Estimation of reactogenicity of preparations produced on the basis of photoinactivated live vaccines against brucellosis and tularaemia on the organismic level. 2. Using the method of speckle-microscopy with high spatial resolution

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

Ulianova, O V; Uianov, S S; Li Pengcheng

2011-04-30

The method of speckle microscopy was adapted to estimate the reactogenicity of the prototypes of vaccine preparations against extremely dangerous infections. The theory is proposed to describe the mechanism of formation of the output signal from the super-high spatial resolution speckle microscope. The experimental studies show that bacterial suspensions, irradiated in different regimes of inactivation, do not exert negative influence on the blood microcirculations in laboratory animals. (optical technologies in biophysics and medicine)

Printing Proteins as Microarrays for High-Throughput Function Determination

NASA Astrophysics Data System (ADS)

MacBeath, Gavin; Schreiber, Stuart L.

2000-09-01

Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

The Relationship between Spatial and Temporal Magnitude Estimation of Scientific Concepts at Extreme Scales

NASA Astrophysics Data System (ADS)

Price, Aaron; Lee, H.

2010-01-01

Many astronomical objects, processes, and events exist and occur at extreme scales of spatial and temporal magnitudes. Our research draws upon the psychological literature, replete with evidence of linguistic and metaphorical links between the spatial and temporal domains, to compare how students estimate spatial and temporal magnitudes associated with objects and processes typically taught in science class.. We administered spatial and temporal scale estimation tests, with many astronomical items, to 417 students enrolled in 12 undergraduate science courses. Results show that while the temporal test was more difficult, students’ overall performance patterns between the two tests were mostly similar. However, asymmetrical correlations between the two tests indicate that students think of the extreme ranges of spatial and temporal scales in different ways, which is likely influenced by their classroom experience. When making incorrect estimations, students tended to underestimate the difference between the everyday scale and the extreme scales on both tests. This suggests the use of a common logarithmic mental number line for both spatial and temporal magnitude estimation. However, there are differences between the two tests in the errors student make in the everyday range. Among the implications discussed is the use of spatio-temporal reference frames, instead of smooth bootstrapping, to help students maneuver between scales of magnitude and the use of logarithmic transformations between reference frames. Implications for astronomy range from learning about spectra to large scale galaxy structure.

Total ozone patterns over the northern mid-latitudes: spatial correlations, extreme events and dynamical contributions

NASA Astrophysics Data System (ADS)

Rieder, H. E.; Staehelin, J.; Maeder, J. A.; Ribatet, M.; Bodeker, G. E.; Davison, A. C.

2009-04-01

Tools from geostatistics and extreme value theory are applied to analyze spatial correlations in total ozone for the northern mid-latitudes. The dataset used in this study is the NIWA combined total ozone dataset (Bodeker et al., 2001; Müller et al., 2008). New tools from extreme value theory (Coles, 2001; Ribatet, 2007) have recently been applied to the world's longest total ozone record from Arosa, Switzerland (e.g. Staehelin 1998a,b), in order to describe extreme events in low and high total ozone (Rieder et al., 200x). Within the current study, patterns in spatial correlation and frequency distributions of extreme events (e.g. ELOs and EHOs) are studied for the northern mid-latitudes. New insights in spatial patterns of total ozone for the northern mid-latitudes are presented. Koch et al. (2005) found that the increase in fast isentropic transport of tropical air to northern mid-latitudes contributed significantly to ozone changes between 1980 and 1989. Within this study the influence of changes in atmospheric dynamics (e.g. tropospheric and lower stratospheric pressure systems) on column ozone over the northern mid-latitudes is analyzed for the time period 1979-2007. References: Bodeker, G.E., J.C. Scott, K. Kreher, and R.L. McKenzie, Global ozone trends in potential vorticity coordinates using TOMS and GOME intercompared against the Dobson network: 1978-1998, J. Geophys. Res., 106 (D19), 23029-23042, 2001. Coles, S.: An Introduction to Statistical Modeling of Extreme Values, Springer Series in Statistics, ISBN:1852334592, Springer, Berlin, 2001. Koch, G., H. Wernli, C. Schwierz, J. Staehelin, and T. Peter (2005), A composite study on the structure and formation of ozone miniholes and minihighs over central Europe, Geophys. Res. Lett., 32, L12810, doi:10.1029/2004GL022062. Müller, R., Grooß, J.-U., Lemmen, C., Heinze, D., Dameris, M., and Bodeker, G.: Simple measures of ozone depletion in the polar stratosphere, Atmos. Chem. Phys., 8, 251-264, 2008. 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 Davison, A.C.: From ozone mini holes and mini highs towards extreme value theory: New insights from extreme events and non stationarity, submitted to J. Geophys. Res., 200x. 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, 1998a. 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, 1998b.

Microwave Atmospheric Sounder on CubeSat

NASA Astrophysics Data System (ADS)

Padmanabhan, S.; Brown, S. E.; Kangaslahti, P.; Cofield, R.; Russell, D.; Stachnik, R. A.; Su, H.; Wu, L.; Tanelli, S.; Niamsuwan, N.

2014-12-01

To accurately predict how the distribution of extreme events may change in the future we need to understand the mechanisms that influence such events in our current climate. Our current observing system is not well-suited for observing extreme events globally due to the sparse sampling and in-homogeneity of ground-based in-situ observations and the infrequent revisit time of satellite observations. Observations of weather extremes, such as extreme precipitation events, temperature extremes, tropical and extra-tropical cyclones among others, with temporal resolution on the order of minutes and spatial resolution on the order of few kms (<10 kms), are required for improved forecasting of extreme weather events. We envision a suite of low-cost passive microwave sounding and imaging sensors on CubeSats that would work in concert with traditional flagship observational systems, such as those manifested on large environmental satellites (i.e. JPSS,WSF,GCOM-W), to monitor weather extremes. A 118/183 GHz sensor would enable observations of temperature and precipitation extremes over land and ocean as well as tropical and extra-tropical cyclones. This proposed project would enable low cost, compact radiometer instrumentation at 118 and 183 GHz that would fit in a 6U Cubesat with the objective of mass-producing this design to enable a suite of small satellites to image the key geophysical parameters needed to improve prediction of extreme weather events. We take advantage of past and current technology developments at JPL viz. HAMSR (High Altitude Microwave Scanning Radiometer), Advanced Component Technology (ACT'08) to enable low-mass, low-power high frequency airborne radiometers. In this paper, we will describe the design and implementation of the 118 GHz temperature sounder and 183 GHz humidity sounder on the 6U CubeSat. In addition, a summary of radiometer calibration and retrieval techniques of temperature and humidity will be discussed. The successful demonstration of this instrument on the 6U CubeSat would pave the way for the development of a constellation which could sample tropospheric temperature and humidity with fine temporal and spatial resolution.

Airborne Deployment and Calibration of Microwave Atmospheric Sounder on 6U CubeSat

NASA Astrophysics Data System (ADS)

Padmanabhan, S.; Brown, S. T.; Lim, B.; Kangaslahti, P.; Russell, D.; Stachnik, R. A.

2015-12-01

To accurately predict how the distribution of extreme events may change in the future we need to understand the mechanisms that influence such events in our current climate. Our current observing system is not well-suited for observing extreme events globally due to the sparse sampling and in-homogeneity of ground-based in-situ observations and the infrequent revisit time of satellite observations. Observations of weather extremes, such as extreme precipitation events, temperature extremes, tropical and extra-tropical cyclones among others, with temporal resolution on the order of minutes and spatial resolution on the order of few kms (<10 kms), are required for improved forecasting of extreme weather events. We envision a suite of low-cost passive microwave sounding and imaging sensors on CubeSats that would work in concert with traditional flagship observational systems, such as those manifested on large environmental satellites (i.e. JPSS,WSF,GCOM-W), to monitor weather extremes. A 118/183 GHz sensor would enable observations of temperature and precipitation extremes over land and ocean as well as tropical and extra-tropical cyclones. This proposed project would enable low cost, compact radiometer instrumentation at 118 and 183 GHz that would fit in a 6U Cubesat with the objective of mass-producing this design to enable a suite of small satellites to image the key geophysical parameters needed to improve prediction of extreme weather events. We take advantage of past and current technology developments at JPL viz. HAMSR (High Altitude Microwave Scanning Radiometer), Advanced Component Technology (ACT'08) to enable low-mass, low-power high frequency airborne radiometers. In this paper, we will describe the design and implementation of the 118 GHz temperature sounder and 183 GHz humidity sounder on the 6U CubeSat. In addition, we will discuss the maiden airborne deployment of the instrument during the Plain Elevated Convection at Night (PECAN) experiment. The successful demonstration of this instrument on the 6U CubeSat would pave the way for the development of a constellation which could sample tropospheric temperature and humidity with fine temporal and spatial resolution.

Tropical precipitation extremes: Response to SST-induced warming in aquaplanet simulations

NASA Astrophysics Data System (ADS)

Bhattacharya, Ritthik; Bordoni, Simona; Teixeira, João.

2017-04-01

Scaling of tropical precipitation extremes in response to warming is studied in aquaplanet experiments using the global Weather Research and Forecasting (WRF) model. We show how the scaling of precipitation extremes is highly sensitive to spatial and temporal averaging: while instantaneous grid point extreme precipitation scales more strongly than the percentage increase (˜7% K-1) predicted by the Clausius-Clapeyron (CC) relationship, extremes for zonally and temporally averaged precipitation follow a slight sub-CC scaling, in agreement with results from Climate Model Intercomparison Project (CMIP) models. The scaling depends crucially on the employed convection parameterization. This is particularly true when grid point instantaneous extremes are considered. These results highlight how understanding the response of precipitation extremes to warming requires consideration of dynamic changes in addition to the thermodynamic response. Changes in grid-scale precipitation, unlike those in convective-scale precipitation, scale linearly with the resolved flow. Hence, dynamic changes include changes in both large-scale and convective-scale motions.

Population exposure to heat-related extremes: Demographic change vs climate change

NASA Astrophysics Data System (ADS)

Jones, B.; O'Neill, B. C.; Tebaldi, C.; Oleson, K. W.

2014-12-01

Extreme heat events are projected to increase in frequency and intensity in the coming decades [1]. The physical effects of extreme heat on human populations are well-documented, and anticipating changes in future exposure to extreme heat is a key component of adequate planning/mitigation [2, 3]. Exposure to extreme heat depends not only on changing climate, but also on changes in the size and spatial distribution of the human population. Here we focus on systematically quantifying exposure to extreme heat as a function of both climate and population change. We compare exposure outcomes across multiple global climate and spatial population scenarios, and characterize the relative contributions of each to population exposure to extreme heat. We consider a 2 x 2 matrix of climate and population output, using projections of heat extremes corresponding to RCP 4.5 and RCP 8.5 from the NCAR community land model, and spatial population projections for SSP 3 and SSP 5 from the NCAR spatial population downscaling model. Our primary comparison is across RCPs - exposure outcomes from RCP 4.5 versus RCP 8.5 - paying particular attention to how variation depends on the choice of SSP in terms of aggregate global and regional exposure, as well as the spatial distribution of exposure. We assess how aggregate exposure changes based on the choice of SSP, and which driver is more important, population or climate change (i.e. does that outcome vary more as a result of RCP or SSP). We further decompose the population component to analyze the contributions of total population change, migration, and changes in local spatial structure. Preliminary results from a similar study of the US suggests a four-to-six fold increase in total exposure by the latter half of the 21st century. Changes in population are as important as changes in climate in driving this outcome, and there is regional variation in the relative importance of each. Aggregate population growth, as well as redistribution of the population across larger US regions, strongly affects outcomes while smaller-scale spatial patterns of population change have smaller effects. [1] Collins, M. et al. (2013) Contribution of WG I to the 5th AR of the IPCC[2] Romero-Lankao, P. et al (2014) Contribution of WG II to the 5th AR of the IPCC[3] Walsh, J. et al. (2014) The 3rd National Climate Assessment

Effects of extreme climatic events on small-scale spatial patterns: a 20-year study of the distribution of a desert spider.

PubMed

Birkhofer, Klaus; Henschel, Joh; Lubin, Yael

2012-11-01

Individuals of most animal species are non-randomly distributed in space. Extreme climatic events are often ignored as potential drivers of distribution patterns, and the role of such events is difficult to assess. Seothyra henscheli (Araneae, Eresidae) is a sedentary spider found in the Namib dunes in Namibia. The spider constructs a sticky-edged silk web on the sand surface, connected to a vertical, silk-lined burrow. Above-ground web structures can be damaged by strong winds or heavy rainfall, and during dispersal spiders are susceptible to environmental extremes. Locations of burrows were mapped in three field sites in 16 out of 20 years from 1987 to 2007, and these grid-based data were used to identify the relationship between spatial patterns, climatic extremes and sampling year. According to Morisita's index, individuals had an aggregated distribution in most years and field sites, and Geary's C suggests clustering up to scales of 2 m. Individuals were more aggregated in years with high maximum wind speed and low annual precipitation. Our results suggest that clustering is a temporally stable property of populations that holds even under fluctuating burrow densities. Climatic extremes, however, affect the intensity of clustering behaviour: individuals seem to be better protected in field sites with many conspecific neighbours. We suggest that burrow-site selection is driven at least partly by conspecific cuing, and this behaviour may protect populations from collapse during extreme climatic events.

Extreme ultra-violet movie camera for imaging microsecond time scale magnetic reconnection

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

Chai, Kil-Byoung; Bellan, Paul M.

2013-12-15

An ultra-fast extreme ultra-violet (EUV) movie camera has been developed for imaging magnetic reconnection in the Caltech spheromak/astrophysical jet experiment. The camera consists of a broadband Mo:Si multilayer mirror, a fast decaying YAG:Ce scintillator, a visible light block, and a high-speed visible light CCD camera. The camera can capture EUV images as fast as 3.3 × 10{sup 6} frames per second with 0.5 cm spatial resolution. The spectral range is from 20 eV to 60 eV. EUV images reveal strong, transient, highly localized bursts of EUV radiation when magnetic reconnection occurs.

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

Drought assessment in the Duero basin (Central Spain) by means of multivariate extreme value statistics

NASA Astrophysics Data System (ADS)

Kallache, M.

2012-04-01

Droughts cause important losses. On the Iberian Peninsula, for example, non-irrigated agriculture and the tourism sector are affected in regular intervals. The goal of this study is the description of droughts and their dependence in the Duero basin in Central Spain. To do so, daily or monthly precipitation data is used. Here cumulative precipitation deficits below a threshold define meteorological droughts. This drought indicator is similar to the commonly used standard precipitation index. However, here the focus lies on the modeling of severe droughts, which is done by applying multivariate extreme value theory (MEVT) to model extreme drought events. Data from several stations are assessed jointly, thus the uncertainty of the results is reduced. Droughts are a complex phenomenon, their severity, spatial extension and duration has to be taken into account. Our approach captures severity and spatial extension. In general we find a high correlation between deficit volumes and drought duration, thus the duration is not explicitely modeled. We apply a MEVT model with asymmetric logistic dependence function, which is capable to model asymptotic dependence and independence (cf. Ramos and Ledford, 2009). To summarize the information on the dependence in the joint tail of the extreme drought events, we utilise the fragility index (Geluk et al., 2007). Results show that droughts also occur frequently in winter. Moreover, it is very common for one site to suffer dry conditions, whilst neighboring areas experience normal or even humid conditions. Interpolation is thus difficult. Bivariate extremal dependence is present in the data. However, most stations are at least asymptotically independent. The according fragility indices are important information for risk calculations. The emerging spatial patterns for bivariate dependence are mostly influenced by topography. When looking at the dependence between more than two stations, it shows that joint extremes can occur more often than randomly for up to 6 stations, this depends on the distance between the stations.

Ongoing climatic extreme dynamics in Siberia

NASA Astrophysics Data System (ADS)

Gordov, E. P.; Shulgina, T. M.; Okladnikov, I. G.; Titov, A. G.

2013-12-01

Ongoing global climate changes accompanied by the restructuring of global processes in the atmosphere and biosphere are strongly pronounced in the Northern Eurasia regions, especially in Siberia. Recent investigations indicate not only large changes in averaged climatic characteristics (Kabanov and Lykosov, 2006, IPCC, 2007; Groisman and Gutman, 2012), but more frequent occurrence and stronger impacts of climatic extremes are reported as well (Bulygina et al., 2007; IPCC, 2012: Climate Extremes, 2012; Oldenborh et al., 2013). This paper provides the results of daily temperature and precipitation extreme dynamics in Siberia for the last three decades (1979 - 2012). Their seasonal dynamics is assessed using 10th and 90th percentile-based threshold indices that characterize frequency, intensity and duration of climatic extremes. To obtain the geographical pattern of these variations with high spatial resolution, the sub-daily temperature data from ECMWF ERA-Interim reanalysis and daily precipitation amounts from APHRODITE JMA dataset were used. All extreme indices and linear trend coefficients have been calculated using web-GIS information-computational platform Climate (http://climate.scert.ru/) developed to support collaborative multidisciplinary investigations of regional climatic changes and their impacts (Gordov et al., 2012). Obtained results show that seasonal dynamics of daily temperature extremes is asymmetric for tails of cold and warm temperature extreme distributions. Namely, the intensity of warming during cold nights is higher than during warm nights, especially at high latitudes of Siberia. The similar dynamics is observed for cold and warm day-time temperatures. Slight summer cooling was observed in the central part of Siberia. It is associated with decrease in warm temperature extremes. In the southern Siberia in winter, we also observe some cooling mostly due to strengthening of the cold temperature extremes. Changes in daily precipitation extremes are spatially inhomogeneous. The largest increase in frequency and intensity of heavy precipitation is observed in the north of East Siberia. Negative trends related to precipitation amount decrease are found in the central West Siberia and in the south of East Siberia. The authors acknowledge partial financial support for this research from the Russian Foundation for Basic Research projects (11-05-01190 and 13-05-12034), SB RAS Integration project 131 and project VIII.80.2.1., the Ministry of Education and Science of the Russian Federation contract 8345 and grant of the President of Russian Federation (decree 181).

A Long-Term Dissipation of the EUV He ii (30.4 nm) Segmentation in Full-Disk Solar Images

NASA Astrophysics Data System (ADS)

Didkovsky, Leonid

2018-06-01

Some quiet-Sun days observed by the Atmospheric Imaging Assembly (AIA) on-board the Solar Dynamics Observatory (SDO) during the time interval in 2010 - 2017 were used to continue our previous analyses reported by Didkovsky and Gurman ( Solar Phys. 289, 153, 2014a) and Didkovsky, Wieman, and Korogodina ( Solar Phys. 292, 32, 2017). The analysis consists of determining and comparing spatial spectral ratios (spectral densities over some time interval) from spatial (segmentation-cell length) power spectra. The ratios were compared using modeled compatible spatial frequencies for spectra from the Extreme ultraviolet Imaging Telescope (EIT) on-board the Solar and Heliospheric Observatory (SOHO) and from AIA images. With the new AIA data added to the EIT data we analyzed previously, the whole time interval from 1996 to 2017 reported here is approximately the length of two "standard" solar cycles (SC). The spectral ratios of segmentation-cell dimension structures show a significant and steady increase with no detected indication of SC-related returns to the values that characterize the SC minima. This increase in spatial power at high spatial frequencies is interpreted as a dissipation of medium-size EUV network structures to smaller-size structures in the transition region. Each of the latest ratio changes for 2010 through 2017 spectra calculated for a number of consecutive short-term intervals has been converted into monthly mean ratio (MMR) changes. The MMR values demonstrate variable sign and magnitudes, thus confirming the solar nature of the changes. These changes do not follow a "typical" trend of instrumental degradation or a long-term activity profile from the He ii (30.4 nm) irradiance measured by the Extreme ultraviolet Spectrophotometer (ESP) either. The ESP is a channel of the Extreme ultraviolet Variability Experiment (EVE) on-board SDO.

The effect of spatial organization of targets and distractors on the capacity to selectively memorize objects in visual short-term memory

PubMed Central

Abbes, Aymen Ben; Gavault, Emmanuelle; Ripoll, Thierry

2014-01-01

We conducted a series of experiments to explore how the spatial configuration of objects influences the selection and the processing of these objects in a visual short-term memory task. We designed a new experiment in which participants had to memorize 4 targets presented among 4 distractors. Targets were cued during the presentation of distractor objects. Their locations varied according to 4 spatial configurations. From the first to the last configuration, the distance between targets’ locations was progressively increased. The results revealed a high capacity to select and memorize targets embedded among distractors even when targets were extremely distant from each other. This capacity is discussed in relation to the unitary conception of attention, models of split attention, and the competitive interaction model. Finally, we propose that the spatial dispersion of objects has different effects on attentional allocation and processing stages. Thus, when targets are extremely distant from each other, attentional allocation becomes more difficult while processing becomes easier. This finding implicates that these 2 aspects of attention need to be more clearly distinguished in future research. PMID:25339978

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

2018-03-01

The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

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.

PHASE QUANTIZATION STUDY OF SPATIAL LIGHT MODULATOR FOR EXTREME HIGH-CONTRAST IMAGING

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

Dou, Jiangpei; Ren, Deqing, E-mail: jpdou@niaot.ac.cn, E-mail: jiangpeidou@gmail.com

2016-11-20

Direct imaging of exoplanets by reflected starlight is extremely challenging due to the large luminosity ratio to the primary star. Wave-front control is a critical technique to attenuate the speckle noise in order to achieve an extremely high contrast. We present a phase quantization study of a spatial light modulator (SLM) for wave-front control to meet the contrast requirement of detection of a terrestrial planet in the habitable zone of a solar-type star. We perform the numerical simulation by employing the SLM with different phase accuracy and actuator numbers, which are related to the achievable contrast. We use an optimizationmore » algorithm to solve the quantization problems that is matched to the controllable phase step of the SLM. Two optical configurations are discussed with the SLM located before and after the coronagraph focal plane mask. The simulation result has constrained the specification for SLM phase accuracy in the above two optical configurations, which gives us a phase accuracy of 0.4/1000 and 1/1000 waves to achieve a contrast of 10{sup -10}. Finally, we have demonstrated that an SLM with more actuators can deliver a competitive contrast performance on the order of 10{sup -10} in comparison to that by using a deformable mirror.« less

Phase Quantization Study of Spatial Light Modulator for Extreme High-contrast Imaging

NASA Astrophysics Data System (ADS)

Dou, Jiangpei; Ren, Deqing

2016-11-01

Direct imaging of exoplanets by reflected starlight is extremely challenging due to the large luminosity ratio to the primary star. Wave-front control is a critical technique to attenuate the speckle noise in order to achieve an extremely high contrast. We present a phase quantization study of a spatial light modulator (SLM) for wave-front control to meet the contrast requirement of detection of a terrestrial planet in the habitable zone of a solar-type star. We perform the numerical simulation by employing the SLM with different phase accuracy and actuator numbers, which are related to the achievable contrast. We use an optimization algorithm to solve the quantization problems that is matched to the controllable phase step of the SLM. Two optical configurations are discussed with the SLM located before and after the coronagraph focal plane mask. The simulation result has constrained the specification for SLM phase accuracy in the above two optical configurations, which gives us a phase accuracy of 0.4/1000 and 1/1000 waves to achieve a contrast of 10-10. Finally, we have demonstrated that an SLM with more actuators can deliver a competitive contrast performance on the order of 10-10 in comparison to that by using a deformable mirror.

Extreme events following bifurcation to spatiotemporal chaos in a spatially extended microcavity laser

NASA Astrophysics Data System (ADS)

Coulibaly, S.; Clerc, M. G.; Selmi, F.; Barbay, S.

2017-02-01

The occurrence of extreme events in a spatially extended microcavity laser has been recently reported [Selmi et al., Phys. Rev. Lett. 116, 013901 (2016), 10.1103/PhysRevLett.116.013901] to be correlated to emergence of spatiotemporal chaos. In this dissipative system, the role of spatial coupling through diffraction is essential to observe the onset of spatiotemporal complexity. We investigate further the formation mechanism of extreme events by comparing the statistical and dynamical analyses. Experimental measurements together with numerical simulations allow us to assign the quasiperiodicity mechanism as the route to spatiotemporal chaos in this system. Moreover, by investigating the fine structure of the maximum Lyapunov exponent, of the Lyapunov spectrum, and of the Kaplan-Yorke dimension of the chaotic attractor, we are able to deduce that intermittency plays a key role in the proportion of extreme events measured. We assign the observed mechanism of generation of extreme events to quasiperiodic extended spatiotemporal intermittency.

Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems

PubMed Central

Wang, Kaibo; Huai, Yin; Lee, Rubao; Wang, Fusheng; Zhang, Xiaodong; Saltz, Joel H.

2012-01-01

As an important application of spatial databases in pathology imaging analysis, cross-comparing the spatial boundaries of a huge amount of segmented micro-anatomic objects demands extremely data- and compute-intensive operations, requiring high throughput at an affordable cost. However, the performance of spatial database systems has not been satisfactory since their implementations of spatial operations cannot fully utilize the power of modern parallel hardware. In this paper, we provide a customized software solution that exploits GPUs and multi-core CPUs to accelerate spatial cross-comparison in a cost-effective way. Our solution consists of an efficient GPU algorithm and a pipelined system framework with task migration support. Extensive experiments with real-world data sets demonstrate the effectiveness of our solution, which improves the performance of spatial cross-comparison by over 18 times compared with a parallelized spatial database approach. PMID:23355955

Control of Spin Wave Dynamics in Spatially Twisted Magnetic Structures

DTIC Science & Technology

2017-06-27

realize high-performance spintronic and magnetic storage devices. 15. SUBJECT TERMS nano- electronics , spin, wave, magnetic, multi-functional, device 16... electronics has required us to develop high-performance and multi-functional electronic devices driven with extremely low power consumption...Spintronics”, simultaneously utilizing the charge and the spin of electrons , provides us with solutions to essential problems for semiconductor-based

Measuring high-density built environment for public health research: Uncertainty with respect to data, indicator design and spatial scale.

PubMed

Sun, Guibo; Webster, Chris; Ni, Michael Y; Zhang, Xiaohu

2018-05-07

Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants' place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman's rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures.

Conditional probability of rainfall extremes across multiple durations

NASA Astrophysics Data System (ADS)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2017-04-01

The conditional probability that extreme rainfall will occur at one location given that it is occurring at another location is critical in engineering design and management circumstances including planning of evacuation routes and the sitting of emergency infrastructure. A challenge with this conditional simulation is that in many situations the interest is not so much the conditional distributions of rainfall of the same duration at two locations, but rather the conditional distribution of flooding in two neighbouring catchments, which may be influenced by rainfall of different critical durations. To deal with this challenge, a model that can consider both spatial and duration dependence of extremes is required. The aim of this research is to develop a model that can take account both spatial dependence and duration dependence into the dependence structure of extreme rainfalls. To achieve this aim, this study is a first attempt at combining extreme rainfall for multiple durations within a spatial extreme model framework based on max-stable process theory. Max-stable processes provide a general framework for modelling multivariate extremes with spatial dependence for just a single duration extreme rainfall. To achieve dependence across multiple timescales, this study proposes a new approach that includes addition elements representing duration dependence of extremes to the covariance matrix of max-stable model. To improve the efficiency of calculation, a re-parameterization proposed by Koutsoyiannis et al. (1998) is used to reduce the number of parameters necessary to be estimated. This re-parameterization enables the GEV parameters to be represented as a function of timescale. A stepwise framework has been adopted to achieve the overall aims of this research. Firstly, the re-parameterization is used to define a new set of common parameters for marginal distribution across multiple durations. Secondly, spatial interpolation of the new parameter set is used to estimate marginal parameters across the full spatial domain. Finally, spatial interpolation result is used as initial condition to estimate dependence parameters via a likelihood function of max-stable model for multiple durations. The Hawkesbury-Nepean catchment near Sydney in Australia was selected as case study for this research. This catchment has 25 sub-daily rain gauges with the minimum record length of 24 years over a region of 300 km × 300 km area. The re-parameterization was applied for each station for durations from 1 hour to 24 hours and then is evaluated by comparing with the at-site fitted GEV. The evaluation showed that the average R2 for all station is around 0.80 with the range from 0.26 to 1.0. The output of re-parameterization then was used to construct the spatial surface based on covariates including longitude, latitude, and elevation. The dependence model showed good agreements between empirical extremal coefficient and theoretical extremal coefficient for multiple durations. For the overall model, a leave-one-out cross-validation for all stations showed it works well for 20 out of 25 stations. The potential application of this model framework was illustrated through a conditional map of return period and return level across multiple durations, both of which are important for engineering design and management.

A nested observation and model approach to non linear groundwater surface water interactions.

NASA Astrophysics Data System (ADS)

van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.

2009-04-01

Surface water quality measurements in The Netherlands are scattered in time and space. Therefore, water quality status and its variations and trends are difficult to determine. In order to reach the water quality goals according to the European Water Framework Directive, we need to improve our understanding of the dynamics of surface water quality and the processes that affect it. In heavily drained lowland catchment groundwater influences the discharge towards the surface water network in many complex ways. Especially a strong seasonal contracting and expanding system of discharging ditches and streams affects discharge and solute transport. At a tube drained field site the tube drain flux and the combined flux of all other flow routes toward a stretch of 45 m of surface water have been measured for a year. Also the groundwater levels at various locations in the field and the discharge at two nested catchment scales have been monitored. The unique reaction of individual flow routes on rainfall events at the field site allowed us to separate the discharge at a 4 ha catchment and at a 6 km2 into flow route contributions. The results of this nested experimental setup combined with the results of a distributed hydrological model has lead to the formulation of a process model approach that focuses on the spatial variability of discharge generation driven by temporal and spatial variations in groundwater levels. The main idea of this approach is that discharge is not generated by catchment average storages or groundwater heads, but is mainly generated by points scale extremes i.e. extreme low permeability, extreme high groundwater heads or extreme low surface elevations, all leading to catchment discharge. We focused on describing the spatial extremes in point scale storages and this led to a simple and measurable expression that governs the non-linear groundwater surface water interaction. We will present the analysis of the field site data to demonstrate the potential of nested-scale, high frequency observations. The distributed hydrological model results will be used to show transient catchment scale relations between groundwater levels and discharges. These analyses lead to a simple expression that can describe catchment scale groundwater surface water interactions.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

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.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

DOE PAGES

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; ...

2017-11-20

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

Recent advances on reconstruction of climate and extreme events in China for the past 2000 year

NASA Astrophysics Data System (ADS)

Zheng, Jingyun; Hao, Zhixin; Ge, Quansheng; Liu, Yang

2016-04-01

The study of regional climate changes for past 2000 year could present spatial pattern of climate variation and various historical analogues for the sensitivity and operation of the climate system (e.g., the modulations of internal variability, feedbacks and teleconnections, abrupt changes and regional extreme events, etc.) from inter-annual to centennial scales and provide the knowledge to predict and project climate in the near future. China is distinguished by a prominent monsoon climate in east, continental arid climate in northwest and high land cold climate in Qinghai-Tibetan Plateau located at southwest. The long history of civilization and the variety of climate in China provides an abundant and well-dated documentary records and a wide range of natural archives (e.g., tree-ring, ice core, stalagmite, varved lake sediment, etc.) for high-resolution paleoclimate reconstruction. This paper presented a review of recent advances on reconstruction of climate and extreme events in China for the past 2000 years. In recent 10 years, there were many new high-resolution paleoclimatic reconstructions reported in China, e.g., the annual and decadal resolution series of temperature and precipitation in eastern China derived from historical documents, in western China derived from tree-ring and other natural archives. These new reconstructions provided more proxies and better spatial coverage to understand the characteristics of climate change over China and the uncertainty of regional reconstructions, as well as to reconstruct the high-resolution temperature series and the spatial pattern of precipitation change for whole China in the past millenniums by synthesizing the multi-proxy together. The updated results show that, in China, the warm intervals for the past 2000 years were in AD 1-200, AD 551-760, AD 951-1320, and after AD 1921; as well as the cold intervals were in AD 201-350, AD 441-530, AD 781-950, and AD 1321-1920. The extreme cold winters occurred in periods of 1500-1900 were more frequent than that after 1950. The intensity of regional heat wave occurred in the context of recent global warming may not exceed the natural climate variability during the historical times. In the eastern monsoon region of China, the significant cycles of precipitation are 90-100a, 70-80a, 43-48a, 35a, 25-27a and 17-18a in North China Plain; 90-100a, 73-75a, 63-68a, 55a, 45a, 37a and 26a in Jiang-Huai area; and 85-100a, 75-77a, 58-65a, 37-39a, 31a and 26a in Jiang-Nan area; respectively. Whereas, the spatial pattern of drought/flood for all cold periods ensemble mean showed an east to west distribution, but for all warm periods ensemble mean showed a tri-pole pattern with drought in south of 25°N, flood in 25°-30°N, and drought in north of 30°N. The extreme drought events were more frequent at the periods of 301-400, 751-800, 1051-1150, 1501-1550 and 1601-1650, the extreme flood events were more frequent at the periods of 101-150, 251-300, 951-1000, 1701-1750, 1801-1850 and 1901-1950, and for the period of 1551-1600, the coexisting extreme drought and extreme flood events most frequently occurred. In arid area, China, it was characterized by a relatively dry in AD 1000-1350, a wet in AD 1500 to 1850 and tending to moisture in recent decades. In the northeastern Qinghai-Tibetan Plateau, there existed evident centennial oscillations for precipitation during the past 1000 years, with interruption of several multi-decadal severe drought events, which two prominent droughty events centered on AD1480s and AD 1710s. In the Southwest of China, the extreme droughts as severe as in Sichuan and Chongqing in 2006 have also been occurred during the historical times.

ClimEx - Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec

NASA Astrophysics Data System (ADS)

Ludwig, Ralf; Baese, Frank; Braun, Marco; Brietzke, Gilbert; Brissette, Francois; Frigon, Anne; Giguère, Michel; Komischke, Holger; Kranzlmueller, Dieter; Leduc, Martin; Martel, Jean-Luc; Ricard, Simon; Schmid, Josef; von Trentini, Fabian; Turcotte, Richard; Weismueller, Jens; Willkofer, Florian; Wood, Raul

2017-04-01

The recent accumulation of extreme hydrological events in Bavaria and Québec has stimulated scientific and also societal interest. In addition to the challenges of an improved prediction of such situations and the implications for the associated risk management, there is, as yet, no confirmed knowledge whether and how climate change contributes to the magnitude and frequency of hydrological extreme events and how regional water management could adapt to the corresponding risks. The ClimEx project (2015-2019) investigates the effects of climate change on the meteorological and hydrological extreme events and their implications for water management in Bavaria and Québec. High Performance Computing is employed to enable the complex simulations in a hydro-climatological model processing chain, resulting in a unique high-resolution and transient (1950-2100) dataset of climatological and meteorological forcing and hydrological response: (1) The climate module has developed a large ensemble of high resolution data (12km) of the CRCM5 RCM for Central Europe and North-Eastern North America, downscaled from 50 members of the CanESM2 GCM. The dataset is complemented by all available data from the Euro-CORDEX project to account for the assessment of both natural climate variability and climate change. The large ensemble with several thousand model years provides the potential to catch rare extreme events and thus improves the process understanding of extreme events with return periods of 1000+ years. (2) The hydrology module comprises process-based and spatially explicit model setups (e.g. WaSiM) for all major catchments in Bavaria and Southern Québec in high temporal (3h) and spatial (500m) resolution. The simulations form the basis for in depth analysis of hydrological extreme events based on the inputs from the large climate model dataset. The specific data situation enables to establish a new method for 'virtual perfect prediction', which assesses climate change impacts on flood risk and water resources management by identifying patterns in the data which reveal preferential triggers of hydrological extreme events. The presentation will highlight first results from the analysis of the large scale ClimEx model ensemble, showing the current and future ratio of natural variability and climate change impacts on meteorological extreme events. Selected data from the ensemble is used to drive a hydrological model experiment to illustrate the capacity to better determine the recurrence periods of hydrological extreme events under conditions of climate change. [The authors acknowledge funding for the project from the Bavarian State Ministry for the Environment and Consumer Protection].

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.

High spatial resolution time-resolved magnetic resonance angiography of lower extremity tumors at 3T

PubMed Central

Wu, Gang; Jin, Teng; Li, Ting; Morelli, John; Li, Xiaoming

2016-01-01

Abstract The aim of this study was to compare diagnostic value of high spatial resolution time-resolved magnetic resonance angiography with interleaved stochastic trajectory (TWIST) using Gadobutrol to Computed tomography angiography (CTA) for preoperative evaluation of lower extremity tumors. This prospective study was approved by the institutional review board. Fifty consecutive patients (31 men, 19 women, age range 18–80 years, average age 42.7 years) with lower extremity tumors underwent TWIST magnetic resonance angiography (MRA) and CTA. Digital subtraction angiography was available for 8 patients. Image quality of MRA was compared with CTA by 2 radiologists according to a 4-point Likert scale. Arterial involvement by tumor was compared using kappa test between MRA and CTA. The ability to identify feeding arteries and arterio-venous fistulae (AVF) was compared using Wilcoxon signed rank test and McNemar test, respectively. Image quality of MRA and CTA was rated without a statistically significant difference (3.88 ± 0.37 vs. 3.97 ± 0.16, P = 0.135). Intramodality agreement was high for the identification of arterial invasion (kappa = 0.806 ± 0.073 for Reader 1, kappa = 0.805 ± 0.073 for Reader 2). Readers found AVF in 27 of 50 MRA cases and 14 of 50 CTA cases (P < 0.001). Mean feeding arteries identified with MRA were significantly more than that with CTA (2.08 ± 1.72 vs. 1.62 ± 1.52, P = .02). TWIST MRA is a reliable imaging modality for the assessment of lower extremity tumors. TWIST MRA is comparable to CTA for the identification of AVF and feeding arteries. PMID:27631262

Future changes of precipitation characteristics in China

NASA Astrophysics Data System (ADS)

Wu, S.; Wu, Y.; Wen, J.

2017-12-01

Global warming has the potential to alter the hydrological cycle, with significant impacts on the human society, the environment and ecosystems. This study provides a detailed assessment of potential changes in precipitation characteristics in China using a suite of 12 high-resolution CMIP5 climate models under a medium and a high Representative Concentration Pathways: RCP4.5 and RCP8.5. We examine future changes over the entire distribution of precipitation, and identify any shift in the shape and/or scale of the distribution. In addition, we use extreme-value theory to evaluate the change in probability and magnitude for extreme precipitation events. Overall, China is going to experience an increase in total precipitation (by 8% under RCP4.5 and 12% under RCP8.5). This increase is uneven spatially, with more increase in the west and less increase in the east. Precipitation frequency is projected to increase in the west and decrease in the east. Under RCP4.5, the overall precipitation frequency for the entire China remains largely unchanged (0.08%). However, RCP8.5 projects a more significant decrease in frequency for large part of China, resulting in an overall decrease of 2.08%. Precipitation intensity is likely increase more uniformly, with an overall increase of 11% for RCP4.5 and 19% for RCP8.5. Precipitation increases for all parts of the distribution, but the increase is more for higher quantiles, i.e. strong events. The relative contribution of small quantiles is likely to decrease, whereas contribution from heavy events is likely to increase. Extreme precipitation increase at much higher rates than average precipitation, and high rates of increase are expected for more extreme events. 1-year events are likely to increase by 15%, but 20-year events are going to increase by 21% under RCP4.5, 26% and 40% respectively under RCP8.5. The increase of extreme events is likely to be more spatially uniform.

Increased Spatial Variability and Intensification of Extreme Monsoon Rainfall due to Urbanization.

PubMed

Paul, Supantha; Ghosh, Subimal; Mathew, Micky; Devanand, Anjana; Karmakar, Subhankar; Niyogi, Dev

2018-03-02

While satellite data provides a strong robust signature of urban feedback on extreme precipitation; urbanization signal is often not so prominent with station level data. To investigate this, we select the case study of Mumbai, India and perform a high resolution (1 km) numerical study with Weather Research and Forecasting (WRF) model for eight extreme rainfall days during 2014-2015. The WRF model is coupled with two different urban schemes, the Single Layer Urban Canopy Model (WRF-SUCM), Multi-Layer Urban Canopy Model (WRF-MUCM). The differences between the WRF-MUCM and WRF-SUCM indicate the importance of the structure and characteristics of urban canopy on modifications in precipitation. The WRF-MUCM simulations resemble the observed distributed rainfall. WRF-MUCM also produces intensified rainfall as compared to the WRF-SUCM and WRF-NoUCM (without UCM). The intensification in rainfall is however prominent at few pockets of urban regions, that is seen in increased spatial variability. We find that the correlation of precipitation across stations within the city falls below statistical significance at a distance greater than 10 km. Urban signature on extreme precipitation will be reflected on station rainfall only when the stations are located inside the urban pockets having intensified precipitation, which needs to be considered in future analysis.

Pinhole X-ray/coronagraph optical systems concept definition study

NASA Technical Reports Server (NTRS)

Zehnpfenning, T. F.; Rappaport, S.; Wattson, R. B.

1980-01-01

The Pinhole X-ray/Coronagraph Concept utilizes the long baselines possible in Earth orbit with the space transportation system (shuttle) to produce observations of solar X-ray emission features at extremely high spatial resolution (up to 0.1 arc second) and high energy (up to 100 keV), and also white light and UV observations of the inner and outer corona at high spatial and/or spectral resolution. An examination of various aspects of a preliminary version of the X-ray Pinhole/Coronagraph Concept is presented. For this preliminary version, the instrument package will be carried in the shuttle bay on a mounting platform, and will be connected to the occulter with a deployable boom such as an Astromast. Generally, the spatial resolution, stray light levels, and minimum limb observing angles improve as the boom length increases. However, the associated engineering problems also become more serious with greater boom lengths.

Butterflies, Black swans and Dragon kings: How to use the Dynamical Systems Theory to build a "zoology" of mid-latitude circulation atmospheric extremes?

NASA Astrophysics Data System (ADS)

Faranda, D.; Yiou, P.; Alvarez-Castro, M. C. M.

2015-12-01

A combination of dynamical systems and statistical techniques allows for a robust assessment of the dynamical properties of the mid-latitude atmospheric circulation. Extremes at different spatial and time scales are not only associated to exceptionally intense weather structures (e.g. extra-tropical cyclones) but also to rapid changes of circulation regimes (thunderstorms, supercells) or the extreme persistence of weather structure (heat waves, cold spells). We will show how the dynamical systems theory of recurrence combined to the extreme value theory can take into account the spatial and temporal dependence structure of the mid-latitude circulation structures and provide information on the statistics of extreme events.

Future summer mega-heatwave and record-breaking temperatures in a warmer France climate

NASA Astrophysics Data System (ADS)

Bador, Margot; Terray, Laurent; Boé, Julien; Somot, Samuel; Alias, Antoinette; Gibelin, Anne-Laure; Dubuisson, Brigitte

2017-07-01

This study focuses on future very hot summers associated with severe heatwaves and record-breaking temperatures in France. Daily temperature observations and a pair of historical and scenario (greenhouse gas radiative concentration pathway 8.5) simulations with the high-resolution (∼12.5 km) ALADIN regional climate model provide a robust framework to examine the spatial distribution of these extreme events and their 21st century evolution. Five regions are identified with an extreme event spatial clustering algorithm applied to observed temperatures. They are used to diagnose the 21st century heatwave spatial patterns. In the 2070s, we find a simulated mega-heatwave as severe as the 2003 observed heatwave relative to its contemporaneous climate. A 20-member initial condition ensemble is used to assess the sensitivity of this future heatwave to the internal variability in the regional climate model and to pre-existing land surface conditions. Even in a much warmer and drier climate in France, late spring dry land conditions may lead to a significant amplification of summer extreme temperatures and heatwave intensity through limitations in evapotranspiration. By 2100, the increase in summer temperature maxima exhibits a range from 6 °C to almost 13 °C in the five regions in France, relative to historical maxima. These projections are comparable with the estimates given by a large number of global climate models.

Towards spatially constrained gust models

NASA Astrophysics Data System (ADS)

Bos, René; Bierbooms, Wim; van Bussel, Gerard

2014-06-01

With the trend of moving towards 10-20 MW turbines, rotor diameters are growing beyond the size of the largest turbulent structures in the atmospheric boundary layer. As a consequence, the fully uniform transients that are commonly used to predict extreme gust loads are losing their connection to reality and may lead to gross overdimensioning. More suiting would be to represent gusts by advecting air parcels and posing certain physical constraints on size and position. However, this would introduce several new degrees of freedom that significantly increase the computational burden of extreme load prediction. In an attempt to elaborate on the costs and benefits of such an approach, load calculations were done on the DTU 10 MW reference turbine where a single uniform gust shape was given various spatial dimensions with the transverse wavelength ranging up to twice the rotor diameter (357 m). The resulting loads displayed a very high spread, but remained well under the level of a uniform gust. Moving towards spatially constrained gust models would therefore yield far less conservative, though more realistic predictions at the cost of higher computation time.

Slit-lamp photography and videography with high magnifications

PubMed Central

Yuan, Jin; Jiang, Hong; Mao, Xinjie; Ke, Bilian; Yan, Wentao; Liu, Che; Cintrón-Colón, Hector R; Perez, Victor L; Wang, Jianhua

2015-01-01

Purpose To demonstrate the use of the slit-lamp photography and videography with extremely high magnifications for visualizing structures of the anterior segment of the eye. Methods A Canon 60D digital camera with Movie Crop Function was adapted into a Nikon FS-2 slit-lamp to capture still images and video clips of the structures of the anterior segment of the eye. Images obtained using the slit-lamp were tested for spatial resolution. The cornea of human eyes was imaged with the slit-lamp and the structures were compared with the pictures captured using the ultra-high resolution optical coherence tomography (UHR-OCT). The central thickness of the corneal epithelium and total cornea was obtained using the slit-lamp and the results were compared with the thickness obtained using UHR-OCT. Results High-quality ocular images and higher spatial resolutions were obtained by using the slit-lamp with extremely high magnifications and Movie Crop Function, rather than the traditional slit-lamp. The structures and characteristics of the cornea, such as the normal epithelium, abnormal epithelium of corneal intraepithelial neoplasia, LASIK interface, and contact lenses, were clearly visualized using this device. These features were confirmed by comparing the obtained images with those acquired using UHR-OCT. Moreover, the tear film debris on the ocular surface and the corneal nerve in the anterior corneal stroma were also visualized. The thicknesses of the corneal epithelium and total cornea were similar to that measured using UHR-OCT (P < 0.05). Conclusions We demonstrated that the slit-lamp photography and videography with extremely high magnifications allows better visualization of the anterior segment structures of the eye, especially of the epithelium, when compared with the traditional slit-lamp. PMID:26020484

Scaling of precipitation extremes with temperature in the French Mediterranean region: What explains the hook shape?

NASA Astrophysics Data System (ADS)

Drobinski, P.; Alonzo, B.; Bastin, S.; Silva, N. Da; Muller, C.

2016-04-01

Expected changes to future extreme precipitation remain a key uncertainty associated with anthropogenic climate change. Extreme precipitation has been proposed to scale with the precipitable water content in the atmosphere. Assuming constant relative humidity, this implies an increase of precipitation extremes at a rate of about 7% °C-1 globally as indicated by the Clausius-Clapeyron relationship. Increases faster and slower than Clausius-Clapeyron have also been reported. In this work, we examine the scaling between precipitation extremes and temperature in the present climate using simulations and measurements from surface weather stations collected in the frame of the HyMeX and MED-CORDEX programs in Southern France. Of particular interest are departures from the Clausius-Clapeyron thermodynamic expectation, their spatial and temporal distribution, and their origin. Looking at the scaling of precipitation extreme with temperature, two regimes emerge which form a hook shape: one at low temperatures (cooler than around 15°C) with rates of increase close to the Clausius-Clapeyron rate and one at high temperatures (warmer than about 15°C) with sub-Clausius-Clapeyron rates and most often negative rates. On average, the region of focus does not seem to exhibit super Clausius-Clapeyron behavior except at some stations, in contrast to earlier studies. Many factors can contribute to departure from Clausius-Clapeyron scaling: time and spatial averaging, choice of scaling temperature (surface versus condensation level), and precipitation efficiency and vertical velocity in updrafts that are not necessarily constant with temperature. But most importantly, the dynamical contribution of orography to precipitation in the fall over this area during the so-called "Cevenoles" events, explains the hook shape of the scaling of precipitation extremes.

Can Regional Climate Modeling Capture the Observed Changes in Spatial Organization of Extreme Storms at Higher Temperatures?

NASA Astrophysics Data System (ADS)

Li, J.; Wasko, C.; Johnson, F.; Evans, J. P.; Sharma, A.

2018-05-01

The spatial extent and organization of extreme storm events has important practical implications for flood forecasting. Recently, conflicting evidence has been found on the observed changes of storm spatial extent with increasing temperatures. To further investigate this question, a regional climate model assessment is presented for the Greater Sydney region, in Australia. Two regional climate models were considered: the first a convection-resolving simulation at 2-km resolution, the second a resolution of 10 km with three different convection parameterizations. Both the 2- and the 10-km resolutions that used the Betts-Miller-Janjic convective scheme simulate decreasing storm spatial extent with increasing temperatures for 1-hr duration precipitation events, consistent with the observation-based study in Australia. However, other observed relationships of extreme rainfall with increasing temperature were not well represented by the models. Improved methods for considering storm organization are required to better understand potential future changes.

Stride search: A general algorithm for storm detection in high resolution climate data

DOE PAGES

Bosler, Peter Andrew; Roesler, Erika Louise; Taylor, Mark A.; ...

2015-09-08

This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared. The commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. Stride Search is designed to work at all latitudes, while grid point searches may fail in polar regions. Results from the two algorithms are compared for the application of tropicalmore » cyclone detection, and shown to produce similar results for the same set of storm identification criteria. The time required for both algorithms to search the same data set is compared. Furthermore, Stride Search's ability to search extreme latitudes is demonstrated for the case of polar low detection.« less

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.

Extreme river flow dependence in Northern Scotland

NASA Astrophysics Data System (ADS)

Villoria, M. Franco; Scott, M.; Hoey, T.; Fischbacher-Smith, D.

2012-04-01

Various methods for the spatial analysis of hydrologic data have been developed recently. Here we present results using the conditional probability approach proposed by Keef et al. [Appl. Stat. (2009): 58,601-18] to investigate spatial interdependence in extreme river flows in Scotland. This approach does not require the specification of a correlation function, being mostly suitable for relatively small geographical areas. The work is motivated by the Flood Risk Management Act (Scotland (2009)) which requires maps of flood risk that take account of spatial dependence in extreme river flow. The method is based on two conditional measures of spatial flood risk: firstly the conditional probability PC(p) that a set of sites Y = (Y 1,...,Y d) within a region C of interest exceed a flow threshold Qp at time t (or any lag of t), given that in the specified conditioning site X > Qp; and, secondly the expected number of sites within C that will exceed a flow Qp on average (given that X > Qp). The conditional probabilities are estimated using the conditional distribution of Y |X = x (for large x), which can be modeled using a semi-parametric approach (Heffernan and Tawn [Roy. Statist. Soc. Ser. B (2004): 66,497-546]). Once the model is fitted, pseudo-samples can be generated to estimate functionals of the joint tails of the distribution of (Y,X). Conditional return level plots were directly compared to traditional return level plots thus improving our understanding of the dependence structure of extreme river flow events. Confidence intervals were calculated using block bootstrapping methods (100 replicates). We report results from applying this approach to a set of four rivers (Dulnain, Lossie, Ewe and Ness) in Northern Scotland. These sites were chosen based on data quality, spatial location and catchment characteristics. The river Ness, being the largest (catchment size 1839.1km2) was chosen as the conditioning river. Both the Ewe (441.1km2) and Ness catchments have predominantly impermeable bedrock, with the Ewe's one being very wet. The Lossie(216km2) and Dulnain (272.2km2) both contain significant areas of glacial deposits. River flow in the Dulnain is usually affected by snowmelt. In all cases, the conditional probability of each of the three rivers (Dulnain, Lossie, Ewe) decreases as the event in the conditioning river (Ness) becomes more extreme. The Ewe, despite being the furthest of the three sites from the Ness shows the strongest dependence, with relatively high (>0.4) conditional probabilities even for very extreme events (>0.995). Although the Lossie is closer geographically to the Ness than the Ewe, it shows relatively low conditional probabilities and can be considered independent of the Ness for very extreme events (> 0.990). The conditional probabilities seem to reflect the different catchment characteristics and dominant precipitation generating events, with the Ewe being more similar to the Ness than the other two rivers. This interpretation suggests that the conditional method may yield improved estimates of extreme events, but the approach is time consuming. An alternative model that is easier to implement, using a spatial quantile regression, is currently being investigated, which would also allow the introduction of further covariates, essential as the effects of climate change are incorporated into estimation procedures.

The effects of climate change and extreme wildfire events on runoff erosion over a mountain watershed

Treesearch

Mingliang Liu; Michael E. Barber; Keith A. Cherkauer; Pete Robichaud; Jennifer C. Adam

2016-01-01

Increases in wildfire occurrence and severity under an altered climate can substantially impact terrestrial ecosystems through enhancing runoff erosion. Improved prediction tools that provide high resolution spatial information are necessary for location-specific soil conservation and watershed management. However, quantifying the magnitude of soil erosion and...

Spatial Navigation Impairments Among Intellectually High-Functioning Adults With Autism Spectrum Disorder: Exploring Relations With Theory of Mind, Episodic Memory, and Episodic Future Thinking

PubMed Central

2013-01-01

Research suggests that spatial navigation relies on the same neural network as episodic memory, episodic future thinking, and theory of mind (ToM). Such findings have stimulated theories (e.g., the scene construction and self-projection hypotheses) concerning possible common underlying cognitive capacities. Consistent with such theories, autism spectrum disorder (ASD) is characterized by concurrent impairments in episodic memory, episodic future thinking, and ToM. However, it is currently unclear whether spatial navigation is also impaired. Hence, ASD provides a test case for the scene construction and self-projection theories. The study of spatial navigation in ASD also provides a test of the extreme male brain theory of ASD, which predicts intact or superior navigation (purportedly a systemizing skill) performance among individuals with ASD. Thus, the aim of the current study was to establish whether spatial navigation in ASD is impaired, intact, or superior. Twenty-seven intellectually high-functioning adults with ASD and 28 sex-, age-, and IQ-matched neurotypical comparison adults completed the memory island virtual navigation task. Tests of episodic memory, episodic future thinking, and ToM were also completed. Participants with ASD showed significantly diminished performance on the memory island task, and performance was positively related to ToM and episodic memory, but not episodic future thinking. These results suggest that (contra the extreme male brain theory) individuals with ASD have impaired survey-based navigation skills—that is, difficulties generating cognitive maps of the environment—and adds weight to the idea that scene construction/self-projection are impaired in ASD. The theoretical and clinical implications of these results are discussed. PMID:24364620

Changes in the extreme wave heights over the Baltic Sea

NASA Astrophysics Data System (ADS)

Kudryavtseva, Nadia; Soomere, Tarmo

2017-04-01

Storms over the Baltic Sea and northwestern Europe have a large impact on the population, offshore industry, and shipping. The understanding of extreme events in sea wave heights and their change due to the climate change and variability is critical for assessment of flooding risks and coastal protection. The BACCII Assessment of Climate Change for the Baltic Sea Basin showed that the extreme events analysis of wind waves is currently not very well addressed, as well as satellite observations of the wave heights. Here we discuss the analysis of all existing satellite altimetry data over the Baltic Sea Basin regarding extremes in the wave heights. In this talk for the first time, we present an analysis of 100-yr return periods, fitted generalized Pareto and Weibull distributions, number, and frequency of extreme events in wave heights in the Baltic Sea measured by the multi-mission satellite altimetry. The data span more than 23 years and provide an excellent spatial coverage over the Baltic Sea, allowing to study in details spatial variations and changes in extreme wave heights. The analysis is based on an application of the Initial Distribution Method, Annual Maxima method and Peak-Over-Threshold approach to satellite altimetry data, all validated in comparison with in-situ wave height measurements. Here we show that the 100-yr return periods of wave heights show significant spatial changes over the Baltic Sea indicating a decrease in the southern part of the Baltic Sea and an increase in adjacent areas, which can significantly affect coast vulnerability. Here we compare the observed shift with storm track database data and discuss a spatial correlation and possible connection between the changes in the storm tracks over the Baltic Sea and the change in the extreme wave heights.

Topographic relationships for design rainfalls over Australia

NASA Astrophysics Data System (ADS)

Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

2016-02-01

Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as for most of the Australian continent, extreme rainfall is closely aligned with elevation, but in areas with high topographic relief the impacts of topography on rainfall extremes are more complex. The interpolated extreme rainfall statistics, using no data transformation, have been used by the Australian Bureau of Meteorology to produce new IDF data for the Australian continent. The comprehensive methods presented for the evaluation of gridded design rainfall statistics will be useful for similar studies, in particular the importance of balancing the need for a continentally-optimum solution that maintains sufficient definition at the local scale.

Analysis of the precipitation and streamflow extremes in Northern Italy using high resolution reanalysis dataset Express-Hydro

NASA Astrophysics Data System (ADS)

Silvestro, Francesco; Parodi, Antonio; Campo, Lorenzo

2017-04-01

The characterization of the hydrometeorological extremes, both in terms of rainfall and streamflow, in a given region plays a key role in the environmental monitoring provided by the flood alert services. In last years meteorological simulations (both near real-time and historical reanalysis) were available at increasing spatial and temporal resolutions, making possible long-period hydrological reanalysis in which the meteo dataset is used as input in distributed hydrological models. In this work, a very high resolution meteorological reanalysis dataset, namely Express-Hydro (CIMA, ISAC-CNR, GAUSS Special Project PR45DE), was employed as input in the hydrological model Continuum in order to produce long time series of streamflows in the Liguria territory, located in the Northern part of Italy. The original dataset covers the whole Europe territory in the 1979-2008 period, at 4 km of spatial resolution and 3 hours of time resolution. Analyses in terms of comparison between the rainfall estimated by the dataset and the observations (available from the local raingauges network) were carried out, and a bias correction was also performed in order to better match the observed climatology. An extreme analysis was eventually carried on the streamflows time series obtained by the simulations, by comparing them with the results of the same hydrological model fed with the observed time series of rainfall. The results of the analysis are shown and discussed.

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Massada, Avi Bar; Radeloff, Volker C.; Stewart, Susan I.; Hawbaker, Todd J.

2009-01-01

The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfirerisk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfirerisk to a 60,000 ha WUI area in northwesternWisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfirerisk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfirerisk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfirerisk and those most vulnerable under extreme weather conditions.

Predicting the Effect of Changing Precipitation Extremes and Land Cover Change on Urban Water Quality

NASA Astrophysics Data System (ADS)

SUN, N.; Yearsley, J. R.; Lettenmaier, D. P.

2013-12-01

Recent research shows that precipitation extremes in many of the largest U.S. urban areas have increased over the last 60 years. These changes have important implications for stormwater runoff and water quality, which in urban areas are dominated by the most extreme precipitation events. We assess the potential implications of changes in extreme precipitation and changing land cover in urban and urbanizing watersheds at the regional scale using a combination of hydrology and water quality models. Specifically, we describe the integration of a spatially distributed hydrological model - the Distributed Hydrology Soil Vegetation Model (DHSVM), the urban water quality model in EPA's Storm Water Management Model (SWMM), the semi-Lagrangian stream temperature model RBM10, and dynamical and statistical downscaling methods applied to global climate predictions. Key output water quality parameters include total suspended solids (TSS), toal nitrogen, total phosphorous, fecal coliform bacteria and stream temperature. We have evaluated the performance of the modeling system in the highly urbanized Mercer Creek watershed in the rapidly growing Bellevue urban area in WA, USA. The results suggest that the model is able to (1) produce reasonable streamflow predictions at fine temporal and spatial scales; (2) provide spatially distributed water temperature predictions that mostly agree with observations throughout a complex stream network, and characterize impacts of climate, landscape, near-stream vegetation change on stream temperature at local and regional scales; and (3) capture plausibly the response of water quality constituents to varying magnitude of precipitation events in urban environments. Next we will extend the scope of the study from the Mercer Creek watershed to include the entire Puget Sound Basin, WA, USA.

Extreme storm surge modelling in the North Sea. The role of the sea state, forcing frequency and spatial forcing resolution

NASA Astrophysics Data System (ADS)

Ridder, Nina; de Vries, Hylke; Drijfhout, Sybren; van den Brink, Henk; van Meijgaard, Erik; de Vries, Hans

2018-02-01

This study shows that storm surge model performance in the North Sea is mostly unaffected by the application of temporal variations of surface drag due to changes in sea state provided the choice of a suitable constant Charnock parameter in the sea-state-independent case. Including essential meteorological features on smaller scales and minimising interpolation errors by increasing forcing data resolution are shown to be more important for the improvement of model performance particularly at the high tail of the probability distribution. This is found in a modelling study using WAQUA/DCSMv5 by evaluating the influence of a realistic air-sea momentum transfer parameterization and comparing it to the influence of changes in the spatial and temporal resolution of the applied forcing fields in an effort to support the improvement of impact and climate analysis studies. Particular attention is given to the representation of extreme water levels over the past decades based on the example of the Netherlands. For this, WAQUA/DCSMv5 is forced with ERA-Interim reanalysis data. Model results are obtained from a set of different forcing fields, which either (i) include a wave-state-dependent Charnock parameter or (ii) apply a constant Charnock parameter ( α C h = 0.032) tuned for young sea states in the North Sea, but differ in their spatial and/or temporal resolution. Increasing forcing field resolution from roughly 79 to 12 km through dynamically downscaling can reduce the modelled low bias, depending on coastal station, by up to 0.25 m for the modelled extreme water levels with a 1-year return period and between 0.1 m and 0.5 m for extreme surge heights.

A plasma microlens for ultrashort high power lasers

NASA Astrophysics Data System (ADS)

Katzir, Yiftach; Eisenmann, Shmuel; Ferber, Yair; Zigler, Arie; Hubbard, Richard F.

2009-07-01

We present a technique for generation of miniature plasma lens system that can be used for focusing and collimating a high intensity femtosecond laser pulse. The plasma lens was created by a nanosecond laser, which ablated a capillary entrance. The spatial configuration of the ablated plasma focused a high intensity femtosecond laser pulse. This configuration offers versatility in the plasma lens small f-number for extremely tight focusing of high power lasers with no damage threshold restrictions of regular optical components.

Mapping snow depth return levels: smooth spatial modeling versus station interpolation

NASA Astrophysics Data System (ADS)

Blanchet, J.; Lehning, M.

2010-12-01

For adequate risk management in mountainous countries, hazard maps for extreme snow events are needed. This requires the computation of spatial estimates of return levels. In this article we use recent developments in extreme value theory and compare two main approaches for mapping snow depth return levels from in situ measurements. The first one is based on the spatial interpolation of pointwise extremal distributions (the so-called Generalized Extreme Value distribution, GEV henceforth) computed at station locations. The second one is new and based on the direct estimation of a spatially smooth GEV distribution with the joint use of all stations. We compare and validate the different approaches for modeling annual maximum snow depth measured at 100 sites in Switzerland during winters 1965-1966 to 2007-2008. The results show a better performance of the smooth GEV distribution fitting, in particular where the station network is sparser. Smooth return level maps can be computed from the fitted model without any further interpolation. Their regional variability can be revealed by removing the altitudinal dependent covariates in the model. We show how return levels and their regional variability are linked to the main climatological patterns of Switzerland.

Normal-incidence EXtreme-Ultraviolet imaging Spectrometer - NEXUS

NASA Astrophysics Data System (ADS)

Dere, K. P.

2003-05-01

NEXUS is the result of a breakthrough optical design that incorporates new technologies to achieve high optical throughput at high spatial (1 arcsec) and spectral (1-2 km s-1) resolution over a wide field of view in an optimal extreme-ultraviolet spectral band. This achievement was made possible primarily by two technical developments. First, a coating of boron-carbide deposited onto a layer of iridium provided a greatly enhanced reflectivity at EUV wavelengths that would enable NEXUS to observe the Sun over a wide temperature range at high cadence. The reflectivity of these coatings have been measured and demonstrated in the laboratory. The second key development was the use of a variable-line-spaced toroidal grating spectrometer. The spectrometer design allowed the Sun to be imaged at high spatial and spectral resolution along a 1 solar radius-long slit and over a wavelength range from 450 to 800 Å, nearly an entire spectral order. Because the spectrograph provided a magnification of about a factor of 6, only 2 optical elements are required to achieved the desired imaging performance. Throughput was enhanced by the use of only 2 reflections. The could all be accomodated within a total instrument length of 1.5m. We would like to acknowledge support from ONR

Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model

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

Wang, Jiali; Han, Yuefeng; Stein, Michael L.

2016-02-10

The Weather Research and Forecast (WRF) model downscaling skill in extreme maximum daily temperature is evaluated by using the generalized extreme value (GEV) distribution. While the GEV distribution has been used extensively in climatology and meteorology for estimating probabilities of extreme events, accurately estimating GEV parameters based on data from a single pixel can be difficult, even with fairly long data records. This work proposes a simple method assuming that the shape parameter, the most difficult of the three parameters to estimate, does not vary over a relatively large region. This approach is applied to evaluate 31-year WRF-downscaled extreme maximummore » temperature through comparison with North American Regional Reanalysis (NARR) data. Uncertainty in GEV parameter estimates and the statistical significance in the differences of estimates between WRF and NARR are accounted for by conducting bootstrap resampling. Despite certain biases over parts of the United States, overall, WRF shows good agreement with NARR in the spatial pattern and magnitudes of GEV parameter estimates. Both WRF and NARR show a significant increase in extreme maximum temperature over the southern Great Plains and southeastern United States in January and over the western United States in July. The GEV model shows clear benefits from the regionally constant shape parameter assumption, for example, leading to estimates of the location and scale parameters of the model that show coherent spatial patterns.« less

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.

Spatial variation of statistical properties of extreme water levels along the eastern Baltic Sea

NASA Astrophysics Data System (ADS)

Pindsoo, Katri; Soomere, Tarmo; Rocha, Eugénio

2016-04-01

Most of existing projections of future extreme water levels rely on the use of classic generalised extreme value distributions. The choice to use a particular distribution is often made based on the absolute value of the shape parameter of the Generalise Extreme Value distribution. If this parameter is small, the Gumbel distribution is most appropriate while in the opposite case the Weibull or Frechet distribution could be used. We demonstrate that the alongshore variation in the statistical properties of numerically simulated high water levels along the eastern coast of the Baltic Sea is so large that the use of a single distribution for projections of extreme water levels is highly questionable. The analysis is based on two simulated data sets produced in the Swedish Meteorological and Hydrological Institute. The output of the Rossby Centre Ocean model is sampled with a resolution of 6 h and the output of the circulation model NEMO with a resolution of 1 h. As the maxima of water levels of subsequent years may be correlated in the Baltic Sea, we also employ maxima for stormy seasons. We provide a detailed analysis of spatial variation of the parameters of the family of extreme value distributions along an approximately 600 km long coastal section from the north-western shore of Latvia in the Baltic Proper until the eastern Gulf of Finland. The parameters are evaluated using maximum likelihood method and method of moments. The analysis also covers the entire Gulf of Riga. The core parameter of this family of distributions, the shape parameter of the Generalised Extreme Value distribution, exhibits extensive variation in the study area. Its values evaluated using the Hydrognomon software and maximum likelihood method, vary from about -0.1 near the north-western coast of Latvia in the Baltic Proper up to about 0.05 in the eastern Gulf of Finland. This parameter is very close to zero near Tallinn in the western Gulf of Finland. Thus, it is natural that the Gumbel distribution gives adequate projections of extreme water levels for the vicinity of Tallinn. More importantly, this feature indicates that the use of a single distribution for the projections of extreme water levels and their return periods for the entire Baltic Sea coast is inappropriate. The physical reason is the interplay of the complex shape of large subbasins (such as the Gulf of Riga and Gulf of Finland) of the sea and highly anisotropic wind regime. The 'impact' of this anisotropy on the statistics of water level is amplified by the overall anisotropy of the distributions of the frequency of occurrence of high and low water levels. The most important conjecture is that long-term behaviour of water level extremes in different coastal sections of the Baltic Sea may be fundamentally different.

Spatio-temporal variations in storm surges along the North Atlantic coasts

NASA Astrophysics Data System (ADS)

Marcos, Marta; Woodworth, Philip

2017-04-01

Extreme sea levels along the coasts of the North Atlantic Ocean and the Gulf of Mexico have been investigated using hourly tide gauge records compiled in the recently released GESLA-2 data set (www.gesla.org). These regions are among the most densely monitored coasts worldwide, with more than 300 high frequency quality-controlled tide gauge time series available. Here we estimate the storm surge component of extreme sea levels using both tidal residuals and skew surges, for which we explore the spatial and temporal coherency of their intensities, duration and frequency. We quantify the relationship of extremes with dominant large scale climate patterns and discuss the impact of mean sea level changes. Finally, we test the assumption of stationarity of the probability of extreme occurrence and to which extent it holds when mean sea level changes are considered in combination with storm surges.

Large uncertainties in observed daily precipitation extremes over land

NASA Astrophysics Data System (ADS)

Herold, Nicholas; Behrangi, Ali; Alexander, Lisa V.

2017-01-01

We explore uncertainties in observed daily precipitation extremes over the terrestrial tropics and subtropics (50°S-50°N) based on five commonly used products: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset, the Global Precipitation Climatology Centre-Full Data Daily (GPCC-FDD) dataset, the Tropical Rainfall Measuring Mission (TRMM) multi-satellite research product (T3B42 v7), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Global Precipitation Climatology Project's One-Degree Daily (GPCP-1DD) dataset. We use the precipitation indices R10mm and Rx1day, developed by the Expert Team on Climate Change Detection and Indices, to explore the behavior of "moderate" and "extreme" extremes, respectively. In order to assess the sensitivity of extreme precipitation to different grid sizes we perform our calculations on four common spatial resolutions (0.25° × 0.25°, 1° × 1°, 2.5° × 2.5°, and 3.75° × 2.5°). The impact of the chosen "order of operation" in calculating these indices is also determined. Our results show that moderate extremes are relatively insensitive to product and resolution choice, while extreme extremes can be very sensitive. For example, at 0.25° × 0.25° quasi-global mean Rx1day values vary from 37 mm in PERSIANN-CDR to 62 mm in T3B42. We find that the interproduct spread becomes prominent at resolutions of 1° × 1° and finer, thus establishing a minimum effective resolution at which observational products agree. Without improvements in interproduct spread, these exceedingly large observational uncertainties at high spatial resolution may limit the usefulness of model evaluations. As has been found previously, resolution sensitivity can be largely eliminated by applying an order of operation where indices are calculated prior to regridding. However, this approach is not appropriate when true area averages are desired (e.g., for model evaluations).

The Extreme Ultraviolet spectrometer on bard the Hisaki satellite

NASA Astrophysics Data System (ADS)

Yoshioka, K.; Murakami, G.; Yamazaki, A.; Tsuchiya, F.; Kagitani, M.; Kimura, T.; Yoshikawa, I.

2017-12-01

The extreme ultraviolet spectroscope EXCEED (EXtrem ultraviolet spetrosCope for ExosphEric Dynamics) on board the Hisaki satellite was launched in September 2013 from the Uchinoura space center, Japan. It is orbiting around the Earth with an orbital altitude of around 950-1150 km. This satellite is dedicated to and optimized for observing the atmosphere and magnetosphere of terrestrial planets such as Mercury, Venus, Mars, as well as Jupiter. The instrument consists of an off axis parabolic entrance mirror, switchable slits with multiple filters and shapes, a toroidal grating, and a photon counting detector, together with a field of view guiding camera. The design goal is to achieve a large effective area but with high spatial and spectral resolution. Based on the after-launch calibration, the spectral resolution of EXCEED is found to be 0.3-0.5 nm FWHM (Full Width at Half Maximum) over the entire spectral band, and the spatial resolution is around 17". The evaluated effective area is larger than 1cm2. In this presentation, the basic concept of the instrument design and the observation technique are introduced. The current status of the spacecraft and its future observation plan are also shown.

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.

Disturbance Impacts on Thermal Hot Spots and Hot Moments at the Peatland-Atmosphere Interface

NASA Astrophysics Data System (ADS)

Leonard, R. M.; Kettridge, N.; Devito, K. J.; Petrone, R. M.; Mendoza, C. A.; Waddington, J. M.; Krause, S.

2018-01-01

Soil-surface temperature acts as a master variable driving nonlinear terrestrial ecohydrological, biogeochemical, and micrometeorological processes, inducing short-lived or spatially isolated extremes across heterogeneous landscape surfaces. However, subcanopy soil-surface temperatures have been, to date, characterized through isolated, spatially discrete measurements. Using spatially complex forested northern peatlands as an exemplar ecosystem, we explore the high-resolution spatiotemporal thermal behavior of this critical interface and its response to disturbances by using Fiber-Optic Distributed Temperature Sensing. Soil-surface thermal patterning was identified from 1.9 million temperature measurements under undisturbed, trees removed and vascular subcanopy removed conditions. Removing layers of the structurally diverse vegetation canopy not only increased mean temperatures but it shifted the spatial and temporal distribution, range, and longevity of thermal hot spots and hot moments. We argue that linking hot spots and/or hot moments with spatially variable ecosystem processes and feedbacks is key for predicting ecosystem function and resilience.

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.

Terrestrial habitat selection and strong density-dependent mortality in recently metamorphosed amphibians.

PubMed

Patrick, David A; Harper, Elizabeth B; Hunter, Malcolm L; Calhoun, Aram J K

2008-09-01

To predict the effects of terrestrial habitat change on amphibian populations, we need to know how amphibians respond to habitat heterogeneity, and whether habitat choice remains consistent throughout the life-history cycle. We conducted four experiments to evaluate how the spatial distribution of juvenile wood frogs, Rana sylvatica (including both overall abundance and localized density), was influenced by habitat choice and habitat structure, and how this relationship changed with spatial scale and behavioral phase. The four experiments included (1) habitat manipulation on replicated 10-ha landscapes surrounding breeding pools; (2) short-term experiments with individual frogs emigrating through a manipulated landscape of 1 m wide hexagonal patches; and habitat manipulations in (3) small (4-m2); and (4) large (100-m2) enclosures with multiple individuals to compare behavior both during and following emigration. The spatial distribution of juvenile wood frogs following emigration resulted from differences in the scale at which juvenile amphibians responded to habitat heterogeneity during active vs. settled behavioral phases. During emigration, juvenile wood frogs responded to coarse-scale variation in habitat (selection between 2.2-ha forest treatments) but not to fine-scale variation. After settling, however, animals showed habitat selection at much smaller scales (2-4 m2). This resulted in high densities of animals in small patches of suitable habitat where they experienced rapid mortality. No evidence of density-dependent habitat selection was seen, with juveniles typically choosing to remain at extremely high densities in high-quality habitat, rather than occupying low-quality habitat. These experiments demonstrate how prediction of the terrestrial distribution of juvenile amphibians requires understanding of the complex behavioral responses to habitat heterogeneity. Understanding these patterns is important, given that human alterations to amphibian habitats may generate extremely high densities of animals, resulting in high density-dependent mortality.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Switzer, A.; Yap, W.; Lauro, F.; Gouramanis, C.; Dominey-Howes, D.; Labbate, M.

2016-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Sorooshian, S.; Nguyen, P.; Hsu, K. L.

2017-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

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.

Extreme Landfalling Atmospheric River Events in Arizona: Possible Future Changes

NASA Astrophysics Data System (ADS)

Singh, I.; Dominguez, F.

2016-12-01

Changing climate could impact the frequency and intensity of extreme atmospheric river events. This can have important consequences for regions like the Southwestern United Sates that rely upon AR-related precipitation for meeting their water demand and are prone to AR-related flooding. This study investigates the effects of climate change on extreme AR events in the Salt and Verde river basins in Central Arizona using a pseudo global warming method (PGW). First, the five most extreme events that affected the region were selected. High-resolution control simulations of these events using the Weather Research and Forecasting model realistically captured the magnitude and spatial distribution of precipitation. Subsequently, following the PGW approach, the WRF initial and lateral boundary conditions were perturbed. The perturbation signals were obtained from an ensemble of 9 General Circulation Models for two warming scenarios - Representative Concentration Pathway (RCP) 4.5 and RCP8.5. Several simulations were conducted changing the temperature and relative humidity fields. PGW simulations reveal that while the overall dynamics of the storms did not change significantly, there was marked strengthening of associated Integrated Vertical Transport (IVT) plumes. There was a general increase in the precipitation over the basins due to increased moisture availability, but heterogeneous spatial changes. Additionally, no significant changes in the strength of the pre-cold frontal low-level jet in the future simulations were observed.

Spatial differences of aeolian desertification responses to climate in arid Asia

NASA Astrophysics Data System (ADS)

Wang, Xunming; Hua, Ting; Lang, Lili; Ma, Wenyong

2017-01-01

Most areas of arid Asia are covered by aeolian dunes, sand sheets, gravels, and desert steppes, and may jeopardize nearly 350 million people if climate change increases aeolian desertification. Although the aeolian desertification is mainly triggered by climate changes are extensively acknowledged, the responses of aeolian desertification to various climate scenarios are poorly understood. Based on the tight combinations of dune activity index (DAI) trends and of aeolian desertification, here the spatial differences of aeolian desertification responses on various climate scenarios were reported. The analyzed results show that the variations in temperature, precipitation and wind regime have no significant contributions on aeolian desertification in the extremely arid Asia. From the early to blooming periods of vegetation growth, although temperature rise may benefit vegetation growths in some high latitudes and altitudes, the temperature rise may increase aeolian desertification in most arid Asia regions such as Mongolia, West and Central Asia. In arid Asia, although precipitation increases may benefit the rehabilitation, decreases in precipitation is not the key role on aeolian desertification occurrences in extremely arid regions. From the early to blooming periods of vegetation growths, spatial trends of the sensitivity of aeolian desertification to wind regime varied. Generally, at the regional scales there are relative high sensitivities for aeolian desertification to climate changes in the eastern and western regions of arid Asia, and the climate changes may not play important roles on aeolian desertification occurrence in the central regions. The spatial differences of aeolian desertification responses to climate changes indicate various strategies for aeolian desertification combating are needed in different regions of arid Asia.

Spatial congruence in language and species richness but not threat in the world's top linguistic hotspot.

PubMed

Turvey, Samuel T; Pettorelli, Nathalie

2014-12-07

Languages share key evolutionary properties with biological species, and global-level spatial congruence in richness and threat is documented between languages and several taxonomic groups. However, there is little understanding of the functional connection between diversification or extinction in languages and species, or the relationship between linguistic and species richness across different spatial scales. New Guinea is the world's most linguistically rich region and contains extremely high biological diversity. We demonstrate significant positive relationships between language and mammal richness in New Guinea across multiple spatial scales, revealing a likely functional relationship over scales at which infra-island diversification may occur. However, correlations are driven by spatial congruence between low levels of language and species richness. Regional biocultural richness may have showed closer congruence before New Guinea's linguistic landscape was altered by Holocene demographic events. In contrast to global studies, we demonstrate a significant negative correlation across New Guinea between areas with high levels of threatened languages and threatened mammals, indicating that landscape-scale threats differ between these groups. Spatial resource prioritization to conserve biodiversity may not benefit threatened languages, and conservation policy must adopt a multi-faceted approach to protect biocultural diversity as a whole.

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.

A probabilistic view of chaparral and forest fire regimes in southern California and northern Baja California

Treesearch

Richard A. Minnich; Ernesto Franco-Vizcaíno

2009-01-01

Fire suppression in industrialized countries encourages massive smoke emissions from high-intensity fires as a result of two inextricably related processes under current suppression policies: the nonrandom occurrence of vegetation fires in extreme weather states and the anomalous accumulation of spatially homogenous fuels. We propose as an organizing idea that the...

Modeling and evaluation of a high-resolution CMOS detector for cone-beam CT of the extremities.

PubMed

Cao, Qian; Sisniega, Alejandro; Brehler, Michael; Stayman, J Webster; Yorkston, John; Siewerdsen, Jeffrey H; Zbijewski, Wojciech

2018-01-01

Quantitative assessment of trabecular bone microarchitecture in extremity cone-beam CT (CBCT) would benefit from the high spatial resolution, low electronic noise, and fast scan time provided by complementary metal-oxide semiconductor (CMOS) x-ray detectors. We investigate the performance of CMOS sensors in extremity CBCT, in particular with respect to potential advantages of thin (<0.7 mm) scintillators offering higher spatial resolution. A cascaded systems model of a CMOS x-ray detector incorporating the effects of CsI:Tl scintillator thickness was developed. Simulation studies were performed using nominal extremity CBCT acquisition protocols (90 kVp, 0.126 mAs/projection). A range of scintillator thickness (0.35-0.75 mm), pixel size (0.05-0.4 mm), focal spot size (0.05-0.7 mm), magnification (1.1-2.1), and dose (15-40 mGy) was considered. The detectability index was evaluated for both CMOS and a-Si:H flat-panel detector (FPD) configurations for a range of imaging tasks emphasizing spatial frequencies associated with feature size aobj. Experimental validation was performed on a CBCT test bench in the geometry of a compact orthopedic CBCT system (SAD = 43.1 cm, SDD = 56.0 cm, matching that of the Carestream OnSight 3D system). The test-bench studies involved a 0.3 mm focal spot x-ray source and two CMOS detectors (Dalsa Xineos-3030HR, 0.099 mm pixel pitch) - one with the standard CsI:Tl thickness of 0.7 mm (C700) and one with a custom 0.4 mm thick scintillator (C400). Measurements of modulation transfer function (MTF), detective quantum efficiency (DQE), and CBCT scans of a cadaveric knee (15 mGy) were obtained for each detector. Optimal detectability for high-frequency tasks (feature size of ~0.06 mm, consistent with the size of trabeculae) was ~4× for the C700 CMOS detector compared to the a-Si:H FPD at nominal system geometry of extremity CBCT. This is due to ~5× lower electronic noise of a CMOS sensor, which enables input quantum-limited imaging at smaller pixel size. Optimal pixel size for high-frequency tasks was <0.1 mm for a CMOS, compared to ~0.14 mm for an a-Si:H FPD. For this fine pixel pitch, detectability of fine features could be improved by using a thinner scintillator to reduce light spread blur. A 22% increase in detectability of 0.06 mm features was found for the C400 configuration compared to C700. An improvement in the frequency at 50% modulation (f 50 ) of MTF was measured, increasing from 1.8 lp/mm for C700 to 2.5 lp/mm for C400. The C400 configuration also achieved equivalent or better DQE as C700 for frequencies above ~2 mm -1 . Images of cadaver specimens confirmed improved visualization of trabeculae with the C400 sensor. The small pixel size of CMOS detectors yields improved performance in high-resolution extremity CBCT compared to a-Si:H FPDs, particularly when coupled with a custom 0.4 mm thick scintillator. The results indicate that adoption of a CMOS detector in extremity CBCT can benefit applications in quantitative imaging of trabecular microstructure in humans. © 2017 American Association of Physicists in Medicine.

Predictive Modeling of Risk Associated with Temperature Extremes over Continental US

NASA Astrophysics Data System (ADS)

Kravtsov, S.; Roebber, P.; Brazauskas, V.

2016-12-01

We build an extremely statistically accurate, essentially bias-free empirical emulator of atmospheric surface temperature and apply it for meteorological risk assessment over the domain of continental US. The resulting prediction scheme achieves an order-of-magnitude or larger gain of numerical efficiency compared with the schemes based on high-resolution dynamical atmospheric models, leading to unprecedented accuracy of the estimated risk distributions. The empirical model construction methodology is based on our earlier work, but is further modified to account for the influence of large-scale, global climate change on regional US weather and climate. The resulting estimates of the time-dependent, spatially extended probability of temperature extremes over the simulation period can be used as a risk management tool by insurance companies and regulatory governmental agencies.

Response of shoal grass, Halodule wrightii, to extreme winter conditions in the Lower Laguna Madre, Texas

USGS Publications Warehouse

Hicks, D.W.; Onuf, C.P.; Tunnell, J.W.

1998-01-01

Effects of a severe freeze on the shoal grass, Halodule wrightii, were documented through analysis of temporal and spatial trends in below-ground biomass. The coincidence of the second lowest temperature (-10.6??C) in 107 years of record, 56 consecutive hours below freezing, high winds and extremely low water levels exposed the Laguna Madre, TX, to the most severe cold stress in over a century. H. wrightii tolerated this extreme freeze event. Annual pre- and post-freeze surveys indicated that below-ground biomass estimated from volume was Unaffected by the freeze event. Nor was there any post-freeze change in biomass among intertidal sites directly exposed to freezing air temperatures relative to subtidal sites which remained submerged during the freezing period.

Recent Development in the CESE Method for the Solution of the Navier-Stokes Equations Using Unstructured Triangular or Tetrahedral Meshes With High Aspect Ratio

NASA Technical Reports Server (NTRS)

Chang, Sin-Chung; Chang, Chau-Lyan; Yen, Joseph C.

2013-01-01

In the multidimensional CESE development, triangles and tetrahedra turn out to be the most natural building blocks for 2D and 3D spatial meshes. As such the CESE method is compatible with the simplest unstructured meshes and thus can be easily applied to solve problems with complex geometries. However, because the method uses space-time staggered stencils, solution decoupling may become a real nuisance in applications involving unstructured meshes. In this paper we will describe a simple and general remedy which, according to numerical experiments, has removed any possibility of solution decoupling. Moreover, in a real-world viscous flow simulation near a solid wall, one often encounters a case where a boundary with high curvature or sharp corner is surrounded by triangular/tetrahedral meshes of extremely high aspect ratio (up to 106). For such an extreme case, the spatial projection of a space-time compounded conservation element constructed using the original CESE design may become highly concave and thus its centroid (referred to as a spatial solution point) may lie far outside of the spatial projection. It could even be embedded beyond a solid wall boundary and causes serious numerical difficulties. In this paper we will also present a new procedure for constructing conservation elements and solution elements which effectively overcomes the difficulties associated with the original design. Another difficulty issue which was addressed more recently is the wellknown fact that accuracy of gradient computations involving triangular/tetrahedral grids deteriorates rapidly as the aspect ratio of grid cells increases. The root cause of this difficulty was clearly identified and several remedies to overcome it were found through a rigorous mathematical analysis. However, because of the length of the current paper and the complexity of mathematics involved, this new work will be presented in another paper.

Spatial Scaling of Global Rainfall and Flood Extremes

NASA Astrophysics Data System (ADS)

Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

2014-05-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

Regional frequency analysis of extreme rainfall for the Baltimore Metropolitan region based on stochastic storm transposition

NASA Astrophysics Data System (ADS)

Zhou, Z.; Smith, J. A.; Yang, L.; Baeck, M. L.; Wright, D.; Liu, S.

2017-12-01

Regional frequency analyses of extreme rainfall are critical for development of engineering hydrometeorology procedures. In conventional approaches, the assumptions that `design storms' have specified time profiles and are uniform in space are commonly applied but often not appropriate, especially over regions with heterogeneous environments (due to topography, water-land boundaries and land surface properties). In this study, we present regional frequency analyses of extreme rainfall for Baltimore study region combining storm catalogs of rainfall fields derived from weather radar and stochastic storm transposition (SST, developed by Wright et al., 2013). The study region is Dead Run, a small (14.3 km2) urban watershed, in the Baltimore Metropolitan region. Our analyses build on previous empirical and modeling studies showing pronounced spatial heterogeneities in rainfall due to the complex terrain, including the Chesapeake Bay to the east, mountainous terrain to the west and urbanization in this region. We expand the original SST approach by applying a multiplier field that accounts for spatial heterogeneities in extreme rainfall. We also characterize the spatial heterogeneities of extreme rainfall distribution through analyses of rainfall fields in the storm catalogs. We examine the characteristics of regional extreme rainfall and derive intensity-duration-frequency (IDF) curves using the SST approach for heterogeneous regions. Our results highlight the significant heterogeneity of extreme rainfall in this region. Estimates of IDF show the advantages of SST in capturing the space-time structure of extreme rainfall. We also illustrate application of SST analyses for flood frequency analyses using a distributed hydrological model. Reference: Wright, D. B., J. A. Smith, G. Villarini, and M. L. Baeck (2013), Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition, J. Hydrol., 488, 150-165.

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

Towards a unified study of extreme events using universality concepts and transdisciplinary analysis methods

NASA Astrophysics Data System (ADS)

Balasis, George; Donner, Reik V.; Donges, Jonathan F.; Radebach, Alexander; Eftaxias, Konstantinos; Kurths, Jürgen

2013-04-01

The dynamics of many complex systems is characterized by the same universal principles. In particular, systems which are otherwise quite different in nature show striking similarities in their behavior near tipping points (bifurcations, phase transitions, sudden regime shifts) and associated extreme events. Such critical phenomena are frequently found in diverse fields such as climate, seismology, or financial markets. Notably, the observed similarities include a high degree of organization, persistent behavior, and accelerated energy release, which are common to (among others) phenomena related to geomagnetic variability of the terrestrial magnetosphere (intense magnetic storms), seismic activity (electromagnetic emissions prior to earthquakes), solar-terrestrial physics (solar flares), neurophysiology (epileptic seizures), and socioeconomic systems (stock market crashes). It is an open question whether the spatial and temporal complexity associated with extreme events arises from the system's structural organization (geometry) or from the chaotic behavior inherent to the nonlinear equations governing the dynamics of these phenomena. On the one hand, the presence of scaling laws associated with earthquakes and geomagnetic disturbances suggests understanding these events as generalized phase transitions similar to nucleation and critical phenomena in thermal and magnetic systems. On the other hand, because of the structural organization of the systems (e.g., as complex networks) the associated spatial geometry and/or topology of interactions plays a fundamental role in the emergence of extreme events. Here, a few aspects of the interplay between geometry and dynamics (critical phase transitions) that could result in the emergence of extreme events, which is an open problem, will be discussed.

Comparison of Extreme Precipitation Return Levels using Spatial Bayesian Hierarchical Modeling versus Regional Frequency Analysis

NASA Astrophysics Data System (ADS)

Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

2017-12-01

We compare gridded extreme precipitation return levels obtained using spatial Bayesian hierarchical modeling (BHM) with their respective counterparts from a traditional regional frequency analysis (RFA) using the same set of extreme precipitation data. Our study area is the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two ­thirds of Oregon's population and 20 of the 25 most populous cities in the state. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams and extreme precipitation estimates are required to support risk­ informed hydrologic analyses as part of the USACE Dam Safety Program. Our intent is to profile for the USACE an alternate methodology to an RFA that was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. We analyze 24-hour annual precipitation maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme precipitation by return level. Our BHM modeling analysis involved application of leave-one-out cross validation (LOO-CV), which not only supported model selection but also a comprehensive assessment of location specific model performance. The LOO-CV results will provide a basis for the BHM RFA comparison.

Modeling the Spatial and Temporal Variation of Monthly and Seasonal Precipitation on the Nevada Test Site and Vicinity, 1960-2006

USGS Publications Warehouse

Blainey, Joan B.; Webb, Robert H.; Magirl, Christopher S.

2007-01-01

The Nevada Test Site (NTS), located in the climatic transition zone between the Mojave and Great Basin Deserts, has a network of precipitation gages that is unusually dense for this region. This network measures monthly and seasonal variation in a landscape with diverse topography. Precipitation data from 125 climate stations on or near the NTS were used to spatially interpolate precipitation for each month during the period of 1960 through 2006 at high spatial resolution (30 m). The data were collected at climate stations using manual and/or automated techniques. The spatial interpolation method, applied to monthly accumulations of precipitation, is based on a distance-weighted multivariate regression between the amount of precipitation and the station location and elevation. This report summarizes the temporal and spatial characteristics of the available precipitation records for the period 1960 to 2006, examines the temporal and spatial variability of precipitation during the period of record, and discusses some extremes in seasonal precipitation on the NTS.

A Radar Climatology for Germany - a 16-year high resolution precipitation data and its possibilities

NASA Astrophysics Data System (ADS)

Walawender, Ewelina; Winterrath, Tanja; Brendel, Christoph; Hafer, Mario; Junghänel, Thomas; Klameth, Anna; Weigl, Elmar; Becker, Andreas

2017-04-01

One of the main features of heavy precipitation events is their small-scale distribution. Despite a local occurrence, these intensive rainfalls may, however, cause most serious damage and have significant impact on the whole river basin area resulting in e.g. flash floods or urban flooding. Thus, it is of great importance not only to detect the life-cycle of extreme precipitation during its occurrence but also to collect precise climatological information on such events. The German weather service (Deutscher Wetterdienst) operates a very dense network of more than 2000 weather stations collecting data on precipitation. It is however not sufficient for detecting spatially limited phenomena. Thanks to radar data, current monitoring of such events is possible. A quality control process is applied to real-time radar products, however only automatic rain gauges data can be used in the adjustment procedure. To merge both radar data and all available rain gauges data, the radar climatology dataset was established. Within the framework of a project financed by the federal agencies' strategic alliance 'Adaptation to Climate Change', 16 years (2001-2016) of radar data have been reanalyzed in order to gain a homogenous, quality-controlled, high-resolution precipitation data set suitable for analyzing extreme events in a climatological approach. Additional corrections methods (e.g. clutter, spokes and beam height correction) were defined and used for the reprocessing procedure to enhance the data quality. Although the time series is still rather short for a climatology, for the first time the data set allows an insight into e.g. the distribution, size, life cycle, and duration of extreme events that cannot be measured by point measurements alone. All radar climatology products share the same spatial and temporal coverage. The whole dataset has been produced for the area of Germany. With the relatively high spatial resolution of 1km, the data can be used as a component of wide range of spatial analyses: from country to city scale. Multiple events can be investigated in details, depending on the user needs, as temporal resolution differs from 15 years to 1 hour. Apart from standard products such as precipitation sum, the radar climatology will provide its derivatives as well e.g. extreme precipitation characteristics and rain erosivity potential (R factor) map. Employing GIS functionalities into the Radar Climatology dataset has made it universal and interoperable - suitable for integration with a wide range of other geodata formats or services. It can be treated also as input layer for further analyses which demand spatially continuous data on precipitation and for building more integrated products tailored to the user needs. One of the most important concepts may be an application of the Radar Climatology data as a key factor in risk assessment analysis and developing strategies for risk management in urban planning, hydrology, agriculture etc.

Socioeconomic indicators of heat-related health risk supplemented with remotely sensed data

PubMed Central

Johnson, Daniel P; Wilson, Jeffrey S; Luber, George C

2009-01-01

Background Extreme heat events are the number one cause of weather-related fatalities in the United States. The current system of alert for extreme heat events does not take into account intra-urban spatial variation in risk. The purpose of this study is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature derived from thermal remote sensing data. Results Comparison of logistic regression models indicates that supplementing known sociodemographic risk factors with remote sensing estimates of land surface temperature improves the delineation of intra-urban variations in risk from extreme heat events. Conclusion Thermal remote sensing data can be utilized to improve understanding of intra-urban variations in risk from extreme heat. The refinement of current risk assessment systems could increase the likelihood of survival during extreme heat events and assist emergency personnel in the delivery of vital resources during such disasters. PMID:19835578

Modulation of Kekulé adatom ordering due to strain in graphene

NASA Astrophysics Data System (ADS)

González-Árraga, L.; Guinea, F.; San-Jose, P.

2018-04-01

Intervalley scattering of carriers in graphene at "top" adatoms may give rise to a hidden Kekulé ordering pattern in the adatom positions. This ordering is the result of a rapid modulation in the electron-mediated interaction between adatoms at the wave vector K -K' , which has been shown experimentally and theoretically to dominate their spatial distribution. Here we show that the adatom interaction is extremely sensitive to strain in the supporting graphene, which leads to a characteristic spatial modulation of the Kekulé order as a function of adatom distance. Our results suggest that the spatial distributions of adatoms could provide a way to measure the type and magnitude of strain in graphene and the associated pseudogauge field with high accuracy.

Evolution of precipitation extremes in two large ensembles of climate simulations

NASA Astrophysics Data System (ADS)

Martel, Jean-Luc; Mailhot, Alain; Talbot, Guillaume; Brissette, François; Ludwig, Ralf; Frigon, Anne; Leduc, Martin; Turcotte, Richard

2017-04-01

Recent studies project significant changes in the future distribution of precipitation extremes due to global warming. It is likely that extreme precipitation intensity will increase in a future climate and that extreme events will be more frequent. In this work, annual maxima daily precipitation series from the Canadian Earth System Model (CanESM2) 50-member large ensemble (spatial resolution of 2.8°x2.8°) and the Community Earth System Model (CESM1) 40-member large ensemble (spatial resolution of 1°x1°) are used to investigate extreme precipitation over the historical (1980-2010) and future (2070-2100) periods. The use of these ensembles results in respectively 1 500 (30 years x 50 members) and 1200 (30 years x 40 members) simulated years over both the historical and future periods. These large datasets allow the computation of empirical daily extreme precipitation quantiles for large return periods. Using the CanESM2 and CESM1 large ensembles, extreme daily precipitation with return periods ranging from 2 to 100 years are computed in historical and future periods to assess the impact of climate change. Results indicate that daily precipitation extremes generally increase in the future over most land grid points and that these increases will also impact the 100-year extreme daily precipitation. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety. Estimated increases in precipitation associated to very extreme precipitation events (e.g. 100 years) will drastically change the likelihood of flooding and their extent in future climate. These results, although interesting, need to be extended to sub-daily durations, relevant for urban flooding protection and urban infrastructure design (e.g. sewer networks, culverts). Models and simulations at finer spatial and temporal resolution are therefore needed.

Trends in 1970-2010 southern California surface maximum temperatures: extremes and heat waves

NASA Astrophysics Data System (ADS)

Ghebreegziabher, Amanuel T.

Daily maximum temperatures from 1970-2010 were obtained from the National Climatic Data Center (NCDC) for 28 South Coast Air Basin (SoCAB) Cooperative Network (COOP) sites. Analyses were carried out on the entire data set, as well as on the 1970-1974 and 2006-2010 sub-periods, including construction of spatial distributions and time-series trends of both summer-average and annual-maximum values and of the frequency of two and four consecutive "daytime" heat wave events. Spatial patterns of average and extreme values showed three areas consistent with climatological SoCAB flow patterns: cold coastal, warm inland low-elevation, and cool further-inland mountain top. Difference (2006-2010 minus 1970-1974) distributions of both average and extreme-value trends were consistent with the shorter period (1970-2005) study of previous study, as they showed the expected inland regional warming and a "reverse-reaction" cooling in low elevation coastal and inland areas open to increasing sea breeze flows. Annual-extreme trends generally showed cooling at sites below 600 m and warming at higher elevations. As the warming trends of the extremes were larger than those of the averages, regional warming thus impacts extremes more than averages. Spatial distributions of hot-day frequencies showed expected maximum at inland low-elevation sites. Regional warming again thus induced increases at both elevated-coastal areas, but low-elevation areas showed reverse-reaction decreases.

Temporal and Spatial Variations of Drought in China: Reconstructed from Historical Memorials Archives during 1689-1911

PubMed Central

Wan, Jinhong; Yan, Denghua; Fu, Guobin; Hao, Lu; Yue, Yaojie; Li, Ruoxi; Li, Yunpeng; Liu, Jiangang; Deng, Jun

2016-01-01

In China, Zou Zhe (Memorials to the Throne, or Palace Memorials), an official communication to the emperors of China by local officials, offers an opportunity to reconstruct the spatial-temporal distributions of droughts at a high-resolution. A 223-year, 1689–1911, time series of drought events was reconstructed in this study based on 2494 pieces of Zou Zhe. The results show that: 1) on the temporal scale, the drought affected areas, i.e., number of affected counties, showed three peak periods during the last 223 years and nine extreme drought years with more than 300 counties affected have been identified; 2) on the spatial scale, there existed three drought-prone areas in China, i.e., Gansu province and Ningxia Hui Autonomous Region in Northwest China, Shandong, Hebei, and Henan provinces and Tianjin in the North China, and Anhui and Jiangsu provinces in Jianghuai area, respectively; 3) the drought-prone areas have been expanding from North China to South China since the second half of 19th century; 4) on the seasonal scale, summer witnessed the largest number of drought events. Meanwhile, the uncertainties of the results were also discussed, i.e. what caused the spatial-temporal distribution of drought. The results of this study can be used to mitigate the adverse effects of extreme weather events on food increasing and stable production. PMID:26836807

Temporal and Spatial Variations of Drought in China: Reconstructed from Historical Memorials Archives during 1689-1911.

PubMed

Wan, Jinhong; Yan, Denghua; Fu, Guobin; Hao, Lu; Yue, Yaojie; Li, Ruoxi; Li, Yunpeng; Liu, Jiangang; Deng, Jun

2016-01-01

In China, Zou Zhe (Memorials to the Throne, or Palace Memorials), an official communication to the emperors of China by local officials, offers an opportunity to reconstruct the spatial-temporal distributions of droughts at a high-resolution. A 223-year, 1689-1911, time series of drought events was reconstructed in this study based on 2494 pieces of Zou Zhe. The results show that: 1) on the temporal scale, the drought affected areas, i.e., number of affected counties, showed three peak periods during the last 223 years and nine extreme drought years with more than 300 counties affected have been identified; 2) on the spatial scale, there existed three drought-prone areas in China, i.e., Gansu province and Ningxia Hui Autonomous Region in Northwest China, Shandong, Hebei, and Henan provinces and Tianjin in the North China, and Anhui and Jiangsu provinces in Jianghuai area, respectively; 3) the drought-prone areas have been expanding from North China to South China since the second half of 19th century; 4) on the seasonal scale, summer witnessed the largest number of drought events. Meanwhile, the uncertainties of the results were also discussed, i.e. what caused the spatial-temporal distribution of drought. The results of this study can be used to mitigate the adverse effects of extreme weather events on food increasing and stable production.

Spatial scaling of bacterial community diversity at shallow hydrothermal vents: a global comparison

NASA Astrophysics Data System (ADS)

Pop Ristova, P.; Hassenrueck, C.; Molari, M.; Fink, A.; Bühring, S. I.

2016-02-01

Marine shallow hydrothermal vents are extreme environments, often characterized by discharge of fluids with e.g. high temperatures, low pH, and laden with elements toxic to higher organisms. They occur at continental margins around the world's oceans, but represent fragmented, isolated habitats of locally small areal coverage. Microorganisms contribute the main biomass at shallow hydrothermal vent ecosystems and build the basis of the food chain by autotrophic fixation of carbon both via chemosynthesis and photosynthesis, occurring simultaneously. Despite their importance and unique capacity to adapt to these extreme environments, little is known about the spatial scales on which the alpha- and beta-diversity of microbial communities vary at shallow vents, and how the geochemical habitat heterogeneity influences shallow vent biodiversity. Here for the first time we investigated the spatial scaling of microbial biodiversity patterns and their interconnectivity at geochemically diverse shallow vents on a global scale. This study presents data on the comparison of bacterial community structures on large (> 1000 km) and small (0.1 - 100 m) spatial scales as derived from ARISA and Illumina sequencing. Despite the fragmented global distribution of shallow hydrothermal vents, similarity of vent bacterial communities decreased with geographic distance, confirming the ubiquity of distance-decay relationship. Moreover, at all investigated vents, pH was the main factor locally structuring these communities, while temperature influenced both the alpha- and beta-diversity.

High-resolution, time-resolved MRA provides superior definition of lower-extremity arterial segments compared to 2D time-of-flight imaging.

PubMed

Thornton, F J; Du, J; Suleiman, S A; Dieter, R; Tefera, G; Pillai, K R; Korosec, F R; Mistretta, C A; Grist, T M

2006-08-01

To evaluate a novel time-resolved contrast-enhanced (CE) projection reconstruction (PR) magnetic resonance angiography (MRA) method for identifying potential bypass graft target vessels in patients with Class II-IV peripheral vascular disease. Twenty patients (M:F = 15:5, mean age = 58 years, range = 48-83 years), were recruited from routine MRA referrals. All imaging was performed on a 1.5 T MRI system with fast gradients (Signa LX; GE Healthcare, Waukesha, WI). Images were acquired with a novel technique that combined undersampled PR with a time-resolved acquisition to yield an MRA method with high temporal and spatial resolution. The method is called PR hyper time-resolved imaging of contrast kinetics (PR-hyperTRICKS). Quantitative and qualitative analyses were used to compare two-dimensional (2D) time-of-flight (TOF) and PR-hyperTRICKS in 13 arterial segments per lower extremity. Statistical analysis was performed with the Wilcoxon signed-rank test. Fifteen percent (77/517) of the vessels were scored as missing or nondiagnostic with 2D TOF, but were scored as diagnostic with PR-hyperTRICKS. Image quality was superior with PR-hyperTRICKS vs. 2D TOF (on a four-point scale, mean rank = 3.3 +/- 1.2 vs. 2.9 +/- 1.2, P < 0.0001). PR-hyperTRICKS produced images with high contrast-to-noise ratios (CNR) and high spatial and temporal resolution. 2D TOF images were of inferior quality due to moderate spatial resolution, inferior CNR, greater flow-related artifacts, and absence of temporal resolution. PR-hyperTRICKS provides superior preoperative assessment of lower limb ischemia compared to 2D TOF.

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

NASA Astrophysics Data System (ADS)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area.

PubMed

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-07-06

We implemented a spatial model for analysing PM 10 maxima across the Mexico City metropolitan area during the period 1995-2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM 10 maxima in space and time. We evaluated the statistical model's performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM 10 maxima and the longitude and latitude. The relationship between time and the PM 10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM 10 maxima presenting levels above 1000 μ g/m 3 (return period: 25 yr) was observed in the northwestern region of the study area.

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area

PubMed Central

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-01-01

We implemented a spatial model for analysing PM10 maxima across the Mexico City metropolitan area during the period 1995–2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM10 maxima in space and time. We evaluated the statistical model’s performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM10 maxima and the longitude and latitude. The relationship between time and the PM10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM10 maxima presenting levels above 1000 μg/m3 (return period: 25 yr) was observed in the northwestern region of the study area. PMID:28684720

Repair of localized defects in multilayer-coated reticle blanks for extreme ultraviolet lithography

DOEpatents

Stearns, Daniel G [Los Altos, CA; Sweeney, Donald W [San Ramon, CA; Mirkarimi, Paul B [Sunol, CA

2004-11-23

A method is provided for repairing defects in a multilayer coating layered onto a reticle blank used in an extreme ultraviolet lithography (EUVL) system. Using high lateral spatial resolution, energy is deposited in the multilayer coating in the vicinity of the defect. This can be accomplished using a focused electron beam, focused ion beam or a focused electromagnetic radiation. The absorbed energy will cause a structural modification of the film, producing a localized change in the film thickness. The change in film thickness can be controlled with sub-nanometer accuracy by adjusting the energy dose. The lateral spatial resolution of the thickness modification is controlled by the localization of the energy deposition. The film thickness is adjusted locally to correct the perturbation of the reflected field. For example, when the structural modification is a localized film contraction, the repair of a defect consists of flattening a mound or spreading out the sides of a depression.

Spatial distribution of precipitation extremes in Norway

NASA Astrophysics Data System (ADS)

Verpe Dyrrdal, Anita; Skaugen, Thomas; Lenkoski, Alex; Thorarinsdottir, Thordis; Stordal, Frode; Førland, Eirik J.

2015-04-01

Estimates of extreme precipitation, in terms of return levels, are crucial in planning and design of important infrastructure. Through two separate studies, we have examined the levels and spatial distribution of daily extreme precipitation over catchments in Norway, and hourly extreme precipitation in a point. The analyses were carried out through the development of two new methods for estimating extreme precipitation in Norway. For daily precipitation we fit the Generalized Extreme Value (GEV) distribution to areal time series from a gridded dataset, consisting of daily precipitation during the period 1957-today with a resolution of 1x1 km². This grid-based method is more objective and less manual and time-consuming compared to the existing method at MET Norway. In addition, estimates in ungauged catchments are easier to obtain, and the GEV approach includes a measure of uncertainty, which is a requirement in climate studies today. Further, we go into depth on the debated GEV shape parameter, which plays an important role for longer return periods. We show that it varies according to dominating precipitation types, having positive values in the southeast and negative values in the southwest. We also find indications that the degree of orographic enhancement might affect the shape parameter. For hourly precipitation, we estimate return levels on a 1x1 km² grid, by linking GEV distributions with latent Gaussian fields in a Bayesian hierarchical model (BHM). Generalized linear models on the GEV parameters, estimated from observations, are able to incorporate location-specific geographic and meteorological information and thereby accommodate these effects on extreme precipitation. Gaussian fields capture additional unexplained spatial heterogeneity and overcome the sparse grid on which observations are collected, while a Bayesian model averaging component directly assesses model uncertainty. We find that mean summer precipitation, mean summer temperature, latitude, longitude, mean annual precipitation and elevation are good covariate candidates for hourly precipitation in our model. Summer indices succeed because hourly precipitation extremes often occur during the convective season. The spatial distribution of hourly and daily precipitation differs in Norway. Daily precipitation extremes are larger along the southwestern coast, where large-scale frontal systems dominate during fall season and the mountain ridge generates strong orographic enhancement. The largest hourly precipitation extremes are mostly produced by intense convective showers during summer, and are thus found along the entire southern coast, including the Oslo-region.

Spatial analysis of extreme precipitation deficit as an index for atmospheric drought in Belgium

NASA Astrophysics Data System (ADS)

Zamani, Sepideh; Van De Vyver, Hans; Gobin, Anne

2014-05-01

The growing concern among the climate scientists is that the frequency of weather extremes will increase as a result of climate change. European society, for example, is particularly vulnerable to changes in the frequency and intensity of extreme events such as heat waves, heavy precipitation, droughts, and wind storms, as seen in recent years [1,2]. A more than 50% of the land is occupied by managed ecosystem (agriculture, forestry) in Belgium. Moreover, among the many extreme weather conditions, drought counts to have a substantial impact on the agriculture and ecosystem of the affected region, because its most immediate consequence is a fall in crop production. Besides the technological advances, a reliable estimation of weather conditions plays a crucial role in improving the agricultural productivity. The above mentioned reasons provide a strong motivation for a research on the drought and its impacts on the economical and agricultural aspects in Belgium. The main purpose of the presented work is to map atmospheric drought Return-Levels (RL), as first insight for agricultural drought, employing spatial modelling approaches. The likelihood of future drought is studied on the basis of precipitation deficit indices for four vegetation types: water (W), grass (G), deciduous (D) and coniferous forests (C) is considered. Extreme Value Theory (EVT) [3,4,5] as a branch of probability and statistics, is dedicated to characterize the behaviour of extreme observations. The tail behaviour of the EVT distributions provide important features about return levels. EVT distributions are applicable in many study areas such as: hydrology, environmental research and meteorology, insurance and finance. Spatial Generalized Extreme Value (GEV) distributions, as a branch of EVT, are applied to annual maxima of drought at 13 hydro-meteorological stations across Belgium. Superiority of the spatial GEV model is that a region can be modelled merging the individual time series of observations from isolated sites and using a common regression model based on climatological/geographical covariates. The behaviour of the fitted spatial GEV-distribution is heavy-tailed with γ ≡ 0.3 over Belgium. A comparison between the RL-maps using GEV model and the ones obtained from Universal Kriging (UK) confirms the reliability of the spatial GEV model in explaining atmospheric drought in Belgium. References [1] Beniston, M., Stephenson, D. B., Christensen, O. B., Ferro, C. A. T., Frei, C., Goyette, S., Halsnaes, K., Holt, T., Jylhü, K., Koffi, B., Palutikoff, J., Schöll, R., Semmler, T., and Woth, K. (2007), Future extreme events in European climate; an exploration of Regional Climate Model projections. Climatic Change, 81, 71-95. [2] Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (Eds.)] (2007), king Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp. [3] Coles, S. (2001), An Introduction to Statistical Modeling of Extreme Values, Springer-Verlag Heidelberg, Germany. [4] Embrechts, P., C. Klüppelberg, and T. Mikosch (1997), Modelling Extremal Events for Insurance and Finance, Springer-Verlag, Berlin. [5] Smith, R., (2004), Statistics of extremes, with application in environment, insurance and finance, in : Extreme Values in Finance, Telecommunications and the Environment, edited by: Finkenstadt, B. and Rootzen, H., 373-388, Chapman and Hall CRC Press, London.

The phase-contrast imaging instrument at the matter in extreme conditions endstation at LCLS

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

Nagler, Bob; Schropp, Andreas; Galtier, Eric C.

2016-10-07

Here, we describe the phase-contrast imaging instrument at the Matter in Extreme Conditions (MEC) endstation of the Linac Coherent Light Source. The instrument can image phenomena with a spatial resolution of a few hundreds of nanometers and at the same time reveal the atomic structure through X-ray diffraction, with a temporal resolution better than 100 fs. It was specifically designed for studies relevant to high-energy-density science and can monitor, e.g., shock fronts, phase transitions, or void collapses. This versatile instrument was commissioned last year and is now available to the MEC user community.

TRMM- and GPM-based precipitation analysis and modelling in the Tropical Andes

NASA Astrophysics Data System (ADS)

Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Onof, Christian

2016-04-01

Despite wide-spread applications of satellite-based precipitation products (SPPs) throughout the TRMM-era, the scarcity of ground-based in-situ data (high density gauge networks, rainfall radar) in many hydro-meteorologically important regions, such as tropical mountain environments, has limited our ability to evaluate both SPPs and individual satellite-based sensors as well as accurately model or merge rainfall at high spatial resolutions, particularly with respect to extremes. This has restricted both the understanding of sensor behaviour and performance controls in such regions as well as the accuracy of precipitation estimates and respective hydrological applications ranging from water resources management to early warning systems. Here we report on our recent research into precipitation analysis and modelling using various TRMM and GPM products (2A25, 3B42 and IMERG) in the tropical Andes. In an initial study, 78 high-frequency (10-min) recording gauges in Colombia and Ecuador are used to generate a ground-based validation dataset for evaluation of instantaneous TRMM Precipitation Radar (TPR) overpasses from the 2A25 product. Detection ability, precipitation time-series, empirical distributions and statistical moments are evaluated with respect to regional climatological differences, seasonal behaviour, rainfall types and detection thresholds. Results confirmed previous findings from extra-tropical regions of over-estimation of low rainfall intensities and under-estimation of the highest 10% of rainfall intensities by the TPR. However, in spite of evident regionalised performance differences as a function of local climatological regimes, the TPR provides an accurate estimate of climatological annual and seasonal rainfall means. On this basis, high-resolution (5 km) climatological maps are derived for the entire tropical Andes. The second objective of this work is to improve the local precipitation estimation accuracy and representation of spatial patterns of extreme rainfall probabilities over the region. For this purpose, an ensemble of high-resolution rainfall fields is generated by stochastic simulation using space-time averaged, coarse-scale (daily, 0.25°) satellite-based rainfall inputs (TRMM 3B42/ -RT) and the high-resolution climatological information derived from the TPR as spatial disaggregation proxies. For evaluation and merging, gridded ground-based rainfall fields are generated from gauge data using sequential simulation. Satellite and ground-based ensembles are subsequently merged using an inverse error weighting scheme. The model was tested over a case study in the Colombian Andes with optional coarse-scale bias correction prior to disaggregation and merging. The resulting outputs were assessed in the context of Generalized Extreme Value theory and showed improved estimation of extreme rainfall probabilities compared to the original TMPA inputs. Initial findings using GPM-IMERG inputs are also presented.

Identification of an Extremely 180-Rich Presolar Silicate Grain in Acfer 094

NASA Technical Reports Server (NTRS)

Nguyen, A. N.; Messenger, S.

2009-01-01

Presolar silicate grains have been abundantly identified since their first discovery less than a decade ago [1,2,3]. The O isotopic compositions of both silicate and oxide stardust indicate the vast majority (>90%) condensed around Orich asymptotic giant branch (AGB) stars. Though both presolar phases have average sizes of 300 nm, grains larger than 1 m are extremely uncommon for presolar silicates. Thus, while numerous isotopic systems have been measured in presolar oxide grains [4], very few isotopic analyses for presolar silicates exist outside of O and Si [2,5]. And still, these measurements suffer from isotopic dilution with surrounding matrix material [6]. We conduct a search for presolar silicates in the primitive carbonaceous chondrite Acfer 094 and in some cases obtain high spatial resolution, high precision isotopic ratios.

Towards prediction of heatwaves based on the complementary relationship between actual and potential evaporation - energy partitioning and hydrologic attributes

NASA Astrophysics Data System (ADS)

Or, D.; Aminzadeh, M.; Roderick, M. L.

2017-12-01

Prediction of extreme climate events such as heatwaves that are characterized by prolonged periods of high air temperatures (accompanied by low precipitation and high radiation) provides an opportunity to potentially mitigate the associated environmental, social and economic impacts. Vegetation may respond to these extreme conditions by reducing evaporative flux either due to soil water depletion or inability to meet the atmospheric evaporative demand (high canopy resistance). We implement a newly generalized Complementary Relationship (CR) for spatially heterogeneous land surfaces to predict the actual evaporation from drying landscapes covered by different vegetation types (i.e., grassland and forest). A strong correlation between air temperature and sensible heat flux anomalies identified from FLUXNET network data suggests that abrupt changes in sensible heat flux above climatological means can serve as indicators for predicting the onset of a heatwave. We thus capitalize on the inherent coupling between evaporative and sensible heat fluxes linked to moisture availability within the CR framework to predict rapid increase in regional sensible heat flux associated with soil drying (low precipitation) or with extreme evaporative demand (high radiation) while soil moisture is not limiting. The proposed approach evaluated using FLUXNET datasets provides an energy constraint framework based on the CR concept to obtain new insights into the onset of heatwaves and climate extremes such as regional droughts.

Living on the edge: Flood risks to societies Balázs M. Fekete, Shahabeddin Afshari Tork and Charles J. Vörösmarty

NASA Astrophysics Data System (ADS)

Fekete, B. M.; Afshari Tork, S.; Vorosmarty, C. J.

2015-12-01

Characterizing hydrological extreme events and assessing their societal impacts is perpetual challenge for hydrologists. Climate models predict that anticipated temperature rise leads to an intensification of the hydrological cycle and to a corresponding increase in the reoccurrence and the severity of extreme events. The societal impact of the hydrological extremes are interlinked with anthropogenic activities therefore the damages to manmade infrastructures are rarely a good measure of the extreme events' magnitudes. Extreme events are rare by definition therefore detecting change in their distributions requires long-term observational records. Currently, only in-situ monitoring time series has the temporal extent necessary for assessing the reoccurrence probabilities of extreme events, but they frequently lack the spatial coverage. Satellite remote sensing is often advocated to provide the required spatial coverage, but satellites have to compromise between spatial and temporal resolutions. Furthermore, the retrieval algorithms are often as complex as comparable hydrological models with similar degree of uncertainties in their parameterization and the validity of the final data products. In addition, anticipated changes over time in the reoccurrence frequencies of extreme events invalidates the stationarity assumption, which is the basis for using past observations to predict the probabilities future extreme events. Probably the best approach to provide more robust predictions of extreme events is the integration of the available data (in-situ and remote sensing) in a comprehensive data assimilation frameworks built on top of adequate hydrological modeling platforms. Our presentation will provide an overview of the current state of hydrological models to support data assimilations and the viable pathways to integrate in-situ and remote sensing observations for flood predictions. We will demonstrate the use of socio-economic data in combination with hydrological data assimilation to assess the resiliency to extreme flood events.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-05-01

Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In this study, 16 simulations are conducted using WRF-Fire to examine the sensitivity of resolving VDLS to spatial resolution and atmosphere-fire coupling within the WRF-Fire model framework. The horizontal grid spacing is varied between 25 and 90 m, and the two-way atmosphere-fire coupling is either enabled or disabled. At high spatial resolution, the atmosphere-fire coupling increases the peak uphill and lateral spread rate by a factor of up to 2.7 and 9.5. The enhancement of the uphill and lateral spread rate diminishes at coarser spatial resolution, and VDLS is not modelled for a horizontal grid spacing of 90 m. The laterally spreading fire fronts become the dominant contributors of the extreme pyro-convection. The resolved fire-induced vortices responsible for driving the lateral spread in the coupled simulations have non-zero vorticity along each unit vector direction, and develop due to an interaction between the background winds and vertical return circulations generated at the flank of the fire front as part of the pyro-convective updraft. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to reproduce VDLS within the current WRF-Fire model framework.

Microchannel plate detector technology potential for LUVOIR and HabEx

NASA Astrophysics Data System (ADS)

Siegmund, O. H. W.; Ertley, C.; Vallerga, J. V.; Schindhelm, E. R.; Harwit, A.; Fleming, B. T.; France, K. C.; Green, J. C.; McCandliss, S. R.; Harris, W. M.

2017-08-01

Microchannel plate (MCP) detectors have been the detector of choice for ultraviolet (UV) instruments onboard many NASA missions. These detectors have many advantages, including high spatial resolution (<20 μm), photon counting, radiation hardness, large formats (up to 20 cm), and ability for curved focal plane matching. Novel borosilicate glass MCPs with atomic layer deposition combine extremely low backgrounds, high strength, and tunable secondary electron yield. GaN and combinations of bialkali/alkali halide photocathodes show promise for broadband, higher quantum efficiency. Cross-strip anodes combined with compact ASIC readout electronics enable high spatial resolution over large formats with high dynamic range. The technology readiness levels of these technologies are each being advanced through research grants for laboratory testing and rocket flights. Combining these capabilities would be ideal for UV instruments onboard the Large UV/Optical/IR Surveyor (LUVOIR) and the Habitable Exoplanet Imaging Mission (HABEX) concepts currently under study for NASA's Astrophysics Decadal Survey.

Landscape changes as a factor affecting the course and consequences of extreme floods in the Otava river basin, Czech Republic.

PubMed

Langhammer, Jakub; Vilímek, Vít

2008-09-01

The paper presents the analysis of anthropogenical modifications of the landscape in relation to the course and consequences of floods. The research was conducted in the Otava river basin which represents the core zone of the extreme flood in August 2002 in Central Europe. The analysis was focused on the key indicators of landscape modification potentially affecting the runoff process - the long-term changes of land-use, changes of land cover structure, land drainage, historical shortening of the river network and the modifications of streams and floodplains. The information on intensity and spatial distribution of modifications was derived from different data sources--historical maps, available GIS data, remote sensing and field mapping. The results revealed a high level of spatial diversity of anthropogenical modifications in different parts of the river basin. The intensive modifications in most of indicators were concentrated in the lowland region of the river basin due to its agricultural use; however important changes were also recorded in the headwater region of the basin. The high spatial diversity of the modifications may result in their varying effect on the course and consequences of floods in different parts of the river basin. This effect is demonstrated by the cluster analysis based on the matrix of indicators of stream and floodplain modification, physiogeographical characteristics and geomorphological evidences of the flood in August 2002, derived from the individual thematic layers using GIS.

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 (

Simulating the Response of Urban Water Quality to Climate and Land Use Change in Partially Urbanized Basins

NASA Astrophysics Data System (ADS)

Sun, N.; Yearsley, J. R.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

Urban stream quality is particularly susceptible to extreme precipitation events and land use change. Although the projected effects of extreme events and land use change on hydrology have been resonably well studied, the impacts on urban water quality have not been widely examined due in part to the scale mismatch between global climate models and the spatial scales required to represent urban hydrology and water quality signals. Here we describe a grid-based modeling system that integrates the Distributed Hydrology Soil Vegetation Model (DHSVM) and urban water quality module adpated from EPA's Storm Water Management Model (SWMM) and Soil and water assessment tool (SWAT). Using the model system, we evaluate, for four partially urbanized catchments within the Puget Sound basin, urban water quality under current climate conditions, and projected potential changes in urban water quality associated with future changes in climate and land use. We examine in particular total suspended solids, toal nitrogen, total phosphorous, and coliform bacteria, with catchment representations at the 150-meter spatial resolution and the sub-daily timestep. We report long-term streamflow and water quality predictions in response to extreme precipitation events of varying magnitudes in the four partially urbanized catchments. Our simulations show that urban water quality is highly sensitive to both climatic and land use change.

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

Image Stability Requirements For a Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

NASA Technical Reports Server (NTRS)

Bingham, G. E.; Cantwell, G.; Robinson, R. C.; Revercomb, H. E.; Smith, W. L.

2001-01-01

A Geostationary Imaging Fourier Transform Spectrometer (GIFTS) has been selected for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. Our paper will discuss one of the key GIFTS measurement requirements, Field of View (FOV) stability, and its impact on required system performance. The GIFTS NMP mission is designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS payload is a versatile imaging FTS with programmable spectral resolution and spatial scene selection that allows radiometric accuracy and atmospheric sounding precision to be traded in near real time for area coverage. The GIFTS sensor combines high sensitivity with a massively parallel spatial data collection scheme to allow high spatial resolution measurement of the Earth's atmosphere and rapid broad area coverage. An objective of the GIFTS mission is to demonstrate the advantages of high spatial resolution (4 km ground sample distance - gsd) on temperature and water vapor retrieval by allowing sampling in broken cloud regions. This small gsd, combined with the relatively long scan time required (approximately 10 s) to collect high resolution spectra from geostationary (GEO) orbit, may require extremely good pointing control. This paper discusses the analysis of this requirement.

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Bar-Massada, A.; Radeloff, V.C.; Stewart, S.I.; Hawbaker, T.J.

2009-01-01

The rapid growth of housing in and near the wildland-urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions. ?? 2009 Elsevier B.V.

EEE - Extreme Energy Events: an astroparticle physics experiment in Italian High Schools

NASA Astrophysics Data System (ADS)

Abbrescia, M.; Avanzini, C.; Baldini, L.; Baldini Ferroli, R.; Batignani, G.; Bencivenni, G.; Bossini, E.; Bressan, E.; Chiavassa, A.; Cicalò, C.; Cifarelli, L.; Coccia, E.; Corvaglia, A.; De Gruttola, D.; De Pasquale, S.; Di Giovanni, A.; D'Incecco, M.; Dreucci, M.; Fabbri, F. L.; Fattibene, E.; Ferrarov, A.; Forster, R.; Frolov, V.; Galeotti, P.; Garbini, M.; Gemme, G.; Gnesi, I.; Grazzi, S.; Gustavino, C.; Hatzifotiadou, D.; La Rocca, P.; Maggiora, A.; Maron, G.; Mazziotta, M. N.; Miozzi, S.; Noferini, F.; Nozzoli, F.; Panareo, M.; Panetta, M. P.; Paoletti, R.; Perasso, L.; Pilo, F.; Piragino, G.; Riggi, F.; Righini, G. C.; Rodriguez Rodriguez, A.; Sartorelli, G.; Scapparone, E.; Schioppa, M.; Scribano, A.; Selvi, M.; Serci, S.; Siddi, E.; Squarcia, S.; Taiuti, M.; Terreni, G.; Vistoli, M. C.; Votano, L.; Williams, M. C. S.; Zani, S.; Zichichi, A.; Zuyeuski, R.

2016-05-01

The Extreme Energy Events project (EEE) is aimed to study Extensive Air Showers (EAS) from primary cosmic rays of more than 1018 eV energy detecting the ground secondary muon component using an array of telescopes with high spatial and time resolution. The second goal of the EEE project is to involve High School teachers and students in this advanced research work and to initiate them in scientific culture: to reach both purposes the telescopes are located inside High School buildings and the detector construction, assembling and monitoring - together with data taking and analysis - are done by researchers from scientific institutions in close collaboration with them. At present there are 42 telescopes in just as many High Schools scattered all over Italy, islands included, plus two at CERN and three in INFN units. We report here some preliminary physics results from the first two common data taking periods together with the outreach impact of the project.

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung

2013-04-01

The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between rainfall and groundwater signal at low frequency and high frequency relationship at some certain extreme rainfall events. Keywords: extreme rainfall, groundwater, EOF, wavelet coherence

Anticipating Future Extreme Climate Events for Alaska Using Dynamical Downscaling and Quantile Mapping

NASA Astrophysics Data System (ADS)

Lader, R.; Walsh, J. E.

2016-12-01

Alaska is projected to experience major changes in extreme climate during the 21st century, due to greenhouse warming and exacerbated by polar amplification, wherein the Arctic is warming at twice the rate compared to the Northern Hemisphere. Given its complex topography, Alaska displays extreme gradients of temperature and precipitation. However, global climate models (GCMs), which typically have a spatial resolution on the order of 100km, struggle to replicate these extremes. To help resolve this issue, this study employs dynamically downscaled regional climate simulations and quantile-mapping methodologies to provide a full suite of daily model variables at 20 km spatial resolution for Alaska, from 1970 to 2100. These data include downscaled products of the: ERA-Interim reanalysis from 1979 to 2015, GFDL-CM3 historical from 1970 to 2005, and GFDL-CM3 RCP 8.5 from 2006 to 2100. Due to the limited nature of long-term observations and high-resolution modeling in Alaska, these data enable a broad expansion of extremes analysis. This study uses these data to highlight a subset of the 27 climate extremes indices, previously defined by the Expert Team on Climate Change Detection and Indices, as they pertain to climate change in Alaska. These indices are based on the statistical distributions of daily surface temperature and precipitation and focus on threshold exceedance, and percentiles. For example, the annual number of days with a daily maximum temperature greater than 25°C is anticipated to triple in many locations in Alaska by the end of the century. Climate extremes can also refer to long duration events, such as the record-setting warmth that defined the 2015-16 cold season in Alaska. The downscaled climate model simulations indicate that this past winter will be considered normal by as early as the mid-2040s, if we continue to warm according to the business-as-usual RCP 8.5 emissions scenario. This represents an accelerated warming as compared to projections form the coarse scale GCMs, and this greater rate of change in the downscaled products is noted with other extremes indices as well.

Quadrant anode image sensor

NASA Technical Reports Server (NTRS)

Lampton, M.; Malina, R. F.

1976-01-01

A position-sensitive event-counting electronic readout system for microchannel plates (MCPs) is described that offers the advantages of high spatial resolution and fast time resolution. The technique relies upon a four-quadrant electron-collecting anode located behind the output face of the microchannel plate, so that the electron cloud from each detected event is partly intercepted by each of the four quadrants. The relative amounts of charge collected by each quadrant depend on event position, permitting each event to be localized with two ratio circuits. A prototype quadrant anode system for ion, electron, and extreme ultraviolet imaging is described. The spatial resolution achieved, about 10 microns, allows individual MCP channels to be distinguished.

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

Investigating the Influence of Anthropogenic Forcing on Observed Mean and Extreme Sea Level Pressure Trends over the Mediterranean Region

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

Barkhordarian, Armineh

We investigate whether the observed mean sea level pressure (SLP) trends over the Mediterranean region in the period from 1975 to 2004 are significantly consistent with what 17 models projected as response of SLP to anthropogenic forcing (greenhouse gases and sulphate aerosols, GS). Obtained results indicate that the observed trends in mean SLP cannot be explained by natural (internal) variability. Externally forced changes are detectable in all seasons, except spring. The large-scale component (spatial mean) of the GS signal is detectable in all the 17 models in winter and in 12 of the 17 models in summer. However, the small-scalemore » component (spatial anomalies about the spatial mean) of GS signal is only detectable in winter within 11 of the 17 models. We also show that GS signal has a detectable influence on observed decreasing (increasing) tendency in the frequencies of extremely low (high) SLP days in winter and that these changes cannot be explained by internal climate variability. While the detection of GS forcing is robust in winter and summer, there are striking inconsistencies in autumn, where analysis points to the presence of an external forcing, which is not GS forcing.« less

Investigating the Influence of Anthropogenic Forcing on Observed Mean and Extreme Sea Level Pressure Trends over the Mediterranean Region

DOE PAGES

Barkhordarian, Armineh

2012-01-01

We investigate whether the observed mean sea level pressure (SLP) trends over the Mediterranean region in the period from 1975 to 2004 are significantly consistent with what 17 models projected as response of SLP to anthropogenic forcing (greenhouse gases and sulphate aerosols, GS). Obtained results indicate that the observed trends in mean SLP cannot be explained by natural (internal) variability. Externally forced changes are detectable in all seasons, except spring. The large-scale component (spatial mean) of the GS signal is detectable in all the 17 models in winter and in 12 of the 17 models in summer. However, the small-scalemore » component (spatial anomalies about the spatial mean) of GS signal is only detectable in winter within 11 of the 17 models. We also show that GS signal has a detectable influence on observed decreasing (increasing) tendency in the frequencies of extremely low (high) SLP days in winter and that these changes cannot be explained by internal climate variability. While the detection of GS forcing is robust in winter and summer, there are striking inconsistencies in autumn, where analysis points to the presence of an external forcing, which is not GS forcing.« less

Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil.

PubMed

Santos, Celso Augusto Guimarães; Brasil Neto, Reginaldo Moura; Passos, Jacqueline Sobral de Araújo; da Silva, Richarde Marques

2017-06-01

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).

Anomaly detection driven active learning for identifying suspicious tracks and events in WAMI video

NASA Astrophysics Data System (ADS)

Miller, David J.; Natraj, Aditya; Hockenbury, Ryler; Dunn, Katherine; Sheffler, Michael; Sullivan, Kevin

2012-06-01

We describe a comprehensive system for learning to identify suspicious vehicle tracks from wide-area motion (WAMI) video. First, since the road network for the scene of interest is assumed unknown, agglomerative hierarchical clustering is applied to all spatial vehicle measurements, resulting in spatial cells that largely capture individual road segments. Next, for each track, both at the cell (speed, acceleration, azimuth) and track (range, total distance, duration) levels, extreme value feature statistics are both computed and aggregated, to form summary (p-value based) anomaly statistics for each track. Here, to fairly evaluate tracks that travel across different numbers of spatial cells, for each cell-level feature type, a single (most extreme) statistic is chosen, over all cells traveled. Finally, a novel active learning paradigm, applied to a (logistic regression) track classifier, is invoked to learn to distinguish suspicious from merely anomalous tracks, starting from anomaly-ranked track prioritization, with ground-truth labeling by a human operator. This system has been applied to WAMI video data (ARGUS), with the tracks automatically extracted by a system developed in-house at Toyon Research Corporation. Our system gives promising preliminary results in highly ranking as suspicious aerial vehicles, dismounts, and traffic violators, and in learning which features are most indicative of suspicious tracks.

The waviness of the extratropical jet and daily weather extremes

NASA Astrophysics Data System (ADS)

Röthlisberger, Matthias; Martius, Olivia; Pfahl, Stephan

2016-04-01

In recent years the Northern Hemisphere mid-latitudes have experienced a large number of weather extremes with substantial socio-economic impact, such as the European and Russian heat waves in 2003 and 2010, severe winter floods in the United Kingdom in 2013/2014 and devastating winter storms such as Lothar (1999) and Xynthia (2010) in Central Europe. These have triggered an engaged debate within the scientific community on the role of human induced climate change in the occurrence of such extremes. A key element of this debate is the hypothesis that the waviness of the extratropical jet is linked to the occurrence of weather extremes, with a wavier jet stream favouring more extremes. Previous work on this topic is expanded in this study by analyzing the linkage between a regional measure of jet waviness and daily temperature, precipitation and wind gust extremes. We show that indeed such a linkage exists in many regions of the world, however this waviness-extremes linkage varies spatially in strength and sign. Locally, it is strong only where the relevant weather systems, in which the extremes occur, are affected by the jet waviness. Its sign depends on how the frequency of occurrence of the relevant weather systems is correlated with the occurrence of high and low jet waviness. These results go beyond previous studies by noting that also a decrease in waviness could be associated with an enhanced number of some weather extremes, especially wind gust and precipitation extremes over western Europe.

Impacts of Climate Change On The Occurrence of Extreme Events: The Mice Project

NASA Astrophysics Data System (ADS)

Palutikof, J. P.; Mice Team

It is widely accepted that climate change due to global warming will have substan- tial impacts on the natural environment, and on human activities. Furthermore, it is increasingly recognized that changes in the severity and frequency of extreme events, such as windstorm and flood, are likely to be more important than changes in the average climate. The EU-funded project MICE (Modelling the Impacts of Climate Extremes) commenced in January 2002. It seeks to identify the likely changes in the occurrence of extremes of rainfall, temperature and windstorm due to global warm- ing, using information from climate models as a basis, and to study the impacts of these changes in selected European environments. The objectives are: a) to evaluate, by comparison with gridded and station observations, the ability of climate models to successfully reproduce the occurrence of extremes at the required spatial and temporal scales. b) to analyse model output with respect to future changes in the occurrence of extremes. Statistical analyses will determine changes in (i) the return periods of ex- tremes, (ii) the joint probability of extremes (combinations of damaging events such as windstorm followed by heavy rain), (iii) the sequential behaviour of extremes (whether events are well-separated or clustered) and (iv) the spatial patterns of extreme event occurrence across Europe. The range of uncertainty in model predictions will be ex- plored by analysing changes in model experiments with different spatial resolutions and forcing scenarios. c) to determine the impacts of the predicted changes in extremes occurrence on selected activity sectors: agriculture (Mediterranean drought), commer- cial forestry and natural forest ecosystems (windstorm and flood in northern Europe, fire in the Mediterranean), energy use (temperature extremes), tourism (heat stress and Mediterranean beach holidays, changes in the snow pack and winter sports ) and civil protection/insurance (windstorm and flood). Impacts will be evaluated through a combination of techniques ranging from quantitative analyses through to expert judge- ment. Throughout the project, a continuing dialogue with stakeholders and end-users will be maintained.

Changes in the Winter-Time Storminess over the North Atlantic, Associated with the 1.5°C and 2°C Levels of Global Warming.

NASA Astrophysics Data System (ADS)

Barcikowska, M. J.; Weaver, S. J.; Feser, F.; Schenk, F.

2017-12-01

This study investigates the changes in extreme winter-time weather conditions over the NH midlatitudes. These conditions are to a large degree caused by extratropical storms, often associated with very intense and hazardous precipitation and wind. Although the skill of CMIP5 models in capturing these extremes is improved when compared to the previous generations, the spatial and temporal resolution of the models still remains a primary reason for the deficiencies. Therefore, many features of the storms projected for the future remain inconsistent. Here we are using the high-res horizontal (0.25° lat x lon) and temporal (3hr) output of the HAPPI experiment. This output facilitates not only an implicit extraction of storm tracks but also an analysis of the storm intensity, in terms of their maximum wind and rainfall, at subdaily time-scales. The analysis of simulated present climate shows an improved spatial pattern of large-scale circulation over North America and Europe, as compared to the CMIP5-generation models, and consequently a reduced zonal bias in storm tracks pattern. The information provided at subdaily time scale provides much more realistic representation of the magnitude of the extremes. These advances significantly contribute to our understanding of differential climate impacts between 1.5°C and 2°C levels of global warming. The spatial pattern of the north-eastward shift of storm tracks, derived from the recent CMIP5 future projections, is remarkably refined here. For example, increasing storminess expands towards Scandinavia, and not towards the north-central Europe. Derived spatial features of the storm intensity, e.g. increase in wind and precipitation on the west coasts of both the British Isles and Scandinavia underlines the relevancy of the results for the local communities and potential climate change adaptation initiatives.

Five centuries of Central European temperature extremes reconstructed from tree-ring density and documentary evidence

NASA Astrophysics Data System (ADS)

Battipaglia, Giovanna; Frank, David; Büntgen, Ulf; Dobrovolný, Petr; Brázdil, Rudolf; Pfister, Christian; Esper, Jan

2010-06-01

Future climate change will likely influence the frequency and intensity of weather extremes. As such events are by definition rare, long records are required to understand their characteristics, drivers, and consequences on ecology and society. Herein we provide a unique perspective on regional-scale temperature extremes over the past millennium, using three tree-ring maximum latewood density (MXD) chronologies from higher elevations in the European Alps. We verify the tree-ring-based extremes using documentary evidences from Switzerland, the Czech Republic, and Central Europe that allowed the identification of 44 summer extremes over the 1550-2003 period. These events include cold temperatures in 1579, 1628, 1675, and 1816, as well as warm ones in 1811 and 2003. Prior to 1550, we provide new evidence for cold (e.g., 1068 and 1258) and warm (e.g., 1333) summers derived from the combined MXD records and thus help to characterize high-frequency temperature variability during medieval times. Spatial coherence of the reconstructed extremes is found over Switzerland, with most signatures even extending across Central Europe. We discuss potential limitations of the tree-ring and documentary archives, including the ( i) ability of MXD to particularly capture extremely warm temperatures, ( ii) methodological identification and relative definition of extremes, and ( iii) placement of those events in the millennium-long context of low-frequency climate change.

Three decades of high-resolution coastal sea surface temperatures reveal more than warming.

PubMed

Lima, Fernando P; Wethey, David S

2012-02-28

Understanding and forecasting current and future consequences of coastal warming require a fine-scale assessment of the near-shore temperature changes. Here we show that despite the fact that 71% of the world's coastlines are significantly warming, rates of change have been highly heterogeneous both spatially and seasonally. We demonstrate that 46% of the coastlines have experienced a significant decrease in the frequency of extremely cold events, while extremely hot days are becoming more common in 38% of the area. Also, we show that the onset of the warm season is significantly advancing earlier in the year in 36% of the temperate coastal regions. More importantly, it is now possible to analyse local patterns within the global context, which is useful for a broad array of scientific fields, policy makers and general public.

Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts

NASA Technical Reports Server (NTRS)

Hilbert, Kent; Pagnutti, Mary; Ryan, Robert; Zanoni, Vicki

2002-01-01

This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (<30-m ground sampling distance (GSD)). Previously published literature indicated that areas with the African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (<5-m GSD) IKONOS multispectral data collected over sites in Libya and Mali. Fine-resolution imagery over a Libyan site exhibited less than 1 percent nonuniformity. The research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

High-resolution imaging of a shock front in plastic by phase contrast imaging at LCLS

NASA Astrophysics Data System (ADS)

Beckwith, M.; Jiang, S.; Zhao, Y.; Schropp, A.; Fernandez-Panella, A.; Rinderknecht, H. G.; Wilks, S.; Fournier, K.; Galtier, E.; Xing, Z.; Granados, E.; Gamboa, E.; Glenzer, S. H.; Heimann, P.; Zastrau, U.; Cho, B. I.; Eggert, J. H.; Collins, G. W.; Ping, Y.

2017-10-01

Understanding the propagation of shock waves is important for many areas of high energy density physics, including inertial confinement fusion (ICF) and shock compression science. In order to probe the shock front structures in detail, a diagnostic capable of detecting both the small spatial and temporal changes in the material is required. Here we show the experiment using hard X-ray phase contrast imaging (PCI) to probe the shock wave propagation in polyimide with submicron spatial resolution. The experiment was performed at the Matter in Extreme Conditions (MEC) endstation of the Linac Coherent Lightsource (LCLS). PCI together with the femtosecond time scales of x-ray free electron lasers enables the imaging of optically opaque materials that undergo rapid temporal and spatial changes. The result reveals the evolution of the density profile with time. Work performed under DOE Contract No. DE-AC52-07NA27344 with support from OFES Early Career and LLNL LDRD program.

Warming and wetting signals emerging from analysis of changes in climate extreme indices over South America

NASA Astrophysics Data System (ADS)

Skansi, María de los Milagros; Brunet, Manola; Sigró, Javier; Aguilar, Enric; Arevalo Groening, Juan Andrés; Bentancur, Oscar J.; Castellón Geier, Yaruska Rosa; Correa Amaya, Ruth Leonor; Jácome, Homero; Malheiros Ramos, Andrea; Oria Rojas, Clara; Pasten, Alejandro Max; Sallons Mitro, Sukarni; Villaroel Jiménez, Claudia; Martínez, Rodney; Alexander, Lisa V.; Jones, P. D.

2013-01-01

Here we show and discuss the results of an assessment of changes in both area-averaged and station-based climate extreme indices over South America (SA) for the 1950-2010 and 1969-2009 periods using high-quality daily maximum and minimum temperature and precipitation series. A weeklong regional workshop in Guayaquil (Ecuador) provided the opportunity to extend the current picture of changes in climate extreme indices over SA. Our results provide evidence of warming and wetting across the whole SA since the mid-20th century onwards. Nighttime (minimum) temperature indices show the largest rates of warming (e.g. for tropical nights, cold and warm nights), while daytime (maximum) temperature indices also point to warming (e.g. for cold days, summer days, the annual lowest daytime temperature), but at lower rates than for minimums. Both tails of night-time temperatures have warmed by a similar magnitude, with cold days (the annual lowest nighttime and daytime temperatures) seeing reductions (increases). Trends are strong and moderate (moderate to weak) for regional-averaged (local) indices, most of them pointing to a less cold SA during the day and warmer night-time temperatures. Regionally-averaged precipitation indices show clear wetting and a signature of intensified heavy rain events over the eastern part of the continent. The annual amounts of rainfall are rising strongly over south-east SA (26.41 mm/decade) and Amazonia (16.09 mm/decade), but north-east Brazil and the western part of SA have experienced non-significant decreases. Very wet and extremely days, the annual maximum 5-day and 1-day precipitation show the largest upward trends, indicating an intensified rainfall signal for SA, particularly over Amazonia and south-east SA. Local trends for precipitation extreme indices are in general less coherent spatially, but with more general spatially coherent upward trends in extremely wet days over all SA.

Modeling short duration extreme precipitation patterns using copula and generalized maximum pseudo-likelihood estimation with censoring

NASA Astrophysics Data System (ADS)

Bargaoui, Zoubeida Kebaili; Bardossy, Andràs

2015-10-01

The paper aims to develop researches on the spatial variability of heavy rainfall events estimation using spatial copula analysis. To demonstrate the methodology, short time resolution rainfall time series from Stuttgart region are analyzed. They are constituted by rainfall observations on continuous 30 min time scale recorded over a network composed by 17 raingages for the period July 1989-July 2004. The analysis is performed aggregating the observations from 30 min up to 24 h. Two parametric bivariate extreme copula models, the Husler-Reiss model and the Gumbel model are investigated. Both involve a single parameter to be estimated. Thus, model fitting is operated for every pair of stations for a giving time resolution. A rainfall threshold value representing a fixed rainfall quantile is adopted for model inference. Generalized maximum pseudo-likelihood estimation is adopted with censoring by analogy with methods of univariate estimation combining historical and paleoflood information with systematic data. Only pairs of observations greater than the threshold are assumed as systematic data. Using the estimated copula parameter, a synthetic copula field is randomly generated and helps evaluating model adequacy which is achieved using Kolmogorov Smirnov distance test. In order to assess dependence or independence in the upper tail, the extremal coefficient which characterises the tail of the joint bivariate distribution is adopted. Hence, the extremal coefficient is reported as a function of the interdistance between stations. If it is less than 1.7, stations are interpreted as dependent in the extremes. The analysis of the fitted extremal coefficients with respect to stations inter distance highlights two regimes with different dependence structures: a short spatial extent regime linked to short duration intervals (from 30 min to 6 h) with an extent of about 8 km and a large spatial extent regime related to longer rainfall intervals (from 12 h to 24 h) with an extent of 34 to 38 km.

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Extreme alien light allows survival of terrestrial bacteria

NASA Astrophysics Data System (ADS)

Johnson, Neil; Zhao, Guannan; Caycedo, Felipe; Manrique, Pedro; Qi, Hong; Rodriguez, Ferney; Quiroga, Luis

2013-07-01

Photosynthetic organisms provide a crucial coupling between the Sun's energy and metabolic processes supporting life on Earth. Searches for extraterrestrial life focus on seeking planets with similar incident light intensities and environments. However the impact of abnormal photon arrival times has not been considered. Here we present the counterintuitive result that broad classes of extreme alien light could support terrestrial bacterial life whereas sources more similar to our Sun might not. Our detailed microscopic model uses state-of-the-art empirical inputs including Atomic Force Microscopy (AFM) images. It predicts a highly nonlinear survivability for the basic lifeform Rsp. Photometricum whereby toxic photon feeds get converted into a benign metabolic energy supply by an interplay between the membrane's spatial structure and temporal excitation processes. More generally, our work suggests a new handle for manipulating terrestrial photosynthesis using currently-available extreme value statistics photon sources.

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

Generation of Bright, Spatially Coherent Soft X-Ray High Harmonics in a Hollow Waveguide Using Two-Color Synthesized Laser Pulses.

PubMed

Jin, Cheng; Stein, Gregory J; Hong, Kyung-Han; Lin, C D

2015-07-24

We investigate the efficient generation of low-divergence high-order harmonics driven by waveform-optimized laser pulses in a gas-filled hollow waveguide. The drive waveform is obtained by synthesizing two-color laser pulses, optimized such that highest harmonic yields are emitted from each atom. Optimization of the gas pressure and waveguide configuration has enabled us to produce bright and spatially coherent harmonics extending from the extreme ultraviolet to soft x rays. Our study on the interplay among waveguide mode, atomic dispersion, and plasma effect uncovers how dynamic phase matching is accomplished and how an optimized waveform is maintained when optimal waveguide parameters (radius and length) and gas pressure are identified. Our analysis should help laboratory development in the generation of high-flux bright coherent soft x rays as tabletop light sources for applications.

Temporal and spatial characterization of zenith total delay (ZTD) in North Europe

NASA Astrophysics Data System (ADS)

Stoew, B.; Elgered, G.

2003-04-01

The estimates of ZTD are often treated as realizations of random walk stochastic processes. We derive the corresponding process parameters for 34 different locations in North Europe using two measurement techniques - Global Positioning System (GPS) and Water Vapor Radiometer (WVR). GPS-estimated ZTD is an excellent candidate for data assimilation in numerical weather prediction (NWP) models in terms of both spatial and temporal resolution. We characterize the long term behavior of the ZTD as a function of site latitude and height. The spatial characteristics of the ZTD are studied as a function of site separation and season. We investigate the influence of the time-interpolated atmospheric pressure data used for the estimation of zenith wet delay (ZWD) from ZTD. Characterization of extreme atmospheric events can aid the development of an early warning system. We consider two types of extreme meteorological phenomena with regard to their spatial scales. The first type concerns larger regions (including several GPS sites); the extreme weather is characterized by intense precipitation which may result in a flood. The second type is related to local variations in the ZWD/ZTD and can be used for detection/monitoring of passing atmospheric fronts.

UAS applications in high alpine, snow-covered terrain

NASA Astrophysics Data System (ADS)

Bühler, Y.; Stoffel, A.; Ginzler, C.

2017-12-01

Access to snow-covered, alpine terrain is often difficult and dangerous. Hence parameters such as snow depth or snow avalanche release and deposition zones are hard to map in situ with adequate spatial and temporal resolution and with spatial continuous coverage. These parameters are currently operationally measured at automated weather stations and by observer networks. However such isolated point measurements are not able to capture the information spatial continuous and to describe the high spatial variability present in complex mountain topography. Unmanned Aerial Systems (UAS) have the potential to fill this gap by frequently covering selected high alpine areas with high spatial resolution down to ground resolutions of even few millimeters. At the WSL Institute for Snow and Avalanche Research SLF we test different photogrammetric UAS with visual and near infrared bands. During the last three years we were able to gather experience in more than 100 flight missions in extreme terrain. By processing the imagery applying state-of-the-art structure from motion (SfM) software, we were able to accurately document several avalanche events and to photogrammetrically map snow depth with accuracies from 1 to 20 cm (dependent on the flight height above ground) compare to manual snow probe measurements. This was even possible on homogenous snow surfaces with very little texture. A key issue in alpine terrain is flight planning. We need to cover regions at high elevations with large altitude differences (up to 1 km) with high wind speeds (up to 20 m/s) and cold temperatures (down to - 25°C). Only a few UAS are able to cope with these environmental conditions. We will give an overview on our applications of UAS in high alpine terrain that demonstrate the big potential of such systems to acquire frequent, accurate and high spatial resolution geodata in high alpine, snow covered terrain that could be essential to answer longstanding questions in avalanche and snow hydrology research.

Can the complementary relationship between actual and potential evaporation be used to quantify heatwaves?

NASA Astrophysics Data System (ADS)

Aminzadeh, Milad; Or, Dani

2017-04-01

Extreme climate events such as heatwaves with prolonged periods of high air temperatures have large environmental, social, and economic impacts ranging from crop failure to health and desiccation damages. Periods of low precipitation with high temperatures decrease soil moisture storage and thus affect surface energy partitioning. The heuristic concepts in the basis of the Complementary Relationship (CR) suggest that a fraction of radiative energy not used for evaporation contributes to increased sensible heat flux thus heats near-surface atmosphere. We have recently generalized the CR framework for spatially heterogeneous landscapes thereby enable prediction of actual evapotranspiration (ET) from routine atmospheric measurements. Capitalizing on the coupling between moisture availability, actual ET and sensible heat flux we propose using the CR to predict conditions conducive to rapid increase in regional sensible heat flux associated with the onset of extreme heatwaves. The proposed framework is evaluated using satellite surface temperature and FLUXNET data with newly derived metrics for the onset of heatwaves. The concepts could be extended to obtain new insights into the dynamics of more persistent climate extremes such as regional droughts.

Phase-detected Brillouin optical correlation-domain reflectometry

NASA Astrophysics Data System (ADS)

Mizuno, Yosuke; Hayashi, Neisei; Fukuda, Hideyuki; Nakamura, Kentaro

2018-05-01

Optical fiber sensing techniques based on Brillouin scattering have been extensively studied for structural health monitoring owing to their capability of distributed strain and temperature measurement. Although a higher signal-to-noise ratio (leading to high spatial resolution and high-speed measurement) is generally obtained for two-end-access systems, they reduce the degree of freedom in embedding the sensors into structures, and render the measurement no longer feasible when extremely high loss or breakage occurs at a point of the sensing fiber. To overcome these drawbacks, a one-end-access sensing technique called Brillouin optical correlation-domain reflectometry (BOCDR) has been developed. BOCDR has a high spatial resolution and cost efficiency, but its conventional configuration suffered from relatively low-speed operation. In this paper, we review the recently developed high-speed configurations of BOCDR, including phase-detected BOCDR, with which we demonstrate real-time distributed measurement by tracking a propagating mechanical wave. We also demonstrate breakage detection with a wide strain dynamic range.

Phase-detected Brillouin optical correlation-domain reflectometry

NASA Astrophysics Data System (ADS)

Mizuno, Yosuke; Hayashi, Neisei; Fukuda, Hideyuki; Nakamura, Kentaro

2018-06-01

Optical fiber sensing techniques based on Brillouin scattering have been extensively studied for structural health monitoring owing to their capability of distributed strain and temperature measurement. Although a higher signal-to-noise ratio (leading to high spatial resolution and high-speed measurement) is generally obtained for two-end-access systems, they reduce the degree of freedom in embedding the sensors into structures, and render the measurement no longer feasible when extremely high loss or breakage occurs at a point of the sensing fiber. To overcome these drawbacks, a one-end-access sensing technique called Brillouin optical correlation-domain reflectometry (BOCDR) has been developed. BOCDR has a high spatial resolution and cost efficiency, but its conventional configuration suffered from relatively low-speed operation. In this paper, we review the recently developed high-speed configurations of BOCDR, including phase-detected BOCDR, with which we demonstrate real-time distributed measurement by tracking a propagating mechanical wave. We also demonstrate breakage detection with a wide strain dynamic range.

The GKSS beamlines at PETRA III and DORIS III

NASA Astrophysics Data System (ADS)

Haibel, A.; Beckmann, F.; Dose, T.; Herzen, J.; Utcke, S.; Lippmann, T.; Schell, N.; Schreyer, A.

2008-08-01

Due to the high brilliance of the new storage ring PETRA III at DESY in Hamburg, the low emittance of 1 nmrad and the high fraction of coherent photons also in the hard X-ray range extremely intense and sharply focused X-ray light will be provided. These advantages of the beam fulfill excellently the qualifications for the planned Imaging BeamLine IBL and the High Energy Materials Science Beamline (HEMS) at PETRA III, i.e. for absorption tomography, phase enhanced and phase contrast experiments, for diffraction, for nano focusing, for nano tomography, and for high speed or in-situ experiments with highest spatial resolution. The existing HARWI II beamline at the DORIS III storage ring at DESY completes the GKSS beamline concept with setups for high energy tomography (16-150 keV) and diffraction (16-250 keV), characterized by a large field of view and an excellent absorption contrast with spatial resolutions down to 2 μm.

Characteristics and present trends of wave extremes in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Pino, Cosimo; Lionello, Piero; Galati, Maria Barbara

2010-05-01

Wind generated surface waves are an important factor characterizing marine storminess and the marine environment. This contribution considers characteristics and trends of SWH (Significant Wave Height) extremes (both high and low extremes, such as dead calm duration are analyzed). The data analysis is based on a 44-year long simulation (1958-2001) of the wave field in the Mediterranean Sea. The quality of the model simulation is controlled using satellite data. The results show the different characteristics of the different parts of the basin with the variability being higher in the western (where the highest values are produced) than in the eastern areas of the basin (where absence of wave is a rare condition). In fact, both duration of storms and of dead calm episodes is larger in the east than in the west part of the Mediterranean. The African coast and the southern Ionian Sea are the areas were exceptional values of SWH are expected to occur in correspondence with exceptional meteorological events. Significant trends of storm characteristics are present only in sparse areas and suggest a decrease of both storm intensity and duration (a marginal increase of storm intensity is present in the center of the Mediterranean). The statistics of extremes and high SWH values is substantially steady during the second half of the 20th century. The influence of the large-scale teleconnection patterns (TlcP) that are known to be relevant for the Mediterranean climate on the intensity and spatial distribution of extreme SWH (Significant Wave Height) has been investigated. The analysis was focused on the monthly scale analysing the variability of links along the annual cycle. The considered TlcP are the North Atlantic Oscillation, the East-Atlantic / West-Russian pattern and the Scandinavian pattern and their effect on the intensity and the frequency of high/low SWH conditions. The results show it is difficult to establish a dominant TlcP for SWH extremes, because all 4 patterns considered are important for at least few months in the year and none of them is important for the whole year. High extremes in winter and fall are more influenced by the TlcPs than in other seasons and low extremes.

Study of Environmental Data Complexity using Extreme Learning Machine

NASA Astrophysics Data System (ADS)

Leuenberger, Michael; Kanevski, Mikhail

2017-04-01

The main goals of environmental data science using machine learning algorithm deal, in a broad sense, around the calibration, the prediction and the visualization of hidden relationship between input and output variables. In order to optimize the models and to understand the phenomenon under study, the characterization of the complexity (at different levels) should be taken into account. Therefore, the identification of the linear or non-linear behavior between input and output variables adds valuable information for the knowledge of the phenomenon complexity. The present research highlights and investigates the different issues that can occur when identifying the complexity (linear/non-linear) of environmental data using machine learning algorithm. In particular, the main attention is paid to the description of a self-consistent methodology for the use of Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. By applying two ELM models (with linear and non-linear activation functions) and by comparing their efficiency, quantification of the linearity can be evaluated. The considered approach is accompanied by simulated and real high dimensional and multivariate data case studies. In conclusion, the current challenges and future development in complexity quantification using environmental data mining are discussed. References - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

Spatial distribution of unidirectional trends in temperature and temperature extremes in Pakistan

NASA Astrophysics Data System (ADS)

Khan, Najeebullah; Shahid, Shamsuddin; Ismail, Tarmizi bin; Wang, Xiao-Jun

2018-06-01

Pakistan is one of the most vulnerable countries of the world to temperature extremes due to its predominant arid climate and geographic location in the fast temperature rising zone. Spatial distribution of the trends in annual and seasonal temperatures and temperature extremes over Pakistan has been assessed in this study. The gauge-based gridded daily temperature data of Berkeley Earth Surface Temperature (BEST) having a spatial resolution of 1° × 1° was used for the assessment of trends over the period 1960-2013 using modified Mann-Kendall test (MMK), which can discriminate the multi-decadal oscillatory variations from secular trends. The results show an increase in the annual average of daily maximum and minimum temperatures in 92 and 99% area of Pakistan respectively at 95% level of confidence. The annual temperature is increasing faster in southern high-temperature region compared to other parts of the country. The minimum temperature is rising faster (0.17-0.37 °C/decade) compared to maximum temperature (0.17-0.29 °C/decade) and therefore declination of diurnal temperature range (DTR) (- 0.15 to - 0.08 °C/decade) in some regions. The annual numbers of both hot and cold days are increasing in whole Pakistan except in the northern sub-Himalayan region. Heat waves are on the rise, especially in the hot Sindh plains and the Southern coastal region, while the cold waves are becoming lesser in the northern cold region. Obtained results contradict with the findings of previous studies on temperature trends, which indicate the need for reassessment of climatic trends in Pakistan using the MMK test to understand the anthropogenic impacts of climate change.

Atmospheric Moisture Budget and Spatial Resolution Dependence of Precipitation Extremes in Aquaplanet Simulations

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

Yang, Qing; Leung, Lai-Yung R.; Rauscher, Sara

This study investigates the resolution dependency of precipitation extremes in an aqua-planet framework. Strong resolution dependency of precipitation extremes is seen over both tropics and extra-tropics, and the magnitude of this dependency also varies with dynamical cores. Moisture budget analyses based on aqua-planet simulations with the Community Atmosphere Model (CAM) using the Model for Prediction Across Scales (MPAS) and High Order Method Modeling Environment (HOMME) dynamical cores but the same physics parameterizations suggest that during precipitation extremes moisture supply for surface precipitation is mainly derived from advective moisture convergence. The resolution dependency of precipitation extremes mainly originates from advective moisturemore » transport in the vertical direction. At most vertical levels over the tropics and in the lower atmosphere over the subtropics, the vertical eddy transport of mean moisture field dominates the contribution to precipitation extremes and its resolution dependency. Over the subtropics, the source of moisture, its associated energy, and the resolution dependency during extremes are dominated by eddy transport of eddies moisture at the mid- and upper-troposphere. With both MPAS and HOMME dynamical cores, the resolution dependency of the vertical advective moisture convergence is mainly explained by dynamical changes (related to vertical velocity or omega), although the vertical gradients of moisture act like averaging kernels to determine the sensitivity of the overall resolution dependency to the changes in omega at different vertical levels. The natural reduction of variability with coarser resolution, represented by areal data averaging (aggregation) effect, largely explains the resolution dependency in omega. The thermodynamic changes, which likely result from non-linear feedback in response to the large dynamical changes, are small compared to the overall changes in dynamics (omega). However, after excluding the data aggregation effect in omega, thermodynamic changes become relatively significant in offsetting the effect of dynamics leading to reduce differences between the simulated and aggregated results. Compared to MPAS, the simulated stronger vertical motion with HOMME also results in larger resolution dependency. Compared to the simulation at fine resolution, the vertical motion during extremes is insufficiently resolved/parameterized at the coarser resolution even after accounting for the natural reduction in variability with coarser resolution, and this is more distinct in the simulation with HOMME. To reduce uncertainties in simulated precipitation extremes, future development in cloud parameterizations must address their sensitivity to spatial resolution as well as dynamical cores.« less

Spatial and temporal variation in emergency transport during periods of extreme heat in Japan: A nationwide study.

PubMed

Onozuka, Daisuke; Hagihara, Akihito

2016-02-15

Several studies have reported the burden of climate change on extreme heat-related mortality or morbidity. However, few studies have investigated the spatial and temporal variation in emergency transport during periods of extreme heat on a national scale. Daily emergency ambulance dispatch data from 2007 to 2010 were acquired from all 47 prefectures of Japan. The temporal variability in the relationship between heat and morbidity in each prefecture was estimated using Poisson regression combined with a distributed lag non-linear model and adjusted for time trends. The spatial variability in the heat-morbidity relationships between prefectures was estimated using a multivariate meta-analysis. A total of 5,289,660 emergency transports were reported during the summer months (June through September) within the study period. The overall cumulative relative risk (RR) at the 99th percentile vs. the minimum morbidity percentile was 1.292 (95% CI: 1.251-1.333) for all causes, 1.039 (95% CI: 0.989-1.091) for cardiovascular diseases, and 1.287 (95% CI: 1.210-1.368) for respiratory diseases. Temporal variation in the estimated effects indicated a non-linear relationship, and there were differences in the temporal variations between heat and all-cause and cause-specific morbidity. Spatial variation between prefectures was observed for all causes (Cochran Q test, p<0.001; I(2)=45.8%); however, there was no significant spatial heterogeneity for cardiovascular (Cochran Q test, p=0.054; I(2)=15.1%) and respiratory (Cochran Q test, p=0.681; I(2)=1.0%) diseases. Our nationwide study demonstrated differences in the spatial and temporal variations in the relative risk for all-cause and cause-specific emergency transport during periods of extreme heat in Japan between 2007 and 2010. Our results suggest that public health strategies aimed at controlling heat-related morbidity should be tailored according to region-specific weather conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of synchrotron X-ray micro-tomography under extreme conditions of pressure and temperature.

PubMed

Álvarez-Murga, M; Perrillat, J P; Le Godec, Y; Bergame, F; Philippe, J; King, A; Guignot, N; Mezouar, M; Hodeau, J L

2017-01-01

X-ray tomography is a non-destructive three-dimensional imaging/microanalysis technique selective to a wide range of properties such as density, chemical composition, chemical states and crystallographic structure with extremely high sensitivity and spatial resolution. Here the development of in situ high-pressure high-temperature micro-tomography using a rotating module for the Paris-Edinburgh cell combined with synchrotron radiation is described. By rotating the sample chamber by 360°, the limited angular aperture of ordinary high-pressure cells is surmounted. Such a non-destructive high-resolution probe provides three-dimensional insight on the morphological and structural evolution of crystalline as well as amorphous phases during high pressure and temperature treatment. To demonstrate the potentials of this new experimental technique the compression behavior of a basalt glass is investigated by X-ray absorption tomography, and diffraction/scattering tomography imaging of the structural changes during the polymerization of C 60 molecules under pressure is performed. Small size and weight of the loading frame and rotating module means that this apparatus is portable, and can be readily installed on most synchrotron facilities to take advantage of the diversity of three-dimensional imaging techniques available at beamlines. This experimental breakthrough should open new ways for in situ imaging of materials under extreme pressure-temperature-stress conditions, impacting diverse areas in physics, chemistry, geology or materials sciences.

Spatial aliasing for efficient direction-of-arrival estimation based on steering vector reconstruction

NASA Astrophysics Data System (ADS)

Yan, Feng-Gang; Cao, Bin; Rong, Jia-Jia; Shen, Yi; Jin, Ming

2016-12-01

A new technique is proposed to reduce the computational complexity of the multiple signal classification (MUSIC) algorithm for direction-of-arrival (DOA) estimate using a uniform linear array (ULA). The steering vector of the ULA is reconstructed as the Kronecker product of two other steering vectors, and a new cost function with spatial aliasing at hand is derived. Thanks to the estimation ambiguity of this spatial aliasing, mirror angles mathematically relating to the true DOAs are generated, based on which the full spectral search involved in the MUSIC algorithm is highly compressed into a limited angular sector accordingly. Further complexity analysis and performance studies are conducted by computer simulations, which demonstrate that the proposed estimator requires an extremely reduced computational burden while it shows a similar accuracy to the standard MUSIC.

Surface Desorption Dielectric-Barrier Discharge Ionization Mass Spectrometry.

PubMed

Zhang, Hong; Jiang, Jie; Li, Na; Li, Ming; Wang, Yingying; He, Jing; You, Hong

2017-07-18

A variant of dielectric-barrier discharge named surface desorption dielectric-barrier discharge ionization (SDDBDI) mass spectrometry was developed for high-efficiency ion transmission and high spatial resolution imaging. In SDDBDI, a tungsten nanotip and the inlet of the mass spectrometer are used as electrodes, and a piece of coverslip is used as a sample plate as well as an insulating dielectric barrier, which simplifies the configuration of instrument and thus the operation. Different from volume dielectric-barrier discharge (VDBD), the microdischarges are generated on the surface at SDDBDI, and therefore the plasma density is extremely high. Analyte ions are guided directly into the MS inlet without any deflection. This configuration significantly improves the ion transmission efficiency and thus the sensitivity. The dependence of sensitivity and spatial resolution of the SDDBDI on the operation parameters were systematically investigated. The application of SDDBDI was successfully demonstrated by analysis of multiple species including amino acids, pharmaceuticals, putative cancer biomarkers, and mixtures of both fatty acids and hormones. Limits of detection (S/N = 3) were determined to be 0.84 and 0.18 pmol, respectively, for the analysis of l-alanine and metronidazole. A spatial resolution of 22 μm was obtained for the analysis of an imprinted cyclophosphamide pattern, and imaging of a "T" character was successfully demonstrated under ambient conditions. These results indicate that SDDBDI has high-efficiency ion transmission, high sensitivity, and high spatial resolution, which render it a potential tool for mass spectrometry imaging.

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

2012-01-01

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Effect of trotting speed on kinematic variables measured by use of extremity-mounted inertial measurement units in nonlame horses performing controlled treadmill exercise.

PubMed

Cruz, Antonio M; Vidondo, Beatriz; Ramseyer, Alessandra A; Maninchedda, Ugo E

2018-02-01

OBJECTIVE To assess effects of speed on kinematic variables measured by use of extremity-mounted inertial measurement units (IMUs) in nonlame horses performing controlled exercise on a treadmill. ANIMALS 10 nonlame horses. PROCEDURES 6 IMUs were attached at predetermined locations on 10 nonlame Franches Montagnes horses. Data were collected in triplicate during trotting at 3.33 and 3.88 m/s on a high-speed treadmill. Thirty-three selected kinematic variables were analyzed. Repeated-measures ANOVA was used to assess the effect of speed. RESULTS Significant differences between the 2 speeds were detected for most temporal (11/14) and spatial (12/19) variables. The observed spatial and temporal changes would translate into a gait for the higher speed characterized by increased stride length, protraction and retraction, flexion and extension, mediolateral movement of the tibia, and symmetry, but with similar temporal variables and a reduction in stride duration. However, even though the tibia coronal range of motion was significantly different between speeds, the high degree of variability raised concerns about whether these changes were clinically relevant. For some variables, the lower trotting speed apparently was associated with more variability than was the higher trotting speed. CONCLUSIONS AND CLINICAL RELEVANCE At a higher trotting speed, horses moved in the same manner (eg, the temporal events investigated occurred at the same relative time within the stride). However, from a spatial perspective, horses moved with greater action of the segments evaluated. The detected changes in kinematic variables indicated that trotting speed should be controlled or kept constant during gait evaluation.

Geostatistics as a tool to study mite dispersion in physic nut plantations.

PubMed

Rosado, J F; Picanço, M C; Sarmento, R A; Pereira, R M; Pedro-Neto, M; Galdino, T V S; de Sousa Saraiva, A; Erasmo, E A L

2015-08-01

Spatial distribution studies in pest management identify the locations where pest attacks on crops are most severe, enabling us to understand and predict the movement of such pests. Studies on the spatial distribution of two mite species, however, are rather scarce. The mites Polyphagotarsonemus latus and Tetranychus bastosi are the major pests affecting physic nut plantations (Jatropha curcas). Therefore, the objective of this study was to measure the spatial distributions of P. latus and T. bastosi in the physic nut plantations. Mite densities were monitored over 2 years in two different plantations. Sample locations were georeferenced. The experimental data were analyzed using geostatistical analyses. The total mite density was found to be higher when only one species was present (T. bastosi). When both the mite species were found in the same plantation, their peak densities occurred at different times. These mites, however, exhibited uniform spatial distribution when found at extreme densities (low or high). However, the mites showed an aggregated distribution in intermediate densities. Mite spatial distribution models were isotropic. Mite colonization commenced at the periphery of the areas under study, whereas the high-density patches extended until they reached 30 m in diameter. This has not been reported for J. curcas plants before.

Long-term changes and spatio-temporal variability of the growing season temperature in Europe during the last Millennium

NASA Astrophysics Data System (ADS)

Guiot, Joel; Corona, Christophe

2010-05-01

A gridded reconstruction of April to September temperature was produced for Europe based on tree-rings, documentaries, pollen and ice cores. The majority of the proxy series have an annual resolution. For a better inference of long-term climate variations, they were completed by number of low resolution data (decadal or more), mostly on pollen and ice-core data. An original spectral analogue method was devised to deal with this heterogeneous dataset, and especially to preserve the long-term variations and the variability of the temperature series. It is the condition is to make pertinent the comparison of the recent climate changes to a broader context of 1400 years. The reconstruction of the April-September temperature was validated with a Jack-knife technique, and it was also compared with other spatially gridded temperature reconstructions, literature data, and glacier advance and retreat curves. We also attempted to relate the spatial distribution of European temperature anomalies to known solar and volcanic forcings. We found that (1) our results are sound back to A.D. 750; (2) conditions during the last decade have exceeded all those known during the last millennium; (3) before the 20th century, cold periods can partly be explained by low solar activity and/or high volcanic activity and that Medieval Warm Period (MWP) is consistent with a high solar activity; (4) during the 20th century, however only anthropogenic forcing can explain the exceptionally high temperature rise; (5) based on an analysis of the distribution of extreme temperatures, the maximum event of the Medieval Period (1.1°C higher than the 1960-1990 reference period) had a return period of more than 1000 years, but this recently fell to less than 26 years; (6) all decades before AD 1350 were warm on average but relatively heterogeneous, while the last decade was homogeneously warmer. These results support the fact that we are facing an unprecedented changing climate in Europe unlike any known in the last 1000 years, as pointed out previously. The new result is that this anthropogenic change is characterised by spatial homogeneity and changes as well in average temperatures than in distribution of extreme events, while natural climate forcings induce warm periods with heterogeneous spatial patterns and less frequent extreme events. This study demonstrates that recent changes in temperature differ substantially from temperature changes reconstructed in the past and are well in excess of normal variations experienced in previous centuries and caused by natural forcings.

Normalization Strategies for Enhancing Spatio-Temporal Analysis of Social Media Responses during Extreme Events: A Case Study based on Analysis of Four Extreme Events using Socio-Environmental Data Explorer (SEDE)

NASA Astrophysics Data System (ADS)

Ajayakumar, J.; Shook, E.; Turner, V. K.

2017-10-01

With social media becoming increasingly location-based, there has been a greater push from researchers across various domains including social science, public health, and disaster management, to tap in the spatial, temporal, and textual data available from these sources to analyze public response during extreme events such as an epidemic outbreak or a natural disaster. Studies based on demographics and other socio-economic factors suggests that social media data could be highly skewed based on the variations of population density with respect to place. To capture the spatio-temporal variations in public response during extreme events we have developed the Socio-Environmental Data Explorer (SEDE). SEDE collects and integrates social media, news and environmental data to support exploration and assessment of public response to extreme events. For this study, using SEDE, we conduct spatio-temporal social media response analysis on four major extreme events in the United States including the "North American storm complex" in December 2015, the "snowstorm Jonas" in January 2016, the "West Virginia floods" in June 2016, and the "Hurricane Matthew" in October 2016. Analysis is conducted on geo-tagged social media data from Twitter and warnings from the storm events database provided by National Centers For Environmental Information (NCEI) for analysis. Results demonstrate that, to support complex social media analyses, spatial and population-based normalization and filtering is necessary. The implications of these results suggests that, while developing software solutions to support analysis of non-conventional data sources such as social media, it is quintessential to identify the inherent biases associated with the data sources, and adapt techniques and enhance capabilities to mitigate the bias. The normalization strategies that we have developed and incorporated to SEDE will be helpful in reducing the population bias associated with social media data and will be useful for researchers and decision makers to enhance their analysis on spatio-temporal social media responses during extreme events.

Bayesian Non-Stationary Index Gauge Modeling of Gridded Precipitation Extremes

NASA Astrophysics Data System (ADS)

Verdin, A.; Bracken, C.; Caldwell, J.; Balaji, R.; Funk, C. C.

2017-12-01

We propose a Bayesian non-stationary model to generate watershed scale gridded estimates of extreme precipitation return levels. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset is used to obtain gridded seasonal precipitation extremes over the Taylor Park watershed in Colorado for the period 1981-2016. For each year, grid cells within the Taylor Park watershed are aggregated to a representative "index gauge," which is input to the model. Precipitation-frequency curves for the index gauge are estimated for each year, using climate variables with significant teleconnections as proxies. Such proxies enable short-term forecasting of extremes for the upcoming season. Disaggregation ratios of the index gauge to the grid cells within the watershed are computed for each year and preserved to translate the index gauge precipitation-frequency curve to gridded precipitation-frequency maps for select return periods. Gridded precipitation-frequency maps are of the same spatial resolution as CHIRPS (0.05° x 0.05°). We verify that the disaggregation method preserves spatial coherency of extremes in the Taylor Park watershed. Validation of the index gauge extreme precipitation-frequency method consists of ensuring extreme value statistics are preserved on a grid cell basis. To this end, a non-stationary extreme precipitation-frequency analysis is performed on each grid cell individually, and the resulting frequency curves are compared to those produced by the index gauge disaggregation method.

Spatio-temporal trends of rainfall across Indian river basins

NASA Astrophysics Data System (ADS)

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

2018-04-01

Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

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.

Evaluation of large-scale meteorological patterns associated with temperature extremes in the NARCCAP regional climate model simulations

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Lee, Huikyo; Neelin, J. David; Lintner, Benjamin R.; McGinnis, Seth; Mearns, Linda O.; Kim, Jinwon

2015-12-01

Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of well-simulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts.

Atomic Force Microscope (AFM) measurements and analysis on Sagem 05R0025 secondary substrate

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

Soufli, R; Baker, S L; Robinson, J C

2006-02-22

The summary of Atomic Force Microscope (AFM) on Sagem 05R0025 secondary substrate: (1) 2 x 2 {micro}m{sup 2} and 10 x 10 {micro}m{sup 2} AFM measurements and analysis on Sagem 05R0025 secondary substrate at LLNL indicate rather uniform and extremely isotropic finish across the surface, with high-spatial frequency roughness {sigma} in the range 5.1-5.5 {angstrom} rms; (2) the marked absence of pronounced long-range polishing marks in any direction, combined with increased roughness in the very high spatial frequencies, are consistent with ion-beam polishing treatment on the surface. These observations are consistent with all earlier mirrors they measured from the samemore » vendor; and (3) all data were obtained with a Digital Instruments Dimension 5000{trademark} atomic force microscope.« less

A hydro-meteorological model chain to assess the influence of natural variability and impacts of climate change on extreme events and propose optimal water management

NASA Astrophysics Data System (ADS)

von Trentini, F.; Willkofer, F.; Wood, R. R.; Schmid, F. J.; Ludwig, R.

2017-12-01

The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. Therefore, a hydro-meteorological model chain is applied. It employs high performance computing capacity of the Leibniz Supercomputing Centre facility SuperMUC to dynamically downscale 50 members of the Global Circulation Model CanESM2 over European and Eastern North American domains using the Canadian Regional Climate Model (RCM) CRCM5. Over Europe, the unique single model ensemble is conjointly analyzed with the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change in the dynamics of extreme events. Furthermore, these 50 members of a single RCM will enhance extreme value statistics (extreme return periods) by exploiting the available 1500 model years for the reference period from 1981 to 2010. Hence, the RCM output is applied to drive the process based, fully distributed, and deterministic hydrological model WaSiM in high temporal (3h) and spatial (500m) resolution. WaSiM and the large ensemble are further used to derive a variety of hydro-meteorological patterns leading to severe flood events. A tool for virtual perfect prediction shall provide a combination of optimal lead time and management strategy to mitigate certain flood events following these patterns.

Influence of an extreme high water event on survival, reproduction, and distribution of snail kites in Florida, USA

USGS Publications Warehouse

Bennetts, R.E.; Kitchens, W.M.; Dreitz, V.J.

2002-01-01

Hydrology frequently has been reported as the environmental variable having the greatest influence on Florida snail kite (Rostrhamus sociabilis) populations. Although drought has received the most attention, high-water conditions also have been reported to affect kites. Years of high water generally have been reported to be favorable for nesting, although prolonged high water may be detrimental to sustaining suitable habitat. During 1994 and 1995, southern Florida experienced an extreme high water event. This event enabled us to compare survival, nesting success, number of young per successful nest, and spatial distribution of nesting before, during, and after the event. We found no evidence of an effect (either negative or positive) on survival of adult kites. In contrast, juvenile kites experienced the highest survival during the event, although our data suggest greater annual variability than can be explained by the event alone. We found no evidence of an effect of the high water event on nest success or number of young per successful nest. Nest success was highest during the event in the southern portion of the range but was quite similar to other years, both before and after the event. Our data do indicate a substantial shift in the spatial distribution of nesting birds. During the event, nesting activity shifted to higher elevations (i.e., shallower water) in the major nesting areas of the Everglades region. Nesting also occurred in Big Cypress National Preserve during the event, which is typically too dry to support nesting kites. Thus, our data indicate a potential short-term benefit of increased juvenile survival and an expansion of nesting habitat. However, the deterioration of habitat quality from prolonged high water precludes any recommendation for such conditions to be maintained for extended periods. ?? 2002, The Society of Wetland Scientists.

The CAOS camera platform: ushering in a paradigm change in extreme dynamic range imager design

NASA Astrophysics Data System (ADS)

Riza, Nabeel A.

2017-02-01

Multi-pixel imaging devices such as CCD, CMOS and Focal Plane Array (FPA) photo-sensors dominate the imaging world. These Photo-Detector Array (PDA) devices certainly have their merits including increasingly high pixel counts and shrinking pixel sizes, nevertheless, they are also being hampered by limitations in instantaneous dynamic range, inter-pixel crosstalk, quantum full well capacity, signal-to-noise ratio, sensitivity, spectral flexibility, and in some cases, imager response time. Recently invented is the Coded Access Optical Sensor (CAOS) Camera platform that works in unison with current Photo-Detector Array (PDA) technology to counter fundamental limitations of PDA-based imagers while providing high enough imaging spatial resolution and pixel counts. Using for example the Texas Instruments (TI) Digital Micromirror Device (DMD) to engineer the CAOS camera platform, ushered in is a paradigm change in advanced imager design, particularly for extreme dynamic range applications.

Exploring the limits to energy scaling and distant-target delivery of high-intensity midinfrared pulses

NASA Astrophysics Data System (ADS)

Panagiotopoulos, Paris; Kolesik, Miroslav; Moloney, Jerome V.

2016-09-01

We numerically investigate the scaling behavior of midinfrared filaments at extremely high input energies. It is shown that, given sufficient power, kilometer-scale, low-loss atmospheric filamentation is attainable by prechirping the pulse. Fully resolved four-dimensional (x y z t ) simulations show that, while in a spatially imperfect beam the modulation instability can lead to multiple hot-spot formation, the individual filaments are still stabilized by the recently proposed mechanism that relies on the temporal walk-off of short-wavelength radiation.

Spatial localization of excitons and charge carriers in hybrid perovskite thin films

DOE PAGES

Simpson, Mary Jane; Doughty, Benjamin; Yang, Bin; ...

2015-07-21

The fundamental photophysics underlying the remarkably high power conversion efficiency of organic-inorganic hybrid perovskite-based solar cells has been increasingly studied using complementary spectroscopic techniques. The spatially heterogeneous polycrystalline morphology of the photoactive layers owing to the presence of distinct crystalline grains has been generally neglected in optical measurements and therefore the reported results are typically averaged over hundreds or even thousands of such grains. Here, we apply femtosecond transient absorption microscopy to spatially and temporally probe ultrafast electronic excited-state dynamics in pristine methylammonium lead tri-iodide (CH 3NH 3PbI 3) thin films and composite structures. We found that the electronic excited-statemore » relaxation kinetics are extremely sensitive to the sample location probed, which was manifested by position-dependent decay timescales and transient signals. As a result, analysis of transient absorption kinetics acquired at distinct spatial positions enabled us to identify contributions of excitons and free charge carriers.« less

Downscaling Satellite Land Surface Temperatures in Urban Regions for Surface Energy Balance Study and Heat Index Development

NASA Astrophysics Data System (ADS)

Norouzi, H.; Bah, A.; Prakash, S.; Nouri, N.; Blake, R.

2017-12-01

A great percentage of the world's population reside in urban areas that are exposed to the threats of global and regional climate changes and associated extreme weather events. Among them, urban heat islands have significant health and economic impacts due to higher thermal gradients of impermeable surfaces in urban regions compared to their surrounding rural areas. Therefore, accurate characterization of the surface energy balance in urban regions are required to predict these extreme events. High spatial resolution Land surface temperature (LST) in the scale of street level in the cities can provide wealth of information to study surface energy balance and eventually providing a reliable heat index. In this study, we estimate high-resolution LST maps using combination of LandSat 8 and infrared based satellite products such as Moderate Resolution Imaging Spectroradiometer (MODIS) and newly launched Geostationary Operational Environmental Satellite-R Series (GOES-R). Landsat 8 provides higher spatial resolution (30 m) estimates of skin temperature every 16 days. However, MODIS and GOES-R have lower spatial resolution (1km and 4km respectively) with much higher temporal resolution. Several statistical downscaling methods were investigated to provide high spatiotemporal LST maps in urban regions. The results reveal that statistical methods such as Principal Component Analysis (PCA) can provide reliable estimations of LST downscaling with 2K accuracy. Other methods also were tried including aggregating (up-scaling) the high-resolution data to a coarse one to examine the limitations and to build the model. Additionally, we deployed flux towers over distinct materials such as concrete, asphalt, and rooftops in New York City to monitor the sensible and latent heat fluxes through eddy covariance method. To account for the incoming and outgoing radiation, a 4-component radiometer is used that can observe both incoming and outgoing longwave and shortwave radiation. This enables us to accurately build the relationship between LST, air temperature, and the heat index in the future.

Repeated, long-distance migrations by a philopatric predator targeting highly contrasting ecosystems

PubMed Central

Lea, James S. E.; Wetherbee, Bradley M.; Queiroz, Nuno; Burnie, Neil; Aming, Choy; Sousa, Lara L.; Mucientes, Gonzalo R.; Humphries, Nicolas E.; Harvey, Guy M.; Sims, David W.; Shivji, Mahmood S.

2015-01-01

Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellite-tracked for multiple years (up to 1101 days) that adult males undertake annually repeated, round-trip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks. PMID:26057337

Repeated, long-distance migrations by a philopatric predator targeting highly contrasting ecosystems.

PubMed

Lea, James S E; Wetherbee, Bradley M; Queiroz, Nuno; Burnie, Neil; Aming, Choy; Sousa, Lara L; Mucientes, Gonzalo R; Humphries, Nicolas E; Harvey, Guy M; Sims, David W; Shivji, Mahmood S

2015-06-09

Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellite-tracked for multiple years (up to 1101 days) that adult males undertake annually repeated, round-trip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks.

Repeated, long-distance migrations by a philopatric predator targeting highly contrasting ecosystems

NASA Astrophysics Data System (ADS)

Lea, James S. E.; Wetherbee, Bradley M.; Queiroz, Nuno; Burnie, Neil; Aming, Choy; Sousa, Lara L.; Mucientes, Gonzalo R.; Humphries, Nicolas E.; Harvey, Guy M.; Sims, David W.; Shivji, Mahmood S.

2015-06-01

Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellite-tracked for multiple years (up to 1101 days) that adult males undertake annually repeated, round-trip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks.

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.

From daily to sub-daily time steps - Creating a high temporal and spatial resolution climate reference data set for hydrological modeling and bias-correction of RCM data

NASA Astrophysics Data System (ADS)

Willkofer, Florian; Wood, Raul R.; Schmid, Josef; von Trentini, Fabian; Ludwig, Ralf

2016-04-01

The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. It builds on the conjoint analysis of a large ensemble of the CRCM5, driven by 50 members of the CanESM2, and the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change on the dynamics of extreme events. A critical point in the entire project is the preparation of a meteorological reference dataset with the required temporal (1-6h) and spatial (500m) resolution to be able to better evaluate hydrological extreme events in mesoscale river basins. For Bavaria a first reference data set (daily, 1km) used for bias-correction of RCM data was created by combining raster based data (E-OBS [1], HYRAS [2], MARS [3]) and interpolated station data using the meteorological interpolation schemes of the hydrological model WaSiM [4]. Apart from the coarse temporal and spatial resolution, this mosaic of different data sources is considered rather inconsistent and hence, not applicable for modeling of hydrological extreme events. Thus, the objective is to create a dataset with hourly data of temperature, precipitation, radiation, relative humidity and wind speed, which is then used for bias-correction of the RCM data being used as driver for hydrological modeling in the river basins. Therefore, daily data is disaggregated to hourly time steps using the 'Method of fragments' approach [5], based on available training stations. The disaggregation chooses fragments of daily values from observed hourly datasets, based on similarities in magnitude and behavior of previous and subsequent events. The choice of a certain reference station (hourly data, provision of fragments) for disaggregating daily station data (application of fragments) is crucial and several methods will be tested to achieve a profound spatial interpolation. This entire methodology shall be applicable for existing or newly developed datasets. References [1] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres) (2008), 113, D20119, doi:10.1029/2008JD10201. [2] Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A. and A. Gratzki. A Central European precipitation climatology - Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift (2013), 22/3, p.238-256. [3] MARS-AGRI4CAST. AGRI4CAST Interpolated Meteorological Data. http://mars.jrc.ec.europa.eu/mars/ About-us/AGRI4CAST/Data-distribution/AGRI4CAST-Interpolated-Meteorological-Data. 2007, last accessed May 10th, 2013. [4] Schulla, J. Model Description WaSiM - Water balance Simulation Model. 2015, available at: http://wasim.ch/en/products/wasim_description.htm. [5] Sharma, A. and S. Srikanthan. Continuous Rainfall Simulation: A Nonparametric Alternative. 30th Hydrology and Water Resources Symposium, Launceston, Tasmania, 4-7 December, 2006.

Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

NASA Astrophysics Data System (ADS)

Zhang, J.; Yang, J.; Pan, S.; Tian, H.

2016-12-01

China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

Understanding extreme sea levels for coastal impact and adaptation analysis

NASA Astrophysics Data System (ADS)

Wahl, T.; Haigh, I. D.; Nicholls, R. J.; Arns, A.; Hinkel, J.; Dangendorf, S.; Slangen, A.

2016-12-01

Coastal impact and adaptation assessments require detailed knowledge on extreme sea levels, because increasing damage due to extreme events, such as storm surges and tropical cyclones, is one of the major consequences of sea level rise and climate change. In fact, the IPCC has highlighted in its AR4 report that "societal impacts of sea level change primarily occur via the extreme levels rather than as a direct consequence of mean sea level changes". Over the last few decades, substantial research efforts have been directed towards improved understanding of past and future mean sea level; different scenarios were developed with process-based or semi-empirical models and used for coastal impact assessments at various spatial scales to guide coastal management and adaptation efforts. The uncertainties in future sea level rise are typically accounted for by analyzing the impacts associated with a range of scenarios leading to a vertical displacement of the distribution of extreme sea-levels. And indeed most regional and global studies find little or no evidence for changes in storminess with climate change, although there is still low confidence in the results. However, and much more importantly, there is still a limited understanding of present-day extreme sea-levels which is largely ignored in most impact and adaptation analyses. The two key uncertainties stem from: (1) numerical models that are used to generate long time series of extreme sea-levels. The bias of these models varies spatially and can reach values much larger than the expected sea level rise; but it can be accounted for in most regions making use of in-situ measurements; (2) Statistical models used for determining present-day extreme sea-level exceedance probabilities. There is no universally accepted approach to obtain such values for flood risk assessments and while substantial research has explored inter-model uncertainties for mean sea level, we explore here, for the first time, inter-model uncertainties for extreme sea-levels at large spatial scales and compare them to the uncertainties in mean sea level projections.

15x optical zoom and extreme optical image stabilisation: diffraction limited integral field spectroscopy with the Oxford SWIFT spectrograph

NASA Astrophysics Data System (ADS)

Tecza, Matthias; Thatte, Niranjan; Clarke, Fraser; Lynn, James; Freeman, David; Roberts, Jennifer; Dekany, Richard

2012-09-01

When commissioned in November 2008 at the Palomar 200 inch Hale Telescope, the Oxford SWIFT I and z band integral field spectrograph, fed by the adaptive optics system PALAO, provided a wide (3×) range of spatial resolutions: three plate scales of 235 mas, 160 mas, and 80 mas per spaxel over a contiguous field-of-view of 89×44 pixels. Depending on observing conditions and guide star brightness we can choose a seeing limited scale of 235 mas per spaxel, or 160 mas and 80 mas per spaxel for very bright guide star AO with substantial increase of enclosed energy. Over the last two years PALAO was upgraded to PALM-3000: an extreme, high-order adaptive optics system with two deformable mirrors with more than 3000 actuators, promising diffraction limited performance in SWIFT's wavelength range. In order to take advantage of this increased spatial resolution we upgraded SWIFT with new pre-optics allowing us to spatially Nyquist sample the diffraction limited PALM-3000 point spread function with 16 mas resolution, reducing the spaxel scale by another factor of 5×. We designed, manufactured, integrated and tested the new pre-optics in the first half of 2011 and commissioned it in December 2011. Here we present the opto-mechanical design and assembly of the new scale changing optics, as well as laboratory and on-sky commissioning results. In optimal observing conditions we achieve substantial Strehl ratios, delivering the near diffraction limited spatial resolution in the I and z bands.

Heating-insensitive scale increase caused by convective precipitation

NASA Astrophysics Data System (ADS)

Haerter, Jan; Moseley, Christopher; Berg, Peter

2017-04-01

The origin of intense convective extremes and their unusual temperature dependence has recently challenged traditional thermodynamic arguments, based on the Clausius-Clapeyron relation. In a sequence of studies (Lenderink and v. Mejgaard, Nat Geosc, 2008; Berg, Haerter, Moseley, Nat Geosc, 2013; and Moseley, Hohenegger, Berg, Haerter, Nat Geosc, 2016) the argument of convective-type precipitation overcoming the 7%/K increase in extremes by dynamical, rather than thermodynamic, processes has been promoted. How can the role of dynamical processes be approached for precipitating convective cloud? One-phase, non-precipitating Rayleigh-Bénard convection is a classical problem in complex systems science. When a fluid between two horizontal plates is sufficiently heated from below, convective rolls spontaneously form. In shallow, non-precipitating atmospheric convection, rolls are also known to form under specific conditions, with horizontal scales roughly proportional to the boundary layer height. Here we explore within idealized large-eddy simulations, how the scale of convection is modified, when precipitation sets in and intensifies in the course of diurnal solar heating. Before onset of precipitation, Bénard cells with relatively constant diameter form, roughly on the scale of the atmospheric boundary layer. We find that the onset of precipitation then signals an approximately linear (in time) increase in horizontal scale. This scale increase progresses at a speed which is rather insensitive to changes in surface temperature or changes in the rate at which boundary conditions change, hinting at spatial characteristics, rather than temperature, as a possible control on spatial scales of convection. When exploring the depth of spatial correlations, we find that precipitation onset causes a sudden disruption of order and a subsequent complete disintegration of organization —until precipitation eventually ceases. Returning to the initial question of convective extremes, we conclude that the formation of extreme events is a highly nonlinear process. However, our results suggest that crucial features of convective organization throughout the day may be independent of temperature - with possible implications for large-scale model parameterizations. Yet, the timing of the onset of initial precipitation depends strongly on the temperature boundary conditions, where higher temperatures, or earlier, moderate heating, lead to earlier initiation of convection and hence allow for more time for development and the production of extremes.

A flexible cure rate model for spatially correlated survival data based on generalized extreme value distribution and Gaussian process priors.

PubMed

Li, Dan; Wang, Xia; Dey, Dipak K

2016-09-01

Our present work proposes a new survival model in a Bayesian context to analyze right-censored survival data for populations with a surviving fraction, assuming that the log failure time follows a generalized extreme value distribution. Many applications require a more flexible modeling of covariate information than a simple linear or parametric form for all covariate effects. It is also necessary to include the spatial variation in the model, since it is sometimes unexplained by the covariates considered in the analysis. Therefore, the nonlinear covariate effects and the spatial effects are incorporated into the systematic component of our model. Gaussian processes (GPs) provide a natural framework for modeling potentially nonlinear relationship and have recently become extremely powerful in nonlinear regression. Our proposed model adopts a semiparametric Bayesian approach by imposing a GP prior on the nonlinear structure of continuous covariate. With the consideration of data availability and computational complexity, the conditionally autoregressive distribution is placed on the region-specific frailties to handle spatial correlation. The flexibility and gains of our proposed model are illustrated through analyses of simulated data examples as well as a dataset involving a colon cancer clinical trial from the state of Iowa. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2014-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2015-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

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.

Total ozone patterns over the southern mid-latitudes: spatial correlations, extreme events and dynamical contributions

NASA Astrophysics Data System (ADS)

Rieder, Harald E.; di Rocco, Stefania; Staehelin, Johannes; Maeder, Jörg A.; Ribatet, Mathieu; Peter, Thomas; Davison, Anthony C.

2010-05-01

Tools from geostatistics and extreme value theory are applied to analyze spatial correlations in total ozone for the southern mid-latitudes. The dataset used in this study is the NIWA-assimilated total ozone dataset (Bodeker et al., 2001; Müller et al., 2008). Recently new tools from extreme value theory (Coles, 2001; Ribatet, 2007) have been applied to the world's longest total ozone record from Arosa, Switzerland (e.g. Staehelin 1998a,b) and 5 other long-term ground based stations to describe extreme events in low and high total ozone (Rieder et al., 2010a,b,c). 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 lead 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 of such fingerprints than conventional time series analysis on basis of annual and seasonal mean values. Especially, the 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,c). Within the current study patterns in spatial correlation and frequency distributions of extreme events (e.g. ELOs and EHOs) are studied for the southern mid-latitudes. It is analyzed if "fingerprints"found for features in the northern hemisphere occur also in the southern mid-latitudes. New insights in spatial patterns of total ozone for the southern mid-latitudes are presented. Within this study the influence of changes in atmospheric dynamics (e.g. tropospheric and lower stratospheric pressure systems, ENSO) as well as influence of major volcanic eruptions (e.g. Mt. Pinatubo) and ozone depleting substances (ODS) on column ozone over the southern mid-latitudes is analyzed for the time period 1979-2007. References: Bodeker, G.E., J.C. Scott, K. Kreher, and R.L. McKenzie, Global ozone trends in potential vorticity coordinates using TOMS and GOME intercompared against the Dobson network: 1978-1998, J. Geophys. Res., 106 (D19), 23029-23042, 2001. Coles, S.: An Introduction to Statistical Modeling of Extreme Values, Springer Series in Statistics, ISBN:1852334592, Springer, Berlin, 2001. Müller, R., Grooß, J.-U., Lemmen, C., Heinze, D., Dameris, M., and Bodeker, G.: Simple measures of ozone depletion in the polar stratosphere, Atmos. Chem. Phys., 8, 251-264, 2008. 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.M., 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., 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, 1998a. 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, 1998b.

Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

Extreme cyclone events in the Arctic during wintertime: Variability and Trends

NASA Astrophysics Data System (ADS)

Rinke, Annette; Maturilli, Marion; Graham, Robert; Matthes, Heidrun; Handorf, Doerthe; Cohen, Lana; Hudson, Stephen; Moore, John

2017-04-01

Extreme cyclone events are of significant interest as they can transport much heat, moisture, and momentum poleward. Associated impacts are warming and sea-ice breakup. Recently, several examples of such extreme weather events occurred in winter (e.g. during the N-ICE2015 campaign north of Svalbard and the Frank North Atlantic storm during the end of December 2015). With Arctic amplification and associated reduced sea-ice cover and warmer sea surface temperatures, the occurrence of extreme cyclones events could be a plausible scenario. We calculate the spatial patterns, and changes and trends of the number of extreme cyclone events in the Arctic based on ERA-Interim six-hourly sea level pressure (SLP) data for winter (November-February) 1979-2015. Further, we analyze the SLP data from the Ny Alesund station for the same 37 year period. We define an extreme cyclone event by a extreme low central pressure (SLP below 985 hPa, which is the 5th percentile of the Ny Alesund/N-ICE2015 SLP data) and a deepening of at least 6 hPa/6 hours. Areas of highest frequency of occurrence of extreme cyclones are south/southeast of Greenland (corresponding to the Islandic low), between Norway and Svalbard and in the Barents/Kara Seas. The time series of the number of occurrence of extreme cyclone events for Ny Alesund/N-ICE show considerable interannual variability. The trend is not consistent through the winter, but we detect an increase in early winter and a slight decrease in late winter. The former is due to the increased occurrence of longer events at the expense of short events. Furthermore, the difference patterns of the frequency of events for months following the September with high and low Arctic sea-ice extent ("Low minus high sea ice") conforms with the change patterns of extreme cyclones numbers (frequency of events "2000-2015 minus 1979-1994") and with the trend patterns. This indicates that the changes in extreme cyclone occurrence in early winter are associated with sea-ice changes (regional feedback). In contrast, different mechanisms via large-scale circulation changes/teleconnections seem to play a role in late winter.

[Life forms of organisms as patterns of organization and spatial ecological factors].

PubMed

Kirpotin, S N

2005-01-01

Tectological and archaetectonical approaches which are conventionally used in morphology are discussed. The similarity of these approaches to some views on the structure and organization of nature systems was shown. These wiews were originated within the framework of the modern system-cybernetic conception. The morphology particularities of natural object of any rank (from organism to biosphere) allow determination of environment influence character. In some cases intensity of the influence can be determined. This, morphological-geometrical approach of nature investigation acquires high prognostic value. The aspects of "pattern organization" concept and its perspectives are discussed. The patterns of organization of organisms could be characterized only in the context of their interactions with environment. Therefore it is necessary to distinguish new group of ecological factors: spatial or chorological one. It was suggested that spatial ecological factors is predominant if all other physical factors have no extreme values.

Arterial imaging in patients with lower extremity ischemia and diabetes mellitus.

PubMed

Pomposelli, Frank

2010-09-01

Precise, comprehensive imaging of the arterial circulation is the cornerstone of successful revascularization of the ischemic extremity in patients with diabetes mellitus. Arterial imaging is challenging in these patients because the disease is often multisegmental with a predilection for the distal tibial and peroneal arteries. Occlusive lesions and the arterial wall itself are often calcified and patients presenting with ischemic complications frequently have underlying renal insufficiency. Intra-arterial digital subtraction angiography (DSA), contrast enhanced magnetic resonance angiography (MRA), and more recently, computerized tomographic angiography (CTA) have been used as imaging modalities in lower extremity ischemia. Each has specific advantages and shortcomings in this patient population, which will be summarized and contrasted in this review. DSA is an invasive technique most often performed from a femoral arterial puncture and requires the injection of arterial contrast, which can occasionally cause allergic reactions. In patients with pre-existing renal insufficiency, contrast infusion can result in worsening renal failure; although usually self-limited, it may occasionally require hemodialysis, especially in patients with diabetes. However, DSA provides the highest degree of spatial resolution and image quality. It is also the only modality in which the diagnosis and treatment of arterial disease can be performed simultaneously. MRA is noninvasive, and when enhanced with gadolinium contrast injection provides arterial images of comparable quality to DSA and in some circumstances may uncover distal arterial targets not visualized on DSA. However, spatial resolution is inferior to DSA and erroneous interpretations due to acquisition artifacts are common. Specialized equipment and imaging techniques are necessary to minimize their occurrence in the distal lower extremity. In addition, due to the risk of inducing nephrogenic systemic fibrosis, gadolinium-enhanced MRA cannot be used in patients with renal insufficiency. CTA is noninvasive and rapidly performed, with better spatial resolution than MRA, but requires the largest volume of contrast infusion, exposes patients to high-doses of radiation, and is subject to interpretive error due to reconstruction artifacts especially in heavily calcified arteries, limiting its usefulness in many patients with diabetes. For patients in whom the planned intervention is a surgical bypass, DSA and MRA will provide high quality images of the lower extremity arterial anatomy. For patients in whom a catheter-based intervention is the likely treatment, a diagnostic DSA immediately followed by a catheter-based treatment in the same procedure is the preferred approach. In patients with pre-existing renal dysfunction, in which gadolinium-enhanced MRA is contraindicated, DSA or CTA can be performed. However, patients should have an infusion of intravenous normal saline solution or sodium bicarbonate before the procedure to reduce the incidence of contrast-induced nephropathy. Copyright © 2010. Published by Mosby, Inc.

Assessing Potential Future Carbon Dynamics with Climate Change and Fire Management in a Mountainous Landscape on the Olympic Peninsula, Washington, USA

NASA Astrophysics Data System (ADS)

Kennedy, R. S.

2010-12-01

Forests of the mountainous landscapes of the maritime Pacific Northwestern USA may have high carbon sequestration potential via their high productivity and moderate to infrequent fire regimes. With climate change, there may be shifts in incidence and severity of fire, especially in the drier areas of the region, via changes to forest productivity and hydrology, and consequent effects to C sequestration and forest structure. To explore this issue, I assessed potential effects of fire management (little fire suppression/wildland fire management/highly effective fire suppression) under two climate change scenarios on future C sequestration dynamics (amounts and spatial pattern) in Olympic National Park, WA, over a 500-year simulation period. I used the simulation platform FireBGCv2, which contains a mechanistic, individual tree succession model, a spatially explicit climate-based biophysical model that uses daily weather data, and a spatially explicit fire model incorporating ignition, spread, and effects on ecosystem components. C sequestration patterns varied over time and spatial and temporal patterns differed somewhat depending on the climate change scenario applied and the fire management methods employed. Under the more extreme climate change scenario with little fire suppression, fires were most frequent and severe and C sequestration decreased. General trends were similar under the more moderate climate change scenario, as compared to current climate, but spatial patterns differed. Both climate change scenarios under highly effective fire suppression showed about 50% of starting total C after the initial transition phase, whereas with 10% fire suppression both scenarios exhibited about 10% of starting amounts. Areas of the landscape that served as refugia for older forest under increasing frequency of high severity fire were also hotspots for C sequestration in a landscape experiencing increasing frequency of disturbance with climate change.

Consequences of the river valley bottom transformation after extreme flood (on the example of the Niida River, Japan)

NASA Astrophysics Data System (ADS)

Botavin, D.; Golosov, V.; Konoplev, A.; Wakiyama, Y.

2018-01-01

Detailed study of different sections of floodplain was undertaken in the Niida River basin (Fukushima Prefecture) after an extreme flood event which occurred in the middle of September 2015. The upstream part of the basin is located in the area with very high level of radionuclide contamination after the accident at Fukushima Dai-ichi NPP. Field and GIS methods were used, including direct measurement of the depth of fresh sediment and its area, with soil descriptions for the typical floodplain sections, measurement of dose rates, interpretation of space images for a few time intervals (before and after flood event) with the following evaluation of spatial changes in deposition for different floodplain sections. In addition, results of quantitative assessment of sedimentation rates and soil radionuclide contamination were applied for understanding the effect of extreme flood on alluvial soils of the different sections. It was established that the maximum sedimentation rates (20-50 cm/event) occurred in the middle part of the lower reach of the Niida River and in some locations of the upper reaches. Dose rates had reduced considerably for all the areas with high sedimentation because the top soil layers with high radionuclide contamination were buried under fresh sediments produced mostly due to bank erosion and mass movements.

Modes of Visual Recognition and Perceptually Relevant Sketch-based Coding for Images

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1991-01-01

A review of visual recognition studies is used to define two levels of information requirements. These two levels are related to two primary subdivisions of the spatial frequency domain of images and reflect two distinct different physical properties of arbitrary scenes. In particular, pathologies in recognition due to cerebral dysfunction point to a more complete split into two major types of processing: high spatial frequency edge based recognition vs. low spatial frequency lightness (and color) based recognition. The former is more central and general while the latter is more specific and is necessary for certain special tasks. The two modes of recognition can also be distinguished on the basis of physical scene properties: the highly localized edges associated with reflectance and sharp topographic transitions vs. smooth topographic undulation. The extreme case of heavily abstracted images is pursued to gain an understanding of the minimal information required to support both modes of recognition. Here the intention is to define the semantic core of transmission. This central core of processing can then be fleshed out with additional image information and coding and rendering techniques.

Integration of modern statistical tools for the analysis of climate extremes into the web-GIS “CLIMATE”

NASA Astrophysics Data System (ADS)

Ryazanova, A. A.; Okladnikov, I. G.; Gordov, E. P.

2017-11-01

The frequency of occurrence and magnitude of precipitation and temperature extreme events show positive trends in several geographical regions. These events must be analyzed and studied in order to better understand their impact on the environment, predict their occurrences, and mitigate their effects. For this purpose, we augmented web-GIS called “CLIMATE” to include a dedicated statistical package developed in the R language. The web-GIS “CLIMATE” is a software platform for cloud storage processing and visualization of distributed archives of spatial datasets. It is based on a combined use of web and GIS technologies with reliable procedures for searching, extracting, processing, and visualizing the spatial data archives. The system provides a set of thematic online tools for the complex analysis of current and future climate changes and their effects on the environment. The package includes new powerful methods of time-dependent statistics of extremes, quantile regression and copula approach for the detailed analysis of various climate extreme events. Specifically, the very promising copula approach allows obtaining the structural connections between the extremes and the various environmental characteristics. The new statistical methods integrated into the web-GIS “CLIMATE” can significantly facilitate and accelerate the complex analysis of climate extremes using only a desktop PC connected to the Internet.

Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes

PubMed Central

Immerzeel, W. W.; Kraaijenbrink, P. D. A.; Shrestha, A. B.; Bierkens, M. F. P.

2016-01-01

The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin’s water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members. PMID:27828994

Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes.

PubMed

Lutz, A F; Immerzeel, W W; Kraaijenbrink, P D A; Shrestha, A B; Bierkens, M F P

2016-01-01

The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin's water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members.

Dynamical structure of extreme ultraviolet macrospicules

NASA Technical Reports Server (NTRS)

Karovska, Margarita; Habbal, Shadia Rifai

1994-01-01

We describe the substructures forming the macrospicules and their temporal evolution, as revealed by the application of an image enhancement algorithm to extreme ultraviolet (EUV) observations of macrospicules. The enhanced images uncover, for the first time, the substructures forming the column-like structures within the macrospicules and the low-lying arches at their base. The spatial and temporal evolution of macrospicules clearly show continuous interaction between these substructures with occasional ejection of plasma following a ballistic trajectory. We comment on the importance of these results for planning near future space observations of macrospicules with better temporal and spatial resolution.

Characterization and imaging of nanostructured materials using tabletop extreme ultraviolet light sources

NASA Astrophysics Data System (ADS)

Karl, Robert; Knobloch, Joshua; Frazer, Travis; Tanksalvala, Michael; Porter, Christina; Bevis, Charles; Chao, Weilun; Abad Mayor, Begoña.; Adams, Daniel; Mancini, Giulia F.; Hernandez-Charpak, Jorge N.; Kapteyn, Henry; Murnane, Margaret

2018-03-01

Using a tabletop coherent extreme ultraviolet source, we extend current nanoscale metrology capabilities with applications spanning from new models of nanoscale transport and materials, to nanoscale device fabrication. We measure the ultrafast dynamics of acoustic waves in materials; by analyzing the material's response, we can extract elastic properties of films as thin as 11nm. We extend this capability to a spatially resolved imaging modality by using coherent diffractive imaging to image the acoustic waves in nanostructures as they propagate. This will allow for spatially resolved characterization of the elastic properties of non-isotropic materials.

High Contrast Imaging in the Visible: First Experimental Results at the Large Binocular Telescope

NASA Astrophysics Data System (ADS)

Pedichini, F.; Stangalini, M.; Ambrosino, F.; Puglisi, A.; Pinna, E.; Bailey, V.; Carbonaro, L.; Centrone, M.; Christou, J.; Esposito, S.; Farinato, J.; Fiore, F.; Giallongo, E.; Hill, J. M.; Hinz, P. M.; Sabatini, L.

2017-08-01

In 2014 February, the System for High contrast And coronography from R to K at VISual bands (SHARK-VIS) Forerunner, a high contrast experimental imager operating at visible wavelengths, was installed at the Large Binocular Telescope (LBT). Here we report on the first results obtained by recent on-sky tests. These results show the extremely good performance of the LBT Extreme Adaptive Optics (ExAO) system at visible wavelengths, both in terms of spatial resolution and contrast achieved. Similarly to what was done by Amara & Quanz (2012), we used the SHARK-VIS Forerunner data to quantitatively assess the contrast enhancement. This is done by injecting several different synthetic faint objects in the acquired data and applying the angular differential imaging (ADI) technique. A contrast of the order of 5 × 10-5 is obtained at 630 nm for angular separations from the star larger than 100 mas. These results are discussed in light of the future development of SHARK-VIS and compared to those obtained by other high contrast imagers operating at similar wavelengths.

Bayesian quantitative precipitation forecasts in terms of quantiles

NASA Astrophysics Data System (ADS)

Bentzien, Sabrina; Friederichs, Petra

2014-05-01

Ensemble prediction systems (EPS) for numerical weather predictions on the mesoscale are particularly developed to obtain probabilistic guidance for high impact weather. An EPS not only issues a deterministic future state of the atmosphere but a sample of possible future states. Ensemble postprocessing then translates such a sample of forecasts into probabilistic measures. This study focus on probabilistic quantitative precipitation forecasts in terms of quantiles. Quantiles are particular suitable to describe precipitation at various locations, since no assumption is required on the distribution of precipitation. The focus is on the prediction during high-impact events and related to the Volkswagen Stiftung funded project WEX-MOP (Mesoscale Weather Extremes - Theory, Spatial Modeling and Prediction). Quantile forecasts are derived from the raw ensemble and via quantile regression. Neighborhood method and time-lagging are effective tools to inexpensively increase the ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Since an EPS provides a large amount of potentially informative predictors, a variable selection is required in order to obtain a stable statistical model. A Bayesian formulation of quantile regression allows for inference about the selection of predictive covariates by the use of appropriate prior distributions. Moreover, the implementation of an additional process layer for the regression parameters accounts for spatial variations of the parameters. Bayesian quantile regression and its spatially adaptive extension is illustrated for the German-focused mesoscale weather prediction ensemble COSMO-DE-EPS, which runs (pre)operationally since December 2010 at the German Meteorological Service (DWD). Objective out-of-sample verification uses the quantile score (QS), a weighted absolute error between quantile forecasts and observations. The QS is a proper scoring function and can be decomposed into reliability, resolutions and uncertainty parts. A quantile reliability plot gives detailed insights in the predictive performance of the quantile forecasts.

Spatial interpolation quality assessments for soil sensor transect datasets

USDA-ARS?s Scientific Manuscript database

Near-ground geophysical soil sensors provide extremely valuable information for precision agriculture applications. Indeed, their readings can be used as proxy for many soil parameters. Typically, leave-one-out (loo) cross-validation (CV) of spatial interpolation of sensor data returns overly optimi...

TEMPLATES: Targeting Extremely Magnified Panchromatic Lensed Arcs and Their Extended Star formation

NASA Astrophysics Data System (ADS)

Spilker, Justin; Rigby, Jane R.; Vieira, Joaquin D.; TEMPLATES Team

2018-06-01

TEMPLATES is a JWST Early Release Science program designed to produce high signal-to-noise imaging and IFU spectroscopic data cubes for four gravitationally lensed galaxies at high redshift. The program will spatially resolve the star formation in galaxies across the peak of cosmic star formation in an extinction-robust manner. Lensing magnification pushes JWST to the highest spatial resolutions possible at these redshifts, to map the key spectral diagnostics of star formation and dust extinction: H-alpha, Pa-alpha, and 3.3um PAH emission within individual distant galaxies. Our targets are among the brightest, best-characterized lensed systems known, and include both UV-bright 'normal' galaxies and heavily dust-obscured submillimeter galaxies, at a range of stellar masses and luminosities. I will describe the scientific motivation for this program, detail the targeted galaxies, and describe the planned data products to be delivered to the community in advance of JWST Cycle 2.

The chilling truth about the solar chromosphere

NASA Astrophysics Data System (ADS)

Ayres, Thomas R.

The notion that much of the solar gas in the low chromosphere is cool is discussed in terms of its validity. The dark CO absorption cores recorded at the extreme limb of the sun are described, including the 3-2 R14 line with a core-brightness temperature of 3620 K. A bifurcation in the plasma energy balance described to explain the high altitude cold gas is reviewed in terms of recent investigations. Spectral simulations of CO are described which examine the range of thermal profiles allowed by CO observations with low spatial resolution and limb darkening. Weak emission shoulders in the K line demonstrate that a cool chromosphere with Ca II emission is feasible, although the cold gas requires a surface coverage of as little as 20 percent to reproduce the limb darkening. To distinguish between the thermal bifurcation notion and the neophotosphere concept, observations of the high spatial resolution spectra of the CO bands are required.

Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data

NASA Astrophysics Data System (ADS)

Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar

2012-10-01

Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.

Intrapersonal, interpersonal, and physical space in anorexia nervosa: a virtual reality and repertory grid investigation.

PubMed

Cipolletta, Sabrina; Malighetti, Clelia; Serino, Silvia; Riva, Giuseppe; Winter, David

2017-06-01

Anorexia nervosa (AN) is an eating disorder characterized by severe body image disturbances. Recent studies from spatial cognition showed a connection between the experience of body and of space. The objectives of this study were to explore the meanings that characterize AN experience and to deepen the examination of spatiality in relational terms, through the study of how the patient construes herself and her interpersonal world. More specifically this study aimed (1) to verify whether spatial variables and aspects of construing differentiate patients with AN and healthy controls (HCs) and are related to severity of anorexic symptomatology; (2) to explore correlations between impairments in spatial abilities and interpersonal construing. A sample of 12 AN patients and 12 HCs participated in the study. The Eating Disorder Inventory, a virtual reality-based procedure, traditional measures of spatial abilities, and repertory grids were administered. The AN group compared to HCs showed significant impairments in spatial abilities, more unidimensional construing, and more extreme construing of the present self and of the self as seen by others. All these dimensions correlated with the severity of symptomatology. Extreme ways of construing characterized individuals with AN and might represent the interpersonal aspect of impairment in spatial reference frames. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Simulating observations with HARMONI: the integral field spectrograph for the European Extremely Large Telescope

NASA Astrophysics Data System (ADS)

Zieleniewski, Simon; Thatte, Niranjan; Kendrew, Sarah; Houghton, Ryan; Tecza, Matthias; Clarke, Fraser; Fusco, Thierry; Swinbank, Mark

2014-07-01

With the next generation of extremely large telescopes commencing construction, there is an urgent need for detailed quantitative predictions of the scientific observations that these new telescopes will enable. Most of these new telescopes will have adaptive optics fully integrated with the telescope itself, allowing unprecedented spatial resolution combined with enormous sensitivity. However, the adaptive optics point spread function will be strongly wavelength dependent, requiring detailed simulations that accurately model these variations. We have developed a simulation pipeline for the HARMONI integral field spectrograph, a first light instrument for the European Extremely Large Telescope. The simulator takes high-resolution input data-cubes of astrophysical objects and processes them with accurate atmospheric, telescope and instrumental effects, to produce mock observed cubes for chosen observing parameters. The output cubes represent the result of a perfect data reduc- tion process, enabling a detailed analysis and comparison between input and output, showcasing HARMONI's capabilities. The simulations utilise a detailed knowledge of the telescope's wavelength dependent adaptive op- tics point spread function. We discuss the simulation pipeline and present an early example of the pipeline functionality for simulating observations of high redshift galaxies.

Observed and simulated hydrologic response for a first-order catchment during extreme rainfall 3 years after wildfire disturbance

USGS Publications Warehouse

Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.

2016-01-01

Hydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., <1 ha) in Colorado, USA that had previously been burned by a wildfire in 2010. We compared measurements of soil-hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire-affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil-hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire-affected headwater catchment by the infiltration-excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil-hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil-hydraulic property parameterizations produced longer duration but lower peak-flow infiltration-excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near-channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.

Pathways for Energization of Ca in Mercury's Exosphere

NASA Technical Reports Server (NTRS)

Killen, Rosemary M.

2015-01-01

We investigate the possible pathways to produce the extreme energy observed in the calcium exosphere of Mercury. Any mechanism must explain the facts that Ca in Mercury's exosphere is extremely hot, that it is seen almost exclusively on the dawnside of the planet, and that its content varies seasonally, not sporadically. Simple diatomic molecules or their clusters are considered, focusing on calcium oxides while acknowledging that Ca sulfides may also be the precursor molecules. We first discuss impact vaporization to justify the assumption that CaO and Ca-oxide clusters are expected from impacts on Mercury. Then we discuss processes by which the atomic Ca is energized to a 70,000 K gas. The processes considered are (1) electron-impact dissociation of CaO molecules, (2) spontaneous dissociation of Ca-bearing molecules following impact vaporization, (3) shock-induced dissociative ionization, (4) photodissociation and (5) sputtering. We conclude that electron-impact dissociation cannot produce the required abundance of Ca, and sputtering cannot reproduce the observed spatial and temporal variation that is measured. Spontaneous dissociation is unlikely to result in the high energy that is seen. Of the two remaining processes, shock induced dissociative ionization produces the required energy and comes close to producing the required abundance, but rates are highly dependent on the incoming velocity distribution of the impactors. Photodissociation probably can produce the required abundance of Ca, but simulations show that photodissociation cannot reproduce the observed spatial distribution.

Jet formation in cerium metal to examine material strength

DOE PAGES

Jensen, B. J.; Cherne, F. J.; Prime, M. B.; ...

2015-11-18

Examining the evolution of material properties at extreme conditions advances our understanding of numerous high-pressure phenomena from natural events like meteorite impacts to general solid mechanics and fluid flow behavior. Some recent advances in synchrotron diagnostics coupled with dynamic compression platforms have introduced new possibilities for examining in-situ, spatially resolved material response with nanosecond time resolution. In this work, we examined jet formation from a Richtmyer-Meshkov instability in cerium initially shocked into a transient, high-pressure phase, and then released to a low-pressure, higher-temperature state. Cerium's rich phase diagram allows us to study the yield stress following a shock induced solid-solidmore » phase transition. X-ray imaging was used to obtain images of jet formation and evolution with 2–3 μm spatial resolution. And from these images, an analytic method was used to estimate the post-shock yield stress, and these results were compared to continuum calculations that incorporated an experimentally validated equation-of-state (EOS) for cerium coupled with a deviatoric strength model. Reasonable agreement was observed between the calculations and the data illustrating the sensitivity of jet formation on the yield stress values. Finally, the data and analysis shown here provide insight into material strength during dynamic loading which is expected to aid in the development of strength aware multi-phase EOS required to predict the response of matter at extreme conditions.« less

Characteristics of digital micromirror projection for 3D shape measurement at extreme speed

NASA Astrophysics Data System (ADS)

Höfling, Roland; Aswendt, Petra; Leischnig, Frank; Förster, Matthias

2015-03-01

3D shape measurement is one of the growing industrial applications of the Texas Instruments DLP® micro-mirror device. This paper presents investigations on precision and repeatability of that spatial light modulators output when it is driven up to its high-speed limit. The study concerns the basic switching behavior of the individual micro-mirror at different frame rates ranging over three orders of magnitude. The 3D shape measuring methodologies are focused on phase encoded triangulation, i.e. the projection of sinusoidal patterns. The DLP chip is a bi-stable device providing an on/off pattern at each certain moment in time, i.e. it has a native binary output. Sinusoidal patterns are the result of either a temporal integration of multiple on/off patterns or a spatial integration within one on/off pattern. Both approaches are studied experimentally with respect to precision and stability of the pattern output. The STAR-07 industrial projection unit, based upon the 0.7" DLP Discovery™4100 chipset, has been used for this work and the pattern frame rates cover the range from 225 frames per second (fps) to 50,000 fps. The STAR-07 output is detected by a photodiode, amplified, and analyzed in a Yokogawa digital storage oscilloscope. All results prove the very high precision and repeatability of the STAR-07 pattern projection, up to the extreme speed of 50,000 fps.

Predictions of extreme precipitation and sea-level rise under climate change.

PubMed

Senior, C A; Jones, R G; Lowe, J A; Durman, C F; Hudson, D

2002-07-15

Two aspects of global climate change are particularly relevant to river and coastal flooding: changes in extreme precipitation and changes in sea level. In this paper we summarize the relevant findings of the IPCC Third Assessment Report and illustrate some of the common results found by the current generation of coupled atmosphere-ocean general circulation models (AOGCMs), using the Hadley Centre models. Projections of changes in extreme precipitation, sea-level rise and storm surges affecting the UK will be shown from the Hadley Centre regional models and the Proudman Oceanographic Laboratory storm-surge model. A common finding from AOGCMs is that in a warmer climate the intensity of precipitation will increase due to a more intense hydrological cycle. This leads to reduced return periods (i.e. more frequent occurrences) of extreme precipitation in many locations. The Hadley Centre regional model simulates reduced return periods of extreme precipitation in a number of flood-sensitive areas of the UK. In addition, simulated changes in storminess and a rise in average sea level around the UK lead to reduced return periods of extreme high coastal water events. The confidence in all these results is limited by poor spatial resolution in global coupled models and by uncertainties in the physical processes in both global and regional models, and is specific to the climate change scenario used.

North Atlantic storm driving of extreme wave heights in the North Sea

NASA Astrophysics Data System (ADS)

Bell, R. J.; Gray, S. L.; Jones, O. P.

2017-04-01

The relationship between storms and extreme ocean waves in the North Sea is assessed using a long-period wave data set and storms identified in the Interim ECMWF Re-Analysis (ERA-Interim). An ensemble sensitivity analysis is used to provide information on the spatial and temporal forcing from mean sea-level pressure and surface wind associated with extreme ocean wave height responses. Extreme ocean waves in the central North Sea arise due to intense extratropical cyclone winds from either the cold conveyor belt (northerly-wind events) or the warm conveyor belt (southerly-wind events). The largest wave heights are associated with northerly-wind events which tend to have stronger wind speeds and occur as the cold conveyor belt wraps rearward round the cyclone to the cold side of the warm front. The northerly-wind events provide a larger fetch to the central North Sea to aid wave growth. Southerly-wind events are associated with the warm conveyor belts of intense extratropical cyclones that develop in the left upper tropospheric jet exit region. Ensemble sensitivity analysis can provide early warning of extreme wave events by demonstrating a relationship between wave height and high pressure to the west of the British Isles for northerly-wind events 48 h prior. Southerly-wind extreme events demonstrate sensitivity to low pressure to the west of the British Isles 36 h prior.

Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications

NASA Astrophysics Data System (ADS)

Venäläinen, Ari; Laapas, Mikko; Pirinen, Pentti; Horttanainen, Matti; Hyvönen, Reijo; Lehtonen, Ilari; Junila, Päivi; Hou, Meiting; Peltola, Heli M.

2017-07-01

The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount) of wind damage for certain forest stand configurations.

Ensemble catchment hydrological modelling for climate change impact analysis

NASA Astrophysics Data System (ADS)

Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

2014-05-01

It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions, more than in high flow conditions. Hence, the mechanism of the slow flow component simulation requires further attention. It is concluded that a multi-model ensemble approach where different plausible model structures are applied, is extremely useful. It improves the reliability of climate change impact results and allows decision making to be based on uncertainty assessment that includes model structure related uncertainties. References: Ntegeka, V., Baguis, P., Roulin, E., Willems, P., 2014. Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508C, 307-321 Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O., 2013. Climate change impact on river flows and catchment hydrology: a comparison of two spatially distributed models. Hydrological Processes, 27(25), 3649-3662. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation. Journal of Hydrology, in press. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of climate scenario impact predictions by a lumped and distributed model ensemble. Journal of Hydrology, in revision.

Patterns of gun deaths across US counties 1999-2013.

PubMed

Kalesan, Bindu; Galea, Sandro

2017-05-01

We examined the socio-demographic distribution of gun deaths across 3143 counties in 50 United States' states to understand the spatial patterns and correlates of high and low gun deaths. We used aggregate counts of gun deaths and population in all counties from 1999 to 2013 from the Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research (WONDER). We characterized four levels of gun violence, as distinct levels of gun death rates of relatively safe, unsafe, violent, and extremely violent counties, based on quartiles of 15-year county-specific gun death rates per 100,000 and used negative binomial regression models allowing clustering by state to calculate incidence rate ratios and 95% confidence intervals (95% CIs). Most states had at least one violent or extremely violent county. Extremely violent gun counties were mostly rural, poor, predominantly minority, had high unemployment rate and homicide rate. Overall, homicide rate was significantly associated with gun deaths (incidence rate ratios = 1.08, 95% CI = 1.06-1.09). In relatively safe counties, this risk was 1.09 (95% CI = 1.05-1.13) and in extremely violent gun counties was 1.03 (95% CI = 1.03-1.04). There are broad differences in gun death rates across the United States representing different levels of gun death rates in each state with distinct socio-demographic profiles. Copyright © 2017 Elsevier Inc. All rights reserved.

Future climate risk from compound events

NASA Astrophysics Data System (ADS)

Zscheischler, Jakob; Westra, Seth; van den Hurk, Bart J. J. M.; Seneviratne, Sonia I.; Ward, Philip J.; Pitman, Andy; AghaKouchak, Amir; Bresch, David N.; Leonard, Michael; Wahl, Thomas; Zhang, Xuebin

2018-06-01

Floods, wildfires, heatwaves and droughts often result from a combination of interacting physical processes across multiple spatial and temporal scales. The combination of processes (climate drivers and hazards) leading to a significant impact is referred to as a `compound event'. Traditional risk assessment methods typically only consider one driver and/or hazard at a time, potentially leading to underestimation of risk, as the processes that cause extreme events often interact and are spatially and/or temporally dependent. Here we show how a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers, who need to work closely together to understand these complex events.

Anomalies detected in Central European Temperature series reconstructed from documentary evidence and instrumental records for the last 500 years

NASA Astrophysics Data System (ADS)

Dobrovolný, P.; Brázdil, R.; Moberg, A.; Wilson, R.

2009-09-01

Various types of documentary evidence from Germany, Switzerland and the Czech Republic have been used to create temperature indices for the period 1500-1854. Homogenized temperature series from 11 Central European stations covering the period 1760-2007 served as target values to reconstruct monthly, seasonal and annual temperatures in Central Europe since AD 1500. Spatial coherency of the compiled Central European Temperature (CEuT) series is presented. The CEuT series is further used to define extremely cold/warm months and seasons and the spatial and temporal distribution of such extremes are presented in context of existing knowledge of climate variability within Europe. The CEuT extremes are compared to corresponding documentary based chronologies from other European countries or regions as well as reconstructions from other proxies (e.g. tree rings). The most pronounced cold/warm seasons are analyzed with respect to potential causes and also with respect to recent warming trends. We discuss the potential of documentary evidence to study weather and climate extremes and show that such data provide valuable information for studying past human response to climatic extremes.

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.

Evaluation of a spatial rainfall generator and an interpolation methods for the creation of future gridded data sets over complex terrains

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Michaelides, Silas; Lange, Manfred A.

2015-04-01

Space-time variability of precipitation plays a key role as a driver of many processes in different environmental fields like hydrology, ecology, biology, agriculture, and natural hazards. The objective of this study was to compare two approaches for statistical downscaling of precipitation from climate models. The study was applied to the island of Cyprus, an orographically complex terrain. The first approach makes use of a spatial temporal Neyman-Scott Rectangular Pulses (NSRP) model and a previously tested interpolation scheme (Camera et al., 2014). The second approach is based on the use of the single site NSRP model and a simplified gridded scheme based on scaling coefficients obtained from past observations. The rainfall generators were evaluated on the period 1980-2010. Both approaches were subsequently used to downscale three RCMs from the EU ENSEMBLE project to calculate climate projections (2020-2050). The main advantage of the spatial-temporal approach is that it allows creating spatially consistent daily maps of precipitation. On the other hand, due to the assumptions made using a stochastic generator based on homogeneous Poisson processes, it shows a smoothing out of all the rainfall statistics (except mean and variance) all over the study area. This leads to high errors when analyzing indices related to extremes. Examples are the number of days with rainfall over 50 mm (R50 - mean error 65%), the 95th percentile value of rainy days (RT95 - mean error 19%), and the mean annual rainfall recorded on days with rainfall above the 95th percentile (RA95 - mean error 22%). The single site approach excludes the possibility of using the created gridded data sets for case studies involving spatial connection between grid cells (e.g. hydrologic modelling), but it leads to a better reproduction of rainfall statistics and properties. The errors for the extreme indices are in fact much lower: 17% for R50, 4% for RT95, and 2% for RA95. Future projections show a decrease of the mean annual rainfall (for both approaches) over the study area between 70 mm (≈15%) and 5 mm (≈1%), in comparison to the reference period 1980-2010. Regarding extremes, calculated only with the single site approach, the projections show a decrease of the R50 index between 25% and 7%, and of the RT95 between 8% and 0%. Thus, these projections indicate that a slight reduction in the number and intensity of extremes can be expected. Further research will be done to adapt and evaluate the use of a spatial-temporal generator with nonhomogeneous spatial activation of raincells (Burton et al., 2010) to the study area. Burton, A., Fowler, H.J., Kilsby, C.G., O'Connell, P. E., 2010a. A stochastic model for the spatial-temporal simulation of non-homogeneous rainfall occurrence and amounts, Water Resour. Res. 46, W11501. DOI: 10.1029/2009WR008884 Camera, C., Bruggeman, A., Hadjinicolaou, P., Pashiardis, S., Lange, M. A., 2014. Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010. J. Geophys. Res. Atmos., 119, 693-712. DOI: 10.1002/2013JD020611.

Tales from the Paleoclimate Underground: Lessons Learned from Reconstructing Extreme Events

NASA Astrophysics Data System (ADS)

Frappier, A. E.

2017-12-01

Tracing patterns of paleoclimate extremes over the past two millennia is becoming ever more important in the effort to understand and predict costly weather hazards and their varied societal impacts. I present three paleoclimate vignettes from the past ten years of different paleotempestology projects I have worked on closely, illustrating our collective challenges and productive pathways in reconstructing rainfall extremes: temporal, spatial, and combining information from disparate proxies. Finally, I aim to share new results from modeling multiple extremes and hazards in Yucatan, a climate change hotspot.

Construction and performance of MEGAs low-mass, high-rate cylindrical MWPCs

NASA Astrophysics Data System (ADS)

Cooper, M. D.; Armijo, V.; Black, J. K.; Bolton, R. D.; Carius, S.; Espinoza, C.; Hart, G.; Hogan, G. E.; Gonzales, A.; Kroupa, M. A.; Mischke, R. E.; Sandoval, J.; Schilling, S.; Sena, J.; Suazo, G.; Whitehouse, D. A.; Wilkinson, C. A.; Stantz, K.; Szymanski, J. J.; Jui, C. C.; Gagliardi, C. A.; Tribble, R. E.; Tu, X.-L.; Fisk, R. J.; Koetke, D. D.; Manweiler, R. W.; Nord, P. M.; Stanislaus, S.; Piilonen, L. E.; Zhang, Y. D.

A design for extremely low mass, high-resolution multiwire proportional chambers (MWPC) was achieved by the MEGA collaboration in its experiment to search for the lepton family number violating decay μ→eγ. To extend the present branching ratio limit by over an order of magnitude, these MWPCs were operated in high particle fluxes. They showed minimal effects of aging, and evidenced spatial and energy resolutions for the orbiting positrons from muon decay which were consistent with our design parameters. The unique features of these chambers, their assembly into the MEGA positron spectrometer, and their performance during the experiment are described in this paper.

Low LET proton microbeam to understand high-LET RBE by shaping spatial dose distribution

NASA Astrophysics Data System (ADS)

Greubel, Christoph; Ilicic, Katarina; Rösch, Thomas; Reindl, Judith; Siebenwirth, Christian; Moser, Marcus; Girst, Stefanie; Walsh, Dietrich W. M.; Schmid, Thomas E.; Dollinger, Günther

2017-08-01

High LET radiation, like heavy ions, are known to have a higher biological effectiveness (RBE) compared to low LET radiation, like X- or γ -rays. Theories and models attribute these higher effectiveness mostly to their extremely inhomogeneous dose deposition, which is concentrated in only a few micron sized spots. At the ion microprobe SNAKE, low LET 20 MeV protons (LET in water of 2.6 keV/μm) can be applied to cells either randomly distributed or focused to submicron spots, approximating heavy ion dose deposition. Thus, the transition between low and high LET energy deposition is experimentally accessible and the effect of different spatial dose distributions can be analysed. Here, we report on the technical setup to cultivate and irradiate 104 cells with submicron spots of low LET protons to measure cell survival in unstained cells. In addition we have taken special care to characterise the beam spot of the 20 MeV proton microbeam with fluorescent nuclear track detectors.

Quantitative x-ray phase imaging at the nanoscale by multilayer Laue lenses

PubMed Central

Yan, Hanfei; Chu, Yong S.; Maser, Jörg; Nazaretski, Evgeny; Kim, Jungdae; Kang, Hyon Chol; Lombardo, Jeffrey J.; Chiu, Wilson K. S.

2013-01-01

For scanning x-ray microscopy, many attempts have been made to image the phase contrast based on a concept of the beam being deflected by a specimen, the so-called differential phase contrast imaging (DPC). Despite the successful demonstration in a number of representative cases at moderate spatial resolutions, these methods suffer from various limitations that preclude applications of DPC for ultra-high spatial resolution imaging, where the emerging wave field from the focusing optic tends to be significantly more complicated. In this work, we propose a highly robust and generic approach based on a Fourier-shift fitting process and demonstrate quantitative phase imaging of a solid oxide fuel cell (SOFC) anode by multilayer Laue lenses (MLLs). The high sensitivity of the phase to structural and compositional variations makes our technique extremely powerful in correlating the electrode performance with its buried nanoscale interfacial structures that may be invisible to the absorption and fluorescence contrasts. PMID:23419650

Paleo-event data standards for dendrochronology

Treesearch

Elaine Kennedy Sutherland; P. Brewer; W. Gross

2017-01-01

Extreme environmental events, such as storm winds, landslides, insect infestations, and wildfire, cause loss of life, resources, and human infrastructure. Disaster riskreduction analysis can be improved with information about past frequency, intensity, and spatial patterns of extreme events. Tree-ring analyses can provide such information: tree rings reflect events as...

Identifying Heat Waves in Florida: Considerations of Missing Weather Data

PubMed Central

Leary, Emily; Young, Linda J.; DuClos, Chris; Jordan, Melissa M.

2015-01-01

Background Using current climate models, regional-scale changes for Florida over the next 100 years are predicted to include warming over terrestrial areas and very likely increases in the number of high temperature extremes. No uniform definition of a heat wave exists. Most past research on heat waves has focused on evaluating the aftermath of known heat waves, with minimal consideration of missing exposure information. Objectives To identify and discuss methods of handling and imputing missing weather data and how those methods can affect identified periods of extreme heat in Florida. Methods In addition to ignoring missing data, temporal, spatial, and spatio-temporal models are described and utilized to impute missing historical weather data from 1973 to 2012 from 43 Florida weather monitors. Calculated thresholds are used to define periods of extreme heat across Florida. Results Modeling of missing data and imputing missing values can affect the identified periods of extreme heat, through the missing data itself or through the computed thresholds. The differences observed are related to the amount of missingness during June, July, and August, the warmest months of the warm season (April through September). Conclusions Missing data considerations are important when defining periods of extreme heat. Spatio-temporal methods are recommended for data imputation. A heat wave definition that incorporates information from all monitors is advised. PMID:26619198

Identifying Heat Waves in Florida: Considerations of Missing Weather Data.

PubMed

Leary, Emily; Young, Linda J; DuClos, Chris; Jordan, Melissa M

2015-01-01

Using current climate models, regional-scale changes for Florida over the next 100 years are predicted to include warming over terrestrial areas and very likely increases in the number of high temperature extremes. No uniform definition of a heat wave exists. Most past research on heat waves has focused on evaluating the aftermath of known heat waves, with minimal consideration of missing exposure information. To identify and discuss methods of handling and imputing missing weather data and how those methods can affect identified periods of extreme heat in Florida. In addition to ignoring missing data, temporal, spatial, and spatio-temporal models are described and utilized to impute missing historical weather data from 1973 to 2012 from 43 Florida weather monitors. Calculated thresholds are used to define periods of extreme heat across Florida. Modeling of missing data and imputing missing values can affect the identified periods of extreme heat, through the missing data itself or through the computed thresholds. The differences observed are related to the amount of missingness during June, July, and August, the warmest months of the warm season (April through September). Missing data considerations are important when defining periods of extreme heat. Spatio-temporal methods are recommended for data imputation. A heat wave definition that incorporates information from all monitors is advised.

Contributions to Global Augmented Compound Urban Heat Extreme (ACUTE) from Climate Change and the Urban Heat Island Effect

NASA Astrophysics Data System (ADS)

Huang, K.

2017-12-01

Over the next decades, climate change is projected to increase the intensity and frequency of extreme heat events (EHEs). The severity and periodicity of these hazards are likely to be further compounded by stronger urban heat island (UHI) effects as the world continues to urbanize. However, there is little known about how greenhouse gases (GHG) induced changes in EHE will interact with UHI, and what this will mean for the exposure of urban populations to high temperature. This work aims to fill this knowledge gap by combining a mesoscale meteorological model (Weather Research Forecasting, WRF) with a global urban expansion forecast, to generate spatially explicit projections of compound urban temperature extremes through 2050. These global projections include all the urban areas in developing world. The respective contributions from GHG-induced climate change, the UHI effect, and their interaction vary across different types of urban areas. The resulting compound heat extremes will be more intense and frequent in emerging Asian and African mega urban regions, located in tropical/subtropical climates, due to their unprecedented sizes and the significantly reduced evaporation. Previous studies neglecting the interaction between global climate change and regional UHI effect have underestimated exposure to heat extremes in urban areas.

The extreme ultraviolet spectroscope for planetary science, EXCEED

NASA Astrophysics Data System (ADS)

Yoshioka, K.; Murakami, G.; Yamazaki, A.; Tsuchiya, F.; Kagitani, M.; Sakanoi, T.; Kimura, T.; Uemizu, K.; Uji, K.; Yoshikawa, I.

2013-09-01

The extreme ultraviolet spectroscope EXtrem ultraviolet spetrosCope for ExosphEric Dynamics (EXCEED) on board the SPRINT-A mission will be launched in the summer of 2013 by the new Japanese solid propulsion rocket Epsilon as its first attempt, and it will orbit around the Earth with an orbital altitude of around 1000 km. EXCEED is dedicated to and optimized for observing the terrestrial planets Mercury, Venus and Mars, as well as Jupiter for several years. The instrument consists of an off axis parabolic entrance mirror, switchable slits with multiple filters and shapes, a toroidal grating, and a photon counting detector, together with a field of view guiding camera. The design goal is to achieve a large effective area but with high spatial and spectral resolution. In this paper, the performance of each optical component will be described as determined from the results of test evaluation of flight models. In addition, the results of the optical calibration of the overall instrument are also shown. As a result, the spectral resolution of EXCEED is found to be 0.3-0.5 nm Full Width at Half Maximum (FWHM) over the entire spectral band (52-148 nm) and the spatial resolution achieve was 10". The evaluated effective area is around 3 cm2. Based on these specifications, the possibility of EXCEED detecting atmospheric ions or atoms around Mercury, Venus, and Mars will be discussed. In addition, we estimate the spectra that might be detected from the Io plasma torus around Jupiter for various hypothetical plasma parameters.

Extremal Approaches to Estimating Spatial Interaction.

DTIC Science & Technology

Two recent theoretical approaches (that of Charnes, Raike, and Bettinger (1972) and that of A . G. Wilson (1967)) to the gravity model of spatial...relationships between the two methods are demonstrated. The two approaches jointly indicate a general method of generating new hypotheses of gravity flows. This

Detection of smoothly distributed spatial outliers, with applications to identifying the distribution of parenchymal hyperinflation following an airway challenge in asthmatics.

PubMed

Thurman, Andrew L; Choi, Jiwoong; Choi, Sanghun; Lin, Ching-Long; Hoffman, Eric A; Lee, Chang Hyun; Chan, Kung-Sik

2017-05-10

Methacholine challenge tests are used to measure changes in pulmonary function that indicate symptoms of asthma. In addition to pulmonary function tests, which measure global changes in pulmonary function, computed tomography images taken at full inspiration before and after administration of methacholine provide local air volume changes (hyper-inflation post methacholine) at individual acinar units, indicating local airway hyperresponsiveness. Some of the acini may have extreme air volume changes relative to the global average, indicating hyperresponsiveness, and those extreme values may occur in clusters. We propose a Gaussian mixture model with a spatial smoothness penalty to improve prediction of hyperresponsive locations that occur in spatial clusters. A simulation study provides evidence that the spatial smoothness penalty improves prediction under different data-generating mechanisms. We apply this method to computed tomography data from Seoul National University Hospital on five healthy and ten asthmatic subjects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Winter is losing its cool

NASA Astrophysics Data System (ADS)

Feng, S.

2017-12-01

Winter seasons have significant societal impacts across all sectors ranging from direct human health to ecosystems, transportation, and recreation. This study quantifies the severity of winter and its spatial-temporal variations using a newly developed winter severity index and daily temperature, snowfall and snow depth. The winter severity and the number of extreme winter days are decreasing across the global terrestrial areas during 1901-2015 except the southeast United States and isolated regions in the Southern Hemisphere. These changes are dominated by winter warming, while the changes in daily snowfall and snow depth played a secondary role. The simulations of multiple CMIP5 climate models can well capture the spatial and temporal variations of the observed changes in winter severity and extremes during 1951-2005. The models are consistent in projecting a future milder winter under various scenarios. The winter severity is projected to decrease 60-80% in the middle-latitude Northern Hemisphere under the business-as-usual scenario. The winter arrives later, ends earlier and the length of winter season will be notably shorter. The changes in harsh winter in the polar regions are weak, mainly because the warming leads to more snowfall in the high latitudes.

Optical correlation based pose estimation using bipolar phase grayscale amplitude spatial light modulators

NASA Astrophysics Data System (ADS)

Outerbridge, Gregory John, II

Pose estimation techniques have been developed on both optical and digital correlator platforms to aid in the autonomous rendezvous and docking of spacecraft. This research has focused on the optical architecture, which utilizes high-speed bipolar-phase grayscale-amplitude spatial light modulators as the image and correlation filter devices. The optical approach has the primary advantage of optical parallel processing: an extremely fast and efficient way of performing complex correlation calculations. However, the constraints imposed on optically implementable filters makes optical correlator based posed estimation technically incompatible with the popular weighted composite filter designs successfully used on the digital platform. This research employs a much simpler "bank of filters" approach to optical pose estimation that exploits the inherent efficiency of optical correlation devices. A novel logarithmically mapped optically implementable matched filter combined with a pose search algorithm resulted in sub-degree standard deviations in angular pose estimation error. These filters were extremely simple to generate, requiring no complicated training sets and resulted in excellent performance even in the presence of significant background noise. Common edge detection and scaling of the input image was the only image pre-processing necessary for accurate pose detection at all alignment distances of interest.

Spatial Neglect Hinders Success of Inpatient Rehabilitation in Individuals With Traumatic Brain Injury: A Retrospective Study.

PubMed

Chen, Peii; Ward, Irene; Khan, Ummais; Liu, Yan; Hreha, Kimberly

2016-06-01

Background Current knowledge about spatial neglect and its impact on rehabilitation mostly originates from stroke studies. Objective To examine the impact of spatial neglect on rehabilitation outcome in individuals with traumatic brain injury (TBI). Methods The retrospective study included 156 consecutive patients with TBI (73 women; median age = 69.5 years; interquartile range = 50-81 years) at an inpatient rehabilitation facility (IRF). We examined whether the presence of spatial neglect affected the Functional Independence Measure (FIM) scores, length of stay, or discharge disposition. Based on the available medical records, we also explored whether spatial neglect was associated with tactile sensation or muscle strength asymmetry in the extremities and whether specific brain injuries or lesions predicted spatial neglect. Results In all, 30.1% (47 of 156) of the sample had spatial neglect. Sex, age, severity of TBI, or time postinjury did not differ between patients with and without spatial neglect. In comparison to patients without spatial neglect, patients with the disorder stayed in IRF 5 days longer, had lower FIM scores at discharge, improved slower in both Cognitive and Motor FIM scores, and might have less likelihood of return home. In addition, left-sided neglect was associated with asymmetric strength in the lower extremities, specifically left weaker than the right. Finally, brain injury-induced mass effect predicted left-sided neglect. Conclusions Spatial neglect is common following TBI, impedes rehabilitation progress in both motor and cognitive domains, and prolongs length of stay. Future research is needed for linking specific traumatic injuries and lesioned networks to spatial neglect and related impairment. © The Author(s) 2015.

Coastal habitat mapping in the Aegean Sea using high resolution orthophoto maps

NASA Astrophysics Data System (ADS)

Topouzelis, Konstantinos; Papakonstantinou, Apostolos; Doukari, Michaela; Stamatis, Panagiotis; Makri, Despina; Katsanevakis, Stelios

2017-09-01

The significance of coastal habitat mapping lies in the need to prevent from anthropogenic interventions and other factors. Until 2015, Landsat-8 (30m) imagery were used as medium spatial resolution satellite imagery. So far, Sentinel-2 satellite imagery is very useful for more detailed regional scale mapping. However, the use of high resolution orthophoto maps, which are determined from UAV data, is expected to improve the mapping accuracy. This is due to small spatial resolution of the orthophoto maps (30 cm). This paper outlines the integration of UAS for data acquisition and Structure from Motion (SfM) pipeline for the visualization of selected coastal areas in the Aegean Sea. Additionally, the produced orthophoto maps analyzed through an object-based image analysis (OBIA) and nearest-neighbor classification for mapping the coastal habitats. Classification classes included the main general habitat types, i.e. seagrass, soft bottom, and hard bottom The developed methodology applied at the Koumbara beach (Ios Island - Greece). Results showed that UAS's data revealed the sub-bottom complexity in large shallow areas since they provide such information in the spatial resolution that permits the mapping of seagrass meadows with extreme detail. The produced habitat vectors are ideal as reference data for studies with satellite data of lower spatial resolution.

Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

NASA Astrophysics Data System (ADS)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

Trends and periodicity of daily temperature and precipitation extremes during 1960-2013 in Hunan Province, central south China

NASA Astrophysics Data System (ADS)

Chen, Ajiao; He, Xinguang; Guan, Huade; Cai, Yi

2018-04-01

In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960-2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960-1986 and 1987-2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4-year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices. Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide significant power at the 4-year period, which are mainly found during 1970-1980 and after 1992.

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

Mapping the Decadal Spatio-temporal Variation of Social Vulnerability to Hydro-climatic Extremes over India

NASA Astrophysics Data System (ADS)

H, V.; Karmakar, S.; Ghosh, S.

2015-12-01

Human induced global warming is unequivocal and observational studies shows that, this has led to increase in the intensity and frequency of hydro-climatic extremes, most importantly precipitation extreme, heat waves and drought; and also is expected to be increased in the future. The occurrence of these extremes have a devastating effects on nation's economy and on societal well-being. Previous studies on India provided the evidences of significant changes in the precipitation extreme from pre- to post-1950, with huge spatial heterogeneity; and projections of heat waves indicated that significant part of India will experience heat stress conditions in the future. Under these circumstance, it is necessary to develop a nation-wide social vulnerability map to scrutinize the adequacy of existing emergency management. Yet there has been no systematic past efforts on mapping social vulnerability to hydro-climatic extremes at nation-wide for India. Therefore, immediate efforts are required to quantify the social vulnerability, particularly developing country like India, where major transformations in demographic characteristics and development patterns are evident during past decades. In the present study, we perform a comprehensive spatio-temporal social vulnerability analysis by considering multiple sensitive indicators for three decades (1990-2010) which identifies the hot-spots, with higher vulnerability to hydro-climatic extremes. The population datasets are procured from Census of India and the meteorological datasets are obtained from India Meteorological Department (IMD). The study derives interesting results on decadal changes of spatial distribution of risk, considering social vulnerability and hazard to extremes.

Future frequencies of extreme weather events in the National Wildlife Refuges of the conterminous U.S.

USGS Publications Warehouse

Martinuzzi, Sebastian; Allstadt, Andrew J.; Bateman, Brooke L.; Heglund, Patricia J.; Pidgeon, Anna M.; Thogmartin, Wayne E.; Vavrus, Stephen J.; Radeloff, Volker C.

2016-01-01

Climate change is a major challenge for managers of protected areas world-wide, and managers need information about future climate conditions within protected areas. Prior studies of climate change effects in protected areas have largely focused on average climatic conditions. However, extreme weather may have stronger effects on wildlife populations and habitats than changes in averages. Our goal was to quantify future changes in the frequency of extreme heat, drought, and false springs, during the avian breeding season, in 415 National Wildlife Refuges in the conterminous United States. We analyzed spatially detailed data on extreme weather frequencies during the historical period (1950–2005) and under different scenarios of future climate change by mid- and late-21st century. We found that all wildlife refuges will likely experience substantial changes in the frequencies of extreme weather, but the types of projected changes differed among refuges. Extreme heat is projected to increase dramatically in all wildlife refuges, whereas changes in droughts and false springs are projected to increase or decrease on a regional basis. Half of all wildlife refuges are projected to see increases in frequency (> 20% higher than the current rate) in at least two types of weather extremes by mid-century. Wildlife refuges in the Southwest and Pacific Southwest are projected to exhibit the fastest rates of change, and may deserve extra attention. Climate change adaptation strategies in protected areas, such as the U.S. wildlife refuges, may need to seriously consider future changes in extreme weather, including the considerable spatial variation of these changes.

Spatial variations of sea level along the coast of Thailand: Impacts of extreme land subsidence, earthquakes and the seasonal monsoon

NASA Astrophysics Data System (ADS)

Saramul, Suriyan; Ezer, Tal

2014-11-01

The study addresses two important issues associated with sea level along the coasts of Thailand: first, the fast sea level rise and its spatial variation, and second, the monsoonal-driven seasonal variations in sea level. Tide gauge data that are more extensive than in past studies were obtained from several different local and global sources, and relative sea level rise (RSLR) rates were obtained from two different methods, linear regressions and non-linear Empirical Mode Decomposition/Hilbert-Huang Transform (EMD/HHT) analysis. The results show extremely large spatial variations in RSLR, with rates varying from ~ 1 mm y-1 to ~ 20 mm y-1; the maximum RSLR is found in the upper Gulf of Thailand (GOT) near Bangkok, where local land subsidence due to groundwater extraction dominates the trend. Furthermore, there are indications that RSLR rates increased significantly in all locations after the 2004 Sumatra-Andaman Earthquake and the Indian Ocean tsunami that followed, so that recent RSLR rates seem to have less spatial differences than in the past, but with high rates of ~ 20-30 mm y-1 almost everywhere. The seasonal sea level cycle was found to be very different between stations in the GOT, which have minimum sea level in June-July, and stations in the Andaman Sea, which have minimum sea level in February. The seasonal sea-level variations in the GOT are driven mostly by large-scale wind-driven set-up/set-down processes associated with the seasonal monsoon and have amplitudes about ten times larger than either typical steric changes at those latitudes or astronomical annual tides.

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.

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

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

Ruebel, Oliver

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research coveredmore » in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle acceleration, physicists model LWFAs computationally. The datasets produced by LWFA simulations are (i) extremely large, (ii) of varying spatial and temporal resolution, (iii) heterogeneous, and (iv) high-dimensional, making analysis and knowledge discovery from complex LWFA simulation data a challenging task. To address these challenges this thesis describes the integration of the visualization system VisIt and the state-of-the-art index/query system FastBit, enabling interactive visual exploration of extremely large three-dimensional particle datasets. Researchers are especially interested in beams of high-energy particles formed during the course of a simulation. This thesis describes novel methods for automatic detection and analysis of particle beams enabling a more accurate and efficient data analysis process. By integrating these automated analysis methods with visualization, this research enables more accurate, efficient, and effective analysis of LWFA simulation data than previously possible.« less

Moisture sources and pathways associated with the spatial variability of seasonal extreme precipitation over Canada

NASA Astrophysics Data System (ADS)

Tan, Xuezhi; Gan, Thian Yew; Chen, Yongqin David

2018-01-01

Nine regions with spatially coherent seasonal 3-day total precipitation extremes across Canada were identified using a clustering method that is compliant to the extreme value theory. Using storm back-trajectory analyses, we then identified possible moisture sources and pathways that are conducive to occurrences of seasonal extreme precipitation events in four seasons for the nine regions identified. Moisture pathways for all extreme precipitation events were clustered to nine dominant moisture pathway patterns using the self-organizing map method. Results show that horizontal moisture pathway patterns and their occurrences were not evidently different between seasons. However, warm (summer and fall) and cold (winter and spring) seasons show considerable differences in the spreading of moisture sources in all nine regions, even though many sources do not frequently contribute to extreme precipitation events. In all four seasons, terrestrial evapotranspiration had provided major moisture sources to many extreme precipitation events occurred in inland regions. Central Canada had received more widespread moisture sources over surrounding oceans of North America than western and eastern Canada, because of more diverse moisture pathway patterns for central Canada that transport moisture from all surrounding oceans to central Canada. Extreme precipitation in southwestern Canada mainly resulted from atmospheric rivers over the North Pacific Ocean. For northwestern Canada, moisture pathway patterns were from the northern Pacific, Arctic and northern Atlantic oceans, even though more than 78% of trajectories for northwestern Canada were from the North Pacific. Westerlies from the North Pacific Ocean and northern polar jet streams controlled dominant pathways to central and eastern Canada. More extreme precipitation events over Canada were fed by the Arctic Ocean in warm than in cold seasons.

Moisture sources and pathways associated with the spatial variability of seasonal extreme precipitation over Canada

NASA Astrophysics Data System (ADS)

Gan, T. Y. Y.; Tan, X.; Chen, Y. D.

2017-12-01

Nine regions with spatially coherent seasonal 3-day total precipitation extremes across Canada were identified using a clustering method that is compliant to the extreme value theory. Using storm back-trajectory analyses, we then identified possible moisture sources and pathways that are conducive to occurrences of seasonal extreme precipitation events in four seasons for the nine regions identified.Moisture pathways for all extreme precipitation events were clustered to nine dominant moisture pathway patterns using the self-organizing map method. Results show that horizontal moisture pathway patterns and their occurrences were not evidently different between seasons. However, warm (summer and fall) and cold (winter and spring) seasons show considerable differences in the spreading ofmoisture sources in all nine regions, even though many sources do not frequently contribute to extreme precipitation events. In all four seasons, terrestrial evapotranspiration had provided major moisture sources to many extreme precipitation events occurred in inland regions. Central Canada had received more widespread moisture sources over surrounding oceans of North America than western and eastern Canada, because of more diverse moisture pathway patterns for central Canada that transport moisture from all surrounding oceans to central Canada. Extreme precipitation in southwestern Canada mainly resulted from atmospheric rivers over the North Pacific Ocean. For northwestern Canada, moisture pathway patterns were from the northern Pacific, Arctic and northern Atlantic oceans, even though more than 78% of trajectories for northwestern Canada were from the North Pacific. Westerlies from the North Pacific Ocean and northern polar jet streams controlled dominant pathways to central and eastern Canada. More extreme precipitation events over Canada were fed by the Arctic Ocean in warm than in cold seasons.

Predictors of Drought Recovery across Forest Ecosystems

NASA Astrophysics Data System (ADS)

Anderegg, W.

2016-12-01

The impacts of climate extremes on terrestrial ecosystems are poorly understood but central for predicting carbon cycle feedbacks to climate change. Coupled climate-carbon cycle models typically assume that vegetation recovery from extreme drought is immediate and complete, which conflicts with basic plant physiological understanding. Here, we discuss what we have learned about forest ecosystem recovery from extreme drought across spatial and temporal scales, drawing on inference from tree rings, eddy covariance data, large scale gross primary productivity products, and ecosystem models. In tree rings, we find pervasive and substantial "legacy effects" of reduced growth and incomplete recovery for 1-4 years after severe drought, and that legacy effects are most prevalent in dry ecosystems, Pinaceae, and species with low hydraulic safety margins. At larger scales, we see relatively rapid recovery of ecosystem fluxes, with strong influences of ecosystem productivity and diversity and longer recovery periods in high latidue forests. In contrast, no or limited legacy effects are simulated in current climate-vegetation models after drought, and we highlight some of the key missing mechanisms in dynamic vegetation models. Our results reveal hysteresis in forest ecosystem carbon cycling and delayed recovery from climate extremes and help advance a predictive understanding of ecosystem recovery.

The natural flow regime of Hawaíi streams

NASA Astrophysics Data System (ADS)

Tsang, Y. P.; Strauch, A. M.; Clilverd, H. M.

2016-12-01

Freshwater is a critical, but limited natural resource on tropical islands; sustaining agriculture, industry, hydropower, urban development, and domestic water supply. The hydrology of Hawaíi islands is largely influenced by the health of mountain forests, which capture and absorb rain and fog drip, recharging aquifers and sustaining stream flow. Forests in Hawaíi are being degraded through the replacement of native vegetation with introduced species or conversion to another land use. Streams in the tropics frequently experience flash flooding due to extreme rainfall-runoff events and low flows due to seasonal drought. These patterns drive habitat availability for freshwater fauna, as well as sediment and nutrient export to near-shore ecosystems. Flow regimes can be used to characterize the frequency and magnitude of extreme high and low flows and are influenced by watershed climate, geology, land cover and soil composition. We examined the effect of climate extremes on stream flow from Hawaiian forests using historical flow data to characterize the spatial and temporal patterns in surface water resources. By defining flow regimes from forests we can improve our understanding of climate extremes on water resource availability across tropical island landscapes.

Climate extremes promote fatal co-infections during canine distemper epidemics in African lions.

PubMed

Munson, Linda; Terio, Karen A; Kock, Richard; Mlengeya, Titus; Roelke, Melody E; Dubovi, Edward; Summers, Brian; Sinclair, Anthony R E; Packer, Craig

2008-06-25

Extreme climatic conditions may alter historic host-pathogen relationships and synchronize the temporal and spatial convergence of multiple infectious agents, triggering epidemics with far greater mortality than those due to single pathogens. Here we present the first data to clearly illustrate how climate extremes can promote a complex interplay between epidemic and endemic pathogens that are normally tolerated in isolation, but with co-infection, result in catastrophic mortality. A 1994 canine distemper virus (CDV) epidemic in Serengeti lions (Panthera leo) coincided with the death of a third of the population, and a second high-mortality CDV epidemic struck the nearby Ngorongoro Crater lion population in 2001. The extent of adult mortalities was unusual for CDV and prompted an investigation into contributing factors. Serological analyses indicated that at least five "silent" CDV epidemics swept through the same two lion populations between 1976 and 2006 without clinical signs or measurable mortality, indicating that CDV was not necessarily fatal. Clinical and pathology findings suggested that hemoparsitism was a major contributing factor during fatal epidemics. Using quantitative real-time PCR, we measured the magnitude of hemoparasite infections in these populations over 22 years and demonstrated significantly higher levels of Babesia during the 1994 and 2001 epidemics. Babesia levels correlated with mortalities and extent of CDV exposure within prides. The common event preceding the two high mortality CDV outbreaks was extreme drought conditions with wide-spread herbivore die-offs, most notably of Cape buffalo (Syncerus caffer). As a consequence of high tick numbers after the resumption of rains and heavy tick infestations of starving buffalo, the lions were infected by unusually high numbers of Babesia, infections that were magnified by the immunosuppressive effects of coincident CDV, leading to unprecedented mortality. Such mass mortality events may become increasingly common if climate extremes disrupt historic stable relationships between co-existing pathogens and their susceptible hosts.

Climate Extremes Promote Fatal Co-Infections during Canine Distemper Epidemics in African Lions

PubMed Central

Munson, Linda; Terio, Karen A.; Kock, Richard; Mlengeya, Titus; Roelke, Melody E.; Dubovi, Edward; Summers, Brian; Sinclair, Anthony R. E.; Packer, Craig

2008-01-01

Extreme climatic conditions may alter historic host-pathogen relationships and synchronize the temporal and spatial convergence of multiple infectious agents, triggering epidemics with far greater mortality than those due to single pathogens. Here we present the first data to clearly illustrate how climate extremes can promote a complex interplay between epidemic and endemic pathogens that are normally tolerated in isolation, but with co-infection, result in catastrophic mortality. A 1994 canine distemper virus (CDV) epidemic in Serengeti lions (Panthera leo) coincided with the death of a third of the population, and a second high-mortality CDV epidemic struck the nearby Ngorongoro Crater lion population in 2001. The extent of adult mortalities was unusual for CDV and prompted an investigation into contributing factors. Serological analyses indicated that at least five “silent” CDV epidemics swept through the same two lion populations between 1976 and 2006 without clinical signs or measurable mortality, indicating that CDV was not necessarily fatal. Clinical and pathology findings suggested that hemoparsitism was a major contributing factor during fatal epidemics. Using quantitative real-time PCR, we measured the magnitude of hemoparasite infections in these populations over 22 years and demonstrated significantly higher levels of Babesia during the 1994 and 2001 epidemics. Babesia levels correlated with mortalities and extent of CDV exposure within prides. The common event preceding the two high mortality CDV outbreaks was extreme drought conditions with wide-spread herbivore die-offs, most notably of Cape buffalo (Syncerus caffer). As a consequence of high tick numbers after the resumption of rains and heavy tick infestations of starving buffalo, the lions were infected by unusually high numbers of Babesia, infections that were magnified by the immunosuppressive effects of coincident CDV, leading to unprecedented mortality. Such mass mortality events may become increasingly common if climate extremes disrupt historic stable relationships between co-existing pathogens and their susceptible hosts. PMID:18575601

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

Beach response dynamics of a littoral cell using a 17-year single-point time series of sand thickness

USGS Publications Warehouse

Barnard, P.L.; Hubbard, D.M.; Dugan, J.E.

2012-01-01

A 17-year time series of near-daily sand thickness measurements at a single intertidal location was compared with 5. years of semi-annual 3-dimensional beach surveys at the same beach, and at two other beaches within the same littoral cell. The daily single point measurements correlated extremely well with the mean beach elevation and shoreline position of ten high-spatial resolution beach surveys. Correlations were statistically significant at all spatial scales, even for beach surveys 10s of kilometers downcoast, and therefore variability at the single point monitoring site was representative of regional coastal behavior, allowing us to examine nearly two decades of continuous coastal evolution. The annual cycle of beach oscillations dominated the signal, typical of this region, with additional, less intense spectral peaks associated with seasonal wave energy fluctuations (~. 45 to 90. days), as well as full lunar (~. 29. days) and semi-lunar (~. 13. days; spring-neap cycle) tidal cycles. Sand thickness variability was statistically linked to wave energy with a 2. month peak lag, as well as the average of the previous 7-8. months of wave energy. Longer term anomalies in sand thickness were also apparent on time scales up to 15. months. Our analyses suggest that spatially-limited morphological data sets can be extremely valuable (with robust validation) for understanding the details of beach response to wave energy over timescales that are not resolved by typical survey intervals, as well as the regional behavior of coastal systems. ?? 2011.

Partitioning into hazard subregions for regional peaks-over-threshold modeling of heavy precipitation

NASA Astrophysics Data System (ADS)

Carreau, J.; Naveau, P.; Neppel, L.

2017-05-01

The French Mediterranean is subject to intense precipitation events occurring mostly in autumn. These can potentially cause flash floods, the main natural danger in the area. The distribution of these events follows specific spatial patterns, i.e., some sites are more likely to be affected than others. The peaks-over-threshold approach consists in modeling extremes, such as heavy precipitation, by the generalized Pareto (GP) distribution. The shape parameter of the GP controls the probability of extreme events and can be related to the hazard level of a given site. When interpolating across a region, the shape parameter should reproduce the observed spatial patterns of the probability of heavy precipitation. However, the shape parameter estimators have high uncertainty which might hide the underlying spatial variability. As a compromise, we choose to let the shape parameter vary in a moderate fashion. More precisely, we assume that the region of interest can be partitioned into subregions with constant hazard level. We formalize the model as a conditional mixture of GP distributions. We develop a two-step inference strategy based on probability weighted moments and put forward a cross-validation procedure to select the number of subregions. A synthetic data study reveals that the inference strategy is consistent and not very sensitive to the selected number of subregions. An application on daily precipitation data from the French Mediterranean shows that the conditional mixture of GPs outperforms two interpolation approaches (with constant or smoothly varying shape parameter).

15N Fractionation in Star-Forming Regions and Solar System Objects

NASA Technical Reports Server (NTRS)

Wirstrom, Eva; Milam, Stefanie; Adande, GIlles; Charnley, Steven; Cordiner, Martin

2015-01-01

A central issue for understanding the formation and evolution of matter in the early Solar System is the relationship between the chemical composition of star-forming interstellar clouds and that of primitive Solar System materials. The pristinemolecular content of comets, interplanetary dust particles and carbonaceous chondrites show significant bulk nitrogen isotopic fractionation relative to the solar value, 14N15N 440. In addition, high spatial resolution measurements in primitive materials locally show even more extreme enhancements of 14N15N 100.

Status of the R&D activity on diamond particle detectors

NASA Astrophysics Data System (ADS)

Adam, W.; Bellini, B.; Berdermann, E.; Bergonzo, P.; de Boer, W.; Bogani, F.; Borchi, E.; Brambilla, A.; Bruzzi, M.; Colledani, C.; Conway, J.; D'Angelo, P.; Dabrowski, W.; Delpierre, P.; Doroshenko, J.; Dulinski, W.; van Eijk, B.; Fallou, A.; Fischer, P.; Fizzotti, F.; Furetta, C.; Gan, K. K.; Ghodbane, N.; Grigoriev, E.; Hallewell, G.; Han, S.; Hartjes, F.; Hrubec, J.; Husson, D.; Kagan, H.; Kaplon, J.; Karl, C.; Kass, R.; Keil, M.; Knöpfle, K. T.; Koeth, T.; Krammer, M.; Logiudice, A.; Lu, R.; mac Lynne, L.; Manfredotti, C.; Marshall, R. D.; Meier, D.; Menichelli, D.; Meuser, S.; Mishina, M.; Moroni, L.; Noomen, J.; Oh, A.; Perera, L.; Pernicka, M.; Polesello, P.; Potenza, R.; Riester, J. L.; Roe, S.; Rudge, A.; Sala, S.; Sampietro, M.; Schnetzer, S.; Sciortino, S.; Stelzer, H.; Stone, R.; Sutera, C.; Trischuk, W.; Tromson, D.; Tuve, C.; Weilhammer, P.; Wermes, N.; Wetstein, M.; Zeuner, W.; Zoeller, M.; RD42 Collaboration

2003-09-01

Chemical Vapor Deposited (CVD) polycrystalline diamond has been proposed as a radiation-hard alternative to silicon in the extreme radiation levels occurring close to the interaction region of the Large Hadron Collider. Due to an intense research effort, reliable high-quality polycrystalline CVD diamond detectors, with up to 270 μm charge collection distance and good spatial uniformity, are now available. The most recent progress on the diamond quality, on the development of diamond trackers and on radiation hardness studies are presented and discussed.

A scan statistic for binary outcome based on hypergeometric probability model, with an application to detecting spatial clusters of Japanese encephalitis.

PubMed

Zhao, Xing; Zhou, Xiao-Hua; Feng, Zijian; Guo, Pengfei; He, Hongyan; Zhang, Tao; Duan, Lei; Li, Xiaosong

2013-01-01

As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff's methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff's statistics for clusters of high population density or large size; otherwise Kulldorff's statistics are superior.

Mapping Extreme Heat Vulnerability and Health Outcomes to inform the District of Columbia's Climate Adaptation Plan

NASA Astrophysics Data System (ADS)

Declet-Barreto, J.; Wilhelmi, O.; Goggans, A.

2016-12-01

In this collaborative engagement, scientists are partnering with the District of Columbia (DC) to develop an extreme heat vulnerability assessment. To do so, we map socio-demographic and built environment indicators of extreme heat vulnerability in Census Tracts in DC neighborhoods. In order to provide information useful for DC public health and urban planning practitioners, we aggregate the indicators into an index of extreme heat vulnerability. We compare the index against heat-related call data from DC's 911 system to better understand the socio-spatial distribution of extreme heat-related health outcomes. Our assessment can help inform the District's Climate Adaptation Plan as well as increase public engagement in reducing vulnerability to extreme heat.

High resolution modeling of a small urban catchment

NASA Astrophysics Data System (ADS)

Skouri-Plakali, Ilektra; Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2016-04-01

Flooding is one of the most complex issues that urban environments have to deal with. In France, flooding remains the first natural risk with 72% of decrees state of natural disaster issued between October 1982 and mid-November 2014. Flooding is a result of meteorological extremes that are usually aggravated by the hydrological behavior of urban catchments and human factors. The continuing urbanization process is indeed changing the whole urban water cycle by limiting the infiltration and promoting runoff. Urban environments are very complex systems due to their extreme variability, the interference between human activities and natural processes but also the effect of the ongoing urbanization process that changes the landscape and hardly influences their hydrologic behavior. Moreover, many recent works highlight the need to simulate all urban water processes at their specific temporal and spatial scales. However, considering urban catchments heterogeneity still challenging for urban hydrology, even after advances noticed in term of high-resolution data collection and computational resources. This issue is more to be related to the architecture of urban models being used and how far these models are ready to take into account the extreme variability of urban catchments. In this work, high spatio-temporal resolution modeling is performed for a small and well-equipped urban catchment. The aim of this work is to identify urban modeling needs in terms of spatial and temporal resolution especially for a very small urban area (3.7 ha urban catchment located in the Perreux-sur-Marne city at the southeast of Paris) MultiHydro model was selected to carry out this work, it is a physical based and fully distributed model that interacts four existing modules each of them representing a portion of the water cycle in urban environments. MultiHydro was implemented at 10m, 5m and 2m resolution. Simulations were performed at different spatio-temporal resolutions and analyzed with respect to real flow measurements. First Results coming out show improvements obtained in terms of the model performance at high spatio-temporal resolution.

Some Spatial Aspects of Southeastern United States Climatology.

ERIC Educational Resources Information Center

Soule, Peter T.

1998-01-01

Focuses on the climatology of an eight-state region in the southern and southeastern United States. Discusses general controls of climate and spatial patterns of various climatic averages. Examines mapped extremes as a means of fostering increased awareness of the variability that exists for climatic conditions in the region. (CMK)

USE OF REVA'S WEB-BASED ENVIRONMENTAL DECISION TOOLKIT (EDT) TO ASSESS VULNERABILITY TO MERCURY ACROSS THE UNITED STATES

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of 1) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

ASSESSING THE RISK ASSOCIATED WITH MERCURY: USING REVA'S WEBTOOL TO COMPARE DATA, ASSUMPTIONS, AND MODELS

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of I) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

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.

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2018-01-01

Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

Back to the Future -Precipitation Extremes, Climate Variability, Environmental Planning and Adaptation

NASA Astrophysics Data System (ADS)

Barros, A. P.

2008-12-01

--"The last major climatic oscillation peak was about 1856, or 74 years ago. Practically all of our important railroad and public highway work has been done since that time. Most of our parks systems driveways, and roads of all type for auto travel, in the various States, have been completed within the past 30 years, namely, beginning at the very lowest point of our climatic swing (1900-1910). There is every reason to believe, therefore, as the next 20 years comes on apace, we will witness considerable damage to work done during the past regime of weather."-- Schuman, 1931 At the beginning of the 21st century, as at the beginning of the 20th century, the fundamental question is whether the nation is more prepared for natural disasters today than it was eight decades ago. Indeed, the question is whether the best science, engineering and policy tools are in place to prepare for and respond to extreme events. Changes in the risk and magnitude of extreme precipitation events rank among the most studied impacts, and indicators (symptoms) of climatic variations. Extreme precipitation translates generally into extreme flooding, landslides, collapse of lifeline infrastructure, and the breakdown of public health services among others. In approaching the problem of quantifying the risk and magnitude of extreme precipitation events, there are two major challenges: 1) it is difficult to characterize "observed" (20th century) conditions due to the lack of long-term observations - i.e., short and incomplete historical records; and 2) it is difficult to characterize "predicted" (21st century) conditions due to the lack of skill of precipitation forecasts at spatial and temporal scales meaningful for impact studies, and the short-duration of climate model simulations themselves. The first challenge translates in estimating the probability of occurrence (rare) and magnitude (very large) of events that may have not happened yet. The second challenge is that of quantifying uncertainty and separating climatic variability and change from model error. Nonstationarity and persistence at multiple scales confound the problem. From an economics perspective, the unprecedented success of environmental control and "conservation" in the 20th century, present another yet challenge in terms of social expectations and human development, including the right to sustainable (high) quality of life. In this presentation, we illustrate these challenges by considering first the estimation of Probable Maximum Precipitation, an engineering design criterion typically used in dam design, and examine how it varies spatially across the continental US according to physiographic region and as a function of climate regime. Second, we explore the spatial and temporal scales that link climate variability to macroscale environmental planning, and the notion of place-based adaptive riskgrade analysis.

Wavefront measurement of single-mode quantum cascade laser beam for seed application in laser-produced plasma extreme ultraviolet system.

PubMed

Nowak, Krzysztof M; Ohta, Takeshi; Suganuma, Takashi; Yokotsuka, Toshio; Fujimoto, Junichi; Mizoguchi, Hakaru

2012-12-01

Quantum cascade laser (QCL) is a very attractive seed source for a multikilowatt pulsed CO2 lasers applied for driving extreme ultraviolet emitting plasmas. In this Letter, we investigate output beam properties of a QCL designed to address P18 and P20 lines of 10.6 micron band of CO2 molecule. In particular, output beam quality and stability are investigated for the first time. A well-defined linear polarization and a single-mode operation enabled a use of phase retrieval method for full description of QCL output beam. A direct, multi-image numerical phase retrieval technique was developed and successfully applied to the measured intensity patterns of a QCL beam. Very good agreement between the measured and reconstructed beam profiles was observed at distances ranging from QCL aperture to infinity, proving a good understanding of the beam propagation. The results also confirm a high spatial coherence and high stability of the beam parameters, the features expected from an excellent seed source.

Multi-band implications of external-IC flares

NASA Astrophysics Data System (ADS)

Richter, Stephan; Spanier, Felix

2015-02-01

Very fast variability on scales of minutes is regularly observed in Blazars. The assumption that these flares are emerging from the dominant emission zone of the very high energy (VHE) radiation within the jet challenges current acceleration and radiation models. In this work we use a spatially resolved and time dependent synchrotron-self-Compton (SSC) model that includes the full time dependence of Fermi-I acceleration. We use the (apparent) orphan γ -ray flare of Mrk501 during MJD 54952 and test various flare scenarios against the observed data. We find that a rapidly variable external radiation field can reproduce the high energy lightcurve best. However, the effect of the strong inverse Compton (IC) cooling on other bands and the X-ray observations are constraining the parameters to rather extreme ranges. Then again other scenarios would require parameters even more extreme or stronger physical constraints on the rise and decay of the source of the variability which might be in contradiction with constraints derived from the size of the black hole's ergosphere.

A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino

2017-03-01

Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.

Uncertainty in determining extreme precipitation thresholds

NASA Astrophysics Data System (ADS)

Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili

2013-10-01

Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method are more reasonable and applicable for the Pearl River Basin.

GeoProMT: A Collaborative Platform Supporting Natural Hazards Project Management From Assessment to Resilience

NASA Astrophysics Data System (ADS)

Renschler, C.; Sheridan, M. F.; Patra, A. K.

2008-05-01

The impact and consequences of extreme geophysical events (hurricanes, floods, wildfires, volcanic flows, mudflows, etc.) on properties and processes should be continuously assessed by a well-coordinated interdisciplinary research and outreach approach addressing risk assessment and resilience. Communication between various involved disciplines and stakeholders is the key to a successful implementation of an integrated risk management plan. These issues become apparent at the level of decision support tools for extreme events/disaster management in natural and managed environments. The Geospatial Project Management Tool (GeoProMT) is a collaborative platform for research and training to document and communicate the fundamental steps in transforming information for extreme events at various scales for analysis and management. GeoProMT is an internet-based interface for the management of shared geo-spatial and multi-temporal information such as measurements, remotely sensed images, and other GIS data. This tool enhances collaborative research activities and the ability to assimilate data from diverse sources by integrating information management. This facilitates a better understanding of natural processes and enhances the integrated assessment of resilience against both the slow and fast onset of hazard risks. Fundamental to understanding and communicating complex natural processes are: (a) representation of spatiotemporal variability, extremes, and uncertainty of environmental properties and processes in the digital domain, (b) transformation of their spatiotemporal representation across scales (e.g. interpolation, aggregation, disaggregation.) during data processing and modeling in the digital domain, and designing and developing tools for (c) geo-spatial data management, and (d) geo-spatial process modeling and effective implementation, and (e) supporting decision- and policy-making in natural resources and hazard management at various spatial and temporal scales of interest. GeoProMT is useful for researchers, practitioners, and decision-makers, because it provides an integrated environmental system assessment and data management approach that considers the spatial and temporal scales and variability in natural processes. Particularly in the occurrence or onset of extreme events it can utilize the latest data sources that are available at variable scales, combine them with existing information, and update assessment products such as risk and vulnerability assessment maps. Because integrated geo-spatial assessment requires careful consideration of all the steps in utilizing data, modeling and decision-making formats, each step in the sequence must be assessed in terms of how information is being scaled. At the process scale various geophysical models (e.g. TITAN, LAHARZ, or many other examples) are appropriate for incorporation in the tool. Some examples that illustrate our approach include: 1) coastal parishes impacted by Hurricane Rita (Southwestern Louisiana), 2) a watershed affected by extreme rainfall induced debris-flows (Madison County, Virginia; Panabaj, Guatemala; Casita, Nicaragua), and 3) the potential for pyroclastic flows to threaten a city (Tungurahua, Ecuador). This research was supported by the National Science Foundation.

Stable time filtering of strongly unstable spatially extended systems

PubMed Central

Grote, Marcus J.; Majda, Andrew J.

2006-01-01

Many contemporary problems in science involve making predictions based on partial observation of extremely complicated spatially extended systems with many degrees of freedom and with physical instabilities on both large and small scale. Various new ensemble filtering strategies have been developed recently for these applications, and new mathematical issues arise. Because ensembles are extremely expensive to generate, one such issue is whether it is possible under appropriate circumstances to take long time steps in an explicit difference scheme and violate the classical Courant–Friedrichs–Lewy (CFL)-stability condition yet obtain stable accurate filtering by using the observations. These issues are explored here both through elementary mathematical theory, which provides simple guidelines, and the detailed study of a prototype model. The prototype model involves an unstable finite difference scheme for a convection–diffusion equation, and it is demonstrated below that appropriate observations can result in stable accurate filtering of this strongly unstable spatially extended system. PMID:16682626

Stable time filtering of strongly unstable spatially extended systems.

PubMed

Grote, Marcus J; Majda, Andrew J

2006-05-16

Many contemporary problems in science involve making predictions based on partial observation of extremely complicated spatially extended systems with many degrees of freedom and with physical instabilities on both large and small scale. Various new ensemble filtering strategies have been developed recently for these applications, and new mathematical issues arise. Because ensembles are extremely expensive to generate, one such issue is whether it is possible under appropriate circumstances to take long time steps in an explicit difference scheme and violate the classical Courant-Friedrichs-Lewy (CFL)-stability condition yet obtain stable accurate filtering by using the observations. These issues are explored here both through elementary mathematical theory, which provides simple guidelines, and the detailed study of a prototype model. The prototype model involves an unstable finite difference scheme for a convection-diffusion equation, and it is demonstrated below that appropriate observations can result in stable accurate filtering of this strongly unstable spatially extended system.

Coherent inflation for large quantum superpositions of levitated microspheres

NASA Astrophysics Data System (ADS)

Romero-Isart, Oriol

2017-12-01

We show that coherent inflation (CI), namely quantum dynamics generated by inverted conservative potentials acting on the center of mass of a massive object, is an enabling tool to prepare large spatial quantum superpositions in a double-slit experiment. Combined with cryogenic, extreme high vacuum, and low-vibration environments, we argue that it is experimentally feasible to exploit CI to prepare the center of mass of a micrometer-sized object in a spatial quantum superposition comparable to its size. In such a hitherto unexplored parameter regime gravitationally-induced decoherence could be unambiguously falsified. We present a protocol to implement CI in a double-slit experiment by letting a levitated microsphere traverse a static potential landscape. Such a protocol could be experimentally implemented with an all-magnetic scheme using superconducting microspheres.

Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative

NASA Astrophysics Data System (ADS)

Frank, Dorothea; Reichstein, Markus

2017-04-01

The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Crosson, W. L.; Al-Hamdan, M. Z.; Estes, M. G., Jr.

2013-12-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981-2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a ';heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.

2013-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

TECA: A Parallel Toolkit for Extreme Climate Analysis

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

Prabhat, Mr; Ruebel, Oliver; Byna, Surendra

2012-03-12

We present TECA, a parallel toolkit for detecting extreme events in large climate datasets. Modern climate datasets expose parallelism across a number of dimensions: spatial locations, timesteps and ensemble members. We design TECA to exploit these modes of parallelism and demonstrate a prototype implementation for detecting and tracking three classes of extreme events: tropical cyclones, extra-tropical cyclones and atmospheric rivers. We process a modern TB-sized CAM5 simulation dataset with TECA, and demonstrate good runtime performance for the three case studies.

The Influence of Coral Reef Benthic Condition on Associated Fish Assemblages

PubMed Central

Chong-Seng, Karen M.; Mannering, Thomas D.; Pratchett, Morgan S.; Bellwood, David R.; Graham, Nicholas A. J.

2012-01-01

Accumulative disturbances can erode a coral reef’s resilience, often leading to replacement of scleractinian corals by macroalgae or other non-coral organisms. These degraded reef systems have been mostly described based on changes in the composition of the reef benthos, and there is little understanding of how such changes are influenced by, and in turn influence, other components of the reef ecosystem. This study investigated the spatial variation in benthic communities on fringing reefs around the inner Seychelles islands. Specifically, relationships between benthic composition and the underlying substrata, as well as the associated fish assemblages were assessed. High variability in benthic composition was found among reefs, with a gradient from high coral cover (up to 58%) and high structural complexity to high macroalgae cover (up to 95%) and low structural complexity at the extremes. This gradient was associated with declining species richness of fishes, reduced diversity of fish functional groups, and lower abundance of corallivorous fishes. There were no reciprocal increases in herbivorous fish abundances, and relationships with other fish functional groups and total fish abundance were weak. Reefs grouping at the extremes of complex coral habitats or low-complexity macroalgal habitats displayed markedly different fish communities, with only two species of benthic invertebrate feeding fishes in greater abundance in the macroalgal habitat. These results have negative implications for the continuation of many coral reef ecosystem processes and services if more reefs shift to extreme degraded conditions dominated by macroalgae. PMID:22870294

The influence of coral reef benthic condition on associated fish assemblages.

PubMed

Chong-Seng, Karen M; Mannering, Thomas D; Pratchett, Morgan S; Bellwood, David R; Graham, Nicholas A J

2012-01-01

Accumulative disturbances can erode a coral reef's resilience, often leading to replacement of scleractinian corals by macroalgae or other non-coral organisms. These degraded reef systems have been mostly described based on changes in the composition of the reef benthos, and there is little understanding of how such changes are influenced by, and in turn influence, other components of the reef ecosystem. This study investigated the spatial variation in benthic communities on fringing reefs around the inner Seychelles islands. Specifically, relationships between benthic composition and the underlying substrata, as well as the associated fish assemblages were assessed. High variability in benthic composition was found among reefs, with a gradient from high coral cover (up to 58%) and high structural complexity to high macroalgae cover (up to 95%) and low structural complexity at the extremes. This gradient was associated with declining species richness of fishes, reduced diversity of fish functional groups, and lower abundance of corallivorous fishes. There were no reciprocal increases in herbivorous fish abundances, and relationships with other fish functional groups and total fish abundance were weak. Reefs grouping at the extremes of complex coral habitats or low-complexity macroalgal habitats displayed markedly different fish communities, with only two species of benthic invertebrate feeding fishes in greater abundance in the macroalgal habitat. These results have negative implications for the continuation of many coral reef ecosystem processes and services if more reefs shift to extreme degraded conditions dominated by macroalgae.

Evaluation of realistic layouts for next generation on-scalp MEG: spatial information density maps.

PubMed

Riaz, Bushra; Pfeiffer, Christoph; Schneiderman, Justin F

2017-08-01

While commercial magnetoencephalography (MEG) systems are the functional neuroimaging state-of-the-art in terms of spatio-temporal resolution, MEG sensors have not changed significantly since the 1990s. Interest in newer sensors that operate at less extreme temperatures, e.g., high critical temperature (high-T c ) SQUIDs, optically-pumped magnetometers, etc., is growing because they enable significant reductions in head-to-sensor standoff (on-scalp MEG). Various metrics quantify the advantages of on-scalp MEG, but a single straightforward one is lacking. Previous works have furthermore been limited to arbitrary and/or unrealistic sensor layouts. We introduce spatial information density (SID) maps for quantitative and qualitative evaluations of sensor arrays. SID-maps present the spatial distribution of information a sensor array extracts from a source space while accounting for relevant source and sensor parameters. We use it in a systematic comparison of three practical on-scalp MEG sensor array layouts (based on high-T c SQUIDs) and the standard Elekta Neuromag TRIUX magnetometer array. Results strengthen the case for on-scalp and specifically high-T c SQUID-based MEG while providing a path for the practical design of future MEG systems. SID-maps are furthermore general to arbitrary magnetic sensor technologies and source spaces and can thus be used for design and evaluation of sensor arrays for magnetocardiography, magnetic particle imaging, etc.

Evaluation of glued-diaphragm fibre optic pressure sensors in a shock tube

NASA Astrophysics Data System (ADS)

Sharifian, S. Ahmad; Buttsworth, David R.

2007-02-01

Glued-diaphragm fibre optic pressure sensors that utilize standard telecommunications components which are based on Fabry-Perot interferometry are appealing in a number of respects. Principally, they have high spatial and temporal resolution and are low in cost. These features potentially make them well suited to operation in extreme environments produced in short-duration high-enthalpy wind tunnel facilities where spatial and temporal resolution are essential, but attrition rates for sensors are typically very high. The sensors we consider utilize a zirconia ferrule substrate and a thin copper foil which are bonded together using an adhesive. The sensors show a fast response and can measure fluctuations with a frequency up to 250 kHz. The sensors also have a high spatial resolution on the order of 0.1 mm. However, with the interrogation and calibration processes adopted in this work, apparent errors of up to 30% of the maximum pressure have been observed. Such errors are primarily caused by mechanical hysteresis and adhesive viscoelasticity. If a dynamic calibration is adopted, the maximum measurement error can be limited to about 10% of the maximum pressure. However, a better approach is to eliminate the adhesive from the construction process or design the diaphragm and substrate in a way that does not require the adhesive to carry a significant fraction of the mechanical loading.

D Mapping of Cultural Heritage: Special Problems and best Practices in Extreme Case-Studies

NASA Astrophysics Data System (ADS)

Patias, P.; Kaimaris, D.; Georgiadis, Ch.; Stamnas, A.; Antoniadis, D.; Papadimitrakis, D.

2013-07-01

Photogrammetrey has a long successful history in the area of 3D modelling and documentation of cultural heritage monuments. In some cases an extensive study, preparation and the application of novel solutions is required for the successful documentation and 3D modelling of monuments. In most of the cases the problem that we have to face is difficulties regarding accessing, photographing, and measuring the monument from the optimal distance, in combination with the need for a high spatial resolution mapping. This paper is highlighting the special problems and the novel solutions, performed during mapping of two significant cultural heritage monuments in Greece. The Roussanou monastery (1527-1529 A.C., Meteora, Center Greece) and its underlying rock, had to be photographed and measured from a far distance and measured with various spatial resolutions. In the lakeside Neolithic settlement of Dispilio (6.000 B.C., western Greece) the enclosure which is covered with vegetation above a height of 3 m, had to be measured with high spatial resolution. The combined use of a laser scanner, a digital camera equipped with a telephoto lens and UAV allowed the successful mapping and the production of orthophotomaps in each case.

Impact of post-stroke unilateral spatial neglect on goal-directed arm movements: systematic literature review.

PubMed

Ogourtsova, Tatiana; Archambault, Philippe; Lamontagne, Anouk

2015-12-01

Unilateral spatial neglect (USN), a highly prevalent post-stroke impairment, refers to one's inability to orient or respond to stimuli located in the contralesional visual hemispace. Unilateral spatial neglect has been shown to strongly affect motor performance in functional activities, including non-affected upper extremity (UE) movements. To date, our understanding of the effects of USN on goal-directed UE movements is limited and comparing performance of individuals post-stroke with and without USN is required. To determine, in individuals with stroke, how does the presence of USN, in comparison to the absence of USN, impacts different types of goal-directed movements of the non-affected UE. The present review approach consisted of a comprehensive literature search, an assessment of the quality of the selected studies and qualitative data analysis. A total of 20 studies of moderate to high quality were selected. The USN-specific impairments were found in tasks that required a perceptual, memory-guided or delayed actions, and fewer impairments were found in tasks that required an immediate action to a predefined target. The results indicate that USN contributes to deficits observed in action execution with the non-effected UE that requires greater perceptual demands.

Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

NASA Astrophysics Data System (ADS)

El-Samra, R.; Bou-Zeid, E.; Bangalath, H. K.; Stenchikov, G.; El-Fadel, M.

2017-12-01

A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model's ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.

North Sea Storm Driving of Extreme Wave Heights

NASA Astrophysics Data System (ADS)

Bell, Ray; Gray, Suzanne; Jones, Oliver

2017-04-01

The relationship between storms and extreme ocean waves in the North sea is assessed using a long-period wave dataset and storms identified in the Interim ECMWF Re-Analysis (ERA-Interim). An ensemble sensitivity analysis is used to provide information on the spatial and temporal forcing from mean sea-level pressure and surface wind associated with extreme ocean wave height responses. Extreme ocean waves in the central North Sea arise due to either the winds in the cold conveyor belt (northerly-wind events) or winds in the warm conveyor belt (southerly-wind events) of extratropical cyclones. The largest wave heights are associated with northerly-wind events which tend to have stronger wind speeds and occur as the cold conveyor belt wraps rearwards round the cyclone to the cold side of the warm front. The northerly-wind events also provide a larger fetch to the central North Sea. Southerly-wind events are associated with the warm conveyor belts of intense extratropical storms developing in the right upper-tropospheric jet exit region. There is predictability in the extreme ocean wave events up to two days before the event associated with a strengthening of a high pressure system to the west (northerly-wind events) and south-west (southerly-wind events) of the British Isles. This acts to increase the pressure gradient over the British Isles and therefore drive stronger wind speeds in the central North sea.

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.

Increase of Elderly Population in the Rainstorm Hazard Areas of China.

PubMed

Liang, Pujun; Xu, Wei; Ma, Yunjia; Zhao, Xiujuan; Qin, Lianjie

2017-08-26

In light of global warming, increased extreme precipitation events have enlarged the population exposed to floods to some extent. Extreme precipitation risk assessments are of great significance in China and allow for the response to climate change and mitigation of risks to the population. China is one of the countries most influenced by climate change and has unique national population conditions. The influence of extreme precipitation depends on the degree of exposure and vulnerability of the population. Accurate assessments of the population exposed to rising rainstorm trends are crucial to mapping extreme precipitation risks. Studying the population exposed to rainstorm hazard areas (RSHA) at the microscale is extremely urgent, due to the local characteristics of extreme precipitation events and regional diversity of the population. The spatial distribution of population density was mapped based on the national population census data from China in 1990, 2000 and 2010. RSHA were also identified using precipitation data from 1975-2015 in China, and the rainstorm tendency values were mapped using GIS in this paper. The spatial characteristics of the rainstorm tendencies were then analyzed. Finally, changes in the population in the RSHA are discussed. The results show that the extreme precipitation trends are increasing in southeastern China. From 1990 to 2010, the population in RSHA increased by 110 million, at a rate of 14.6%. The elderly in the region increased by 38 million at a rate of 86.4%. Studying the size of the population exposed to rainstorm hazards at the county scale can provide scientific evidence for developing disaster prevention and mitigation strategies from the bottom up.

Modal analysis of the ultrahigh finesse Haroche QED cavity

NASA Astrophysics Data System (ADS)

Marsic, Nicolas; De Gersem, Herbert; Demésy, Guillaume; Nicolet, André; Geuzaine, Christophe

2018-04-01

In this paper, we study a high-order finite element approach to simulate an ultrahigh finesse Fabry–Pérot superconducting open resonator for cavity quantum electrodynamics. Because of its high quality factor, finding a numerically converged value of the damping time requires an extremely high spatial resolution. Therefore, the use of high-order simulation techniques appears appropriate. This paper considers idealized mirrors (no surface roughness and perfect geometry, just to cite a few hypotheses), and shows that under these assumptions, a damping time much higher than what is available in experimental measurements could be achieved. In addition, this work shows that both high-order discretizations of the governing equations and high-order representations of the curved geometry are mandatory for the computation of the damping time of such cavities.

Method and apparatus for measuring gravitational acceleration utilizing a high temperature superconducting bearing

DOEpatents

Hull, John R.

2000-01-01

Gravitational acceleration is measured in all spatial dimensions with improved sensitivity by utilizing a high temperature superconducting (HTS) gravimeter. The HTS gravimeter is comprised of a permanent magnet suspended in a spaced relationship from a high temperature superconductor, and a cantilever having a mass at its free end is connected to the permanent magnet at its fixed end. The permanent magnet and superconductor combine to form a bearing platform with extremely low frictional losses, and the rotational displacement of the mass is measured to determine gravitational acceleration. Employing a high temperature superconductor component has the significant advantage of having an operating temperature at or below 77K, whereby cooling may be accomplished with liquid nitrogen.

Concept Study Report: Extreme-Ultraviolet Imaging Spectrometer Solar-B

NASA Technical Reports Server (NTRS)

Doschek, George, A.; Brown, Charles M.; Davila, Joseph M.; Dere, Kenneth P.; Korendyke, Clarence M.; Mariska, John T.; Seely, John F.

1999-01-01

We propose a next generation Extreme-ultraviolet Imaging Spectrometer (EIS) that for the first time combines high spectral, spatial, and temporal resolution in a single solar spectroscopic instrument. The instrument consists of a multilayer-coated off-axis telescope mirror and a multilayer-coated grating spectrometer. The telescope mirror forms solar images on the spectrometer entrance slit assembly. The spectrometer forms stigmatic spectra of the solar region located at the slit. This region is selected by the articulated telescope mirror. Monochromatic images are obtained either by rastering the solar region across a narrow entrance slit, or by using a very wide slit (called a slot) in place of the slit. Monochromatic images of the region centered on the slot are obtained in a single exposure. Half of each optic is coated to maximize reflectance at 195 Angstroms; the other half to maximize reflectance at 270 Angstroms. The two Extreme Ultraviolet (EUV) wavelength bands have been selected to maximize spectral and dynamical and plasma diagnostic capabilities. Spectral lines are observed that are formed over a temperature range from about 0.1 MK to about 20 MK. The main EIS instrument characteristics are: wavelength bands - 180 to 204 Angstroms; 250 to 290 Angstroms; spectral resolution - 0.0223 Angstroms/pixel (34.3km/s at 195 Angstroms and 23.6 km/s at 284 Angstroms); slit dimensions - 4 slits, two currently specified dimensions are 1" x 1024" and 50" x 1024" (the slot); largest spatial field of view in a single exposure - 50" x 1024"; highest time resolution for active region velocity studies - 4.4 s.

Compact advanced extreme-ultraviolet imaging spectrometer for spatiotemporally varying tungsten spectra from fusion plasmas.

PubMed

Song, Inwoo; Seon, C R; Hong, Joohwan; An, Y H; Barnsley, R; Guirlet, R; Choe, Wonho

2017-09-01

A compact advanced extreme-ultraviolet (EUV) spectrometer operating in the EUV wavelength range of a few nanometers to measure spatially resolved line emissions from tungsten (W) was developed for studying W transport in fusion plasmas. This system consists of two perpendicularly crossed slits-an entrance aperture and a space-resolved slit-inside a chamber operating as a pinhole, which enables the system to obtain a spatial distribution of line emissions. Moreover, a so-called v-shaped slit was devised to manage the aperture size for measuring the spatial resolution of the system caused by the finite width of the pinhole. A back-illuminated charge-coupled device was used as a detector with 2048 × 512 active pixels, each with dimensions of 13.5 × 13.5 μm 2 . After the alignment and installation on Korea superconducting tokamak advanced research, the preliminary results were obtained during the 2016 campaign. Several well-known carbon atomic lines in the 2-7 nm range originating from intrinsic carbon impurities were observed and used for wavelength calibration. Further, the time behavior of their spatial distributions is presented.

A statistical model of extreme storm rainfall

NASA Astrophysics Data System (ADS)

Smith, James A.; Karr, Alan F.

1990-02-01

A model of storm rainfall is developed for the central Appalachian region of the United States. The model represents the temporal occurrence of major storms and, for a given storm, the spatial distribution of storm rainfall. Spatial inhomogeneities of storm rainfall and temporal inhomogeneities of the storm occurrence process are explicitly represented. The model is used for estimating recurrence intervals of extreme storms. The parameter estimation procedure developed for the model is based on the substitution principle (method of moments) and requires data from a network of rain gages. The model is applied to a 5000 mi2 (12,950 km2) region in the Valley and Ridge Province of Virginia and West Virginia.

Remote sensing, global warming, and vector-borne disease

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

Wood, B.; Beck, L.; Dister, S.

1997-12-31

The relationship between climate change and the pattern of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are changes such as global warming, which are continental in scale and occur over periods of years, decades, or longer. At the opposite extreme are changes associated with severe weather events, which can occur at local and regional scales over periods of days, weeks, or months. Key ecological factors affecting the distribution of vector-borne diseases include temperature, precipitation, and habitat availability, and their impact on vectors, pathogens, reservoirs, and hosts. Global warming can potentially altermore » these factors, thereby affecting the spatial and temporal patterns of disease.« less

Optical Rogue Waves in Vortex Turbulence.

PubMed

Gibson, Christopher J; Yao, Alison M; Oppo, Gian-Luca

2016-01-29

We present a spatiotemporal mechanism for producing 2D optical rogue waves in the presence of a turbulent state with creation, interaction, and annihilation of optical vortices. Spatially periodic structures with bound phase lose stability to phase unbound turbulent states in complex Ginzburg-Landau and Swift-Hohenberg models with external driving. When the pumping is high and the external driving is low, synchronized oscillations are unstable and lead to spatiotemporal vortex-mediated turbulence with high excursions in amplitude. Nonlinear amplification leads to rogue waves close to turbulent optical vortices, where the amplitude tends to zero, and to probability density functions (PDFs) with long tails typical of extreme optical events.

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

NASA Technical Reports Server (NTRS)

Crosson, William L; Al-Hamdan, Mohammad Z.; Economou, Sigrid, A.; Estes, Maurice G.; Estes, Sue M.; Puckett, Mark; Quattrochi, Dale A

2013-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

High Temperature Extremes - Will They Transform Structure of Avian Assemblages in the Desert Southwest?

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Albright, T. P.; Wolf, B. O.; Mckechnie, A. E.; Gerson, A. R.; Talbot, W. A.; Sadoti, G.; O'Neill, J.; Smith, E.

2014-12-01

Extreme weather events can alter ecosystem structure and function and have caused mass mortality events in animals. With climate change, high temperature extremes are increasing in frequency and magnitude. To better understand the consequences of climate change, scientists have frequently employed correlative models based on species occurrence records. However, these approaches may be of limited utility in the context of extremes, as these are often outside historical ranges and may involve strong non-linear responses. Here we describe work linking physiological response informed by experimental data to geospatial climate datasets in order to mechanistically model the dynamics of dehydration risk to dessert passerine birds. Specifically, we modeled and mapped the occurrence of current (1980-2013) high temperature extremes and evaporative water loss rates for eight species of passerine birds ranging in size from 6.5-75g in the US Southwest portion of their range. We then explored the implications of a 4° C warming scenario. Evaporative water loss (EWL) across a range of high temperatures was measured in heat-acclimated birds captured in the field. We used the North American Land Data Assimilation System 2 dataset to obtain hourly estimates of EWL with a 14-km spatial grain. Assuming lethal dehydration occurs when water loss reaches 15% of body weight, we then produced maps of total daily EWL and time to lethal dehydration based on both current data and future scenarios. We found that milder events capable of producing dehydration in passerine birds over four or more hours were not uncommon over the Southwest, but rapid dehydration conditions (<3 hours) were rare. Under the warming scenario, the frequency and extent of dehydration events expanded greatly, often affecting areas several times larger than in present-day climate. Dehydration risk was especially high among smaller bodied passerines due to their higher mass-specific rates of water loss. Even after accounting for the moderating effects of microsite and topoclimatic refugia, the increase in occurrence of lethal dehydration risk is cause for concern. In particular, our results suggest that smaller bodied passerines may have difficulty in avoiding extirpation over portions of their current range in the desert southwest.

A Novel Method of High Accuracy, Wavefront Phase and Amplitude Correction for Coronagraphy

NASA Technical Reports Server (NTRS)

Bowers, Charles W.; Woodgate, Bruce E.; Lyon, Richard G.

2003-01-01

Detection of extra-solar, and especially terrestrial-like planets, using coronagraphy requires an extremely high level of wavefront correction. For example, the study of Woodruff et al. (2002) has shown that phase uniformity of order 10(exp -4)lambda(rms) must be achieved over the critical range of spatial frequencies to produce the approx. 10(exp 10) contrast needed for the Terrestrial Planet Finder (TPF) mission. Correction of wavefront phase errors to this level may be accomplished by using a very high precision deformable mirror (DM). However, not only phase but also amplitude uniformity of the same scale (approx. 10(exp -4)) and over the same spatial frequency range must be simultaneously obtained to remove all residual speckle in the image plane. We present a design for producing simultaneous wavefront phase and amplitude uniformity to high levels from an input wavefront of lower quality. The design uses a dual Michelson interferometer arrangement incorporating two DM and a single, fixed mirror (all at pupils) and two beamsplitters: one with unequal (asymmetric) beam splitting and one with symmetric beam splitting. This design allows high precision correction of both phase and amplitude using DM with relatively coarse steps and permits a simple correction algorithm.

An exploratory analysis linking neuropsychological testing to quantification of tractography using High Definition Fiber Tracking (HDFT) in military TBI.

PubMed

Presson, Nora; Beers, Sue R; Morrow, Lisa; Wagener, Lauren M; Bird, William A; Van Eman, Gina; Krishnaswamy, Deepa; Penderville, Joshua; Borrasso, Allison J; Benso, Steven; Puccio, Ava; Fissell, Catherine; Okonkwo, David O; Schneider, Walter

2015-09-01

To realize the potential value of tractography in traumatic brain injury (TBI), we must identify metrics that provide meaningful information about functional outcomes. The current study explores quantitative metrics describing the spatial properties of tractography from advanced diffusion imaging (High Definition Fiber Tracking, HDFT). In a small number of right-handed males from military TBI (N = 7) and civilian control (N = 6) samples, both tract homologue symmetry and tract spread (proportion of brain mask voxels contacted) differed for several tracts among civilian controls and extreme groups in the TBI sample (high scorers and low scorers) for verbal recall, serial reaction time, processing speed index, and trail-making. Notably, proportion of voxels contacted in the arcuate fasciculus distinguished high and low performers on the CVLT-II and PSI, potentially reflecting linguistic task demands, and GFA in the left corticospinal tract distinguished high and low performers in PSI and Trail Making Test Part A, potentially reflecting right hand motor response demands. The results suggest that, for advanced diffusion imaging, spatial properties of tractography may add analytic value to measures of tract anisotropy.

Sensitivity analysis of a FMC model for improving forecasting forest fires: Comparison with real fires in Spain

NASA Astrophysics Data System (ADS)

San Jose, Roberto; Perez, Juan Luis; Gonzalez-Barras, Rosa M.; Pecci, Julia; Palacios, Marino

2014-05-01

Forest fires continue to be a very dangerous and extreme violent episode jeopardizing the human lives and owns. Spain is plagued by forest and brush fires every summer, when extremely dry weather sets in along with high temperatures. The use of fire behavior models requires the availability of high resolution environmental and fuel data; in absence of realistic data, errors on the simulated fire spread con be compounded to produce o decrease of the spatial and temporal accuracy of predicted data. In this work we have carried out a sensitivity analysis of different components of the fire model and particularly the fuel moisture content (FMC) such as microphysics and solar radiation model. Three different real fire models have been used: Murcia (September, 7, 2010 19h09 and 9 hours duration), Gabiel (March, 7, 2007, 22h15 and 38 hours duration) and Culla (Marzo, 7, 2007, 23h36 and 37 hours duration). We use the 100 m European Corine Land Cover map. We use the WRF-Fire model developed by NCAR (USA). The WRF mode is run using the GFS global data and over the Iberian Peninsula with 15 km spatial resolution. We apply the nesting approach over the fires areas (located in the South East of the Iberian Peninsula) with 3 km, 1 km and 200 m spatial resolution. The Fire module included into WRF is run with 20 m spatial resolution and the landuse is interpolated from the Corine 100 m land use map. The results show that the Thompson et al. microphysics scheme and the RRTM solar radiation scheme are those with the best combination using a specific counting score to classify the goodness of the results compare with the real burned area. Those pixels not burned by the simulations but burned by the observational data sets are penalized double compare with the vice versa process. The NDVI obtained by satellite on the day of starting the fire is included in the simulations and a substantial improving in the final score is obtained.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

Ecosystem services and urban heat riskscape moderation: water, green spaces, and social inequality in Phoenix, USA.

PubMed

Jenerette, G Darrel; Harlan, Sharon L; Stefanov, William L; Martin, Chris A

2011-10-01

Urban ecosystems are subjected to high temperatures--extreme heat events, chronically hot weather, or both-through interactions between local and global climate processes. Urban vegetation may provide a cooling ecosystem service, although many knowledge gaps exist in the biophysical and social dynamics of using this service to reduce climate extremes. To better understand patterns of urban vegetated cooling, the potential water requirements to supply these services, and differential access to these services between residential neighborhoods, we evaluated three decades (1970-2000) of land surface characteristics and residential segregation by income in the Phoenix, Arizona, USA metropolitan region. We developed an ecosystem service trade-offs approach to assess the urban heat riskscape, defined as the spatial variation in risk exposure and potential human vulnerability to extreme heat. In this region, vegetation provided nearly a 25 degrees C surface cooling compared to bare soil on low-humidity summer days; the magnitude of this service was strongly coupled to air temperature and vapor pressure deficits. To estimate the water loss associated with land-surface cooling, we applied a surface energy balance model. Our initial estimates suggest 2.7 mm/d of water may be used in supplying cooling ecosystem services in the Phoenix region on a summer day. The availability and corresponding resource use requirements of these ecosystem services had a strongly positive relationship with neighborhood income in the year 2000. However, economic stratification in access to services is a recent development: no vegetation-income relationship was observed in 1970, and a clear trend of increasing correlation was evident through 2000. To alleviate neighborhood inequality in risks from extreme heat through increased vegetation and evaporative cooling, large increases in regional water use would be required. Together, these results suggest the need for a systems evaluation of the benefits, costs, spatial structure, and temporal trajectory for the use of ecosystem services to moderate climate extremes. Increasing vegetation is one strategy for moderating regional climate changes in urban areas and simultaneously providing multiple ecosystem services. However, vegetation has economic, water, and social equity implications that vary dramatically across neighborhoods and need to be managed through informed environmental policies.

Evolution of star formation conditions from high-redshift to low-redshift

NASA Astrophysics Data System (ADS)

Shirazi, Maryam

2015-08-01

There are some hints indicating extreme interstellar medium (ISM) conditions at high redshift e.g., harder ionsing radiation fields and higher electron densities. By analysing the ionisation state of galaxies using their [OIII]5007/[OII]3727 line ratios we recently showed that star-forming galaxies at z~ 1. 5 -- 3. 5 have higher ionisation parameters and higher gas densities relative to that of local galaxies with similar global properties (Shirazi et al. 2014). This means the intrinsic properties e.g., the density of star forming regions at high redshift is different from what we observe in the local Universe. Based on the distribution of galaxies in the BPT diagram, it is proposed that the transition to nearby like conditions happen at 0. 8 < z < 1. 5 (Kewley et al 2013). However, we do not know how star-forming regions of the intermediate redshift galaxies are compared to that of high redshift galaxies that have higher gas fractions and are close to the peak of star formation activity in the Universe. We use the unique capability of the MUSE to indirectly trace the ISM conditions at those redshifts. We measure the spatially-resolved ionisation parameter using [OIII ]5007/ [O II]3727 ratio and we measure the spatially resolved gas density using the [OII] 3727,3729 doublet. We probe the spatial distributions of the ionisation parameter and gas density and search for systematic differences between high, intermediate and low redshift galaxies in terms of their global galaxy properties.

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

NASA Technical Reports Server (NTRS)

Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

2013-01-01

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

Investigation of temporal-resolved emission spectra of highly charged Al ions from laser-produced plasmas

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

Su, M. G., E-mail: sumg@nwnu.edu.cn; Sun, D. X.; Dong, C. Z.

2016-03-15

Temporal evolution of extreme ultraviolet emission from laser-produced aluminum (Al) plasma has been experimentally and theoretically investigated. Al plasmas have been measured by using the temporal-spatially resolved laser-produced plasma technique. The emission lines can be identified from 2p-3s, 3d, 4s, 4d, 5d transition lines from Al{sup 3+} to Al{sup 6+} ions. In order to quickly diagnose the plasma, the assumptions of a normalized Boltzmann distribution among the excited states and a steady-state collisional-radiative model are used to estimate the values of electron temperature and electron density in plasma. We succeeded in reproducing the simulated spectra related to the different timemore » delays, which are in good agreement with experiments. Temporal evolution behavior of highly charged Al ions in plasma has been analyzed, and the exponential decay about electron temperature and electron density has been obtained. The results indicate that the temporal-spatially resolved measurement is essential for accurate understanding of evolution behavior of highly charged ions in laser-produced plasmas.« less

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

The Belle-II Depfet Pixel Detector at the Superkekb Flavour Factory

NASA Astrophysics Data System (ADS)

Heindl, Stefan

2012-08-01

The ongoing upgrade of the asymmetric electron positron collider KEKB also requires extensive detector upgrades to cope with the new design luminosity of 8 · 1035 cm-2 · s-1 · Of critical importance is the new silicon pixel vertex tracker, which will significantly improve the decay vertex resolution, crucial for time dependent CP violation measurements. This new detector will consist of two layers of DEPFET pixel seii8ors very close to the interaction point. These sensors combine both particle detection and amplification of the signal by embedding a field effect transistor into a 75 μm thick fully depleted silicon substrate, providing very high signal to noise ratios and excellent spatial resolution. Using this technology satisfies the given requirements of extremely low material and high radiation tolerance at the new Belle II experiment. The power dissipation due to continuous readout at high rate and spatial constraints also give strict requirements for the mechanical support and cooling of the new detector. We will discuss the overall concept of the pixel vertex tracker, its expected performance and the challenging mechanical integration.

Assessing the Impacts of Flooding Caused by Extreme Rainfall Events Through a Combined Geospatial and Numerical Modeling Approach

NASA Astrophysics Data System (ADS)

Santillan, J. R.; Amora, A. M.; Makinano-Santillan, M.; Marqueso, J. T.; Cutamora, L. C.; Serviano, J. L.; Makinano, R. M.

2016-06-01

In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.

Climate change projections over three metropolitan regions in Southeast Brazil using the non-hydrostatic Eta regional climate model at 5-km resolution

NASA Astrophysics Data System (ADS)

Lyra, Andre; Tavares, Priscila; Chou, Sin Chan; Sueiro, Gustavo; Dereczynski, Claudine; Sondermann, Marcely; Silva, Adan; Marengo, José; Giarolla, Angélica

2018-04-01

The objective of this work is to assess changes in three metropolitan regions of Southeast Brazil (Rio de Janeiro, São Paulo, and Santos) based on the projections produced by the Eta Regional Climate Model (RCM) at very high spatial resolution, 5 km. The region, which is densely populated and extremely active economically, is frequently affected by intense rainfall events that trigger floods and landslides during the austral summer. The analyses are carried out for the period between 1961 and 2100. The 5-km simulations are results from a second downscaling nesting in the HadGEM2-ES RCP4.5 and RCP8.5 simulations. Prior to the assessment of the projections, the higher resolution simulations were evaluated for the historical period (1961-1990). The comparison between the 5-km and the coarser driver model simulations shows that the spatial patterns of precipitation and temperature of the 5-km Eta simulations are in good agreement with the observations. The simulated frequency distribution of the precipitation and temperature extremes from the 5-km Eta RCM is consistent with the observed structure and extreme values. Projections of future climate change using the 5-km Eta runs show stronger warming in the region, primarily during the summer season, while precipitation is strongly reduced. Projected temperature extremes show widespread heating with maximum temperatures increasing by approximately 9 °C in the three metropolitan regions by the end of the century in the RCP8.5 scenario. A trend of drier climate is also projected using indices based on daily precipitation, which reaches annual rainfall reductions of more than 50 % in the state of Rio de Janeiro and between 40 and 45 % in São Paulo and Santos. The magnitude of these changes has negative implications to the population health conditions, energy security, and economy.

Phenological response of an Arizona dryland forest to short-term climatic extremes

USGS Publications Warehouse

Walker, Jessica; de Beurs, Kirsten; Wynne, Randolph

2015-01-01

Baseline information about dryland forest phenology is necessary to accurately anticipate future ecosystem shifts. The overarching goal of our study was to investigate the variability of vegetation phenology across a dryland forest landscape in response to climate alterations. We analyzed the influence of site characteristics and climatic conditions on the phenological patterns of an Arizona, USA, ponderosa pine (Pinus ponderosa) forest during a five-year period (2005 to 2009) that encompassed extreme wet and dry precipitation regimes. We assembled 80 synthetic Landsat images by applying the spatial and temporal adaptive reflectance fusion method (STARFM) to 500 m MODIS and 30 m Landsat-5 Thematic Mapper (TM) data. We tested relationships between site characteristics and the timing of peak Normalized Difference Vegetation Index (NDVI) to assess the effect of climatic stress on the green-up of individual pixels during or after the summer monsoon. Our results show that drought-induced stress led to a fragmented phenological response that was highly dependent on microsite parameters, as both the spatial autocorrelation of peak timing and the number of significant site variables increased during the drought year. Pixels at lower elevations and with higher proportions of herbaceous vegetation were more likely to exhibit dynamic responses to changes in precipitation conditions. Our study demonstrates the complexity of responses within dryland forest ecosystems and highlights the need for standardized monitoring of phenology trends in these areas. The spatial and temporal variability of phenological signals may provide a quantitative solution to the problem of how to evaluate dryland land surface trends across time.

Fine-scale spatial distribution of orchid mycorrhizal fungi in the soil of host-rich grasslands.

PubMed

Voyron, Samuele; Ercole, Enrico; Ghignone, Stefano; Perotto, Silvia; Girlanda, Mariangela

2017-02-01

Mycorrhizal fungi are essential for the survival of orchid seedlings under natural conditions. The distribution of these fungi in soil can constrain the establishment and resulting spatial arrangement of orchids at the local scale, but the actual extent of occurrence and spatial patterns of orchid mycorrhizal (OrM) fungi in soil remain largely unknown. We addressed the fine-scale spatial distribution of OrM fungi in two orchid-rich Mediterranean grasslands by means of high-throughput sequencing of fungal ITS2 amplicons, obtained from soil samples collected either directly beneath or at a distance from adult Anacamptis morio and Ophrys sphegodes plants. Like ectomycorrhizal and arbuscular mycobionts, OrM fungi (tulasnelloid, ceratobasidioid, sebacinoid and pezizoid fungi) exhibited significant horizontal spatial autocorrelation in soil. However, OrM fungal read numbers did not correlate with distance from adult orchid plants, and several of these fungi were extremely sporadic or undetected even in the soil samples containing the orchid roots. Orchid mycorrhizal 'rhizoctonias' are commonly regarded as unspecialized saprotrophs. The sporadic occurrence of mycobionts of grassland orchids in host-rich stands questions the view of these mycorrhizal fungi as capable of sustained growth in soil. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Skillful prediction of hot temperature extremes over the source region of ancient Silk Road.

PubMed

Zhang, Jingyong; Yang, Zhanmei; Wu, Lingyun

2018-04-27

The source region of ancient Silk Road (SRASR) in China, a region of around 150 million people, faces a rapidly increased risk of extreme heat in summer. In this study, we develop statistical models to predict summer hot temperature extremes over the SRASR based on a timescale decomposition approach. Results show that after removing the linear trends, the inter-annual components of summer hot days and heatwaves over the SRASR are significantly related with those of spring soil temperature over Central Asia and sea surface temperature over Northwest Atlantic while their inter-decadal components are closely linked to those of spring East Pacific/North Pacific pattern and Atlantic Multidecadal Oscillation for 1979-2016. The physical processes involved are also discussed. Leave-one-out cross-validation for detrended 1979-2016 time series indicates that the statistical models based on identified spring predictors can predict 47% and 57% of the total variances of summer hot days and heatwaves averaged over the SRASR, respectively. When the linear trends are put back, the prediction skills increase substantially to 64% and 70%. Hindcast experiments for 2012-2016 show high skills in predicting spatial patterns of hot temperature extremes over the SRASR. The statistical models proposed herein can be easily applied to operational seasonal forecasting.

Synchrony, Weather, and Cycles in Southern Pine Beetle (Coleoptera: Curculionidae).

PubMed

Reeve, John D

2018-02-08

Spatial synchrony and cycles are common features of forest insect pests, but are often studied as separate phenomenon. Using time series of timber damage caused by Dendroctonus frontalis Zimmermann (Coleoptera: Curculionidae) (southern pine beetle) in 10 states within the southern United States, this study examines synchrony in D. frontalis abundance, the synchronizing effects of temperature extremes, and the evidence for shared cycles among state populations. Cross-correlation and cluster analyses are used to quantify synchrony across a range of geographic distances and to identify groups of states with synchronous dynamics. Similar techniques are used to quantify spatial synchrony in temperature extremes and to examine their relationship to D. frontalis fluctuations. Cross-wavelet analysis is then used to examine pairs of time series for shared cycles. These analyses suggest there is substantial synchrony among states in D. frontalis fluctuations, and there are regional groups of states with similar dynamics. Synchrony in D. frontalis fluctuations also appears related to spatial synchrony in summer and winter temperature extremes. The cross-wavelet results suggest that D. frontalis dynamics may differ among regions and are not stationary. Significant oscillations were present in some states over certain time intervals, suggesting an endogenous feedback mechanism. Management of D. frontalis outbreaks could potentially benefit from a multistate regional approach because populations are synchronous on this level. Extreme summer temperatures are likely to become the most important synchronizing agent due to climate change. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Geo-spatial analysis of temporal trends of temperature and its extremes over India using daily gridded (1°×1°) temperature data of 1969-2005

NASA Astrophysics Data System (ADS)

Chakraborty, Abhishek; Seshasai, M. V. R.; Rao, S. V. C. Kameswara; Dadhwal, V. K.

2017-10-01

Daily gridded (1°×1°) temperature data (1969-2005) were used to detect spatial patterns of temporal trends of maximum and minimum temperature (monthly and seasonal), growing degree days (GDDs) over the crop-growing season ( kharif, rabi, and zaid) and annual frequencies of temperature extremes over India. The direction and magnitude of trends, at each grid level, were estimated using the Mann-Kendall statistics ( α = 0.05) and further assessed at the homogeneous temperature regions using a field significance test ( α=0.05). General warming trends were observed over India with considerable variations in direction and magnitude over space and time. The spatial extent and the magnitude of the increasing trends of minimum temperature (0.02-0.04 °C year-1) were found to be higher than that of maximum temperature (0.01-0.02 °C year-1) during winter and pre-monsoon seasons. Significant negative trends of minimum temperature were found over eastern India during the monsoon months. Such trends were also observed for the maximum temperature over northern and eastern parts, particularly in the winter month of January. The general warming patterns also changed the thermal environment of the crop-growing season causing significant increase in GDDs during kharif and rabi seasons across India. The warming climate has also caused significant increase in occurrences of hot extremes such as hot days and hot nights, and significant decrease in cold extremes such as cold days and cold nights.

Ownership and ecosystem as sources of spatial heterogeneity in a forested landscape, Wisconsin, USA

Treesearch

Thomas R. Crow; George E. Host; David J. Mladenoff

1999-01-01

The interaction between physical environment and land ownership in creating spatial heterogeneity was studied in largely forested landscapes of northern Wisconsin, USA. A stratified random approach was used in which 2500-ha plots representing two ownerships (National Forest and private non-industrial) were located within two regional ecosystems (extremely well-drained...

The TESIS experiment on the CORONAS-PHOTON spacecraft

NASA Astrophysics Data System (ADS)

Kuzin, S. V.; Zhitnik, I. A.; Shestov, S. V.; Bogachev, S. A.; Bugaenko, O. I.; Ignat'ev, A. P.; Pertsov, A. A.; Ulyanov, A. S.; Reva, A. A.; Slemzin, V. A.; Sukhodrev, N. K.; Ivanov, Yu. S.; Goncharov, L. A.; Mitrofanov, A. V.; Popov, S. G.; Shergina, T. A.; Solov'ev, V. A.; Oparin, S. N.; Zykov, A. M.

2011-04-01

On February 26, 2009, the first data was obtained in the TESIS experiment on the research of the solar corona using imaging spectroscopy. The TESIS is a part of the scientific equipment of the CORONAS-PHO-TON spacecraft and is designed for imaging the solar corona in soft X-ray and extreme ultraviolet regions of the spectrum with high spatial, spectral, and temporal resolutions at altitudes from the transition region to three solar radii. The article describes the main characteristics of the instrumentation, management features, and operation modes.

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.

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

Extreme Universe Space Observatory (EUSO) Optics Module

NASA Technical Reports Server (NTRS)

Young, Roy; Christl, Mark

2008-01-01

A demonstration part will be manufactured in Japan on one of the large Toshiba machines with a diameter of 2.5 meters. This will be a flat PMMA disk that is cut between 0.5 and 1.25 meters radius. The cut should demonstrate manufacturing the most difficult parts of the 2.5 meter Fresnel pattern and the blazed grating on the diffractive surface. Optical simulations, validated with the subscale prototype, will be used to determine the limits on manufacturing errors (tolerances) that will result in optics that meet EUSO s requirements. There will be limits on surface roughness (or errors at high spatial frequency); radial and azimuthal slope errors (at lower spatial frequencies) and plunge cut depth errors in the blazed grating. The demonstration part will be measured to determine whether it was made within the allowable tolerances.

Terahertz-wave near-field imaging with subwavelength resolution using surface-wave-assisted bow-tie aperture

NASA Astrophysics Data System (ADS)

Ishihara, Kunihiko; Ohashi, Keishi; Ikari, Tomofumi; Minamide, Hiroaki; Yokoyama, Hiroyuki; Shikata, Jun-ichi; Ito, Hiromasa

2006-11-01

We demonstrate the terahertz-wave near-field imaging with subwavelength resolution using a bow-tie shaped aperture surrounded by concentric periodic structures in a metal film. A subwavelength aperture with concentric periodic grooves, which are known as a bull's eye structure, shows extremely large enhanced transmission beyond the diffraction limit caused by the resonant excitation of surface waves. Additionally, a bow-tie aperture exhibits extraordinary field enhancement at the sharp tips of the metal, which enhances the transmission and the subwavelength spatial resolution. We introduced a bow-tie aperture to the bull's eye structure and achieved high spatial resolution (˜λ/17) in the near-field region. The terahertz-wave near-field image of the subwavelength metal pattern (pattern width=20μm) was obtained for the wavelength of 207μm.

SUMER: Solar Ultraviolet Measurements of Emitted Radiation

NASA Technical Reports Server (NTRS)

Wilhelm, K.; Axford, W. I.; Curdt, W.; Gabriel, A. H.; Grewing, M.; Huber, M. C. E.; Jordan, M. C. E.; Lemaire, P.; Marsch, E.; Poland, A. I.

1988-01-01

The SUMER (solar ultraviolet measurements of emitted radiation) experiment is described. It will study flows, turbulent motions, waves, temperatures and densities of the plasma in the upper atmosphere of the Sun. Structures and events associated with solar magnetic activity will be observed on various spatial and temporal scales. This will contribute to the understanding of coronal heating processes and the solar wind expansion. The instrument will take images of the Sun in EUV (extreme ultra violet) light with high resolution in space, wavelength and time. The spatial resolution and spectral resolving power of the instrument are described. Spectral shifts can be determined with subpixel accuracy. The wavelength range extends from 500 to 1600 angstroms. The integration time can be as short as one second. Line profiles, shifts and broadenings are studied. Ratios of temperature and density sensitive EUV emission lines are established.

Interferometric at-wavelength flare characterization of EUV optical systems

DOEpatents

Naulleau, Patrick P.; Goldberg, Kenneth Alan

2001-01-01

The extreme ultraviolet (EUV) phase-shifting point diffraction interferometer (PS/PDI) provides the high-accuracy wavefront characterization critical to the development of EUV lithography systems. Enhancing the implementation of the PS/PDI can significantly extend its spatial-frequency measurement bandwidth. The enhanced PS/PDI is capable of simultaneously characterizing both wavefront and flare. The enhanced technique employs a hybrid spatial/temporal-domain point diffraction interferometer (referred to as the dual-domain PS/PDI) that is capable of suppressing the scattered-reference-light noise that hinders the conventional PS/PDI. Using the dual-domain technique in combination with a flare-measurement-optimized mask and an iterative calculation process for removing flare contribution caused by higher order grating diffraction terms, the enhanced PS/PDI can be used to simultaneously measure both figure and flare in optical systems.

Spatially explicit scenario analysis for hydrologic services in an urbanizing agricultural watershed

NASA Astrophysics Data System (ADS)

Qiu, J.; Booth, E.; Carpenter, S. R.; Turner, M.

2013-12-01

The sustainability of hydrologic services (benefits to people generated by terrestrial ecosystem effects on freshwater) is challenged by changes in climate and land use. Despite the importance of hydrologic services, few studies have investigated how the provision of ecosystem services related to freshwater quantity and quality may vary in magnitude and spatial pattern for alternative future trajectories. Such analyses may provide useful information for sustaining freshwater resources in the face of a complex and uncertain future. We analyzed the supply of multiple hydrologic services from 2010 to 2070 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) What are the potential trajectories for the supply of hydrologic services under contrasting but plausible future scenarios? (ii) Where on the landscape is the delivery of hydrologic services most vulnerable to future changes? The Nested Watershed scenario represents extreme climate change (warmer temperatures and more frequent extreme events) and a concerted response from institutions, whereas in the Investment in Innovation scenario, climate change is less severe and technological innovations play a major role. Despite more extreme climate in the Nested Watershed scenario, all hydrologic services (i.e., freshwater supply, surface water quality, flood regulation) were maintained or enhanced (~30%) compared to the 2010 baseline, by strict government interventions that prioritized freshwater resources. Despite less extreme climate in the Investment in Innovation scenario and advances in green technology, only surface water quality and flood regulation were maintained or increased (~80%); freshwater supply declined by 25%, indicating a potential future tradeoff between water quality and quantity. Spatially, the locations of greatest vulnerability (i.e., decline) differed by service and among scenarios. In the Nested Watershed scenario, although freshwater supply and surface water quality were sustained or enhanced overall, these hydrologic services declined in ~60% and 20% of the landscape, respectively. The greatest improvement for most hydrologic services corresponded to areas of restored wetland, forest and perennial crops, which were less vulnerable to future degradation. In the Investment in Innovation scenario, freshwater supply declined in almost the entire watershed; improvement of surface water quality and flood regulation occurred mainly in urban areas, where highly engineered systems made them less vulnerable. Overall, our results indicated that hydrologic services will respond differently to future climate and land-use change, and sustaining one may involve tradeoffs of another. Technological progress can conserve particular services but might not be the panacea for the future. How society reacts in the face of changes can have an important role in determining the pathways to the future and the provision and spatial patterns of ecosystem services.

Microbial Communities of High-Elevation Fumaroles, Penitentes, and Dry Tephra "Soils" of the Puna de Atacama Volcanic Zone.

PubMed

Solon, Adam J; Vimercati, Lara; Darcy, J L; Arán, Pablo; Porazinska, Dorota; Dorador, C; Farías, M E; Schmidt, S K

2018-01-05

The aim of this study was to understand the spatial distribution of microbial communities (18S and 16S rRNA genes) across one of the harshest terrestrial landscapes on Earth. We carried out Illumina sequencing using samples from two expeditions to the high slopes (up to 6050 m.a.s.l.) of Volcán Socompa and Llullaillaco to describe the microbial communities associated with the extremely dry tephra compared to areas that receive water from fumaroles and ice fields made up of nieves penitentes. There were strong spatial patterns relative to these landscape features with the most diverse (alpha diversity) communities being associated with fumaroles. Penitentes did not significantly increase alpha diversity compared to dry tephra at the same elevation (5825 m.a.s.l.) on Volcán Socompa, but the structure of the 18S community (beta diversity) was significantly affected by the presence of penitentes on both Socompa and Llullaillaco. In addition, the 18S community was significantly different in tephra wetted by penitentes versus dry tephra sites across many elevations on Llullaillaco. Traditional phototrophs (algae and cyanobacteria) were abundant in wetter tephra associated with fumaroles, and algae (but not cyanobacteria) were common in tephra associated with penitentes. Dry tephra had neither algae nor cyanobacteria but did host potential phototrophs in the Rhodospirillales on Volcán Llullaillaco, but not on Socompa. These results provide new insights into the distribution of microbes across one of the most extreme terrestrial environments on Earth and provide the first ever glimpse of life associated with nieves penitentes, spire-shaped ice structures that are widespread across the mostly unexplored high-elevation Andean Central Volcanic Zone.

A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-07-01

Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

Rainfall disaggregation for urban hydrology: Effects of spatial consistence

NASA Astrophysics Data System (ADS)

Müller, Hannes; Haberlandt, Uwe

2015-04-01

For urban hydrology rainfall time series with a high temporal resolution are crucial. Observed time series of this kind are very short in most cases, so they cannot be used. On the contrary, time series with lower temporal resolution (daily measurements) exist for much longer periods. The objective is to derive time series with a long duration and a high resolution by disaggregating time series of the non-recording stations with information of time series of the recording stations. The multiplicative random cascade model is a well-known disaggregation model for daily time series. For urban hydrology it is often assumed, that a day consists of only 1280 minutes in total as starting point for the disaggregation process. We introduce a new variant for the cascade model, which is functional without this assumption and also outperforms the existing approach regarding time series characteristics like wet and dry spell duration, average intensity, fraction of dry intervals and extreme value representation. However, in both approaches rainfall time series of different stations are disaggregated without consideration of surrounding stations. This yields in unrealistic spatial patterns of rainfall. We apply a simulated annealing algorithm that has been used successfully for hourly values before. Relative diurnal cycles of the disaggregated time series are resampled to reproduce the spatial dependence of rainfall. To describe spatial dependence we use bivariate characteristics like probability of occurrence, continuity ratio and coefficient of correlation. Investigation area is a sewage system in Northern Germany. We show that the algorithm has the capability to improve spatial dependence. The influence of the chosen disaggregation routine and the spatial dependence on overflow occurrences and volumes of the sewage system will be analyzed.

Performance of the Multi-Radar Multi-Sensor System over the Lower Colorado River, Texas

NASA Astrophysics Data System (ADS)

Bayabil, H. K.; Sharif, H. O.; Fares, A.; Awal, R.; Risch, E.

2017-12-01

Recently observed increases in intensities and frequencies of climate extremes (e.g., floods, dam failure, and overtopping of river banks) necessitate the development of effective disaster prevention and mitigation strategies. Hydrologic models can be useful tools in predicting such events at different spatial and temporal scales. However, accuracy and prediction capability of such models are often constrained by the availability of high-quality representative hydro-meteorological data (e.g., precipitation) that are required to calibrate and validate such models. Improved technologies and products such as the Multi-Radar Multi-Sensor (MRMS) system that allows gathering and transmission of vast meteorological data have been developed to provide such data needs. While the MRMS data are available with high spatial and temporal resolutions (1 km and 15 min, respectively), its accuracy in estimating precipitation is yet to be fully investigated. Therefore, the main objective of this study is to evaluate the performance of the MRMS system in effectively capturing precipitation over the Lower Colorado River, Texas using observations from a dense rain gauge network. In addition, effects of spatial and temporal aggregation scales on the performance of the MRMS system were evaluated. Point scale comparisons were made at 215 gauging locations using rain gauges and MRMS data from May 2015. Moreover, the effects of temporal and spatial data aggregation scales (30, 45, 60, 75, 90, 105, and 120 min) and (4 to 50 km), respectively on the performance of the MRMS system were tested. Overall, the MRMS system (at 15 min temporal resolution) captured precipitation reasonably well, with an average R2 value of 0.65 and RMSE of 0.5 mm. In addition, spatial and temporal data aggregations resulted in increases in R2 values. However, reduction in RMSE was achieved only with an increase in spatial aggregations.

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.

Comparison Of Downscaled CMIP5 Precipitation Datasets For Projecting Changes In Extreme Precipitation In The San Francisco Bay Area.

NASA Technical Reports Server (NTRS)

Milesi, Cristina; Costa-Cabral, Mariza; Rath, John; Mills, William; Roy, Sujoy; Thrasher, Bridget; Wang, Weile; Chiang, Felicia; Loewenstein, Max; Podolske, James

2014-01-01

Water resource managers planning for the adaptation to future events of extreme precipitation now have access to high resolution downscaled daily projections derived from statistical bias correction and constructed analogs. We also show that along the Pacific Coast the Northern Oscillation Index (NOI) is a reliable predictor of storm likelihood, and therefore a predictor of seasonal precipitation totals and likelihood of extremely intense precipitation. Such time series can be used to project intensity duration curves into the future or input into stormwater models. However, few climate projection studies have explored the impact of the type of downscaling method used on the range and uncertainty of predictions for local flood protection studies. Here we present a study of the future climate flood risk at NASA Ames Research Center, located in South Bay Area, by comparing the range of predictions in extreme precipitation events calculated from three sets of time series downscaled from CMIP5 data: 1) the Bias Correction Constructed Analogs method dataset downscaled to a 1/8 degree grid (12km); 2) the Bias Correction Spatial Disaggregation method downscaled to a 1km grid; 3) a statistical model of extreme daily precipitation events and projected NOI from CMIP5 models. In addition, predicted years of extreme precipitation are used to estimate the risk of overtopping of the retention pond located on the site through simulations of the EPA SWMM hydrologic model. Preliminary results indicate that the intensity of extreme precipitation events is expected to increase and flood the NASA Ames retention pond. The results from these estimations will assist flood protection managers in planning for infrastructure adaptations.

Use of local statistics to reveal hidden information of pollution hotspots in urban soil geochemistry

NASA Astrophysics Data System (ADS)

Zhang, Chaosheng

2017-04-01

The identification of pollution hotspots is an important approach for a better understanding of spatial distribution patterns and the exploration for their influencing factors in environmental studies. One of the most often asked questions in an environmental investigation is: Where are the pollution hotspots? This presentation explains one of the popularly used methodologies called local index of spatial association (LISA) and its applications in urban geochemical studies in Galway, Ireland and London of the UK. The LISA is a useful tool for identifying pollution hotspots and classifying them into spatial clusters and spatial outliers. The results were affected by the definition of weight function, data transformation and existence of extreme values, and it is suggested that all these influencing factors should be considered until reasonable and reliable results are obtained. This method has been applied to identify Pb pollution in Galway, polluted areas in bonfires sites, elevated P and REE concentrations in London. Hotspots in identified in urban soils are related to locations of high road density, traditional festival bonfires, industries and other human activities. The results of hotspots analysis provide useful information for the management of urban soils.

Random Distribution Pattern and Non-adaptivity of Genome Size in a Highly Variable Population of Festuca pallens

PubMed Central

Šmarda, Petr; Bureš, Petr; Horová, Lucie

2007-01-01

Background and Aims The spatial and statistical distribution of genome sizes and the adaptivity of genome size to some types of habitat, vegetation or microclimatic conditions were investigated in a tetraploid population of Festuca pallens. The population was previously documented to vary highly in genome size and is assumed as a model for the study of the initial stages of genome size differentiation. Methods Using DAPI flow cytometry, samples were measured repeatedly with diploid Festuca pallens as the internal standard. Altogether 172 plants from 57 plots (2·25 m2), distributed in contrasting habitats over the whole locality in South Moravia, Czech Republic, were sampled. The differences in DNA content were confirmed by the double peaks of simultaneously measured samples. Key Results At maximum, a 1·115-fold difference in genome size was observed. The statistical distribution of genome sizes was found to be continuous and best fits the extreme (Gumbel) distribution with rare occurrences of extremely large genomes (positive-skewed), as it is similar for the log-normal distribution of the whole Angiosperms. Even plants from the same plot frequently varied considerably in genome size and the spatial distribution of genome sizes was generally random and unautocorrelated (P > 0·05). The observed spatial pattern and the overall lack of correlations of genome size with recognized vegetation types or microclimatic conditions indicate the absence of ecological adaptivity of genome size in the studied population. Conclusions These experimental data on intraspecific genome size variability in Festuca pallens argue for the absence of natural selection and the selective non-significance of genome size in the initial stages of genome size differentiation, and corroborate the current hypothetical model of genome size evolution in Angiosperms (Bennetzen et al., 2005, Annals of Botany 95: 127–132). PMID:17565968

Characterization of extreme ultraviolet laser ablation mass spectrometry for actinide trace analysis and nanoscale isotopic imaging

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

Green, Tyler; Kuznetsov, Ilya; Willingham, David

The purpose of this research was to characterize Extreme Ultraviolet Time-of-Flight (EUV TOF) Laser Ablation Mass Spectrometry for high spatial resolution elemental and isotopic analysis. We compare EUV TOF results with Secondary Ionization Mass Spectrometry (SIMS) to orient the EUV TOF method within the overall field of analytical mass spectrometry. Using the well-characterized NIST 61x glasses, we show that the EUV ionization approach produces relatively few molecular ion interferences in comparison to TOF SIMS. We demonstrate that the ratio of element ion to element oxide ion is adjustable with EUV laser pulse energy and that the EUV TOF instrument hasmore » a sample utilization efficiency of 0.014%. The EUV TOF system also achieves a lateral resolution of 80 nm and we demonstrate this lateral resolution with isotopic imaging of closely spaced particles or uranium isotopic standard materials.« less

Three-dimensional nanoscale molecular imaging by extreme ultraviolet laser ablation mass spectrometry

PubMed Central

Kuznetsov, Ilya; Filevich, Jorge; Dong, Feng; Woolston, Mark; Chao, Weilun; Anderson, Erik H.; Bernstein, Elliot R.; Crick, Dean C.; Rocca, Jorge J.; Menoni, Carmen S.

2015-01-01

Analytical probes capable of mapping molecular composition at the nanoscale are of critical importance to materials research, biology and medicine. Mass spectral imaging makes it possible to visualize the spatial organization of multiple molecular components at a sample's surface. However, it is challenging for mass spectral imaging to map molecular composition in three dimensions (3D) with submicron resolution. Here we describe a mass spectral imaging method that exploits the high 3D localization of absorbed extreme ultraviolet laser light and its fundamentally distinct interaction with matter to determine molecular composition from a volume as small as 50 zl in a single laser shot. Molecular imaging with a lateral resolution of 75 nm and a depth resolution of 20 nm is demonstrated. These results open opportunities to visualize chemical composition and chemical changes in 3D at the nanoscale. PMID:25903827

Nerve Entrapment Syndromes at the Wrist and Elbow by Sonography.

PubMed

Klauser, Andrea S; Buzzegoli, Tommaso; Taljanovic, Mihra S; Strobl, Sylvia; Rauch, Stefan; Teh, James; Wanschitz, Julia; Löscher, Wolfgang; Martinoli, Carlo

2018-07-01

Nerve entrapment syndromes of the upper extremity are associated with structural abnormalities or by an intrinsic abnormality of the nerve. Nerve entrapment syndromes generally have a typical clinical presentation, and findings on physical examination and in conjunction with electrodiagnostic studies imaging is used to evaluate the cause, severity, and etiology of the entrapment. With the development of high-frequency linear array transducers (12-24 MHz), ultrasound (US) is incomparable in terms of spatial resolution to depict morphological aspects and changes in nerves. US can identify the abnormalities causing entrapment, such as fibrous bands, ganglia, anomalous muscles, and osseous deformities, with the advantage of dynamic assessment under active and passive examination. US is a unique diagnostic modality that allows superb visualization of both large and small peripheral terminal nerve branches of the upper extremity and enables the correct diagnosis of various nerve entrapment syndromes. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

System characterization of RiceWrist-S: a forearm-wrist exoskeleton for upper extremity rehabilitation.

PubMed

Pehlivan, Ali Utku; Rose, Chad; O'Malley, Marcia K

2013-06-01

Rehabilitation of the distal joints of the upper extremities is crucial to restore the ability to perform activities of daily living to patients with neurological lesions resulting from stroke or spinal cord injury. Robotic rehabilitation has been identified as a promising new solution, however, much of the existing technology in this field is focused on the more proximal joints of the upper arm. A recently presented device, the RiceWrist-S, focuses on the rehabilitation of the forearm and wrist, and has undergone a few important design changes. This paper first addresses the design improvements achieved in the recent design iteration, and then presents the system characterization of the new device. We show that the RiceWrist-S has capabilities beyond other existing devices, and exhibits favorable system characteristics as a rehabilitation device, in particular torque output, range of motion, closed loop position performance, and high spatial resolution.

Monitoring of Vegetation Impact Due to Trampling on Cadillac Mountain Summit Using High Spatial Resolution Remote Sensing Data Sets

NASA Astrophysics Data System (ADS)

Kim, Min-Kook; Daigle, John J.

2012-11-01

Cadillac Mountain—the highest peak along the eastern seaboard of the United States—is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies—based on placing physical barriers and educational messages for visitors—have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P < 0.001). Research implications are explored that relate to the spatial extent of the radial patterns of impact of trampling on vegetation at the site level. Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.

Monitoring of vegetation impact due to trampling on Cadillac Mountain summit using high spatial resolution remote sensing data sets.

PubMed

Kim, Min-Kook; Daigle, John J

2012-11-01

Cadillac Mountain--the highest peak along the eastern seaboard of the United States--is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies--based on placing physical barriers and educational messages for visitors--have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P < 0.001). Research implications are explored that relate to the spatial extent of the radial patterns of impact of trampling on vegetation at the site level. Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.

Application of High- and Low-Orbiting Radio Tomography for Exploring the Ionospheric Structures on Different Scales

NASA Astrophysics Data System (ADS)

Andreeva, Elena; Padokhin, Artem; Nazarenko, Marina; Nesterov, Ivan; Tumanova, Yulia; Tereshchenko, Evgeniy; Kozharin, Maksim

2016-07-01

The methods of ionospheric radio tomography (RT) are actively developing at present. These methods are suitable for reconstructing the spatial distributions of electron density from radio signals transmitted from the navigational satellite systems and recorded by the networks of ground-based receivers. The RT systems based on the low-orbiting (LO) (Parus/Transit) navigational systems have been in operation since the early 1990s. Recently, the RT methods employing the signals from high-orbiting (HO) satellite navigational systems such as GPS/GLONASS have come into play. In our presentation, we discuss the accuracies, advantages, and limitations of LORT and HORT as well as the possibilities of their combined application fro reconstructing the structure of the ionosphere in the same region during the same time interval on the different spatiotemporal scales. The LORT reconstructions provide practically instantaneous (spanning 5-10 min) 2D snapshots of the ionosphere within a spatial interval with a length of up to a few thousand km. The vertical resolution of LORT is 25-30 km and the horizontal resolution, 15-25 km. The HORT methods are capable of reconstructing the 4D structure of the ionosphere (three spatial coordinates and time). The spatial resolution of HORT is generally not better than 100 km with a 60-20 min interval between the successive reconstructions. In the regions of dense receiving networks, the resolution can be improved to 30-50 km and the time step can be reduced to 30-10 min. In California and Japan which are covered by extremely dense receiving networks the resolution can be even higher (10-30 km) and the time interval between the reconstruction even shorter (up to 2 min). In the presentation, we discuss the LORT and HORT reconstructions of the ionosphere during different time periods of the 23rd and 24th solar cycles in the different regions of the world. We analyze the spatiotemporal features and dynamics of the ionosphere depending on the solar and geophysical conditions. Particular attention is attached to the periods of the strong geomagnetic disturbances. The stormy ionosphere is characterized by extremely sophisticated structure and rapid dynamics. Being affected by a variety of the perturbing factors, the ionospheric parameters experience striking variations which can be traced by the RT methods. The RT reconstructions revealed multi-extremal plasma structures, steep wall-like gradients of electron density, and spots of enhanced ionization. A complicated structure of the main ionization trough with its polar wall moving equatorwards was observed. In contrast to the middle and lower latitudes where the magnetic field largely shields the Earth from the energetic particle fluxes, the RT reconstructions in the northern high latitudes demonstrate the presence of localized highly ionized features and wavelike disturbances associated with the injections of corpuscular radiation into the ionosphere. We present and discuss the examples of the qualitative comparisons of the RT ionospheric images with the data on the ionizing particle fluxes measured by the DMSP satellite. The examples of RT data comparison with the ionosonde measurements are demonstrated.

Assessing Climate Change Impacts for Military Installations in the Southwest United States During the Warm Season

NASA Astrophysics Data System (ADS)

Castro, C.

2013-05-01

Arid and semi-arid regions are experiencing some of the most adverse impacts of climate change with increased heat waves, droughts, and extreme weather. These events will likely exacerbate socioeconomic and political instabilities in regions where the United States has vital strategic interests and ongoing military operations. The Southwest U.S. is strategically important in that it houses some of the most spatially expansive and important military installations in the country. The majority of severe weather events in the Southwest occur in association with the North American monsoon system (NAMS), and current observational record has shown a 'wet gets wetter and dry gets drier' global monsoon precipitation trend. We seek to evaluate the warm season extreme weather projection in the Southwest U.S., and how the extremes can affect Department of Defense (DoD) military facilities in that region. A baseline methodology is being developed to select extreme warm season weather events based on historical sounding data and moisture surge observations from Gulf of California. Numerical Weather Prediction (NWP)-type high resolution simulations will be performed for the extreme events identified from Weather Research and Forecast (WRF) model simulations initiated from IPCC GCM and NCAR Reanalysis data in both climate control and climate change periods. The magnitude in extreme event changes will be analyzed, and the synoptic forcing patterns of the future severe thunderstorms will provide a guide line to assess if the military installations in the Southwest will become more or less susceptible to severe weather in the future.

Lossless Video Sequence Compression Using Adaptive Prediction

NASA Technical Reports Server (NTRS)

Li, Ying; Sayood, Khalid

2007-01-01

We present an adaptive lossless video compression algorithm based on predictive coding. The proposed algorithm exploits temporal, spatial, and spectral redundancies in a backward adaptive fashion with extremely low side information. The computational complexity is further reduced by using a caching strategy. We also study the relationship between the operational domain for the coder (wavelet or spatial) and the amount of temporal and spatial redundancy in the sequence being encoded. Experimental results show that the proposed scheme provides significant improvements in compression efficiencies.

Visual and Spatial Mental Imagery: Dissociable Systems of Representation.

DTIC Science & Technology

1987-08-07

identification of visual stimuli (the visual agnosias ) could occur independently of impairr-’e"s in their spatial localization (Potzl. 1928: Lange. 1936) Patients...of brain damage that is generally associated with visual "PIre - i’ e/ e~~ :S~ OF Visual and Spatial Imagery 1i agnosia . Details of L.H.’s medical...This approach is nowhere more called for than in the study of subjects with visual object agnosia . a condition that is both extremely rare and somewhat

A geostatistical extreme-value framework for fast simulation of natural hazard events

PubMed Central

Stephenson, David B.

2016-01-01

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student’s t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements. PMID:27279768

Suitability of holographic beam scanning in high resolution applications

NASA Astrophysics Data System (ADS)

Kalita, Ranjan; Goutam Buddha, S. S.; Boruah, Bosanta R.

2018-02-01

The high resolution applications of a laser scanning imaging system very much demand the accurate positioning of the illumination beam. The galvanometer scanner based beam scanning imaging systems, on the other hand, suffer from both short term and long term beam instability issues. Fortunately Computer generated holography based beam scanning offers extremely accurate beam steering, which can be very useful for imaging in high-resolution applications in confocal microscopy. The holographic beam scanning can be achieved by writing a sequence of holograms onto a spatial light modulator and utilizing one of the diffracted orders as the illumination beam. This paper highlights relative advantages of such a holographic beam scanning based confocal system and presents some of preliminary experimental results.

Improvements of ModalMax High-Fidelity Piezoelectric Audio Device

NASA Technical Reports Server (NTRS)

Woodard, Stanley E.

2005-01-01

ModalMax audio speakers have been enhanced by innovative means of tailoring the vibration response of thin piezoelectric plates to produce a high-fidelity audio response. The ModalMax audio speakers are 1 mm in thickness. The device completely supplants the need to have a separate driver and speaker cone. ModalMax speakers can perform the same applications of cone speakers, but unlike cone speakers, ModalMax speakers can function in harsh environments such as high humidity or extreme wetness. New design features allow the speakers to be completely submersed in salt water, making them well suited for maritime applications. The sound produced from the ModalMax audio speakers has sound spatial resolution that is readily discernable for headset users.

Development of an Amorphous Selenium-Based Photodetector Driven by a Diamond Cold Cathode

PubMed Central

Masuzawa, Tomoaki; Saito, Ichitaro; Yamada, Takatoshi; Onishi, Masanori; Yamaguchi, Hisato; Suzuki, Yu; Oonuki, Kousuke; Kato, Nanako; Ogawa, Shuichi; Takakuwa, Yuji; Koh, Angel T. T.; Chua, Daniel H. C.; Mori, Yusuke; Shimosawa, Tatsuo; Okano, Ken

2013-01-01

Amorphous-selenium (a-Se) based photodetectors are promising candidates for imaging devices, due to their high spatial resolution and response speed, as well as extremely high sensitivity enhanced by an internal carrier multiplication. In addition, a-Se is reported to show sensitivity against wide variety of wavelengths, including visible, UV and X-ray, where a-Se based flat-panel X-ray detector was proposed. In order to develop an ultra high-sensitivity photodetector with a wide detectable wavelength range, a photodetector was fabricated using a-Se photoconductor and a nitrogen-doped diamond cold cathode. In the study, a prototype photodetector has been developed, and its response to visible and ultraviolet light are characterized. PMID:24152932

Automated Wetland Delineation from Multi-Frequency and Multi-Polarized SAR Images in High Temporal and Spatial Resolution

NASA Astrophysics Data System (ADS)

Moser, L.; Schmitt, A.; Wendleder, A.

2016-06-01

Water scarcity is one of the main challenges posed by the changing climate. Especially in semi-arid regions where water reservoirs are filled during the very short rainy season, but have to store enough water for the extremely long dry season, the intelligent handling of water resources is vital. This study focusses on Lac Bam in Burkina Faso, which is the largest natural lake of the country and of high importance for the local inhabitants for irrigated farming, animal watering, and extraction of water for drinking and sanitation. With respect to the competition for water resources an independent area-wide monitoring system is essential for the acceptance of any decision maker. The following contribution introduces a weather and illumination independent monitoring system for the automated wetland delineation with a high temporal (about two weeks) and a high spatial sampling (about five meters). The similarities of the multispectral and multi-polarized SAR acquisitions by RADARSAT-2 and TerraSAR-X are studied as well as the differences. The results indicate that even basic approaches without pre-classification time series analysis or post-classification filtering are already enough to establish a monitoring system of prime importance for a whole region.

The Nike Laser Facility and its Capabilities

NASA Astrophysics Data System (ADS)

Serlin, V.; Aglitskiy, Y.; Chan, L. Y.; Karasik, M.; Kehne, D. M.; Oh, J.; Obenschain, S. P.; Weaver, J. L.

2013-10-01

The Nike laser is a 56-beam krypton fluoride (KrF) system that provides 3 to 4 kJ of laser energy on target. The laser uses induced spatial incoherence to achieve highly uniform focal distributions. 44 beams are overlapped onto target with peak intensities up to 1016 W/cm2. The effective time-averaged illumination nonuniformity is < 0 . 2 %. Nike produces highly uniform ablation pressures on target allowing well-controlled experiments at pressures up to 20 Mbar. The other 12 laser beams are used to generate diagnostic x-rays radiographing the primary laser-illuminated target. The facility includes a front end that generates the desired temporal and spatial laser profiles, two electron-beam pumped KrF amplifiers, a computer-controlled optical system, and a vacuum target chamber for experiments. Nike is used to study the physics and technology issues of direct-drive laser fusion, such as, hydrodynamic and laser-plasma instabilities, studies of the response of materials to extreme pressures, and generation of X rays from laser-heated targets. Nike features a computer-controlled data acquisition system, high-speed, high-resolution x-ray and visible imaging systems, x-ray and visible spectrometers, and cryogenic target capability. Work supported by DOE/NNSA.

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.

The association between preceding drought occurrence and heat waves in the Mediterranean

NASA Astrophysics Data System (ADS)

Russo, Ana; Gouveia, Célia M.; Ramos, Alexandre M.; Páscoa, Patricia; Trigo, Ricardo M.

2017-04-01

A large number of weather driven extreme events has occurred worldwide in the last decade, namely in Europe that has been struck by record breaking extreme events with unprecedented socio-economic impacts, including the mega-heatwaves of 2003 in Europe and 2010 in Russia, and the large droughts in southwestern Europe in 2005 and 2012. The last IPCC report on extreme events points that a changing climate can lead to changes in the frequency, intensity, spatial extent, duration, and timing of weather and climate extremes. These, combined with larger exposure, can result in unprecedented risk to humans and ecosystems. In this context it is becoming increasingly relevant to improve the early identification and predictability of such events, as they negatively affect several socio-economic activities. Moreover, recent diagnostic and modelling experiments have confirmed that hot extremes are often preceded by surface moisture deficits in some regions throughout the world. In this study we analyze if the occurrence of hot extreme months is enhanced by the occurrence of preceding drought events throughout the Mediterranean area. In order to achieve this purpose, the number of hot days in the regions' hottest month will be associated with a drought indicator. The evolution and characterization of drought was analyzed using both the Standardized Precipitation Evaporation Index (SPEI) and the Standardized Precipitation Index (SPI), as obtained from CRU TS3.23 database for the period 1950-2014. We have used both SPI and SPEI for different time scales between 3 and 9 months with a spatial resolution of 0.5°. The number of hot days and nights per month (NHD and NHN) was determined using the ECAD-EOBS daily dataset for the same period and spatial resolution (dataset v14). The NHD and NHN were computed, respectively, as the number of days with a maximum or minimum temperature exceeding the 90th percentile. Results show that the most frequent hottest months for the Mediterranean region occur in July and August. Moreover, the magnitude of correlations between detrended NHD/NHN and the preceding 6- and 9-month SPEI/SPI are usually dimmer than for the 3 month time-scale. Most regions exhibit significantly negative correlations, i.e. high (low) NHD/NHN following negative (positive) SPEI/SPI values, and thus a potential for NHD/NHN early warning. Finally, correlations between the NHD/NHN with SPI and SPEI differ, with SPEI characterized by slightly higher values observed mainly for the 3-months time-scale. Acknowledgments: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project IMDROFLOOD (WaterJPI/0004/2014). Ana Russo thanks FCT for granted support (SFRH/BPD/99757/2014). A. M. Ramos was also supported by a FCT postdoctoral grant (FCT/DFRH/ SFRH/BPD/84328/2012).

Regional forest land cover characterisation using medium spatial resolution satellite data

USGS Publications Warehouse

Huang, Chengquan; Homer, Collin G.; Yang, Limin; Wulder, Michael A.; Franklin, Steven E.

2003-01-01

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and Sturdevant 1993; Fuller et al. 1994b; Skole et al. 1997), and a circa 1990 Landsat image data set covering the entire land area of the globe has also been developed recently (Jones and Smith 2001). An acquisition strategy aimed at acquiring at least one cloud free image per year for the entire land area of the globe has been initiated for Landsat-7 (Arvidson et al. 2001). This will probably ensure the continued dominance of Landsat in the near future.

Inclusive fitness analysis of cumulative cultural evolution in an island-structured population.

PubMed

Ohtsuki, Hisashi; Wakano, Joe Yuichiro; Kobayashi, Yutaka

2017-06-01

The success of humans on the globe is largely supported by our cultural excellence. Our culture is cumulative, meaning that it is improved from generation to generation. Previous works have revealed that two modes of learning, individual learning and social learning, play pivotal roles in the accumulation of culture. However, under the trade-off between learning and reproduction, one's investment into learning is easily exploited by those who copy the knowledge of skillful individuals and selfishly invest more efforts in reproduction. It has been shown that in order to prevent such a breakdown, the rate of vertical transmission (i.e. transmission from parents to their offspring) of culture must be unrealistically close to one. Here we investigate what if the population is spatially structured. In particular, we hypothesize that spatial structure should favor highly cumulative culture through endogenously arising high kinship. We employ Wright's island model and assume that cultural transmission occurs within a local island. Our inclusive fitness analysis reveals combined effects of direct fitness of the actor, indirect fitness through relatives in the current generation, and indirect fitness through relatives in future generations. The magnitude of those indirect benefits is measured by intergenerational coefficients of genetic relatedness. Our result suggests that the introduction of spatial structure raises the stationary level of culture in the population, but that the extent of its improvement compared with a well-mixed population is marginal unless spatial localization is extreme. Overall, our model implies that we need an alternative mechanism to explain highly cumulative culture of modern humans. Copyright © 2017 Elsevier Inc. All rights reserved.

Laser Scanning System for Pressure and Temperature Paints

NASA Technical Reports Server (NTRS)

Sullivan, John

1997-01-01

Acquiring pressure maps of aerodynamic surfaces is very important for improving and validating the performance of aerospace vehicles. Traditional pressure measurements are taken with pressure taps embedded in the model surface that are connected to transducers. While pressure taps allow highly accurate measurements to be acquired, they do have several drawbacks. Pressure taps do not give good spatial resolution due to the need for individual pressure tubes, compounded by limited space available inside models. Also, building a model proves very costly if taps are needed because of the large amount of labor necessary to drill, connect and test each one. The typical cost to install one tap is about $200. Recently, a new method for measuring pressure on aerodynamic surfaces has been developed utilizing a technology known as pressure sensitive paints (PSP). Using PSP, pressure distributions can be acquired optically with high spatial resolution and simple model preparation. Flow structures can be easily visualized using PSP, but are missed using low spatial resolution arrays of pressure taps. PSP even allows pressure distributions to be found on rotating machinery where previously this has been extremely difficult or even impossible. The goal of this research is to develop a laser scanning system for use with pressure sensitive paints that allows accurate pressure measurements to be obtained on various aerodynamic surfaces ranging from wind tunnel models to high speed jet engine compressor blades.

Predicting Fish Growth Potential and Identifying Water Quality Constraints: A Spatially-Explicit Bioenergetics Approach

NASA Astrophysics Data System (ADS)

Budy, Phaedra; Baker, Matthew; Dahle, Samuel K.

2011-10-01

Anthropogenic impairment of water bodies represents a global environmental concern, yet few attempts have successfully linked fish performance to thermal habitat suitability and fewer have distinguished co-varying water quality constraints. We interfaced fish bioenergetics, field measurements, and Thermal Remote Imaging to generate a spatially-explicit, high-resolution surface of fish growth potential, and next employed a structured hypothesis to detect relationships among measures of fish performance and co-varying water quality constraints. Our thermal surface of fish performance captured the amount and spatial-temporal arrangement of thermally-suitable habitat for three focal species in an extremely heterogeneous reservoir, but interpretation of this pattern was initially confounded by seasonal covariation of water residence time and water quality. Subsequent path analysis revealed that in terms of seasonal patterns in growth potential, catfish and walleye responded to temperature, positively and negatively, respectively; crappie and walleye responded to eutrophy (negatively). At the high eutrophy levels observed in this system, some desired fishes appear to suffer from excessive cultural eutrophication within the context of elevated temperatures whereas others appear to be largely unaffected or even enhanced. Our overall findings do not lead to the conclusion that this system is degraded by pollution; however, they do highlight the need to use a sensitive focal species in the process of determining allowable nutrient loading and as integrators of habitat suitability across multiple spatial and temporal scales. We provide an integrated approach useful for quantifying fish growth potential and identifying water quality constraints on fish performance at spatial scales appropriate for whole-system management.

Spatiotemporal distribution characteristics and attribution of extreme regional low temperature event

NASA Astrophysics Data System (ADS)

Feng, Tai-Chen; Zhang, Ke-Quan; Su, Hai-Jing; Wang, Xiao-Juan; Gong, Zhi-Qiang; Zhang, Wen-Yu

2015-10-01

Based on an objective identification technique for regional low temperature event (OITRLTE), the daily minimum temperature in China has been detected from 1960 to 2013. During this period, there were 60 regional extreme low temperature events (ERLTEs), which are included in the 690 regional low temperature events (RLTEs). The 60 ERLTEs are analyzed in this paper. The results show that in the last 50 years, the intensity of the ERLTEs has become weak; the number of lasted days has decreased; and, the affected area has become small. However, that situation has changed in this century. In terms of spatial distribution, the high intensity regions are mainly in Northern China while the high frequency regions concentrate in Central and Eastern China. According to the affected area of each event, the 60 ERLTEs are classified into six types. The atmospheric circulation background fields which correspond to these types are also analyzed. The results show that, influenced by stronger blocking highs of Ural and Lake Baikal, as well as stronger southward polar vortex and East Asia major trough at 500-hPa geopotential height, cold air from high latitudes is guided to move southward and abnormal northerly winds at 850 hPa makes the cold air blow into China along diverse paths, thereby forming different types of regional extreme low temperatures in winter. Project supported by the National Natural Science Foundation of China (Grant No. 41305075), the National Basic Research Program of China (Grant Nos. 2012CB955203 and 2012CB955902), and the Special Scientific Research on Public Welfare Industry, China (Grant No. GYHY201306049).

Co-Phasing the Large Binocular Telescope:. [Status and Performance of LBTI-PHASECam

NASA Technical Reports Server (NTRS)

Defrere, D.; Hinz, P.; Downey, E.; Ashby, D.; Bailey, V.; Brusa, G.; Christou, J.; Danchi, W. C.; Grenz, P.; Hill, J. M.;

WE-AB-207A-01: BEST IN PHYSICS (IMAGING): High-Resolution Cone-Beam CT of the Extremities and Cancellous Bone Architecture with a CMOS Detector

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

Cao, Q; Brehler, M; Sisniega, A

Purpose: Extremity cone-beam CT (CBCT) with an amorphous silicon (aSi) flat-panel detector (FPD) provides low-dose volumetric imaging with high spatial resolution. We investigate the performance of the newer complementary metal-oxide semiconductor (CMOS) detectors to enhance resolution of extremities CBCT to ∼0.1 mm, enabling morphological analysis of trabecular bone. Quantitative in-vivo imaging of bone microarchitecture could present an important advance for osteoporosis and osteoarthritis diagnosis and therapy assessment. Methods: Cascaded systems models of CMOS- and FPD-based extremities CBCT were implemented. Performance was compared for a range of pixel sizes (0.05–0.4 mm), focal spot sizes (0.3–0.6 FS), and x-ray techniques (0.05–0.8 mAs/projection)more » using detectability of high-, low-, and all-frequency tasks for a nonprewhitening observer. Test-bench implementation of CMOS-based extremity CBCT involved a Teledyne DALSA Xineos3030HR detector with 0.099 mm pixels and a compact rotating anode x-ray source with 0.3 FS (IMD RTM37). Metrics of bone morphology obtained using CMOS-based CBCT were compared in cadaveric specimens to FPD-based system using a Varian PaxScan4030 (0.194 mm pixels). Results: Finer pixel size and reduced electronic noise for CMOS (136 e compared to 2000 e for FPD) resulted in ∼1.9× increase in detectability for high-frequency tasks and ∼1.1× increase for all-frequency tasks. Incorporation of the new x-ray source with reduced focal spot size (0.3 FS vs. 0.5 FS used on current extremities CBCT) improved detectability for CMOS-based CBCT by ∼1.7× for high-frequency tasks. Compared to FPD CBCT, the CMOS detector yielded improved agreement with micro-CT in measurements of trabecular thickness (∼1.7× reduction in relative error), bone volume (∼1.5× reduction), and trabecular spacing (∼3.5× reduction). Conclusion: Imaging performance modelling and experimentation indicate substantial improvements for high-frequency imaging tasks through adoption of the CMOS detector and small FS x-ray source, motivating the use of these components in a new system for quantitative in-vivo imaging of trabecular bone. Financial Support: US NIH grant R01EB018896. Qian Cao is a Howard Hughes Medical Institute International Student Research Fellow. Disclosures: W Zbijewski, J Siewerdsen and A Sisniega receive research funding from Carestream Health.« less

Simulation of Extreme Arctic Cyclones in IPCC AR5 Experiments

NASA Astrophysics Data System (ADS)

Vavrus, S. J.

2012-12-01

Although impending Arctic climate change is widely recognized, a wild card in its expression is how extreme weather events in this region will respond to greenhouse warming. Intense polar cyclones represent one type of high-latitude phenomena falling into this category, including very deep synoptic-scale cyclones and mesoscale polar lows. These systems inflict damage through high winds, heavy precipitation, and wave action along coastlines, and their impact is expected to expand in the future, when reduced sea ice cover allows enhanced wave energy. The loss of a buffering ice pack could greatly increase the rate of coastal erosion, which has already been increasing in the Arctic. These and related threats may amplify if extreme Arctic cyclones become more frequent and/or intense in a warming climate with much more open water to fuel them. This possibility has merit on the basis of GCM experiments, which project that greenhouse forcing causes lower mean sea level pressure (SLP) in the Arctic and a strengthening of the deepest storms over boreal high latitudes. In this study, the latest Coupled Model Intercomparison Project (CMIP5) climate model output is used to investigate the following questions: (1) What are the spatial and seasonal characteristics of extreme Arctic cyclones? (2) How well do GCMs simulate these phenomena? (3) Are Arctic cyclones already showing the expected response to greenhouse warming in climate models? To address these questions, a retrospective analysis is conducted of the transient 20th century simulations among the CMIP5 GCMs (spanning years 1850-2005). The results demonstrate that GCMs are able to reasonably represent extreme Arctic cyclones and that the simulated characteristics do not depend significantly on model resolution. Consistent with observational evidence, climate models generate these storms primarily during winter and within the climatological Aleutian and Icelandic Low regions. Occasionally the cyclones remain very intense over the Arctic Ocean. The historical tendency in Arctic SLP varies considerably among the GCMs, but the intermodel average trend exhibits a lowering of mean-annual pressure over the Arctic during the past 150 years and an increase in extreme cyclones in the vicinity of the Aleutian and Icelandic Lows. However, only weak trends in extreme cyclones are simulated through 2005 over the Arctic Ocean, where simulations of future climate change produce the largest SLP falls.

Processing and Synthesis of Pre-Biotic Chemicals in Hypervelocity Impacts

NASA Technical Reports Server (NTRS)

Brickerhoff, W. B.; Managadze, G. G.; Chumikov, A. E.; Managadze, N. G.

2005-01-01

Hypervelocity impacts (HVIs) may have played a significant role in establishing the initial organic inventory for pre-biotic chemistry on the Earth and other planetary bodies. In addition to the delivery of organic compounds intact to planetary surfaces, generally at velocities below approx.20 km/s, HVIs also enable synthesis of new molecules. The cooling post-impact plasma plumes of HVIs in the interstellar medium (ISM), the protosolar nebula (PSN), and the early solar system comprise pervasive conditions for organic synthesis. Such plasma synthesis (PS) can operate over many length scales (from nm-scale dust to planets) and energy scales (from molecular rearrangement to atomization and recondensation). HVI experiments with the flexibility to probe the highest velocities and distinguish synthetic routes are a high priority to understand the relevance of PS to exobiology. We describe here recent studies of PS at small spatial scales and extremely high velocities with pulsed laser ablation (PLA). PLA can simulate the extreme plasma conditions generated in impacts of dust particles at speeds of up to 100 km/s or more. When applied to carbonaceous solids, new and pre-biotically relevant molecular species are formed with high efficiency [1,2].

Using GPS TEC measurements to probe ionospheric spatial spectra at mid-latitudes

NASA Astrophysics Data System (ADS)

Lay, E. H.; Parker, P. A.; Light, M. E.; Carrano, C. S.; Debchoudhury, S.; Haaser, R. A.

2017-12-01

The physics of how random ionospheric structure causes signal degradation is well understood as weak forward scattering through an effective diffraction grating created by plasma irregularities in the ionosphere. However, the spatial scale spectrum of those irregularities required for input into scintillation models and models of traveling ionospheric disturbances is poorly characterized, particularly at the kilometer to tens of kilometer scale lengths important for very-high-frequency (VHF) scintillation prediction. Furthermore, the majority of characterization studies have been performed in low-latitude or high-latitude regions where geomagnetic activity dominates the physical processes. At mid-latitudes, tropospheric and geomagnetic phenomena compete in disturbing the ionosphere, and it is not well understood how these multiple sources affect the drivers that influence the spatial spectrum. In this study, we are interested in mid-latitude electron density irregularities on the order of 10s of kilometers that would affect VHF signals. Data from the GPS networks Japan GEONET and the Plate Boundary Observatory (PBO, UNAVCO) in the western United States were analyzed for this study. Japan GEONET is a dense network of GPS receivers (station spacing of tens of km), with fairly evenly spaced positions over all of Japan. The PBO, on the other hand, has several pockets of extremely dense coverage (station spacing within a few km), but is less dense on average. We analyze a day with a large solar storm (2015/03/17, St. Patrick's Day Storm) to allow high scintillation potential at mid-latitudes, a day with low geomagnetic activity and low thunderstorm activity (2016/01/31), and a day with low geomagnetic activity and high thunderstorm activity (2015/08/02). We then perform two-dimensional spatial analyses on the TEC data from these two networks on scale lengths of 20 to 200 km to infer the spatial scale spectra.

Extremely cold events and sudden air temperature drops during winter season in the Czech Republic

NASA Astrophysics Data System (ADS)

Crhová, Lenka; Valeriánová, Anna; Holtanová, Eva; Müller, Miloslav; Kašpar, Marek; Stříž, Martin

2014-05-01

Today a great attention is turned to analysis of extreme weather events and frequency of their occurrence under changing climate. In most cases, these studies are focused on extremely warm events in summer season. However, extremely low values of air temperature during winter can have serious impacts on many sectors as well (e.g. power engineering, transportation, industry, agriculture, human health). Therefore, in present contribution we focus on extremely and abnormally cold air temperature events in winter season in the Czech Republic. Besides the seasonal extremes of minimum air temperature determined from station data, the standardized data with removed annual cycle are used as well. Distribution of extremely cold events over the season and the temporal evolution of frequency of occurrence during the period 1961-2010 are analyzed. Furthermore, the connection of cold events with extreme sudden temperature drops is studied. The extreme air temperature events and events of extreme sudden temperature drop are assessed using the Weather Extremity Index, which evaluates the extremity (based on return periods) and spatial extent of the meteorological extreme event of interest. The generalized extreme value distribution parameters are used to estimate return periods of daily temperature values. The work has been supported by the grant P209/11/1990 funded by the Czech Science Foundation.

Retrieval of total suspended particulate matter in highly turbid Hangzhou Bay waters based on geostationary ocean color imager

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Jiahang; He, Xianqiang; Chen, Tieqiao; Zhu, Feng; Wang, Yihao; Hao, Zengzhou; Chen, Peng

2017-10-01

Hangzhou Bay waters are often characterized by extremely high total suspended particulate matter (TSM) concentration due to terrestrial inputs, bottom sediment resuspension and human activities. The spatial-temporal variability of TSM directly contributes to the transport of carbon, nutrients, pollutants, and other materials. Therefore, it is essential to maintain and monitor sedimentary environment in coastal waters. Traditional field sampling methods limit observation capability for insufficient spatial-temporal resolution. Thus, it is difficult to synoptically monitor high diurnal dynamics of TSM. However, the in-orbit operation of the world's first geostationary satellite ocean color sensor, GOCI, thoroughly changes this situation with hourly observations of covered area. Taking advantage of GOCI high spatial-temporal resolution, we generated TSM maps from GOCI Level-1B data after atmospheric correction based on six TSM empirical algorithms. Validation of GOCI-retrieved normalized water-leaving radiances and TSM concentration was presented in comparison with matched-up in-situ measurements. The mean absolute percentage differences of those six TSM regional algorithms were 24.52%, 163.93%, 195.50%, 70.50%, 121.02%, 82.72%, respectively. In addition, the discrepancy reasons were presented, taking more factors such as diversified satellite data, various study area, and different research season into consideration. It is effective and indispensable to monitor and catch the diurnal dynamics of TSM in Hangzhou Bay coastal waters, with hourly GOCI observations data and appropriate inversion algorithm.

Solving phase appearance/disappearance two-phase flow problems with high resolution staggered grid and fully implicit schemes by the Jacobian-free Newton–Krylov Method

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

Zou, Ling; Zhao, Haihua; Zhang, Hongbin

2016-04-01

The phase appearance/disappearance issue presents serious numerical challenges in two-phase flow simulations. Many existing reactor safety analysis codes use different kinds of treatments for the phase appearance/disappearance problem. However, to our best knowledge, there are no fully satisfactory solutions. Additionally, the majority of the existing reactor system analysis codes were developed using low-order numerical schemes in both space and time. In many situations, it is desirable to use high-resolution spatial discretization and fully implicit time integration schemes to reduce numerical errors. In this work, we adapted a high-resolution spatial discretization scheme on staggered grid mesh and fully implicit time integrationmore » methods (such as BDF1 and BDF2) to solve the two-phase flow problems. The discretized nonlinear system was solved by the Jacobian-free Newton Krylov (JFNK) method, which does not require the derivation and implementation of analytical Jacobian matrix. These methods were tested with a few two-phase flow problems with phase appearance/disappearance phenomena considered, such as a linear advection problem, an oscillating manometer problem, and a sedimentation problem. The JFNK method demonstrated extremely robust and stable behaviors in solving the two-phase flow problems with phase appearance/disappearance. No special treatments such as water level tracking or void fraction limiting were used. High-resolution spatial discretization and second- order fully implicit method also demonstrated their capabilities in significantly reducing numerical errors.« less

Extreme fluctuations in stochastic network coordination with time delays

NASA Astrophysics Data System (ADS)

Hunt, D.; Molnár, F.; Szymanski, B. K.; Korniss, G.

2015-12-01

We study the effects of uniform time delays on the extreme fluctuations in stochastic synchronization and coordination problems with linear couplings in complex networks. We obtain the average size of the fluctuations at the nodes from the behavior of the underlying modes of the network. We then obtain the scaling behavior of the extreme fluctuations with system size, as well as the distribution of the extremes on complex networks, and compare them to those on regular one-dimensional lattices. For large complex networks, when the delay is not too close to the critical one, fluctuations at the nodes effectively decouple, and the limit distributions converge to the Fisher-Tippett-Gumbel density. In contrast, fluctuations in low-dimensional spatial graphs are strongly correlated, and the limit distribution of the extremes is the Airy density. Finally, we also explore the effects of nonlinear couplings on the stability and on the extremes of the synchronization landscapes.

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

NASA Astrophysics Data System (ADS)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude, latitude, distance from sea and distance to the highest orographic barrier) on the rainfall behaviours described by the studied variables. The techniques of spatial interpolation evaluated include univariate and multivariate methods: cokriging, kriging, IDW (inverse distance weighted) and multiple linear regression. Validation procedures were used, assessing the estimated errors in the analysis of descriptive statistics of the models. Multiple linear regression models produced satisfactory results in relation to 70% of the rainfall parameters, suggested by lower average percentage of error. However, the results also demonstrates that there is no an unique and ideal model, depending on the rainfall parameter in consideration. Probably, the unsatisfactory results obtained in relation to some rainfall parameters was motivated by constraints as the spatial complexity of the precipitation patterns, as well as to the deficient spatial coverage of the territory by the rain-gauges network. References Diodato, N. (2005). The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. Internacional Journal of Climatology, 25(3), 351-363. Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113 - 129.

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.

2014-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Mortality related to extreme temperature for 15 cities in northeast Asia.

PubMed

Chung, Yeonseung; Lim, Youn-Hee; Honda, Yasushi; Guo, Yue-Liang Leon; Hashizume, Masahiro; Bell, Michelle L; Chen, Bing-Yu; Kim, Ho

2015-03-01

Multisite time-series studies for temperature-related mortality have been conducted mainly in the United States and Europe, but are lacking in Asia. This multisite time-series study examined mortality related to extreme temperatures (both cold and hot) in Northeast Asia, focusing on 15 cities of 3 high-income countries. This study includes 3 cities in Taiwan for 1994-2007, 6 cities in Korea for 1992-2010, and 6 cities in Japan for 1972-2009. We used 2-stage Bayesian hierarchical Poisson semiparametric regression to model the nonlinear relationship between temperature and mortality, providing city-specific and country-wide estimates for cold and heat effects. Various exposure time frames, age groups, and causes of death were considered. Cold effects had longer time lags (5-11 days) than heat effects, which were immediate (1-3 days). Cold effects were larger for cities in Taiwan, whereas heat effects were larger for cities in Korea and Japan. Patterns of increasing effects with age were observed in both cold and heat effects. Both cold and heat effects were larger for cardiorespiratory mortality than for other causes of death. Several city characteristics related to weather or air pollution were associated with both cold and heat effects. Mortality increased with either cold or hot temperature in urban populations of high-income countries in Northeast Asia, with spatial variations of effects among cities and countries. Findings suggest that climate factors are major contributors to the spatial heterogeneity of effects in this region, although further research is merited to identify other factors as determinants of variability.

Atmospheric conditions associated with extreme fire activity in the Western Mediterranean region.

PubMed

Amraoui, Malik; Pereira, Mário G; DaCamara, Carlos C; Calado, Teresa J

2015-08-15

Active fire information provided by TERRA and AQUA instruments on-board sun-synchronous polar MODIS platform is used to describe fire activity in the Western Mediterranean and to identify and characterize the synoptic patterns of several meteorological fields associated with the occurrence of extreme fire activity episodes (EEs). The spatial distribution of the fire pixels during the period of 2003-2012 leads to the identification of two most affected sub-regions, namely the Northern and Western parts of the Iberian Peninsula (NWIP) and Northern Africa (NAFR). The temporal distribution of the fire pixels in these two sub-regions is characterized by: (i) high and non-concurrent inter- and intra-annual variability with maximum values during the summer of 2003 and 2005 in NWIP and 2007 and 2012 in NAFR; and, (ii) high intra-annual variability dominated by a prominent annual cycle with a main peak centred in August in both sub-regions and a less pronounced secondary peak in March only evident in NWIP region. The 34 EEs identified were grouped according to the location, period of occurrence and spatial configuration of the associated synoptic patterns into 3 clusters (NWIP-summer, NWIP-winter and NAFR-summer). Results from the composite analysis reveal similar fire weather conditions (statistically significant positive anomalies of air temperature and negative anomalies of air relative humidity) but associated with different circulation patterns at lower and mid-levels of the atmosphere associated with the occurrence of EEs in each cluster of the Western Mediterranean region. Copyright © 2015 Elsevier B.V. All rights reserved.

Remote sensor digital image data analysis using the General Electric Image 100 analysis system (a study of analysis speed, cost, and performance)

NASA Technical Reports Server (NTRS)

Mcmurtry, G. J.; Petersen, G. W. (Principal Investigator)

1975-01-01

The author has identified the following significant results. It was found that the high speed man machine interaction capability is a distinct advantage of the image 100; however, the small size of the digital computer in the system is a definite limitation. The system can be highly useful in an analysis mode in which it complements a large general purpose computer. The image 100 was found to be extremely valuable in the analysis of aircraft MSS data where the spatial resolution begins to approach photographic quality and the analyst can exercise interpretation judgements and readily interact with the machine.

A rocket spectroscopic payload in support of the Apollo Telescope Mount experiments

NASA Technical Reports Server (NTRS)

Rugge, H. R.

1974-01-01

The scientific instrumentation and other payload systems of a solar rocket experiment are described in detail. The objectives of the rocket payload were: (1) to carry out high-spectral-resolution measurements of a coronal active region in the X-ray and extreme ultraviolet regions at the same time as high-spatial-resolution measurements were being made of the same active region by the Apollo Telescope Mount experiments flown on Skylab; and (2) to derive a physical model of the conditions in the coronal active regions, which dominate the X-ray spectrum of the nonflaring active sun, on the basis of data obtained from both the rocket instrumentation and several of the Apollo Telescope Mount experiments.

5.5-7.5 MeV Proton Generation by a Moderate-Intensity Ultrashort-Pulse Laser Interaction with H2O Nanowire Targets

NASA Astrophysics Data System (ADS)

Zigler, A.; Palchan, T.; Bruner, N.; Schleifer, E.; Eisenmann, S.; Botton, M.; Henis, Z.; Pikuz, S. A.; Faenov, A. Y., Jr.; Gordon, D.; Sprangle, P.

2011-04-01

We report on the first generation of 5.5-7.5 MeV protons by a moderate-intensity short-pulse laser (˜5×1017W/cm2, 40 fsec) interacting with frozen H2O nanometer-size structure droplets (snow nanowires) deposited on a sapphire substrate. In this setup, the laser intensity is locally enhanced by the snow nanowire, leading to high spatial gradients. Accordingly, the nanoplasma is subject to enhanced ponderomotive potential, and confined charge separation is obtained. Electrostatic fields of extremely high intensities are produced over the short scale length, and protons are accelerated to MeV-level energies.

Preliminary investigations into macroscopic attenuated total reflection-fourier transform infrared imaging of intact spherical domains: spatial resolution and image distortion.

PubMed

Everall, Neil J; Priestnall, Ian M; Clarke, Fiona; Jayes, Linda; Poulter, Graham; Coombs, David; George, Michael W

2009-03-01

This paper describes preliminary investigations into the spatial resolution of macro attenuated total reflection (ATR) Fourier transform infrared (FT-IR) imaging and the distortions that arise when imaging intact, convex domains, using spheres as an extreme example. The competing effects of shallow evanescent wave penetration and blurring due to finite spatial resolution meant that spheres within the range 20-140 microm all appeared to be approximately the same size ( approximately 30-35 microm) when imaged with a numerical aperture (NA) of approximately 0.2. A very simple model was developed that predicted this extreme insensitivity to particle size. On the basis of these studies, it is anticipated that ATR imaging at this NA will be insensitive to the size of intact highly convex objects. A higher numerical aperture device should give a better estimate of the size of small spheres, owing to superior spatial resolution, but large spheres should still appear undersized due to the shallow sampling depth. An estimate of the point spread function (PSF) was required in order to develop and apply the model. The PSF was measured by imaging a sharp interface; assuming an Airy profile, the PSF width (distance from central maximum to first minimum) was estimated to be approximately 20 and 30 microm for IR bands at 1600 and 1000 cm(-1), respectively. This work has two significant limitations. First, underestimation of domain size only arises when imaging intact convex objects; if surfaces are prepared that randomly and representatively section through domains, the images can be analyzed to calculate parameters such as domain size, area, and volume. Second, the model ignores reflection and refraction and assumes weak absorption; hence, the predicted intensity profiles are not expected to be accurate; they merely give a rough estimate of the apparent sphere size. Much further work is required to place the field of quantitative ATR-FT-IR imaging on a sound basis.

Pluviometric characterization of the Coca river basin by using a stochastic rainfall model

NASA Astrophysics Data System (ADS)

González-Zeas, Dunia; Chávez-Jiménez, Adriadna; Coello-Rubio, Xavier; Correa, Ángel; Martínez-Codina, Ángela

2014-05-01

An adequate design of the hydraulic infrastructures, as well as, the prediction and simulation of a river basin require historical records with a greater temporal and spatial resolution. However, the lack of an extensive network of precipitation data, the short time scale data and the incomplete information provided by the available rainfall stations limit the analysis and design of complex hydraulic engineering systems. As a consequence, it is necessary to develop new quantitative tools in order to face this obstacle imposed by ungauged or poorly gauged basins. In this context, the use of a spatial-temporal rainfall model allows to simulate the historical behavior of the precipitation and at the same time, to obtain long-term synthetic series that preserve the extremal behavior. This paper provides a characterization of the precipitation in the Coca river basin located in Ecuador by using RainSim V3, a robust and well tested stochastic rainfall model based on a spatial-temporal Neyman-Scott rectangular pulses process. A preliminary consistency analysis of the historical rainfall data available has been done in order to identify climatic regions with similar precipitation behavior patterns. Mean and maximum yearly and monthly fields of precipitation of high resolution spaced grids have been obtained through the use of interpolation techniques. According to the climatological similarity, long time series of daily temporal resolution of precipitation have been generated in order to evaluate the model skill in capturing the structure of daily observed precipitation. The results show a good performance of the model in reproducing very well the gross statistics, including the extreme values of rainfall at daily scale. The spatial pattern represented by the observed and simulated precipitation fields highlights the existence of two important regions characterized by different pluviometric comportment, with lower precipitation in the upper part of the basin and higher precipitation in the lower part of the basin.

Long-term monitoring on environmental disasters using multi-source remote sensing technique

NASA Astrophysics Data System (ADS)

Kuo, Y. C.; Chen, C. F.

2017-12-01

Environmental disasters are extreme events within the earth's system that cause deaths and injuries to humans, as well as causing damages and losses of valuable assets, such as buildings, communication systems, farmlands, forest and etc. In disaster management, a large amount of multi-temporal spatial data is required. Multi-source remote sensing data with different spatial, spectral and temporal resolutions is widely applied on environmental disaster monitoring. With multi-source and multi-temporal high resolution images, we conduct rapid, systematic and seriate observations regarding to economic damages and environmental disasters on earth. It is based on three monitoring platforms: remote sensing, UAS (Unmanned Aircraft Systems) and ground investigation. The advantages of using UAS technology include great mobility and availability in real-time rapid and more flexible weather conditions. The system can produce long-term spatial distribution information from environmental disasters, obtaining high-resolution remote sensing data and field verification data in key monitoring areas. It also supports the prevention and control on ocean pollutions, illegally disposed wastes and pine pests in different scales. Meanwhile, digital photogrammetry can be applied on the camera inside and outside the position parameters to produce Digital Surface Model (DSM) data. The latest terrain environment information is simulated by using DSM data, and can be used as references in disaster recovery in the future.

Compact 200 kHz HHG source driven by a few-cycle OPCPA

NASA Astrophysics Data System (ADS)

Harth, Anne; Guo, Chen; Cheng, Yu-Chen; Losquin, Arthur; Miranda, Miguel; Mikaelsson, Sara; Heyl, Christoph M.; Prochnow, Oliver; Ahrens, Jan; Morgner, Uwe; L'Huillier, Anne; Arnold, Cord L.

2018-01-01

We present efficient high-order harmonic generation (HHG) based on a high-repetition rate, few-cycle, near infrared (NIR), carrier-envelope phase stable, optical parametric chirped pulse amplifier (OPCPA), emitting 6 fs pulses with 9 μJ pulse energy. In krypton, we reach conversion efficiencies from the NIR to the extreme ultraviolet (XUV) radiation pulse energy on the order of ˜10-6 with less than 3 μJ driving pulse energy. This is achieved by optimizing the OPCPA for a spatially and temporally clean pulse and by a specially designed high-pressure gas target. In the future, the high efficiency of the HHG source will be beneficial for high-repetition rate two-colour (NIR-XUV) pump-probe experiments, where the available pulse energy from the laser has to be distributed economically between pump and probe pulses.

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.

The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather.

PubMed

Krstic, Nikolas; Yuchi, Weiran; Ho, Hung Chak; Walker, Blake B; Knudby, Anders J; Henderson, Sarah B

2017-12-01

Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evolution of Precipitation Extremes in Three Large Ensembles of Climate Simulations - Impact of Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Martel, J. L.; Brissette, F.; Mailhot, A.; Wood, R. R.; Ludwig, R.; Frigon, A.; Leduc, M.; Turcotte, R.

2017-12-01

Recent studies indicate that the frequency and intensity of extreme precipitation will increase in future climate due to global warming. In this study, we compare annual maxima precipitation series from three large ensembles of climate simulations at various spatial and temporal resolutions. The first two are at the global scale: the Canadian Earth System Model (CanESM2) 50-member large ensemble (CanESM2-LE) at a 2.8° resolution and the Community Earth System Model (CESM1) 40-member large ensemble (CESM1-LE) at a 1° resolution. The third ensemble is at the regional scale over both Eastern North America and Europe: the Canadian Regional Climate Model (CRCM5) 50-member large ensemble (CRCM5-LE) at a 0.11° resolution, driven at its boundaries by the CanESM-LE. The CRCM5-LE is a new ensemble issued from the ClimEx project (http://www.climex-project.org), a Québec-Bavaria collaboration. Using these three large ensembles, change in extreme precipitations over the historical (1980-2010) and future (2070-2100) periods are investigated. This results in 1 500 (30 years x 50 members for CanESM2-LE and CRCM5-LE) and 1200 (30 years x 40 members for CESM1-LE) simulated years over both the historical and future periods. Using these large datasets, the empirical daily (and sub-daily for CRCM5-LE) extreme precipitation quantiles for large return periods ranging from 2 to 100 years are computed. Results indicate that daily extreme precipitations generally will increase over most land grid points of both domains according to the three large ensembles. Regarding the CRCM5-LE, the increase in sub-daily extreme precipitations will be even more important than the one observed for daily extreme precipitations. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety.

Peripheral Quantitative CT (pQCT) Using a Dedicated Extremity Cone-Beam CT Scanner

PubMed Central

Muhit, A. A.; Arora, S.; Ogawa, M.; Ding, Y.; Zbijewski, W.; Stayman, J. W.; Thawait, G.; Packard, N.; Senn, R.; Yang, D.; Yorkston, J.; Bingham, C.O.; Means, K.; Carrino, J. A.; Siewerdsen, J. H.

2014-01-01

Purpose We describe the initial assessment of the peripheral quantitative CT (pQCT) imaging capabilities of a cone-beam CT (CBCT) scanner dedicated to musculoskeletal extremity imaging. The aim is to accurately measure and quantify bone and joint morphology using information automatically acquired with each CBCT scan, thereby reducing the need for a separate pQCT exam. Methods A prototype CBCT scanner providing isotropic, sub-millimeter spatial resolution and soft-tissue contrast resolution comparable or superior to standard multi-detector CT (MDCT) has been developed for extremity imaging, including the capability for weight-bearing exams and multi-mode (radiography, fluoroscopy, and volumetric) imaging. Assessment of pQCT performance included measurement of bone mineral density (BMD), morphometric parameters of subchondral bone architecture, and joint space analysis. Measurements employed phantoms, cadavers, and patients from an ongoing pilot study imaged with the CBCT prototype (at various acquisition, calibration, and reconstruction techniques) in comparison to MDCT (using pQCT protocols for analysis of BMD) and micro-CT (for analysis of subchondral morphometry). Results The CBCT extremity scanner yielded BMD measurement within ±2–3% error in both phantom studies and cadaver extremity specimens. Subchondral bone architecture (bone volume fraction, trabecular thickness, degree of anisotropy, and structure model index) exhibited good correlation with gold standard micro-CT (error ~5%), surpassing the conventional limitations of spatial resolution in clinical MDCT scanners. Joint space analysis demonstrated the potential for sensitive 3D joint space mapping beyond that of qualitative radiographic scores in application to non-weight-bearing versus weight-bearing lower extremities and assessment of phalangeal joint space integrity in the upper extremities. Conclusion The CBCT extremity scanner demonstrated promising initial results in accurate pQCT analysis from images acquired with each CBCT scan. Future studies will include improved x-ray scatter correction and image reconstruction techniques to further improve accuracy and to correlate pQCT metrics with known pathology. PMID:25076823

Can animal habitat use patterns influence their vulnerability to extreme climate events? An estuarine sportfish case study.

PubMed

Boucek, Ross E; Heithaus, Michael R; Santos, Rolando; Stevens, Philip; Rehage, Jennifer S

2017-10-01

Global climate forecasts predict changes in the frequency and intensity of extreme climate events (ECEs). The capacity for specific habitat patches within a landscape to modulate stressors from extreme climate events, and animal distribution throughout habitat matrices during events, could influence the degree of population level effects following the passage of ECEs. Here, we ask (i) does the intensity of stressors of an ECE vary across a landscape? And (ii) Do habitat use patterns of a mobile species influence their vulnerability to ECEs? Specifically, we measured how extreme cold spells might interact with temporal variability in habitat use to affect populations of a tropical, estuarine-dependent large-bodied fish Common Snook, within Everglades National Park estuaries (FL US). We examined temperature variation across the estuary during cold disturbances with different degrees of severity, including an extreme cold spell. Second, we quantified Snook distribution patterns when the passage of ECEs is most likely to occur from 2012 to 2016 using passive acoustic tracking. Our results revealed spatial heterogeneity in the intensity of temperature declines during cold disturbances, with some habitats being consistently 3-5°C colder than others. Surprisingly, Snook distributions during periods of greatest risk to experience an extreme cold event varied among years. During the winters of 2013-2014 and 2014-2015 a greater proportion of Snook occurred in the colder habitats, while the winters of 2012-2013 and 2015-2016 featured more Snook observed in the warmest habitats. This study shows that Snook habitat use patterns could influence vulnerability to extreme cold events, however, whether Snook habitat use increases or decreases their vulnerability to disturbance depends on the year, creating temporally dynamic vulnerability. Faunal global change research should address the spatially explicit nature of extreme climate events and animal habitat use patterns to identify potential mechanisms that may influence population effects following these disturbances. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Extreme Rainfall Analysis using Bayesian Hierarchical Modeling in the Willamette River Basin, Oregon

NASA Astrophysics Data System (ADS)

Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

2016-12-01

We present preliminary results of ongoing research directed at evaluating the worth of including various covariate data to support extreme rainfall analysis in the Willamette River basin using Bayesian hierarchical modeling (BHM). We also compare the BHM derived extreme rainfall estimates with their respective counterparts obtained from a traditional regional frequency analysis (RFA) using the same set of rain gage extreme rainfall data. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams in the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two-thirds of Oregon's population and 20 of the 25 most populous cities in the state. Extreme rainfall estimates are required to support risk-informed hydrologic analyses for these projects as part of the USACE Dam Safety Program. We analyze daily annual rainfall maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme rainfall by return level. Our intent is to profile for the USACE an alternate methodology to a RFA which was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. Unlike RFA, the advantage of a BHM-based analysis of hydrometeorological extremes is its ability to account for non-stationarity while providing robust estimates of uncertainty. BHM also allows for the inclusion of geographical and climatological factors which we show for the WRB influence regional rainfall extremes. Moreover, the Bayesian framework permits one to combine additional data types into the analysis; for example, information derived via elicitation and causal information expansion data, both being additional opportunities for future related research.

Dry, drier, driest: An Australian story of extreme years and potential ecosystem collapse

NASA Astrophysics Data System (ADS)

Wardle, G. M.; Dickman, C. R.; Greenville, A. C.

2016-12-01

Ecosystems are expected to undergo large changes due to an increase in the frequency and intensity of extreme events. We can expect droughts to be longer, flooding to be more intense, and heatwaves and fires to increase. Importantly, at the regional scale these projections which are based on global climate models come with additional uncertainties that challenge how we can plan and evaluate options for adaptation. For many ecosystems, the understanding of the interdependencies and function is still limited, and particularly so for areas such as inland Australia that already exhibit unpredictable rainfall and lack strong seasonality. These drylands are water-limited and operate differently in dry, or wet years, when episodic pulses of resources drive increases in productivity. Increased extremes have the potential to disrupt the function of these highly dynamic and complex systems through feedbacks, synergies and through memory or delayed responses to change. Using our long-term work in the Simpson Desert as a case study, we explore the trends in productivity, the responses of flora and fauna to these opportunities and the spatial connectedness and heterogeneities that support the persistence of the ecosystem through dry times. Theory tells us that ecosystems may shift states abruptly when they cross critical thresholds. For example, arid grasslands may no longer have the capacity to return to a productive state following good rains. This happens under desertification, where plant cover and growth is limited — with flow on consequences for the entire ecosystem. Forecasting such changes is crucial but the fundamental knowledge relies on information that spans both long time scales and large spatial scales. We examine the knowledge gaps in quantifying ecosystem collapse using our IUCN ecosystem risk assessment of the Georgina gidgee woodlands. We conclude by arguing that without long-term data on trends and integration across the biophysical and and biological components at large spatial scales we cannot hope to anticipate ecosystem collapse and take appropriate action. The Terrestrial Ecosystem Research Network is leading the way for Australia to contribute to this important global ecosystem capability.

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, Dani; Tecon, Robin; Ebrahimi, Ali; Kleyer, Hannah; Ilie, Olga; Wang, Gang

2015-04-01

Microbial life in soil occurs within fragmented aquatic habitats formed in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, D.; Tecon, R.; Ebrahimi, A.; Kleyer, H.; Ilie, O.; Wang, G.

2014-12-01

Microbial life in soil occurs within fragmented aquatic habitats in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world.

Attribution of the 1995 and 2006 storm surge events in the southern Baltic Sea

NASA Astrophysics Data System (ADS)

Klehmet, K.; Rockel, B.; von Storch, H.

2016-12-01

In November 1995 and 2006, the German Baltic Sea coast experienced severe storm surge conditions. Exceptional water level heights of about 1.8m above mean sea level were measured at German tide gauges. Extreme event attribution poses unique challenges trying to distinguish the role of anthropogenic influence, as e.g. greenhouse gas emissions or land-use changes, from natural variability. This study, which is part of the EUCLEIA project (EUropean CLimate and weather Events: Interpretation and Attribution, www. eucleia.eu), aims to estimate how the contribution of anthropogenic drivers has altered the probability of single extreme events such as the 1995 and 2006 storm surge events. We explore these aspects using two 7-member ensembles of Hadley Centre Global Environmental Model version 3-A (HadGEM3-A), the atmosphere only component of the HadGEM3, provided by the Met Office Hadley Centre. The ensemble of HadGEM3-A consists of two multi-decadal experiments from 1960-2013 - one with anthropogenic forcing factors and natural forcings representing the actual climate. The second experiment represents the natural climate including only natural forcing factors. These two 7-member ensembles of about 60km spatial resolution are used as atmospheric forcing data to drive the regional ocean model TRIM-NP in order to calculate water level in the Baltic Sea in 12.8km spatial resolution. Findings indicate some limitations of the regional model ensemble to reproduce the magnitude of extreme water levels well. It is tested whether increased spatial resolution of atmospheric forcing fields can improve the representation of Baltic Sea extreme water levels along the coast and thus add value in the attribution analysis.

Modeled changes in extreme wave climate for US and US-affiliated Pacific Islands during the 21st century

NASA Astrophysics Data System (ADS)

Shope, J. B.; Storlazzi, C. D.; Erikson, L. H.; Hegermiller, C.

2013-12-01

Changes in future wave climates in the tropical Pacific Ocean from global climate change are not well understood. Waves are the dominant spatially- and temporally-varying processes that influence the coastal morphology and ecosystem structure of the islands throughout the tropical Pacific. Waves also impact the coastal infrastructure, natural and cultural resources, and coastal-related economic activities of these islands. Wave heights, periods, and directions were forecast through 2100 using wind parameter outputs from four coupled atmosphere-ocean global climate models from the Coupled Model Inter-Comparison Project, Phase 5., for Representative Concentration Pathways scenarios 4.5 and 8.5 that correspond to moderately mitigated and unmitigated greenhouse gas emissions, respectively. Wind fields from the global climate models were used to drive the global WAVEWATCH III wave model and generate hourly time-series of bulk wave parameters for 25 islands in the mid to western tropical Pacific. Although the results show some spatial heterogeneity, overall, the December-February extreme significant wave heights increase from present to mid century and then decrease toward the end of the century; June-August extreme wave heights decrease throughout the century. Peak wave periods decrease west of the International Date Line through all seasons, whereas peak periods increase in the eastern half of the study area; these trends are smaller during December-February and greatest during June-August. Extreme wave directions in equatorial Micronesia during June-August undergo an approximate 30 degree counter-clockwise rotation from primarily northwest to west. The spatial patterns and trends are similar between the two different greenhouse gas emission scenarios, with the magnitude of the trends greater for the higher scenario.

An Adaptive Multiscale Finite Element Method for Large Scale Simulations

DTIC Science & Technology

2015-09-28

Illinois at Urbana-Champaign Abstract Hypersonic vehicles are subjected to extreme acoustic, thermal and mechanical loading with strong spatial and temporal...07/15/2012 Reporting Period End Date 07/14/2015 Abstract Hypersonic vehicles are subjected to extreme acoustic, thermal and mechanical loading with...gradients and for extended periods of time. Long duration, 3-D simulations of non-linear response of these vehicles , is prohibitively expensive using

Stochastic Downscaling of Digital Elevation Models

NASA Astrophysics Data System (ADS)

Rasera, Luiz Gustavo; Mariethoz, Gregoire; Lane, Stuart N.

2016-04-01

High-resolution digital elevation models (HR-DEMs) are extremely important for the understanding of small-scale geomorphic processes in Alpine environments. In the last decade, remote sensing techniques have experienced a major technological evolution, enabling fast and precise acquisition of HR-DEMs. However, sensors designed to measure elevation data still feature different spatial resolution and coverage capabilities. Terrestrial altimetry allows the acquisition of HR-DEMs with centimeter to millimeter-level precision, but only within small spatial extents and often with dead ground problems. Conversely, satellite radiometric sensors are able to gather elevation measurements over large areas but with limited spatial resolution. In the present study, we propose an algorithm to downscale low-resolution satellite-based DEMs using topographic patterns extracted from HR-DEMs derived for example from ground-based and airborne altimetry. The method consists of a multiple-point geostatistical simulation technique able to generate high-resolution elevation data from low-resolution digital elevation models (LR-DEMs). Initially, two collocated DEMs with different spatial resolutions serve as an input to construct a database of topographic patterns, which is also used to infer the statistical relationships between the two scales. High-resolution elevation patterns are then retrieved from the database to downscale a LR-DEM through a stochastic simulation process. The output of the simulations are multiple equally probable DEMs with higher spatial resolution that also depict the large-scale geomorphic structures present in the original LR-DEM. As these multiple models reflect the uncertainty related to the downscaling, they can be employed to quantify the uncertainty of phenomena that are dependent on fine topography, such as catchment hydrological processes. The proposed methodology is illustrated for a case study in the Swiss Alps. A swissALTI3D HR-DEM (with 5 m resolution) and a SRTM-derived LR-DEM from the Western Alps are used to downscale a SRTM-based LR-DEM from the eastern part of the Alps. The results show that the method is capable of generating multiple high-resolution synthetic DEMs that reproduce the spatial structure and statistics of the original DEM.

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).

TEMPLATES: Targeting Extremely Magnified Panchromatic Lensed Arcs and Their Extended Star Formation

NASA Astrophysics Data System (ADS)

Rigby, Jane; Vieira, Joaquin; Bayliss, M.; Fischer, T.; Florian, M.; Gladders, M.; Gonzalez, A.; Law, D.; Marrone, D.; Phadke, K.; Sharon, K.; Spilker, J.

2017-11-01

We propose high signal-to-noise NIRSpec and MIRI IFU spectroscopy, with accompanying imaging, for 4 gravitationally lensed galaxies at 1

Stand-alone scattering optical device using holographic photopolymer (Conference Presentation)

NASA Astrophysics Data System (ADS)

Park, Jongchan; Lee, KyeoReh; Park, YongKeun

2016-03-01

When a light propagates through highly disordered medium, its optical parameters such as amplitude, phase and polarization states are completely scrambled because of multiple scattering events. Since the multiple scattering is a fundamental optical process that contains extremely high degrees of freedom, optical information of a transmitted light is totally mingled. Until recently, the presence of multiple scattering in an inhomogeneous medium is considered as a major obstacle when manipulating a light transmitting through the medium. However, a recent development of wavefront shaping techniques enable us to control the propagation of light through turbid media; a light transmitting through a turbid medium can be effectively controlled by modulating the spatial profile of the incident light using spatial light modulator. In this work, stand-alone scattering optical device is proposed; a holographic photopolymer film, which is much economic compared to the other digital spatial light modulators, is used to record and reconstruct permanent wavefront to generate optical field behind a scattering medium. By employing our method, arbitrary optical field can be generated since the scattering medium completely mixes all the optical parameters which allow us to access all the optical information only by modulating spatial phase profile of the impinging wavefront. The method is experimentally demonstrated in both the far-field and near-field regime where it shows promising fidelity and stability. The proposed stand-alone scattering optical device will opens up new avenues for exploiting the randomness inherent in disordered medium.

Spatial rule-based assessment of habitat potential to predict impact of land use changes on biodiversity at municipal scale.

PubMed

Scolozzi, Rocco; Geneletti, Davide

2011-03-01

In human dominated landscapes, ecosystems are under increasing pressures caused by urbanization and infrastructure development. In Alpine valleys remnant natural areas are increasingly affected by habitat fragmentation and loss. In these contexts, there is a growing risk of local extinction for wildlife populations; hence assessing the consequences on biodiversity of proposed land use changes is extremely important. The article presents a methodology to assess the impacts of land use changes on target species at a local scale. The approach relies on the application of ecological profiles of target species for habitat potential (HP) assessment, using high resolution GIS-data within a multiple level framework. The HP, in this framework, is based on a species-specific assessment of the suitability of a site, as well of surrounding areas. This assessment is performed through spatial rules, structured as sets of queries on landscape objects. We show that by considering spatial dependencies in habitat assessment it is possible to perform better quantification of impacts of local-level land use changes on habitats.

A Spatially Resolved Investigation on the Influence of AGN and Star Formation in a Lensed Main-Sequence Galaxy at z = 2.39

NASA Astrophysics Data System (ADS)

Fischer, Travis; Rigby, Jane; Gladders, Michael; Sharon, Keren q.; Barrientos, L. Felipe; Bayliss, Matt; Dahle, Håkon; Florian, Michael; Johnson, Traci Lin; Wuyts, Eva

2018-01-01

We present rest-frame optical SINFONI integral field spectroscopy and rest-frame UV HST imaging of a lensed galaxy hosting an active galactic nucleus (AGN) at z = 2.39. Galactic wind feedback is widely acknowledged to play a critical role in the evolution of galaxies, however, the physical mechanisms involved and the relative importance of AGN and star formation as the main feedback drivers remain poorly understood. AGN-driven feedback has been evident in very luminous but rare quasars and radio galaxies, but observational evidence remains lacking for less extreme, “normal” star-forming galaxies. We report, for the first time at high redshift, spatially resolved velocity profiles and geometries of an AGN-driven outflow in a normal star-forming galaxy and spatial extents and morphologies of Lyα emission and stellar UV continuum. Analyzing these measurements in tandem, we determine the physical conditions, geometry, and excitation sources of the interstellar medium in a star-forming, AGN-hosting galaxy at cosmic noon.

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

Clark's nutcracker spatial memory: the importance of large, structural cues.

PubMed

Bednekoff, Peter A; Balda, Russell P

2014-02-01

Clark's nutcrackers, Nucifraga columbiana, cache and recover stored seeds in high alpine areas including areas where snowfall, wind, and rockslides may frequently obscure or alter cues near the cache site. Previous work in the laboratory has established that Clark's nutcrackers use spatial memory to relocate cached food. Following from aspects of this work, we performed experiments to test the importance of large, structural cues for Clark's nutcracker spatial memory. Birds were no more accurate in recovering caches when more objects were on the floor of a large experimental room nor when this room was subdivided with a set of panels. However, nutcrackers were consistently less accurate in this large room than in a small experimental room. Clark's nutcrackers probably use structural features of experimental rooms as important landmarks during recovery of cached food. This use of large, extremely stable cues may reflect the imperfect reliability of smaller, closer cues in the natural habitat of Clark's nutcrackers. This article is part of a Special Issue entitled: CO3 2013. Copyright © 2013 Elsevier B.V. All rights reserved.

Evidence of fuels management and fire weather influencing fire severity in an extreme fire event

USGS Publications Warehouse

Lydersen, Jamie M; Collins, Brandon M.; Brooks, Matthew L.; Matchett, John R.; Shive, Kristen L.; Povak, Nicholas A.; Kane, Van R.; Smith, Douglas F.

2017-01-01

Following changes in vegetation structure and pattern, along with a changing climate, large wildfire incidence has increased in forests throughout the western U.S. Given this increase there is great interest in whether fuels treatments and previous wildfire can alter fire severity patterns in large wildfires. We assessed the relative influence of previous fuels treatments (including wildfire), fire weather, vegetation and water balance on fire severity in the Rim Fire of 2013. We did this at three different spatial scales to investigate whether the influences on fire severity changed across scales. Both fuels treatments and previous low to moderate severity wildfire reduced the prevalence of high severity fire. In general, areas without recent fuels treatments and areas that previously burned at high severity tended to have a greater proportion of high severity fire in the Rim Fire. Areas treated with prescribed fire, especially when combined with thinning, had the lowest proportions of high severity. Proportion of the landscape burned at high severity was most strongly influenced by fire weather and proportional area previously treated for fuels or burned by low to moderate severity wildfire. The proportion treated needed to effectively reduce the amount of high fire severity fire varied by spatial scale of analysis, with smaller spatial scales requiring a greater proportion treated to see an effect on fire severity. When moderate and high severity fire encountered a previously treated area, fire severity was significantly reduced in the treated area relative to the adjacent untreated area. Our results show that fuels treatments and low to moderate severity wildfire can reduce fire severity in a subsequent wildfire, even when burning under fire growth conditions. These results serve as further evidence that both fuels treatments and lower severity wildfire can increase forest resilience.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

Focal overlap gating in velocity map imaging to achieve high signal-to-noise ratio in photo-ion pump-probe experiments

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

Shivaram, Niranjan; Champenois, Elio G.; Cryan, James P.

We demonstrate a technique in velocity map imaging (VMI) that allows spatial gating of the laser focal overlap region in time resolved pump-probe experiments. This significantly enhances signal-to-noise ratio by eliminating background signal arising outside the region of spatial overlap of pump and probe beams. This enhancement is achieved by tilting the laser beams with respect to the surface of the VMI electrodes which creates a gradient in flight time for particles born at different points along the beam. By suitably pulsing our microchannel plate detector, we can select particles born only where the laser beams overlap. Furthermore, this spatialmore » gating in velocity map imaging can benefit nearly all photo-ion pump-probe VMI experiments especially when extreme-ultraviolet light or X-rays are involved which produce large background signals on their own.« less

MPATHav: A software prototype for multiobjective routing in transportation risk assessment

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

Ganter, J.H.; Smith, J.D.

Most routing problems depend on several important variables: transport distance, population exposure, accident rate, mandated roads (e.g., HM-164 regulations), and proximity to emergency response resources are typical. These variables may need to be minimized or maximized, and often are weighted. `Objectives` to be satisfied by the analysis are thus created. The resulting problems can be approached by combining spatial analysis techniques from geographic information systems (GIS) with multiobjective analysis techniques from the field of operations research (OR); we call this hybrid multiobjective spatial analysis` (MOSA). MOSA can be used to discover, display, and compare a range of solutions that satisfymore » a set of objectives to varying degrees. For instance, a suite of solutions may include: one solution that provides short transport distances, but at a cost of high exposure; another solution that provides low exposure, but long distances; and a range of solutions between these two extremes.« less

Evaluation of High-Resolution Precipitation Estimates from Satellites during July 2012 Beijing Flood Event Using Dense Rain Gauge Observations

PubMed Central

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing. PMID:24691358

Evaluation of high-resolution precipitation estimates from satellites during July 2012 Beijing flood event using dense rain gauge observations.

PubMed

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.